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COVID-19 pandemic triggers 25% increase in prevalence of anxiety and depression worldwide

Wake-up call to all countries to step up mental health services and support.

In the first year of the COVID-19 pandemic, global prevalence of anxiety and depression increased by a massive 25%, according to a scientific brief released by the World Health Organization (WHO) today. The brief also highlights who has been most affected and summarizes the effect of the pandemic on the availability of mental health services and how this has changed during the pandemic.

Concerns about potential increases in mental health conditions had already prompted 90% of countries surveyed to include mental health and psychosocial support in their COVID-19 response plans, but major gaps and concerns remain.

“The information we have now about the impact of COVID-19 on the world’s mental health is just the tip of the iceberg,” said Dr Tedros Adhanom Ghebreyesus, WHO Director-General. “This is a wake-up call to all countries to pay more attention to mental health and do a better job of supporting their populations’ mental health.”

Multiple stress factors

One major explanation for the increase is the unprecedented stress caused by the social isolation resulting from the pandemic. Linked to this were constraints on people’s ability to work, seek support from loved ones and engage in their communities.

Loneliness, fear of infection, suffering and death for oneself and for loved ones, grief after bereavement and financial worries have also all been cited as stressors leading to anxiety and depression. Among health workers, exhaustion has been a major trigger for suicidal thinking.

Young people and women worst hit

The brief, which is informed by a comprehensive review of existing evidence about the impact of COVID-19 on mental health and mental health services, and includes estimates from the latest Global Burden of Disease study, shows that the pandemic has affected the mental health of young people and that they are disproportionally at risk of suicidal and self-harming behaviours. It also indicates that women have been more severely impacted than men and that people with pre-existing physical health conditions, such as asthma, cancer and heart disease, were more likely to develop symptoms of mental disorders.

Data suggests that people with pre-existing mental disorders do not appear to be disproportionately vulnerable to COVID-19 infection. Yet, when these people do become infected, they are more likely to suffer hospitalization, severe illness and death compared with people without mental disorders. People with more severe mental disorders, such as psychoses, and young people with mental disorders, are particularly at risk.

Gaps in care

This increase in the prevalence of mental health problems has coincided with severe disruptions to mental health services, leaving huge gaps in care for those who need it most. For much of the pandemic, services for mental, neurological and substance use conditions were the most disrupted among all essential health services reported by WHO Member States. Many countries also reported major disruptions in life-saving services for mental health, including for suicide prevention.

By the end of 2021 the situation had somewhat improved but today too many people remain unable to get the care and support they need for both pre-existing and newly developed mental health conditions.

Unable to access face-to-face care, many people have sought support online, signaling an urgent need to make reliable and effective digital tools available and easily accessible. However, developing and deploying digital interventions remains a major challenge in resource-limited countries and settings.

WHO and country action

Since the early days of the pandemic, WHO and partners have worked to develop and disseminate resources in multiple languages and formats to help different groups cope with and respond to the mental health impacts of COVID-19. For example, WHO produced a story book for 6-11-year-olds, My Hero is You, now available in 142 languages and 61 multimedia adaptations, as well as a toolkit for supporting older adults available in 16 languages.

At the same time, the Organization has worked with partners, including other United Nations agencies, international nongovernmental organizations and the Red Cross and Red Crescent Societies, to lead an interagency mental health and psychosocial response to COVID-19. Throughout the pandemic, WHO has also worked to promote the integration of mental health and psychosocial support across and within all aspects of the global response.

WHO Member States have recognized the impact of COVID-19 on mental health and are taking action. WHO’s most recent pulse survey on continuity of essential health services indicated that 90% of countries are working to provide mental health and psychosocial support to COVID-19 patients and responders alike. Moreover, at last year’s World Health Assembly, countries emphasized the need to develop and strengthen mental health and psychosocial support services as part of strengthening preparedness, response and resilience to COVID-19 and future public health emergencies. They adopted the updated Comprehensive Mental Health Action Plan 2013-2030, which includes an indicator on preparedness for mental health and psychosocial support in public health emergencies.

Step up investment

However, this commitment to mental health needs to be accompanied by a global step up in investment. Unfortunately, the situation underscores a chronic global shortage of mental health resources that continues today. WHO’s most recent Mental Health Atlas showed that in 2020, governments worldwide spent on average just over 2% of their health budgets on mental health and many low-income countries reported having fewer than 1 mental health worker per 100 000 people.

Dévora Kestel, Director of the Department of Mental Health and Substance Use at WHO, sums up the situation: ”While the pandemic has generated interest in and concern for mental health, it has also revealed historical under-investment in mental health services. Countries must act urgently to ensure that mental health support is available to all.”

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03 February 2021

COVID’s mental-health toll: how scientists are tracking a surge in depression

Alison Abbott

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As the COVID-19 pandemic enters its second year, new fast-spreading variants have caused a surge in infections in many countries, and renewed lockdowns. The devastation of the pandemic — millions of deaths, economic strife and unprecedented curbs on social interaction — has already had a marked effect on people’s mental health. Researchers worldwide are investigating the causes and impacts of this stress, and some fear that the deterioration in mental health could linger long after the pandemic has subsided. Ultimately, scientists hope that they can use the mountains of data being collected in studies about mental health to link the impact of particular control measures to changes in people’s well-being, and to inform the management of future pandemics.

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Nature 590 , 194-195 (2021)

doi: https://doi.org/10.1038/d41586-021-00175-z

Additional reporting by Paul Adepoju

Jordan, H. T. et al. Environ. Health 18 , 12 (2019).

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Long-term effects of COVID-19 on mental health: A systematic review

Affiliations.

1 Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, United Kingdom.
2 North Bristol NHS Trust, Bristol, Northern Ireland, United Kingdom.
3 Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, PO74, King's College London, De Crespigny Park, London, Northern Ireland SE5 8AZ, United Kingdom; National Institute for Health Research Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, Northern Ireland SE5 8AZ, United Kingdom.
4 Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, De Crespigny Park, London SE5 8AF, United Kingdom. Electronic address: [email protected].
PMID: 34798148
PMCID: PMC8758130
DOI: 10.1016/j.jad.2021.11.031

Background: Acute effects of COVID-19 can be life-threatening. Alterations in mental health during the active infection have been documented, but the long-term consequences are less clear.

Method: A systematic review was undertaken to investigate the effect of COVID-19 infection on long-term mental health outcomes. Three databases [PubMed, Medline (Ovid) and Cochrane library] were searched between 1st October 2019 and 29th August 2021 with additional hand searching to identify all published studies reporting symptoms of generalised anxiety, depression, post-traumatic stress disorder (PTSD), or sleep disturbance in participants at least one month after COVID-19 infection. The prevalence and mean symptom score of each were assessed.

Results: Eight hundred and eighty five studies were found, of which 33 were included in the review involving a total of 6743 participants. The studies' risk of bias were typically fair quality. The median study age of participants was 57.8 years (IQR 49.3-60.7), with 63.0% male (IQR 57.0%-73.0%). Participants typically experienced no or mild symptoms of long-term anxiety (GAD-7, STAI-S, HADS) and depression (PHQ-9, BDI, PHQ-2, HADS). Prevalence varied depending on the measurement tool. Sleep disturbances (primarily insomnia) were most commonly reported as mild. PTSD prevalence was similar to anxiety and depression.

Conclusion: The overall effect of the pandemic has been linked with worsening psychiatric symptoms. However, the long-term effect from direct COVID-19 infection has been associated with no or mild symptoms. Studies exhibited the long-term prevalence of anxiety, depression, PTSD, and sleep disturbances to be comparable to general population levels.

Keywords: Anxiety; COVID-19; Depression; Mental health; PTSD; Sleep disturbance.

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All authors declare no conflicts of Interest.

PRISMA flow diagram.

Plot A: Generalized Anxiety (GAD-7).…

Plot A: Generalized Anxiety (GAD-7). Plot B: State Trait Anxiety scale – state…

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Published: 15 June 2022

COVID-19 and mental health in Australia – a scoping review

Yixuan Zhao 1 ,
Liana S. Leach 1 ,
Erin Walsh 1 ,
Philip J. Batterham 1 ,
Alison L. Calear 1 ,
Christine Phillips 2 ,
Anna Olsen 2 ,
Tinh Doan 1 ,
Christine LaBond 1 &
Cathy Banwell 1

BMC Public Health volume 22 , Article number: 1200 ( 2022 ) Cite this article

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The COVID-19 outbreak has spread to almost every country around the world and caused more than 3 million deaths. The pandemic has triggered enormous disruption in people’s daily lives with profound impacts globally. This has also been the case in Australia, despite the country’s comparative low mortality and physical morbidity due to the virus. This scoping review aims to provide a broad summary of the research activity focused on mental health during the first 10 months of the pandemic in Australia.

A search of the Australian literature was conducted between August-November 2020 to capture published scientific papers, online reports and pre-prints, as well as gaps in research activities. The search identified 228 unique records in total. Twelve general population and 30 subpopulation group studies were included in the review.

Conclusions

Few studies were able to confidently report changes in mental health driven by the COVID-19 context (at the population or sub-group level) due to a lack of pre-COVID comparative data and non-representative sampling. Never-the-less, in aggregate, the findings show an increase in poor mental health over the early period of 2020. Results suggest that young people, those with pre-existing mental health conditions, and the financially disadvantaged, experienced greater declines in mental health. The need for rapid research appears to have left some groups under-researched (e.g. Culturally and Linguistically Diverse populations and Indigenous peoples were not studied), and some research methods under-employed (e.g. there was a lack of qualitative and mixed-methods studies). There is a need for further reviews as the follow-up results of longitudinal studies emerge and understandings of the impact of the pandemic are refined.

Peer Review reports

The outbreak of COVID-19, an infectious disease causing severe acute respiratory syndrome, led the Director-General of the World Health Organisation (WHO) to declare a public health emergency of international concern on the 30 th January 2020 [ 72 ]. By April 2021, the disease had spread to almost every country around the world, and caused more than 3 million deaths [ 74 ]. The pandemic has triggered enormous disruption in people’s daily lives and has undoubtedly had a widespread and profound global impact.

Australia has managed to date to achieve low total numbers of local infection, partly because of its geographic isolation (i.e. all borders are surrounded by sea) and also because of early interventions to contain the virus. Following the first confirmed case on the 25 th January 2020 [ 34 ], the Federal Government quickly introduced border controls, quarantine measures and urged the public to take precautions in response to the virus. By March 2020, a series of stringent containment measures were put in place by the state and territory governments to stop the spread of the virus and protect people’s lives. These included requirements to stay at home (except for specific reasons), business closures, restrictions on social gatherings and interstate travel, as well as a ban on all international travel. Residents in the state of Victoria experienced particularly stringent restrictions (e.g. a nightly curfew, a 5 km-limit for all activities, and mandatory mask-wearing [ 6 ]) during a second wave of COVID from June-October, 2020. To date, these restrictions have proven to be successful at reducing the transmission of the virus in Australia [ 16 , 13 ]. However, they have come at a considerable economic and health cost to individuals, businesses, communities and the nation. Government data shows that during June-July, 2020, the Australian Gross Domestic Product fell by a record 7% and the unemployment rate hit 7.5%—the highest it had been in over 20 years. Reassuringly, after July, the Australian economy started to improve in all states except Victoria [ 3 ].

Despite the successful management of the pandemic to date and the ongoing economic recovery, there are indications that Australians’ mental health declined in the early months of the pandemic and that this reduction has been somewhat sustained. Data from the Australian Bureau of Statistics (ABS) shows that in January 2021 22% of Australians reported that their mental health was ‘worse’ or ‘much worse’ than in March 2020; comparatively only 0.1% of people in Australia have been infected with COVID-19. Similarly, 21% reported that their mental health was ‘fair’ or ‘poor’ in January 2021—higher than the 14.4% who reported this in July 2020 [ 2 , 4 ]. Although this self-report data is not based on validated mental health measures, it demonstrates the importance of investigating the widespread and potentially enduring impact of the pandemic on mental health in Australia. Mental health experts have stated that increases in mental health problems are likely due to risk factors attributable to the virus itself (e.g. fear of contracting the virus, concerns about the lack of treatment options and/or being in a high-risk group for mortality, and uncertainty about when the virus will be controlled) as well as risk factors attributable to the lockdowns aimed at combating the virus (e.g. interrupted daily routines, unemployment and underemployment, loss of income, reduced social support, financial distress, and loneliness) [ 38 ]. The latter are well-established risk factors for poor mental health generally, let alone within the complex context of a global pandemic [ 50 , 32 ].

The Australian context is unusual in terms of the focus on individuals’ and communities’ mental health in 2020. In part, because the prevalence of COVID-19 has been relatively low in Australia compared to other countries, discussion regarding the more distal mental health impacts of COVID has been prominent alongside concerns about the proximal physical impacts. Justifiably, the research community (and the media) in Australia has paid tremendous attention to the potential mental health impacts of the outbreak. An influx of studies have been conducted in the past year (mainly from March to September 2020) to understand people’s experiences and gauge any increase in mental health problems during the pandemic. While many of these studies are still ongoing, numerous results have been published reporting on the prevalence and severity of mental health problems during this time (mostly common experiences such as psychological distress, depression and anxiety), and the vulnerability of different groups. For context, it is also important to note that the COVID pandemic closely followed the Black Summer bushfires. From September 2019 to February 2020, large swathes of Australia were burnt, accompanied by destruction of life, property, the natural environment and wildlife [ 11 ] (although most COVID-focused studies have not considered the population’s possible lingering emotional responses to the bushfires).

Despite the influx of research activity in Australia investigating mental health during 2020, comprehensive summaries of what has been done and what has been found are scarce (for an international review and meta-analyses see Prati & Mancini [ 56 ]). Given it has been over a year since the outbreak began, the current scoping review provides a timely summary of the Australian research conducted in 2020 during the early phase of the COVID-19 outbreak. The review also aimed to identify gaps in research activities, knowledge and understanding of how the pandemic is affecting Australian’s mental health.

Study design

In this review, the use of the term ‘mental health’ goes beyond the presence/absence of diagnosed mental illness and instead focuses on the most common psychological symptoms experienced in the community, such as distress, anxiety, and depression. Because this review aimed to be inclusive, and also considering much research regarding the pandemic is ongoing (with some research reports and online pre-prints not yet available in peer-reviewed scientific journals), we deemed a descriptive broader scoping review more appropriate than a traditional systematic review [ 44 , 64 ]. This review follows the PRISMA-ScR checklist, an extension of the PRISMA statement for conducting scoping reviews [ 66 , 51 ].

Eligibility criteria

While this scoping review was necessarily broad, clear well-defined eligibility criteria and research questions were still required. Following the JBI recommendations [ 51 ] we define our population as Australians, our context as Australia during the first 10 months of the COVID-19 pandemic, and our concept as mental health prevalence (or outcomes) and risk factors during this window of time.

Publications (reports, non-reviewed pre-prints of papers and peer-reviewed articles) were eligible to be included if they were focused on mental health during the COVID-19 pandemic, reported original research findings/results (i.e. media releases, editorials, opinion pieces, commentaries, protocol papers or general text summaries within reports (with no detailed findings) were excluded), were conducted within the Australian population, and were written in English.

Literature search and data extraction

Searches of the literature were conducted between August-November 2020 to capture research with a focus on COVID-19 and mental health in Australia. The search included three elements:

Four databases (PsycINFO, PubMed, Scopus and Web of Science) were searched using key words to capture published peer-reviewed articles focused on COVID-19 and mental health in Australia. These keywords were COVID AND ("mental health" OR "psychological dis*" OR "mental dis*" OR depress* OR anxiety OR wellbeing OR well-being OR "well being" OR worr* OR fear OR lonel* OR "alcohol use" OR "substance use” OR stress OR confus* OR anger OR optimism OR pessimism OR "mental ill*" OR mood OR panic) AND Australia *. The search was generally within the title and abstract field (in some databases, keywords and author information were also included). The document type was limited to “article” where possible so that other types of publications such as reviews, study protocols, editorials, commentaries, viewpoints, letters to editors, and dissertations, were excluded.

The online search engine Google was searched using the phrase “COVID mental health research survey Australia” to capture research findings not yet published in scientific journals. The results were limited to records within one year, verbatim, and pages published in or originating from Australia. Reports, online papers and pre-prints that included mental health/wellbeing measures or interview questions (and sufficient information about study methods) were identified and recorded. In addition, we checked the reference lists of identified publications and reached out to our existing research networks to identify relevant pre-prints or recently accepted publications.

All the records in the databases for the Research Tracker and Facilitator for Assessment of COVID-19 Experiences and Mental Health project [ 14 ] were checked for any additional studies not already identified. This project aims to track research being undertaken on COVID-19 and mental health by Australian researchers.

General description of studies included

The search and selection process is outlined in Fig. 1 . As the manual search of reference lists did not yield any more records beyond the records identified through other search methods, this was not specified in Fig. 1 . The records identified through the database searches were reviewed by two researchers (YZ and LL) independently. Any disagreements regarding the eligibility of articles were resolved via broader discussion with the project team. Overall, 42 articles were identified as eligible for inclusion in the scoping review. Two reviewers (YZ and EW) independently assessed the full-texts of the 42 articles and extracted and recorded relevant data (including sample characteristics, whether the study included pre-COVID comparisons, mental health outcomes and measures, study key findings, and any main risk or protective factors identified). All discrepancies regarding data extraction were resolved through discussion.

Search and selection process for the review

The characteristics of the 42 included studies are outlined in Tables 1 and 2 (see Additional file 1 ).

Study time-frame and geographical coverage

The majority of the eligible studies were conducted between the end of March and early June 2020, covering the time period when the whole country was under stringent stay-at-home measures, with strict restrictions placed on social gatherings. Seven studies included data collected after this period, when the restrictions were beginning to relax across Australia (except for Victoria) [ 9 , 10 , 30 , 36 , 39 , 40 , 57 ]. All but one [ 39 ] of these seven studies included data from every state including Victoria after the second wave’s containment measures. However, Griffiths et al. [ 30 ] was the only study that made direct comparisons between Victoria and the rest of Australia.

Study populations

Out of the 42 research studies, 12 were conducted among the general Australian adult population, while the remaining 30 focused on a specific group within the population (e.g. parents of young children, health workers, people with an existing health or mental health condition, or young people). The characteristics and key findings for the general population studies are summarized in Table 1 and for specific group studies in Table 2 . Three studies [ 10 , 52 , 68 ] drew a subsample of data from surveys conducted among the general population. However, because the aims and findings of these studies focused on specific subpopulation groups, they were included as research conducted among specific groups.

Pre-COVID comparisons

Of the total 42 studies, nine studies were longitudinal or repeated cross-sectional and had data collection points covering the time period before and during the COVID-19 outbreak (with comparative data collection methods and mental health measures employed) [ 7 , 8 , 15 , 22 , 39 , 43 , 63 , 65 , 67 ]. These studies were more robustly able to compare participants’ mental health during the COVID-19 pandemic to a pre-COVD level. In other words, the evidence provided in these studies was higher quality than other studies with no baseline pre-COVID comparison. Ten further studies compared the results of their studies to norms or results of similar studies conducted before the pandemic. Four studies asked the participants to self-report on whether, and to what extent, their mental health had changed since the onset of the pandemic (these studies are susceptible to recall misjudgements). Several studies used more than one mental health measure and the pre-COVID comparison for each measure sometimes varied. Twenty studies did not report any pre-COVID comparison data, making it difficult to draw confident conclusions about changes in mental health due to COVID.

Research on the general population in Australia

Study sampling and data sources.

In the 12 general population studies (Table 1 ), the participants were usually required to be aged over 18 and currently living in Australia. Four of the 12 studies were based on representative samples of Australian population – 1 & 2. ANUpoll study (Life in Australia™) Footnote 1 [ 7 , 8 ]; 3. Taking the Pulse of the Nation Survey Footnote 2 [ 9 ]; 4. The Australian National COVID-19 Mental Health, Behaviour and Risk Communication (COVID-MHBRC) Survey [ 18 ]. Six studies recruited participants online via social media (e.g. through Facebook advertisements) – 1 & 2. Fisher et al. [ 27 ] and Owen et al. [ 48 ] drew data from the Living with COVID-19 restrictions in Australia survey Footnote 3 ; 3. Rossell et al. [ 58 ] used data from the COVID-19 and you: Mental health in Australia now survey (COLLATE) Footnote 4 ; 4. Gurvich et al. [ 31 ] used data drawn from the COVID-19 and Mental Health Survey Footnote 5 ; 5. Newby et al. [ 45 ] used data from the Mental Health and Coronavirus Study conducted by UNSW and the Black Dog Institute (approval number 3330); 6. Survey data used by Stanton, To & Khalesi et al. [ 62 ] (approval number 22332). The sample representativeness when recruiting participants via online platforms varies greatly in published research [ 53 ]. It is generally accepted that studies based on random and/or representative samples are higher quality with more generalisable findings. However, online methodologies are considered feasible and efficient for broadly summarising population experiences and for correlational research, as they provide timely access to a significant number of individuals [ 40 ]. The two remaining studies in Table 1 [ 21 , 25 ] were based on analyses of online content. Given the ubiquity of internet use, analysing online content offers researchers an avenue to understand public sentiments and opinions [ 21 , 25 ].

During-COVID/Pre-COVID study comparisons

Most of the surveys investigating the COVID-19 outbreak and mental health have collected, or intend to collect, follow-up data to understand changes in the public’s experiences and mental health symptomology as the pandemic evolves, but currently available publications mostly report baseline data. In other words, the majority of studies are cross-sectional and the longitudinal results are not yet available. Out of the 12 studies included in Table 1 , four report changes in participants’ mental health over time during the pandemic. These studies correlate changes in mental health symptomology with varying case rates of COVID-19, as well as changes in social and economic policies and other life circumstances in the first few months of the pandemic [ 7 , 9 , 21 , 25 ].

