research objectives and methodology

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What Are Research Objectives and How to Write Them (with Examples)

Table of Contents

Introduction

Research is at the center of everything researchers do, and setting clear, well-defined research objectives plays a pivotal role in guiding scholars toward their desired outcomes. Research papers are essential instruments for researchers to effectively communicate their work. Among the many sections that constitute a research paper, the introduction plays a key role in providing a background and setting the context. 1 Research objectives, which define the aims of the study, are usually stated in the introduction. Every study has a research question that the authors are trying to answer, and the objective is an active statement about how the study will answer this research question. These objectives help guide the development and design of the study and steer the research in the appropriate direction; if this is not clearly defined, a project can fail!

Research studies have a research question, research hypothesis, and one or more research objectives. A research question is what a study aims to answer, and a research hypothesis is a predictive statement about the relationship between two or more variables, which the study sets out to prove or disprove. Objectives are specific, measurable goals that the study aims to achieve. The difference between these three is illustrated by the following example:

• Research question : How does low-intensity pulsed ultrasound (LIPUS) compare with a placebo device in managing the symptoms of skeletally mature patients with patellar tendinopathy?
• Research hypothesis : Pain levels are reduced in patients who receive daily active-LIPUS (treatment) for 12 weeks compared with individuals who receive inactive-LIPUS (placebo).
• Research objective : To investigate the clinical efficacy of LIPUS in the management of patellar tendinopathy symptoms.

This article discusses the importance of clear, well-thought out objectives and suggests methods to write them clearly.

What is the introduction in research papers?

Research objectives are usually included in the introduction section. This section is the first that the readers will read so it is essential that it conveys the subject matter appropriately and is well written to create a good first impression. A good introduction sets the tone of the paper and clearly outlines the contents so that the readers get a quick snapshot of what to expect.

A good introduction should aim to: 2,3

• Indicate the main subject area, its importance, and cite previous literature on the subject
• Define the gap(s) in existing research, ask a research question, and state the objectives
• Announce the present research and outline its novelty and significance
• Avoid repeating the Abstract, providing unnecessary information, and claiming novelty without accurate supporting information.

Why are research objectives important?

Objectives can help you stay focused and steer your research in the required direction. They help define and limit the scope of your research, which is important to efficiently manage your resources and time. The objectives help to create and maintain the overall structure, and specify two main things—the variables and the methods of quantifying the variables.

A good research objective:

• defines the scope of the study
• gives direction to the research
• helps maintain focus and avoid diversions from the topic
• minimizes wastage of resources like time, money, and energy

Types of research objectives

Research objectives can be broadly classified into general and specific objectives . 4 General objectives state what the research expects to achieve overall while specific objectives break this down into smaller, logically connected parts, each of which addresses various parts of the research problem. General objectives are the main goals of the study and are usually fewer in number while specific objectives are more in number because they address several aspects of the research problem.

Example (general objective): To investigate the factors influencing the financial performance of firms listed in the New York Stock Exchange market.

Example (specific objective): To assess the influence of firm size on the financial performance of firms listed in the New York Stock Exchange market.

In addition to this broad classification, research objectives can be grouped into several categories depending on the research problem, as given in Table 1.

Table 1: Types of research objectives

Characteristics of research objectives

Research objectives must start with the word “To” because this helps readers identify the objective in the absence of headings and appropriate sectioning in research papers. 5,6

• A good objective is SMART (mostly applicable to specific objectives):
• Specific—clear about the what, why, when, and how
• Measurable—identifies the main variables of the study and quantifies the targets
• Achievable—attainable using the available time and resources
• Realistic—accurately addresses the scope of the problem
• Time-bound—identifies the time in which each step will be completed
• Research objectives clarify the purpose of research.
• They help understand the relationship and dissimilarities between variables.
• They provide a direction that helps the research to reach a definite conclusion.

How to write research objectives?

Research objectives can be written using the following steps: 7

• State your main research question clearly and concisely.
• Describe the ultimate goal of your study, which is similar to the research question but states the intended outcomes more definitively.
• Divide this main goal into subcategories to develop your objectives.
• Limit the number of objectives (1-2 general; 3-4 specific)
• Assess each objective using the SMART
• Start each objective with an action verb like assess, compare, determine, evaluate, etc., which makes the research appear more actionable.
• Use specific language without making the sentence data heavy.
• The most common section to add the objectives is the introduction and after the problem statement.
• Add the objectives to the abstract (if there is one).
• State the general objective first, followed by the specific objectives.

Formulating research objectives

Formulating research objectives has the following five steps, which could help researchers develop a clear objective: 8

• Identify the research problem.
• Review past studies on subjects similar to your problem statement, that is, studies that use similar methods, variables, etc.
• Identify the research gaps the current study should cover based on your literature review. These gaps could be theoretical, methodological, or conceptual.
• Define the research question(s) based on the gaps identified.
• Revise/relate the research problem based on the defined research question and the gaps identified. This is to confirm that there is an actual need for a study on the subject based on the gaps in literature.
• Identify and write the general and specific objectives.
• Incorporate the objectives into the study.

Advantages of research objectives

Adding clear research objectives has the following advantages: 4,8

• Maintains the focus and direction of the research
• Optimizes allocation of resources with minimal wastage
• Acts as a foundation for defining appropriate research questions and hypotheses
• Provides measurable outcomes that can help evaluate the success of the research
• Determines the feasibility of the research by helping to assess the availability of required resources
• Ensures relevance of the study to the subject and its contribution to existing literature

Disadvantages of research objectives

Research objectives also have few disadvantages, as listed below: 8

• Absence of clearly defined objectives can lead to ambiguity in the research process
• Unintentional bias could affect the validity and accuracy of the research findings

Key takeaways

• Research objectives are concise statements that describe what the research is aiming to achieve.
• They define the scope and direction of the research and maintain focus.
• The objectives should be SMART—specific, measurable, achievable, realistic, and time-bound.
• Clear research objectives help avoid collection of data or resources not required for the study.
• Well-formulated specific objectives help develop the overall research methodology, including data collection, analysis, interpretation, and utilization.
• Research objectives should cover all aspects of the problem statement in a coherent way.
• They should be clearly stated using action verbs.

Frequently asked questions on research objectives

Q: what’s the difference between research objectives and aims 9.

A: Research aims are statements that reflect the broad goal(s) of the study and outline the general direction of the research. They are not specific but clearly define the focus of the study.

Example: This research aims to explore employee experiences of digital transformation in retail HR.

Research objectives focus on the action to be taken to achieve the aims. They make the aims more practical and should be specific and actionable.

Example: To observe the retail HR employees throughout the digital transformation.

Q: What are the examples of research objectives, both general and specific?

A: Here are a few examples of research objectives:

• To identify the antiviral chemical constituents in Mumbukura gitoniensis (general)
• To carry out solvent extraction of dried flowers of Mumbukura gitoniensis and isolate the constituents. (specific)
• To determine the antiviral activity of each of the isolated compounds. (specific)
• To examine the extent, range, and method of coral reef rehabilitation projects in five shallow reef areas adjacent to popular tourist destinations in the Philippines.
• To investigate species richness of mammal communities in five protected areas over the past 20 years.
• To evaluate the potential application of AI techniques for estimating best-corrected visual acuity from fundus photographs with and without ancillary information.
• To investigate whether sport influences psychological parameters in the personality of asthmatic children.

Q: How do I develop research objectives?

A: Developing research objectives begins with defining the problem statement clearly, as illustrated by Figure 1. Objectives specify how the research question will be answered and they determine what is to be measured to test the hypothesis.

Q: Are research objectives measurable?

A: The word “measurable” implies that something is quantifiable. In terms of research objectives, this means that the source and method of collecting data are identified and that all these aspects are feasible for the research. Some metrics can be created to measure your progress toward achieving your objectives.

Q: Can research objectives change during the study?

A: Revising research objectives during the study is acceptable in situations when the selected methodology is not progressing toward achieving the objective, or if there are challenges pertaining to resources, etc. One thing to keep in mind is the time and resources you would have to complete your research after revising the objectives. Thus, as long as your problem statement and hypotheses are unchanged, minor revisions to the research objectives are acceptable.

Q: What is the difference between research questions and research objectives? 10

Q: Are research objectives the same as hypotheses?

A: No, hypotheses are predictive theories that are expressed in general terms. Research objectives, which are more specific, are developed from hypotheses and aim to test them. A hypothesis can be tested using several methods and each method will have different objectives because the methodology to be used could be different. A hypothesis is developed based on observation and reasoning; it is a calculated prediction about why a particular phenomenon is occurring. To test this prediction, different research objectives are formulated. Here’s a simple example of both a research hypothesis and research objective.

Research hypothesis : Employees who arrive at work earlier are more productive.

Research objective : To assess whether employees who arrive at work earlier are more productive.

To summarize, research objectives are an important part of research studies and should be written clearly to effectively communicate your research. We hope this article has given you a brief insight into the importance of using clearly defined research objectives and how to formulate them.

• Farrugia P, Petrisor BA, Farrokhyar F, Bhandari M. Practical tips for surgical research: Research questions, hypotheses and objectives. Can J Surg. 2010 Aug;53(4):278-81.
• Abbadia J. How to write an introduction for a research paper. Mind the Graph website. Accessed June 14, 2023. https://mindthegraph.com/blog/how-to-write-an-introduction-for-a-research-paper/
• Writing a scientific paper: Introduction. UCI libraries website. Accessed June 15, 2023. https://guides.lib.uci.edu/c.php?g=334338&p=2249903
• Research objectives—Types, examples and writing guide. Researchmethod.net website. Accessed June 17, 2023. https://researchmethod.net/research-objectives/#:~:text=They%20provide%20a%20clear%20direction,track%20and%20achieve%20their%20goals .
• Bartle P. SMART Characteristics of good objectives. Community empowerment collective website. Accessed June 16, 2023. https://cec.vcn.bc.ca/cmp/modules/pd-smar.htm
• Research objectives. Studyprobe website. Accessed June 18, 2023. https://www.studyprobe.in/2022/08/research-objectives.html
• Corredor F. How to write objectives in a research paper. wikiHow website. Accessed June 18, 2023. https://www.wikihow.com/Write-Objectives-in-a-Research-Proposal
• Research objectives: Definition, types, characteristics, advantages. AccountingNest website. Accessed June 15, 2023. https://www.accountingnest.com/articles/research/research-objectives
• Phair D., Shaeffer A. Research aims, objectives & questions. GradCoach website. Accessed June 20, 2023. https://gradcoach.com/research-aims-objectives-questions/
• Understanding the difference between research questions and objectives. Accessed June 21, 2023. https://board.researchersjob.com/blog/research-questions-and-objectives

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What is Research Methodology? Definition, Types, and Examples

Research methodology 1,2 is a structured and scientific approach used to collect, analyze, and interpret quantitative or qualitative data to answer research questions or test hypotheses. A research methodology is like a plan for carrying out research and helps keep researchers on track by limiting the scope of the research. Several aspects must be considered before selecting an appropriate research methodology, such as research limitations and ethical concerns that may affect your research.

The research methodology section in a scientific paper describes the different methodological choices made, such as the data collection and analysis methods, and why these choices were selected. The reasons should explain why the methods chosen are the most appropriate to answer the research question. A good research methodology also helps ensure the reliability and validity of the research findings. There are three types of research methodology—quantitative, qualitative, and mixed-method, which can be chosen based on the research objectives.

What is research methodology ?

A research methodology describes the techniques and procedures used to identify and analyze information regarding a specific research topic. It is a process by which researchers design their study so that they can achieve their objectives using the selected research instruments. It includes all the important aspects of research, including research design, data collection methods, data analysis methods, and the overall framework within which the research is conducted. While these points can help you understand what is research methodology, you also need to know why it is important to pick the right methodology.

Why is research methodology important?

Having a good research methodology in place has the following advantages: 3

• Helps other researchers who may want to replicate your research; the explanations will be of benefit to them.
• You can easily answer any questions about your research if they arise at a later stage.
• A research methodology provides a framework and guidelines for researchers to clearly define research questions, hypotheses, and objectives.
• It helps researchers identify the most appropriate research design, sampling technique, and data collection and analysis methods.
• A sound research methodology helps researchers ensure that their findings are valid and reliable and free from biases and errors.
• It also helps ensure that ethical guidelines are followed while conducting research.
• A good research methodology helps researchers in planning their research efficiently, by ensuring optimum usage of their time and resources.

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Types of research methodology.

There are three types of research methodology based on the type of research and the data required. 1

• Quantitative research methodology focuses on measuring and testing numerical data. This approach is good for reaching a large number of people in a short amount of time. This type of research helps in testing the causal relationships between variables, making predictions, and generalizing results to wider populations.
• Qualitative research methodology examines the opinions, behaviors, and experiences of people. It collects and analyzes words and textual data. This research methodology requires fewer participants but is still more time consuming because the time spent per participant is quite large. This method is used in exploratory research where the research problem being investigated is not clearly defined.
• Mixed-method research methodology uses the characteristics of both quantitative and qualitative research methodologies in the same study. This method allows researchers to validate their findings, verify if the results observed using both methods are complementary, and explain any unexpected results obtained from one method by using the other method.

What are the types of sampling designs in research methodology?

Sampling 4 is an important part of a research methodology and involves selecting a representative sample of the population to conduct the study, making statistical inferences about them, and estimating the characteristics of the whole population based on these inferences. There are two types of sampling designs in research methodology—probability and nonprobability.

• Probability sampling

In this type of sampling design, a sample is chosen from a larger population using some form of random selection, that is, every member of the population has an equal chance of being selected. The different types of probability sampling are:

• Systematic —sample members are chosen at regular intervals. It requires selecting a starting point for the sample and sample size determination that can be repeated at regular intervals. This type of sampling method has a predefined range; hence, it is the least time consuming.
• Stratified —researchers divide the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized, and then a sample can be drawn from each group separately.
• Cluster —the population is divided into clusters based on demographic parameters like age, sex, location, etc.
• Convenience —selects participants who are most easily accessible to researchers due to geographical proximity, availability at a particular time, etc.
• Purposive —participants are selected at the researcher’s discretion. Researchers consider the purpose of the study and the understanding of the target audience.
• Snowball —already selected participants use their social networks to refer the researcher to other potential participants.
• Quota —while designing the study, the researchers decide how many people with which characteristics to include as participants. The characteristics help in choosing people most likely to provide insights into the subject.

What are data collection methods?

During research, data are collected using various methods depending on the research methodology being followed and the research methods being undertaken. Both qualitative and quantitative research have different data collection methods, as listed below.

Qualitative research 5

• One-on-one interviews: Helps the interviewers understand a respondent’s subjective opinion and experience pertaining to a specific topic or event
• Document study/literature review/record keeping: Researchers’ review of already existing written materials such as archives, annual reports, research articles, guidelines, policy documents, etc.
• Focus groups: Constructive discussions that usually include a small sample of about 6-10 people and a moderator, to understand the participants’ opinion on a given topic.
• Qualitative observation : Researchers collect data using their five senses (sight, smell, touch, taste, and hearing).

Quantitative research 6

• Sampling: The most common type is probability sampling.
• Interviews: Commonly telephonic or done in-person.
• Observations: Structured observations are most commonly used in quantitative research. In this method, researchers make observations about specific behaviors of individuals in a structured setting.
• Document review: Reviewing existing research or documents to collect evidence for supporting the research.
• Surveys and questionnaires. Surveys can be administered both online and offline depending on the requirement and sample size.

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What are data analysis methods.

The data collected using the various methods for qualitative and quantitative research need to be analyzed to generate meaningful conclusions. These data analysis methods 7 also differ between quantitative and qualitative research.

Quantitative research involves a deductive method for data analysis where hypotheses are developed at the beginning of the research and precise measurement is required. The methods include statistical analysis applications to analyze numerical data and are grouped into two categories—descriptive and inferential.

Descriptive analysis is used to describe the basic features of different types of data to present it in a way that ensures the patterns become meaningful. The different types of descriptive analysis methods are:

• Measures of frequency (count, percent, frequency)
• Measures of central tendency (mean, median, mode)
• Measures of dispersion or variation (range, variance, standard deviation)
• Measure of position (percentile ranks, quartile ranks)

Inferential analysis is used to make predictions about a larger population based on the analysis of the data collected from a smaller population. This analysis is used to study the relationships between different variables. Some commonly used inferential data analysis methods are:

• Correlation: To understand the relationship between two or more variables.
• Cross-tabulation: Analyze the relationship between multiple variables.
• Regression analysis: Study the impact of independent variables on the dependent variable.
• Frequency tables: To understand the frequency of data.
• Analysis of variance: To test the degree to which two or more variables differ in an experiment.

Qualitative research involves an inductive method for data analysis where hypotheses are developed after data collection. The methods include:

• Content analysis: For analyzing documented information from text and images by determining the presence of certain words or concepts in texts.
• Narrative analysis: For analyzing content obtained from sources such as interviews, field observations, and surveys. The stories and opinions shared by people are used to answer research questions.
• Discourse analysis: For analyzing interactions with people considering the social context, that is, the lifestyle and environment, under which the interaction occurs.
• Grounded theory: Involves hypothesis creation by data collection and analysis to explain why a phenomenon occurred.
• Thematic analysis: To identify important themes or patterns in data and use these to address an issue.

How to choose a research methodology?

Here are some important factors to consider when choosing a research methodology: 8

• Research objectives, aims, and questions —these would help structure the research design.
• Review existing literature to identify any gaps in knowledge.
• Check the statistical requirements —if data-driven or statistical results are needed then quantitative research is the best. If the research questions can be answered based on people’s opinions and perceptions, then qualitative research is most suitable.
• Sample size —sample size can often determine the feasibility of a research methodology. For a large sample, less effort- and time-intensive methods are appropriate.
• Constraints —constraints of time, geography, and resources can help define the appropriate methodology.

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How to write a research methodology .

A research methodology should include the following components: 3,9

• Research design —should be selected based on the research question and the data required. Common research designs include experimental, quasi-experimental, correlational, descriptive, and exploratory.
• Research method —this can be quantitative, qualitative, or mixed-method.
• Reason for selecting a specific methodology —explain why this methodology is the most suitable to answer your research problem.
• Research instruments —explain the research instruments you plan to use, mainly referring to the data collection methods such as interviews, surveys, etc. Here as well, a reason should be mentioned for selecting the particular instrument.
• Sampling —this involves selecting a representative subset of the population being studied.
• Data collection —involves gathering data using several data collection methods, such as surveys, interviews, etc.
• Data analysis —describe the data analysis methods you will use once you’ve collected the data.
• Research limitations —mention any limitations you foresee while conducting your research.
• Validity and reliability —validity helps identify the accuracy and truthfulness of the findings; reliability refers to the consistency and stability of the results over time and across different conditions.
• Ethical considerations —research should be conducted ethically. The considerations include obtaining consent from participants, maintaining confidentiality, and addressing conflicts of interest.

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Frequently Asked Questions

Q1. What are the key components of research methodology?

A1. A good research methodology has the following key components:

• Research design
• Data collection procedures
• Data analysis methods
• Ethical considerations

Q2. Why is ethical consideration important in research methodology?

A2. Ethical consideration is important in research methodology to ensure the readers of the reliability and validity of the study. Researchers must clearly mention the ethical norms and standards followed during the conduct of the research and also mention if the research has been cleared by any institutional board. The following 10 points are the important principles related to ethical considerations: 10

• Participants should not be subjected to harm.
• Respect for the dignity of participants should be prioritized.
• Full consent should be obtained from participants before the study.
• Participants’ privacy should be ensured.
• Confidentiality of the research data should be ensured.
• Anonymity of individuals and organizations participating in the research should be maintained.
• The aims and objectives of the research should not be exaggerated.
• Affiliations, sources of funding, and any possible conflicts of interest should be declared.
• Communication in relation to the research should be honest and transparent.
• Misleading information and biased representation of primary data findings should be avoided.

Q3. What is the difference between methodology and method?

A3. Research methodology is different from a research method, although both terms are often confused. Research methods are the tools used to gather data, while the research methodology provides a framework for how research is planned, conducted, and analyzed. The latter guides researchers in making decisions about the most appropriate methods for their research. Research methods refer to the specific techniques, procedures, and tools used by researchers to collect, analyze, and interpret data, for instance surveys, questionnaires, interviews, etc.

Research methodology is, thus, an integral part of a research study. It helps ensure that you stay on track to meet your research objectives and answer your research questions using the most appropriate data collection and analysis tools based on your research design.

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• Research methodologies. Pfeiffer Library website. Accessed August 15, 2023. https://library.tiffin.edu/researchmethodologies/whatareresearchmethodologies
• Types of research methodology. Eduvoice website. Accessed August 16, 2023. https://eduvoice.in/types-research-methodology/
• The basics of research methodology: A key to quality research. Voxco. Accessed August 16, 2023. https://www.voxco.com/blog/what-is-research-methodology/
• Sampling methods: Types with examples. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/types-of-sampling-for-social-research/
• What is qualitative research? Methods, types, approaches, examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-qualitative-research-methods-types-examples/
• What is quantitative research? Definition, methods, types, and examples. Researcher.Life blog. Accessed August 15, 2023. https://researcher.life/blog/article/what-is-quantitative-research-types-and-examples/
• Data analysis in research: Types & methods. QuestionPro website. Accessed August 16, 2023. https://www.questionpro.com/blog/data-analysis-in-research/#Data_analysis_in_qualitative_research
• Factors to consider while choosing the right research methodology. PhD Monster website. Accessed August 17, 2023. https://www.phdmonster.com/factors-to-consider-while-choosing-the-right-research-methodology/
• What is research methodology? Research and writing guides. Accessed August 14, 2023. https://paperpile.com/g/what-is-research-methodology/
• Ethical considerations. Business research methodology website. Accessed August 17, 2023. https://research-methodology.net/research-methodology/ethical-considerations/

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Home » Research Methodology – Types, Examples and writing Guide

Research Methodology – Types, Examples and writing Guide

Table of Contents

Research Methodology

Definition:

Research Methodology refers to the systematic and scientific approach used to conduct research, investigate problems, and gather data and information for a specific purpose. It involves the techniques and procedures used to identify, collect , analyze , and interpret data to answer research questions or solve research problems . Moreover, They are philosophical and theoretical frameworks that guide the research process.

