anxiety research articles 2020

Novel Insights Into Pathological Anxiety and Anxiety-Related Disorders

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• Anxiety Disorders
• Posttraumatic Stress Disorder
• Obsessive-Compulsive Disorder

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Anxiety is characterized by excessive uneasiness, apprehension or dread. It can be generalized or be directed towards specific, usually imagined or exaggerated threat.

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• Published: 06 July 2020

Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: a systematic review and meta-analysis

• Nader Salari 1 , 2 ,
• Amin Hosseinian-Far 3 ,
• Rostam Jalali 4 ,
• Aliakbar Vaisi-Raygani 4 ,
• Shna Rasoulpoor 5 ,
• Masoud Mohammadi   ORCID: orcid.org/0000-0002-5722-8300 4 ,
• Shabnam Rasoulpoor 4 &
• Behnam Khaledi-Paveh 2  

Globalization and Health volume  16 , Article number:  57 ( 2020 ) Cite this article

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The COVID-19 pandemic has had a significant impact on public mental health. Therefore, monitoring and oversight of the population mental health during crises such as a panedmic is an immediate priority. The aim of this study is to analyze the existing research works and findings in relation to the prevalence of stress, anxiety and depression in the general population during the COVID-19 pandemic.

In this systematic review and meta-analysis, articles that have focused on stress and anxiety prevalence among the general population during the COVID-19 pandemic were searched in the Science Direct, Embase, Scopus, PubMed, Web of Science (ISI) and Google Scholar databases, without a lower time limit and until May 2020. In order to perform a meta-analysis of the collected studies, the random effects model was used, and the heterogeneity of studies was investigated using the I 2 index. Moreover. data analysis was conducted using the Comprehensive Meta-Analysis (CMA) software.

The prevalence of stress in 5 studies with a total sample size of 9074 is obtained as 29.6% (95% confidence limit: 24.3–35.4), the prevalence of anxiety in 17 studies with a sample size of 63,439 as 31.9% (95% confidence interval: 27.5–36.7), and the prevalence of depression in 14 studies with a sample size of 44,531 people as 33.7% (95% confidence interval: 27.5–40.6).

COVID-19 not only causes physical health concerns but also results in a number of psychological disorders. The spread of the new coronavirus can impact the mental health of people in different communities. Thus, it is essential to preserve the mental health of individuals and to develop psychological interventions that can improve the mental health of vulnerable groups during the COVID-19 pandemic.

In December 2019, in the city of Wuhan, China, unusual cases of patients with pneumonia caused by the new Coronavirus (COVID-19) were reported [ 1 ], and the spread of the virus swiftly became a global health threat [ 2 ]. There have been several viral diseases in the past 20 years including Severe Acute Respiratory Syndrome (SARS) in 2003, influenza virus with the H1N1 subtype in 2009, Middle East Respiratory Syndrome (MERS) in 2012, and Ebola virus in 2014 [ 3 , 4 , 5 ].

Although COVID-19 is a new strain of coronaviruses, it is known to cause diseases ranging from cold to more severe illnesses such as SARS and MERS [ 5 ]. Symptoms of the Coronavirus infection include fever, chills, cough, sore throat, myalgia, nausea and vomiting, and diarrhea. Men with a history of underlying diseases are more likely to be infected with the virus and would experience worse outcomes [ 6 ]. Severe cases of the disease can lead to heart, and respiratory failure, acute respiratory syndrome, or even death [ 7 ]. In addition to the physical impacts, COVID-19 can have serious effects on people’s mental health [ 8 ]. A wide range of psychological outcomes have been observed during the Virus outbreak, at individual, community, national, and international levels. At the individual level, people are more likely to experience fear of getting sick or dying, feeling helpless, and being stereotyped by others [ 9 ]. The pandemic has had a harmful effect on the public mental health which can even lead to psychological crises [ 10 ]. Early identification of individuals in the early stages of a psychological disorder makes the intervention strategies more effective. Health crises such the COVID-19 pandemic lead to psychological changes, not only in the medical workers, but also in the citizens, and such psychological changes are instigated by fear, anxiety, depression, or insecurity [ 11 ].

Nervousness and anxiety in a society affect everyone to a large extent. Recent evidence suggests that people who are kept in isolation and quarantine experience significant levels of anxiety, anger, confusion, and stress [ 12 ]. At large, all of the studies that have examined the psychological disorders during the COVID-19 pandemic have reported that the affected individuals show several symptoms of mental trauma, such as emotional distress, depression, stress, mood swings, irritability, insomnia, attention deficit hyperactivity disorder, post-traumatic stress, and anger [ 12 , 13 , 14 ]. Research has also shown that frequent media exposure may cause distress [ 15 ]. Nevertheless, in the current situation, it is challenging to accurately predict the psychological and emotional consequences of COVID-19. Studies conducted in China, the first country that was affected by this recent Virus spread, show that people’s fear of the unknown nature of the Virus can lead to mental disorders [ 16 ].

Due to the pathogenicity of the virus, the rate of spread, the resulting high mortality rate, COVID-19 may affect the mental health of individuals at several layers of society, ranging from the infected patients, and health care workers, to families, children, students, patients with mental illness, and even workers in other sectors [ 17 , 18 , 19 ].

Considering several reported psychological consequences of COVID-19 and its spread (Fig.  1 ), and the lack of general statistics on the topic globally, we decided to conduct a systematic review of the existing studies in this field, with a view to providing a holistic, yet comprehensive statistics on the impact of the Virus on general population mental health. The aim of this study is to examine and systematically review and analyze the literature and their reported results related to the impacts of COVID-19 on the prevalence of stress, anxiety, and depression.

Impacts of the COVID-19 pandemic on mental health

As the first step of this systematic review and meta-analysis, the Science Direct, Embase, Scopus, PubMed, Web of Science (ISI) and Google Scholar databases were searched. To identify the articles, the search terms of Coronavirus, COVID-19, 2019-ncov, SARS-cov-2, Mental illness, Mental health problem, Distress, Anxiety, Depression, and all the possible combinations of these keywords were used.

(((((((((((((Coronavirus [Title/Abstract]) OR (COVID-19[Title/Abstract])) OR (2019-ncov [Title/Abstract])) AND (SARS-cov-2[Title/Abstract])) AND (Mental illness [Title/Abstract])) OR (Mental health problem [Title/Abstract])) AND (Anxiety [Title/Abstract])) AND (Social Anxiety [Title/Abstract])) OR (Anxiety Disorders [Title/Abstract])) AND (Depression [Title/Abstract])) OR (Emotional Depression [Title/Abstract])) OR (Depressive Symptoms [Title/Abstract]))))))))))))

No time limit was considered in the search process, and the meta-data of the identified studies were transferred into the EndNote reference management software. In order to maximize the comprehensiveness of the search, the lists of references used within all the collected articles were manually reviewed.

Inclusion and exclusion criteria

The criteria for entering the systematic review included: 1- Studies that examined the prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic. 2- Studies that were observational (i.e. non-interventional studies) 3- Studies that their full text was available. The criteria for excluding a study were: 1- Unrelated research works, 2- Studies without sufficient data, 3- Duplicate sources, 4-Pieces of research with unclear methods 5- Interventional studies 6- Case reports, and 7- Articles that their full text was not available.

Study selection

Initially, duplicate articles that were repeatedly found in various databases were removed. Then, a title list of all the remaining articles was prepared, so that the articles could be filtered out during the evaluation phase in a structured way. As part of the first stage of the systematic review process, i.e. screening, the title and abstract of the remaining articles were carefully examined, and a number of articles were removed considering the inclusion and exclusion criteria. In the second stage, i.e. eligibility evaluation, the full text of the studies, remaining from the screening stage, were thoroughly examined according to the criteria, and similarly, a number of other unrelated studies were excluded. To prevent subjectivity, article review and data extraction activities were performed by two reviewers, independently. If an article was not included, the reason for excluding it was mentioned. In cases where there was a disagreement between the two reviewers, a third person reviewed the article. Seventeen studies entered the third stage, i.e. quality evaluation.

Quality evaluation

In order to examine the quality of the remaining articles (i.e. methodological validity and results), a checklist appropriate to the type of study was adopted. STROBE checklists are commonly used to critique and evaluate the quality of observational studies. The checklist consists of six scales/general sections that are: title, abstract, introduction, methods, results, and discussion. Some of these scales have subscales, resulting in a total of 32 fields (subscales). In fact, these 32 fields represent different methodological aspects of a piece of research. Examples of subscales include title, problem statement, study objectives, study type, statistical population, sampling method, sample size, the definition of variables and procedures, data collection method(s), statistical analysis techniques, and findings. Accordingly, the maximum score that can be obtained during the quality evaluation phase and using the STROBE checklist is 32. By considering the score of 16 as the cut-off point, any article with a score of 16 or above is considered as a medium or a high-quality article [ 20 ]. Sixteen papers obtained a score below 16, denoting a low methodological quality, and were therefore excluded from the study. In the present study, following the quality evaluation by means of the STROBE checklist, 17 papers, with a medium or high quality, entered the systematic review and meta-analysis phases.