In terms of pre-COVID comparisons, we identified no studies tracking mental health from pre-COVID and into the COVID period using the same sample/cohort over time. However, six of the 12 studies made comparisons between current COVID results and results from a pre-COVID sample in Australia. Biddle et al. [ 7 ] and [ 8 ] compared their current results with previous waves of the same survey, although the same cohort of respondents was not tracked individually. Four studies compared their results with findings from various representative studies conducted prior to COVID [ 9 , 18 , 27 , 58 ]. These comparisons provided some information about whether, and how, people’s mental health changed during COVID, but the comparisons are less rigorous than if pre-COVID data were available from longitudinal cohort studies tracking temporal changes in individuals.

Mental health outcome measures

Studies generally focused on psychological distress, depression and anxiety. These mental health problems were primarily examined using validated psychometric scales – demonstrating good quality, robust measurement. The most common measures included the Kessler 6 (K6) scale (used by Biddle et al., [ 7 , 8 ] as an indicator for general psychological distress; Patient Health Questionnaire-9 (PHQ-9) (used by Dawel et al. [ 18 ]; Fisher et al. [ 27 ]; Owen et al. [ 48 ]) to assess depression symptoms, suicidality and eating patterns; Generalized Anxiety Disorder-7 (GAD-7) (used by Dawel et al. [ 18 ]; Fisher et al. [ 27 ] to measure anxiety and irritability; and the 21-item Depression Anxiety Stress Scales (DASS-21) (used by Gurvich et al. [ 31 ]; Newby et al. [ 45 ]; Rossell et al. [ 58 ]; Stanton et al. 62 ]) to measure dimensions of depression and anxiety symptoms. Gurvich et al. [ 31 ] also reported on suicidal thoughts using the relevant items in Beck Depression Inventory (BDI). Among the two studies analysing online content, Du et al. [ 21 ] selected the terms “fear”, “panic”, “worry” to represent fear-related emotions as they showed high consistency with each other, while Ewing & Vu [ 25 ] harvested public sentiments through researchers’ interpretations of the tweet data from Twitter.

Overall study findings

The results of the four nationally representative studies (Biddle, et al. [ 7 , 8 ], Botha et al. [ 9 ], Dawel et al. [ 18 ] all showed an increase in mental health problems compared to pre-pandemic published statistics. Three of the remaining general population studies also found an elevation in mental health problems when comparing their results with pre-pandemic norms [ 27 , 45 , 58 ]. Du et al. [ 21 ] tracked the internet searches for fear-related emotions, protective behaviours, health-related knowledge, and panic buying by Australian throughout March, and Ewing &Vu [ 25 ] analysed 3-weeks of tweets by Australian in April. They both found a decline in positive emotions, which matched the deterioration of the COVID-19 situation over time. The three studies by Gurvich et al. [ 31 ], Owen et al. [ 48 ] and Stanton et al. [ 62 ] had no pre-COVID comparisons, and provided no evidence about whether mental health deteriorated during the pandemic. Instead, these studies identified a series of risk and protective factors for mental health during COVID-19. Despite the reports of pessimism in the population, some optimistic feelings were also identified – Biddle et al. [ 8 ] found a significant increase in social cohesion and trust to fellow Australians in the population and Fisher et al. [ 27 ] found that on average Australians were optimistic about the future.

Several studies identified demographic and socio-economic characteristics associated with mental health during COVID-19. For example, Newby et al. [ 45 ], Biddle et al. [ 7 ] and Dawel et al. [ 18 ] all found that younger people reported poorer mental health during the pandemic relative to older groups. Those who experienced job loss, reductions in work hours, and financial hardship during COVID were also more likely to record mental health problems (e.g. [ 7 , 9 ]). Another important factor was pre-existing mental health conditions. Participants with a prior mental health diagnosis were more likely to report worse mental health during COVID-19 [ 18 , 45 , 58 , 62 ].

Studies also showed that people who were worried about contracting COVID-19 were more likely to report poorer mental health [ 27 , 45 , 48 ]. Surprisingly, Dawel et al. [ 18 ] found that direct COVID-19 exposure was not associated with mental health problems. Instead, impairments in work and social functioning and financial distress due to COVID-19 were more strongly associated with poorer mental health. Dawel et al.’s study [ 18 ] also considered the experience of bushfire exposure during the 2019–2020 fires. The results showed that exposure to the fire was not associated with mental health symptomology, but exposure to the bushfire smoke was associated with decreased wellbeing.

Research on specific subpopulation groups

The 30 studies with a focus on specific subpopulations included 25 quantitative studies (with the majority based on survey data and five based on administrative data), four qualitative studies and one mix-method study. Two of the four qualitative studies (Digby et al., 2021; [ 19 , 24 ]) reported the qualitative findings of mixed-methods research, with the quantitative findings reported elsewhere.

Study samples and populations of interest

Of these 30 studies, 20 studies collected data from participants across the nation (although one comprised largely of people living in Victoria (88.2%)) [ 57 ]. Only Sollis et al. [ 61 ] and Broadway et al. [ 10 ] were based on survey data analysed from nationally representative samples, and Johnston et al. [ 36 ] pre-stratified their data/sample to approximate a nationally representative sample. The remaining ten studies focused on specific states or cities. One focused on South Australian [ 67 ]; one on Queensland [ 39 ]; two studies were conducted in Western Australia [ 22 , 41 ]; and two studies in Sydney or New South Wales [ 43 , 60 ]. Four studies were conducted in Melbourne or Victoria [ 15 ]; Digby et al. 2020; [ 20 , 33 ].

People with a particular vulnerability were a major focus of these studies. They included patients presenting to and/or staying in hospital due to poor health or mental health in the study period [ 15 , 22 , 60 ]; people with a pre-existing physical or mental health disorder [ 52 , 68 ]; and people accessing mental health services [ 63 , 65 , 67 ]. Leske et al. [ 39 ] studied suicide rates and motives during the pandemic. Hospital staff, whose physical and mental health may have been more vulnerable during the pandemic, were the population of interest in three studies (Digby et al., 2021, [ 19 , 20 , 33 ]. Other potential participant vulnerabilities included being an adolescent or young adult [ 40 , 41 , 43 ], in self-isolation/quarantine [ 35 ], living alone [ 46 ] and having higher dysmorphic concern [ 55 ].

Families with young children were considered vulnerable and therefore a population of interest in nine studies. Six studies drew data from the COVID-19 Pandemic Adjustment Survey which was conducted among parents of children under the age of 18 (see Table 2 ). Two studies drew data from other nationwide surveys [ 36 , 10 ]. Additionally, Chivers et al. [ 17 ] conducted a qualitative research on new and expecting parents.

Pre-COVID/ during-COVID study comparisons

As indicated in Table 2 , 15 of the 30 studies reported on changes in mental health and other wellbeing indicators before and during the COVID-19 outbreak. Most studies investigating specific populations were cross-sectional and compared current results with the results or statistics from pre-COVID studies that used similar samples (or comparable admissions/administrative data). Other studies asked participants to self-report on the differences in their mental health before and during the pandemic. Four studies reporting administrative data from health services [ 15 , 22 , 63 , 65 ] selected data collected during the corresponding period of 2019 as their pre-COVID comparisons (to avoid the period immediately before the pandemic when Australia experienced the severe bushfire crisis). One longitudinal study tracking the same cohort of participants [ 43 ] adopted a cut-off date to compare mental health before and after the implementation of the COVID-19 restrictions. Separate from the pre-COVID comparisons, four studies [ 15 , 22 , 30 , 63 ] compared mental health across multiple time points during the pandemic, linking changes in participants’ mental health to changes in case rates for COVID-19 in Australia.

Mental health measures

Similar to studies focused on the whole general population, most of the subpopulation studies measured participants’ mental health and wellbeing using validated scales such as the K6, K10, PHQ-9, GAD-7 and the DASS-21. A series of other mental health measures were also adopted (see Table 2 ). Apart from the validated mental health measures, behaviours related to mental health, including eating and exercise behaviours [ 52 ], and appearance-focused behaviours [ 55 ], were also adopted as mental health indicators. Several studies examined public or administrative records, including emergency department presentations [ 15 , 22 ], suicide registers [ 39 ] and website visits and call centre traffic for mental health services [ 65 , 63 ]. A small number of studies did not use validated measures and instead asked participants to self-report on their mental health, lowering the quality of mental health measurement in these studies (e.g. [ 10 , 35 , 36 , 41 , 43 ]). None of the sub-group studies assessed the widespread and likely traumatic impact of the 2019–20 bushfires (a significant individual and community-level pre-pandemic vulnerability).

Five studies qualitatively assessed participants’ descriptions of their experiences and feelings during the COVID-19 pandemic [ 17 ], Digby et al., 2021; [ 19 , 24 , 46 , 60 ] to gain a deeper understanding into participants’ psychological wellbeing in relation to their specific contexts. Of the five studies, Chivers et al. [ 17 ] analysed posts related to COVID-19 in an online parenting forum to understand perinatal distress. Shaban et al. [ 60 ] conducted bedside interviews of COVID-19 patients to explore their lived experiences and perceptions. The other three studies added open-ended questions asking about participants’ concerns related to COVID-19 in their surveys.

In general, the studies investigating specific subpopulation groups showed similar patterns to the findings of the studies on the general population – mental health and wellbeing deteriorated with the emergence of the COVID-19 pandemic and associated restrictions. This trend is consistent across the different populations of interest. However, it is also apparent that important population groups, such as Indigenous and CALD (Culturally and Linguistically Diverse) groups were not researched, limiting our knowledge for these groups. Psychological distress was reported widely among hospital staff in the two studies that measured hospital workers’ mental health [ 20 , 33 ]. Three studies focusing on adolescents and university students consistently showed higher psychological distress and lower subjective wellbeing since the COVID-19 outbreak [ 40 , 41 , 43 ]. Studies focusing on parents with young children identified a range of mental health challenges and risks during the COVID-19 period, and the three studies that included a pre-COVID comparison indicated that psychological distress increased [ 10 , 70 , 71 ]. The themes identified from the qualitative studies differed as they were specific to the experiences of each subpopulation group. However, participants in these studies acknowledged the impact and the challenges brought by the COVID-19 pandemic and expressed worry and concerns (refer to Table 2 for details).

The two studies [ 30 , 63 ] reporting on participants’ mental health several times across the pandemic showed similar results to Biddle et al.’s [ 7 ] study of the general population. Griffiths et al. [ 30 ] focused on working adults and Staples et al. [ 63 ] focused on consecutive users of digital mental health services during the pandemic. Corresponding with Biddle et al. [ 7 ], both studies found that declines in mental health appeared to be more significant during March to April, and then improved in later months (returning normal levels) (except for the Victorian participants in Griffiths et al. [ 30 ]).

In contrast to the consistent findings from survey data showing increases in common mental health problems (i.e. psychological distress, depression and anxiety), two studies analysed data on emergency department (ED) presentations during the pandemic and showed varying results. Cheek et al. [ 15 ] found that mental health presentations potentially increased,while Dragovic et al. [ 22 ] found that the total number of mental health presentations decreased and that the trend varied depending on the reasons for the presentation. A decrease in ED presentations is not surprising given that face-to-face access to many health services declined during the pandemic (as people restricted their mobility) [ 5 ] – and thus, actual service use during this time does not likely reflect the need for services in the community. Importantly, according to data from AIHW [ 5 ], mental health related services, particularly services delivered online or via phone showed heightened service usage since the restrictions were introduced. The contrast between the two studies is likely because they were based on data from two different states with different COVID-19 responses, and Cheek et al. [ 15 ] only included paediatric patients.

In terms of suicidal intention, plans or behaviours, data from Queensland showed no change in suspected suicides [ 39 ] and in Western Australia, the presentations to emergency departments due to suicide or self-harm decreased significantly during this period [ 22 ]. On a national level, those who accessed digital mental health services during the pandemic also showed no changes regarding suicidal thoughts or plans [ 63 ].

Several potentially positive experiences related to the COVID-19 situation were identified from existing studies. Many individuals and families practicing isolation/social distancing reported some “silver linings”, such as strengthening relationships with their families, enjoying spending time at home, and developing new hobbies [ 24 , 35 ]. Patients with COVID-19 who were in isolation also reported some positive factors [ 60 ]. For example, although patients reported that they were disconnected from the outside world, lost track of time, and had limited mobility, some saw this as a reflection of the professionalism and quality of care provided. This enhanced their confidence and helped to ameliorate their initial concerns about being infected. Positive experiences were also identified as potential indicators of resilience and helped to mitigate the negative effect of the pandemic and restrictions on mental health [ 20 , 35 , 42 , 24 ]. For example, Oliva & Johnston’s study [ 24 ], showed the mental health benefits of having a dog during the lockdown, likely because it encouraged exercise and provided an opportunity to socialize with other people.

Several studies made comparisons between specific population groups and the general population, or other population groups. These studies provide insights into which population groups might be at greater risk of experiencing mental health problems, and what factors were protective during the pandemic. Specifically, Broadway et al. [ 10 ] showed the protective effect of having two earners in the family in times of uncertainty. Phillipou et al. [ 52 ] found that individuals previously diagnosed with eating disorders experienced more mental health problems compared to the general population while people with high and low dysmorphic concern displayed different psychological and behaviour responses to the shutdown of the beauty industry in the COVID-19 lockdown [ 55 ].

In summary, we found that Australians in general experienced poorer mental health during the early stages of the pandemic in 2020 compared to pre-COVID. However, the absence of robust longitudinal cohort studies with pre-pandemic baseline data with makes this difficult to conclude definitively. Despite variation in the prevalence of and responses to COVID in individual countries, internationally research similarly indicates there has been a consistent deterioration in mental health and wellbeing levels around the world (see Findlay et al. [ 26 ] (Canada), Fitzpatrick et al. [ 28 ] (US), Pierce, Hope & Ford et al. [ 54 ] (UK). For example, the results of a meta-analysis [ 56 ] of longitudinal studies and natural experiments regarding the psychological impact of COVID-19 pandemic lockdowns internationally, aligns with our findings, showing an increase in psychological symptoms such as depression and anxiety, but no changes in suicidal risk. However, it is worth mentioning that all studies above were conducted in relatively high-income countries. Low-to-middle income countries have experienced even greater impacts during the pandemic, because of their inadequate and underprepared health systems and the uncertainty of their economies. Therefore the mental health impacts of COVID-19 are possibly more serious in the low-to-middle income countries and worthy of specific attention [ 1 , 12 ].

Apart from this general trend, some other key issues regarding the impact of the COVID-19 pandemic on mental health were also evident from the research findings. First, a series of demographic and socio-economic characteristics were identified as risk factors for adverse mental health outcomes. Most clearly, mental health and wellbeing levels seemed to deteriorate in younger age groups – while adolescents and young adults are at greater risk of poor mental health at any time (i.e. outside of pandemic conditions) the deterioration in their mental health during COVID appeared greater than for older age groups [ 7 ]. One explanation is that age is associated with other mental health risk factors that were heightened during the pandemic – such as employment and financial status. In April 2020, the underemployment rate in Australia was 13.8% while the youth underemployment rate hit 23.6% [ 3 ]. Along with employment and financial insecurity, young people are also more likely to have precarious housing and be more reliant on social and peer support which diminished during the pandemic [ 69 ]. As a consequence, it appears there has been a disproportional impact on younger adult’s mental health, despite their relative physical robustness [ 73 ]. Another important risk factor identified was pre-existing mental health problems. Earlier in 2020, Galletly [ 29 ] stated that the pandemic would be a difficult time for people with chronic mental illness. This is echoed by research showing that participants with a prior mental health diagnosis had poorer mental health during the pandemic – however the lack of studies reporting pre-COVID comparative data makes it difficult to determine the extent to which mental health decline for this group comparative to those with no pre-existing mental health problems.

The current review found that people reported some positive mental health and wellbeing experiences that emerged during the early stages of the pandemic. Potentially positive experiences reported by the participants in the reviewed studies included strengthening relationship with family and increased confidence in healthcare system [ 24 , 60 ]. Identifying the positive aspects of peoples’ experience during this challenging time is as important as identifying risk factors in terms of grasping a holistic understanding of what approaches and strategies are most useful to mitigate the negative impact of the pandemic on mental health.

Shortcomings in the research response

The current scoping review demonstrates that many Australian mental health researchers, like researchers internationally, responded rapidly to the pandemic. While this swift response captures a highly valuable snapshot of the impacts of this worldwide disaster, there are shortcomings in terms of design and the reliability and validity of findings. One key gap highlighted in this review is the lack of longitudinal studies with comparative pre-COVID data from the same cohort. Consequently, conclusions about how mental health changed over the course of the pandemic (from pre-pandemic levels), how people adapted during COVID, and whether trajectories varied for different groups are currently limited. A number of important national Australian studies (longitudinal and repeated cross-sectional) are yet to release data collected towards the end of 2020 (e.g. the Longitudinal Study of Australian Children wave 9C1; the ABS Intergenerational Health and Mental Health Study) – we expect these and other studies still to be published will go some way to addressing this knowledge gap. A further shortcoming is that the impact of the 2019–2020 Australian bushfires has rarely been considered.

The small number of qualitative and mixed method studies indicates another gap in the available research. There is value in adding qualitative research components to the mix that can elucidate contextual factors and lived experience particularly for specific and vulnerable groups which may assist in better provision of services to them. As COVID-19 is a novel virus leading to unprecedented challenges and experiences, qualitative research may contribute to a deeper understanding of the complexities (and emerging issues) of mental health and wellbeing pathways during the pandemic, and its potentially lasting impact on mental health once the pandemic has subsided.

These possibilities suggest that we need to fund good quality longitudinal research, as well as turn to rigorous and multi-faceted research. There is a need to gather baseline and follow-up data (including the use of administrative data, longitudinal, mixed-methods studies, and in-depth qualitative research). On a practical note, while the practicalities and mechanics of research are not the focus of the current review, it is important to note that the pandemic has revealed some of the barriers to conducting high quality mental health research that is responsive and has longevity. The time sensitivity of the pandemic, and its rapidly evolving nature highlighted delays related to need to for prompt ethics clearances across multiple institutions in Australia (under-resourced ethics committees were inundated with requests that needed to be expedited). The formal requirements of funding bodies are not well suited to rapidly evolving pandemics either, with funding for COVID-19 mental health research announced in November 2020 after the most restrictive lockdowns had ended. While Australia is a success story compared to similar wealthy western nations, the mental health impacts of COVID-19 (and the current gaps in this body of research) suggests that efforts to address current research practices and resource constraints may improve the country’s responsiveness to comprehensively study future challenges.

Research still to come….

The studies included in this review were conducted generally between April–May 2020. However, the COVID experience in Australia and worldwide is rapidly evolving: it has been contained in some Australian locations while additional outbreaks have occurred elsewhere. It is anticipated that Australian research results from studies conducted in the second half of 2020 and early 2021 will be different from those reported in the current review as efforts to contain the virus have been also evolving across the states and territories. The vaccine program rollout, currently being implemented, may have a significant impact. Research on the long-term mental health effects of disasters suggest that people’s responses evolve considerably [ 59 ]. However, the health nature of this pandemic may differentiate it from natural disasters, and comparative literature is not currently available.

While most existing studies show that COVID-19 containment measures have impacted negatively on the mental health of the general population and on specific vulnerable groups, it is anticipated that the population’s mental health outlook will improve as the vaccination program takes hold and lockdown measures are no longer needed [ 30 ]. However, the discontinuation of the national Job-keeper program (a federally funded program paid to businesses to keep their employees) and the Coronavirus Supplement payment for Job-seekers (an unemployment payment) [ 23 ] by end of March 2021 may trigger job and income losses, leading to declines in mental health for some. Financial insecurity is an important risk factor for poorer mental health—the Taking the Pulse of the Nation survey showed mental distress (depression or anxiety) was closely aligned with financial stress throughout 2021 [ 10 ]. Concerns remain for those with pre-existing mental health conditions, for those who may experience financial hardship over a long period, and for those who experience future lockdowns. For example, it appears that the mental health of residents in Victoria varied from the rest of Australia [ 30 ] as they were subjected to a second lengthy and severe lockdown period when the virus re-emerged that delayed re-entry to employment, schooling and services.

The COVID-19 pandemic may have a delayed impact on mental health in subpopulation groups in myriad interactive and cumulative ways. One example is the mental health of those who were pregnant during the early phases of the pandemic, who in 2021 will have infants and be in the postnatal phase and may have added vulnerability to postnatal depression and anxiety. In addition, as we note above, some vulnerable population groups are under-represented in the existing studies with implications for the management of the pandemic. For example, media reports at the time suggested that some CALD and socially and economically disadvantaged groups may have had different COVID-19 experiences and may have missed out on mainstream messaging; consequently, there may be discrimination that impacts the mental health for different ethnic groups for some time to come. The mental health status of healthcare workers, who have been on the frontline of this crisis, also requires further attention from the research community. The existing studies on the mental health of healthcare workers identified in this review were only conducted among hospital staff in several health services in Melbourne – not nearly enough to cover the experience of this population group in Australia. Fear of transmitting the virus to family, community perception of frontline workers as potential disease carriers, extreme workloads, limited availability of protective equipment and moral dilemmas have all added extra burdens to the mental health of the healthcare workers (Digby et al., 2021) [ 19 ]. A systematic review and meta-analysis of studies conducted in other countries has found high prevalence of mood and sleep disturbances among this specific group [ 49 ]. These future possibilities and identified research gaps demonstrate the need for ongoing research to better understand what happened to mental health both during the pandemic phase and in the aftermath.