Structure of Research Methodology

Research methodology formats can vary depending on the specific requirements of the research project, but the following is a basic example of a structure for a research methodology section:

I. Introduction

• Provide an overview of the research problem and the need for a research methodology section
• Outline the main research questions and objectives

II. Research Design

• Explain the research design chosen and why it is appropriate for the research question(s) and objectives
• Discuss any alternative research designs considered and why they were not chosen
• Describe the research setting and participants (if applicable)

III. Data Collection Methods

• Describe the methods used to collect data (e.g., surveys, interviews, observations)
• Explain how the data collection methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or instruments used for data collection

IV. Data Analysis Methods

• Describe the methods used to analyze the data (e.g., statistical analysis, content analysis )
• Explain how the data analysis methods were chosen and why they are appropriate for the research question(s) and objectives
• Detail any procedures or software used for data analysis

V. Ethical Considerations

• Discuss any ethical issues that may arise from the research and how they were addressed
• Explain how informed consent was obtained (if applicable)
• Detail any measures taken to ensure confidentiality and anonymity

VI. Limitations

• Identify any potential limitations of the research methodology and how they may impact the results and conclusions

VII. Conclusion

• Summarize the key aspects of the research methodology section
• Explain how the research methodology addresses the research question(s) and objectives

Research Methodology Types

Types of Research Methodology are as follows:

Quantitative Research Methodology

This is a research methodology that involves the collection and analysis of numerical data using statistical methods. This type of research is often used to study cause-and-effect relationships and to make predictions.

Qualitative Research Methodology

This is a research methodology that involves the collection and analysis of non-numerical data such as words, images, and observations. This type of research is often used to explore complex phenomena, to gain an in-depth understanding of a particular topic, and to generate hypotheses.

Mixed-Methods Research Methodology

This is a research methodology that combines elements of both quantitative and qualitative research. This approach can be particularly useful for studies that aim to explore complex phenomena and to provide a more comprehensive understanding of a particular topic.

Case Study Research Methodology

This is a research methodology that involves in-depth examination of a single case or a small number of cases. Case studies are often used in psychology, sociology, and anthropology to gain a detailed understanding of a particular individual or group.

Action Research Methodology

This is a research methodology that involves a collaborative process between researchers and practitioners to identify and solve real-world problems. Action research is often used in education, healthcare, and social work.

Experimental Research Methodology

This is a research methodology that involves the manipulation of one or more independent variables to observe their effects on a dependent variable. Experimental research is often used to study cause-and-effect relationships and to make predictions.

Survey Research Methodology

This is a research methodology that involves the collection of data from a sample of individuals using questionnaires or interviews. Survey research is often used to study attitudes, opinions, and behaviors.

Grounded Theory Research Methodology

This is a research methodology that involves the development of theories based on the data collected during the research process. Grounded theory is often used in sociology and anthropology to generate theories about social phenomena.

Research Methodology Example

An Example of Research Methodology could be the following:

Research Methodology for Investigating the Effectiveness of Cognitive Behavioral Therapy in Reducing Symptoms of Depression in Adults

Introduction:

The aim of this research is to investigate the effectiveness of cognitive-behavioral therapy (CBT) in reducing symptoms of depression in adults. To achieve this objective, a randomized controlled trial (RCT) will be conducted using a mixed-methods approach.

Research Design:

The study will follow a pre-test and post-test design with two groups: an experimental group receiving CBT and a control group receiving no intervention. The study will also include a qualitative component, in which semi-structured interviews will be conducted with a subset of participants to explore their experiences of receiving CBT.

Participants:

Participants will be recruited from community mental health clinics in the local area. The sample will consist of 100 adults aged 18-65 years old who meet the diagnostic criteria for major depressive disorder. Participants will be randomly assigned to either the experimental group or the control group.

Intervention :

The experimental group will receive 12 weekly sessions of CBT, each lasting 60 minutes. The intervention will be delivered by licensed mental health professionals who have been trained in CBT. The control group will receive no intervention during the study period.

Data Collection:

Quantitative data will be collected through the use of standardized measures such as the Beck Depression Inventory-II (BDI-II) and the Generalized Anxiety Disorder-7 (GAD-7). Data will be collected at baseline, immediately after the intervention, and at a 3-month follow-up. Qualitative data will be collected through semi-structured interviews with a subset of participants from the experimental group. The interviews will be conducted at the end of the intervention period, and will explore participants’ experiences of receiving CBT.

Data Analysis:

Quantitative data will be analyzed using descriptive statistics, t-tests, and mixed-model analyses of variance (ANOVA) to assess the effectiveness of the intervention. Qualitative data will be analyzed using thematic analysis to identify common themes and patterns in participants’ experiences of receiving CBT.

Ethical Considerations:

This study will comply with ethical guidelines for research involving human subjects. Participants will provide informed consent before participating in the study, and their privacy and confidentiality will be protected throughout the study. Any adverse events or reactions will be reported and managed appropriately.

Data Management:

All data collected will be kept confidential and stored securely using password-protected databases. Identifying information will be removed from qualitative data transcripts to ensure participants’ anonymity.

Limitations:

One potential limitation of this study is that it only focuses on one type of psychotherapy, CBT, and may not generalize to other types of therapy or interventions. Another limitation is that the study will only include participants from community mental health clinics, which may not be representative of the general population.

Conclusion:

This research aims to investigate the effectiveness of CBT in reducing symptoms of depression in adults. By using a randomized controlled trial and a mixed-methods approach, the study will provide valuable insights into the mechanisms underlying the relationship between CBT and depression. The results of this study will have important implications for the development of effective treatments for depression in clinical settings.

How to Write Research Methodology

Writing a research methodology involves explaining the methods and techniques you used to conduct research, collect data, and analyze results. It’s an essential section of any research paper or thesis, as it helps readers understand the validity and reliability of your findings. Here are the steps to write a research methodology:

• Start by explaining your research question: Begin the methodology section by restating your research question and explaining why it’s important. This helps readers understand the purpose of your research and the rationale behind your methods.
• Describe your research design: Explain the overall approach you used to conduct research. This could be a qualitative or quantitative research design, experimental or non-experimental, case study or survey, etc. Discuss the advantages and limitations of the chosen design.
• Discuss your sample: Describe the participants or subjects you included in your study. Include details such as their demographics, sampling method, sample size, and any exclusion criteria used.
• Describe your data collection methods : Explain how you collected data from your participants. This could include surveys, interviews, observations, questionnaires, or experiments. Include details on how you obtained informed consent, how you administered the tools, and how you minimized the risk of bias.
• Explain your data analysis techniques: Describe the methods you used to analyze the data you collected. This could include statistical analysis, content analysis, thematic analysis, or discourse analysis. Explain how you dealt with missing data, outliers, and any other issues that arose during the analysis.
• Discuss the validity and reliability of your research : Explain how you ensured the validity and reliability of your study. This could include measures such as triangulation, member checking, peer review, or inter-coder reliability.
• Acknowledge any limitations of your research: Discuss any limitations of your study, including any potential threats to validity or generalizability. This helps readers understand the scope of your findings and how they might apply to other contexts.
• Provide a summary: End the methodology section by summarizing the methods and techniques you used to conduct your research. This provides a clear overview of your research methodology and helps readers understand the process you followed to arrive at your findings.

When to Write Research Methodology

Research methodology is typically written after the research proposal has been approved and before the actual research is conducted. It should be written prior to data collection and analysis, as it provides a clear roadmap for the research project.

The research methodology is an important section of any research paper or thesis, as it describes the methods and procedures that will be used to conduct the research. It should include details about the research design, data collection methods, data analysis techniques, and any ethical considerations.

The methodology should be written in a clear and concise manner, and it should be based on established research practices and standards. It is important to provide enough detail so that the reader can understand how the research was conducted and evaluate the validity of the results.

Applications of Research Methodology

Here are some of the applications of research methodology:

• To identify the research problem: Research methodology is used to identify the research problem, which is the first step in conducting any research.
• To design the research: Research methodology helps in designing the research by selecting the appropriate research method, research design, and sampling technique.
• To collect data: Research methodology provides a systematic approach to collect data from primary and secondary sources.
• To analyze data: Research methodology helps in analyzing the collected data using various statistical and non-statistical techniques.
• To test hypotheses: Research methodology provides a framework for testing hypotheses and drawing conclusions based on the analysis of data.
• To generalize findings: Research methodology helps in generalizing the findings of the research to the target population.
• To develop theories : Research methodology is used to develop new theories and modify existing theories based on the findings of the research.
• To evaluate programs and policies : Research methodology is used to evaluate the effectiveness of programs and policies by collecting data and analyzing it.
• To improve decision-making: Research methodology helps in making informed decisions by providing reliable and valid data.

Purpose of Research Methodology

Research methodology serves several important purposes, including:

• To guide the research process: Research methodology provides a systematic framework for conducting research. It helps researchers to plan their research, define their research questions, and select appropriate methods and techniques for collecting and analyzing data.
• To ensure research quality: Research methodology helps researchers to ensure that their research is rigorous, reliable, and valid. It provides guidelines for minimizing bias and error in data collection and analysis, and for ensuring that research findings are accurate and trustworthy.
• To replicate research: Research methodology provides a clear and detailed account of the research process, making it possible for other researchers to replicate the study and verify its findings.
• To advance knowledge: Research methodology enables researchers to generate new knowledge and to contribute to the body of knowledge in their field. It provides a means for testing hypotheses, exploring new ideas, and discovering new insights.
• To inform decision-making: Research methodology provides evidence-based information that can inform policy and decision-making in a variety of fields, including medicine, public health, education, and business.

Advantages of Research Methodology

Research methodology has several advantages that make it a valuable tool for conducting research in various fields. Here are some of the key advantages of research methodology:

• Systematic and structured approach : Research methodology provides a systematic and structured approach to conducting research, which ensures that the research is conducted in a rigorous and comprehensive manner.
• Objectivity : Research methodology aims to ensure objectivity in the research process, which means that the research findings are based on evidence and not influenced by personal bias or subjective opinions.
• Replicability : Research methodology ensures that research can be replicated by other researchers, which is essential for validating research findings and ensuring their accuracy.
• Reliability : Research methodology aims to ensure that the research findings are reliable, which means that they are consistent and can be depended upon.
• Validity : Research methodology ensures that the research findings are valid, which means that they accurately reflect the research question or hypothesis being tested.
• Efficiency : Research methodology provides a structured and efficient way of conducting research, which helps to save time and resources.
• Flexibility : Research methodology allows researchers to choose the most appropriate research methods and techniques based on the research question, data availability, and other relevant factors.
• Scope for innovation: Research methodology provides scope for innovation and creativity in designing research studies and developing new research techniques.

Research Methodology Vs Research Methods

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The Ultimate Guide To Research Methodology

Research methodology is a crucial aspect of any investigative process, serving as the blueprint for the entire research journey. If you are stuck in the methodology section of your research paper , then this blog will guide you on what is a research methodology, its types and how to successfully conduct one. 

Table of Contents

What Is Research Methodology?

Research methodology can be defined as the systematic framework that guides researchers in designing, conducting, and analyzing their investigations. It encompasses a structured set of processes, techniques, and tools employed to gather and interpret data, ensuring the reliability and validity of the research findings. 

Research methodology is not confined to a singular approach; rather, it encapsulates a diverse range of methods tailored to the specific requirements of the research objectives.

Here is why Research methodology is important in academic and professional settings.

Facilitating Rigorous Inquiry

Research methodology forms the backbone of rigorous inquiry. It provides a structured approach that aids researchers in formulating precise thesis statements , selecting appropriate methodologies, and executing systematic investigations. This, in turn, enhances the quality and credibility of the research outcomes.

Ensuring Reproducibility And Reliability

In both academic and professional contexts, the ability to reproduce research outcomes is paramount. A well-defined research methodology establishes clear procedures, making it possible for others to replicate the study. This not only validates the findings but also contributes to the cumulative nature of knowledge.

Guiding Decision-Making Processes

In professional settings, decisions often hinge on reliable data and insights. Research methodology equips professionals with the tools to gather pertinent information, analyze it rigorously, and derive meaningful conclusions.

This informed decision-making is instrumental in achieving organizational goals and staying ahead in competitive environments.

Contributing To Academic Excellence

For academic researchers, adherence to robust research methodology is a hallmark of excellence. Institutions value research that adheres to high standards of methodology, fostering a culture of academic rigour and intellectual integrity. Furthermore, it prepares students with critical skills applicable beyond academia.

Enhancing Problem-Solving Abilities

Research methodology instills a problem-solving mindset by encouraging researchers to approach challenges systematically. It equips individuals with the skills to dissect complex issues, formulate hypotheses , and devise effective strategies for investigation.

Understanding Research Methodology

In the pursuit of knowledge and discovery, understanding the fundamentals of research methodology is paramount. 

Basics Of Research

Research, in its essence, is a systematic and organized process of inquiry aimed at expanding our understanding of a particular subject or phenomenon. It involves the exploration of existing knowledge, the formulation of hypotheses, and the collection and analysis of data to draw meaningful conclusions. 

Research is a dynamic and iterative process that contributes to the continuous evolution of knowledge in various disciplines.

Types of Research

Research takes on various forms, each tailored to the nature of the inquiry. Broadly classified, research can be categorized into two main types:

• Quantitative Research: This type involves the collection and analysis of numerical data to identify patterns, relationships, and statistical significance. It is particularly useful for testing hypotheses and making predictions.
• Qualitative Research: Qualitative research focuses on understanding the depth and details of a phenomenon through non-numerical data. It often involves methods such as interviews, focus groups, and content analysis, providing rich insights into complex issues.

Components Of Research Methodology

To conduct effective research, one must go through the different components of research methodology. These components form the scaffolding that supports the entire research process, ensuring its coherence and validity.

Research Design

Research design serves as the blueprint for the entire research project. It outlines the overall structure and strategy for conducting the study. The three primary types of research design are:

• Exploratory Research: Aimed at gaining insights and familiarity with the topic, often used in the early stages of research.
• Descriptive Research: Involves portraying an accurate profile of a situation or phenomenon, answering the ‘what,’ ‘who,’ ‘where,’ and ‘when’ questions.
• Explanatory Research: Seeks to identify the causes and effects of a phenomenon, explaining the ‘why’ and ‘how.’

Data Collection Methods

Choosing the right data collection methods is crucial for obtaining reliable and relevant information. Common methods include:

• Surveys and Questionnaires: Employed to gather information from a large number of respondents through standardized questions.
• Interviews: In-depth conversations with participants, offering qualitative insights.
• Observation: Systematic watching and recording of behaviour, events, or processes in their natural setting.

Data Analysis Techniques

Once data is collected, analysis becomes imperative to derive meaningful conclusions. Different methodologies exist for quantitative and qualitative data:

• Quantitative Data Analysis: Involves statistical techniques such as descriptive statistics, inferential statistics, and regression analysis to interpret numerical data.
• Qualitative Data Analysis: Methods like content analysis, thematic analysis, and grounded theory are employed to extract patterns, themes, and meanings from non-numerical data.

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Choosing a Research Method

Selecting an appropriate research method is a critical decision in the research process. It determines the approach, tools, and techniques that will be used to answer the research questions. 

Quantitative Research Methods

Quantitative research involves the collection and analysis of numerical data, providing a structured and objective approach to understanding and explaining phenomena.

Experimental Research

Experimental research involves manipulating variables to observe the effect on another variable under controlled conditions. It aims to establish cause-and-effect relationships.

Key Characteristics:

• Controlled Environment: Experiments are conducted in a controlled setting to minimize external influences.
• Random Assignment: Participants are randomly assigned to different experimental conditions.
• Quantitative Data: Data collected is numerical, allowing for statistical analysis.

Applications: Commonly used in scientific studies and psychology to test hypotheses and identify causal relationships.

Survey Research

Survey research gathers information from a sample of individuals through standardized questionnaires or interviews. It aims to collect data on opinions, attitudes, and behaviours.

• Structured Instruments: Surveys use structured instruments, such as questionnaires, to collect data.
• Large Sample Size: Surveys often target a large and diverse group of participants.
• Quantitative Data Analysis: Responses are quantified for statistical analysis.

Applications: Widely employed in social sciences, marketing, and public opinion research to understand trends and preferences.

Descriptive Research

Descriptive research seeks to portray an accurate profile of a situation or phenomenon. It focuses on answering the ‘what,’ ‘who,’ ‘where,’ and ‘when’ questions.

• Observation and Data Collection: This involves observing and documenting without manipulating variables.
• Objective Description: Aim to provide an unbiased and factual account of the subject.
• Quantitative or Qualitative Data: T his can include both types of data, depending on the research focus.

Applications: Useful in situations where researchers want to understand and describe a phenomenon without altering it, common in social sciences and education.

Qualitative Research Methods

Qualitative research emphasizes exploring and understanding the depth and complexity of phenomena through non-numerical data.

A case study is an in-depth exploration of a particular person, group, event, or situation. It involves detailed, context-rich analysis.

• Rich Data Collection: Uses various data sources, such as interviews, observations, and documents.
• Contextual Understanding: Aims to understand the context and unique characteristics of the case.
• Holistic Approach: Examines the case in its entirety.

Applications: Common in social sciences, psychology, and business to investigate complex and specific instances.

Ethnography

Ethnography involves immersing the researcher in the culture or community being studied to gain a deep understanding of their behaviours, beliefs, and practices.

• Participant Observation: Researchers actively participate in the community or setting.
• Holistic Perspective: Focuses on the interconnectedness of cultural elements.
• Qualitative Data: In-depth narratives and descriptions are central to ethnographic studies.

Applications: Widely used in anthropology, sociology, and cultural studies to explore and document cultural practices.

Grounded Theory

Grounded theory aims to develop theories grounded in the data itself. It involves systematic data collection and analysis to construct theories from the ground up.

• Constant Comparison: Data is continually compared and analyzed during the research process.
• Inductive Reasoning: Theories emerge from the data rather than being imposed on it.
• Iterative Process: The research design evolves as the study progresses.

Applications: Commonly applied in sociology, nursing, and management studies to generate theories from empirical data.

Research design is the structural framework that outlines the systematic process and plan for conducting a study. It serves as the blueprint, guiding researchers on how to collect, analyze, and interpret data.

Exploratory, Descriptive, And Explanatory Designs

Exploratory design.

Exploratory research design is employed when a researcher aims to explore a relatively unknown subject or gain insights into a complex phenomenon.

• Flexibility: Allows for flexibility in data collection and analysis.
• Open-Ended Questions: Uses open-ended questions to gather a broad range of information.
• Preliminary Nature: Often used in the initial stages of research to formulate hypotheses.

Applications: Valuable in the early stages of investigation, especially when the researcher seeks a deeper understanding of a subject before formalizing research questions.

Descriptive Design

Descriptive research design focuses on portraying an accurate profile of a situation, group, or phenomenon.

• Structured Data Collection: Involves systematic and structured data collection methods.
• Objective Presentation: Aims to provide an unbiased and factual account of the subject.
• Quantitative or Qualitative Data: Can incorporate both types of data, depending on the research objectives.

Applications: Widely used in social sciences, marketing, and educational research to provide detailed and objective descriptions.

Explanatory Design

Explanatory research design aims to identify the causes and effects of a phenomenon, explaining the ‘why’ and ‘how’ behind observed relationships.

• Causal Relationships: Seeks to establish causal relationships between variables.
• Controlled Variables : Often involves controlling certain variables to isolate causal factors.
• Quantitative Analysis: Primarily relies on quantitative data analysis techniques.

Applications: Commonly employed in scientific studies and social sciences to delve into the underlying reasons behind observed patterns.

Cross-Sectional Vs. Longitudinal Designs

Cross-sectional design.

Cross-sectional designs collect data from participants at a single point in time.

• Snapshot View: Provides a snapshot of a population at a specific moment.
• Efficiency: More efficient in terms of time and resources.
• Limited Temporal Insights: Offers limited insights into changes over time.

Applications: Suitable for studying characteristics or behaviours that are stable or not expected to change rapidly.

Longitudinal Design

Longitudinal designs involve the collection of data from the same participants over an extended period.

• Temporal Sequence: Allows for the examination of changes over time.
• Causality Assessment: Facilitates the assessment of cause-and-effect relationships.
• Resource-Intensive: Requires more time and resources compared to cross-sectional designs.

Applications: Ideal for studying developmental processes, trends, or the impact of interventions over time.

Experimental Vs Non-experimental Designs

Experimental design.

Experimental designs involve manipulating variables under controlled conditions to observe the effect on another variable.