Data extraction

Data of from all the final studies were extracted using a different pre-prepared checklist. The items on the checklist included: article title, first author’s name, year of publication, place of study, sample size, assessment method, gender, type of study, the prevalence of depression, anxiety, and stress.

Statistical analysis

The I 2 (%) test was used to assess the heterogeneity of the selected research works. In order to assess publication bias, due to the high volume of samples that entered the study, the Egger’s test was conducted with the significance level of 0.05, and the corresponding Forest plots were drawn. Data analysis was performed using the Comprehensive Meta-Analysis (CMA version 2.0) software.

In this work, the prevalence of stress and anxiety among general population during the COVID-19 pandemic was assessed. Articles with this focus were collected with no lower time limit and until May 2020 and were systematically reviewed according to the PRISMA guidelines. Following the initial search, 350 possible related articles were identified and transferred to the reference management software, EndNote. Of the 350 studies identified, 100 were duplicates, and therefore excluded. At the screening stage, out of the remaining 250 studies, 170 articles were removed after assessing their title and abstract and considering the inclusion and exclusion criteria. At the eligibility evaluation phase, out of the remaining 80 studies, 60 articles were removed after the examination of their full text, and similarly by considering the inclusion and exclusion criteria. At the quality evaluation stage, through the evaluation of the full text of the articles, and based on the score obtained from the STROBE checklist for each paper, out of the remaining 20 studies, 3 studies, that were assessed as low methodological quality works, were eliminated, and finally 17 cross-sectional studies reached the final analysis stage (please see Fig.  2 ). Details and characteristics of these articles are also provided in Table  1 .

PRISMA (2009) flow diagram demonstrating the stages for sieving articles in this systematic review and meta-analysis

Investigating heterogeneity and publication Bias

To investigate the heterogeneity of the studies, the I 2 (%) indices for the prevalence of stress (I 2 : 96.8%), anxiety (I 2 : 99.3%) and depression (I 2 : 99.4%) were obtained. Due to the high heterogeneity in the studies, the random effects model was used in the analysis of findings. To examine publication bias in the collected articles, the Egger’s test indices were obtained for the prevalence of stress (p: 0.304) (Fig.  3 ), anxiety (p: 0.064) (Fig.  4 ), and depression (p: 0.073) (Fig.  5 ), indicating that publication bias was not significant for any of the three clinical symptoms.

Funnel plot of results of prevalence of stress among the general population during the COVID-19 pandemic

Funnel plot of results of prevalence of anxiety among the general population during the COVID-19 pandemic

Funnel plot of results of prevalence of depression among the general population during the COVID-19 pandemic

• Meta-analysis

The prevalence of stress in 5 of the studies with a sample size of 9074 was 29.6% (95% CI: 24.3–35.4). Results of the 5 studies are evaluated by the Depression, Anxiety and Stress Scale (DASS-21) instrument (Fig.  6 ). The prevalence of anxiety in 17 studies with a sample size of 63,439 was obtained as 31.9% (95% CI: 27.5–36.7) (Fig.  7 ). Moreover, the prevalence of depression in 14 studies with a sample size of 44,531 was 33.7% (95% CI: 27.5–40.6) (Fig.  8 ).

The prevalence of stress in the studies based on the random effects model

The prevalence of anxiety in the studies based on the random effects model

The prevalence of depression in the studies based on the random effects model

Figures 3 , 4 and 5 present the Forest plots for the prevalence of stress, anxiety, and depression based on the random effects model, in which each black square is the prevalence rate, and the length of the line on which the square is located denotes 95% confidence interval. The black diamond shape represents the overall prevalence rate for the symptoms.

Subgroup analysis

Table  2 , reports the prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic in different continents. The highest prevalence of anxiety in Asia is 32.9 (95% CI: 28.2–37.9), the highest prevalence of stress in Europe is 31.9 (95% CI: 23.1–42.2), and the highest prevalence of depression in Asia is 35.3 (95% CI: 27.3–44.1) (Table 2 ).

This work is the first systematic review and meta-analysis on the prevalence of stress, anxiety and depression in the general population following the COVID-19 pandemic. This study has followed the appropriate methods of secondary data analysis for examining 17 related research works. The articles used in this study were all cross-sectional. According to our analysis, the prevalences of stress, anxiety, and depression, as a result of the pandemic in the general population, are 29.6, 31.9 and 33.7% respectively.

The emergence of COVID-19, with its rapid spread, has exacerbated anxiety in populations globally, leading to mental health disorders in individuals. This has even caused cases of stereotyping and discrimination [ 37 , 38 ]. Therefore, it is necessary to examine and recognize people’s mental states in this challenging, destructive and unprecedented time. Evidence suggests that individuals may experience symptoms of psychosis, anxiety, trauma, suicidal thoughts, and panic attacks [ 39 , 40 ]. Recent studies have similarly shown that COVID-19 affects mental health outcomes such as anxiety, depression, and post-traumatic stress symptoms [ 22 , 24 , 31 ]. COVID-19 is novel and unexplored, and its rapid transmission, its high mortality rate, and concerns about the future can be the causes of anxiety [ 41 ]. Anxiety, when above normal, weakens body’s immune system and consequently increases the risk of contracting the virus [ 39 ].

Research shows that people who follow COVID-19 news the most, experience more anxiety [ 39 ]. Most of the news published on COVID-19 are distressing, and sometimes news are associated with rumors, which is why anxiety levels rise when a person is constantly exposed to COVID-19 news [ 21 ]. Misinformation and fabricated reports about COVID-19 can exacerbate depressive symptoms in the general population [ 23 ]. The latest and most accurate information, such as the number of people who have improved and the progress of medications and vaccines, can reduce anxiety levels [ 42 ]. In this regard, mental health professionals recommend promoting healthy behaviors, avoiding exposure to negative news, and using alternative communication methods such as social networks and digital communication platforms to prevent social isolation [ 41 ].

Such conditions are even more significant for populations with poorer health conditions. In the under-developed and developing countriesthe epidemic conditions of COVID-19 impose greater psychological effects on the population, given that these countries are also affected by many other infectious diseases. Uncertainty about health status, follow-up of patients, treatment care, and inefficiency in these communities can also increase the vulnerability of such communities to the psychological effects of COVID-19 [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 ].

The results of epidemiological studies show that women are at a higher risk of depression [ 43 ]. Women are more vulnerable to stress and post-traumatic stress disorder than men [ 44 ]. In recent studies, the prevalence of anxiety and depression and stress during COVID-19 pandemic is shown to be higher in women than in men [ 21 , 23 , 27 , 31 ].

Aging increases the risk of COVID-19 infection and mortality, however, the results of existing studies show that during the pandemic, the levels of anxiety, depression and stress are significantly higher in the age group of 21–40 years. The main reason for this seems to be that this age group are concerned over the future consequences and economic challenges caused by the pandemic, as they are key active working forces in a society and are, therefore, mostly affected by redundancies and business closures [ 21 , 22 , 25 ]. Some researchers have argued that a greater anxiety among young people may be due to their greater access to information through social media, which can also cause stress [ 45 ].

During the COVID-19 pandemic, people with higher levels of education had greater levels of anxiety, depression, and stress. According to recent studies, during the COVID-19 pandemic, there is an association between education levels, and anxiety and depression levels [ 21 , 31 ]. According to a study which was conducted in China, the higher prevalence of mental symptoms among people with higher levels of education is probably due to this group’s high self-awareness in relation to their own health [ 46 ]. In addition, anxiety levels are significantly higher in people with at least one family member, relative, or a friend with the COVID-19 disease [ 21 , 24 , 42 ].

Recent studies have revealed an association between medical history and increased anxiety and depression caused by the COVID-19 spread [ 36 ]. Previous research works had shown that medical history and chronic illnesses are associated with increased psychiatric distress levels [ 42 , 47 ]. People who have a history of medical problems and are also suffering from poor health may feel more vulnerable to a new disease [ 48 ].

Governments and health officials must provide accurate information on the state of the pandemic, refute rumors in a timely manner, and reduce the impact of misinformation on the general public’s emotional state. These high level activities result in a sense of public security and potential psychological benefits. Governments and health authorities need to ensure that infrastructure is provided to produce and supply adequate amounts of personal protective equipment (PPE), e.g. masks, hand sanitizers and other personal hygiene products during the COVID-19 pandemic. Optimistic and positive thoughts and attitude toward the COVID-19 spread are also protective factors against depression and anxiety [ 23 ]. The use of electronic devices and applications to provide counseling can reduce the psychological damages caused by COVID-19, and can consequently promote social stability [ 31 ]. The rise in the number of infections and mortalities are likely to affect the symptoms of depression and anxiety. During the H1N1 epidemic, anxiety reached the highest point at the peak of the epidemic and decreased with its decline [ 49 ].