Limitations

As noted, there are a number of limitations to this scoping review that need to be briefly acknowledged. The first relates to the rapidly changing and emergence of new published results. This review only provides a snapshot of the research available during the period when the existing literature was searched and it is possible that some information published online has been missed. Further updated reviews need to be conducted to continue to synthesize research findings. Second, while the current review did not perform a quality rating of the studies included in the review, discussion of study quality is included throughout and Tables 1 and 2 list detailed information about the characteristics of each study—including document type, sample size and representativeness, as well as whether pre-COVID comparisons were made. This information provides a reference for making judgements about the strengths and weaknesses (quality) of each study. We do conclude that studies published in peer-reviewed journals, based on a nationally representative sample of Australian population, with a pre-COVID comparison sample from the Australian population are the highest quality. We also make the point that prospective longitudinal studies including baseline (pre-COVID) data from the same sample or cohort are the most robust, but are rare. Third, an analysis of publication bias was not undertaken given that the body of literature is still so new – an analysis of publication bias that extends to considering those vulnerable groups that may have been missed (or difficult to access during COVID-19) would be worthwhile once a more substantial body of literature exists.

The review does not provide detailed data on prevalence rates and statistical associations for each study as many of them did not provide this information. Therefore, we instead aimed to scope the breadth of research conducted and provide a narrative overview (in the text and the Tables) of the findings. Future reviews will provide a comparative summary of the prevalence rates and associations (such as meta-analyses), once this information is obtained. Although the range of differences between studies (e.g. measures used, timing of survey within 2020) that we have observed is likely to make it challenging to combine the data to obtain comparative estimates.

The current scoping review provides a detailed record of the studies published online and in the academic literature investigating mental health during the COVID-19 pandemic in Australia. Our findings suggest that despite the comparatively low prevalence of the disease in the population, mental health problems (i.e. psychological distress, anxiety, depression, poor wellbeing) increased during the early part of the COVID pandemic in 2020. This finding points to the need to focus on mental health problems once the physical health impacts are reduced in countries where the pandemic has been widespread. However, limitations associated with many of the studies in the review, preclude reaching a more definite finding. Young people, those with fewer socio-economic resources and those with pre-existing mental health conditions showed the strongest associations with poor mental health during this time. The review highlights the importance of considering particular vulnerable groups, including health and hospital workers, those in quarantine or isolation, adolescents, parents of children, and people with a pre-existing mental health condition or who were accessing services. Heightened impact on these vulnerable groups suggests that policy attention needs to be given to their economic and psycho-social health to reduce the pandemic’s potentially long-lasting regressive effect. There is a need for further reviews as the follow-up results of longitudinal studies emerge and estimates and understandings of the impact of the pandemic are refined. There is also an important opportunity to consider the limitations of the research available and identify what resources are needed to ensure future timely responses to major disruptions to our way of life to understand the mental health impacts.

Availability of data and materials

Data sharing is not applicable to this article as no datasets were generated or analysed during the current study.

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Table 1 Research conducted among general Australian adult population [ 37 , 47 ]. Table 2 Research conducted among specific subgroups in the population.

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Zhao, Y., Leach, L.S., Walsh, E. et al. COVID-19 and mental health in Australia – a scoping review. BMC Public Health 22 , 1200 (2022). https://doi.org/10.1186/s12889-022-13527-9

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Impact of COVID-19 pandemic on mental health: An international study

Roles Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

¶ ‡ ATG, MK and AK designed and implemented the study together. AK and MK should be considered joint senior authors.

Affiliation Division of Clinical Psychology & Intervention Science, Department of Psychology, University of Basel, Basel, Switzerland

Roles Data curation, Formal analysis, Writing – original draft, Writing – review & editing

Affiliation Department of Health Sciences, European University Cyprus, Nicosia, Cyprus

Roles Investigation, Resources, Writing – review & editing

Affiliation Psychological Laboratory, Faculty of Public Health and Social Welfare, Riga Stradiņš University, Riga, Latvia

Affiliation Kore University Behavioral Lab (KUBeLab), Faculty of Human and Social Sciences, Kore University of Enna, Enna, Italy

Affiliation Department of Social Sciences, School of Humanities and Social Sciences, University of Nicosia, Nicosia, Cyprus

Affiliation Department of Nursing, Cyprus University of Technology, Limassol, Cyprus

Affiliation Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus

Affiliation Department of Psychological Counseling and Guidance, Faculty of Education, Hasan Kalyoncu University, Gaziantep, Turkey

Affiliation The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong

Affiliation Department of Psychology, Fundación Universitaria Konrad Lorenz, Bogotà, Columbia

Roles Conceptualization, Investigation, Resources, Writing – review & editing

Affiliation Faculty of Psychology, University of La Sabana, Chía, Columbia

Affiliation School of Applied Psychology, University College Cork, Cork, Ireland

Affiliation School of Psychology, University College Dublin, Dublin, Ireland

Affiliation Medical University Innsbruck, Innsbruck, Austria

Affiliation Department of Psychology, Babeş-Bolyai University (UBB), Cluj-Napoca, Romania

Affiliation Instituto Superior de Psicologia Aplicada (ISPA), Instituto Universitário; APPsyCI—Applied Psychology Research Center Capabilities & Inclusion, Lisboa, Portugal

Affiliation Faculdade de Psicologia, Alameda da Universidade, Universidade de Lisboa, Lisboa, Portugal

Affiliation LIP/PC2S, Université Grenoble Alpes, Grenoble, France

Affiliation Department of Biomedicine, Biotechnology and Public Health, University of Cadiz, Cadiz, Spain

Affiliation Instituto ACT, Madrid, Spain

Affiliation Department of Psychology, European University of Madrid, Madrid, Spain

Affiliation Department of Psychology and Sociology, University of Zaragoza, Zaragoza, Spain

Affiliation Vadaskert Child and Adolescent Psychiatric Hospital, Budapest, Hungary

Affiliation Private Pratice, Poland

Affiliation Department of Psychology, University of Jyväskylä, Jyväskylä, Finland

Affiliation Clinic for Psychiatry, Clinical Center of Montenegro, Podgorica, Montenegro

Affiliation Ljubljana University Medical Centre, Ljubljana, Slovania

Affiliation Département de Psychologie, Université du Québec à Trois-Rivières, Trois-Rivières, Canada

Affiliation Department of Psychiatry and Behavioral Science, Duke University, Durham, North Carolina, United States of America

Roles Conceptualization, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

Affiliation Department of Psychology, University of Cyprus, Nicosia, Cyprus

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Andrew T. Gloster,
Demetris Lamnisos,
Jelena Lubenko,
Giovambattista Presti,
Valeria Squatrito,
Marios Constantinou,
Christiana Nicolaou,
Savvas Papacostas,
Gökçen Aydın,

Published: December 31, 2020
https://doi.org/10.1371/journal.pone.0244809
Reader Comments

The COVID-19 pandemic triggered vast governmental lockdowns. The impact of these lockdowns on mental health is inadequately understood. On the one hand such drastic changes in daily routines could be detrimental to mental health. On the other hand, it might not be experienced negatively, especially because the entire population was affected.

The aim of this study was to determine mental health outcomes during pandemic induced lockdowns and to examine known predictors of mental health outcomes. We therefore surveyed n = 9,565 people from 78 countries and 18 languages. Outcomes assessed were stress, depression, affect, and wellbeing. Predictors included country, sociodemographic factors, lockdown characteristics, social factors, and psychological factors.

Results indicated that on average about 10% of the sample was languishing from low levels of mental health and about 50% had only moderate mental health. Importantly, three consistent predictors of mental health emerged: social support, education level, and psychologically flexible (vs. rigid) responding. Poorer outcomes were most strongly predicted by a worsening of finances and not having access to basic supplies.

Conclusions

These results suggest that on whole, respondents were moderately mentally healthy at the time of a population-wide lockdown. The highest level of mental health difficulties were found in approximately 10% of the population. Findings suggest that public health initiatives should target people without social support and those whose finances worsen as a result of the lockdown. Interventions that promote psychological flexibility may mitigate the impact of the pandemic.

Citation: Gloster AT, Lamnisos D, Lubenko J, Presti G, Squatrito V, Constantinou M, et al. (2020) Impact of COVID-19 pandemic on mental health: An international study. PLoS ONE 15(12): e0244809. https://doi.org/10.1371/journal.pone.0244809

Editor: Joel Msafiri Francis, University of the Witwatersrand, SOUTH AFRICA

Received: October 3, 2020; Accepted: December 16, 2020; Published: December 31, 2020

Copyright: © 2020 Gloster 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: All relevant data are within the paper and its Supporting Information files.

Funding: This work was supported by grants from the Swiss National Science Foundation awarded to Andrew T. Gloster (PP00P1_ 163716/1 & PP00P1_190082). The funder provided support in the form of salaries for authors [ATG], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section. One of the authors is employed by a commercial affiliation: Private Pratice, Poland. This affiliation provided support in the form of salaries for authors [BK], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: One of the authors is employed by a commercial affiliation: Private Pratice, Poland. This affiliation provided support in the form of salaries for author BK, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. This does not alter our adherence to PLOS ONE policies on sharing data and materials. No other authors have competing interests to declare.

Introduction

The COVID-19 global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) virus triggered governmentally mandated lockdowns, social distancing, quarantines and other measures in the interest of public health. The mandated lockdowns abruptly and dramatically altered people’s daily routines, work, travel, and leisure activities to a degree unexperienced by most people living outside of war zones. Simultaneously, the highly contagious, yet invisible virus transformed previously neutral situations to perceived potentially dangerous ones: social interaction, touching one’s face, going to a concert, shaking someone’s hand, and even hugging grandparents. Given these changes and looming threat, increases in anxiety and depression can be expected [ 1 ]. Indeed, common psychological reactions to previous quarantines include post-traumatic symptoms, confusion, and anger [ 2 ], though these data stem from quarantines of specific regions or a subgroup of exposed people, such as medical professionals. It therefore remains an empirical question whether such patterns are consistent when entire populations across the globe are simultaneously affected.

For most people, it stands to reason that governmentally mandated lockdowns decrease their activity levels and the number of stimuli experienced compared to pre-lockdown levels. The impact of reducing activities, stimuli and routines on the population is unknown, but various analogue situations can be used to make predictions, like death of a spouse [ 3 ]; hearing loss [ 4 ]; job loss [ 5 ]; long duration expeditions [ 6 ]; poor acculturation [ 7 ]; and even ageing when combined with loneliness [ 8 ]. Each of these situations is associated with increases in psychological distress. This reduction of stimulations may lead to boredom and reductions in reinforcement, which has been associated with depression [ 9 ]. The sum total of these literatures, and some evidence from country specific studies on COVID-19 suggests that for some people, the mental distress in the form of stress, depression, and negative affect are likely reactions to the lockdown; therefore, people’s wellbeing is likely to suffer. Indeed, increased loneliness, social isolation, and living alone are associated with increased mortality [ 10 ]–the exact effect that mandated lockdown and social distancing rules aimed to counteract.

Alternately, the planned slowing down of daily routines can be beneficial. For example, vacations and weekends are highly sought-after–if not always achieved–periods of relaxation and stress reduction [ 11 ]. Likewise, some religious and spiritual traditions encourage simplicity, mindfulness, and solitude with the goal of increasing wellbeing [ 12 ]. It is therefore conceivable that for some people the lockdown could offer a reprieve from daily hassles and stress and even lead to increases in wellbeing. It is therefore equally important to identify protective factors that can buffer against the negative effects of the lockdown.

Although nearly all people around the globe have been subject to some form of lockdown measures to contain the COVID-19 response, variations exist with respect to how each person is confined, even within a single country. For instance, during the COVID-19 pandemic some people were allowed to go to work, whereas others were required to work exclusively from home. For various reasons, some people had difficulty obtaining some basic supplies. Further, some were thrust into the situation of taking care of others (e.g., children, due to closing of schools). Finally, some people lost income as a result of the lockdown, and this is a known risk-factor for poor mental health [ 13 , 14 ]. Finally, a lockdown may be experienced differently the longer it continues and potentially when in confined spaces [ 2 ]. All of these lockdown-specific features may have an impact on one’s mental health, but to date it remains inadequately explored.

As the risk of the pandemic continues, it is important to understand to what degree the virus-induced uncertainty and the lockdown-induced changes in daily routines impact stress, depression, affect, and wellbeing. Towards this end, it is important to identify factors that can mitigate potential negative psychological effects of pandemics and lockdowns. Various social and psychological factors have been identified in other contexts that may also help build resilience in large-scale pandemics such as COVID-19. On the social level, one such candidate is social support, which has repeatedly been found to positively impact mental health and wellbeing [ 15 – 18 ]. Another social factor is the family climate and family functioning, which clearly impacts people’s mental health [ 19 , 20 ]. Psychological factors such as mindfulness and psychologically flexible response styles (as opposed to rigid and avoidant response styles) are behavioral repertoires that have previously been shown to buffer the impact of stress and facilitate wellbeing [ 21 – 24 ].

Given the scope of the COVID-19 pandemic, it is crucial to better understand how a pandemic and associated lockdowns impact on mental health. Thus, the aim of this study was to determine mental health outcomes and to examine known predictors of outcomes to identify psychological processes and contextual factors that can be used in developing public health interventions. It can be assumed, but remains untested, that those with risks in social-demographic factors, living conditions, social factors and psychological factors have more severe reactions to the lockdown. We therefore tested whether outcomes of stress, depression, affect, and wellbeing were predicted by country of residence, social demographic characteristics, COVID-19 lockdown related predictors, social predictors, and psychological predictors.

Participants

The inclusion criteria were ≥18 years of age and ability to read one of the 18 languages (English, Greek, German, French, Spanish, Turkish, Dutch, Latvian, Italian, Portuguese, Finnish, Slovenian, Polish, Romanian, Hong Kong, Hungarian, Montenegrin, & Persian.). There were no exclusion criteria. People from all countries were eligible to participate.

Ethics approval was obtained from the Cyprus National Bioethics Committee (ref.: EEBK EΠ 2020.01.60) followed by site approvals from different research teams involved in data collection. All participants provided written informed consent prior to completing the survey (computer-based, e.g., by clicking “yes”).

A population based cross-sectional study was conducted in order to explore how people across the world reacted to the COVID-19. The anonymous online survey was distributed using a range of methods. Universities emailed the online survey to students and academic staff and also posted the survey link to their websites. In addition, and in order to broaden the sample to older age groups and to those with different socio-demographic characteristics, the survey was disseminated in local press (e.g., newspapers, newsletters, radio stations), in social media (e.g., Facebook, Twitter, etc.), in professional networks, local hospitals and health centers and professional groups’ email lists (e.g., medical doctors, teachers, engineers, psychologists, government workers), and to social institutions in the countries (e.g., churches, schools, cities/townships, clubs, etc.).

Data were collected for two months between 07th April and 07th June 2020. The majority of countries where data were collected had declared a state of emergency for COVID-19 during this time.

Well validated and established measures were used to assess constructs. When measures did not already exist in a language, they were subject to forward and backward translation procedures. Well-validated measures of predictors and outcomes and items measuring COVID-19 related characteristics were selected after a consensus agreement among the members of this study.

Respondents’ countries were coded and entered as predictors.

Socio-demographic status.

Participants responded to questions related to their socio-demographic characteristics including their age, gender, country of residence, marital status, employment status, educational level, whether they have children as well as their living situation.

Lockdown variables.

Participants responded to questions related to lockdown including length of lockdown, whether they need to leave home for work, any change in their finances, whether they were able to obtain basic supplies, the amount of their living space confined in during the lockdown. They were also asked whether they, their partner, or a significant other was diagnosed with COVID-19.

Social factors.

Social factors were measured using the Brief Assessment of Family Functioning Scale (BAFFS; [ 25 ]) and the Oslo Social Support Scale (OSSS; [ 26 ]). The BAFFS items are summed to produce a single score with higher scores indicating worse family functioning. The OSSS items are summed up and provide three levels types of social support: low (scored 3–8), moderate (scored 9–11) and high (scored 12–14).

Psychological factors.

Psychological factors including mindfulness and psychological flexibility. Mindfulness was measured using the Cognitive Affective Mindfulness Scale (CAMS; [ 27 ]). The CAMS produces a single score with higher scores indicating better mindfulness qualities. Psychological flexibility (e.g., hold one’s thoughts lightly, be accepting of one’s experiences, engage in what is important to them despite challenging situations) was measured using the Psyflex scale [ 28 ]. The Psyflex produces a single score with higher scores indicating better psychological flexibility qualities.

Stress was measured using the Perceived Stress Scale (PSS; [ 29 ]). The PSS assesses an individual’s appraisal of how stressful situations in their life are. Items ask about people’s feelings and thoughts during the last month. A total score is produced, with higher scores indicating greater overall distress.

Depression.

Depressive symptomatology was assessed using two items from the disengagement subscale of the Multidimensional State Boredom Scale (MSBS; [ 30 ]). These items assessed wanting to do pleasurable things but not finding anything appealing (i.e., boredom), as well as wasting time. Based on concepts of reinforcement deprivation (i.e., lack of access to or engagement with positive stimuli) that is known to contribute to depression, we added an item that measured how rewarding or pleasurable people found the activities that they were engaging in (i.e., reinforcement). Higher scores indicated higher depressive symptomatology.

Positive affect/ negative affect.

The Positive And Negative Affect Scale (PANAS) was used to measure affect [ 31 ]. The original version of the questionnaire was used with five additional items: bored, confused, angry, frustrated and lonely. All items were scored on a 5-point Likert type scale, ranging from 1 = very little/not at all to 5 = extremely and summed up so that higher scores in the positive-related items indicating higher positive affect and higher scores in the negative-related items indicating higher negative affect. In order to capture additional dimensions of negative affect believed to be relevant to the COVID-19 lockdowns, we additionally added five items: bored, confused, angry, frustrated, lonely.

Wellbeing was assessed using the Mental Health Continuum Short Form (MHC-SF; [ 32 ]); which assesses three aspects of wellbeing: emotional, psychological, and social. The MHC-SF produces a total score and scores for each of the three aspects of wellbeing. The MHC-SF can also be scored to produce categories of languishing (i.e., low levels of emotional, psychological, and social well-being), flourishing (i.e., high levels of emotional psychological and social well-being almost every day), and moderately mentally healthy (in between languishing and flourishing).

Statistical analysis

The mean and standard deviation was calculated for dependent variables that follow the normal distribution while the median and interquartile range (IQR) were computed for non-normally distributed data. Bivariable association between an outcome variable and each predictor was investigated with ANOVA test for categorical predictor and univariable linear regression for numerical predictor. Linear mixed-effect model with random effect for country was performed to consider simultaneously several predictors in the same model and to account for the variation in outcome variable between countries. Four separate linear mixed-effect models were used for each outcome variable, one for each set of socio-demographic, lockdown, social and psychosocial predictors and multicollinearity for each set of predictors was investigated with the variation inflation criterion (VIF). Standardized regression coefficients were computed as effect size indices to measure the strength of the association between predictor variables and outcome variables. The comparison between the country mean and overall mean for each outcome variable was estimated though a linear regression model with dependent variable the mean centering outcome and predictor the country. Cohen’s d effect size of the standardize difference between country mean and the overall mean was computed as a measure of the magnitude of the difference between the two means.

The whole sample was used in linear mixed-effect models while for the comparison of country mean to the overall mean was used the sample from countries with sample size ≥100. The R packages lme4 and effect sizes were used for fitting the linear mixed effect model and to compute the standardized regression coefficients of the linear mixed effect models [ 33 ]. Significance test and confidence intervals were calculated at a significance level of 0.05. The following cut-off values were used for the evaluation of the effect sizes: ‘tiny’ ≤0.05, ‘very small’ from 0.05 to ≤0.10, ‘small’ from 0.10 to ≤ 0.20, ‘medium’ from 0.20 to ≤ 0.30, ‘large’ from 0.30 to ≤ 0.40 and ‘very large’ > 0.40 [ 34 ].

Descriptive

Participants were n = 9,565 people from 78 countries. See supporting information for a participation flowchart ( S1 Appendix ). The countries with the largest samples were: Latvia (n = 1285), Italy (n = 962), Cyprus (n = 957), Turkey (n = 702), Switzerland (n = 550), Hong Kong (n = 516), Colombia (n = 485), Ireland (n = 414), Austria (n = 368), Romania (n = 339), Portugal (n = 334), France (n = 313), Spain (n = 296), Germany (n = 279), Hungary (n = 273), Greece (n = 270), USA (n = 268), Finland (n = 157), Montenegro (n = 147), Poland (n = 135), United Kingdom (n = 100), Slovenia (n = 77), and Canada (n = 60). The remaining countries are listed in the supporting information ( S1 Table ).

Outcome variables

The means, standard deviations, and where appropriate percentage of participants within categories of the five outcome variables can be seen in Table 1 .

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https://doi.org/10.1371/journal.pone.0244809.t001

Predictor variables

A full list of countries can be found in the supporting information ( S1 Table ).

The mean age was 36.9 (13.3) years. A majority of participants were female (77.7%), approximately a fifth male (22.0%), and small minority identified as other (0.3%). More than half of the respondents were either in a relationship (25.7%) or married (36.1%), almost a third were single (30.8%), and the rest were either divorced (5%), widower (1.1%) or other (1.3%). Participants indicated that they lived: alone (14.6%), with both parents (20.8%), one parent (5.1%), with their own family including partner and children (54.1%), or with friends or roommates (5.5%). Less than half of respondents had children (40.8%). Approximately half of the participants were working full time (53.4%), almost a fifth were working part-time (17.5%), 23.2% were unemployed and a small minority were either on parental leave (2.2%) or retired (3.7%).

COVID-19 lockdown variables.

At the time of responding, participants were in lockdown or self-isolation for a median of 5.0 (3.0 IQR) weeks. Most people indicated that they had not been infected with COVID-19 (88.0%), a small minority indicated they had been infected (1.4%) and the rest had symptoms but were unsure (10.6%). Similar patterns were seen with reported infection rates of partners (no: 92.2%, yes: 0.7%, unsure: 7.1%) and of people close to them (no: 86.0%; yes: 5.6%; unsure: 8.4%). With respect to leaving the house for work, almost half (47.7%) indicated that this never occurred, 7.7% indicated leaving only once, whereas an almost equal number indicated leaving a couple times per week (23.7%) or more than three times per week (21.0%). Nearly all participants indicated they were able to obtain all the basic supplies they needed (93.5%). Participants reported having a median inner living space of 90.0 square meters (80.0 IQR) and median outdoor space of 20.0 square meters (192.1 IQR). Finally, with respect to finances, more than half indicated that their financial situation remained about the same (57.9%), a minority indicated it improved (8.9%), and a third reported that their finances had gotten worse (33.3%).