• Causality Inference: Enables the inference of cause-and-effect relationships.
• Quantitative Data: Primarily involves the collection and analysis of numerical data.

Applications: Commonly used in scientific studies, psychology, and medical research to establish causal relationships.

Non-Experimental Design

Non-experimental designs observe and describe phenomena without manipulating variables.

• Natural Settings: Data is often collected in natural settings without intervention.
• Descriptive or Correlational: Focuses on describing relationships or correlations between variables.
• Quantitative or Qualitative Data: This can involve either type of data, depending on the research approach.

Applications: Suitable for studying complex phenomena in real-world settings where manipulation may not be ethical or feasible.

Effective data collection is fundamental to the success of any research endeavour. 

Designing Effective Surveys

Objective Design:

• Clearly define the research objectives to guide the survey design.
• Craft questions that align with the study’s goals and avoid ambiguity.

Structured Format:

• Use a structured format with standardized questions for consistency.
• Include a mix of closed-ended and open-ended questions for detailed insights.

Pilot Testing:

• Conduct pilot tests to identify and rectify potential issues with survey design.
• Ensure clarity, relevance, and appropriateness of questions.

Sampling Strategy:

• Develop a robust sampling strategy to ensure a representative participant group.
• Consider random sampling or stratified sampling based on the research goals.

Conducting Interviews

Establishing Rapport:

• Build rapport with participants to create a comfortable and open environment.
• Clearly communicate the purpose of the interview and the value of participants’ input.

Open-Ended Questions:

• Frame open-ended questions to encourage detailed responses.
• Allow participants to express their thoughts and perspectives freely.

Active Listening:

• Practice active listening to understand areas and gather rich data.
• Avoid interrupting and maintain a non-judgmental stance during the interview.

Ethical Considerations:

• Obtain informed consent and assure participants of confidentiality.
• Be transparent about the study’s purpose and potential implications.

Observation

1. participant observation.

Immersive Participation:

• Actively immerse yourself in the setting or group being observed.
• Develop a deep understanding of behaviours, interactions, and context.

Field Notes:

• Maintain detailed and reflective field notes during observations.
• Document observed patterns, unexpected events, and participant reactions.

Ethical Awareness:

• Be conscious of ethical considerations, ensuring respect for participants.
• Balance the role of observer and participant to minimize bias.

2. Non-participant Observation

Objective Observation:

• Maintain a more detached and objective stance during non-participant observation.
• Focus on recording behaviours, events, and patterns without direct involvement.

Data Reliability:

• Enhance the reliability of data by reducing observer bias.
• Develop clear observation protocols and guidelines.

Contextual Understanding:

• Strive for a thorough understanding of the observed context.
• Consider combining non-participant observation with other methods for triangulation.

Archival Research

1. using existing data.

Identifying Relevant Archives:

• Locate and access archives relevant to the research topic.
• Collaborate with institutions or repositories holding valuable data.

Data Verification:

• Verify the accuracy and reliability of archived data.
• Cross-reference with other sources to ensure data integrity.

Ethical Use:

• Adhere to ethical guidelines when using existing data.
• Respect copyright and intellectual property rights.

2. Challenges and Considerations

Incomplete or Inaccurate Archives:

• Address the possibility of incomplete or inaccurate archival records.
• Acknowledge limitations and uncertainties in the data.

Temporal Bias:

• Recognize potential temporal biases in archived data.
• Consider the historical context and changes that may impact interpretation.

Access Limitations:

• Address potential limitations in accessing certain archives.
• Seek alternative sources or collaborate with institutions to overcome barriers.

Common Challenges in Research Methodology

Conducting research is a complex and dynamic process, often accompanied by a myriad of challenges. Addressing these challenges is crucial to ensure the reliability and validity of research findings.

Sampling Issues

Sampling bias:.

• The presence of sampling bias can lead to an unrepresentative sample, affecting the generalizability of findings.
• Employ random sampling methods and ensure the inclusion of diverse participants to reduce bias.

Sample Size Determination:

• Determining an appropriate sample size is a delicate balance. Too small a sample may lack statistical power, while an excessively large sample may strain resources.
• Conduct a power analysis to determine the optimal sample size based on the research objectives and expected effect size.

Data Quality And Validity

Measurement error:.

• Inaccuracies in measurement tools or data collection methods can introduce measurement errors, impacting the validity of results.
• Pilot test instruments, calibrate equipment, and use standardized measures to enhance the reliability of data.

Construct Validity:

• Ensuring that the chosen measures accurately capture the intended constructs is a persistent challenge.
• Use established measurement instruments and employ multiple measures to assess the same construct for triangulation.

Time And Resource Constraints

Timeline pressures:.

• Limited timeframes can compromise the depth and thoroughness of the research process.
• Develop a realistic timeline, prioritize tasks, and communicate expectations with stakeholders to manage time constraints effectively.

Resource Availability:

• Inadequate resources, whether financial or human, can impede the execution of research activities.
• Seek external funding, collaborate with other researchers, and explore alternative methods that require fewer resources.

Managing Bias in Research

Selection bias:.

• Selecting participants in a way that systematically skews the sample can introduce selection bias.
• Employ randomization techniques, use stratified sampling, and transparently report participant recruitment methods.

Confirmation Bias:

• Researchers may unintentionally favour information that confirms their preconceived beliefs or hypotheses.
• Adopt a systematic and open-minded approach, use blinded study designs, and engage in peer review to mitigate confirmation bias.

Tips On How To Write A Research Methodology

Conducting successful research relies not only on the application of sound methodologies but also on strategic planning and effective collaboration. Here are some tips to enhance the success of your research methodology:

Tip 1. Clear Research Objectives

Well-defined research objectives guide the entire research process. Clearly articulate the purpose of your study, outlining specific research questions or hypotheses.

Tip 2. Comprehensive Literature Review

A thorough literature review provides a foundation for understanding existing knowledge and identifying gaps. Invest time in reviewing relevant literature to inform your research design and methodology.

Tip 3. Detailed Research Plan

A detailed plan serves as a roadmap, ensuring all aspects of the research are systematically addressed. Develop a detailed research plan outlining timelines, milestones, and tasks.

Tip 4. Ethical Considerations

Ethical practices are fundamental to maintaining the integrity of research. Address ethical considerations early, obtain necessary approvals, and ensure participant rights are safeguarded.

Tip 5. Stay Updated On Methodologies

Research methodologies evolve, and staying updated is essential for employing the most effective techniques. Engage in continuous learning by attending workshops, conferences, and reading recent publications.

Tip 6. Adaptability In Methods

Unforeseen challenges may arise during research, necessitating adaptability in methods. Be flexible and willing to modify your approach when needed, ensuring the integrity of the study.

Tip 7. Iterative Approach

Research is often an iterative process, and refining methods based on ongoing findings enhance the study’s robustness. Regularly review and refine your research design and methods as the study progresses.

Frequently Asked Questions

What is the research methodology.

Research methodology is the systematic process of planning, executing, and evaluating scientific investigation. It encompasses the techniques, tools, and procedures used to collect, analyze, and interpret data, ensuring the reliability and validity of research findings.

What are the methodologies in research?

Research methodologies include qualitative and quantitative approaches. Qualitative methods involve in-depth exploration of non-numerical data, while quantitative methods use statistical analysis to examine numerical data. Mixed methods combine both approaches for a comprehensive understanding of research questions.

How to write research methodology?

To write a research methodology, clearly outline the study’s design, data collection, and analysis procedures. Specify research tools, participants, and sampling methods. Justify choices and discuss limitations. Ensure clarity, coherence, and alignment with research objectives for a robust methodology section.

How to write the methodology section of a research paper?

In the methodology section of a research paper, describe the study’s design, data collection, and analysis methods. Detail procedures, tools, participants, and sampling. Justify choices, address ethical considerations, and explain how the methodology aligns with research objectives, ensuring clarity and rigour.

What is mixed research methodology?

Mixed research methodology combines both qualitative and quantitative research approaches within a single study. This approach aims to enhance the details and depth of research findings by providing a more comprehensive understanding of the research problem or question.

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What is research methodology?

The basics of research methodology

Why do you need a research methodology, what needs to be included, why do you need to document your research method, what are the different types of research instruments, qualitative / quantitative / mixed research methodologies, how do you choose the best research methodology for you, frequently asked questions about research methodology, related articles.

When you’re working on your first piece of academic research, there are many different things to focus on, and it can be overwhelming to stay on top of everything. This is especially true of budding or inexperienced researchers.

If you’ve never put together a research proposal before or find yourself in a position where you need to explain your research methodology decisions, there are a few things you need to be aware of.

Once you understand the ins and outs, handling academic research in the future will be less intimidating. We break down the basics below:

A research methodology encompasses the way in which you intend to carry out your research. This includes how you plan to tackle things like collection methods, statistical analysis, participant observations, and more.

You can think of your research methodology as being a formula. One part will be how you plan on putting your research into practice, and another will be why you feel this is the best way to approach it. Your research methodology is ultimately a methodological and systematic plan to resolve your research problem.

In short, you are explaining how you will take your idea and turn it into a study, which in turn will produce valid and reliable results that are in accordance with the aims and objectives of your research. This is true whether your paper plans to make use of qualitative methods or quantitative methods.

The purpose of a research methodology is to explain the reasoning behind your approach to your research - you'll need to support your collection methods, methods of analysis, and other key points of your work.

Think of it like writing a plan or an outline for you what you intend to do.

When carrying out research, it can be easy to go off-track or depart from your standard methodology.

Tip: Having a methodology keeps you accountable and on track with your original aims and objectives, and gives you a suitable and sound plan to keep your project manageable, smooth, and effective.

With all that said, how do you write out your standard approach to a research methodology?

As a general plan, your methodology should include the following information:

• Your research method.  You need to state whether you plan to use quantitative analysis, qualitative analysis, or mixed-method research methods. This will often be determined by what you hope to achieve with your research.
• Explain your reasoning. Why are you taking this methodological approach? Why is this particular methodology the best way to answer your research problem and achieve your objectives?
• Explain your instruments.  This will mainly be about your collection methods. There are varying instruments to use such as interviews, physical surveys, questionnaires, for example. Your methodology will need to detail your reasoning in choosing a particular instrument for your research.
• What will you do with your results?  How are you going to analyze the data once you have gathered it?
• Advise your reader.  If there is anything in your research methodology that your reader might be unfamiliar with, you should explain it in more detail. For example, you should give any background information to your methods that might be relevant or provide your reasoning if you are conducting your research in a non-standard way.
• How will your sampling process go?  What will your sampling procedure be and why? For example, if you will collect data by carrying out semi-structured or unstructured interviews, how will you choose your interviewees and how will you conduct the interviews themselves?
• Any practical limitations?  You should discuss any limitations you foresee being an issue when you’re carrying out your research.

In any dissertation, thesis, or academic journal, you will always find a chapter dedicated to explaining the research methodology of the person who carried out the study, also referred to as the methodology section of the work.

A good research methodology will explain what you are going to do and why, while a poor methodology will lead to a messy or disorganized approach.

You should also be able to justify in this section your reasoning for why you intend to carry out your research in a particular way, especially if it might be a particularly unique method.

Having a sound methodology in place can also help you with the following:

• When another researcher at a later date wishes to try and replicate your research, they will need your explanations and guidelines.
• In the event that you receive any criticism or questioning on the research you carried out at a later point, you will be able to refer back to it and succinctly explain the how and why of your approach.
• It provides you with a plan to follow throughout your research. When you are drafting your methodology approach, you need to be sure that the method you are using is the right one for your goal. This will help you with both explaining and understanding your method.
• It affords you the opportunity to document from the outset what you intend to achieve with your research, from start to finish.

A research instrument is a tool you will use to help you collect, measure and analyze the data you use as part of your research.

The choice of research instrument will usually be yours to make as the researcher and will be whichever best suits your methodology.

There are many different research instruments you can use in collecting data for your research.

Generally, they can be grouped as follows:

• Interviews (either as a group or one-on-one). You can carry out interviews in many different ways. For example, your interview can be structured, semi-structured, or unstructured. The difference between them is how formal the set of questions is that is asked of the interviewee. In a group interview, you may choose to ask the interviewees to give you their opinions or perceptions on certain topics.
• Surveys (online or in-person). In survey research, you are posing questions in which you ask for a response from the person taking the survey. You may wish to have either free-answer questions such as essay-style questions, or you may wish to use closed questions such as multiple choice. You may even wish to make the survey a mixture of both.
• Focus Groups.  Similar to the group interview above, you may wish to ask a focus group to discuss a particular topic or opinion while you make a note of the answers given.
• Observations.  This is a good research instrument to use if you are looking into human behaviors. Different ways of researching this include studying the spontaneous behavior of participants in their everyday life, or something more structured. A structured observation is research conducted at a set time and place where researchers observe behavior as planned and agreed upon with participants.

These are the most common ways of carrying out research, but it is really dependent on your needs as a researcher and what approach you think is best to take.

It is also possible to combine a number of research instruments if this is necessary and appropriate in answering your research problem.

There are three different types of methodologies, and they are distinguished by whether they focus on words, numbers, or both.

➡️ Want to learn more about the differences between qualitative and quantitative research, and how to use both methods? Check out our guide for that!

If you've done your due diligence, you'll have an idea of which methodology approach is best suited to your research.

It’s likely that you will have carried out considerable reading and homework before you reach this point and you may have taken inspiration from other similar studies that have yielded good results.

Still, it is important to consider different options before setting your research in stone. Exploring different options available will help you to explain why the choice you ultimately make is preferable to other methods.

If proving your research problem requires you to gather large volumes of numerical data to test hypotheses, a quantitative research method is likely to provide you with the most usable results.

If instead you’re looking to try and learn more about people, and their perception of events, your methodology is more exploratory in nature and would therefore probably be better served using a qualitative research methodology.

It helps to always bring things back to the question: what do I want to achieve with my research?

Once you have conducted your research, you need to analyze it. Here are some helpful guides for qualitative data analysis:

➡️  How to do a content analysis

➡️  How to do a thematic analysis

➡️  How to do a rhetorical analysis

Research methodology refers to the techniques used to find and analyze information for a study, ensuring that the results are valid, reliable and that they address the research objective.

Data can typically be organized into four different categories or methods: observational, experimental, simulation, and derived.

Writing a methodology section is a process of introducing your methods and instruments, discussing your analysis, providing more background information, addressing your research limitations, and more.

Your research methodology section will need a clear research question and proposed research approach. You'll need to add a background, introduce your research question, write your methodology and add the works you cited during your data collecting phase.

The research methodology section of your study will indicate how valid your findings are and how well-informed your paper is. It also assists future researchers planning to use the same methodology, who want to cite your study or replicate it.

Formulating Research Aims and Objectives

Formulating research aim and objectives in an appropriate manner is one of the most important aspects of your thesis. This is because research aim and objectives determine the scope, depth and the overall direction of the research. Research question is the central question of the study that has to be answered on the basis of research findings.

Research aim emphasizes what needs to be achieved within the scope of the research, by the end of the research process. Achievement of research aim provides answer to the research question.

Research objectives divide research aim into several parts and address each part separately. Research aim specifies WHAT needs to be studied and research objectives comprise a number of steps that address HOW research aim will be achieved.

As a rule of dumb, there would be one research aim and several research objectives. Achievement of each research objective will lead to the achievement of the research aim.

Consider the following as an example:

Research title: Effects of organizational culture on business profitability: a case study of Virgin Atlantic

Research aim: To assess the effects of Virgin Atlantic organizational culture on business profitability

Following research objectives would facilitate the achievement of this aim:

• Analyzing the nature of organizational culture at Virgin Atlantic by September 1, 2022
• Identifying factors impacting Virgin Atlantic organizational culture by September 16, 2022
• Analyzing impacts of Virgin Atlantic organizational culture on employee performances by September 30, 2022
• Providing recommendations to Virgin Atlantic strategic level management in terms of increasing the level of effectiveness of organizational culture by October 5, 2022

Figure below illustrates additional examples in formulating research aims and objectives:

Formulation of research question, aim and objectives

Common mistakes in the formulation of research aim relate to the following:

1. Choosing the topic too broadly . This is the most common mistake. For example, a research title of “an analysis of leadership practices” can be classified as too broad because the title fails to answer the following questions:

a) Which aspects of leadership practices? Leadership has many aspects such as employee motivation, ethical behaviour, strategic planning, change management etc. An attempt to cover all of these aspects of organizational leadership within a single research will result in an unfocused and poor work.

b) An analysis of leadership practices in which country? Leadership practices tend to be different in various countries due to cross-cultural differences, legislations and a range of other region-specific factors. Therefore, a study of leadership practices needs to be country-specific.

c) Analysis of leadership practices in which company or industry? Similar to the point above, analysis of leadership practices needs to take into account industry-specific and/or company-specific differences, and there is no way to conduct a leadership research that relates to all industries and organizations in an equal manner.

Accordingly, as an example “a study into the impacts of ethical behaviour of a leader on the level of employee motivation in US healthcare sector” would be a more appropriate title than simply “An analysis of leadership practices”.

2. Setting an unrealistic aim . Formulation of a research aim that involves in-depth interviews with Apple strategic level management by an undergraduate level student can be specified as a bit over-ambitious. This is because securing an interview with Apple CEO Tim Cook or members of Apple Board of Directors might not be easy. This is an extreme example of course, but you got the idea. Instead, you may aim to interview the manager of your local Apple store and adopt a more feasible strategy to get your dissertation completed.

3. Choosing research methods incompatible with the timeframe available . Conducting interviews with 20 sample group members and collecting primary data through 2 focus groups when only three months left until submission of your dissertation can be very difficult, if not impossible. Accordingly, timeframe available need to be taken into account when formulating research aims and objectives and selecting research methods.

Moreover, research objectives need to be formulated according to SMART principle,

 where the abbreviation stands for specific, measurable, achievable, realistic, and time-bound.

Examples of SMART research objectives

At the conclusion part of your research project you will need to reflect on the level of achievement of research aims and objectives. In case your research aims and objectives are not fully achieved by the end of the study, you will need to discuss the reasons. These may include initial inappropriate formulation of research aims and objectives, effects of other variables that were not considered at the beginning of the research or changes in some circumstances during the research process.

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Choosing the Right Research Methodology: A Guide for Researchers

• 3 minute read

Table of Contents

Choosing an optimal research methodology is crucial for the success of any research project. The methodology you select will determine the type of data you collect, how you collect it, and how you analyse it. Understanding the different types of research methods available along with their strengths and weaknesses, is thus imperative to make an informed decision.

Understanding different research methods:

There are several research methods available depending on the type of study you are conducting, i.e., whether it is laboratory-based, clinical, epidemiological, or survey based . Some common methodologies include qualitative research, quantitative research, experimental research, survey-based research, and action research. Each method can be opted for and modified, depending on the type of research hypotheses and objectives.

Qualitative vs quantitative research:

When deciding on a research methodology, one of the key factors to consider is whether your research will be qualitative or quantitative. Qualitative research is used to understand people’s experiences, concepts, thoughts, or behaviours . Quantitative research, on the contrary, deals with numbers, graphs, and charts, and is used to test or confirm hypotheses, assumptions, and theories. 

Qualitative research methodology:

Qualitative research is often used to examine issues that are not well understood, and to gather additional insights on these topics. Qualitative research methods include open-ended survey questions, observations of behaviours described through words, and reviews of literature that has explored similar theories and ideas. These methods are used to understand how language is used in real-world situations, identify common themes or overarching ideas, and describe and interpret various texts. Data analysis for qualitative research typically includes discourse analysis, thematic analysis, and textual analysis. 

Quantitative research methodology:

The goal of quantitative research is to test hypotheses, confirm assumptions and theories, and determine cause-and-effect relationships. Quantitative research methods include experiments, close-ended survey questions, and countable and numbered observations. Data analysis for quantitative research relies heavily on statistical methods.

Analysing qualitative vs quantitative data:

The methods used for data analysis also differ for qualitative and quantitative research. As mentioned earlier, quantitative data is generally analysed using statistical methods and does not leave much room for speculation. It is more structured and follows a predetermined plan. In quantitative research, the researcher starts with a hypothesis and uses statistical methods to test it. Contrarily, methods used for qualitative data analysis can identify patterns and themes within the data, rather than provide statistical measures of the data. It is an iterative process, where the researcher goes back and forth trying to gauge the larger implications of the data through different perspectives and revising the analysis if required.

When to use qualitative vs quantitative research:

The choice between qualitative and quantitative research will depend on the gap that the research project aims to address, and specific objectives of the study. If the goal is to establish facts about a subject or topic, quantitative research is an appropriate choice. However, if the goal is to understand people’s experiences or perspectives, qualitative research may be more suitable. 

Conclusion:

In conclusion, an understanding of the different research methods available, their applicability, advantages, and disadvantages is essential for making an informed decision on the best methodology for your project. If you need any additional guidance on which research methodology to opt for, you can head over to Elsevier Author Services (EAS). EAS experts will guide you throughout the process and help you choose the perfect methodology for your research goals.

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When Data Speak, Listen: Importance of Data Collection and Analysis Methods

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How To Choose Your Research Methodology

Qualitative vs quantitative vs mixed methods.

By: Derek Jansen (MBA). Expert Reviewed By: Dr Eunice Rautenbach | June 2021

Without a doubt, one of the most common questions we receive at Grad Coach is “ How do I choose the right methodology for my research? ”. It’s easy to see why – with so many options on the research design table, it’s easy to get intimidated, especially with all the complex lingo!