Our research has a few limitations; All of the studies in our analysis were periodic, which could reflect the psychological state of the population over a period of time. However, psychological states change with the passage of time and with the alterations in one’s surrounding environment. Therefore, it is necessary to portray the psychological impacts of the COVID-19 catastrophe over a longer and more forward-looking period. Follow-up studies can be helpful in clarifying the mental state of the population in future. Although several research works in this meta-analysis have used the same tests for population screening, yet there were a few studies that followed different scales to assess stress, anxiety and depression.

In less than a few months, the COVID-19 pandemic has created an emergency state globally. This contagious virus has not only raised concerns over general public health, but has also caused a number of psychological and mental disorders. According to our analysis, it can be concluded that the COVID-19 pandemic can affect mental health in individuals and different communities. Therefore, in the current crisis, it is vital to identify individuals prone to psychological disorders from different groups and at different layers of populations, so that with appropriate psychological strategies, techniques and interventions, the general population mental health is preserved and improved.

Availability of data and materials

Datasets are available through the corresponding author upon reasonable request.

Abbreviations

Severe Acute Respiratory Syndrome

Middle East Respiratory Syndrome

Strengthening the Reporting of Observational studies in Epidemiology

Preferred Reporting Items for Systematic Reviews and Meta-Analysis

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Gender differences in severity and parental estimation of adolescent’s pandemic-related stress in the United States

Roles Conceptualization, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

Affiliation KDH Research & Communication, Atlanta, Georgia, United States of America

Roles Supervision, Writing – review & editing

* E-mail: [email protected]

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• Andrew Simkus, 
• Kristen Holtz, 
• Morgan Fleming, 
• Eric Twombly, 
• Nicole Wanty

• Published: September 3, 2024
• https://doi.org/10.1371/journal.pmen.0000101
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Research has consistently shown that female adolescents have experienced worse pandemic-related stress compared to males. A parent’s ability to accurately track their child’s stress levels likely increases the likelihood a problem is acknowledged and addressed as it arises. Therefore, we assessed how parents’ estimation of their adolescent children’s self-reported pandemic-related stress related to the child’s gender. We performed cross-sectional secondary analysis using the nationally representative Population Assessment of Tobacco and Health study datasets from Wave 5 (2018–2019) and Wave 5.5 (July 2020-December 2020) among respondents aged 12–17. We conducted four logistic regression models to explore the relationship between child gender and parental underestimation of their child’s pandemic-related stress. We controlled for sociodemographic factors and personal characteristics associated with pandemic-related stress including, whether the adolescent had been diagnosed with COVID-19, the extent social distancing measures were practiced, school performance, previous year anxiety, depression, and overall mental health ratings, sleep trouble, TV screen time, and past year substance use. Even when controlling for these factors, female child gender was significantly and positively associated with parental underestimation of their child’s pandemic-related stress (Underestimated stress: OR = 1.25 95% CI = [1.07–1.46]). Informing parents that female adolescents were significantly more likely to have their levels of pandemic-related stress underestimated at home may encourage parents to take extra effort when checking in on their daughters’ mental health needs, which in turn may lead to more female adolescents receiving the familial and professional support they require.

Citation: Simkus A, Holtz K, Fleming M, Twombly E, Wanty N (2024) Gender differences in severity and parental estimation of adolescent’s pandemic-related stress in the United States. PLOS Ment Health 1(4): e0000101. https://doi.org/10.1371/journal.pmen.0000101

Editor: Jinjin Lu, Xi’an Jiaotong-Liverpool University, CHINA

Received: February 5, 2024; Accepted: July 20, 2024; Published: September 3, 2024

Copyright: © 2024 Simkus et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The Population Assessment of Tobacco and Health (PATH) Study deidentified public use files are publicly available. United States Department of Health and Human Services. National Institutes of Health. National Institute on Drug Abuse, and United States Department of Health and Human Services. Food and Drug Administration. Center for Tobacco Products. Population Assessment of Tobacco and Health (PATH) Study [United States] Restricted-Use Files. Inter-university Consortium for Political and Social Research [distributor], 2024-04-08. https://doi.org/10.3886/ICPSR36231.v38

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interest exist.

1. Introduction

The COVID-19 Pandemic brought many abrupt adjustments and transitions to family life. Of great concern is how pandemic-related changes affected stress levels, particularly those of developing adolescents. Studies have consistently shown that female adolescents experienced worse levels of pandemic-related mental health outcomes compared to males [ 1 – 5 ]. However, few studies have explored the potential mechanisms driving this disparity and even fewer have looked at how familial support dynamics may contribute to differences in child stress levels. Research has shown that parental support is instrumental in fortifying resiliency to stress during the pandemic [ 6 ]. However, we have not found any studies assessing differences in parental support during the pandemic based on child gender, this study aims to begin addressing this gap in the existing literature.

Because parents are often the first line of defense for their children’s wellbeing, especially during the pandemic when lockdowns and social distancing became the norm–we wondered whether parents’ ability to correctly estimate the level of their child’s pandemic-related stress differed by the child’s gender. In this study, we explored self-reported levels of pandemic-related stress among adolescents during the COVID-19 pandemic and whether parental estimations of their adolescent child’s pandemic-related stress differed significantly based on the child’s gender.

Adolescence is an important period in which the development of healthy emotional and social habits is ideally established for long-term psychological well-being. In adolescence, youth learn and hopefully adopt healthy sleep and exercise patterns, coping mechanisms, interpersonal skills, emotional regulation, and problem-solving skills [ 7 ]. Such skillsets are typically developed naturally through experience and typical social encounters. But when the pandemic surged in 2020, adolescents suddenly faced a tremendous number of social changes–suspension of in-person school, social-distancing from friends and relatives, and an array of often-haphazard adaptations to in-home roles, routines, and schedules. These stressors may have lasting impacts. While pandemic-related stress stemmed from a combination of factors, perhaps most detrimental was forced social isolation [ 8 ].

Numerous negative adolescent outcomes have been associated with the stress related to the COVID-19 pandemic including increased uptake of tobacco and prescription drug use [ 9 ], increased frequency of alcohol and marijuana use [ 10 ], lower health related quality of life ratings [ 11 ], increased anxiety [ 11 ], mental health struggles [ 11 ], and post-traumatic stress [ 12 ]. Prior to the pandemic, longitudinal research has correlated adolescent stress from social isolation with detrimental physical, cognitive, and behavioral health outcomes later in adulthood including increased levels of inflammatory biomarkers, depression, and the clustering of metabolic risk markers [ 13 , 14 ]. There is concern that adolescents who experienced high levels of pandemic-related stress may encounter more severe mental health struggles and larger social deficits moving forward.

Overall, the effects of adolescent psychosocial stress are known to vary by gender [ 15 ]. Indeed, the Centers for Disease Control and Prevention (CDC) reported that in 2021 nearly 60% of high school females encountered persisting feelings of hopelessness or sadness, with almost 25% actually making a plan for suicide. The percentage of female high school students who have seriously considered attempting suicide within the past year has risen 11 percentage points from 19% in 2011 to 30% in 2021 while the percentage for high school males has remained largely unchanged from 12% to 13% [ 16 ].

Studies have shown that adolescents tend to vary by gender in their preferred coping mechanisms for dealing with stress. O’Rourk et al., (2022) found that females were more likely than males to make use of social supports in effort to alleviate stress [ 17 ] a scarcely available strategy during a pandemic when social distancing is mandated, and periods of isolation are increased.

Given overarching findings about adolescent females and stress, it is unsurprising that studies worldwide find that adolescent females struggle with higher pandemic-related stress than adolescent males [ 1 – 4 ]. If female adolescents are experiencing disproportionate degrees of pandemic-related stress, they may also be at increased risk of detrimental mental health and behavioral outcomes both immediate and later in adulthood. In efforts to narrow the potential gender divide in health outcomes, it is important to thoroughly explore contributing factors to this gender disparity.

Female adolescents have been found to be more likely than males to report experiencing distress from pandemic-related changes to their day-to-day lives and school performance [ 18 ]. While a multitude of social, biological, and behavioral differences help explain gender differences observed in pandemic-related stress levels, this paper specifically examines the role of parental social support. We explore how parents perceive their children’s level of stress, surmising that awareness may affect the parents’ ability to accurately track, identify, and respond to their children’s stress levels and respond accordingly. Parental underestimation of adolescent stress levels likely relates to adolescents receiving less support and worsening degrees of stress over time. Lower parental support during stressful life events has been linked to increased substance use among adolescent females [ 19 ]. And, because it is well known that tobacco, alcohol, and other substances are often used by adolescents as stress coping mechanisms, child substance use could potentially further affect a child’s behavior, and in turn, the ability of parents to identify the level of pandemic-related stress their child is experiencing, worsening this cyclical relationship.