Social and psychological predictors.

Mean values of the other predictors (i.e., social predictors and psychological predictors) can be seen in Table 1 .

Multivariate analyses

Results of multivariate analyses for the outcome of stress can be seen in Table 2 . The largest protective factor against stress was social support (high support vs low support (-3.35, 95%CI, -3.39 to -2.92), with a very large effect size). Positive predictors of stress with large effect sizes were being female (2.42, 95%CI, 2.07 to 2.77) and worsening of finances (2.32, 95%CI, 1.68 to 2.96), whereas psychological flexibility buffered this response (-0.65, 95%CI, -0.69 to -0.62). Higher education levels were also associated with lower levels of stress, with a large effect size (see Table 2 ). Moderate effect sizes for predictors associated with less stress were older age (-0.13, 95%CI, -0.14, -0.11) and mindfulness (-0.69, 95%CI, -0.74, -0.64). Moderate effect sizes of predictors associated with more stress were worse family functioning (0.98, 95%CI, 0.90, 1.06) and not being able to obtain all basic supplies (1.82 95%CI, 1.12, 2.52).

https://doi.org/10.1371/journal.pone.0244809.t002

Differences in reported levels of stress across countries were largely negligible, with the exception of two countries that reported higher levels of stress (Hong Kong (2.85, 95%CI, 2.22, 3.49) and Turkey (2.47, 95%CI, 1.93, 3.02)) and two that reported lower levels of stress (Portugal (-2.50, 95%CI, -3.29, -1.71) and Montenegro (-3.30, 95%CI, -4.49, -2.11)) than the average stress level across all countries. See supporting information for information on each country ( S2 – S6 Tables).

Results of multivariate analyses for the outcome of depression can be seen in Table 3 . The strongest predictor of depression was social support, such that high (-1.30, 95%CI, -1.44, -1.16) and medium levels (-0.73, 95%CI, -0.85, -0.62) of social support were protective against depression (relative to low levels) with a very large and large effect sizes, respectively. The only other large effect size was for psychological flexibility, which also served in a protective manner (-0.20, 95%CI, -0.22, -0.19). Moderate effect sizes of predictors associated with less depression symptoms were also observed for higher education levels (see Table 3 ). Moderate effect sizes of predictors associated with more depression were worse family functioning (0.29, 95%CI, 0.27, 0.32) and not being able to obtain all basic supplies (0.49, 95%CI, 0.27, 0.70).

https://doi.org/10.1371/journal.pone.0244809.t003

The amount of depression symptoms reported on average within countries was similar for most countries with the exception of one country with lower reported levels than average with a large effect size (Austria (-0.71, 95%CI, -0.95, -0.47)) and one with higher levels than average with a large effect size (USA (0.85, 95%CI, 0.58, 1.13)). See supporting information for information on each country ( S2 – S6 Tables).

Results of multivariate analyses for the outcome of affect can be seen in Table 4 . With respect to positive affect, social support (high support vs low support (5.69, 95%CI, 5.23, 6.16) and psychological flexibility (0.77, 95%CI, 0.74, 0.81) were both predictors with very large effect sizes. Interestingly, those who left their house more than three times per week had higher levels of positive affect than those that did not leave their house for work (1.68, 95%CI, 1.18, 2.17), with a medium effect size. Higher education levels were associated with higher levels of positive affect with a medium to large effect size (see Table 4 , PANAS-Positive).

https://doi.org/10.1371/journal.pone.0244809.t004

The amount of positive affect reported on average within countries was similar for most countries with the exception of one country with lower reported levels than average with a large effect size (Finland (-2.96, 95%CI, -4.19, -1.73)) and one with higher reported levels than average with a large effect size (Portugal (2.96, 95%CI, 2.12, 3.80)). See supporting information for information on each country ( S2 – S6 Tables).

With respect to negative affect, social support (high support vs low support (-2.74, 95%CI, -3.2, -2.29) and psychological flexibility (-0.62, 95%CI, -0.66, -0.58) were again the strongest associated predictors, with large effects. Higher education levels were also associated with lower levels of negative affect, with a medium effect (see Table 4 , PANAS-Negative). Higher levels of negative affect were noted, with medium effect sizes, for the predictors: worsening of finances (1.75, 95%CI, 1.10, 2.40) and not being able to obtain all basic supplies (1.6, 95%CI, 0.89, 2.31).

The amount of negative affect reported on average within countries was similar for most countries with the exception of few countries with lower reported negative affect levels than average with a very large effect sizes (Switzerland (-4.96, 95%CI, -5.91, -4.01), Germany (-4.70, 95%CI, -6.03, -3.37) & Austria (-6.49, 95%CI, -7.65, -5.33)) and one with a large effect size (Montenegro (-3.56, 95%CI, -5.39, -1.73). The average amount of negative affect was higher than average in two countries, with very large effects size (Turkey (5.75, 95%CI, 4.92, 6.59) & Finland (7.57, 95%CI, 5.80, 9.34)). See supporting information for information on each country ( S2 – S6 Tables).

Results of multivariate analyses for the outcome of wellbeing can be seen in Table 5 . Once again, social support (high support vs low support (13.20, 95%CI, 12.39, 14.01)) and psychological flexibility (1.42, 95%CI, 1.34, 1.49) were the predictors with the largest effect sizes (very large) on wellbeing. Higher education levels were associated with higher levels of wellbeing with a medium to large effect sizes (see Table 5 ). Medium negative effect sizes were noted for family functioning (-1.98, 95%CI, -2.12, -1.83) and inability to obtain all basic supplies (-3.27, 95%CI, -4.67, -1.87). Two medium positive effect sizes were observed: mindfulness (0.95, 95%CI, 0.86–1.04) and living with friends/roommates ((3.04, 95%CI, 1.59, 4.48), relative to living alone).

https://doi.org/10.1371/journal.pone.0244809.t005

The level of wellbeing reported on average within countries was similar for most countries with the exception of three countries with higher levels with large effect sizes (Austria (4.95, 95%CI, 3.55, 6.34), Finland (5.24, 95%CI, 3.10, 7.38), & Portugal (4.59, 95%CI, 3.12, 6.05)) and two countries with lower levels of wellbeing than average with large (Italy (-4.36, 95%CI, -11.06, 2.35)) and very large effect sizes (Hong Kong (-6.84, 95%CI, -8.02, -5.66)). See supporting information for information on each country ( S2 – S6 Tables).

The COVID-19 is the largest pandemic in modern history. This study assessed nearly 10,000 participants across many countries to examine the impact of the pandemic and resultant governmental lockdown measures on mental health. During the height of the lockdown, the pandemic was experienced as at least moderately stressful for most people, and 11% reported the highest levels of stress. Symptoms of depression were also high, including 25% of the sample indicating that the things they did were not reinforcing, 33% reporting high levels of boredom, and nearly 50% indicating they wasted a lot of time. Consistent with symptoms of stress and depression, 10% of participants were psychologically languishing. These results suggest that there is a subgroup of people who are especially suffering and that in about 50% of the respondents’ levels of mental health was only moderate. Previous studies have found that along with low levels, even moderate levels of mental health (which consists of only moderate levels of emotional, psychological, and social well-being) are associated with increased subsequent disability, productivity loss, and healthcare use [ 35 – 37 ]. Not everyone was suffering, however, as evidenced by the nearly 40% of participants who reported levels of mental health consistent with flourishing. The present results, while serious, do not point to more severe reactions observed in previous samples of selective quarantined individuals or groups [ 2 ]. Perhaps the previously reported distress in these groups is prevented when an entire country or world is in lockdown so that the feeling emerges that “everyone is in it together”.

Importantly, a handful of predictors emerged that consistently predicted all outcomes: Social support, education level, finances, access to basic needs, and the ability to respond psychologically flexible. The consistency of results examining predictors is noteworthy, both in terms of the consistently strong predictors (e.g., social support, education, psychological flexibly, as well as loss of income and lack of access to necessities) and in terms of the other predictors that were either not predictive or only weakly so. All predictors were chosen based on theoretical ties to the outcomes, previous findings, and studies on quarantines [ 2 ].

A novel finding was that people who left their house three or more times per week reported more positive affect than those that left their house less often. It is possible that these people experienced more variation, which contributed to positive affect. It is also possible they experienced a greater sense of normality. Future studies are encouraged to further investigate possible mechanisms through which this result unfolds.

Overall, these patterns did not differ substantially between countries. Although some differences did emerge, they were mostly inconsistent across outcomes. Three countries fared worse on two outcomes each: Hong Kong (stress & wellbeing); Turkey (stress & negative affect); and Finland (lower positive affect and higher negative affect)–though participants in Finland also reported higher levels of wellbeing than average. Two countries had more favorable outcomes than the average levels across all countries: Portugal (lower stress and higher wellbeing) and Austria (lower depression and higher wellbeing). The differences observed are likely due to a combination of chance, sampling, nation specific responses to the COVID-19 pandemic, cultural differences, and other factors playing out in the countries (e.g., political unrest [ 38 ]). If replicated, future studies are encouraged to examine possible mechanisms of these outcomes.

This study provides valuable insights on several levels. First, it documents the mental health outcomes across a broad sample during the COVID-19 global pandemic. Second, it informs about the conditions and resilience factors (social support, education, and psychological flexibility) and risk factors (loss of income and inability to get basic supplies) that affect mental health outcomes. Third, these factors can be used in future public health responses are being made, including those that require large scale lockdowns or quarantines. That is, public health officials should direct resources to identifying and supporting people with poor social support, income loss, and potentially lower levels of education and provide a strategy to mitigate special risks in these subpopulations. The importance of social support needs to be made clear to the public and to the degree possible mechanisms that can contribute to social support should be supported. Further, psychological flexibility is a trainable set of skills that has repeatedly been shown to ameliorate suffering [ 22 , 39 ]; and can be widely distributed with modern technological intervention tools such as digital, internet, or virtual means [ 40 ]. We do not claim, however, that psychological flexibility is the only factor that can be used for interventions. Instead, it is a recognized transdiagnostic factor assessed in this study and one that is feasible to be targeted and modified by interventions and prevention [ 41 – 43 ].

This study is limited by several important factors. First, the results are based on cross sectional analysis and correlations. As such, causation cannot be inferred and any delayed impact of the pandemic and lockdown on peoples’ mental health was not captured. Second, all results of this survey were obtained via self-report questionnaires, which can be subject to retrospective response bias. Third, although the sample was large and based on varied recruitment sources, it was not representative of the population and undersampled people who suffered most from the pandemic (i.e., front line health care professionals, people in intensive care, etc.) or people without internet access, etc. Finally, the country-specific incidence rates and lockdown measures differed across countries. These were not assessed, but future studies are encouraged to investigate how such factors impact mental health outcomes.

These limitations notwithstanding, based on nearly 10,000 international participants, this study found that approximately 10% of the population was languishing during or shortly after the lockdown period. These finding have implications for public health initiatives. First, officials are urged to attend to, find, and target people who have little social support and/ or whose finances have worsened as a result of the measures. Second, public health interventions are further urged to target psychological processes such as psychological flexibility in general to potentially help buffer other risk factors for mental health. Likewise, availability of social support and information about where to get support and remain connected are needed. These recommendations should become part of public health initiatives designed to promote mental health in general, and should equally be considered when lockdowns or physical distancing are prescribed during a pandemic.

Supporting information

S1 table. list of all countries included in the data set..

https://doi.org/10.1371/journal.pone.0244809.s001

S2 Table. Geodemographic predictors for Perceived Stress Scale.

https://doi.org/10.1371/journal.pone.0244809.s002

S3 Table. Geodemographic predictors for MSBS–depression.

https://doi.org/10.1371/journal.pone.0244809.s003

S4 Table. Geodemographic predictors for PANAS positive.

https://doi.org/10.1371/journal.pone.0244809.s004

S5 Table. Geodemographic predictors for PANAS negative.

https://doi.org/10.1371/journal.pone.0244809.s005

S6 Table. Geodemographic predictors for MHCSF—mental health continuum.

https://doi.org/10.1371/journal.pone.0244809.s006

S1 Appendix. Participation flowchart.

https://doi.org/10.1371/journal.pone.0244809.s007

Acknowledgments

We wish to thank the following people for their work in helping to implement the study: Spyros Demosthenous, Christiana Karashali, Diamanto Rovania (University of Cyprus); Maria Antoniade (European University of Cyprus); Ioanna Menoikou (Cyprus University of Technology); Elias Ioannou (University of Nicosia); Sonja Borner, Victoria Firsching-Block, Alexander Fenn (University of Basel); Cristīne Šneidere, Ingrīda Trups-Kalne, Lolita Vansovica, Sandra Feldmane, (Riga Stradiņš University); David Nilsson (Lund University); Miguel A. Segura-Vargas (Fundación Universitaria Konrad Lorenz); Claudia Lenuţa Rus, Catalina Otoiu, Cristina Vajaean (Babes-Bolyai University). We further wish to thank Fabio Coviello and Sonja Borner (University of Basel) for their help in preparing the manuscript.

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The impact of mental health and the COVID-19 pandemic on employability and learning outcomes: evidence from Taiwanese University students

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Published: 28 August 2024
Volume 5 , article number 216 , ( 2024 )

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Yi-Chih Lee ORCID: orcid.org/0009-0006-2565-4918 1

In response to the emergence of COVID-19, schools were forced to adopt online learning, which later transitioned into a hybrid mode of teaching. However, these changes in the teaching and learning mode may have an adverse effect on mental health, thereby affecting learning outcomes. Therefore, providing immediate resource support for disadvantaged groups may improve students’ learning outcomes. This study investigated the impact of mental health on employability, learning outcomes in the context of blended learning, and the support provided by school resources among college students. We then analyzed survey data from university students and examined the associations among mental health, employability, learning outcomes before and after blended learning, frequency of seeking counseling, and school resource support. The research findings indicate that as the severity of mental health worsened, participants perceived lower learning ability for their future careers. Moreover, during the pandemic, there were variations in learning outcomes for students exposed to blended learning, but it was found that female students demonstrated better learning outcomes. It was also determined that it is beneficial for disadvantaged students to promptly apply for school resource support, as such support can contribute to improved learning effectiveness. Establishing mental health prevention mechanisms and providing school and external resources in a timely manner are the best solutions for helping students learn.

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1 Introduction

Mental health is an essential component of individual and collective health and well-being, representing people’s ability to exercise their human rights, not just the absence of disease [ 1 ]. However, under the impact of COVID-19, the global mental health condition has continued to deteriorate [ 1 ]. One in seven children and adolescents aged 10–19 years experience mental health issues worldwide, and suicide is the fourth leading cause of death among adolescents aged 15–29 years [ 2 ]. Individuals with mental health problems often face human rights violations and discrimination, with severe cases leading to premature death.

Mental health issues are prevalent in all countries, with varying prevalence rates based on sex and age [ 1 ]. Moreover, mental health significantly impacts individuals’ performance at school and work, their relationships with family and friends, and their ability to participate in society [ 3 ]. However, not all individuals with mental health issues experience low levels of mental well-being [ 1 ].

Many students with mental health issues pursue higher education, which may involve various pressures in their lives, including academic and social concerns [ 4 ]. Thus, there is a great need for mental health services and support for these students. A prepandemic survey conducted in Canada in 2019 reported that among more than 50,000 university students from 58 institutions, 68.9% experienced extreme anxiety, and 51.6% had experienced depression in the previous 12 months [ 5 ]. During the COVID-19 pandemic in the United States in 2021, a survey of more than 30,000 university students from 41 schools reported that 50.8% of the students experienced moderate psychological distress and 22% experienced severe psychological distress [ 6 ].

During the COVID-19 pandemic, researchers reported that Thai university students exhibited the highest levels of anxiety, whereas Taiwanese students presented the lowest levels of negative psychological responses [ 7 ]. Another study indicated that many Malaysian university students faced mental health issues during the pandemic [ 8 ]. In Taiwan, one out of every four university students sought psychological counseling [ 9 ].

Students choose to pursue higher education with the expectation that higher qualifications will lead to better job opportunities in the future. Learning workplace skills supports individuals in their daily activities in the workplace and ensures that they will be productive and fulfill the requisite job responsibilities. Workplace skills are generally categorized into two types: soft skills, which include communication, teamwork, critical thinking, among others, and hard skills, such as information technology, data analysis, and other skills that are often acquired through formal education [ 10 ]. Therefore, during their university studies, students need to not only focus on their academic courses but also develop their workplace skills. However, university students may encounter challenges with respect to their work performance due to mental health issues [ 11 ].

The first COVID-19 case in 2019 marked the beginning of the pandemic [ 12 ], a crisis that caused significant harm to people’s mental health. In the first year of the pandemic, the global incidence of depression and anxiety increased by 25%, and the number of people with mental health issues rose by nearly 1 billion [ 1 ]. Because of the pandemic, many university students suddenly had to shift from in-person learning to online learning, and the research indicates that this transition had a negative impact on academic performance [ 13 ].

According to a report by the United Nations [ 14 ], the COVID-19 pandemic created multiple stressors that led to increased or intensified anxiety and distress among individuals who previously experienced few to no such symptoms. Some individuals developed mental health issues, while those already suffering from mental health conditions saw their conditions worsen. During the COVID-19 pandemic, the stress arising from changes in academic responsibilities and daily life also exacerbated the mental health of university students [ 15 , 16 ]. A study of college students revealed that respondents reported increased anxiety due to the COVID-19 pandemic, citing concerns about family members contracting the virus, financial pressures, and academic disruptions [ 17 ].

Social status reflects individuals' education and occupation, influences their thoughts and attitudes, and consequently impacts their behavior [ 18 ]. People may seek relative social prestige, a higher economic class, and power in society to highlight their social status and achieve psychological satisfaction [ 19 , 20 , 21 ]. Education not only allows individuals to build their social networks but it also reflects their social standing [ 22 ]. Social status is observed publicly through a person's social mobility, thereby influencing other people’s beliefs about the individual’s level of intelligence. This motivation for status is often magnified into economic inequalities among people from different social backgrounds [ 23 ] given that social status affects individuals in the process of acquiring tangible resources and intangible social influence.

According to the United Nations, vulnerable groups include indigenous populations; ethnic, religious, and linguistic minorities; immigrants, refugees, asylum seekers, and internally displaced persons; individuals living in extreme poverty; women; and LGBTQI individuals [ 24 ]. In Taiwan, the Ministry of Education classifies university students as vulnerable if they fall into one of the two categories, namely, the culturally disadvantaged, which includes new immigrants and their children; and the economically disadvantaged, which includes students from low- and middle- to low-income households, students with disabilities, students whose parents have disabilities, indigenous students, students from families with special circumstances, and vulnerable students who receive financial assistance [ 25 , 26 ]. These classifications also constitute the criteria for defining vulnerable students in this study.

In Taiwan, according to statistics from 2022, the tuition fees at private universities were approximately twice as high as those at public universities, and yet, approximately 40% of university students attend public universities, whereas 60% attend private universities. Public universities receive more resources, but many vulnerable students can only attend private universities and face starting salaries approximately TWD 2,000 lower than their counterparts from public universities after graduation [ 27 ]. In Taiwan, educational attainment significantly influences employment opportunities. Students with lower social status may choose to continue their university studies to have better job prospects, but this decision often entails higher tuition fees and, in some cases, student loans, as there are relatively few educational resources. After entering the workforce, they may receive lower starting salaries or struggle to find good jobs and thus fall into the trap of the poverty cycle [ 27 ].

Vulnerable students at Taiwanese universities can access various resources provided by the Ministry of Education, including tuition assistance, living subsidies, emergency relief grants, accommodation benefits, scholarships, academic counseling funds, peer support funds, career counseling, accommodation and transportation subsidies for those from remote areas attending interviews, etc. [ 25 , 26 , 28 ]. Additionally, universities raise funds to assist these students. In this study, the higher education SPROUT project refers to the external resources provided by the Ministry of Education to support vulnerable students.

Research has shown that being in a marginalized racial group, having low socioeconomic status, being unemployed, and having similar factors are risk factors for negative mental health in adults after disasters, particularly in the postpandemic context [ 29 ]. As a consequence, there is increasing concern about the impact of COVID-19 on the mental health of vulnerable populations [ 30 ], as the economic repercussions may lead to students losing internship opportunities and low-income students experiencing delays in graduation [ 31 ]. Therefore, economically disadvantaged students who faced multiple impacts during the COVID-19 period are in greater need of support from the government, schools, and society [ 32 ].

Previous studies have explored the impact of the mental health of workers on their work performance [ 33 , 34 ], and have confirmed a link between poor mental health and reduced work capacity. Additionally, many studies have investigated the effects of the COVID-19 pandemic on students' mental health and learning outcomes [ 35 , 36 , 37 ]. Paz et al. [ 35 ] synthesize 47 articles and conclude that the COVID-19 outbreak had negative effects on medical students' mental health that resulted in increased levels of stress, depression, and anxiety as well as emotional and behavioral changes. Koh and Daniel [ 36 ] analyze 36 articles on teaching strategies implemented by higher education institutions during the pandemic and report that designing replicable online classes, providing online practical skills training, ensuring integrity in online assessments, and implementing student engagement strategies improve the quality of online learning. Meo et al.'s research suggests that isolation among university students led to emotional distancing from family, colleagues, and friends, resulting in decreased overall work performance and reduced study time, and hence, negative effects on learning outcomes [ 37 ].