In this post, we’ll explain the three overarching types of research – qualitative, quantitative and mixed methods – and how you can go about choosing the best methodological approach for your research.

Overview: Choosing Your Methodology

Understanding the options – Qualitative research – Quantitative research – Mixed methods-based research

Choosing a research methodology – Nature of the research – Research area norms – Practicalities

1. Understanding the options

Before we jump into the question of how to choose a research methodology, it’s useful to take a step back to understand the three overarching types of research – qualitative , quantitative and mixed methods -based research. Each of these options takes a different methodological approach.

Qualitative research utilises data that is not numbers-based. In other words, qualitative research focuses on words , descriptions , concepts or ideas – while quantitative research makes use of numbers and statistics. Qualitative research investigates the “softer side” of things to explore and describe, while quantitative research focuses on the “hard numbers”, to measure differences between variables and the relationships between them.

Importantly, qualitative research methods are typically used to explore and gain a deeper understanding of the complexity of a situation – to draw a rich picture . In contrast to this, quantitative methods are usually used to confirm or test hypotheses . In other words, they have distinctly different purposes. The table below highlights a few of the key differences between qualitative and quantitative research – you can learn more about the differences here.

• Uses an inductive approach
• Is used to build theories
• Takes a subjective approach
• Adopts an open and flexible approach
• The researcher is close to the respondents
• Interviews and focus groups are oftentimes used to collect word-based data.
• Generally, draws on small sample sizes
• Uses qualitative data analysis techniques (e.g. content analysis , thematic analysis , etc)
• Uses a deductive approach
• Is used to test theories
• Takes an objective approach
• Adopts a closed, highly planned approach
• The research is disconnected from respondents
• Surveys or laboratory equipment are often used to collect number-based data.
• Generally, requires large sample sizes
• Uses statistical analysis techniques to make sense of the data

Mixed methods -based research, as you’d expect, attempts to bring these two types of research together, drawing on both qualitative and quantitative data. Quite often, mixed methods-based studies will use qualitative research to explore a situation and develop a potential model of understanding (this is called a conceptual framework), and then go on to use quantitative methods to test that model empirically.

In other words, while qualitative and quantitative methods (and the philosophies that underpin them) are completely different, they are not at odds with each other. It’s not a competition of qualitative vs quantitative. On the contrary, they can be used together to develop a high-quality piece of research. Of course, this is easier said than done, so we usually recommend that first-time researchers stick to a single approach , unless the nature of their study truly warrants a mixed-methods approach.

The key takeaway here, and the reason we started by looking at the three options, is that it’s important to understand that each methodological approach has a different purpose – for example, to explore and understand situations (qualitative), to test and measure (quantitative) or to do both. They’re not simply alternative tools for the same job. 

Right – now that we’ve got that out of the way, let’s look at how you can go about choosing the right methodology for your research.

2. How to choose a research methodology

To choose the right research methodology for your dissertation or thesis, you need to consider three important factors . Based on these three factors, you can decide on your overarching approach – qualitative, quantitative or mixed methods. Once you’ve made that decision, you can flesh out the finer details of your methodology, such as the sampling , data collection methods and analysis techniques (we discuss these separately in other posts ).

The three factors you need to consider are:

• The nature of your research aims, objectives and research questions
• The methodological approaches taken in the existing literature
• Practicalities and constraints

Let’s take a look at each of these.

Factor #1: The nature of your research

As I mentioned earlier, each type of research (and therefore, research methodology), whether qualitative, quantitative or mixed, has a different purpose and helps solve a different type of question. So, it’s logical that the key deciding factor in terms of which research methodology you adopt is the nature of your research aims, objectives and research questions .

But, what types of research exist?

Broadly speaking, research can fall into one of three categories:

• Exploratory – getting a better understanding of an issue and potentially developing a theory regarding it
• Confirmatory – confirming a potential theory or hypothesis by testing it empirically
• A mix of both – building a potential theory or hypothesis and then testing it

As a rule of thumb, exploratory research tends to adopt a qualitative approach , whereas confirmatory research tends to use quantitative methods . This isn’t set in stone, but it’s a very useful heuristic. Naturally then, research that combines a mix of both, or is seeking to develop a theory from the ground up and then test that theory, would utilize a mixed-methods approach.

Let’s look at an example in action.

If your research aims were to understand the perspectives of war veterans regarding certain political matters, you’d likely adopt a qualitative methodology, making use of interviews to collect data and one or more qualitative data analysis methods to make sense of the data.

If, on the other hand, your research aims involved testing a set of hypotheses regarding the link between political leaning and income levels, you’d likely adopt a quantitative methodology, using numbers-based data from a survey to measure the links between variables and/or constructs .

So, the first (and most important thing) thing you need to consider when deciding which methodological approach to use for your research project is the nature of your research aims , objectives and research questions. Specifically, you need to assess whether your research leans in an exploratory or confirmatory direction or involves a mix of both.

The importance of achieving solid alignment between these three factors and your methodology can’t be overstated. If they’re misaligned, you’re going to be forcing a square peg into a round hole. In other words, you’ll be using the wrong tool for the job, and your research will become a disjointed mess.

If your research is a mix of both exploratory and confirmatory, but you have a tight word count limit, you may need to consider trimming down the scope a little and focusing on one or the other. One methodology executed well has a far better chance of earning marks than a poorly executed mixed methods approach. So, don’t try to be a hero, unless there is a very strong underpinning logic.

Need a helping hand?

Factor #2: The disciplinary norms

Choosing the right methodology for your research also involves looking at the approaches used by other researchers in the field, and studies with similar research aims and objectives to yours. Oftentimes, within a discipline, there is a common methodological approach (or set of approaches) used in studies. While this doesn’t mean you should follow the herd “just because”, you should at least consider these approaches and evaluate their merit within your context.

A major benefit of reviewing the research methodologies used by similar studies in your field is that you can often piggyback on the data collection techniques that other (more experienced) researchers have developed. For example, if you’re undertaking a quantitative study, you can often find tried and tested survey scales with high Cronbach’s alphas. These are usually included in the appendices of journal articles, so you don’t even have to contact the original authors. By using these, you’ll save a lot of time and ensure that your study stands on the proverbial “shoulders of giants” by using high-quality measurement instruments .

Of course, when reviewing existing literature, keep point #1 front of mind. In other words, your methodology needs to align with your research aims, objectives and questions. Don’t fall into the trap of adopting the methodological “norm” of other studies just because it’s popular. Only adopt that which is relevant to your research.

Factor #3: Practicalities

When choosing a research methodology, there will always be a tension between doing what’s theoretically best (i.e., the most scientifically rigorous research design ) and doing what’s practical , given your constraints . This is the nature of doing research and there are always trade-offs, as with anything else.

But what constraints, you ask?

When you’re evaluating your methodological options, you need to consider the following constraints:

• Data access
• Equipment and software
• Your knowledge and skills

Let’s look at each of these.

Constraint #1: Data access

The first practical constraint you need to consider is your access to data . If you’re going to be undertaking primary research , you need to think critically about the sample of respondents you realistically have access to. For example, if you plan to use in-person interviews , you need to ask yourself how many people you’ll need to interview, whether they’ll be agreeable to being interviewed, where they’re located, and so on.

If you’re wanting to undertake a quantitative approach using surveys to collect data, you’ll need to consider how many responses you’ll require to achieve statistically significant results. For many statistical tests, a sample of a few hundred respondents is typically needed to develop convincing conclusions.

So, think carefully about what data you’ll need access to, how much data you’ll need and how you’ll collect it. The last thing you want is to spend a huge amount of time on your research only to find that you can’t get access to the required data.

Constraint #2: Time

The next constraint is time. If you’re undertaking research as part of a PhD, you may have a fairly open-ended time limit, but this is unlikely to be the case for undergrad and Masters-level projects. So, pay attention to your timeline, as the data collection and analysis components of different methodologies have a major impact on time requirements . Also, keep in mind that these stages of the research often take a lot longer than originally anticipated.

Another practical implication of time limits is that it will directly impact which time horizon you can use – i.e. longitudinal vs cross-sectional . For example, if you’ve got a 6-month limit for your entire research project, it’s quite unlikely that you’ll be able to adopt a longitudinal time horizon. 

Constraint #3: Money

As with so many things, money is another important constraint you’ll need to consider when deciding on your research methodology. While some research designs will cost near zero to execute, others may require a substantial budget .

Some of the costs that may arise include:

• Software costs – e.g. survey hosting services, analysis software, etc.
• Promotion costs – e.g. advertising a survey to attract respondents
• Incentive costs – e.g. providing a prize or cash payment incentive to attract respondents
• Equipment rental costs – e.g. recording equipment, lab equipment, etc.
• Travel costs
• Food & beverages

These are just a handful of costs that can creep into your research budget. Like most projects, the actual costs tend to be higher than the estimates, so be sure to err on the conservative side and expect the unexpected. It’s critically important that you’re honest with yourself about these costs, or you could end up getting stuck midway through your project because you’ve run out of money.

Constraint #4: Equipment & software

Another practical consideration is the hardware and/or software you’ll need in order to undertake your research. Of course, this variable will depend on the type of data you’re collecting and analysing. For example, you may need lab equipment to analyse substances, or you may need specific analysis software to analyse statistical data. So, be sure to think about what hardware and/or software you’ll need for each potential methodological approach, and whether you have access to these.

Constraint #5: Your knowledge and skillset

The final practical constraint is a big one. Naturally, the research process involves a lot of learning and development along the way, so you will accrue knowledge and skills as you progress. However, when considering your methodological options, you should still consider your current position on the ladder.

Some of the questions you should ask yourself are:

• Am I more of a “numbers person” or a “words person”?
• How much do I know about the analysis methods I’ll potentially use (e.g. statistical analysis)?
• How much do I know about the software and/or hardware that I’ll potentially use?
• How excited am I to learn new research skills and gain new knowledge?
• How much time do I have to learn the things I need to learn?

Answering these questions honestly will provide you with another set of criteria against which you can evaluate the research methodology options you’ve shortlisted.

So, as you can see, there is a wide range of practicalities and constraints that you need to take into account when you’re deciding on a research methodology. These practicalities create a tension between the “ideal” methodology and the methodology that you can realistically pull off. This is perfectly normal, and it’s your job to find the option that presents the best set of trade-offs.

Recap: Choosing a methodology

In this post, we’ve discussed how to go about choosing a research methodology. The three major deciding factors we looked at were:

• Exploratory
• Confirmatory
• Combination
• Research area norms
• Hardware and software
• Your knowledge and skillset

If you have any questions, feel free to leave a comment below. If you’d like a helping hand with your research methodology, check out our 1-on-1 research coaching service , or book a free consultation with a friendly Grad Coach.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

Very useful and informative especially for beginners

Nice article! I’m a beginner in the field of cybersecurity research. I am a Telecom and Network Engineer and Also aiming for PhD scholarship.

I find the article very informative especially for my decitation it has been helpful and an eye opener.

Hi I am Anna ,

I am a PHD candidate in the area of cyber security, maybe we can link up

The Examples shows by you, for sure they are really direct me and others to knows and practices the Research Design and prepration.

I found the post very informative and practical.

I struggle so much with designs of the research for sure!

I’m the process of constructing my research design and I want to know if the data analysis I plan to present in my thesis defense proposal possibly change especially after I gathered the data already.

Thank you so much this site is such a life saver. How I wish 1-1 coaching is available in our country but sadly it’s not.

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• Aims and Objectives – A Guide for Academic Writing
• Doing a PhD

One of the most important aspects of a thesis, dissertation or research paper is the correct formulation of the aims and objectives. This is because your aims and objectives will establish the scope, depth and direction that your research will ultimately take. An effective set of aims and objectives will give your research focus and your reader clarity, with your aims indicating what is to be achieved, and your objectives indicating how it will be achieved.

Introduction

There is no getting away from the importance of the aims and objectives in determining the success of your research project. Unfortunately, however, it is an aspect that many students struggle with, and ultimately end up doing poorly. Given their importance, if you suspect that there is even the smallest possibility that you belong to this group of students, we strongly recommend you read this page in full.

This page describes what research aims and objectives are, how they differ from each other, how to write them correctly, and the common mistakes students make and how to avoid them. An example of a good aim and objectives from a past thesis has also been deconstructed to help your understanding.

What Are Aims and Objectives?

Research aims.

A research aim describes the main goal or the overarching purpose of your research project.

In doing so, it acts as a focal point for your research and provides your readers with clarity as to what your study is all about. Because of this, research aims are almost always located within its own subsection under the introduction section of a research document, regardless of whether it’s a thesis , a dissertation, or a research paper .

A research aim is usually formulated as a broad statement of the main goal of the research and can range in length from a single sentence to a short paragraph. Although the exact format may vary according to preference, they should all describe why your research is needed (i.e. the context), what it sets out to accomplish (the actual aim) and, briefly, how it intends to accomplish it (overview of your objectives).

To give an example, we have extracted the following research aim from a real PhD thesis:

Example of a Research Aim

The role of diametrical cup deformation as a factor to unsatisfactory implant performance has not been widely reported. The aim of this thesis was to gain an understanding of the diametrical deformation behaviour of acetabular cups and shells following impaction into the reamed acetabulum. The influence of a range of factors on deformation was investigated to ascertain if cup and shell deformation may be high enough to potentially contribute to early failure and high wear rates in metal-on-metal implants.

Note: Extracted with permission from thesis titled “T he Impact And Deformation Of Press-Fit Metal Acetabular Components ” produced by Dr H Hothi of previously Queen Mary University of London.

Research Objectives

Where a research aim specifies what your study will answer, research objectives specify how your study will answer it.

They divide your research aim into several smaller parts, each of which represents a key section of your research project. As a result, almost all research objectives take the form of a numbered list, with each item usually receiving its own chapter in a dissertation or thesis.

Following the example of the research aim shared above, here are it’s real research objectives as an example:

Example of a Research Objective

• Develop finite element models using explicit dynamics to mimic mallet blows during cup/shell insertion, initially using simplified experimentally validated foam models to represent the acetabulum.
• Investigate the number, velocity and position of impacts needed to insert a cup.
• Determine the relationship between the size of interference between the cup and cavity and deformation for different cup types.
• Investigate the influence of non-uniform cup support and varying the orientation of the component in the cavity on deformation.
• Examine the influence of errors during reaming of the acetabulum which introduce ovality to the cavity.
• Determine the relationship between changes in the geometry of the component and deformation for different cup designs.
• Develop three dimensional pelvis models with non-uniform bone material properties from a range of patients with varying bone quality.
• Use the key parameters that influence deformation, as identified in the foam models to determine the range of deformations that may occur clinically using the anatomic models and if these deformations are clinically significant.

It’s worth noting that researchers sometimes use research questions instead of research objectives, or in other cases both. From a high-level perspective, research questions and research objectives make the same statements, but just in different formats.

Taking the first three research objectives as an example, they can be restructured into research questions as follows:

Restructuring Research Objectives as Research Questions

• Can finite element models using simplified experimentally validated foam models to represent the acetabulum together with explicit dynamics be used to mimic mallet blows during cup/shell insertion?
• What is the number, velocity and position of impacts needed to insert a cup?
• What is the relationship between the size of interference between the cup and cavity and deformation for different cup types?

Difference Between Aims and Objectives

Hopefully the above explanations make clear the differences between aims and objectives, but to clarify:

• The research aim focus on what the research project is intended to achieve; research objectives focus on how the aim will be achieved.
• Research aims are relatively broad; research objectives are specific.
• Research aims focus on a project’s long-term outcomes; research objectives focus on its immediate, short-term outcomes.
• A research aim can be written in a single sentence or short paragraph; research objectives should be written as a numbered list.

How to Write Aims and Objectives

Before we discuss how to write a clear set of research aims and objectives, we should make it clear that there is no single way they must be written. Each researcher will approach their aims and objectives slightly differently, and often your supervisor will influence the formulation of yours on the basis of their own preferences.

Regardless, there are some basic principles that you should observe for good practice; these principles are described below.

Your aim should be made up of three parts that answer the below questions:

• Why is this research required?
• What is this research about?
• How are you going to do it?

The easiest way to achieve this would be to address each question in its own sentence, although it does not matter whether you combine them or write multiple sentences for each, the key is to address each one.

The first question, why , provides context to your research project, the second question, what , describes the aim of your research, and the last question, how , acts as an introduction to your objectives which will immediately follow.

Scroll through the image set below to see the ‘why, what and how’ associated with our research aim example.

Note: Your research aims need not be limited to one. Some individuals per to define one broad ‘overarching aim’ of a project and then adopt two or three specific research aims for their thesis or dissertation. Remember, however, that in order for your assessors to consider your research project complete, you will need to prove you have fulfilled all of the aims you set out to achieve. Therefore, while having more than one research aim is not necessarily disadvantageous, consider whether a single overarching one will do.

Research Objectives

Each of your research objectives should be SMART :

• Specific – is there any ambiguity in the action you are going to undertake, or is it focused and well-defined?
• Measurable – how will you measure progress and determine when you have achieved the action?
• Achievable – do you have the support, resources and facilities required to carry out the action?
• Relevant – is the action essential to the achievement of your research aim?
• Timebound – can you realistically complete the action in the available time alongside your other research tasks?

In addition to being SMART, your research objectives should start with a verb that helps communicate your intent. Common research verbs include:

Table of Research Verbs to Use in Aims and Objectives

Last, format your objectives into a numbered list. This is because when you write your thesis or dissertation, you will at times need to make reference to a specific research objective; structuring your research objectives in a numbered list will provide a clear way of doing this.

To bring all this together, let’s compare the first research objective in the previous example with the above guidance:

Checking Research Objective Example Against Recommended Approach

Research Objective:

1. Develop finite element models using explicit dynamics to mimic mallet blows during cup/shell insertion, initially using simplified experimentally validated foam models to represent the acetabulum.

Checking Against Recommended Approach:

Q: Is it specific? A: Yes, it is clear what the student intends to do (produce a finite element model), why they intend to do it (mimic cup/shell blows) and their parameters have been well-defined ( using simplified experimentally validated foam models to represent the acetabulum ).

Q: Is it measurable? A: Yes, it is clear that the research objective will be achieved once the finite element model is complete.

Q: Is it achievable? A: Yes, provided the student has access to a computer lab, modelling software and laboratory data.

Q: Is it relevant? A: Yes, mimicking impacts to a cup/shell is fundamental to the overall aim of understanding how they deform when impacted upon.

Q: Is it timebound? A: Yes, it is possible to create a limited-scope finite element model in a relatively short time, especially if you already have experience in modelling.

Q: Does it start with a verb? A: Yes, it starts with ‘develop’, which makes the intent of the objective immediately clear.

Q: Is it a numbered list? A: Yes, it is the first research objective in a list of eight.

Mistakes in Writing Research Aims and Objectives

1. making your research aim too broad.

Having a research aim too broad becomes very difficult to achieve. Normally, this occurs when a student develops their research aim before they have a good understanding of what they want to research. Remember that at the end of your project and during your viva defence , you will have to prove that you have achieved your research aims; if they are too broad, this will be an almost impossible task. In the early stages of your research project, your priority should be to narrow your study to a specific area. A good way to do this is to take the time to study existing literature, question their current approaches, findings and limitations, and consider whether there are any recurring gaps that could be investigated .

Note: Achieving a set of aims does not necessarily mean proving or disproving a theory or hypothesis, even if your research aim was to, but having done enough work to provide a useful and original insight into the principles that underlie your research aim.

2. Making Your Research Objectives Too Ambitious

Be realistic about what you can achieve in the time you have available. It is natural to want to set ambitious research objectives that require sophisticated data collection and analysis, but only completing this with six months before the end of your PhD registration period is not a worthwhile trade-off.

3. Formulating Repetitive Research Objectives

Each research objective should have its own purpose and distinct measurable outcome. To this effect, a common mistake is to form research objectives which have large amounts of overlap. This makes it difficult to determine when an objective is truly complete, and also presents challenges in estimating the duration of objectives when creating your project timeline. It also makes it difficult to structure your thesis into unique chapters, making it more challenging for you to write and for your audience to read.

Fortunately, this oversight can be easily avoided by using SMART objectives.

Hopefully, you now have a good idea of how to create an effective set of aims and objectives for your research project, whether it be a thesis, dissertation or research paper. While it may be tempting to dive directly into your research, spending time on getting your aims and objectives right will give your research clear direction. This won’t only reduce the likelihood of problems arising later down the line, but will also lead to a more thorough and coherent research project.

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The Importance Of Research Objectives

Imagine you’re a student planning a vacation in a foreign country. You’re on a tight budget and need to draw…

Imagine you’re a student planning a vacation in a foreign country. You’re on a tight budget and need to draw up a pocket-friendly plan. Where do you begin? The first step is to do your research.

Before that, you make a mental list of your objectives—finding reasonably-priced hotels, traveling safely and finding ways of communicating with someone back home. These objectives help you focus sharply during your research and be aware of the finer details of your trip.

More often than not, research is a part of our daily lives. Whether it’s to pick a restaurant for your next birthday dinner or to prepare a presentation at work, good research is the foundation of effective learning. Read on to understand the meaning, importance and examples of research objectives.

Why Do We Need Research?

What are the objectives of research, what goes into a research plan.

Research is a careful and detailed study of a particular problem or concern, using scientific methods. An in-depth analysis of information creates space for generating new questions, concepts and understandings. The main objective of research is to explore the unknown and unlock new possibilities. It’s an essential component of success.