Parents and guardians also experienced majorly stressful transitions during the pandemic because of remote schooling, work changes, and mandated quarantines/home isolation. Heightened parental stress likely aggravates family dynamics. Lockdowns have been associated with worsened family mental health outcomes including depression and anxiety [ 20 , 21 ]. Higher degrees of home isolation have been associated with heightened familial conflicts and worsening adolescent psychosocial adjustment [ 22 ]. These changes and often coinciding conflicts may further hinder parents’ abilities to track their children’s emotional states.

De Los Reyes et al. (2015) conducted meta-analysis across 341 studies to assess agreement on reporting of child internalizing behaviors and found higher agreement between parents than between parent and child [ 23 ]. Lopez-Perez & Wilson (2015) assessed parent-child discrepancies in adolescent happiness and found that parents of younger children were more likely to overestimate happiness while parents of adolescent children were more likely to underestimate happiness [ 24 ]. They also found that parents’ own self-reported ratings of happiness were more strongly associated with the parents’ ratings for their adolescent’s happiness than with the adolescent’s self-reported ratings, suggesting a degree of self-bias in parental emotional assessments of their children.

Parents/guardians are usually the first to recognize signs of stress and mental unwellness in their children and are the ones responsible for helping support their child in finding help when something is wrong. But to what degree are parents able to accurately identify their adolescent child’s level of pandemic-related stress? Is an adolescent’s gender associated with their parents underestimating the degree their child is suffering from pandemic-related stress? Our main goal in this study is to assess whether the odds of parents underestimating their child’s pandemic-related stress statistically differ depending on the child’s gender.

Because research has consistently found that female adolescents experienced worse levels of pandemic-related stress compared to males, we hypothesize that 1) female adolescents would report higher self-ratings of pandemic-related stress than male adolescents; and 2) there would be less congruence between parent estimation of their child’s stress and the child’s self-rating by child’s gender, which we refer to as parental underestimation.

Portions of the methods reported here were used previously by Holtz and colleagues [ 25 ]. We used the Population Assessment of Tobacco and Health (PATH) study’s anonymized public-use data files for this analysis [ 26 ] with exempted review due to secondary data analysis from KDH Research & Communication (KDHRC) internal IRB, FWA00011177, IRB 00005850. The PATH study was launched in 2011 through collaboration with the Food and Drug Administration (FDA) and the National Institutes of Health (NIH) to study tobacco use in the United States and track related health effects over time. Findings from the PATH study data have been used to inform the FDA’s regulatory policies on tobacco marketing, manufacturing, and distribution [ 27 ].

The PATH study used a four-stage stratified probability sampling to select youth and adult participants [ 27 ]. Strengths of the PATH study data include its complex longitudinal design, scope of behavioral and psychographic questions, and national representativeness. Analyses of non-response bias in the PATH study may be found in the PATH study non-response reports online with information on each Wave in the Special Collection Public-Use Files User Guide [ 28 ].

PATH study data have been collected via telephone from youth respondents and one of their parents/guardians in waves each year since the initial launch. Each observation in the data represents answers from a youth respondent and usually includes youth and household related information provided by one of the youth respondent’s parents/guardians [ 26 ]. The sample was replenished at Wave 4 to replace aged out youth, thus, there are two cohorts with baselines at Wave 1 and Wave 4. The weighted response rate was 66.8% for Wave 5.5 youth.

This study examines the most recent available youth data from Wave 5.5 (July 2020-December 2020). The PATH study treated “I don’t know” answers and skip errors as missing in the data. We treated cases marked “prefer not to answer” as missing and excluded observations with missing data from our analyses for all variables. We used the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) for guidance in our reporting [ 29 ].

We hypothesized that: 1) female adolescents would report higher self-ratings of pandemic-related stress than male adolescents; and 2) there would be less congruence between parent estimation of their child’s stress and the child’s self-rating by child’s gender, which we refer to as parental underestimation.

In this study we account for important personal and social characteristics that may affect pandemic-related stress among adolescents and/or parental estimation of their child’s stress, including sociodemographic variables [ 30 , 31 ], parental education [ 32 ] whether the adolescent had been diagnosed with COVID-19 [ 33 ], body mass index (BMI) [ 34 ], physical activity [ 35 ], adolescent sleep trouble [ 36 ], TV screentime [ 37 ], the extent of social distancing practiced [ 38 ], prior anxiety and depression levels [ 39 ], prior overall mental health [ 40 ], parental marital status [ 40 ], school performance [ 41 ], past year tobacco use [ 42 – 45 ], and whether the adolescent reported using alcohol and/or illicit drugs during the past year [ 46 ].

2.1 Study population

PATH study youth participant eligibility included nonincarcerated, noninstitutionalized citizens of the United States aged 12 to 17, living in the United States at the time of the survey. The final sample included 6,813 youth respondents, representing a population of 18,824,942 United States youth between the ages of 12 and 17.

2.2 Measures / data classification

Because stable demographic covariates were only inquired about at each baseline, age, gender, race, and ethnicity were all collected at Wave 1 or Wave 4, depending on the cohort of the respondent. Prior overall mental health, anxiety, and depression were all taken from the previous PATH study Wave 5 to assess pre-pandemic levels, all other variables are from Wave 5.5, the most recent data available. In S1 Table , we provide operational definitions for each of the covariates used in our analyses.

2.3 Main independent variable

We created a dummy variable for gender where 1 represented a respondent who was female and 0 represented a respondent who was male.

2.4 Dependent variable

Parental underestimation..

We used the following two questions to create a variable for parental underestimation of their child’s pandemic-related stress rating.

• Youth respondents were asked to provide, “ Rating of your experience of stress related to the coronavirus pandemic that spread to the US around January 2020 ”. Answer choices included: “None” ; “Mild (such as occasional worries; feeling a little anxious , sad , or angry; or having mild trouble sleeping)” ; “Moderate (such as frequent worries; feeling moderately anxious , sad , or angry; or having moderate trouble sleeping)” ; and “Severe (such as persistent worries; feeling extremely anxious , sad , or angry; or having severe trouble sleeping)” .
• Parents were asked to provide, “ Rating of your child’s experience of stress related to the coronavirus pandemic that spread to the US around January 2020 . Answer choices included: “None” ; “Mild (such as occasional worries; feeling a little anxious , sad , or angry; or having mild trouble sleeping)” ; “Moderate (such as frequent worries; feeling moderately anxious , sad , or angry; or having moderate trouble sleeping)” ; and “Severe (such as persistent worries; feeling extremely anxious , sad , or angry; or having severe trouble sleeping)” .

We created a dummy variable where 1 represented a parent whose overall rating was lower than that of their child’s, and 0 represented a parent whose overall rating was higher or equal to that of their child’s.

2.5 Statistical analysis

We used STATA 16.1 to conduct statistical analyses. We ran a two-group t-test between adolescent male and female ratings of pandemic-related stress, then conducted four multivariate logistic regression models to determine whether parental underestimation of their child’s pandemic-related stress was associated with gender. Across these four models we added three general categories of covariates because each may impact both adolescent pandemic-related stress and parental observations of such stress. We began by adding sociodemographic and health related variables, then added psychographic/behavioral variables, and in the final model included variables related to substance use:

Model 1 was an unadjusted model. In Model 2, we adjusted for respondent sociodemographic and health related characteristics including age, gender, race/ethnicity, parental education, parental marital status, income, BMI, and whether the adolescent had been diagnosed with COVID-19. In Model 3, we inserted additional controls for psychographic and behavioral variables associated with pandemic-related stress including physical activity, TV screen time, sleep trouble, social distancing measures practiced, previous year anxiety, previous year depression, and perceptions of overall mental health the previous year. We further adjusted Model 4 to include all previous controls and added substance use variables which may be related to adolescent stress including past year usage of tobacco, alcohol, marijuana, painkillers, and hallucinogens. Statistical significance was set at p < 0.05.

The design of the PATH study oversamples tobacco users and is susceptible to attrition due to its longitudinal nature; there are several available weights to adjust for these issues depending on the type of analyses and waves being assessed [ 27 ]. We used the svyset procedure with Wave 5.5: Youth/Parent ‐ Wave 4 Cohort All-Waves Weights to adjust for oversampling and nonresponse. Our estimates were computed with balanced repeated replication (BRR) using Fay’s adjustment value of 0.3 based on the PATH study user guide [ 26 ].