However, despite numerous studies exploring the impact of mental health factors and COVID-19 on education and the recognized need to support disadvantaged students affected by the pandemic [ 38 ], there is a paucity of empirical research that comprehensively examines the effects of employability and learning outcomes among students with varying mental health statuses and socioeconomic backgrounds during the pandemic. Furthermore, investigations into the effectiveness of providing appropriate resource support to students in need under the adverse conditions of the pandemic are limited. Therefore, this study significantly contributes to filling this research gap.

This study had several objectives. First, it aimed to investigate the impact of mental health on employability among university students. The second objective was to analyze whether students with different mental health statuses before and after the pandemic were affected differently by various teaching methods with respect to their learning outcomes. The third objective was to explore whether students with different mental health statuses, genders, and social statuses, especially those from vulnerable backgrounds, experienced learning difficulties during the pandemic. Finally, the study aimed to determine whether providing timely resources and support to vulnerable students during the pandemic contributed to improved learning outcomes.

2.1 Samples

This study used secondary data from different databases. The data source was a private university in Taoyuan, Taiwan, which conducted surveys on mental health, employability, learning outcomes before and after the COVID-19 pandemic, and use of scholarships among daytime students. The purpose of administering the psychological health questionnaire was to proactively provide counseling and assistance for high-risk students to support their academic pursuits. The employability survey was aimed at assessing students' individual capabilities and strengths in the workplace. Both questionnaires were administered by the school's psychologists, who personally explained the survey objectives to the students. The age and gender variables used in the study were based on the information provided by the students on their enrollment forms.

Learning outcomes were presented based on the course assessments conducted at Taiwan University from 2021 to 2022, including both in-person and blended teaching approaches in response to the COVID-19 pandemic. In this study, blended teaching refers to a method in which instructors combine online and offline instruction via video conferencing tools or cloud-based smart classrooms as a novel approach for delivering instruction. School-supported financial aid refers to scholarships provided to students with lower social status who voluntarily participated in the higher education SPROUT project and engaged in school activities to receive awards and financial assistance. Survey participants consented and voluntarily completed the questionnaires after being informed of the survey’s purpose.

Before the data analysis, all database information was de-identified. The research project was classified as minimal risk, and the risks to participants were not greater than those encountered by nonparticipants. Following an assessment by the review committee, the project was deemed exempt from review, and an exemption certificate was issued. This project was certified for exemption from the Human Research Ethics Committee at National Cheng Kung University (HREC (Exempt)112–502). The study was performed in accordance with the ethical standards of the 1964 Declaration of Helsinki and its later amendments and comparable ethical standards.

2.2 Measures

The psychological health variables were measured via the Ko Depression Inventory (KDI) [ 39 ], which consists of 26 items. This inventory categorizes depressive symptoms into five major domains: mood (e.g., irritability), physical activity (e.g., decreased or increased appetite), behavioral ability (e.g., psychomotor retardation or agitation), cognitive thinking (e.g., pessimism), and motivation (e.g., loss of interest). The options are presented on a 4-point scale ranging from 0 (not feeling low or rarely feeling low) to 3 (feeling low and depressed all the time, unable to improve, and intolerably distressed). Summing the scores of all items, a total score of 0–9 indicates no depressive symptoms, a score of 10–20 suggests mild to moderate depression, and a score of 21 or above indicates a state of high-level depression. The inventory exhibits good reliability and validity [ 39 ].

The employability survey questionnaire adopted the UCAN Higher Education Employment Competency questionnaire developed by the Taiwan Ministry of Education [ 40 ]. Generic workplace competency refers to the skills required for various professions and are measured across eight categories: communication and expression, continuous learning, interpersonal interaction, teamwork, problem-solving, innovation, work responsibility and discipline, and information technology application. The questionnaire consists of a total of 54 items, with a score of 1 indicating, "I am unable to complete this task and find it difficult to learn," and a score of 5 indicating, "I can perform this task exceptionally well".

2.3 Data analysis

Data analyses were performed via the IBM Statistical Package for the Social Sciences (SPSS) version 18 (Chicago: SPSS Inc.) [ 41 ]. This study used different statistical analyses based on different variables and different situations. The variable analysis in this study was conducted using means, standard deviations, chi-square tests, ANOVA, the Scheffe test, Welch's ANOVA, the Games–Howell test, independent sample t tests, paired sample t tests, and regression analysis. A p -value less than 0.05 indicates statistical significance.

The survey collected data from 2592 students whose average age was 22.9 (SD ± 0.8) years. Table 1 provides the students’ mental health conditions and their basic characteristics, employability, and learning outcomes. The participants underwent a psychological health assessment, and the majority of the students reported having no depressive symptoms, whereas approximately 15.3% indicated that they experienced severe depressive states.

As the severity of their psychological health worsened, the participants perceived that they had weaker workplace competency. There was no significant difference among individuals with different psychological health conditions in the context of face-to-face learning, but learning outcomes varied in the blended learning context. A comparison of learning outcomes before and during the COVID-19 pandemic revealed that students with severe depression experienced the sharpest decline in learning outcomes (75.0 vs. 73.6; p = 0.019). Moreover, during the pandemic, students with severe depression sought counseling more frequently.

A cross-analysis of mental health status and gender revealed that, in the blended learning context, individuals with good mental health, especially women, exhibited better learning outcomes than did men (78.8 ± 12.4 vs. 72.3 ± 14.3; p < 0.001), had fewer absences (14.7 ± 24.1 vs. 25.2 ± 38.3; p < 0.001), and failed fewer subjects (0.9 ± 1.9 vs. 1.4 ± 2.4; p < 0.001). Among those with mild to moderate depression, women also exhibited better learning outcomes than did men (80.2 ± 12.9 vs. 74.0 ± 14.0; p < 0.001), had fewer absences (13.7 ± 28.9 vs. 23.7 ± 35.9; p < 0.001), and failed fewer subjects (0.7 ± 1.7 vs. 1.3 ± 2.5; p < 0.001). Even among those with severe depression, women had better learning outcomes than did men (75.9 ± 14.3 vs. 72.1 ± 14.5; p = 0.031), but there were no statistically significant differences in absences or failed subjects between the genders.

Overall, in the blended learning context, disadvantaged students had lower learning outcomes than did non-disadvantaged students (73.1 ± 16.3 vs. 75.1 ± 13.7; p = 0.048). When the cross-analysis is based on mental health and disadvantaged status, in the blended teaching context, disadvantaged students with good mental health had more absences than did the non-disadvantaged students (33.1 ± 47.0 vs. 20.9 ± 33.1; p = 0.005), while the remaining classifications exhibited no difference. Among the students with mild to moderate depression, the disadvantaged group had poorer learning outcomes than did the non-disadvantaged the group (73.6 ± 15.5 vs. 76.5 ± 13.7; p = 0.037), had more absences (27.7 ± 40.0 vs. 19.2 ± 32.9; p = 0.028), and they also failed more subjects (1.6 ± 3.0 vs. 1.0 ± 2.1; p = 0.041). Among those with severe depression, there were no statistically significant differences between disadvantaged and non-disadvantaged students in terms of learning outcomes, absences, or failed subjects.

With respect to disadvantaged groups, further analysis on the basis of mental health status and gender revealed that among mentally healthy individuals, women had better learning outcomes (77.1 ± 16.1 vs. 69.4 ± 18.0; p = 0.020) and fewer absences (19.3 ± 30.7 vs. 40.2 ± 52.3; p = 0.005). In the case of students with mild to moderate depression, gender was statistically significant only for learning outcomes, with women outperforming men (78.8 ± 15.9 vs. 71.7 ± 15.0; p = 0.029). However, no statistically significant differences between genders were observed among students with severe depression.

Vulnerable students with different mental health statuses who participated in the higher education SPROUT project exhibited improved learning outcomes and failed fewer subjects, as shown in Table 2 . Students who received more financial aid had higher academic achievement and failed fewer subjects. Table 3 shows that students with various mental health statuses experienced better learning outcomes after joining the higher education SPROUT project.

4 Discussion

This study reveals the impact of mental health on the employability of Taiwanese university students, as well as their learning outcomes under different teaching strategies and varied participation in financial aid programs. This study specifically explored these relationships with respect to vulnerable students and gender. This is the first study in Taiwan to integrate mental health status, workplace and professional competency, and support from assistance programs among university students during the COVID-19 pandemic.

This study investigated students with different mental health issues and examined their perceptions regarding whether they had sufficient knowledge and skills to successfully complete work tasks or improve their personal performance. The results indicated that students with good mental health had the best performance, whereas those with severe depression rated their personal ability as the lowest among the three groups. Students with severe depression perceived that they were less proficient in various skills, including expressing their thoughts effectively for others to understand and comprehending information conveyed by others; efficiently planning and managing their time with a growth mindset; adopting appropriate ways to interact with others on the basis of different situations; actively participating in team tasks; having positive interactions with team members to achieve goals; identifying and systematically solving problems; proposing effective methods to improve systems or processes; understanding and executing personal tasks within the organization while adhering to ethical, regulatory, and integrity requirements; and utilizing information technology to manage information effectively. These findings are consistent with previous studies that reported that students with suicidal ideation had lower problem-solving ability than did those without such thoughts [ 42 ]. This suggests that individuals with better mental health are more likely to exhibit personal efficacy and autonomy as well as better ability to interact with others and realize their potential [ 43 ].

Additionally, this study revealed that during the COVID-19 pandemic, students continued to seek psychological counseling from their schools. Before the pandemic, there were no statistically significant difference in learning outcomes based on students' mental states when they were attending in-person classes. However, after the pandemic, the transition to virtual learning had varied effects on students’ mental states. Specifically, students with mild to moderate depression had better learning outcomes. Research has indicated that individuals who experienced social anxiety before COVID-19 tend to prefer virtual learning [ 44 ], which could explain why the students in this study with mild to moderate depression exhibited improved learning outcomes, as long as they were not further affected by external factors. Conversely, another study noted that some students mentioned that during the pandemic, anxiety and stress motivated them to work harder in their studies, but most students believed that high-risk depressive symptoms were associated with lower academic performance [ 45 ]. This study also revealed that the pandemic led to lower learning outcomes among students with severe depression and caused further setbacks in their grades.

In the context of blended learning, gender had a stronger influence on learning outcomes than did mental health status. Compared with men, women outperformed men academically, and among students with mild to moderate depression and those with normal mental health, women received fewer failing grades and had fewer absences. Among the groups with good mental health and severe depression, there were no differences in learning outcomes between non-disadvantaged and disadvantaged students. However, in the mild to moderate depression group, vulnerable students had lower outcomes, with more failing grades and absences. Regarding the impact of gender on learning outcomes during the COVID-19 period, there is no consensus in the current research [ 46 ]. A South African study reported that girls lagged behind boys in reading performance [ 47 ], whereas other studies reported that girls academically outperformed boys [ 48 , 49 ]. In this study, female students had better learning outcomes in the blended learning context. However, some research suggests that the pandemic may have led vulnerable families to allocate valuable educational resources to boys, thereby affecting girls' educational performances [ 50 ]; however, this study did not find any differences in resource allocation, but rather, it revealed better learning outcomes among girls.

With respect to social status, this study analyzed the possibility for individuals to gradually rise from their disadvantaged position by participating in the higher education SPROUT project and by acquiring resources and transforming them into personal capabilities through the learning process. Students with lower social status do not have an inferior learning nature or diminished abilities. The main obstacles that hinder their learning process are economic and cultural. For example, they may need to spend more time working to meet their living expenses, which limits their ability to fully and freely spend time and economic resources on showcasing their talents. However, for students with lower social status, actively pursuing external offerings, such as participating in school scholarship assistance programs, seeking academic guidance, engaging in competitions, and obtaining the certifications required for employment, can provide these students with additional economic resources. This not only helps them meet their basic living needs but also reduces the time spent on work, allowing them to focus more on academic learning.

The results of this study show that disadvantaged students with different mental health conditions can improve their learning outcomes by participating in the higher education SPROUT project. Such students can significantly reduce the number of failed courses, absences, and leaves of absence. By effectively transferring their time resources from work to learning and acquiring multiple professional skills, they are more likely to obtain job interview opportunities in the future. This, in turn, will enable them to effectively transform their social status.

5 Limitations

This study is limited to data from a single university; thus, it reflects only the performance of students within that specific institution. However, the results align with similar findings in studies conducted in different countries. A limitation is that gender minorities, such as nonbinary individuals, were excluded from this study. Furthermore, the scale used in this study is not a depression and employability questionnaire but rather is specifically designed for the COVID-19 pandemic. Another limitation of this research is the inability to obtain reliability and validity data for the questionnaire items. In addition, the survey is an ongoing test that was initiated before the outbreak, and the timing may have had some influence that this study did not take into account. Therefore future research should examine different time points to study the changes in mental health and students' learning outcomes.

6 Conclusion

Overall, our study revealed that the mental health status of university students influenced their employability and learning outcomes in the context of blended learning. During the pandemic, students from vulnerable backgrounds exhibited lower learning outcomes than did those from nonvulnerable backgrounds. Furthermore, this study found that female students outperformed male students across all groups. During the pandemic, students with poorer mental health sought school counseling and guidance at a higher rate. In situations with limited resources, participating in school support programs helped to improve the learning outcomes of vulnerable students with different mental health statuses. Therefore, in the long run, establishing mental health prevention mechanisms and providing immediate access to schools and external resources are the optimal solutions for supporting student learning.

Data availability

The relevant data can be requested from the author via email.

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Lee, YC. The impact of mental health and the COVID-19 pandemic on employability and learning outcomes: evidence from Taiwanese University students. Discov Sustain 5 , 216 (2024). https://doi.org/10.1007/s43621-024-00444-7

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The COVID-19 pandemic has had a huge impact on public health around the globe in terms of both physical and mental health, and the mental health implications of the pandemic may continue long after the physical health consequences have resolved. This research area aims to contribute to our understanding of the COVID-19 pandemics implications for mental health, building on a robust literature on how environmental crises, such as SARS or natural disasters, can lead to mental health challenges, including loneliness, acute stress, anxiety, and depression. The social distancing aspects of the COVID-19 pandemic may have particularly significant effects on mental health. Understanding how mental health evolves as a result of this serious global pandemic will inform prevention and treatment strategies moving forward, including allocation of resources to those most in need. Critically, these data can also serve as evidence-based information for public health organizations and the public as a whole.

Understanding the Mental Health Implications of a Pandemic

Introduction

The world is entering into a new phase with COVID-19 spreading rapidly. People will be studying various consequences of the COVID-19 pandemic and mental and behavioral health should be a core part of that effort. There is a robust literature on how environmental crises, such as SARS or natural disasters, can lead to mental health challenges, including loneliness, acute stress, anxiety, and depression. The social distancing aspects of the current pandemic may have particularly significant effects on mental health. Understanding how mental health evolves as a result of this serious global outbreak will inform prevention and treatment strategies moving forward, including allocation of resources to those most in need. Critically, these data can also serve as evidence-based information for public health organizations and the public as a whole.

The data will be leveraged to address many questions, such as:

Which individuals are at greatest risk for high levels of mental health distress during a pandemic?
As individuals spend more time inside and isolated, how does their mental health distress evolve?
How do different behaviors (such as media consumption) relate to mental health?

Read more about how our experts are measuring mental distress amid a pandemic.

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Kira Riehm, JHSPH
Emily J. Smail, JHSPH
Elizabeth Stuart, JHSPH
Johannes Thrul, JHSPH
Cindy Veldhuis, Columbia University School of Nursing

The Johns Hopkins COVID-19 Mental Health Measurement Working Group developed key questions to add to existing large domestic and international surveys to measure the mental health impact of the pandemic.

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Mental Health Research During the COVID-19 Pandemic: Focuses and Trends

Yaodong liang.

1 Law School, Changsha University, Changsha, China

2 Department of Psychology, University of Toronto St. George, Toronto, ON, Canada

3 Centre for Mental Health and Education, Central South University, Changsha, China

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The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The COVID-19 pandemic has profoundly influenced the world. In wave after wave, many countries suffered from the pandemic, which caused social instability, hindered global growth, and harmed mental health. Although research has been published on various mental health issues during the pandemic, some profound effects on mental health are difficult to observe and study thoroughly in the short term. The impact of the pandemic on mental health is still at a nascent stage of research. Based on the existing literature, we used bibliometric tools to conduct an overall analysis of mental health research during the COVID-19 pandemic.

Researchers from universities, hospitals, communities, and medical institutions around the world used questionnaire surveys, telephone-based surveys, online surveys, cross-sectional surveys, systematic reviews and meta-analyses, and systematic umbrella reviews as their research methods. Papers from the three academic databases, Web of Science (WOS), ProQuest Academic Database (ProQuest), and China National Knowledge Infrastructure (CNKI), were included. Their previous research results were systematically collected, sorted, and translated and CiteSpace 5.1 and VOSviewers 1.6.13 were used to conduct a bibliometric analysis of them.

Authors with papers in this field are generally from the USA, the People's Republic of China, the UK, South Korea, Singapore, and Australia. Huazhong University of Science and Technology, Hong Kong Polytechnic University, and Shanghai Jiao Tong University are the top three institutions in terms of the production of research papers on the subject. The University of Toronto, Columbia University, and the University of Melbourne played an important role in the research of mental health problems during the COVID-19 pandemic. The numbers of related research papers in the USA and China are significantly larger than those in the other countries, while co-occurrence centrality indexes in Germany, Italy, England, and Canada may be higher.

We found that the most mentioned keywords in the study of mental health research during the COVID-19 pandemic can be divided into three categories: keywords that represent specific groups of people, that describe influences and symptoms, and that are related to public health policies. The most-cited issues were about medical staff, isolation, psychological symptoms, telehealth, social media, and loneliness. Protection of the youth and health workers and telemedicine research are expected to gain importance in the future.

Introduction

Although the impacts of the COVID-19 pandemic will be recorded in human medical history and in socio-economic history, various psychological consequences regarding mental health among populations cannot be ignored, including stress, anxiety, depression, frustration, insomnia, and so on. Researchers from universities, hospitals, communities, and medical institutions worldwide have been focusing on mental health problems during the pandemic. They have used questionnaire surveys, telephone-based surveys, online surveys, cross-sectional surveys, systematic reviews and meta-analysis, and systematic umbrella reviews to investigate mental health problems during the pandemic. Two years after the outbreak of the COVID-19, the pandemic has gradually subsided in some countries, while others have adopted a strategy of coexisting with the virus. If more deadly mutant strains do not appear in the future, it is very likely that the pandemic will not climax again. It is pertinent to summarize and study mental health research during the pandemic, because many psychological problems have arisen as a result, and there has been significant interest in research on such issues in the previous two years.

As an effective quantitative analysis method, bibliometrics can be used not only to assess the quality and quantity of published papers, but also to explore research focuses and trends, the distribution of authors and institutions, the impact of publications, journals, and different countries regarding research contributions to the theme. Due to the rapid growth in research in this area, there are now over 1,000 academic papers, and accordingly, it would appear necessary to investigate important, valid, and meaningful information from large databases to guide scientific research. The authors used CiteSpace and VOSviewers to determine the focuses and trends in this regard.

Data Analysis and Visualization

The authors searched the Web of Science (WOS), ProQuest Academic Database (ProQuest), and China National Knowledge Infrastructure (CNKI) to extract publications related to mental health and COVID-19. Their previous research results were systematically collected, sorted, and translated, and CiteSpace 5.1 and VOSviewers 1.6.13 were used to conduct a bibliometric analysis of them.

Data Source and Search Strategy

Our team selected 1,226 papers from 2019 to 2022 using three combinations of keywords, mental health and COVID-19, mental health and new coronavirus, and mental health and novel coronavirus, from the three academic paper databases, WOS, ProQuest, and CNKI. Two explanations are necessary here, the first is about the keywords and the second is about the databases. (1) The reason we used new or novel coronavirus as keywords was that the name COVID-19 has not been determined about 2 years ago. In order not to miss relevant research results, we also included these synonyms as keywords for the search. (2) Among the three databases, WOS and ProQuest, in which most of the English-language papers were published, are well-known to scholars all around the world. However, the CNKI database is not as popular as WOS or ProQuest given that most of the papers in CNKI were published in Chinese. We chose to use the CNKI data for the following three reasons: first, China was the most affected country during the COVID-19 outbreak and Chinese academic journals published significant research on mental health. Second, CNKI is the largest Chinese academic database. Third, after the outbreak, the Chinese government's virus clearance policy has been implemented and continues to date. Strict control has helped suppress the spread of the virus, but has also likely had mental health implications, given the severe reduction in social interactions. Therefore, we think that the Chinese database is appropriate and useful in this study.

About 50% of the articles were from the WOS, about 10% of the articles from ProQuest, and about 40% from CNKI. Basic information such as title, author, institution, country, abstract, keywords, methods, results, and conclusions of all articles, if not in English, are translated into English and analyzed using SiteSpaceII and VOSviewers. Since the keywords include COVID-19 and mental health, synonyms such as novel coronavirus and psychological distress spontaneously appeared while searching. Words that are closely related to the subject, such as public health, quarantine, and insomnia, were most frequently mentioned.

Most articles were published during the period from February 2020 to July 2022, including those pre-published online from April to July, and only one article that had been published in 2019 was included. Judging from the line chart above, since the volume of COVID-19 and mental health-related articles had already risen two times in June 2020 and June 2021 and then remained low until now, it is high time to conclude a previous study on COVID-19 and mental health, to sort out the foci of those studies, and to analyze and predict future trends ( Figure 1 ).

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The volume of COVID-19 and mental health-related articles in 2020–2022.

Scholars from around the world have contributed to the study of mental health issues during the COVID-19 pandemic. The top 10 countries with the largest quantum of publications related to mental health during COVID-19 are the USA, People's Republic of China, England, Canada, Australia, India, Italy, Japan, Iran, and Germany. Wide and active participation of several countries has laid a solid foundation for its future development. Universities, hospitals, communities, and medical institutions around the world have conducted sample surveys of patients, students, community residents, medical workers, and other sample populations of considerable sample sizes since the outbreak. Survey and research methods include questionnaire survey, telephone-based survey, online survey, cross-sectional survey, systematic review and meta-analyses, and systematic umbrella review ( Table 1 ).