Over the years, businesses have started emphasizing the need for research. You’ve probably noticed organizations hiring research managers and analysts. The primary purpose of business research is to determine the goals and opportunities of an organization. It’s critical in making business decisions and appropriately allocating available resources.

Here are a few benefits of research that’ll explain why it is a vital aspect of our professional lives:

Expands Your Knowledge Base

One of the greatest benefits of research is to learn and gain a deeper understanding. The deeper you dig into a topic, the more well-versed you are. Furthermore, research has the power to help you build on any personal experience you have on the subject.

Keeps You Up To Date

Research encourages you to discover the most recent information available. Updated information prevents you from falling behind and helps you present accurate information. You’re better equipped to develop ideas or talk about a topic when you’re armed with the latest inputs.

Builds Your Credibility

Research provides you with a good foundation upon which you can develop your thoughts and ideas. People take you more seriously when your suggestions are backed by research. You can speak with greater confidence because you know that the information is accurate.

Sparks Connections

Take any leading nonprofit organization, you’ll see how they have a strong research arm supported by real-life stories. Research also becomes the base upon which real-life connections and impact can be made. It even helps you communicate better with others and conveys why you’re pursuing something.

Encourages Curiosity

As we’ve already established, research is mostly about using existing information to create new ideas and opinions. In the process, it sparks curiosity as you’re encouraged to explore and gain deeper insights into a subject. Curiosity leads to higher levels of positivity and lower levels of anxiety.

Well-defined objectives of research are an essential component of successful research engagement. If you want to drive all aspects of your research methodology such as data collection, design, analysis and recommendation, you need to lay down the objectives of research methodology. In other words, the objectives of research should address the underlying purpose of investigation and analysis. It should outline the steps you’d take to achieve desirable outcomes. Research objectives help you stay focused and adjust your expectations as you progress.

The objectives of research should be closely related to the problem statement, giving way to specific and achievable goals. Here are the four types of research objectives for you to explore:

General Objective

Also known as secondary objectives, general objectives provide a detailed view of the aim of a study. In other words, you get a general overview of what you want to achieve by the end of your study. For example, if you want to study an organization’s contribution to environmental sustainability, your general objective could be: a study of sustainable practices and the use of renewable energy by the organization.

Specific Objectives

Specific objectives define the primary aim of the study. Typically, general objectives provide the foundation for identifying specific objectives. In other words, when general objectives are broken down into smaller and logically connected objectives, they’re known as specific objectives. They help define the who, what, why, when and how aspects of your project. Once you identify the main objective of research, it’s easier to develop and pursue a plan of action.

Let’s take the example of ‘a study of an organization’s contribution to environmental sustainability’ again. The specific objectives will look like this:

To determine through history how the organization has changed its practices and adopted new solutions

To assess how the new practices, technology and strategies will contribute to the overall effectiveness

Once you’ve identified the objectives of research, it’s time to organize your thoughts and streamline your research goals. Here are a few effective tips to develop a powerful research plan and improve your business performance.

Set SMART Goals

Your research objectives should be SMART—Specific, Measurable, Achievable, Realistic and Time-constrained. When you focus on utilizing available resources and setting realistic timeframes and milestones, it’s easier to prioritize objectives. Continuously track your progress and check whether you need to revise your expectations or targets. This way, you’re in greater control over the process.

Create A Plan

Create a plan that’ll help you select appropriate methods to collect accurate information. A well-structured plan allows you to use logical and creative approaches towards problem-solving. The complexity of information and your skills are bound to influence your plan, which is why you need to make room for flexibility. The availability of resources will also play a big role in influencing your decisions.

Collect And Collate

After you’ve created a plan for the research process, make a list of the data you’re going to collect and the methods you’ll use. Not only will it help make sense of your insights but also keep track of your approach. The information you collect should be:

Logical, rigorous and objective

Can be reproduced by other people working on the same subject

Free of errors and highlighting necessary details

Current and updated

Includes everything required to support your argument/suggestions

Analyze And Keep Ready

Data analysis is the most crucial part of the process and there are many ways in which the information can be utilized. Four types of data analysis are often seen in a professional environment. While they may be divided into separate categories, they’re linked to each other.

Descriptive Analysis:

The most commonly used data analysis, descriptive analysis simply summarizes past data. For example, Key Performance Indicators (KPIs) use descriptive analysis. It establishes certain benchmarks after studying how someone has been performing in the past.

Diagnostic Analysis:

The next step is to identify why something happened. Diagnostic analysis uses the information gathered through descriptive analysis and helps find the underlying causes of an outcome. For example, if a marketing initiative was successful, you deep-dive into the strategies that worked.

Predictive Analysis:

It attempts to answer ‘what’s likely to happen’. Predictive analysis makes use of past data to predict future outcomes. However, the accuracy of predictions depends on the quality of the data provided. Risk assessment is an ideal example of using predictive analysis.

Prescriptive Analysis: 

The most sought-after type of data analysis, prescriptive analysis combines the insights of all of the previous analyses. It’s a huge organizational commitment as it requires plenty of effort and resources. A great example of prescriptive analysis is Artificial Intelligence (AI), which consumes large amounts of data. You need to be prepared to commit to this type of analysis.

Review And Interpret

Once you’ve collected and collated your data, it’s time to review it and draw accurate conclusions. Here are a few ways to improve the review process:

Identify the fundamental issues, opportunities and problems and make note of recurring trends if any

Make a list of your insights and check which is the most or the least common. In short, keep track of the frequency of each insight

Conduct a SWOT analysis and identify the strengths, weaknesses, opportunities and threats

Write down your conclusions and recommendations of the research

When we think about research, we often associate it with academicians and students. but the truth is research is for everybody who is willing to learn and enhance their knowledge. If you want to master the art of strategically upgrading your knowledge, Harappa Education’s Learning Expertly course has all the answers. Not only will it help you look at things from a fresh perspective but also show you how to acquire new information with greater efficiency. The Growth Mindset framework will teach you how to believe in your abilities to grow and improve. The Learning Transfer framework will help you apply your learnings from one context to another. Begin the journey of tactful learning and self-improvement today!

Explore Harappa Diaries to learn more about topics related to the THINK Habit such as  Learning From Experience ,  Critical Thinking  & What is  Brainstorming  to think clearly and rationally.

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• Knowledge Base

Methodology

Research Methods | Definitions, Types, Examples

Research methods are specific procedures for collecting and analyzing data. Developing your research methods is an integral part of your research design . When planning your methods, there are two key decisions you will make.

First, decide how you will collect data . Your methods depend on what type of data you need to answer your research question :

• Qualitative vs. quantitative : Will your data take the form of words or numbers?
• Primary vs. secondary : Will you collect original data yourself, or will you use data that has already been collected by someone else?
• Descriptive vs. experimental : Will you take measurements of something as it is, or will you perform an experiment?

Second, decide how you will analyze the data .

• For quantitative data, you can use statistical analysis methods to test relationships between variables.
• For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.

Table of contents

Methods for collecting data, examples of data collection methods, methods for analyzing data, examples of data analysis methods, other interesting articles, frequently asked questions about research methods.

Data is the information that you collect for the purposes of answering your research question . The type of data you need depends on the aims of your research.

Qualitative vs. quantitative data

Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.

For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data .

If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing , collect quantitative data .

You can also take a mixed methods approach , where you use both qualitative and quantitative research methods.

Primary vs. secondary research

Primary research is any original data that you collect yourself for the purposes of answering your research question (e.g. through surveys , observations and experiments ). Secondary research is data that has already been collected by other researchers (e.g. in a government census or previous scientific studies).

If you are exploring a novel research question, you’ll probably need to collect primary data . But if you want to synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

Descriptive vs. experimental data

In descriptive research , you collect data about your study subject without intervening. The validity of your research will depend on your sampling method .

In experimental research , you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design .

To conduct an experiment, you need to be able to vary your independent variable , precisely measure your dependent variable, and control for confounding variables . If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.

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Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.

Qualitative analysis methods

Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that was collected:

• From open-ended surveys and interviews , literature reviews , case studies , ethnographies , and other sources that use text rather than numbers.
• Using non-probability sampling methods .

Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions and be careful to avoid research bias .

Quantitative analysis methods

Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).

You can use quantitative analysis to interpret data that was collected either:

• During an experiment .
• Using probability sampling methods .

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

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If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square test of independence
• Statistical power
• Descriptive statistics
• Degrees of freedom
• Pearson correlation
• Null hypothesis
• Double-blind study
• Case-control study
• Research ethics
• Data collection
• Hypothesis testing
• Structured interviews

Research bias

• Hawthorne effect
• Unconscious bias
• Recall bias
• Halo effect
• Self-serving bias
• Information bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
• If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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Handy Tips To Write A Clear Research Objectives With Examples

Introduction.

Research objectives play a crucial role in any research study. They provide a clear direction and purpose for the research, guiding the researcher in their investigation. Understanding research objectives is essential for conducting a successful study and achieving meaningful results.

In this comprehensive review, we will delve into the definition of research objectives, exploring their characteristics, types, and examples. We will also discuss the relationship between research objectives and research questions, as well as provide insights into how to write effective research objectives. Additionally, we will examine the role of research objectives in research methodology and highlight the importance of them in a study. By the end of this review, you will have a comprehensive understanding of research objectives and their significance in the research process.

Definition of Research Objectives: What Are They?

A research objective is defined as a clear and concise statement that outlines the specific goals and aims of a research study. These objectives are designed to be specific, measurable, achievable, relevant, and time-bound (SMART), ensuring they provide a structured pathway to accomplishing the intended outcomes of the project. Each objective serves as a foundational element that summarizes the purpose of your study, guiding the research activities and helping to measure progress toward the study’s goals. Additionally, research objectives are integral components of the research framework , establishing a clear direction that aligns with the overall research questions and hypotheses. This alignment helps to ensure that the study remains focused and relevant, facilitating the systematic collection, analysis, and interpretation of data.

Characteristics of Effective Research Objectives

Characteristics of research objectives include:

• Specific: Research objectives should be clear about the what, why, when, and how of the study.
• Measurable: Research objectives should identify the main variables of the study that can be measured or observed.
• Relevant: Research objectives should be relevant to the research topic and contribute to the overall understanding of the subject.
• Feasible: Research objectives should be achievable within the constraints of time, resources, and expertise available.
• Logical: Research objectives should follow a logical sequence and build upon each other to achieve the overall research goal.
• Observable: Research objectives should be observable or measurable in order to assess the progress and success of the research project.
• Unambiguous: Research objectives should be clear and unambiguous, leaving no room for interpretation or confusion.
• Measurable: Research objectives should be measurable, allowing for the collection of data and analysis of results.

By incorporating these characteristics into research objectives, researchers can ensure that their study is focused, achievable, and contributes to the body of knowledge in their field.

Types of Research Objectives

Research objective can be broadly classified into general and specific objectives. General objectives are broad statements that define the overall purpose of the research. They provide a broad direction for the study and help in setting the context. Specific objectives, on the other hand, are detailed objectives that describe what will be researched during the study. They are more focused and provide specific outcomes that the researcher aims to achieve. Specific objectives are derived from the general objectives and help in breaking down the research into smaller, manageable parts. The specific objectives should be clear, measurable, and achievable. They should be designed in a way that allows the researcher to answer the research questions and address the research problem.

In addition to general and specific objectives, research objective can also be categorized as descriptive or analytical objectives. Descriptive objectives focus on describing the characteristics or phenomena of a particular subject or population. They involve surveys, observations, and data collection to provide a detailed understanding of the subject. Analytical objectives, on the other hand, aim to analyze the relationships between variables or factors. They involve data analysis and interpretation to gain insights and draw conclusions.

Both descriptive and analytical objectives are important in research as they serve different purposes and contribute to a comprehensive understanding of the research topic.

Examples of Research Objectives

Here are some examples of research objectives in different fields:

1. Objective: To identify key characteristics and styles of Renaissance art.

This objective focuses on exploring the characteristics and styles of art during the Renaissance period. The research may involve analyzing various artworks, studying historical documents, and interviewing experts in the field.

2. Objective: To analyze modern art trends and their impact on society.

This objective aims to examine the current trends in modern art and understand how they influence society. The research may involve analyzing artworks, conducting surveys or interviews with artists and art enthusiasts, and studying the social and cultural implications of modern art.

3. Objective: To investigate the effects of exercise on mental health.

This objective focuses on studying the relationship between exercise and mental health. The research may involve conducting experiments or surveys to assess the impact of exercise on factors such as stress, anxiety, and depression.

4. Objective: To explore the factors influencing consumer purchasing decisions in the fashion industry.

This objective aims to understand the various factors that influence consumers’ purchasing decisions in the fashion industry. The research may involve conducting surveys, analyzing consumer behavior data, and studying the impact of marketing strategies on consumer choices.

5. Objective: To examine the effectiveness of a new drug in treating a specific medical condition.

This objective focuses on evaluating the effectiveness of a newly developed drug in treating a particular medical condition. The research may involve conducting clinical trials, analyzing patient data, and comparing the outcomes of the new drug with existing treatment options.

These examples demonstrate the diversity of research objectives across different disciplines. Each objective is specific, measurable, and achievable, providing a clear direction for the research study.

Aligning Research Objectives with Research Questions

Research objectives and research questions are essential components of a research project. Research objective describe what you intend your research project to accomplish. They summarize the approach and purpose of the project and provide a clear direction for the research. Research questions, on the other hand, are the starting point of any good research. They guide the overall direction of the research and help identify and focus on the research gaps .

The main difference between research questions and objectives is their form. Research questions are stated in a question form, while objectives are specific, measurable, and achievable goals that you aim to accomplish within a specified timeframe. Research questions are broad statements that provide a roadmap for the research, while objectives break down the research aim into smaller, actionable steps.

Research objectives and research questions work together to form the ‘golden thread’ of a research project. The research aim specifies what the study will answer, while the objectives and questions specify how the study will answer it. They provide a clear focus and scope for the research project, helping researchers stay on track and ensure that their study is meaningful and relevant.

When writing research objectives and questions, it is important to be clear, concise, and specific. Each objective or question should address a specific aspect of the research and contribute to the overall goal of the study. They should also be measurable, meaning that their achievement can be assessed and evaluated. Additionally, research objectives and questions should be achievable within the given timeframe and resources of the research project. By clearly defining the objectives and questions, researchers can effectively plan and execute their research, leading to valuable insights and contributions to the field.

Guidelines for Writing Clear Research Objectives

Writing research objective is a crucial step in any research project. The objectives provide a clear direction and purpose for the study, guiding the researcher in their data collection and analysis. Here are some tips on how to write effective research objective:

1. Be clear and specific

Research objective should be written in a clear and specific manner. Avoid vague or ambiguous language that can lead to confusion. Clearly state what you intend to achieve through your research.

2. Use action verbs

Start your research objective with action verbs that describe the desired outcome. Action verbs such as ‘investigate’, ‘analyze’, ‘compare’, ‘evaluate’, or ‘identify’ help to convey the purpose of the study.

3. Align with research questions or hypotheses

Ensure that your research objectives are aligned with your research questions or hypotheses. The objectives should address the main goals of your study and provide a framework for answering your research questions or testing your hypotheses.

4. Be realistic and achievable

Set research objectives that are realistic and achievable within the scope of your study. Consider the available resources, time constraints, and feasibility of your objectives. Unrealistic objectives can lead to frustration and hinder the progress of your research.

5. Consider the significance and relevance

Reflect on the significance and relevance of your research objectives. How will achieving these objectives contribute to the existing knowledge or address a gap in the literature? Ensure that your objectives have a clear purpose and value.

6. Seek feedback

It is beneficial to seek feedback on your research objectives from colleagues, mentors, or experts in your field. They can provide valuable insights and suggestions for improving the clarity and effectiveness of your objectives.

7. Revise and refine

Research objectives are not set in stone. As you progress in your research, you may need to revise and refine your objectives to align with new findings or changes in the research context. Regularly review and update your objectives to ensure they remain relevant and focused.

By following these tips, you can write research objectives that are clear, focused, and aligned with your research goals. Well-defined objectives will guide your research process and help you achieve meaningful outcomes.

The Role of Research Objectives in Research Methodology

Research objectives play a crucial role in the research methodology . In research methodology, research objectives are formulated based on the research questions or problem statement. These objectives help in defining the scope and focus of the study, ensuring that the research is conducted in a systematic and organized manner.

The research objectives in research methodology act as a roadmap for the research project. They help in identifying the key variables to be studied, determining the research design and methodology, and selecting the appropriate data collection methods .

Furthermore, research objectives in research methodology assist in evaluating the success of the study. By setting clear objectives, researchers can assess whether the desired outcomes have been achieved and determine the effectiveness of the research methods employed. It is important to note that research objectives in research methodology should be aligned with the overall research aim. They should address the specific aspects or components of the research aim and provide a framework for achieving the desired outcomes.

Understanding The Dynamic of Research Objectives in Your Study

The research objectives of a study play a crucial role in guiding the research process, ensuring that the study is focused, purposeful, and contributes to the advancement of knowledge in the field. It is important to note that the research objectives may evolve or change as the study progresses. As new information is gathered and analyzed, the researcher may need to revise the objectives to ensure that they remain relevant and achievable.

In summary, research objectives are essential components in writing an effective research paper . They provide a roadmap for the research process, guiding the researcher in their investigation and helping to ensure that the study is purposeful and meaningful. By understanding and effectively utilizing research objectives, researchers can enhance the quality and impact of their research endeavors.

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Research Objective and Methodology

• First Online: 18 September 2020

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• Gabriele Baratto 2  

Part of the book series: SpringerBriefs in Criminology ((BRIEFSCRIMINOL))

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The chapter illustrates both the objective and the methodology of the research presented in the book. Possible evaluation research designs are reviewed, highlighting their strengths and weaknesses and analysing which one is the more suitable for the purposes of the present research – i.e. a natural experiment with one group(s) post-test only design, using a non-equivalent qualitative pre-test. Then, strategies for data gathering and analysis are presented. In more detail, the methodology used consisted of systematic keyword searches on the three mayor social media platforms – i.e. Twitter, Facebook, and Instagram – after the implementation of the SCP measures in order to identify and analyse contents linked to the illegal online trade of medicines. The keyword list comprises 76 terms of two different types: 36 names of medicines, both generic and branded names, and 8 general terms in 5 languages – i.e. 40 keywords overall – referring to disease or condition and the medicines that are intended to treat them, or their therapeutic category. In order to assess the impact of the SCP interventions, data was analysed ‘vertically’ (i.e. by social media and by therapeutic category) and ‘horizontally’ (i.e. across social media and therapeutic category). Results (presented in Chap. 5 ) were compared to the situation existing before the implementation of the measures by using six qualitative indicators.

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The last five keywords included a list of different medicines mainly used to treat serious diseases, i.e. (a) expensive medicines to treat hepatitis C (Sovaldi and Harvoni); (b) a medicine to treat infertility in women (Clomid); (c) a medicine to treat breast cancer (Nolvadex); and (d) a medicine to treat alcoholism (Disulfiram).

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Baratto, G. (2020). Research Objective and Methodology. In: The Illegal Trade of Medicines on Social Media. SpringerBriefs in Criminology. Springer, Cham. https://doi.org/10.1007/978-3-030-57582-3_4

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Public dialogue on the use of data by the public sector in Scotland

This report presents the findings from a public dialogue on the use of data in Scotland commissioned by the Scottish Government to explore the ethics of data-led projects. The purpose of the panel was to inform approaches to data use by the Scottish Government and public sector agencies in Scotland.

Introduction

The Scottish Government has stated a commitment to using data and digital technologies in an ethical way for the benefit of the people of Scotland. [5]

During the pandemic the Data and Intelligence Network ( DIN ) was set up by the Scottish Government as a dedicated team, providing additional capabilities to ensure that data were utilised effectively and ethically to address key challenges relating to COVID -19. The DIN operated from within the Scottish Government, providing skills and expertise to a wide range of organisations across Scotland’s public sector and providing support with their data-led projects at the height of the COVID -19 pandemic. The projects that the DIN advised on presented ethical dilemmas in how to reconcile the privacy, rights and freedoms of people in Scotland with rapid, proactive, and responsible use of information. The need for urgent and decisive action during the COVID -19 pandemic meant that data-led projects were fast-tracked to implementation, and the opportunities for consideration of public views on the social and ethical implications of the data use were limited.

In an increasingly data driven world, good governance is required to ensure public data are used effectively, ethically and appropriately. Engaging the public – those whose data is used in research, planning and service development and delivery – helps to develop trustworthy and robust frameworks for how government and other agencies collect, analyse and use data. Public engagement can take many forms and have multiple purposes, but an overriding aim is to promote better policy and decision making, often through deliberative engagement. [6]

The Scottish Government, together with Research Data Scotland ( RDS ), decided to build on the work done by the DIN which had started to expose some of the ethical challenges of data-led projects. The Scottish Government and RDS agreed to convene a public panel to explore the ethics of past data-led projects supported by the DIN , and possible future projects to inform approaches to data use by the Scottish Government and public sector agencies in Scotland.

Research objectives

The aim of this public panel was to explore perceptions and understanding of public sector data-led projects in order to produce a set of ethical guidelines that the Scottish Government and public sector organisations should follow when using data about citizens. The key research objectives of the panel itself were to explore:

• Public perception and understanding of public sector data-led projects (involving different types of data including anonymised or identifiable records from NHS health data, census data, education data, housing data, and location data).
• Levels of public trust in different methodologies to ensure privacy of individuals’ data.