Table 1 presents youths’ characteristics according to whether their parents underestimated their level of pandemic-related stress during Wave 5.5. Non-Hispanic White was the most prevalent race (52.58%), most were in the 15–17 age group (60.74%), and males had a slight majority (51.27%). Nearly a quarter of adolescents had a parent that underestimated their level of pandemic-related stress (23.84%). Among female adolescents, 27.38% had a parent or guardian underestimate their rating of pandemic-related stress, compared to 20.48% of adolescent males. Pandemic-related stress ratings ranged from 1 (none) to 4 (severe). We confirmed that female adolescents had significantly higher average ratings of pandemic-related stress (2.09) compared to males (1.75), p<0.001.

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https://doi.org/10.1371/journal.pmen.0000101.t001

Table 2 presents the results of the four logistic regression models that explore the relationship between parental underestimation of their adolescent child’s pandemic-related stress and the child’s gender at Wave 5.5. Across all four models female adolescents had statistically significantly higher odds of having their pandemic-related stress ratings underestimated by their parent/guardian compared to males.

https://doi.org/10.1371/journal.pmen.0000101.t002

3.1 Sensitivity analyses

The significance of parental underestimation of female adolescents’ pandemic-related stress scores at Wave 5.5 was upheld across all four models, showing the results were not sensitive to changes in the variables included. To assess selection bias, we also ran each of the four logistic regression models after replacing missing data with each variable’s median values. Results were similar across all four models, suggesting that the missing values do not cause selection bias.

We checked the variance inflation factor (VIF), which reveals how much of the coefficient estimate’s variance is inflated due to multicollinearity [ 47 ]. There were moderately high VIF scores for three categories in the control variable for income and three categories in the control variable for parental education; however, the VIF value for gender in Model 4 was 1.16 showing low collinearity between the independent variable and the control variables.

4. Discussion

All four logistic regression analyses on Wave 5.5 of the PATH study illustrated that female adolescents experienced significantly higher odds of having a parent/guardian underestimate their pandemic-related stress ratings compared to adolescent males, revealing an additional potential mechanism or contributor to the recent findings that female adolescents are faring worse in terms of pandemic-related mental health struggles than males [ 1 – 4 ]. Because a parent/guardian’s ability to accurately track their child’s stress levels likely increases the likelihood a problem is acknowledged and addressed when it arises, disproportionate underestimation of female pandemic-related stress may decrease the chances that adolescent females receive additional support at home or professionally. Our exploration of the relevant literature highlights a lack of research on parental ability to track their children’s stress levels, especially during the COVID-19 pandemic. Future research should explore factors associated with adequate parental assessment of their children’s stress levels and whether parental underestimation of their adolescent child’s pandemic-related stress may predict longer-term psychosocial and behavioral struggles.

Research has confirmed the importance of parental ability to support their children in increasing their child’s resiliency to stress during the pandemic [ 6 ]. Intuitively, a parent’s ability to support their child begins with the ability to observe and estimate the level of stress their child is experiencing. Our findings show that levels of adolescent female pandemic-related stress were often underestimated by parents, suggesting that levels of parental support for female children in particular may have been suboptimal. There are a multitude of factors that may help explain why parental estimation of their child’s pandemic-related stress differs significantly by the child’s gender. Compared to adolescent females, research has found adolescent males demonstrate significantly higher externalizing behaviors such as aggression, [ 48 , 49 ] parents may translate increased aggressive behavior as an indicator of their adolescent child’s stress levels, an indicator which female adolescents were less likely to present. Another possible explanation for this finding is response bias, where males may have reported lower stress ratings out of insecurity regarding being viewed as weak. Parents may be overconfident in their daughters’ coping abilities, or daughters may be more adept at hiding their stress levels.

Pandemic-related studies have confirmed that regardless of age ‐ depression and somatic symptoms such as pain significantly increased among females during the pandemic but not for males [ 50 , 51 ]. Hawes et al., (2022) identified a three-fold increase in elevated depression rates among females during the pandemic compared to prior to the pandemic [ 50 ]. Alarmingly, they also found that almost 60% of the females in their study met the clinical threshold for at least one mental health disorder during the COVID-19 pandemic [ 50 ]. Hawes and colleagues surmised that their findings could be due to heightened exposure to stressors or a stronger response to stress among females during the pandemic [ 50 ]. Accordingly, studies have shown that even though females are less likely to experience potentially traumatic events (accidents, assault, combat, etc.) compared to males they are more prone to developing internalizing symptoms such as post-traumatic stress disorder [ 52 ].

Because these experiences during the pandemic may relate to worsening degrees of stress over time, it is important that parents are made aware that the gendered differences in stress responses and can intervene accordingly to support their children.

4.1 Study limitations

While the findings in this study provide important implications for future research regarding pandemic-related stress among adolescents, there were limitations which we were unable to address. For one, the PATH study used one question with four answer choices to estimate overall pandemic-related stress levels, further insights could be gained with more specific questions that detail different aspects of the pandemic which were stressful, along with wider ranged Likert-type scales for ratings. We were unable to find any study seeking to validate the sensitivity or specificity of this survey question. The use of more detailed questions regarding specific stressors such as social distancing, remote schooling, and fear of infection could reveal more robust insights. We were further limited in our ability to control for parental psychosocial covariates that could impact parental estimation of their child’s wellbeing. For example, we had no parental self-reports of pandemic-related stress to assess or control for parental bias in ratings.

5. Conclusion

Using a nationally representative sample of adolescents across the United States aged 12 to 17, we investigated the relationship between adolescent gender and parental estimations of their adolescent child’s pandemic-related stress. We confirmed that female adolescents experienced higher levels of pandemic-related stress compared to males. We also discovered that female adolescents had significantly increased odds of having their pandemic-related stress underestimated compared to adolescent males, even when controlling for relevant covariates. These findings are particularly pertinent for parents, but also for researchers, counselors, school personnel, and others directly engaged in fostering the healthiest outcomes for adolescents who are currently transitioning back to normal life.

Decreasing gender divides in mental and physical health outcomes is an important public health concern, which, after the pandemic’s toll, may warrant the promotion of additional screenings and supports for female adolescents. Parents are the front line in protecting and supporting their children and as such must be informed by research about how to better identify and address their child’s stress levels.

The transitions and restrictions that accompanied the COVID-19 pandemic took a tremendous toll on adolescents during a particularly impressionable period of their emotional and social development. As research continues to identify potential reasons why female adolescents are faring worse than males in response to the pandemic experience, we can develop more informed strategies in efforts to mitigate future gender divides in health outcomes.

Informing parents how female adolescents experienced significantly higher levels of pandemic-related stress yet were also significantly more likely to have their levels of stress underestimated at home may help persuade parents to take a different approach to checking in on their daughter’s mental health, which may lead to more adolescent girls receiving the familial and professional support they require.

Supporting information

S1 table. covariates used in analyses..

This table presents each covariate used in the analysis with its definition and coding notes.

https://doi.org/10.1371/journal.pmen.0000101.s001

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Anxiety Evolution among Healthcare Workers—A Prospective Study Two Years after the Onset of the COVID-19 Pandemic Including Occupational and Psychoemotional Variables

Fernanda gil-almagro.

1 Psychology Deparment, Universidad Rey Juan Carlos, Av. de Atenas, s/n, 28922 Madrid, Spain; moc.liamg@orgamlaligf (F.G.-A.); [email protected] (C.P.-P.)

2 Nurse Intensive Care Unit, Hospital Universitario Fundación Alcorcón, Budapest, 1, 28922 Madrid, Spain; moc.liamg@haicragjf

Fernando José García-Hedrera

Cecilia peñacoba-puente, francisco javier carmona-monge.

3 Anesthesia Department, Hospital Universitario Santiago de Compostela, Rúa da Choupana, s/n, 15706 A Coruña, Spain

Associated Data

Research data will be available upon request to the corresponding author.

Background and objectives: Although previous research has found a high prevalence of anxiety during the COVID-19 pandemic among healthcare workers, longitudinal studies on post-pandemic anxiety and predictor variables have been less abundant. To examine the evolution of anxiety in healthcare workers from the beginning of the pandemic until one and a half years later, analyzing the influence of occupational and psychosocial variables, as well as their possible predictors. Materials and Methods : This was a prospective longitudinal design with three periods of data collection: (1) between 5 May and 21 June 2020, (2) six months after the end of the state of alarm (January–March 2021), and (3) one year after this second assessment (April–July 2022), in which generalized anxiety (GAD-7) was evaluated, as well as occupational and psycho-emotional variables (i.e., social support, self-efficacy, resilience, and cognitive fusion) in healthcare workers in direct contact with COVID-19 patients in Spain. Results : A high prevalence of anxiety was found, with a clear decrease over time. Associations were found between anxiety and certain sociodemographic and work variables (i.e., years of experience, p = 0.046; COVID-19 symptoms, p = 0.001; availability of PPE, p = 0.002; workload, p < 0.001; family contagion concern, p = 0.009). Anxiety maintained negative relationships with social support ( p < 0.001), self-efficacy ( p < 0.001), and resilience ( p < 0.001) and positive associations with cognitive fusion ( p < 0.001). Cognitive fusion seemed to be a clear predictor of anxiety. Conclusions : Our findings suggest that social support, self-efficacy, and resilience act as buffers for anxiety, whilst cognitive fusion was found to be a clear risk factor for anxiety. It is important to emphasize the risk role played by cognitive fusion on HCWs as a clear risk factor for stressful work events. The findings emphasize the need to implement specific interventions to promote the mental well-being of healthcare workers, particularly in crisis contexts such as the COVID-19 pandemic.