Top 20 countries.


1	280	USA	11	27	Spain
2	223	China	12	26	Brazil
3	85	England	13	22	Saudi Arabia
4	69	Canada	14	19	Pakistan
5	68	Australia	15	18	Turkey
6	54	India	16	12	Bangladesh
7	50	Italy	17	11	Sweden
8	41	Japan	18	10	Singapore
9	37	Iran	18	10	Poland
10	27	Germany	20	9	Malaysia

Most papers are from the USA, the People's Republic of China, England, Australia, Canada, India, Italy, Iran, Japan, and Germany. Judging from the country or region co-occurrence graph, England and Canada are in the center of this graph, with India, Poland, Denmark, Spain, South Korea, Portugal, Italy, and Canada around them. England, Australia, Canada, Japan, Brazil, India, Iran, and Germany have done significant research work in this field. In addition, the number of related research papers in the USA and China is significantly larger than that in all other countries ( Figure 2 ).

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Country or region co-occurrence.

In Table 2 , we can see that most names of the top 20 authors are Asian names, and they are mainly from China. Six of them published more than 10 articles by the end of 2021. In the extended ranking, we find that the authors who have published a large number of papers are generally from the USA, China, the UK, South Korea, Singapore, and Australia. The authors Griffiths MD, Cheung T, Xiang Y, Lin C, Wang Y, and Zhang L were very active in this field of study.

Top 20 authors.


1	14	Xiang YT	7	7	Zvolensky MJ
2	13	Zhang L	12	6	Ng CH
2	13	Wang Y	12	6	Pakpour AH
2	13	Cheung T	14	5	Li W
5	11	Li Y	14	5	Li X
5	11	Griffiths MD	14	5	Garey L
7	7	Li L	14	5	Zhong BL
7	7	Zhang Y	14	5	Wang W
7	7	Zhang Q	14	5	Yang Y
7	7	Lin CY	20	4	Hu SH

In the abovementioned graphs, we can see six groups of related authors. The VOSviewer was used to describe the partnership between them. Though six colors were used to separate these groups, there were still lines connecting the groups to represent the partnership between them. We can take Cheung T and Xiang Y as the center of the largest group. Another group with Griffiths MD and Lin C as its center was also significant ( Figures 3 , ,4 4 ).

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Author co-occurrence.

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Author co-occurrence groups.

The top five institutions are Huazhong University of Science and Technology, Hong Kong Polytechnic University, Shanghai Jiao Tong University, Columbia University, and the University of Toronto. Meanwhile, the top five institutions in centrality are the University of Macau, the University of Melbourne, Columbia University, Wuhan University, and the University of Toronto. It is worth mentioning that Huazhong University of Science and Technology and Wuhan University are located in the city of Wuhan, one of the areas most affected by the virus through the outbreak. The society and economy of the city temporarily stagnated at the time, and its medical system was once paralyzed. Eventually, Wuhan City's medical system was fully recovered. The University of Toronto, Columbia University, and the University of Melbourne have played an important role in the research of mental health problems during the COVID-19 pandemic ( Table 3 and Figure 5 ).

Top 20 institutions.


1	25	0.18	Huazhong University of Science and Technology
2	25	0.14	Hong Kong Polytechnic University
3	21	0.12	Shanghai Jiao Tong University
4	19	0.56	Columbia University
5	18	0.44	The University of Toronto
6	16	0.61	The University of Melbourne
7	16	0.35	Harvard Medical School
8	14	0.78	The University of Macau
9	14	0.50	Wuhan University
10	13	0.12	Kings College London
11	13	0.01	Capital Medical University
12	12	0	Nottingham Trent University
13	11	0	Peking University
14	11	0.22	New York University
15	10	0.12	Zhejiang University
16	10	0	The University of California Los Angeles
16	10	0	Sichuan University
18	9	0.21	Dalhousie University
19	9	0	Xi An Jiao Tong University
20	8	0	The University of Calgary

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Institutions' co-occurrence.

As can be seen in Figure 6 , Huazhong University of Science and Technology has led Chinese universities and research institutions, such as Shanghai Jiao Tong University and Peking University, in conducting research on COVID-19 and mental health. Hong Kong Polytechnic University, Fudan University, and the University of Melbourne acted as bridges, connecting famous universities and research institutions in Europe, America, and other countries in the world, such as Kings College London and Harvard Medical School, to jointly study issues in this field. In particular, they conduct joint research, directly or indirectly, through Hong Kong Polytechnic University, which display the important communication and joint role of Hong Kong Polytechnic University.

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Keyword clustering.

Judging from Table 4 , the most mentioned keywords, in addition to COVID-19 and mental health, can be roughly divided into three categories: (1) keywords representing specific groups of people, such as adolescents, young adults, doctors, nurses, medical staff, and healthcare workers; (2) keywords describing influences and symptoms, such as isolation, loneliness, anxiety, depression, stress, and insomnia; and (3) keywords related to public health policies, such as lockdown, social distancing, telehealth, telemedicine, and quarantine.

Keyword clustering I.


227	0.54	Mental health	2020	0
16	0.1	Psychological distress	2020	0
16	0.41	Fear	2020	0
14	0	Lockdown	2020	0
13	0.1	Healthcare worker	2020	0
10	0	Psychological impact	2020	0
9	0	Adolescent	2021	0
7	0.06	Social distancing	2020	0
6	0	Burnout	2021	0
4	0	Distress	2021	0
4	0	Stigma	2020	0
4	0.05	Social media	2020	0
3	0	Trauma	2020	0
3	0	COVID-19	2020	0
2	0	Spirituality	2022	0
20	0.05	Nurse	2020	1
15	0.24	Insomnia	2020	1
14	0.46	Medical staff	2020	1
11	0.05	Resilience	2020	1
8	0.1	Sleep	2021	1
5	0	Qualitative research	2021	1
5	0	Coping	2021	1
5	0.1	Coping strategy	2021	1
4	0.15	Perceived stress	2021	1
4	0	Prevalence	2021	1
4	0	Physician	2021	1
13	0.16	Telehealth	2020	2
10	0.17	Children	2021	2
10	0.27	Telemedicine	2020	2
8	0.21	Mental health service	2020	2
7	0	Quality of life	2021	2
6	0	COVID	2020	2
6	0	College student	2021	2
5	0.21	Coronavirus disease 2019	2020	2
4	0.05	COVID19	2020	2
3	0	Viral infection	2020	2
31	0.21	Novel coronavirus	2020	3
18	0.41	Public health	2020	3
9	0.03	Infectious disease	2020	3
8	0.12	Mentalhealth	2020	3
7	0.07	Psychiatry	2020	3
7	0	Pandemics	2020	3
3	0.03	Young adult	2020	3
3	0	Risk communication	2020	3
3	0	COVID-19 outbreak	2020	3
3	0.12	Psychotherapy	2020	3
112	0.95	Coronavirus	2020	4
14	0.22	Physical activity	2020	4
9	0	Meta-analysis	2020	4
7	0.05	University student	2021	4
6	0.23	Exercise	2021	4
5	0.15	Health	2021	4
4	0	Depressive symptom	2021	4
4	0	Attitude	2021	4
3	0.05	Health care worker	2020	4
537	1.08	COVID-19	2020	5
98	0.6	Pandemic	2020	5
19	0.15	China	2020	5
13	0.66	Epidemic	2020	5
11	0	Social support	2020	5
4	0	Knowledge	2020	5
3	0.05	Psychological stress	2020	5
3	0	Psychological intervention	2020	5
2	0.19	Qualitative study	2022	5
106	0.72	Anxiety	2020	6
95	0.66	Depression	2020	6
57	0	SARS-CoV-2	2020	6
54	0.61	Stress	2020	6
10	0	Ptsd	2021	6
6	0	Outbreak	2020	6
4	0	Sleep quality	2020	6
3	0.1	Isolation	2020	6
25	0	Quarantine	2020	7
21	0.1	COVID-19 pandemic	2020	7
13	0.78	Loneliness	2021	7
10	0	Wellbeing	2021	7
7	0.78	Worry	2021	7
2	0.2	Youth	2022	7
2	0	Suicidal ideation	2022	7
2	0.34	Longitudinal	2022	7

In Graph 7, we can judge that COVID-19, mental health, pandemic, and coronavirus are represented by larger red dots as their centrality indexes are naturally higher. In this bibliometric network map, other keywords emerged next to them and together formed this visualization bibliometric network. Occupational and sociodemographic characteristics are clustered together, while symptoms of mental health problems are clustered next to them. Specific groups of people and their typical symptoms and causes occupy certain areas on the map. For example, typical symptoms of university students and the possible causes of these symptoms are grouped together on the map. Similarly, quarantine policy and its influence are also classified in certain areas. In addition, research methods and solutions appeared sporadically on this map.

Table 5 shows eight groups of core keywords separated from keyword clustering I. Each of these groups contains three keywords, which proves that these keywords appear at the same time in a considerable part of the research, and are more closely related. Keyword ClusteringII cannot only present the outline of existing mental health research in academia, but also highlights the focus of research. In addition, SiteSpaceII and VOSviewers also gave us some clues about the research trends and further development.

Keyword clustering II.


0	13	0.918	2020	Quarantine	COVID-19 pandemic	Psychological distress
1	10	0.936	2020	Epidemic	Telehealth	Telemedicine
2	10	0.925	2020	Nurse	Insomnia	Medical staff
3	9	0.737	2020	Coronavirus	Lockdown	Physical activity
4	9	0.863	2020	COVID-19	Mental health	Pandemic
5	8	0.949	2020	Novel coronavirus	Public health	Mental health
6	7	0.827	2020	Anxiety	Depression	Stress
7	6	0.887	2021	Loneliness	Health	University student

Research Focuses

Medical staff.

The COVID-19 pandemic has exacerbated mental health problems among populations, especially medical staff, patients with COVID-19, chronic disease patients, and isolated people. Doctors, nurses, and other medical staff have significantly higher rates of insomnia than other populations ( 1 ). The researchers obtained the relevant demographic data through the WeChat questionnaire survey. Questions in the questionnaire are related to insomnia, depression, anxiety, and stress-related symptoms during the pandemic. Their research found that, since the outbreak, more than one-third of the medical staff suffered from symptoms of insomnia. Psychological intervention measures were necessary for those people ( 2 ). Research within medical institutions shows that the psychological pressure of medical staff in isolation wards was greater, but had also attracted greater attention from hospital administrators. The concern of hospital managers alleviated the pressure of medical staff to a certain extent. Further, concern for the public also reduced their psychological burden. In terms of anxiety about infection and fatigue factors, the research results showed that the psychological burden of nurses was heavier than that of doctors. Healthcare workers who lived with their own children showed more obvious fatigue and anxiety, which might be due to the fear of their children becoming infected. In terms of workload and work motivation, medical staff who have been working for more than 20 years have a heavier workload, but they can still maintain their enthusiasm to fight against the pandemic ( 3 ). Another survey showed that 73.4% of healthcare workers, mainly physicians, nurses, and auxiliary staff, reported post-traumatic stress symptoms during outbreaks, with symptoms persisting for up to 3 years in 10–40% of the cases. Depressive symptoms were reported in 27.5–50.7%, insomnia symptoms in 34–36.1%, and severe anxiety symptoms in 45% ( 4 ). A subgroup analysis revealed gender and occupational differences, with female health care practitioners and nurses exhibiting higher rates of affective symptoms compared to men and medical staff, respectively ( 5 ).

As a result, depressive symptoms (21%) and anxiety symptoms (19%) are higher during the COVID-19 pandemic compared to previous epidemiological data. About 16% of the subjects suffered from severe clinical insomnia during the lockdown. The pandemic and lockdown seemed to be particularly stressful for younger adults who were under 35 years old, women, people out of work, or those with low incomes ( 6 ). In the fight against the pandemic, China adopted measures to restrict population aggregation, such as the blockade of pandemic areas, individual patient isolation, and restrictions on the movement of people in non-pandemic areas. These measures effectively prevented the spread of the pandemic. At the same time, the use of health codes, grid-like community management, and the operational efficiency of infectious disease information networks have greatly improved. However, quarantine has also brought with it a number of problems, such as increasing psychological pressure on the population, affecting the daily lives of families, and hindering social and economic development ( 7 ). A large sample size study with wide coverage published in 2021 showed that young people quarantined at home in different provinces had different rates of anxiety and depression due to different severity of pandemic situations in different regions. The risk of anxiety and depression was statistically significantly higher in girls than in boys. The rate of anxiety and depression was affected by factors, such as gender, age, and area, as well as the existence of COVID-19 cases in the surrounding area ( 8 ).

Psychological Symptoms

The impact of the aforementioned isolation measures on mental health is only part of the impact of the COVID-19 on mental health. Psychological symptoms brought about by the pandemic have also been systematically sorted out by scholars. These studies show two clues. First, certain people have special psychological symptoms; second, psychological symptoms in different countries of the world are roughly the same. Several factors were associated with a higher risk of psychiatric symptoms or low psychological wellbeing, including female gender and poor self-related health ( 9 ). Relatively, severe symptoms of anxiety, depression, post-traumatic stress disorder, psychological distress, and stress were reported in the general population during the COVID-19 pandemic in China, Spain, Italy, Iran, the USA, Turkey, Nepal, and Denmark. Risk factors associated with measures of distress include female gender, younger age group, the presence of chronic or psychiatric illnesses, unemployment, student status, and frequent exposure to social media or news concerning COVID-19. The pandemic is associated with significant levels of psychological distress that, in many cases, will meet the threshold for clinical relevance. Mitigating the hazardous effects of COVID-19 on mental health is an international public health priority ( 1 ). Infectious disease pandemics often cause some people to act irrationally. The results of a survey based on psychological symptoms and irrational behaviors have drawn some conclusions. First, the vast majority of people remain in good physical and mental health, but some exhibit irrational behaviors. Second, women, elderly people, and those with confirmed cases showed more physical and mental symptoms and irrational behaviors. Finally, paradoxically, people with high education levels showed more mental symptoms, but fewer irrational behaviors ( 10 ).

Telemedicine

Just as the pandemic has enabled the rapid development of online education, the prospects of telemedicine are also favored by experts, observers, and investors. However, there are two restrictive aspects, namely, telemedicine equipment and telemedicine human resources. The application of 5G communication technology, telemedicine equipment, remote monitoring equipment, remote physical sign monitoring equipment, and medical artificial intelligence triage equipment all need to be urgently developed and improved. Jiangsu, a province in China, is a model province of the national project called “Internet + Medical and Health.” During the pandemic, the telemedicine by public hospitals in Jiangsu Province helped improve the efficiency of diagnosis and treatment, alleviating the pressure of offline diagnosis and treatment, and reducing the risk of cross-infection. Subsequently, medical staff were fully supportive of telemedicine. However, there was a shortage of medical staff in fever clinics, obstetrics and gynecology, pediatrics, and psychiatrists that provided telemedicine services, and they lacked corresponding incentive mechanisms ( 11 ). Effective mitigation strategies to improve mental health were developed by public health management experts. To control the rapid spread of COVID-19 and manage the crisis better, both developed and developing countries have been improving the efficiency of their health system by replacing a proportion of face-to-face clinical encounters with telemedicine solutions ( 12 ).

Social Media

There were rumors in various kinds of media during the COVID-19 pandemic. Although we can regard rumors as a disturbing error for psychological measurement, if they are not strictly controlled, their impact on people's mental health and behavior cannot be ignored. A study focusing on the spread of WeChat rumors has explored the psychological perception mechanism of audiences affected by rumor spreading in emergency situations. The study has significant results in the following terms: the form characteristics of the rumors in COVID-19, the ranking of susceptible age groups, the degree of dependence of the test subject on certain media and its psychological impact, and the follow-up behavior of the test subjects related to psychological variables ( 2 ). In 2021, another interesting study based on the data of TikTok videos released by three mainstream media in China showed that they inevitably caused some psychological trauma to the public. However, from the perspective of overall emotional orientation, short-format videos with positive reporting emotional tendencies had an advantage in attracting likes from TikTok users. Positive government responses to pandemic information were very important, and those responses could be recognized and praised by most social media users. Some of the TikTok videos, such as The Plasma of a Recovered Patient Cured 11 Other ICU Patients, The First COVID-19 Test Kit Passed Inspection, and A Frenchman Named Fred gave up Returning to Home to Join China's Anti-COVID-19 Battle, are extremely popular among social media users. Most social media users have been providing spiritual sustenance for people in the pandemic ( 13 ). When a public health crisis occurs, social media plays an important role in increasing public vigilance, helping the public identify rumors, and boosting public morale.

University Students and Loneliness

A study that assessed the adverse impact on the mental health of university students has drawn some conclusions. First, the severity of the outbreak has an indirect effect on negative emotions by affecting sleep quality. Second, a possible mitigation strategy to improve mental health includes ensuring suitable amounts of daily physical activity and deep sleep. Third, the pandemic has reduced people's aggressiveness, probably by making people realize the fragility and preciousness of life ( 14 ). Another research focused on social networks and mental health compared two cohorts of Swiss undergraduate students who were experiencing the crisis, and made an additional comparison with an earlier cohort who did not experience the pandemic. The researchers found that interaction and co-study networks had become sparser, and more students were studying alone. Stressors shifted from fear of missing out on social life to concern about health, family, friends, and their future ( 15 ). Young adults, women, people with lower education or lower income, the economically inactive, people living alone, and urban residents were at greater risk of being lonely during the pandemic. Being a student emerged as a higher than usual risk factor for loneliness during the lockdown ( 16 ). A study to explore the relationship between loneliness and stress among undergraduates in North America showed that the loneliness and stress among college students increased. On one hand, stress plays a key role in the deterioration of college students' mental health; on the other hand, reducing the loneliness of college students is expected to reduce the negative impact of stress on college students' mental health ( 17 ).

Research Trends

Due to the limited training sample of academic papers at present, it is difficult to predict the outcomes accurately. Though we cannot exactly predict the hot issues in the future, we can sort out some possible research trends in this field by analyzing existing research approaches. Psychological symptoms that affected people's mental health during the COVID-19 pandemic will be discovered further, especially those that probably continued to affect people's mental health even after the pandemic is controlled.

Studies on mild psychological symptoms, such as mild insomnia and anxiety, tend to decrease slowly, and in the case of severe problems caused by the pandemic, or severe psychological symptoms, such as clinical insomnia, depression, bipolar disorder, the corresponding in-depth research will continue. The impact of a global pandemic on the mental health of the global population must be profound and worthy of study. Due to the rapid development of COVID-19, many famous universities and research institutions have not had enough time to collect sufficient data and relevant research materials. The different effects on populations in different countries with different pandemic prevention policies are not yet fully displayed.

Regardless of how research on mental health develops, the COVID-19 pandemic has indeed brought us some new insights. As mentioned in many articles on mental health interventions for adolescents and college students, the mental health of specific populations and the development of telemedicine all deserve continued academic attention. Mental health intervention for adolescents and college students is a means to consider and prepare for the future. To ensure responsible and accountable behavior for future generations, we should all pay attention to the research and application of this method. Caring for specific groups of people, such as doctors, nurses, and other healthcare workers, and studying how to protect them in a global pandemic is a topic that global academia must study in the future, or we will lose protection the next time the virus sweeps the world. In addition, telemedicine is the trend in the future, and face-to-face diagnosis and treatment will undoubtedly increase the risk of cross-infection during the pandemic. Therefore, the development of telemedicine is an important way to avoid contact between the patients. The COVID-19 pandemic has accelerated the research and development of telemedicine.

Limitations

(1) Though we have selected three databases for analysis, there are still some databases that may be related to this field that are not covered in this study. (2) Since COVID-19-related research was started just 2 years ago, the results of the bibliometric analysis may vary after adding new data. (3) The citation frequency of articles is influenced by the time of publication, thus previously published articles should be cited more frequently than new ones. (4) Bibliometric data change over time, and different conclusions may be drawn over time. Therefore, this study should be updated in the future.

Conclusions

The most mentioned keywords, in addition to COVID-19 and mental health, can be roughly divided into three categories: keywords representing specific groups of people, keywords describing influences and symptoms, and keywords related to public health policies. The most mentioned issues were about medical staff, quarantine, psychological symptoms, telemedicine, social media, and loneliness. Mild psychological symptoms, such as insomnia, depression, and anxiety, tend to decrease slowly, while severe ones, such as severe clinical insomnia, depression, and bipolar disorder, are yet to be discovered. The importance of studies on the protection of youth medical staff and telemedicine studies will become even more significant in the future. While physical health is threatened by the pandemic, human mental health also suffers. Judging from the current situation of pandemic prevention and control, if severe prevention and control measures are taken, the impact of COVID-19 on the health of the social population is controllable; if a strategy of coexistence with the virus is adopted, as long as a new deadly mutation of COVID-19 does not emerge, the outcomes can be controllable. However, the impact of the pandemic on human mental health is not easy to predict. In addition to the abovementioned papers on mental health, the author also noted that some papers focused on neuromedicine pointed out that the virus might have some damage to the normal working mechanism of the human nervous system, but these studies are outside the scope of mental health research, at least for now. This study aims to summarize the observations, analysis, and research of scholars on mental health during the pandemic from 2020 to early 2022, with a view to provide more clues for future researchers. We hope that more researchers will build on our research to discover new research areas and new questions to help more countries, groups, and individuals affected by the COVID-19 pandemic.

Data Availability Statement

Author contributions.

YL was responsible for the concept and design, drafting this article, and bibliometric analysis. YL, LS, and XT were responsible for the revision and data collection. All authors contributed to this article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

The authors thank the study participants for their time and effort.

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COVID-19 and Mental Health

What is covid-19.