Broader objectives of the project were to:

• Drive an increase in the amount of public engagement on data use taking place across the public sector by introducing and involving a range members from the DIN Network in the design and delivery of the project. [7]
• Create a blueprint for a long-term, sustainable forum for engaging and involving the public in data policy, scrutiny and decisions.

The public dialogue reported here builds on previous public engagements in Scotland on the use of data (key insights from which are summarised in appendix A). [8]

Methodology

Ipsos, along with its partners at the University of Edinburgh, designed and facilitated a public panel that was funded and guided by the Scottish Government and UK Research and Innovation’s Sciencewise programme, an internationally recognised public engagement programme which enables policy makers to develop socially informed policy. The specific methodology used with the public panel is known as a “public dialogue”. [9] Public dialogue is a process during which members of the public interact with scientists, stakeholders and policy makers to deliberate on issues relevant to future policy and research decisions.

The panel brought together a group of 25 people from across Scotland to learn about the topic of data use by the Scottish Government and public sector agencies. The panel met over six three-hour online workshops [10] between September and December 2022 to answer the following key question:

What guidelines should the public sector follow when using citizens’ data?

Over the course of the public dialogue, participants reviewed different data-led projects that the DIN had been involved in previously or were considering involvement in. The panel listened to presentations from experts, learned about the issues, discussed them, and then drew conclusions together to form a set of ethical guidelines which are presented in this report.

Further details about the process (including an overview of each session with dates, times, content and specialists) can be found in appendix D but the overarching design of the dialogue is summarised in figure 1.2 below.

Alongside the online meetings, an online community helped support ongoing engagement with panellists, facilitating continued discussion and reflection.

An oversight group – comprising Scottish Government representatives, Research Data Scotland representatives, and independent experts from academia and civil society – met regularly to advise on the methodology. The oversight group provided checks and challenges over the course of the project to ensure the design of the panel was appropriate, relevant and robust. A list of oversight group members and meeting times is detailed in appendix B.

Sampling and recruitment

Participants were recruited using a civic lottery approach, [11] which involves inviting a random selection of households to participate. They were recruited to be broadly reflective of the Scottish population in terms of age, gender, region, ethnicity, disability and education. Ethnic minority groups were over-sampled to ensure sufficient representation of these groups. An attitudinal measure was also included in the selection process to ensure a range of views were represented in terms of trust in the Scottish Government and public sector agencies to use data for the public good. The recruitment process is outlined in more detail in appendix C.

Overall, 30 people were selected to join the panel and 25 participated throughout. A table summarising the demographic profile of the final selected and confirmed sample can be found in appendix C.

To support and enable participation in all workshops, participants were each paid £400 for joining the online sessions and online community. Where necessary, participants were provided with equipment, such as headsets, laptops or internet dongles and were supported with training on how to use the technology and access the meeting platform.

Materials and input from specialists

Discussion guides and stimulus materials were developed by Ipsos and reviewed by the Scottish Government, Sciencewise and the oversight group. A range of specialists joined at different points in the dialogue to provide information that would be useful for participants’ learning and deliberation. In the first session, specialists included academics and professionals who explained key concepts to support participants’ discussions (including the role of the DIN , the legal context of data use and an introduction to data ethics). In the following sessions, those involved in the data-led projects being reviewed by the panel provided overviews of these, while academics and representatives from independent research institutes provided alternative perspectives on the projects to help participants consider different views on the use of data about citizens.

Presentations were either delivered live or recorded in advance and played live during the sessions. Some specialists presented in plenary and then stayed to answer questions that arose during breakout discussions. Others presented in smaller groups, remaining in the groups afterwards to take questions directly from participants. Any questions that were not answered during the live sessions were compiled in a Question and Answer (Q&A) document (see appendix E).

Interpretation of qualitative data

The guidelines set out and discussed in this report are intended for consideration in the possible future use of data about citizens by the public sector.

This report synthesises the diverse expressions of participants to draw out major themes of discussions and to draw attention to the way that the panel – individually and collectively – made sense of a complex topic, describing what mattered to them and why. On occasion, the report refers to verbatim assertions by participants and their understanding of the issues. These are not intended as authoritative statements of fact, but they tell us something important about how the issues can be perceived and understood by members of the public.

A robust and systematic analysis approach was used, with conclusions based on groups that are reflective of the diversity of the wider public. The deliberative nature of the project allowed for ongoing analysis throughout fieldwork, which ensured that emerging principles and themes - both from workshop discussions and online community activities - could be played back to participants as the dialogue progressed. Analysis does not seek to quantify findings nor does it indicate statistical significance from a representative sample. A more detailed summary of the analytical approach to the dialogue can be found in appendix D.

This report offers a constructive insight into public perspectives on the key questions posed to them after receiving and deliberating on essential information relevant to the questions.

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• Open access
• Published: 19 August 2024

Radiology education for medical students: a qualitative exploration of educational topics, teaching methods and future strategies

• Frederike S. Harthoorn 1 , 2 ,
• Sascha W. J. Scharenborg 1 , 2 ,
• Monique Brink 2 ,
• Liesbeth Peters-Bax 2 &
• Dylan Henssen 2  

BMC Medical Education volume  24 , Article number:  891 ( 2024 ) Cite this article

Metrics details

Imaging techniques play a central role in modern medicine and therefore it would be beneficial for all medical students to incorporate radiology education in medical school curricula. However, a formal undergraduate radiology curriculum with well-defined learning objectives remains lacking in The Netherlands. This study aims to qualitatively ascertain opinions from clinicians (radiologists and non-radiologists) with regard to radiology education in the medical school curricula, including topics, teaching methods and strategies.

A qualitative study with in-depth semi-structured interviews was conducted. Inclusion was carried out until saturation was achieved, after which 2 additional interviews were held. Interviews were conducted using open-ended questions, following a predefined topic list. The constant comparative method was applied in order to include new questions when unexpected topics arose during the interviews. All interviews were transcribed verbatim and coded using a thematic analysis approach. Codes were organized into categories and themes by discussion between the researchers.

Forty-four clinicians were interviewed (8 radiologists, 36 non-radiologists). The three main themes that were derived from the interviews were: (1) expectations of indispensable knowledge and skills on radiology, (2) organization of radiology education within the medical curriculum and (3) promising educational innovations for the radiology curriculum. The qualitative study design provides more in-depth knowledge on clinicians’ views on educational topics.

Conclusions

The themes and statements of this study provided new insights into educational methods, timing of radiology education and new topics to teach. More research is needed to gain consensus on these subjects and inclusion of the opinion of medical students with regard to radiology education is needed.

• Radiology education in medical curricula was considered important by all interviewees

• Integrating radiology and anatomy in Longitudinal learning communities (LLC’s) could be a promising educational strategy

• Integration of ultrasound education in medical curricula should be investigated further

Peer Review reports

Imaging technologies play a central role in the practice of modern medicine. Therefore, it is not surprising that previous studies suggest that all medical students would benefit from (basic) knowledge concerning medical imaging technologies and radiology [ 24 , 37 , 63 ]. However, radiology education is not well integrated in the medical curricula [ 21 , 25 , 29 , 37 ] and students’ lacking knowledge can be potentially dangerous [ 19 , 63 ]. In turn, medical students (including interns) and residents reported a lack of confidence when interpreting radiology examinations, including (chest) radiographs [ 19 , 48 ]. Moreover, lacking radiological knowledge was found to be correlated with an overutilization of medical imaging services [ 27 ], leading to increased societal healthcare-related expenses. Consequently, a need for radiology education in medical schools is recognized among teachers, medical students and curriculum designers [ 1 , 29 , 37 , 42 , 44 , 47 , 48 , 52 , 61 ]. Albeit, the learning objectives of such a radiology curriculum remains a topic of debate [ 61 ]. Therefore, proper identification of useful learning objectives for radiology education in medical curricula should be carried out [ 23 , 54 , 60 , 61 ]. The first step of defining learning objectives is to determine which educational topics are important to teach [ 26 , 34 , 60 , 5 ].

When defining these, it is important to identify the opinions of both clinicians (radiologists and non-radiologists) and medical students since both groups influence which topics are considered important to teach during medical school [ 39 ]. Opinions on this topic diverse, due to the fast technological developments in this broad field, which covers nearly every medical discipline for diagnostic and therapeutic purposes [ 23 , 34 , 63 ]. Several studies have previously aimed to determine radiology curriculum topics by questioning different groups of physicians (both radiologists and non-radiologists) and educational experts using questionnaires [ 32 , 36 , 48 , 53 , 53 , 54 , 55 , 55 , 61 ]. Overall, these studies provided lists of interpretative and non-interpretative skills that respondents agreed on what should be taught in medical school regarding radiology. The most commonly mentioned interpretative skill concerned the systematic approach of reading chest radiographs [ 32 , 36 , 48 , 53 , 53 , 54 , 55 , 55 ]. Suggested non-interpretative skills were more diverse and included (a) the basic physical mechanisms of ionizing radiation, including knowledge on radiation risks [ 32 , 36 , 53 , 53 , 54 , 55 , 55 , 61 ], (b) the principles of justification of procedures (e.g., knowing when to use intravenous contrast agents) [ 32 , 36 , 48 , 53 , 53 , 54 , 55 , 55 , 61 ], and comprehension of the role, indications and limitations of diagnostic imaging (and interventional) techniques [ 32 , 36 , 48 , 53 , 53 , 54 , 55 , 55 , 61 ].

Nevertheless, the aforementioned studies used a survey-based approach in which rather pre-determined information is collected from a large group of participants [ 32 , 36 , 48 , 53 , 53 , 54 , 55 , 55 ]. This study aimed to build on this work by employing an inductive, qualitative approach, allowing for the opportunity to acquire participants’ opinions without any influence of preset questions and to explore these answers to gain more detailed information on a broad range of topics [ 22 , 58 ]. Therefore, it is possible to gain a more accurate insight into the wide diversity of current ideas on education on imaging technology that are continuously changing. Limitations of qualitative research, on the other hand, concern the labor-intensive nature of such studies, which explains why in most fields, qualitative data are lacking. Also, qualitative data are more subjective than quantitative data as the interviewee has more control over the content of the data. Therefore, unnecessary quantification of qualitative data should be avoided as it falsely suggests objective, statistically proven results [ 10 , 38 ].

Consequently, there is a recognized need for enhanced radiology education in medical schools among teachers, students, and curriculum designers. This study aimed to 1) Identify key topics that should be included in a radiology curriculum, 2) Determine effective teaching methods for radiology education and 3) Propose strategies for integrating radiology education into existing medical school curricula. Therefore, we qualitatively investigated the perspectives of clinicians (both radiologists and non-radiologists) on radiology education in medical curricula.

An exploratory inductive qualitative study focusing on the role of radiology education in medical curricula was performed. A pragmatic qualitative approach was used with the aim to identify topics in radiology education that clinicians considered important to embed in the medical curriculum. A sample of clinicians involved in medical education in the Netherlands was asked to provide their insights using in-depth semi-structured interviews. Interviews were performed following an inductive iterative process using the constant comparative method [ 31 ]. This implies that if new topics arose during interviews, it was possible to explore these topics and thereby allowing new topics to be added to the interview guide during the experiment. The interview guide is provided in Table  1 . After interviewing, a thematic approach was used to analyze the data.

Relevant scientific literature was reviewed on learning objectives and teaching methods in radiology education in medical school. After reviewing the available literature, two researchers (F.H. en D.H.) constructed a topic list. An inductive iterative interviewing process was carried out using the constant comparative method [ 51 ]. Therefore, new topics could be added to the topic list during the interviews.

Participants

A list of eligible clinicians was constructed by reviewing hospitals and general practitioners within the training region of the university medical center in the east of The Netherlands (OpleidingsRegio Oost-Nederland). The contact person of each practice or department that provided a mandatory internship within the medical curriculum or an elective internship in radiology was contacted by e-mail in order to recruit eligible clinicians. Only clinical specialties embedding radiological imaging in their daily clinical practice were deemed eligible. Therefore, clinicians of the department of psychiatry, dermatology and ophthalmology were excluded from this study. The remaining clinicians were eligible if they participated in any medical curriculum in the Netherlands, regardless of being involved in the Bachelor’s or Master’s phase. Additionally, clinicians needed to be board-certified and actively working medical specialists, general practitioners or residents in radiology. Moreover, board-certified radiologists of the same training region who were involved in (any) medical curriculum in the Netherlands were included to provide more insight into what these “imaging experts” considered important to teach. Eligible clinicians were contacted by use of e-mail. After no initial response, the eligible clinicians were contacted again two weeks later. A third reminder was sent after a longer period of time, which varied from two weeks to three months. If no response was received, the participant was excluded from further inclusion.

Ethical statement

This study was approved by the ethics committee of the Netherlands Association of Medical Education (NVMO, case number 2023.2.9). Before being interviewed, clinicians confirmed to participate in the study. Informed consent was obtained from all clinicians prior to the interview in which the clinicians consented to have the interview audio-recorded for further analyses. Moreover, all methods were carried out in accordance with relevant guidelines and regulations. All recorded data was stored on a secured disc, to which only one researcher (F.H.) had access. Transcribed data was stored and analyzed anonymously.

Individual semi-structured interviews were conducted by one of the researchers (F.H.). Clinicians decided in which way the interviews were held: in person, via electronic telecommunication software (i.e. Skype version 8.65.0.78; Skype Technologies, Luxembourg City, Luxembourg Palo Alto, CA, United States) or by telephone. In addition, four clinicians provided extensive answers to interview questions via e-mail. These data were also used in the data analysis. The interviews started with a short introduction of the research content followed by an open question on the participant’s thoughts on this matter. During the interviews, the interviewer used open-ended questions and encouraged the clinicians to speak openly and express their opinions, thoughts and considerations. The interviewer explained that there were no relations with the board of examiners, the university medical center educational board or the educational management team. In order to ensure reliable data, all interviews were audio-recorded and transcribed verbatim afterwards. Each transcript was thereafter analyzed using direct content analysis [ 30 ]. Starting after the first interview had taken place; transcriptions were coded line-by-line, through which a code list was created. Coding was continued after each interview. Inclusion of new participants was halted when no new topics and codes arose from this process, indicating that data saturation occurred. To confirm data saturation, two additional interviews were held. When confirmed, inclusion of new participants was stopped.

Data analysis

The interview transcripts were analyzed qualitatively. The first four transcripts were independently analyzed by two researchers (F.H. and B.v.W.). Coding results were compared and discrepancies were resolved by discussion. If necessary, a third more experienced investigator (D.H.) could be asked to help resolve issues. Since there were no major discrepancies, further coding and analysis were carried out independently by one of the researchers (F.H.), who met periodically with one of the other researchers (D.H.) to discuss codes and themes until consensus was reached. The coding process was performed using Atlas.ti software, version 8.2.29.0 (ATLAS.ti Scientific Software Development GmbH, Berlin, Germany). The constructed codebook was organized into categories and themes which arose after discussion of all the different codes between two of the researchers (F.H. and D.H.). Categories were used to group codes, which were then grouped into several themes. The categories and themes were shared with the other researchers in order to assess their validity.

A total of 97 eligible clinicians (radiologists; 10.3% and non-radiologists; 89.7%) were contacted by one of the researchers (F.H.) via e-mail between July and October 2020 (Table  2 ). Non-responders were excluded after a period of six months after the first e-mail was sent ( n  = 44). Clinicians were also excluded if they expressed to have no active involvement in medical curricula ( n  = 3) (Fig.  1 ). Of the included clinicians, four reactions were received via e-mail, while the other forty respondents provided their input by participating in an interview. The interviews lasted between 17 and 59 min. Participant characteristics are displayed in Table  2 .

Selection of the clinicians. 1 Six clinicians were not available due to lack of time . 2 Three contacted clinicians were excluded since they no longer worked for the specific training region

Ten categories of items were distilled from the transcribed codes, which were arranged in the following three themes (Fig.  2 ).

An overview of the subcategorized themes. Three themes accompanied by ten categories were derived from the interviews during the analysis after qualitative exploration of the opinions of clinicians and general practicioners on imaging technologies in medical school curricula

Theme 1: Expectations with regard to educational topics in radiology education

Anatomical knowledge.

Interviewees advocated that students need to be able to identify important anatomical landmarks and gross anatomical structures on the different radiologic imaging techniques. Knowledge of anatomy was believed to be the foundation of understanding a radiologic image by both radiologists and non-radiologists.

“It starts with that [knowledge of the human anatomy], as this forms the foundation of radiology. Then, you can also start interpreting medical images” – General Practitioner

“… but I sense that there is little attention for forming an idea on the anatomical relations. And in the end, that is the essence…” – Surgeon

Conversely, Computed Tomography scans (CT-scans) and Ultrasound (US) were suggested as ideal tools to teach anatomy in medical school. This was believed to benefit both anatomy education and radiology education. This combination provides clinical significance to anatomical structures as well as a three-dimensional insight into the anatomy. Furthermore, it would lead to early exposure to medical imaging in the curriculum. Magnetic Resonance Imaging scans (MRI-scans) were both suggested and dissuaded as a teaching tool because of their complexity.

Skills in interpretation

Interviews with both radiologists and non-radiologists revealed that the ability to interpret a wide range of radiological studies should not be included as a learning objective in medical school. Learning to interpret specific radiological studies (e.g., CT study of the thorax, brain MRI) should be incorporated in post-academic education for residents in training, as there is a greater exposure to these specific radiological studies during this period. Nevertheless, interviewees stated four things a medical student should be able to do concerning radiographs: (1) distinguish abnormal from normal (recognizing gross abnormalities), (2) identify some very common pathologies (e.g., pulmonary infiltrates, common bone fractures, joint luxation, pulmonary edema, hemorrhage, ischemia and malignancies), (3) identify acute diagnoses (e.g., vertebral fractures and pneumothorax on radiographs) and (4) acquire a systematic approach when reading radiographs (both chest radiographies and musculoskeletal radiographies). The extent to which these skills should be mastered under supervision was scarcely discussed and varied greatly.

Basic technological knowledge

Knowledge on the techniques of the four major different imaging modalities (radiography, CT, MRI and ultrasound) was regarded important as this provides knowledge on (contra-)indications and strengths and weaknesses of each imaging modality. It can also help a student interpret medical images as it helps to understand which structures are visible and why they are displayed in the way they are (e.g., the differences in size while comparing an AP- and PA-radiograph). It could also help students to understand the content of a radiological report (e.g., helping to understand why radiologists discuss patient positioning in their reports).

“You have to know the basics. You can order radiographs, a CT-scan, or an ultrasound or an MRI-scan. And the reason why you would choose one option or another is always different, but you always visualize something with it. I consider it important to know what a specific imaging technique shows you.” – Emergency doctor.

More specifically, it was considered important to have knowledge on the basics of ionization radiation, including its hazardous effects. For MR imaging, knowledge of the basic differences between T1-weighted-, T2-weighted-, and fluid-attenuation inversion recovery (FLAIR) sequences were disclosed as important subjects to master for medical students.

In addition, the impact that a radiological examination has on a patient (both mentally as well as physically) should also be embedded in the medical curriculum. This would also help future healthcare professionals to inform their patients properly in order to achieve well-informed consent.

“...I think that it is good to know because we receive a lot of questions from patients about radiologic studies” – General Practitioner

Comprehension of the role, indications and limitations of diagnostic imaging techniques

The most common (contra-)indications and limitations of the most frequently used modalities are seen as imperative knowledge which a student should acquire in medical school. This includes insights in accuracy rates of different radiological imaging methods and how these rates are influenced by other factors, as well as the costs of the different modalities. It should be noted that some clinicians mentioned that keeping up with the quickly changing indications could be a challenge and another participant did not find knowledge in indication important. All believed that you should always consult a radiologist when in doubt.

The benefits and drawbacks of the use of contrast agents, especially in CT imaging, and its (contra-)indications are worth emphasizing, for it has been mentioned multiple times in the interviews and is apart from one explicit modality.

“I believe that it is very important that you know which radiological examinations are available and what you can use each one of them for. I also believe that it is very important that students are aware of the costs of the different imaging modalities and that they also take this into account when making a decision. And that they realize which study is useful for a specific question” – General Practitioner.

Implications of radiology use in clinical practice

As each medical specialty has some level of experience with certain radiological imaging methods, it is important that students learn which techniques are used in various settings.. This was reported as a learning goal which should be achieved through experience-based learning (i.e., during internships). Also, clinicians expressed that it was paramount that students learn to write a concise though complete request for radiological imaging. In addition, students need to learn to look critically and should learn how to implement the radiologist's conclusion in the clinical setting for further medical management and/or follow-up.

Finally, students should also learn to consult the radiologist when questions arise regarding the most optimal imaging method or the radiological conclusion and how to interpret it.

“Radiological findings are subjected to interpretation: someone sees an abnormality and expects it to be something. And those expectations are supported or undermined by the clinical presentation and you have to either provide this knowledge to the radiologist or have to take this into account yourself”—ENT-specialist.

“I noticed that they [students and junior doctors] have no comprehension of contrast agents and therefore just follow guidelines which state to ‘Check renal function’. They have no idea why and whether they have to order for contrast agents” – Radiologist.

Theme 2: Teaching strategies with regard to radiology education

Timing and emphasizing responsibilities.