1. Introduction

Data recorded in the aftermath of the COVID-19 pandemic have shown that healthcare workers (HCWs) have suffered psychoemotional disturbances derived from this stressful work situation [ 1 , 2 , 3 ], added to the complicated situation in Spain resulting from the pandemic itself. In Spain, the state of alarm was decreed on 14 March 2020, leading to a subsequent phase of home confinement of the population. The end of the state of alarm was 9 May 2020. However, movements between autonomous communities were not allowed until 21 June 2020. One of the most studied consequences on HCWs following the COVID-19 pandemic has been anxiety [ 4 , 5 ], having found a high prevalence among HCWs in the early stages of the pandemic. Prior to the pandemic, several studies had already shown a high prevalence of anxiety among HCWs, and this was found to be due to several work-related variables, such as the fear of making mistakes in the administration of medication, the high workload, or the carrying out of care activities in highly complex units, such as intensive care units (ICU) [ 6 , 7 ]. During the pandemic, new studies were developed on anxiety in HCWs and its consequences on their emotional health, showing a clear increase in its prevalence derived from the fear of contagion or bedside work with infectious patients [ 8 , 9 ]. Specifically, most of the studies found a high prevalence of generalized anxiety, measured mostly using the Generalized Anxiety Disorder (GAD-7) instrument [ 10 , 11 ].

During the COVID-19 pandemic, anxiety was analyzed in the general population and in HCWs, showing a higher prevalence of anxiety suffered by HCWs, being especially high in the case of physicians and nurses (OR = 1.9, 95% CI: 1.367–2.491, p < 0.001) [ 12 ]. Most of the research published to date was carried out at the beginning of the pandemic, covering the period up to the summer of 2020. The data collected worldwide indicated moderate to severe anxiety, with percentages ranging between 20% and 60% [ 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. In HCWs, these anxiety levels remained stable until the end of 2020 [ 20 , 21 , 22 , 23 ].

China has been one of the most studied contexts, likely because it is the country where the pandemic started, presenting high anxiety averages for HCWs. In China, a prevalence of anxiety between 45% and 60% was found in HCWs in 2021 [ 24 ], which is considerably higher than that of the general population of China [ 25 ]. Anxiety studies conducted in China subsequently, coinciding with new hospitalization peaks, reflect figures between November 2022 and February 2023 of close to 50% anxiety prevalence among HCWs [ 26 ].

However, the study of long-term anxiety after the critical stage of the pandemic has not been frequent. To understand the real impact and the variables involved in the evolution of anxiety, studies based on the time after the acute stress of the onset of the pandemic, which could reveal factors that act as buffers or chronifiers of anxiety, are essential. Thus, longitudinal studies based on the long-term evolution of anxiety and the variables involved are necessary, as the only scientific evidence currently available is focused on the evolution of pandemic anxiety until 2021 [ 27 , 28 ].

Different longitudinal studies have shown a prevalence of anxiety in nurses of 43.1% during confinement and 16% a few months later [ 29 ]. Research carried out in the USA also found a decrease in the levels of generalized anxiety, from 46.3% to 23.2% [ 28 ]. Longitudinal studies carried out in Spain suggest that the improvement in anxiety levels over time is not so evident, indicating similar percentages of anxiety prevalence during the first and second waves [ 10 ].

Studies carried out in Spain and the U.S.A. that analyzed the influence of sociodemographic and occupational variables on the anxiety suffered by HCWs during the COVID-19 pandemic have suggested that several variables acted as risk factors, some of which were the fear of contagion, the development of care activities with infectious patients, the high workload, or the scarcity of personal protective equipment (PPE) [ 30 , 31 ]. Other studies from China have found that working in highly complex units such as the ICU is an added risk factor for the development of anxiety [ 32 ]. Similarly, a systematic review including different studies from China and Singapore indicated a higher prevalence of anxiety in nurses than in physicians during this time [ 9 ].

However, studies analyzing the influence that different psychosocial or personality variables have had on anxiety during the COVID-19 pandemic are not as abundant. Most of the available studies have focused on the influence of resilience, stating that low levels of resilience negatively affected the evolution of anxiety in HCWs at this time [ 33 ]. Likewise, different studies have pointed out the positive effect that social support, hobbies, or a healthy lifestyle had on the evolution of anxiety [ 34 ]. The study of cognitive fusion has shown a clear relationship between high levels of cognitive fusion and high levels of anxiety among HCWs [ 35 , 36 ]. Meanwhile, self-efficacy allows cushioning of the negative consequences of anxiety, such as burnout, facilitating better management of negative emotional states [ 37 ].

Most studies evaluating the influence of different psychosocial or personality variables on anxiety have focused on a specific time point, without considering the consequences that these variables may have had on the evolution of anxiety in later phases. Some studies call these later phases of the pandemic “the post-pandemic era of COVID-19” [ 38 ]. Because of this approach, it is particularly relevant to conduct prospective studies in the mid- and long-term, allowing us to explore not only the evolution of anxiety and its possible chronification but also the possible precipitating or dampening factors involved in its evolution.

The aim of the present study was to analyze the evolution of anxiety, using the GAD-7 questionnaire, in a sample of HCWs who were in direct contact with infectious patients during the first stage of the COVID-19 pandemic. The professionals were followed up at two additional time points, six months after the initial assessment and one year later. As additional aims, we analyzed the association of anxiety and its evolution with sociodemographic, occupational, and personality variables in order to find out the possible predictors that affected the evolution of anxiety among HCWs during and after the COVID-19 pandemic.

2. Materials and Methods

2.1. design.

A prospective longitudinal study was carried out with three data collection periods: (1) between 5 May and 21 June 2020 (the final phase of the state of alarm and confinement, declared in Spain on 14 March), (2) six months after the end of the state of alarm (January–March 2021), and (3) one year after this second assessment (April–July 2022). During the first data collection period, Spain was in a state of alarm from 14 March, which decreed a confinement phase, until 28 April, at which time a de-escalation began, culminating in the end of the state of alarm and population confinement on 21 June 2020. During the second data collection period, the situation was still complicated with 3,347,512 confirmed cases and 76,328 deaths as of 9 April 2021. The third data collection period ended with 12,973,615 confirmed COVID-19 cases and 108,730 deaths. During the three time periods, participants’ generalized anxiety was assessed for its evolution. Sociodemographic and occupational variables were evaluated at the first time point, while variables related to personality were assessed during the first and second time points ( Table 1 ).

Variables collected at different time points.

2.2. Procedure and Participants

The research team designed an electronic questionnaire for data collection in which all the variables to be studied were included and the different validated instruments were attached. Informed consent was requested from the participants, as well as an e-mail if they were interested in participating in the following phases of the research evaluation.

The sample consisted of HCWs belonging to the Spanish National Health System. Probabilistic convenience sampling was carried out with the following inclusion criteria: being a nurse, physician, or nursing care technician; carrying out healthcare activities in a public or private service of the National Health System; being 18 years old or older; and having been in direct contact with COVID-19 patients. The following criteria were used as exclusion criteria: having been on sick leave during the data collection period or performing healthcare activity in the field of health management.

A minimum study population of 120 was taken as the reference figure established for prospective studies [ 39 ]. In addition to the complicated circumstances of the COVID-19 pandemic, we have to take into account the fact that the study was conducted in a longitudinal manner [ 40 , 41 ]. Therefore, a minimum sample size of 400 participants was established for the first time point, obtaining a total sample of 1374 HCWs during this period. Of these, 881 continued to participate in the second time point; of these, 257 continued to participate in the third assessment, constituting the final sample of the study, well above the 120 initially estimated.

To obtain the sample, the link with the questionnaire was sent to HCWs belonging to the Spanish health system, both public and private, distributing the questionnaire through social networks (Facebook, LinkedIn, Twitter, and WhatsApp), in addition to the corporate e-mails of the different public and private services of the National Health System. For the circulation of the questionnaire during the second and third time points, the e-mails of the HCWs who had participated in the first evaluation were used, requesting their participation again in the following phases of the study.