COVID-19 is a disease caused by a virus named SARS-CoV-2. COVID-19 most often affects the lungs and respiratory system, but it can also affect other parts of the body. Some people develop post-COVID conditions, also called Long COVID . These symptoms can include neurological symptoms such as difficulty thinking or concentrating, sleep problems, and depression or anxiety.

Why is NIMH studying COVID-19 and mental health?

Both SARS-CoV-2 and the COVID-19 pandemic have significantly affected the mental health of adults and children. Many people experienced symptoms of anxiety , depression , and substance use disorder during the pandemic. Data also suggest that people are more likely to develop mental illnesses or disorders in the months following COVID-19 infection. People with Long COVID may experience many symptoms related to brain function and mental health .

While the COVID-19 pandemic has had widespread mental health impacts, some people are more likely to be affected than others. This includes people from racial and ethnic minority groups, mothers and pregnant people, people with financial and housing insecurity, children, people with disabilities, people with preexisting mental illnesses or substance use problems, and health care workers.

How is NIMH research addressing this critical topic?

NIMH is supporting research to understand and address the impacts of the pandemic on mental health. This includes research to understand how COVID-19 affects people with existing mental illnesses across their entire lifespan. NIMH also supports research to help meet people’s mental health needs during the pandemic and beyond. This includes research focused on making mental health services more accessible through telehealth, digital tools, and community-based interventions.

NIMH is also working to understand the unique impacts of the pandemic on specific groups of people, including people in underserved communities and children. For example, NIMH supports research investigating how pandemic-related factors, such as school disruptions, may influence children’s brain, cognitive, social, and emotional development.

Where can I learn more about COVID-19 and mental health?

NIMH video: Mental Illnesses and COVID-19 Risks
NIMH Director’s Messages about COVID-19
NIMH events about COVID-19
NIMH news about COVID-19

Where can I learn more about Long COVID and COVID-19?

NIH page on Long COVID
NIH RECOVER Initiative
CDC COVID-19 resources

How can I find help for mental health concerns?

If you have concerns about your mental health, talk to a primary care provider. They can refer you to a qualified mental health professional, such as a psychologist, psychiatrist, or clinical social worker, who can help you figure out the next steps. Find tips for talking with a health care provider about your mental health.

You can learn more about getting help on the NIMH website. You can also learn about finding support and locating mental health services in your area on the Substance Abuse and Mental Health Services Administration (SAMHSA) website.

Last Reviewed: May 2024

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ORIGINAL RESEARCH article

The effect of covid-19 on mental health and wellbeing in a representative sample of australian adults.

A correction has been applied to this article in:

Corrigendum: The Effect of COVID-19 on Mental Health and Wellbeing in a Representative Sample of Australian Adults

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1 Research School of Psychology, The Australian National University, Canberra, ACT, Australia
2 Centre for Research on Ageing, Health and Wellbeing, Research School of Population Health, The Australian National University, Canberra, ACT, Australia
3 Centre for Mental Health Research, Research School of Population Health, The Australian National University, Canberra, ACT, Australia
4 Department of Global Health, Research School of Population Health, The Australian National University, Canberra, ACT, Australia
5 National Centre for Epidemiology and Population Health, Research School of Population Health, The Australian National University, Canberra, ACT, Australia

There is minimal knowledge about the impact of large-scale epidemics on community mental health, particularly during the acute phase. This gap in knowledge means we are critically ill-equipped to support communities as they face the unprecedented COVID-19 pandemic. This study aimed to provide data urgently needed to inform government policy and resource allocation now and in other future crises. The study was the first to survey a representative sample from the Australian population at the early acute phase of the COVID-19 pandemic. Depression, anxiety, and psychological wellbeing were measured with well-validated scales (PHQ-9, GAD-7, WHO-5). Using linear regression, we tested for associations between mental health and exposure to COVID-19, impacts of COVID-19 on work and social functioning, and socio-demographic factors. Depression and anxiety symptoms were substantively elevated relative to usual population data, including for individuals with no existing mental health diagnosis. Exposure to COVID-19 had minimal association with mental health outcomes. Recent exposure to the Australian bushfires was also unrelated to depression and anxiety, although bushfire smoke exposure correlated with reduced psychological wellbeing. In contrast, pandemic-induced impairments in work and social functioning were strongly associated with elevated depression and anxiety symptoms, as well as decreased psychological wellbeing. Financial distress due to the pandemic, rather than job loss per se , was also a key correlate of poorer mental health. These findings suggest that minimizing disruption to work and social functioning, and increasing access to mental health services in the community, are important policy goals to minimize pandemic-related impacts on mental health and wellbeing. Innovative and creative strategies are needed to meet these community needs while continuing to enact vital public health strategies to control the spread of COVID-19.

Introduction

The new coronavirus SARS-CoV-2 (COVID-19) pandemic is unprecedented in recent history, with global impacts including high rates of mortality and morbidity, and loss of income and sustained social isolation for billions of people. The effect this crisis will have on population mental health, both in the short- and long-term, is unknown. There is minimal evidence about the acute phase mental health impacts of large-scale epidemics across communities. Existing work has focused on those individuals most directly affected by disease (e.g., infected individuals and their families, healthcare workers ( 1 – 5 ) and examined mental health impacts across broader communities only after the acute phase has passed ( 1 ). In the acute phase however, fear about potential exposure to infection, loss of employment, and financial strain are also likely to increase psychological distress in the broader population ( 1 – 4 ). This distress may be further exacerbated in individuals who have experienced prior traumatic events ( 2 ). In the longer term, grief and trauma are likely to emerge ( 3 ) and, as financial and social impacts become entrenched, risk of depression and suicidality may increase ( 2 , 6 – 8 ).

Reports of the mental health impacts of previous severe health epidemics have focused primarily on disease survivors [e.g., of Ebola virus disease ( 2 ) and SARS ( 1 )]. Almost invariably, these studies show survivors experience greater psychological distress post-epidemic than others from affected communities ( 1 , 3 ). Risk for psychological distress may also be greater for people employed in occupations that potentially expose them to infection ( 4 , 5 ), and in those who have friends or family members who have been infected ( 3 ). However, in the acute phase of COVID-19, there are clear reasons to also expect that Government policies and physical distancing measures aimed at limiting disease spread will impact mental health in the broader community. For instance, loss of employment ( 6 ), financial strain ( 9 ), and social isolation ( 8 , 10 ) are all well-documented correlates of mental health problems. In many countries, physical distancing measures have already resulted in an enormous increase in unemployment ( 11 ), likely causing significant financial strain for many.

Gathering early evidence of the impacts of COVID-19 is vital for informing mental health service delivery as the pandemic and its extended effects continue. The present study surveyed a representative sample of Australians from 28 to 31 March 2020, during the acute phase of the pandemic in Australia. Figure 1 shows the number of confirmed cases in Australia had just started to escalate at this time, relative to global cases. A total of 19 deaths had been reported in Australia by the survey close, relative to over 36,500 across the globe. In the fortnight leading up to the survey, the Australian government had closed restaurants, bars, and churches, severely restricted the size of public and private gatherings, banned foreign nationals from entering Australia, and was enforcing strict quarantine measures for Australians returning from overseas.

Figure 1 The cumulative number of COVID-19 confirmed cases and deaths (A) across the globe and (B) in Australia, in the month leading up to the first survey wave of this study. Case and death data are from https://covid19.who.int/ .

The present study aimed to document the initial mental health scenario across the Australian community and examine its association with exposure to the broad COVID-19 environment at this critical acute phase by: (1) measuring the current prevalence of clinically significant symptoms of generalized anxiety and depression, including associations with other recent adversities; and (2) investigating the degree to which symptom severity is associated with exposure to COVID-19, and pandemic-related impacts on employment, finances, and social functioning. We also accounted for exposure to the catastrophic bushfires that occurred across Australia in November 2019–January 2020. We hypothesized that greater exposure to COVID-19, and impairment in employment, finances, and social functioning, would be associated with higher psychological distress and decreased psychological wellbeing

Study Design and Sample

We established a new longitudinal study—The Australian National COVID-19 Mental Health, Behavior and Risk Communication (COVID-MHBRC) Survey—to investigate the impact of the COVID-19 pandemic on a representative sample of the Australian adult population (≥18 years). Participants were required to be able to respond to an online English language survey. The study comprises seven survey waves initiated online fortnightly, via Qualtrics Research Services. Recruitment was conducted using quota sampling to obtain a representative sample on the basis of age group, gender, and geographical location (State/Territory). Participants gave written informed consent after receiving a complete description of the study. The study was approved by The Australian National University Human Research Ethics Committee (number 2020/152). The full study protocol is available here: https://psychology.anu.edu.au/files/COVID_MHBRCS_protocol.pdf .

We report data (N = 1,296) from the first assessment (Wave 1, 28–31 March 2020). The sample size requirement estimate was based on planned power analyses for finding an effect of f 2 = 0.1 in linear and logistic regression models, setting 1 - β = .95 and α = .05, and taking into account variations in the prevalence of binary outcomes and attrition over the stages of the longitudinal survey, and an allowance for 10% unusable data. Our sample of N = 1,296 was only 2% less than our target sample of N = 1,320 (see Supplement S1 for additional details). Only 2–3% of the data were unusable for the present analyses.

Table 1 reports Wave 1 sample distributions by gender, age, and location. These distributions aligned well with population data from the Australian Bureau of Statistics ( 12 ), demonstrating that a representative sample of the Australian community was achieved.

Table 1 Sample demographics and comparison with population data from the 2016 Australian Census ( 12 ).

Survey Measures

Symptoms of depression and anxiety over the last 2 weeks were assessed by the Patient Health Questionnaire-9 (PHQ-9) ( 13 ) and Generalized Anxiety Disorder-7 (GAD-7) ( 13 ) respectively. These measures align closely with diagnostic criteria for major depressive disorder and generalized anxiety disorder respectively ( 14 ). General psychological wellbeing over the last 2 weeks was measured using the World Health Organization Wellbeing Index (WHO-5) ( 15 ).

COVID-19 exposure was computed as the sum of self-reports of possible or actual exposures to the virus, of the related population health response, or of close social impact including: having been diagnosed with the virus, awaiting results from a test, having tested negative to the test, being in direct contact with a carrier of the virus, having had to isolate in the past, having chosen to isolate in the past, being currently forced to isolate, currently choosing to isolate, having a family member diagnosed with the virus, having a family member in isolation, knowing someone who was diagnosed, knowing someone in isolation, or being asked to work from home because of the virus.

Our measures of the work and social impacts of COVID-19 were whether someone had lost their job due to COVID-19 (yes/no); was working from home due to COVID-19 (yes/no); was experiencing financial distress due to COVID-19 (six-point Likert-type rating, from Not at all to Extremely); and the overall extent to which their work and social activities were impaired by COVID-19, measured using the Work and Social Adjustment Scale (WSAS) ( 16 ). For the WSAS, participants rated the level of impairment COVID-19 had caused (eight-point Likert-type rating, from Not at all impaired to Very severely impaired) for five work and social domains (ability to work, home management, social leisure activities, private leisure activities, and ability to form and maintain close relationships).

We also measured other background factors that could be associated with mental health: age (in years); gender (male/female/other); years of education; partner status (yes/no); living alone (yes/no); living with dependent children (yes/no); existing health, neurological, or psychological conditions, diagnosed by an appropriate clinician (yes/no); recent exposure to bushfire smoke (yes/no) or fire (yes/no); and impact of other recent adverse life events (five-point Likert-type rating, from Not at all to Extremely). Regarding the bushfire exposure variables, our reason for separating out smoke from fire is that many Australians who were exposed to smoke lived far away from the actual fires and their home/region was never under direct threat. The major impact for smoke-but-not-fire affected individuals was poor air quality, which prohibited people from spending time outside for several weeks over the Summer.

Statistical Analysis

Statistical analyses were conducted in R version 3.6.3 under RStudio version 1.1.456 ( 17 ). Multiple linear regression was the primary technique employed to assess correlates of poor mental health. Models were checked and showed an absence of multicollinearity, outliers, and non-normality in the residuals. However, as is typical in non-clinical samples, the PHQ-9 and GAD-7 variables had high frequencies at their lowest possible values, resulting in incorrigible skew. Therefore, compound Poisson-gamma (Tweedie distribution) generalized linear models ( 18 ) were estimated as a check on the linear models ( Supplement S2 ). Their results were consistent with the linear models. Likewise, the models included categorical predictors with small subsample sizes, so cross-validation was conducted to ensure that the models were stable ( Supplement S3 ). Overall, <1% of data were missing. Models reported in the main text dealt with these cases using listwise deletion. We also multiply imputed the missing values and reran the models, which produced the same pattern of findings ( Supplement S5 ).

Table 2 presents our sample characteristics. Overall, 20.3 and 16.4 of our sample scored above the clinical cut-offs on our depression (PHQ-9) and anxiety (GAD-7) measures respectively. Table 3 shows these rates are notably elevated compared to other community-based samples. Even among individuals without a current diagnosis, the rates remained elevated well above levels seen in other representative community-based samples.

Table 2 Description of sample characteristics, including comparison of men and women.

Table 3 Prevalence of depression and generalized anxiety based on self-reported current mental health diagnosis.

Investigation of the relationships between our predictor measures and three mental health outcome measures used a Bonferroni adjusted significance threshold of 0.17 to control for the three sets of comparisons, i.e., α = .05/3 = .017. Note, all three measures showed good reliability (see Supplement S6 ).

Our initial univariate tests revealed that higher levels of depression and anxiety symptoms, and lower psychological wellbeing (WHO-5), were all associated with job loss and financial distress, and overall work and social impairment due to COVID-19, as measured by the WSAS. Being required to work from home was not associated with any mental health effects at this acute stage of the pandemic, all ps > 0.27 (see Supplement S6 for all univariate results).

The linear regression models, presented in Table 4 , established that the effects of financial distress and overall work and social impairment were independent, and not better accounted for by demographic or other background factors. Job loss however did not have a significant independent association with mental health after accounting for financial distress and other covariates, all ps > 0.25.

Table 4 Linear regression models for each mental health outcome.

In contrast, the regression analyses found no significant unique association between exposure to COVID-19 and depression or anxiety symptoms, or wellbeing.

Depression and anxiety symptoms were also elevated in people who had experienced other recent adversities, although this did not include direct exposure to the recent catastrophic Australian bushfires. Exposure to bushfire smoke was however associated with decreased wellbeing.

Finally, within these regression models, we also found that younger age, identifying as female, and having at least one current mental health disorder were each independently associated with higher levels of depression and anxiety, and decreased wellbeing.

We found the social, work, and financial disruptions induced by the acute phase of the COVID-19 pandemic were associated with considerable impairments in community mental health in Australian adults. In contrast, exposure to COVID-19 was not found to predict mental health in this cohort. A key strength of this study was the testing of a representative community sample early in the pandemic, providing rapid evidence of population mental health status. The results highlight that epidemics may cause serious problems for community mental health in the acute phase of disease.

Indeed, our results suggest that, at a population level, changes to social and work functioning due to COVID-19 were more strongly associated with decrements in mental health than amount of disease contact. This finding is consistent with a recent UK-based finding that their citizens were more concerned about how societal changes will impact their psychological and financial wellbeing, than becoming unwell with the virus ( 7 ). This finding is also consistent with emergent work indicating that loneliness is playing a central role in the observed mental health impacts of the COVID-19 pandemic ( 22 – 24 ). Altogether then, it is evident that the necessary public health arrangements surrounding the pandemic are having serious implications for community mental health, via their disruption to social and work functioning.

However, this does not mean the mental health costs of pandemic-related social changes will inevitably be greater than those caused by exposure to disease. In Australia, mortality rates were very low at the time of this study, and the health system had capacity to meet demand. The relatively low case rates were also reflected in our sample; although the majority of the sample had some exposure, such as needing to self-isolate, only 36 participants reported direct exposure to the virus (self or close contact diagnosed). The short-term mental health impacts of disease contact may be considerably greater in communities that have high mortality rates, and health systems over-burdened by disease. In the longer-term, disease contact may also lead to elevated levels of trauma and grief for affected individuals ( 3 ).

The elevated levels of psychological distress observed in this study indicate mental health services are likely to experience increased demand during pandemics. Following recommended physical distancing guidelines, these will need to be delivered flexibly, leveraging resources for telehealth and internet-based Cognitive Behavior Therapy (CBT) programs, which have been shown to be effective in preventing and treating common mental disorders ( 7 , 25 , 26 ). There may also be an increased role for community cohesion strategies ( 27 ) and peer support ( 28 ), for instance, drawing on the experience and knowledge of people already living with mental health issues to support those experiencing these issues for the first time.

The findings also provide clear evidence that minimizing social and financial disruption during the COVID-19 pandemic should be a central goal of public health policy. A key challenge is how to best achieve this goal without compromising public safety by, for instance, relaxing physical distancing restrictions too early. Our results suggest policy approaches that target financial support to those experiencing financial strain may be useful, rather than on the basis of lost employment alone. We also found that well-established risk factors for poorer mental health—younger age, identifying as female, and having a pre-existing mental health condition—continue to be associated with increased risk within the pandemic context. Governments should consider additional measures to monitor and support these at-risk groups. Psychosocial interventions to support multiple aspects of wellbeing, including minimizing financial debt, may have positive impacts on depression and anxiety in the community ( 29 ). Clinicians should also remain vigilant for potential added social and financial impacts that existing clients in primary care and psychological settings may be experiencing.

A possible limitation of the present study is the use of self-report scales that may not characterize mental health status with the accuracy of structured clinical interviews, although both the PHQ-9 and GAD-7 have previously demonstrated strong alignment with clinical diagnosis in population samples ( 14 ), and the WHO-5 is also well-validated ( 15 ). Another potential issue is the influence of selection bias on the prevalence of mental health problems seen in this sample, however, the likelihood of this is low. We were careful to ensure the recruitment advertisement did not mention the topic or nature of our survey (e.g., no mention of mental health or COVID-19 at all), and the service we used also recruits participants for non-psychological research (i.e., market research panel). Most importantly, we did obtain a sample that was representative of the Australian population by age, gender, and location. It is however important to note that online survey methods may bias samples towards people who have good internet literacy and access ( 30 ). This type of bias may have a disproportionate impact on subsections of the population, such as older adults.

Finally, this initial report of our work is cross-sectional. The observed associations may not reflect causal effects, and the nature of any causal relationships may be more complicated than our interpretation suggests (e.g., possible bi-directional effects between psychological distress and social/occupational functioning). We intend to balance the necessity of providing our first wave findings in a timely fashion, to rapidly inform ongoing global responses to the pandemic, by reporting longitudinal outcomes as they become available in the coming months. Examination of population subgroups within our sample may also be possible in longitudinal analyses, although additional targeted studies may be required to provide greater insight into how specific vulnerable groups are affected. These findings should also be considered in combination with other studies that survey the mental health impacts of COVID-19 in communities that have adopted different approaches to managing the pandemic and/or have differing social structures (e.g., low GDP) to Australia.

In conclusion, the current study provides a snapshot of the acute phase impact of COVID-19 on the mental health of the Australian adult community. The findings are concerning, suggesting markedly elevated rates of depression and anxiety, even among individuals with no current diagnosis. This worsening of mental health may also have been exacerbated by the recent severe bushfire season Australians had experienced in the months leading up to the pandemic, although bushfire exposure was controlled for in our analyses. Overall, the findings suggest that interventions to counteract the social, financial and role disruptions induced by COVID-19, particularly among people with existing health conditions, are likely to have the greatest impact on community mental health and wellbeing.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The studies involving human participants were reviewed and approved by the Australian National University Human Research Ethics Committee. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

All authors contributed to the design and conceptualization of the study, which was coordinated by AD. AD, PJB, and LMF contributed to the literature review. AD, PJB, YS, MS, and NC contributed to the data analyses and formulation of the manuscript, with input from all other authors. AD, PJB, NC, and MS drafted the manuscript and all authors critically revised the manuscript. All authors contributed to the article and approved the submitted version.

This study was funded by the ANU College of Health and Medicine, ANU Research School of Psychology, and ANU Research School of Population Health. PJB is supported by National Health and Medical Research Council (NHMRC) Fellowship 1158707. ALC is supported by NHMRC Fellowships 1122544 and 1173146. LMF is supported by Australian Research Council Discovery Early Career Researcher Award (ARC DECRA) DE190101382. YS is supported by ARC DECRA DE180100015. AG and ARM are supported by funding provided by the ACT Health Directorate for ACACIA: The ACT Consumer and Carer Mental Health Research Unit.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank Patrice Ford for assistance with preparing this manuscript and Georgia Baines for media monitoring.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyt.2020.579985/full#supplementary-material

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Keywords: coronavirus, COVID-19, bushfire, mental health, anxiety, depression, financial strain

Citation: Dawel A, Shou Y, Smithson M, Cherbuin N, Banfield M, Calear AL, Farrer LM, Gray D, Gulliver A, Housen T, McCallum SM, Morse AR, Murray K, Newman E, Rodney Harris RM and Batterham PJ (2020) The Effect of COVID-19 on Mental Health and Wellbeing in a Representative Sample of Australian Adults. Front. Psychiatry 11:579985. doi: 10.3389/fpsyt.2020.579985

Received: 03 July 2020; Accepted: 07 September 2020; Published: 06 October 2020.

Reviewed by:

Copyright © 2020 Dawel, Shou, Smithson, Cherbuin, Banfield, Calear, Farrer, Gray, Gulliver, Housen, McCallum, Morse, Murray, Newman, Rodney Harris and Batterham. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Amy Dawel, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Developmental Timing of Adversity and Mental Health Across the Lifespan—Time to Rethink Sensitive Periods?