Most interviewees were convinced that during the Bachelor’s phase (i.e., the first three years of the university curriculum), imaging technology education needs to focus on the differences between modalities from a technical point of view. During those three years, radiological images should be used to help students understand the technical basis of imaging and recognize anatomical structures. This should gradually evolve into using radiological images to recognize simple pathology at the end of the Bachelor’s phase (e.g., bone fractures, pneumonia, pneumothorax). During the Master’s phase (last three years of university curriculum), the interviewees considered applied radiology as an important learning goal. This education could then be combined with recapitulating the anatomy.

“I think that it should definitely be addressed in the Bachelor’s phase, but that the subjects in radiology that are embedded in an internship should be addressed in more detailed and specific way before that internship. I am actually getting thrilled by that idea”—General practitioner.

It was believed that students will get more familiar with radiology when learning about imaging technologies is combined with anatomy and repeated over the years. Doing this while emphasizing different aspects of radiology during different learning phases of students, was also believed to result in a greater feeling of competence for medical students, especially with regard to chest radiographs and musculoskeletal radiographs. Therefore, radiology education during the Master’s phase of medicine should also focus on basic, structured interpretation of chest radiographs.

Assessment during internships of other disciplines

Interviewees suggested incorporating Entrusted Professional Abilities (EPAs) for radiology in the internships, so that radiology knowledge can be reviewed and improved continuously. Therefore, the knowledge of radiology can be monitored during the internships in the same way the discipline of radiology is integrated through all the different specialisms in medicine.

Theme 3: Promising educational strategies in radiology education

Longitudinal subject planning.

The idea of Longitudinal Learning Communities (LLCs) in radiology was discussed during all interviews. LLCs were defined as a community-based approach to learning during a time period of more than 1 year, encouraging meaningful student interaction and small-group learning as well as peer-group evaluation. LLCs were believed to help students to develop a collaborative approach to clinical practice, particularly in radiology. Clinicians believed that a timely repetition of anatomical and radiological knowledge before an internship would result in an improved learning experience.

Three clinicians, all non-radiologists, did not support more radiology education in already overcrowded medical curricula. One participant explicitly expressed that an LLC in radiology would take up too much time. Other interviewees (both radiologists and non-radiologists), however, considered radiology to be important enough to devote attention to, for example by use of LLCs. One participant also suggested saving time by combining the LLC with anatomy and physiology education throughout the medical curriculum. The learning materials used in such LLCs on radiology education were discussed as well. Suggested teaching methods included e-learnings and interactive workgroups. Additionally, the use of clinical cases during education as a form of applied radiology was expressed by many. Nevertheless, discrepancies remained with regard to the different teaching forms. Proposed forms were interactive teaching forms, clinical cases, lectures, computer orientated education, e-learnings, workshops, self-study, seminars, learning during the internships themselves (via specific educational moments, multidisciplinary meetings, during consulting hours at the outpatient department, radiology meetings, before surgery or via assignments). Clinicians expressed that they found it difficult to decide which educational methods would create the best learning environment for students.

Some additions to the described LLC were mentioned during the interviews. Several clinicians, both radiologists and non-radiologists, suggested adding practical ultrasound education to the LLC’s. One participant highlighted the importance of recapitulation shortly before practical education, also called in-time learning. This person believed that students would benefit more from good references, so they would know where to look when they need it and have clear learning objectives for radiology during their internships.

‘…I strongly believe that just in time learning would be a valuable option. If you simply teach students in-time where to find specific knowledge on radiology, they will use it when they need it the most. Then, all they need to do is practice their knowledge” – Geriatrician.

‘If you learn about radiological examinations relevant in the clinical practice that you are about to embark in, you will learn the basics just prior to your internship and the clinical context will help you to complete the picture. Together, I would consider this a rich learning experience for students” – Radiologist.

Internship in radiology

Due to a lack of time in the medical curriculum, most of the interviewees would not opt for the incorporation of a mandatory internship in radiology. Nevertheless, it was considered an important elective internship. Only one participant believed it was important to create time for a mandatory internship.

On the other hand, interviewees expressed that some practical experience in radiology for all medical students would be beneficial to: (1) gain insight into the tasks of a radiologist, (2) become aware of one’s own strengths and limitations regarding reading radiological examinations and (3) learn how to establish an optimal collaboration between radiologist and clinician. It was mentioned that such “intern days” could be integrated into the proposed LLCs in radiology or in various internships such as emergency and internal medicine or surgery.

“I consider it a good idea to offer it as an internship for choice, apart from the LLC”- Internal medicine doctor

Intracurricular primary radiologic skills

There was some discussion with regard to learning the skill of interpretation of a chest radiograph and the skill to perform a point-of-care ultrasound (POCUS). Chest radiography in itself takes a prominent place in radiology education and was believed to deserve a specific view on learning goals. There is an emerging use of POCUS in health care and the opinions on what should be taught on this subject diverse widely. Some interviewees thought that integrating POCUS as an intra-curricular learning goal would take up too much time to really let students master this skill. On the other hand, others were eager to implement teaching POCUS in the medical curriculum as it could serve as an extension on the physical examination with immediate results, low costs and high mobility with hand-held devices. It was mentioned that since so little is taught on ultrasound, there is so much to gain out of a bit more education.

“If you ask me, we will all throw out our stethoscope and let everyone have an ultrasound machine and I do believe that time will come. I just do not know how soon” – Emergency doctor

This study elucidated the views of both radiologists and non-radiologists and grouped these views in three themes: 1) Expectations with regard to educational topics in radiology education; 2) Teaching strategies with regard to radiology education; and 3) Promising educational strategies in radiology education.

These findings are largely corroborated by others. For example, Subramaniam et al. [ 53 , 55 , 55 ] also showed that radiology education should include the teaching of (contra-)indications for different imaging techniques, skills to systematically review chest and musculoskeletal radiographs, skills to identify gross abnormalities on radiographs and teaching students how to fit important findings in the clinical setting. However, contradictory to the studies of Subramaniam et al., interviewees did not express the reading of abdominal radiographs as an educational topic, which can be explained by the ongoing development of radiology in the clinical setting [ 2 , 57 ]. At the time of the publication of the papers of Subramaniam et al., abdominal radiographs had a more prominent clinical role than today.

Integration of radiology and anatomy education

Interviewees in this study stated that basic anatomical knowledge is needed to fully comprehend imaging studies. However, as less time is being assigned to anatomy education in medical curricula [ 18 , 35 , 4 ], learning about radiological examinations could become more complicated for students. Also, as Kourdioukova et al. [ 33 ] mention in their paper, Problem Based Curricula create a building block approach in which radiology and radiologic anatomy is relatively underrepresented in examinations. Integration of applied anatomy and applied radiology has been commonly suggested to optimize quality of anatomy and radiology education in modern medical curricula, [ 4 ,  14 , 28 , 36 ]. This was also objectified as radiology small group teaching significantly improved anatomy scores [ 8 , 9 ] and radiology skills [ 40 ]. Additionally, combining radiology and anatomy education has been described to be easily implementable in existing preclinical curricula, because it requires few additional resources [ 62 ]. Integration of radiology education with other disciplines has also been suggested [ 42 ]. Interestingly, in the current study, MRI sequence which were considered basic knowledge comprised T1-weighted images, T2-weighted images and FLAIR images, whereas other sequences were not mentioned. Fat suppression techniques were not discussed, although several advantages are well-known in for example neuroradiology [ 56 ] and imaging of the musculoskeletal system [ 16 ]. Also, the use of diffusion-weighted imaging was not mentioned as part of the basic knowledge that a medical student must obtain. Possibly, clinicians omitted these sequence as the physical concepts are somewhat more complex to explain to students during rotations. However, the exact motives remain elusive. Together with the positive feedback to the LLC in the interviews of this study, a balanced integration of radiology education in various subjects of teaching could be a promising next step for radiology educators.

Other innovative teaching methods which might play a role in the future of anatomy and radiology education, such as augmented reality, virtual reality and combined use of these techniques with radiological data were not mentioned during the interviews. Nevertheless, several publications point out the possible advantages of each individual technique [ 6 ,  3 , 12 , 13 , 41 ].

Radiology education topics: reading chest radiographs and practical teaching of ultrasound skills

Although in this study chest radiographs were considered an important educational topic in medical school, there was a wide diversity in opinion to what extent a student should master this subcategory of imaging technologies. Even though this study was not able to provide results to what extent of supervision level or entrusted professional activity a medical student should master this skill, this study was the first that objectified this wide diversity in opinions. We believe this should be investigated more profoundly to be able to create a properly adjusted learning objective on this topic. Especially since Eisen and colleagues found that only 15% of their study population, consisting of medical students, interns, residents and fellows, felt capable to interpret chest radiographs independently in an academic medical center setting [ 19 ]. This lack of confidence has been found by others as well [ 7 , 11 ].

Lastly, teaching ultrasound was a topic of debate in our study, which was widely discussed among the interviewees. This observed discrepancy is in line with literature on this topic [ 36 , 50 ]. Although ultrasound has been described as an educational tool to improve anatomy knowledge, physical examination skills, increase diagnostic accuracy and advance patient safety, the evidence regarding the effects of ultrasound education on these outcomes is very limited [ 20 ]. Nevertheless, various studies reported that medical students consider ultrasound education as valuable [ 15 , 17 , 46 , 49 , 59 ]. Despite this increased demand of ultrasound education in medical school, studies showed that hands-on education of ultrasound is taught at a minority of universities in Europe and the United States [ 43 , 45 ]. More research is needed to either create insight into the learning objectives of ultrasound in medical curricula or to chart the potential benefits of teaching ultrasound in medical school. Additionally, the effects of using ultrasound for educational goals on learning outcomes should be studied as well.

Strengths and limitations

The major strength of this study was the qualitative study design as a recent review highlighted that quality research is needed to investigate when and how radiology should be included in medical education [ 8 , 9 ]. A second strength concerns the exploration of the thoughts and opinions of a wide variety of clinicians included in this study. The sparse availability of recent scientific literature on the teaching of a dynamic subject like medical imaging illustrates that this is a relatively understudied domain and, simultaneously, shows the importance of the present work. This work, however, is not without its limitations. One limitation of this study was formed by the strictly defined inclusion criteria which only allowed clinicians from one region within The Netherlands to participate. The ideas on this topic within this region can differ from others since every training region has its own personal and cultural view on certain subjects and specific spearheads. This limitation regarding generalizability of the reported themes might also exist for the clinicians’ views on radiology education in countries other than The Netherlands. Secondly, this study population cannot be considered as a generalizable population of clinicians which are involved in medical education. For example, the number of radiologists participating in this study was larger as compared to the number of general practitioners (Table  2 ). Therefore, radiologists were overrepresented in the study population. In addition, some medical disciplines, such as psychiatry, ophthalmology and dermatology were excluded from this interview study due to the fact that these clinicians do not frequently encounter radiology. However, the risk of potential bias is limited as the nature of this study and research question did not warrant the inclusion of these clinicians. Furthermore, a limitation of the qualitative study design concerns the relative subjectivity of the results as participants hold control over the content of the data. This prevents quantification of the results and warrants future studies to investigate the statistical significance of the here described findings [ 10 , 38 ]. Additionally, it must be noted that clinicians are no education experts. Future implementation of these results should be carried out in close collaboration with education experts.

This qualitative study provided more in-depth knowledge on well-known topics with regard to radiology education in medical curricula. More knowledge with regard to educational methods, timing of radiology education was distilled and several new topics arose. This includes thoughts on educating ultrasound skills to undergraduates and the views on a longitudinal learning community in radiology in order to integrate imaging technologies in a problem based medical curriculum. It was recommended that radiology education should be more embedded in the medical curriculum and various educational strategies and topics to achieve this were suggested. Nevertheless, to which extent these educational topics should be mastered, what resulting learning objectives will need to entail and how to evaluate them need further research.

Availability of data and materials

The dataset generated from the interviews and analyzed during the current study are not publicly available since individual privacy could potentially be compromised but are available from the corresponding author on reasonable request.

Abbreviations

Longitudinal learning community/curriculum

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Acknowledgements

The authors would like to acknowledge Beau van Woudenberg, MSc, for his help with coding the interviews and with his valuable insights into qualitative research methods. No potential conflict of interest was reported.

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Harthoorn, F.S., Scharenborg, S.W.J., Brink, M. et al. Radiology education for medical students: a qualitative exploration of educational topics, teaching methods and future strategies. BMC Med Educ 24 , 891 (2024). https://doi.org/10.1186/s12909-024-05879-0

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Published on 19.8.2024 in Vol 26 (2024)

The Dual Task Ball Balancing Test and Its Association With Cognitive Function: Algorithm Development and Validation

Authors of this article:

Original Paper

• Barry Greene 1, 2 , PhD   ; 
• Sean Tobyne 1 , PhD   ; 
• Ali Jannati 1 , PhD   ; 
• Killian McManus 1, 2 , PhD   ; 
• Joyce Gomes Osman 1 , PhD   ; 
• Russell Banks 1 , PhD   ; 
• Ranjit Kher 1   ; 
• John Showalter 1 , MD   ; 
• David Bates 1 , PhD   ; 
• Alvaro Pascual-Leone 1, 3 , MD, PhD  

1 Linus Health, Boston, MA, United States

2 Linus Health Europe, Dublin, Ireland

3 Hinda and Arthur Marcus Institute for Aging Research, Deanna and Sidney Wolk Center for Memory Health, Hebrew SeniorLife, Boston, MA, United States

Corresponding Author:

Killian McManus, PhD

Linus Health

280 Summer St

Boston, MA, 02210

United States

Phone: 1 851682046

Email: [email protected]

Background: Dual task paradigms are thought to offer a quantitative means to assess cognitive reserve and the brain’s capacity to allocate resources in the face of competing cognitive demands. The most common dual task paradigms examine the interplay between gait or balance control and cognitive function. However, gait and balance tasks can be physically challenging for older adults and may pose a risk of falls.

Objective: We introduce a novel, digital dual-task assessment that combines a motor-control task (the “ball balancing” test), which challenges an individual to maintain a virtual ball within a designated zone, with a concurrent cognitive task (the backward digit span task [BDST]).

Methods: The task was administered on a touchscreen tablet, performance was measured using the inertial sensors embedded in the tablet, conducted under both single- and dual-task conditions. The clinical use of the task was evaluated on a sample of 375 older adult participants (n=210 female; aged 73.0, SD 6.5 years).

Results: All older adults, including those with mild cognitive impairment (MCI) and Alzheimer disease–related dementia (ADRD), and those with poor balance and gait problems due to diabetes, osteoarthritis, peripheral neuropathy, and other causes, were able to complete the task comfortably and safely while seated. As expected, task performance significantly decreased under dual task conditions compared to single task conditions. We show that performance was significantly associated with cognitive impairment; significant differences were found among healthy participants, those with MCI, and those with ADRD. Task results were significantly associated with functional impairment, independent of diagnosis, degree of cognitive impairment (as indicated by the Mini Mental State Examination [MMSE] score), and age. Finally, we found that cognitive status could be classified with >70% accuracy using a range of classifier models trained on 3 different cognitive function outcome variables (consensus clinical judgment, Rey Auditory Verbal Learning Test [RAVLT], and MMSE).

Conclusions: Our results suggest that the dual task ball balancing test could be used as a digital cognitive assessment of cognitive reserve. The portability, simplicity, and intuitiveness of the task suggest that it may be suitable for unsupervised home assessment of cognitive function.

Introduction

Recent research has suggested that up to 40% of dementia cases [ 1 ] can be delayed or prevented through early identification of impairment and adherence to recommended lifestyle modifications [ 2 ]. Furthermore, recent developments in pharmaceutical intervention suggest that the progression of Alzheimer dementia can be delayed through amyloid plaque removal [ 3 ].

An individual's cognitive and behavioral performance is a combination of brain activity and cognitive reserve. Cognitive reserve can be conceptualized as a property of the brain that allows for better than expected performance, given the degree of life-course related brain changes and brain injury or disease [ 4 ]. Cognitive reserve can be influenced by multiple genetic and environmental factors, operating at various points or continuously across the lifespan. In the presence of disease, for example, a neurodegenerative disease such as Alzheimer disease, cognitive reserve is engaged to sustain function for as long as possible and minimize symptoms and disability. Thus, individuals with more cognitive reserve manifest symptoms or disability later than those with lower cognitive reserve; symptoms are less prominent or severe than might be expected for a given amount of pathology. Low cognitive reserve makes individuals with underlying brain pathology prone to episodes of confusion, delirium, and other acute decompensations when exposed to a stressor or insult, for example, elective surgery, infection, sleep, and deprivation. Individuals with mild cognitive impairment (MCI) and higher cognitive reserve can delay the development of dementia. Thus, assessment of cognitive reserve is important to predict an individual’s functional state and prognosis. In addition, cognitive reserve can be a powerful therapeutic target, as increasing cognitive reserve might reduce disability.

The brain’s resource allocation capacity has been studied extensively and is thought to provide insight into cognitive reserve and depend on prefrontal function. However, the nature and causality of this relationship is not as well understood. Dual task paradigms have long been thought to unlock deficits in the allocation of prefrontal resources [ 5 ]. Recent studies [ 6 - 8 ] have examined the impact of a cognitive task (eg, backward counting) on a participant’s gait or balance, and thus, are dependent on peripheral nerve and musculoskeletal factors often affected in older adults. Furthermore, gait and balance analysis may not be suitable or safe for use with older adults or those with comorbidities such as osteoarthritis, neuropathies, etc. A validated tool that can support objective characterization and quantitative evaluation of cognitive reserve safely and reliably in older adults, as well as early identification of cognitive decline in nonclinical settings, could be of clinical benefit in more accurately identifying those patients who would benefit most from early and targeted intervention.

We introduce a novel test of motor control, coordination, and attention—the “ball balancing” test, in which an individual is asked to maintain the position of a virtual ball in the center of a circular target area. Task performance is measured by examining the position of a virtual ball on the screen of a touchscreen tablet, estimated using the inertial sensors embedded in the tablet. The test can be easily adapted to a dual task condition, for example, by asking the individual to balance the ball while simultaneously doing a different, attention demanding task. The test can be completed comfortably and safely in a sitting position. In an initial version of a dual task paradigm, an individual’s ball balancing test performance was assessed while simultaneously conducting a backward digit span test (BDST).

We aimed to examine the use of the ball balancing test under single and dual conditions [as quantified using the inertial measurement unit (IMU) sensors embedded in the target device] in assessment of cognitive reserve and identification of cognitive impairment. While this task (and other dual task paradigms) is not primarily aimed at serving as a means to classify cognitive function, one may predict there should be a loss of cognitive reserve between MCI and dementia, given that cognitive reserve would be “used up” to sustain cognitive function and ultimately be no longer sufficient to prevent progression of deficit, impact on activities of daily living (ADL), and thus transition from MCI to dementia. We report the performance of the task in classifying cognitive status according to 3 different outcome measures (consensus clinical judgment, Rey Auditory Verbal Learning, and Mini Mental State Examination). Given that the outcome measures are imperfectly mutually correlated, it can be assumed that they may contain complementary information pertinent to assessment of cognitive function, which can be leveraged to examine cognitive reserve deficits.

Ball Balancing Task

Participants were seated in a comfortable and supportive chair and asked to hold a touchscreen tablet device (iPad Pro, Apple) parallel to the ground and tilt the screen as needed to keep a virtual ball within a target area—the ball was not perturbed during the test unless the tablet was moved by the participant.

Participants were asked to balance a virtual ball on a touchscreen tablet screen, the subsequent movement is measured by the IMU sensors embedded in the tablet and used to calculate the position of the virtual ball on the tablet screen. The ball balancing test was completed under both single task (ball balancing alone) as well as under dual task conditions, with participants completing a single trial of each. The dual task involved asking the participant to complete the ball balancing test while simultaneously completing a BDST. In the BDST, the participant is played an audio sequence of 4 digits and is prompted to repeat them in reverse order. The single task was 20 seconds in duration while the dual task was 45 seconds in duration.

A custom iOS application (Swift, iOS) was developed to conduct the ball balancing test, supporting single and dual tasks. IMU and ball position data were stored within the application in JSON format and exported for offline analysis. All analyses were conducted using MATLAB (R2017b, MathWorks; Figure 1 ).

The following two distinct approaches were used to analyze the data, that is, by examining: (1) the ball position on the screen (estimated from IMU data); and (2) the IMU data from the movement of the tablet during the test.

Signal Processing: Ball Position Metrics

The position of the ball on the screen was calculated using the inertial sensor data as input to a kinematic model, which derives the ball placement on the screen using Newtonian mechanics and allowed plotting of ball displacement on the screen. The following parameters were calculated from the virtual ball displacement (values in parenthesis indicate variants of the calculated feature) ( Textbox 1 ).

For all ball position metrics, the displacement is normalized to the range [ 9 ], where the outer edge is the radius of the outer circle, while the radius of the inner circle is calculated based on the ratio of the inner circle radius to the outer circle. The percentage of time spent within the inner circle is calculated as the proportion of time where the resultant displacement is less than the radius of the inner circle less the radius of the ball. The radial symmetry is calculated as the sum of the first difference values of the resultant displacement from the center of the circle. It is intended to measure quadrant placement of the ball within the outer circle. To examine learning effects and changes in performance over the course of each test, the percentage of time within the inner circle is calculated for each 5-s epoch within the test. The mean, standard deviation, and first difference were then calculated across all epochs per test to provide a measure of intratest performance. A number of standard center of pressure measures [ 10 , 11 ] were also calculated based on time and frequency domain analysis of the ball displacement. Each ball position metric was calculated for each participant under single task (ST) and dual task (DT) conditions; the dual task cost was calculated as the percentage difference between the parameter value under DT conditions and the parameter value under ST conditions and can be expressed mathematically as –100*(DT-ST)/ST [ 12 ].