2.3. Variables and Instruments

2.3.1. generalized anxiety [time point 1, 2 and 3].

The presence of symptoms of generalized anxiety disorder was evaluated using the Generalized Anxiety Disorder (GAD-7) [ 42 ] in its Spanish version [ 43 ]. It consists of a 7-item scale with a Likert-type response format, consisting of a 4-point scale ranging from 0 (not at all) to 3 (almost every day), with a total score range from 0 to 21. Four severity groups are established with the following cut-off points [ 42 ]: no anxiety/minimal (0–4), mild (5–9), moderate (10–14), or severe anxiety (15–21). Internal consistency in our sample was excellent at all three time points, with Cronbach’s alpha coefficients of 0.93, 0.93, and 0.94, respectively.

2.3.2. Sociodemographic and Occupational Variables [Time Point 1]

An ad hoc questionnaire developed by the research team was used to collect these data. Specifically, these data were sociodemographic data (age, gender, and family situation), work data (category, service, work experience in years, availability of PPE, workload (less, equal, or greater than usual)), and concerns about contagion (their own or a family member’s (with a 4-point Likert-type response format (from 1 “not at all concerned” to 4 “very concerned”)).

2.3.3. Personality Variables [Time Points 1 and 2]

• - Social support [time point 1]: measured using the Spanish version [ 44 ] of the Multidimensional Scale of Perceived Social Support (MSPSS) [ 45 ], which is composed of 12 items divided into three dimensions: family, friends, and significant others, with a 7-point Likert-type response scale (from 1 “completely disagree” to 7 “completely agree”). The final score comes from the sum of its three subscales. The instrument has good properties [ 46 , 47 ], and for our study, its reliability was α = 0.85 for the general questionnaire, while for the subscales, the α values obtained were 0.81, for family, 0.82 for friends, and 0.79 for significant others.
• - Self-efficacy [time point 1]: The Spanish version of the General Self-Efficacy Scale (GSES) [ 48 ] was used, consisting of 10 Likert-type items scoring from 1 “completely disagree” to 4 “completely agree,” with the total score ranging from 10 to 40. This instrument, in our study, presented high internal consistency α = 0.91.
• - Resilience [time point 1]: we used the Spanish version of the Resilience Questionnaire (RS-14) [ 49 ], made up of 14 Likert-type items with 7 alternatives, scoring from 1 “strongly disagree” to 7 “strongly agree”, with a total score ranging from 14 to 98, whereby higher scores indicate greater resilience. In our study, α was 0.94.
• - Cognitive Fusion [time point 2]: The Spanish version [ 50 ] of the Cognitive Fusion Questionnaire (CFQ) [ 51 ] was administered, which is made up of 7 Likert-type items with 7 response options, ranging from 1 “never” to 7 “always”, whereby higher scale scores imply a higher degree of cognitive fusion. A Cronbach’s α of 0.97 was obtained for our study.

2.4. Data Analysis

Descriptive analysis and Cronbach’s alpha were performed. Qualitative variables were described with frequencies (n) and percentages (%) and quantitative variables with means (M) and standard deviations (SD). To analyze the bivariate association between variables (analysis of possible covariates), Student’s t -test, one-factor analysis of variance (ANOVA), and Pearson’s correlations were used, depending on the nature of the variables analyzed. A linear regression analysis was performed to define the weight of the personality variables at each of the time points, following the stepwise method to introduce the predictor variables. Statistical analysis was performed with the Statistical Package for the Social Sciences (SPSS), version 21 for Windows. The results were considered statistically significant for values of p < 0.05.

3.1. Description of the Sociodemographic, Occupational, and Personality Variables of the Sample

Table 2 shows the sociodemographic, occupational, and health data of the 257 participating HCWs, represented by frequencies, percentages, means, and SD. Of them, 210 (81.7%) were female and the mean age was 43.67 years old (SD 9.78). Most participants were nurses 151 (58.8%), followed by physicians 65 (25.3%), whilst 41 (16.0%) were other types of HCWs. The most represented service was the ICU with 94 HCWs (36.6%), followed by hospitalization with 73 HCWs (28.4%). The mean number of years of experience in the service in which they worked was 10.70 (SD 9.23). Of the sample, 195 HCWs (75.9%) were very worried about their own and/or a family member’s infection. Fifty-one professionals (19.8%) requested psychological help. The scores of the instruments used to describe the different personality variables of the participants are shown in Table 2 .

Sociodemographic and health characteristics. Association between the different variables and anxiety.

3.2. Description of Anxiety in HCWs and Its Evolution over Time

The sample presented the highest mean score for the anxiety scale (10.82; SD = 5.86) at the first time point, and for the score compatible with severe anxiety symptoms, a downward trajectory was found at the following data collection points ( Table 3 and Figure 1 ). At the third time point (T3), HCWs presented a mean score of 7.61 (SD = 5.13), compatible with moderate anxiety symptoms. Statistically significant differences were observed between the three time points. Table 4 shows the evolution over time of anxiety levels. Moderate and severe anxiety were more prevalent at T1, whilst mild and moderate anxiety were more frequent at T3. Thus, at T1, the total number of HCWs with symptoms compatible with moderate and severe anxiety was 148 (57.6%) and with minimal and mild anxiety was 109 (42.4%), while these values appeared inverted at T3, reaching 32.7% and 67.3%, respectively.

Anxiety averages for the sample at the different time points.

Anxiety at each of the time points of data collection.

Anxiety level percentages at each of the time points of data collection.

1 Anxiety Moderate/Severe 2 No anxiety/Minimal.

3.3. Associations between Anxiety and Sociodemographic, Professional, Occupational, Health, and Personality Variables of the Sample

Table 1 shows the relationship between anxiety at the three time points and sociodemographic, occupational, and psychosocial variables. Women showed significantly higher anxiety scores than men at all three time points ( p < 0.004). Physicians showed lower anxiety scores than the other HCWs at T1 ( p = 0.048), a difference that does not occur at any other time point with any other HCW. At none of the time points were there differences in anxiety scores depending on the service in which HCWs performed their activity.

Although it does not hold at all time points, work experience in the current unit at T1 was significantly associated with anxiety ( p = 0.046), whereby professionals with less experience had higher anxiety scores. Higher workload was significantly related to higher anxiety scores at T1 and T2 ( p < 0.001). Similarly, the lack of availability of PPE was significantly related to higher anxiety scores at all time points ( p = 0.002).

HCWs who sought psychological help at all time points showed significantly higher anxiety scores ( p = 0.001). Social support was associated with lower anxiety scores, mainly on the friend subscale, which was significant at all time points ( p < 0.001).

In relation to the psychological variables, all of them were significantly associated with anxiety at all time points. Self-efficacy and resilience presented a significant and negative correlation (r = −0.347, p < 0.001; r = −0.269, p < 0.001) while cognitive fusion presented a significant and positive correlation (r = 0.539, p < 0.001).

3.4. Linear Regression Analysis between Anxiety and Personality Variables

A linear regression using a stepwise approach was carried out for anxiety and the different psychological variables that presented significant associations with it at each of the time points. The final models are presented in Table 5 , including only the variables that were statistically significant in the proposed models. The model explained 35.2% of the variance at T1, 51.1% of the variance at T2, and 27.2% of the variance at T3.

Linear regression analysis between anxiety and the different personality variables.

4. Discussion

In the present study, a group of HCWs working with COVID-19 patients at the beginning of the pandemic were followed up over time (more than two years) to evaluate the evolution of their anxiety, as well as to assess possible factors that may help to control or worsen it. In general, our results show a decrease in the levels of anxiety perceived by HCWs, although with a smaller reduction than that found in other studies carried out with a shorter follow-up time [ 31 , 52 ]. A relevant aspect of our study was the inclusion of cognitive fusion, which has only very recently been studied in the literature. In our sample of HCWs, this variable was shown to be a precipitator of anxiety, interfering in its evolution, having found that HCWs with high levels of cognitive fusion presented worse anxiety evolution. In addition, self-efficacy, resilience, and social support from friends were shown to be buffers.

As already mentioned, anxiety is a very common symptom among HCWs, the prevalence of which increased during the COVID-19 pandemic due to several socio-occupational factors [ 30 , 53 ]. However, the number of studies that have attempted to carry out a long-term follow-up of this situation has been very scarce, making it difficult to define psychological, occupational, or personal aspects that may facilitate or protect the appearance of this type of disorder, with this being one of the main strengths of our study.

The present study shows a significant decrease in the anxiety levels of HCWs across the three time points, showing lower means for anxiety symptoms in the last time point compared to the beginning of the pandemic, with statistically significant differences between each time point. These results are consistent with previous research assessing the evolution of anxiety in HCWs [ 28 ].