1 Department of Child and Adolescent Psychiatry and Behavioral Science, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
2 Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia
Original Investigation Negative Life Events and Emotional Symptoms From Ages 2 to 30 Years William E. Copeland, PhD; Ryan Keen, PhD; Guangyu Tong, PhD; Lilly Shanahan, PhD JAMA Network Open

Associations of adversity in the form of traumatic experiences and stressful events with health outcomes are well appreciated, particularly when adversity is experienced early in the lifespan. 1 Copeland and colleagues 2 address an open question regarding the role of development in the association of adversity with mental health. Through integration of data from 3 studies spanning the age range from 2 to 30 years and via combination of cross-sectional and longitudinal analyses, this study 2 found that the magnitude of the association of adversity with depressive and anxiety symptoms was consistent across developmental stages. The authors 2 additionally found that, overall, compared with past exposure to trauma, recent stressful events that are not considered traumatic had similar or even greater associations with mental health symptoms. Last, they report that the combination of recent stressful events and past trauma resulted in additive, but not interactive, effects on mental health symptoms. 2

These findings challenge some theoretical models of developmental science. Based on the sensitive periods framework, the brain is differentially susceptible to adversity throughout development given differences in neuroplasticity across developmental stages, 3 such that adversity experienced in a certain developmental stage should have different associations with mental health than if experienced in other stages. Furthermore, the findings do not align with developmental theories of differential susceptibilities to adversity based on past exposures, such as stress sensitization, 4 whereby prior exposure to trauma sensitizes the individual to later stress exposures, or stress inoculation, 5 where past adversity makes the individual less vulnerable to future stress exposure.

The current study 2 advances the field of developmental science in 2 ways that allow empirical testing of theoretical frameworks. First, by leveraging 3 cohort studies that used harmonized measures from infancy to adulthood and collected data on exposures prospectively, the authors 2 were able to test the association of development with vulnerability to adversity exposure over a long period of time while mitigating risk of recall bias. Second, by teasing apart adversity to components of trauma (exposures that would meet Diagnostic and Statistical Manual of Mental Disorders [Fourth Edition] criterion A for a posttraumatic stress disorder diagnosis) and recent stressful events (ie, negative life events that would not be considered traumatic and that occurred in the past 3 months), the authors 2 were able to compare contributions of different magnitudes of adversity and to appreciate their combined contribution to mental health.

The consistency of the association of adversity with emotional symptoms across developmental stages can be explained by different mechanisms. First, it is possible that the vulnerability to adversity is stable, perhaps through evolutionary forces that conserve distress in response to adversity because it may promote survival throughout the lifespan. Second, stress vulnerability may well be a dynamic process that changes throughout development, but there may also be opposing dynamic factors that buffer stress exposures in the form of resilience mechanisms, which counter the deleterious effects of adversity and result in a zero-sum effect, where the observed associations of adversity with mental health remain stable. This explanation can align with theoretical models that conceptualize resilience as a dynamic construct that keeps adapting to meet developmental requirements. 6 Third, it may be the case that as individuals age, they experience health impacts of adversity in areas beyond mental health, which were not measured in the current study. 2 One conceptual model that may support this explanation is that of allostatic load, the wear and tear of physiological systems in response to chronic stress, which affects both mental and physical health. 7 Accordingly, it is possible that over the lifespan, the toll of adversity takes the form of increased allostatic load that may lead to more physical health symptoms than mental health symptoms, which remain stable in their association with adversity. Last, it could be that some inherent challenges in this study design (eg, harmonizing measures across ages) or measurement (eg, relying on parent report in early age and transitioning to self-report in older age) may have hampered the researchers’ ability to detect differential associations of adversity with mental health across developmental stages.

To conclude, Copeland et al 2 leveraged 3 studies spanning infancy to young adulthood to demonstrate that associations of adversity with mental health do not depend on the developmental stage. This finding may require rethinking and potential adaptation of existing conceptual models in developmental science and should propel more investigation of other processes that are critical in determining health outcomes in relation to adversity exposure, such as resilience mechanisms 6 and allostatic load. 8 Those processes are likely critical in determining interindividual differences in vulnerability, which merits further investigation. The current study’s approach 2 of integrating multiple developmental cohorts across the lifespan with harmonized measures can be a blueprint for future studies and encourage researchers to empirically test developmental theories in human cohorts, particularly in the era of open science, when there are multiple resources available for longitudinal analyses of human data throughout the lifespan. 9 From a clinical perspective, this study 2 adds to the body of literature on the critical contribution of adversity to mental health as a key determinant of health across development, and further emphasizes the need to include assessment of adversity exposure in clinical settings. 10

Published: August 29, 2024. doi:10.1001/jamanetworkopen.2024.29376

Corresponding Author: Ran Barzilay, MD, PhD, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, 3400 Spruce, 10 Gates, Philadelphia, PA 19104 ( [email protected] ).

Conflict of Interest Disclosures: Dr Barzilay reported receiving grants from the National Institute of Mental Health and American Foundation of Suicide Prevention, holding equity and serving on the scientific advisory board of Taliaz Health, and receiving consulting fees from Zynerba Pharmaceuticals outside the submitted work.

Barzilay R. Developmental Timing of Adversity and Mental Health Across the Lifespan—Time to Rethink Sensitive Periods? JAMA Netw Open. 2024;7(8):e2429376. doi:10.1001/jamanetworkopen.2024.29376

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COVID can cause mental illness—but being vaccinated helps, new study shows

The COVID-19 vaccine may protect against SARS-CoV-2’s adverse effects on mental health, according to an analysis of more than 18.6 million adults by a team of researchers in the U.K.

You’re not alone if you’ve experienced new or worsening mental illness after recovering from COVID. While the coronavirus’s long-term consequences on mental health remain a mystery, in the four years since the pandemic’s onset, researchers worldwide have already documented a link between infection and mental health deterioration .

Now scientists in the U.K. have uncovered a new piece of the puzzle: COVID vaccination may mitigate the virus’s adverse effects on mental health. The team, including researchers from the universities of Bristol , Cambridge , Oxford , and Swansea , as well as University College London , showed higher rates of mental illnesses among unvaccinated people, up to a year after severe COVID infection. Their findings were published Wednesday in JAMA Psychiatry .

“Our findings have important implications for public health and mental health service provision, as serious mental illnesses are associated with more intensive health care needs and longer-term health and other adverse effects,” Venexia Walker, PhD , a senior research fellow in epidemiology at Bristol Medical School and one of the study’s lead authors, said in a news release . “Our results highlight the importance of COVID-19 vaccination in the general population and particularly among those with mental illnesses, who may be at higher risk of both SARS-CoV-2 infection and adverse outcomes following COVID-19 .”

The observational study assessed the medical records of more than 18.6 million adults ages 18 to 110 (50% female; median age 49) who were registered with a general practitioner in England. In this first cohort, which centered on the pandemic’s early days before a vaccine was available, about 5% of patients had been diagnosed with COVID . Two other cohorts represented the vaccination era from June through December 2021:

Female: 52%
Median age: 53
COVID diagnosis: 6%
Female: 42%
Median age: 35
COVID diagnosis: 5%

In each of the three cohorts, researchers compared incidence of the following mental illnesses before and after a confirmed COVID diagnosis:

Eating disorders
General anxiety
Posttraumatic stress disorder
Serious mental illness (including bipolar disorder and schizophrenia)

Compared to before or without COVID, the prevalence of most of these conditions increased one to four weeks following COVID diagnosis. This trend primarily applied to severe infections that had required hospitalization and among unvaccinated people, incidence remained elevated for up to a year.

Mental illness incidence increased slightly in COVID patients who endured milder infection. Depression rates, for example, spiked 16-fold among hospitalized patients but did so by just 1.2 times among nonhospitalized patients. While no vaccine is 100% effective, COVID immunization is intended to prevent severe illness and death. Researchers noted that the vaccinated cohort showed little variation in depression prevalence before/without or after nonhospitalized infection.

The link between COVID and mental illness didn’t change significantly between racial and ethnic groups. It did, however, vary by age and biological sex . For instance, this association was stronger among men and older age groups .

Despite boasting a large sample size, the study has its limitations. The millions of participants hailed from a single nation, and the vast majority were white. Researchers also stressed that they analyzed only confirmed infections recorded in electronic health records, meaning COVID-positive individuals who hadn’t sought medical care weren’t included. In addition, researchers couldn’t rule out that viruses besides SARS-CoV-2 hadn’t contributed to the mental illnesses studied.

“We have already identified associations of COVID-19 with cardiovascular disease , diabetes, and now mental illnesses,” Jonathan Sterne, PhD , study coauthor and professor of medical statistics and epidemiology at Bristol Medical School, said in the news release. “We are continuing to explore the consequences of COVID-19 with ongoing projects looking at associations of COVID-19 with renal, autoimmune, and neurodegenerative conditions .”

When will the new COVID vaccines be available?

Updated 2024–2025 COVID vaccines likely will be available in the early fall. Vaccines manufactured by Pfizer , Moderna , and Novavax will arrive “later this year,” the Centers for Disease Control and Prevention (CDC) announced in June. Last year’s version launched in mid-September.

When the new vaccines are available, the CDC recommends everyone aged 6 months and older get a dose to shield themselves from the latest Omicron subvariants . People with compromised immune systems and those 65 and older may be eligible for additional doses.

“Our top recommendation for protecting yourself and your loved ones from respiratory illness is to get vaccinated,” CDC Director Dr. Mandy Cohen said in a June news release. “Make a plan now for you and your family to get both updated flu and COVID vaccines this fall, ahead of the respiratory virus season.”

If you need immediate mental health support, contact the 988 Suicide & Crisis Lifeline .

For more on COVID-19 and mental health:

Antidepressant not working? AI may do a better job than your doctor in matching you with the best medicine
The summer COVID surge has arrived. Here’s the latest on symptoms and treatment
Got late-summer travel plans? Here’s where COVID cases are spiking in the U.S.
One of the best things you can do for your mental health , according to a psychologist who counsels U.S. Olympians

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Safe outdoor activities during the COVID-19 pandemic

The COVID-19 pandemic doesn't have to halt all of your outdoor fun. Here are several fun outdoor activities you can still enjoy.

Since the start of the coronavirus disease 2019 (COVID-19) pandemic, the activities of many people have been affected.

With COVID-19 vaccines, testing and treatment, events and travel are back to typical levels in many places. But as waves of COVID-19 cases — called outbreaks — happen, it's important to stay flexible with your plans.

Even if it takes extra planning, seeking out fun activities can help you cope with life's challenges. That's especially true if you do activities with people in your community and boost your social network.

When it comes to being social and active during the COVID-19 pandemic, outdoor activities can be a good way to have fun safely.

Why choose outdoor activities?

It's harder to catch the virus that causes COVID-19 when you are in a space with good airflow and where you can spread out.

The COVID-19 virus is mainly spread from person to person. The virus spreads when a person with COVID-19 breathes, coughs, sneezes, sings or talks.

When you're outside, fresh air is always moving, so your risk of breathing in the virus that causes COVID-19 is lower.

Low-risk ways to move more

When COVID-19 is spreading in your area, low-risk activities can keep you active in a safe way. In general, any activity that allows you to keep your distance from others is a lower risk activity.

Wearing a mask can give you added protection against catching the COVID-19 virus.

In warm or cold weather, there are many ways to be active outdoors. Walking, running and hiking are common options either in your neighborhood or at a park.

Cold-weather activities, such as skiing or sledding, can be an option for one person or a group. Finding a fun activity during the cold months can help you enjoy the season and winter activities more.

Low- to moderate-risk outdoor activities

Some outdoor activities have a low to moderate risk of exposure to the virus that causes COVID-19. Basically, the less an activity brings you into contact with groups of people, the lower the risk of exposure to the virus.

Outdoor patio dining at uncrowded restaurants where patio tables are spaced apart is typically safer than indoor dining.

Gathering with a small group of friends and meeting outdoors may be a good option.

At the beach or swimming pool, it's the close contact with others, not water itself, that can make activities at these locations risky. Water itself doesn't spread the virus that causes COVID-19 from person to person.

High-risk outdoor activities

Being in large gatherings or crowds of people where it's difficult to stay a safe distance apart makes some outdoor activities higher risk for exposure to the COVID-19 virus. Festivals and parades are examples.

Think safety and enjoyment

As the COVID-19 pandemic continues, it's important to take care of yourself and those around you.

Stay up to date with COVID-19 vaccines to help prevent serious COVID-19 illness.
Make your activities as safe as possible.
Test for COVID-19 if you have symptoms.
Cancel plans if someone may be sick.

When you are out, clean your hands often. Avoid touching your face. If you live in an area where the virus that causes COVID-19 is spreading, wear a well-fitted mask.

With the right information, you can make thoughtful choices about ways to bring a sense of normalcy and joy to your life during the ups and downs of the COVID-19 pandemic.

There is a problem with information submitted for this request. Review/update the information highlighted below and resubmit the form.

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Create joy and satisfaction. Mental Health America. https://www.mhanational.org/create-joy-and-satisfaction. Accessed June 7, 2024.
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DeSimone DC (expert opinion) Mayo Clinic. June 7, 2024.
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How COVID-19 spreads. Centers for Disease Control and Prevention. https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/how-covid-spreads.html. Accessed June 7, 2024.
Preventing respiratory viruses. Centers for Disease Control and Prevention. https://www.cdc.gov/respiratory-viruses/prevention/index.html. Accessed June 7, 2024.
Hygiene and respiratory viruses Prevention. Centers for Disease Control and Prevention. https://www.cdc.gov/respiratory-viruses/prevention/hygiene.html. Accessed June 7, 2024.

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Mental Health and the Covid-19 Pandemic
Investigating the Prevalence of COVID-19-Related Sleep Disorders Among Individuals Recovering from COVID-19: A Cross-Sectional Analytical Study, Jundishapur Journal of Health Sciences, 15, 4 ...
How COVID-19 shaped mental health: from infection to pandemic effects
On a global scale and based on imputations and modeling from survey data of self-reported mental health problems, the Global Burden of Disease (GBD) study 29 estimated that the COVID-19 pandemic has led to a 28% (95% uncertainty interval (UI): 25-30) increase in major depressive disorders and a 26% (95% UI: 23-28) increase in anxiety disorders.
How COVID-19 shaped mental health: from infection to pandemic effects
On a global scale and based on imputations and modeling from survey data of self-reported mental health problems, the Global Burden of Disease (GBD) study 29 estimated that the COVID-19 pandemic ...
The coronavirus (COVID‐19) pandemic's impact on mental health
COVID‐19 can also result in increased stress, anxiety, and depression among elderly people already dealing with mental health issues. Family members may witness any of the following changes to the behavior of older relatives 11 ; Irritating and shouting behavior. Change in their sleeping and eating habits.
Impact of COVID-19 pandemic on mental health in the general population
The COVID-19 pandemic represents an unprecedented threat to mental health in high, middle, and low-income countries. In addition to flattening the curve of viral transmission, priority needs to be given to the prevention of mental disorders (e.g. major depressive disorder, PTSD, as well as suicide).
Mental Health and COVID-19: Early evidence of the pandemic's impact
The COVID-19 pandemic has had a severe impact on the mental health and wellbeing of people around the world while also raising concerns of increased suicidal behaviour. In addition access to mental health services has been severely impeded. However, no comprehensive summary of the current data on these impacts has until now been made widely ...
COVID-19 pandemic triggers 25% increase in prevalence of anxiety and
Español. In the first year of the COVID-19 pandemic, global prevalence of anxiety and depression increased by a massive 25%, according to a scientific brief released by the World Health Organization (WHO) today. The brief also highlights who has been most affected and summarizes the effect of the pandemic on the availability of mental health ...
Mental health concerns during the COVID-19 pandemic as ...
We collected data on 8 million calls from 19 countries, focusing on the COVID-19 crisis. Call volumes peaked six weeks after the initial outbreak, at 35% above pre-pandemic levels. The increase ...
COVID's mental-health toll: how scientists are tracking a ...
COVID's mental-health toll: how scientists are tracking a surge in depression. Researchers are using huge data sets to link changes in mental health to coronavirus-response measures. By. Alison ...
Lifestyle and mental health disruptions during COVID-19
A mental health crisis has emerged during the COVID-19 pandemic. The US Centers for Disease Control and Prevention (CDC) estimates that as of June 2020 nearly one-third of US adults were suffering from anxiety or depression ().The rates are almost two times higher for young adults, a population that has already seen a significant increase in the prevalence of mental health disorders over the ...
COVID-19 pandemic and mental health consequences: Systematic ...
Background: During the COVID-19 pandemic general medical complications have received the most attention, whereas only few studies address the potential direct effect on mental health of SARS-CoV-2 and the neurotropic potential. Furthermore, the indirect effects of the pandemic on general mental health are of increasing concern, particularly since the SARS-CoV-1 epidemic (2002-2003) was ...
COVID-19 and mental health
The coronavirus disease 2019 (COVID-19) pandemic is having a profound effect on all aspects of society, including mental health and physical health. We explore the psychological, social, and neuroscientific effects of COVID-19 and set out the immediate priorities and longer-term strategies for mental health science research.
Impact of COVID-19 on mental health: A quantitative analysis of anxiety
COVID-19 has a significant impact on mental health. It is creating a destructive mentality and increasing depression in regular life. As a result, suicidal attempts are increasing. Life of people are becoming more irritable, and people have social anxiety. For COVID-19 social distance has increased. So, physical contact is decreasing.
Long-term effects of COVID-19 on mental health: A systematic review
Conclusion: The overall effect of the pandemic has been linked with worsening psychiatric symptoms. However, the long-term effect from direct COVID-19 infection has been associated with no or mild symptoms. Studies exhibited the long-term prevalence of anxiety, depression, PTSD, and sleep disturbances to be comparable to general population levels.
COVID-19 and mental health in Australia
Publications (reports, non-reviewed pre-prints of papers and peer-reviewed articles) were eligible to be included if they were focused on mental health during the COVID-19 pandemic, reported original research findings/results (i.e. media releases, editorials, opinion pieces, commentaries, protocol papers or general text summaries within reports ...
COVID-19 and your mental health
Worldwide surveys done in 2020 and 2021 found higher than typical levels of stress, insomnia, anxiety and depression. By 2022, levels had lowered but were still higher than before 2020. Though feelings of distress about COVID-19 may come and go, they are still an issue for many people. You aren't alone if you feel distress due to COVID-19.
Impact of COVID-19 pandemic on mental health: An international study
Background The COVID-19 pandemic triggered vast governmental lockdowns. The impact of these lockdowns on mental health is inadequately understood. On the one hand such drastic changes in daily routines could be detrimental to mental health. On the other hand, it might not be experienced negatively, especially because the entire population was affected.
The impact of mental health and the COVID-19 pandemic on ...
Mental health is an essential component of individual and collective health and well-being, representing people's ability to exercise their human rights, not just the absence of disease [].However, under the impact of COVID-19, the global mental health condition has continued to deteriorate [].One in seven children and adolescents aged 10-19 years experience mental health issues worldwide ...
Mental Health and COVID-19
In this section. The COVID-19 pandemic has had a huge impact on public health around the globe in terms of both physical and mental health, and the mental health implications of the pandemic may continue long after the physical health consequences have resolved. This research area aims to contribute to our understanding of the COVID-19 ...
Mental Health Research During the COVID-19 Pandemic: Focuses and Trends
The COVID-19 pandemic has profoundly influenced the world. In wave after wave, many countries suffered from the pandemic, which caused social instability, hindered global growth, and harmed mental health. Although research has been published on various mental health issues during the pandemic, some profound effects on mental health are ...
Longitudinal Changes in Youth Mental Health From Before to During the
Key Points. Question How did the COVID-19 pandemic impact youth mental health?. Findings In this cohort study of 1229 US youths, the pandemic was associated with minor changes in youth mental health overall. However, youth entering the pandemic with prepandemic mental health problems experienced notable improvements across all outcomes, and lower-income and Black youth had small improvements ...
COVID-19 and Mental Health
COVID-19 is a disease caused by a virus named SARS-CoV-2. COVID-19 most often affects the lungs and respiratory system, but it can also affect other parts of the body. Some people develop post-COVID conditions, also called Long COVID . These symptoms can include neurological symptoms such as difficulty thinking or concentrating, sleep problems ...
The Effect of COVID-19 on Mental Health and Wellbeing in a
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COVID-19 pandemic triggers 25% increase in prevalence of anxiety and depression worldwide

COVID’s mental-health toll: how scientists are tracking a surge in depression

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Long-term effects of COVID-19 on mental health: A systematic review

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COVID-19 and mental health in Australia – a scoping review

Conclusions

Study design

Eligibility criteria

Literature search and data extraction

General description of studies included

Study time-frame and geographical coverage

Study populations

Pre-COVID comparisons

Research on the general population in Australia

During-COVID/Pre-COVID study comparisons

Mental health outcome measures

Overall study findings

Research on specific subpopulation groups

Study samples and populations of interest

Pre-COVID/ during-COVID study comparisons

Mental health measures

Shortcomings in the research response

Research still to come….

Limitations

Availability of data and materials

Acknowledgements

Author information

Contributions

Corresponding author

Ethics declarations

Additional information

Supplementary Information

Additional file 2.

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BMC Public Health

Impact of COVID-19 pandemic on mental health: An international study

Conclusions

Introduction

Participants

Socio-demographic status.

Lockdown variables.

Social factors.

Psychological factors.

Depression.

Positive affect/ negative affect.

Statistical analysis

Descriptive

Outcome variables

Predictor variables

COVID-19 lockdown variables.

Social and psychological predictors.

Multivariate analyses

Supporting information

S2 Table. Geodemographic predictors for Perceived Stress Scale.

S3 Table. Geodemographic predictors for MSBS–depression.

S4 Table. Geodemographic predictors for PANAS positive.

S5 Table. Geodemographic predictors for PANAS negative.

S6 Table. Geodemographic predictors for MHCSF—mental health continuum.

S1 Appendix. Participation flowchart.

Acknowledgments

The impact of mental health and the COVID-19 pandemic on employability and learning outcomes: evidence from Taiwanese University students

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1 Introduction

2.1 Samples