A “perfect score” was achieved when the ball was found to lie within the inner circle for 100% of the test. As it was possible to achieve a perfect score by placing the tablet flat on a table, we examined if perfect score tests had any effect on the overall results to rule out the possibility that certain participants were engaging less with the task but achieving a perfect score.

• Percentage of test time spent within inner circle
• Radial symmetry
• Percentage of time spent in the inner circle per 5-second epoch (mean, SD, and first difference)
• Median frequency of ball displacement (mean, X, and Y)
• 95% spectral edge frequency of ball displacement (mean, X, and Y)
• Sway area of ball displacement
• Mean sway frequency (mean, X, and Y)
• Mean sway distance (mean, X, and Y)
• Resultant sway distance (mean, X, and Y)
• Sway length of ball displacement (mean, X, and Y))
• Sway velocity (mean, X, and Y)

Inertial Sensor Parameters

Inertial sensor data from the tablet device under both ST and DT conditions were processed using an adapted version of a previously reported algorithm [ 13 , 14 ]; this approach treats the IMU data as arising from motion about a rigid plane. Figure 2 below shows the IMU (triaxial accelerometer and triaxial gyroscope) data for a dual task ball balancing test.

For each test, 1 second of data was excluded from the start and end of each recording to remove artifacts due to tablet positioning. Any recordings less than 10 seconds were discarded. IMU data were resampled to 100 Hz as iPad IMU data can be unevenly sampled, leading to distortion in frequency domain signal features [ 15 ]. Signals were bandpass filtered using a fourth order Butterworth IIR filter, in the range 0.1-40 Hz and calibrated using a standard method [ 16 ].

The following parameters were calculated from the IMU data for each ball balancing test ( Textbox 2 ).

For each calculated parameter, the dual task cost was calculated as the percentage difference between the parameter value under dual task conditions and the parameter value under single task conditions. Figure 2 provides a 3D representation of the ball balancing test signal relative to the rigid plane.

• Root mean square (RMS) acceleration (m/s 2 )
• RMS acceleration—x-axis (m/s 2 )
• RMS acceleration—y-axis (m/s 2 )
• RMS acceleration—z-axis (m/s 2 )
• RMS angular velocity (°/s)
• Median frequency acceleration (Hz)
• RMS angular velocity—x-axis (°/s)
• RMS angular velocity-y-axis (°/s)
• Spectral edge frequency acceleration (Hz)
• Spectral entropy acceleration
• Median frequency angular velocity (Hz)
• Spectral edge frequency angular velocity (Hz)
• Spectral entropy angular velocity
• Sway path length of acceleration—x-axis (m/s 2 )
• Sway path length of acceleration—z-axis (m/s 2 )
• Sway area of the acceleration
• Sway jerk of the acceleration
• Area of 95% confidence ellipse of acceleration

Statistical Analysis

To examine the association between the calculated ball balancing test parameters and cognitive function, we considered the 3 available neurocognitive measures (cohort status, Mini Mental State Examination [MMSE], and Rey Auditory Verbal Learning Test [RAVLT]), treated as either continuous variables or binary labels (eg, impaired or not impaired). Cohort status was treated as a 3-category label (healthy, MCI, and Alzheimer disease–related dementia [ADRD]). Similarly, the differences between the healthy and impaired subgroups (MCI and ADRD) were also examined using a Wilcoxon rank sum test. A Wilcoxon signed rank test was used to test for significant differences across task conditions.

The MMSE (total score) and RAVLT (long recall delay score) data were dichotomized into cognitively impaired and cognitively intact with values below a threshold of 28 for the MMSE [ 17 ] and age group thresholds for the RAVLT [ 18 ] used to identify impaired cognition.

Spearman rank correlation was used to examine the relationship between each feature with the MMSE and RAVLT, while the Wilcoxon rank sum test was used to test for differences between impaired and nonimpaired groups for each feature. A confusion matrix was calculated for each set of binary labels (impaired/nonimpaired) to see how well cohort status, MMSE-, and RAVLT-based categorization agree with each other.

To examine the association of each variable with cognitive function and allow for the effect of age, a linear mixed effects model analysis was conducted with age as a within-subjects’ factor and cohort status as a categorical response variable. ANOVA was then used to examine the effect of each factor on cohort status, while controlling for age. This analysis was repeated for each variant with binary cohort status as well as impaired and nonimpaired labels obtained from MMSE and RAVLT.

In addition, we aimed to examine if any of the calculated ball balancing parameters were associated with functional impairment, independent of cognitive impairment. We conducted a one-way ANOVA for each ball balancing parameter with functional impairment (as measured by the Functional Activity Questionnaire [FAQ], with a threshold greater than or equal to 6 denoting functional impairment), controlling for MMSE and age. This analysis was then repeated when controlling for RAVLT and age.

To determine how well ball balancing parameters (features) could classify “unseen” participants according to binary cognitive status (cognitively impaired or cognitively intact), we used a logistic regression classifier model with a sequential forward feature selection procedure [ 19 ] validated using 10-fold cross-validation. Interaction terms were included in the candidate feature set and separate models were produced for each condition and feature set (ST, DT, dual task cost, all features as well as age only).

A sample of 375 older adults (n=210 female; aged 73.0, SD 6.5 years). Completed a battery of cognitive and motor function tests as part of wider study on brain health. The Bio-Hermes research study is managed by the Global Alzheimer Platform (GAP) and seeks new solutions to monitor and maintain brain health. Each participant received a clinical examination, which included the MMSE [ 20 ], the RAVLT [ 21 ] and “cohort status,” which classified participants into 3 clinical categories (healthy, MCI, and ADRD), as determined by a panel of qualified clinicians. For RAVLT, 2 summary scores were examined: the RAVLT total score and the RAVLT long recall delay score. In addition, each participant completed an FAQ [ 9 ] to examine functional status including ADL.

Ethical Considerations

The Bio-Hermes research study is managed by the GAP. The study was performed in accordance with the Declaration of Helsinki and its later amendments. The study procedures were explained to participants verbally and through written informed consent that was approved by the local IRB of each site participating in the GAP consortium (see the Bio-Hermes study website [ 22 ] for a list of study sites). If, in the opinion of the site principal investigator, the participant did not have the capacity to sign the informed consent form, a legally authorized representative was used to grant consent on behalf of the participant. Ethical approval was granted by each institution participating in the GAP consortium (reference number: Pro00046018). Inclusion criteria for the study were adults 60-85 years of age, fluent in the language of the tests used and the test site, and with an MMSE score of 20-30 at Screening. Exclusion criteria were extensive and based on underlying conditions. All data collected as part of this study were deidentified to confidentiality protection. Participants in the study were compensated in order to cover any time or expense they incurred as a result of completing the study.

Age was significantly different ( P <.001) across cohort status groups. The mean total MMSE scores for the sample was 26.3 (SD 3.0), mean total adjusted RAVLT score was 38.8 (SD 14.3), while mean RAVLT long delay score was 5.4 (3.5). According to cohort status, 132 participants were deemed cognitively normal, 116 were considered to have MCI and 126 had probable AD (ADRD), 1 participant did not have a valid cohort status label. Combining the MCI and ADRD classes to produce 2 classes (Impaired and Intact) produced 242 participants with cognitive impairment and 132 deemed intact. Using MMSE and FAQ cut-offs of 28 and 6, respectively, along with RAVLT age group thresholds [ 18 ] to categorize participants as impaired or unimpaired, allowed a comparison of these labels against binary cohort status. MMSE agreed with cohort status with 73.8% (277/375) accuracy, RAVLT total score agreed with cohort status 45.7% (171/375), while RAVLT long recall delay score agreed with 84.8% (318/375) accuracy. Pearson's correlation coefficient between MMSE and RAVLT total score was 0.43, while correlation coefficient between MMSE and RAVLT long delay recall score was 0.60 (see Figure 3 ).

Ball Balancing Task Performance

All participants were able to complete the task under ST and DT conditions. The main metric of task performance was the percentage of time the virtual ball spent within the inner circle (“percentage time in circle”). Mean percentage time spent in the inner circle was 86.0% (SD 23.0%) and 66.1% (SD 35.8%) under ST and DT conditions, respectively, while the mean DT cost was 21.0% (SD 34.1%). Task performance was significantly different ( P <.05) across cognitive status groups and between ST and DT conditions ( Table 1 ). As expected, participants achieved lower performance under DT conditions with a higher mean percentage time within the inner circle and a lower proportion of “perfect score” tests (see Figures 4 and 5 ). Removing tests with “perfect” task performance (percentage time is circle equal to 100%) did not change this finding. Performance in the task declined with increased cognitive impairment, with best mean performance observed in the healthy group for both ST and DT and worst task performance in the ADRD group.

Task performance was statistically significantly different ( P <.05) across group and between conditions.

Exploratory Results for Cohort Status

Age is significantly different between impaired and nonimpaired groups. When controlling for age using ANOVA, a large number of calculated parameters below were significantly ( P <.05) different on the basis of 3 category cohort status.

Similarly, when using ANOVA with a binary cohort label and correcting for age, a large number of parameters were significantly ( P <.05) different on the basis of binary cognitive status. Figure 6 below details 2 IMU parameters where there were significant differences across groups when corrected for age.

Classification Using Cohort Status

A linear logistic regression classifier model based on ball balancing measures from the DT condition (including age and gender) compared against a model obtained from age only found that ball balancing parameters could classify cognitive status with 70.5% accuracy compared to 62.3% accuracy for age alone ( Table 2 ).

a Results are shown for a model based on ball balancing inertial measurement unit (IMU) parameters and a model based on age only. The best result per group is italicized. Results for separate gender stratified male and female models are reported as well as models based on All available data.

Exploratory Results of the FAQ

A small number of ball balancing parameters under both single and dual task conditions were significantly associated with functional impairment (as measured by the FAQ with a threshold of 6), independent of cognitive function (as measured by MMSE total score) and age. These parameters included dual task cost of task performance (percent time in circle), dual task median frequency acceleration and single task radial frequency. A similar analysis controlling for age and RAVLT long recall delay score found that several ball balancing parameters including median frequency acceleration and single task radial frequency were significantly associated with functional impairment.

RAVLT Exploratory Results

A number of ball balancing parameters under both single and dual task conditions were significantly different on the basis of cognitive status (using RAVLT long recall delay score, with age bucketed thresholds) to define cognitive impairment) and correcting for age.

Pearson correlation coefficient was used to calculate the correlation between the RAVLT (long recall delay score) and each of the calculated ball balancing parameters per task condition. Weak correlations were observed for a number of parameters.

Classification Using RAVLT Long Delay

A linear logistic regression using RAVLT long recall delay score with age bucket thresholds to denote impairment yielded a mean classification accuracy of 70.43% compared to 57.03% for age alone ( Table 3 ).

Classification results for a model using age alone trained with the RAVLT long delay are also supplied. Results for separate genders stratified as male and female models are reported as well as models based on all available data.

a Italics are used to highlight the values most indicative of the true model accuracy.

Exploratory Results of the MMSE

A number of parameters under both single and dual task conditions were significantly different (using ANOVA and correcting for age) on the basis of cognitive status using MMSE, with a threshold of 28 to classify participants as cognitively impaired or cognitively unimpaired.

Pearson correlation coefficient was used to calculate the correlation between the MMSE (total score) and each of the calculated ball balancing parameters per task condition. Weak correlations were observed for a number of parameters.

Classification Using the MMSE

A linear logistic regression using the MMSE total score with a threshold of 28 to denote impairment yielded a mean classification accuracy of 72.8% compared to 69.6% for age alone ( Table 4 ).

Classification results for a model using age alone trained with the MMSE are also supplied. Results for separate genders stratified as male and female models are reported as well as models based on all available data.

We introduce a novel dual task paradigm to evaluate cognitive reserve and prefrontal resource allocation that does not rely on gait and balance metrics and can, thus, be safely completed by older adults and those with falls risk. We found that older adults were able to complete the task regardless of their age or level of cognitive impairment. Even those with MCI and ADRD, as well as those with peripheral neuropathy, osteoarthritis, frailty, and other potential sources of gait and balance problems were able to complete the task reliably and safely.

A sample of 375 participants completed the dual task ball balancing test protocol. Participants ranged in age from 60 to 85 years and exhibited a wide range of cognitive ability. As predicted, participants achieved significantly higher ball balancing test performance under ST conditions (as measured by the percentage of test time, the ball was within the inner circle) compared to DT performance. Thus, along with the higher proportion of perfect tests under ST conditions, the findings confirm that participants were more challenged by the test under DT conditions and that task performance decreased with increasing cognitive impairment. We found that task performance was significantly improved in healthy individuals compared to those with MCI and that performance was worse again in those with ADRD.

A number of significant differences were observed between cognitively intact (unimpaired) and cognitively impaired participants for ball positioning and IMU parameters calculated during a ball balancing test, when correcting statistics for the effect of age, using cohort status, RAVLT long delay score, and MMSE to determine cognitive status.

Significantly decreased performance in the ball balancing test was observed during the DT compared to the ST. Similarly, decreased performance was observed for increasing levels of cognitive impairment. An interpretation of this result is that with increasing impairment, there needs to be greater reliance on cognitive reserve to sustain (or attempt to sustain) cognitive and functional performance. These results are in line with results reported in the literature for other DT paradigms, which suggest that task performance reduced during a DT as compared to an ST and that the reduction in task performance is increased with increased impairment [ 6 , 22 ]. As such, DT performance across different tasks becomes increasingly altered and with that increasingly correlated, while before the high DT cost suggesting impaired reserve (if present at all) might be detectable for some but not all DT conditions. Importantly, a number of ball balancing parameters, measured under both ST and DT conditions were found to be significantly associated with functional impairment (as measured by the FAQ score) independent of MMSE, RAVLT, and age. This suggests that differences observed between MCI to ADRD groups under dual task conditions are consistent with loss of cognitive reserve contributing to progression of clinical manifestation and impact on ADL [ 4 , 23 ]. The ball balancing dual task paradigm may, thus, offer a valuable, objective means to evaluate the risk of ADL impact and enable early detection of MCI-to-dementia transition risk [ 24 ].

Moderate classification performance (>70%) was also observed in classifying binary cognitive status using a logistic regression classifier model trained on each of the cognitive function outcome measures. This compared favorably to models based on age alone, which distinguished between impaired and unimpaired groups with ~60% accuracy. A simple linear classifier model (logistic regression) was used to obtain a baseline of classification performance; improved performance may be achieved through the addition of nonlinear interaction terms or the use of higher order classification methods (eg, support vector machines), given the wider data set and potential nonlinear statistical relationships between features. To provide an indication of how well the ball balancing test can distinguish cognitively impaired participants from cognitively intact participants, cross-validation and wrapper-based feature selection was used. This method ensures unbiased estimate of classifier performance on previously unseen participants [ 25 ].

Three cognitive function outcome measures were considered in analyzing the use of the ball balancing test in classifying cognitive status. Each outcome measure (MMSE, RAVLT, and cohort status) contains differing and potentially complementary information about cognitive status (as evidenced by the modest mutual correlation observed between each outcome measure). In future work, we will examine the ability of a model based on the weighted combination of the 3 outcomes in longitudinally predicting cognitive impairment on a statistically independent data set. Furthermore, future work may also seek to examine the relationship of the ball balancing test parameters with blood biomarkers [ 26 ] and brain structure and pathology [ 5 ].

A limitation of this implementation of the ball balancing test is that the virtual ball is not perturbed during the test (other than by the movement of the tablet). This means that placement of the tablet on a flat, stable surface would allow the participant to achieve “perfect” task performance. However, it should be noted that the presence of “perfect score” tests were not found to affect the group-wise findings. An additional limitation is potential usability issues in using this task with an older adult population, particularly those with cognitive fine motor or visual impairments. While the current study involved participants conducting the task under supervised conditions to ensure adequate adherence to the task protocol, there may have been participants in the cognitively impaired groups who struggled to understand the instructions even with the support of the research assistant. Furthermore, impairment to fine motor skills may have prevented some participants from performing to their full capacity. Such usability issues may be exacerbated if the task were to be conducted under unsupervised conditions and would need to be carefully considered in the protocol for future studies.

The ball balancing test is a novel dual task paradigm that may have use in assessment of cognitive reserve and identification of cognitive impairment. Participants with mild or severe cognitive impairment performed less well on the task than healthy participants, particularly when a DT was introduced. A simple cross-validated classifier model used inertial sensor derived parameters obtained during the task to distinguish between cognitively impaired and cognitively intact participants with 70% accuracy. As the ball balancing test can be delivered entirely through a touchscreen tablet device, does not require a controlled environment, and is relatively simple to understand, the task may be suitable for administration by nonexpert users or for unsupervised use in the home environment and could support remote, longitudinal assessment of cognitive function.

Acknowledgments

The data that support the findings of this study were collected as part of the Bio-Hermes study and are governed by the Global Alzheimer Platform (GAP) consortium agreement. We would like to thank Dante Smith for his help in determining kinematic position of the virtual ball during the task. We would also like to thank the patients and clinicians involved in the study.

Data Availability

The data sets generated and analyzed during this study are not publicly available due to the terms of the Global Alzheimer Platform (GAP) consortium agreement. However, the data are available from the corresponding author on reasonable request.

Authors' Contributions

Data analysis was carried out by BG. All authors contributed to manuscript preparation and analysis plan.

Conflicts of Interest

APL is a co-founder and Chief Medical Officer of Linus Health and declares ownership of shares or share options in the company. APL serves as a paid member of the scientific advisory boards for Neuroelectrics, Magstim Inc, TetraNeuron, Skin2Neuron, MedRhythms, and Hearts Radiant. All other authors are employees of Linus Health and declare ownership of shares or share options in the company.

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Abbreviations

Edited by A Mavragani; submitted 09.06.23; peer-reviewed by H-F Hsieh, J Rider, B Poston; comments to author 21.11.23; revised version received 23.11.23; accepted 13.05.24; published 19.08.24.

©Barry Greene, Sean Tobyne, Ali Jannati, Killian McManus, Joyce Gomes Osman, Russell Banks, Ranjit Kher, John Showalter, David Bates, Alvaro Pascual-Leone. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 19.08.2024.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.

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Regional consultation on Draft Global Strategy for traditional medicine 2025:2034 and to set the regional research priorities for WHO SEA region

Regional director who south-east asia ms saima wazed’s address at the regional consultation.

The World Health Organization has sought to achieve “Health for All” as its goal for the past 75 years. Not health for some, not health for many, but Health for All . This does not just mean health in a physical sense, but also well-being - as highlighted in our founding Constitution. 

To achieve this goal, the Alma Ata Declaration of 1978 makes two important declarations:

First, that primary health care is essential for achieving Health for All;

And secondly, that primary health care must be based on scientific and socially acceptable methods including traditional medicine.

Thus, safe and effective traditional medicine has a definite and significant role in achieving our core objective. 

Today, almost all countries of our South-East Asia Region have developed and implemented a national policy for Traditional medicine.

Nine countries have established formal training and education systems for traditional medicine practitioners, and six countries have co-located traditional medicine services within their health systems.

Five countries have national essential medicine policies on traditional medicine and have also provided financial protection for traditional medicine services.

We recently launched our WHO South-East Asia Regional Roadmap for Results and Resilience. This is a shared strategic framework for a healthier Region, and I’d like to reiterate some of the salient points.

Our roadmap lays out what we call the ‘Five Rs ’ :

R1: Reinforcing mental health, well-being and quality of life for all

R2: Reaffirming investment in women, girls, adolescents and vulnerable populations

R3: Realizing access to technology and innovations

R4: Raising capacity, knowledge management and research

R5: Refining WHO leadership and performance

This regional consultation is well aligned with our regional roadmap. It will help advance holistic health and well-being, and also strengthen research and knowledge management.

The global health landscape in general, and our Region in particular, and GPW14 and the WHO Transformation Agenda warrant that we enhance agility, accountability, and operational efficiency. These also compel us to champion key policy developments, such as the Global Strategy for Traditional M edicine , and system-strengthening initiatives such as setting up of the regional research priorities. These, of course, are the two important outcomes of this consultation.

We look forward to fast-tracking this agenda, in alignment with our Region-wide push to reorient health systems towards accessible, affordable, comprehensive and quality primary health care, in conjunction with the new Global Centre for Traditional Medicine. 

We also look forward to the outcomes of this Regional consultation, which will help finalize the next WHO Global Strategy for Traditional Medicine, set to be launched next year. May the new Global strategy usher in a new era of scientific, evidence-based Traditional medicine delivering ancient wisdom with modern tools, technologies and innovations.

We also look forward to the outcomes of the deliberations to setup the regional research priorities. This will go a long way in streamlining efforts and resources into a more coordinated and focused manner and building required evidence.

At this consultative meeting and beyond, let us together build the strongest evidence for the safest, most impactful outcomes.

Let us act on Astana, Alma Ata, and the Gujarat declarations, accelerating a person-centred, holistic approach to health and well-being, for a biodiverse planet, and a healthier, more equitable and sustainable future for all.

I once again thank you and extend a very warm welcome to you all.   

Media Contacts

Public Information and Advocacy Unit

WHO South-East Asia Regional Office