With regards to the possible sociodemographic and occupational variables involved, our findings show the association of gender; specifically, being a woman was predisposed to developing increased levels of anxiety. Previous studies conducted in Taiwan support a clear association between being female and higher levels of anxiety [ 6 ]. In our study, younger professionals had higher levels of anxiety at the first time point. In terms of the professional category, nurses and nursing care technicians had higher anxiety scores at the three time points compared to physicians, with this difference being significant at the first time point ( p = 0.048). Previous research has also placed the youngest professionals at the top of the list [ 54 , 55 ] and bedside caregivers as the category most likely to experience elevated levels of anxiety following a stressful work event such as the COVID-19 pandemic [ 9 ].

As far as service is concerned, our findings suggest that anxiety levels do not seem to be related to the unit in which the care services are performed (considering, in this case, intensive care units (ICUs), hospitalization, emergency, and primary care). This result seems contradictory to some research that has shown an association between the nature of the work environment and anxiety in nurses, stating, specifically, that nurses working in the ICU reported higher levels of anxiety compared to those working in other hospital services [ 56 , 57 ]. Significant associations have also been found between working in critical care units and high levels of anxiety in nurses [ 7 ]. Other studies have indicated that the stress inherent in emergency settings may contribute to higher levels of anxiety in nurses working in these services [ 58 ]. These results are not in accordance with our findings and suggest that the association between work environment and anxiety among HCWs may be more complex than previously considered, varying from one specific context to another and depending on the individual characteristics of the HCWs. Furthermore, we also believe that the time point at which these assessments are made should also be considered. Regarding the sociodemographic and occupational variables assessed, our findings show that the work overload experienced by HCWs throughout the COVID-19 pandemic had a significant direct relationship with anxiety throughout the three time points, which is in line with previous research associating perceptions of high workload with high levels of anxiety [ 59 ].

Our results also point to additional variables that are particularly relevant to anxiety experienced at the first time point, such as work experience, which had a significant negative relationship with anxiety. This significant relationship disappeared in the second time point, likely linked to the learning and development of adaptive strategies to cope with anxiety. Our results support the trend observed in previous research that similarly shows a relationship between less work experience and higher levels of anxiety in nurses [ 30 ]. These findings suggest that anxiety may be more prevalent in inexperienced HCWs, perhaps due to a lack of adaptation to the work environment or the complexity of specific units [ 60 ]. The relationship between the unavailability of PPE and concerns about contagion of family members with regard to anxiety was significant and positive throughout the study, as previous studies have shown [ 61 , 62 ].

Regarding the role of psychosocial variables, bivariate analyses indicated that social support behaved as a protective variable for anxiety, although it is necessary to take into account its multidimensional nature. In this case, the social support of friends was particularly relevant, given that it maintained significantly negative relationships with anxiety at the three time points [ 63 , 64 ]. Thus, considering this multidimensional nature, in the first time point, social support played a protective role for anxiety in all its spheres, with larger effect sizes with regards to total social support and the social support of friends. During the pandemic, the role of social support in HCWs was widely studied, with studies finding it played a protective role against psychoemotional alterations derived from work stress, as is the case of anxiety [ 65 , 66 ]. Within our results, it is interesting to observe how this relationship between social support and anxiety disappears over time, with only social support from friends maintaining an inversely significant relationship with anxiety throughout the study. Different authors point out the importance of the social support derived from friends in transit through stressful situations, defining it as a clear buffer of anxiety [ 63 ].

Regarding the effect of self-efficacy on anxiety, the results of the univariate analyses indicated that it behaves as a protective trait over time and that it acts as a clear buffer against anxiety for HCWs in situations of high occupational stress. However, in the regression models, this effect was not maintained, so the protective effect initially identified may have been derived from other interactions or variables with greater weight in the final models. However, previous research has analyzed the role of self-efficacy in nurses, corroborating the protective role played by self-efficacy on HCWs, not only in the reduction in emotional symptoms but also in the development of strength in the face of stressful work situations [ 37 ].

Resilience has also been a well-studied trait of HCWs throughout the pandemic [ 61 , 67 ]. Our results from univariate analyses revealed that resilience was negatively related to anxiety at all three time points, as nurses who showed higher levels of resilience maintained lower anxiety scores. These results are consistent with previous research conducted throughout the pandemic on HCWs, which reflects the relevance of training HCWs in resilience for more adaptive coping and less distress in stressful work situations [ 61 , 67 ]. However, when performing regression models, this effect did not hold and did not appear to have an effect on the evolution of anxiety over time in our HCWs sample.

Within our study, the influence of cognitive fusion on the evolution of anxiety was assessed as a personality trait. Our results suggest that cognitive fusion is a clear precipitator of anxiety, maintaining significant positive relationships with anxiety throughout the three time points. Although cognitive fusion is a trait that is not well recorded in the existing literature, some research already points to the clear positive association between cognitive fusion and anxiety [ 68 ]. Studies on HCWs during the pandemic have found a negative effect of thought rumination on anxiety [ 36 , 69 ]. Only through the longitudinal nature of our study can it be affirmed that cognitive fusion represents a clear risk factor for the development of anxiety derived from a stressful work event.

Finally, it is necessary to point out some of the limitations of our research. Among them, we can highlight the non-probabilistic convenience sampling, which limits the generalization of the results. In addition, the low participation of males may lead to a bias in terms of gender analysis, although this low representation corresponds to the reality of the profession. On the other hand, it would have been of interest to obtain previous (baseline) assessments of anxiety of the professionals who participated in the study from before the pandemic. The loss of participants over the course of the study could also have been a source of bias.

5. Conclusions

In contrast to the abundance of cross-sectional studies documenting anxiety in HCWs, there is a notable paucity of longitudinal research examining its evolution over time. These studies are essential to understanding the dynamics of anxiety, identifying risk and protective factors, and developing effective interventions [ 70 ]. Without this longitudinal understanding, it is difficult to determine whether current interventions are effective or whether new approaches are needed to adequately address anxiety in HCWs. The present study, in addition to identifying occupational risk factors documented in previous research, points to the protective role of resilience, self-efficacy, and especially, social support (from friends), in addition to marking a clear negative predictor in the evolution of anxiety such as cognitive fusion.

Anxiety in HCWs not only affects their own well-being but can also have negative consequences on the quality of care they provide to patients. The fatigue, exhaustion, and lack of focus associated with anxiety can influence clinical decision making and the ability to provide safe and effective care [ 71 ]. Therefore, interventions aimed at mitigating the anxiety of HCWs are important not only for their own health but also for the general quality of medical care.

Acknowledgments

Thanks to all HCWs who participated in our study and helped in its dissemination, and those who put all their heart into caring for others every day and trying to bring the quality of care to its highest level.

Funding Statement

This research received no external funding.

Author Contributions

Conceptualization, F.G.-A. and C.P.-P.; methodology, C.P.-P.; software, F.G.-A. and C.P.-P.; validation, F.G.-A., F.J.G.-H., F.J.C.-M. and C.P.-P.; formal analysis, C.P.-P.; investigation, F.G.-A., F.J.G.-H., F.J.C.-M. and C.P.-P.; resources, F.G.-A., F.J.G.-H., F.J.C.-M. and C.P.-P.; data curation, F.G.-A., F.J.G.-H., F.J.C.-M. and C.P.-P.; writing—original draft preparation, F.G.-A. and C.P.-P.; writing—review and editing, C.P.-P.; visualization, F.G.-A., F.J.G.-H., F.J.C.-M. and C.P.-P.; supervision, F.J.G.-H., F.J.C.-M. and C.P.-P.; project administration, F.G.-A., F.J.G.-H., F.J.C.-M. and C.P.-P.; funding acquisition, F.J.G.-H. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

This study was approved by the Ethics Committee (Ref: 20/88) and ratified by the Central Research Commission (Ref: 28/20) in order to disseminate the questionnaire to primary care nursing professionals. At the beginning of the questionnaire, all participants were informed of the objective and procedure of the research, and their consent was requested, as well as the possibility of contacting them again by e-mail, given the longitudinal nature of the study. The study was supported by the Spanish Society of Intensive Care Nursing and Coronary Units (SEEIUC), which collaborated with the dissemination of the study. The present study followed national and international deontological guidelines, the Helsinki Declaration, and the Code of Good Practice and Order SAS/3470/2009. The processing of the personal data of the study participants complied with Organic Law 15/1999, of 13 December, on the Protection of Personal Data (LOPD) and with Regulation no. 2016/679 of the European Parliament and of the Council, of 27 April, on Data Protection (GDPR). Hospital Universitario Fundación Alcorcón, Code 20/88, Date: 1 May 2020.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Conflicts of interest.

The authors declare no conflicts of interest.

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