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Association between level of compliance with COVID-19 public health measures and depressive symptoms: A cross-sectional survey of young adults in Canada and France

  • Pierre-julien Coulaud ,

    Roles Conceptualization, Investigation, Supervision, Writing – original draft

    pierre-julien.coulaud@bccsu.ubc.ca

    Affiliations British Columbia Centre on Substance Use, Vancouver, British Columbia, Canada, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada

  • Julie Jesson,

    Roles Formal analysis, Writing – original draft

    Affiliation Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada

  • Naseeb Bolduc,

    Roles Investigation, Project administration

    Affiliations British Columbia Centre on Substance Use, Vancouver, British Columbia, Canada, School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada

  • Olivier Ferlatte,

    Roles Writing – review & editing

    Affiliations British Columbia Centre on Substance Use, Vancouver, British Columbia, Canada, Département de Médecine Sociale et Préventive, École de Santé Publique de l’Université de Montréal, Montréal, Québec, Canada, Centre de Recherche en Santé Publique, Université de Montréal et CIUSSS du Centre-Sud-de-l’Île-de-Montréal, Montréal, Canada

  • Karine Bertrand,

    Roles Writing – review & editing

    Affiliation Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, Longueuil, Québec, Canada

  • Travis Salway,

    Roles Writing – review & editing

    Affiliations Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada, British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada, Centre for Gender and Sexual Health Equity, Vancouver, British Columbia, Canada

  • Marie Jauffret-Roustide ,

    Contributed equally to this work with: Marie Jauffret-Roustide, Rod Knight

    Roles Conceptualization, Supervision, Writing – review & editing

    Affiliations British Columbia Centre on Substance Use, Vancouver, British Columbia, Canada, Centre d’Étude des Mouvements Sociaux (EHESS/CNRS UMR8044/INSERM U1276), Paris, France, Baldy Center on Law and Social Policy, Buffalo University, Buffalo, NY, United States of America

  • Rod Knight

    Contributed equally to this work with: Marie Jauffret-Roustide, Rod Knight

    Roles Conceptualization, Supervision, Writing – review & editing

    Affiliations British Columbia Centre on Substance Use, Vancouver, British Columbia, Canada, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada, Département de Médecine Sociale et Préventive, École de Santé Publique de l’Université de Montréal, Montréal, Québec, Canada, Centre de Recherche en Santé Publique, Université de Montréal et CIUSSS du Centre-Sud-de-l’Île-de-Montréal, Montréal, Canada

Abstract

Background

While compliance with preventive measures remains central to limit the spread of COVID-19, these measures critically affected mental health of young adults. We therefore investigated the association between the level of compliance with COVID-19 preventive measures and depressive symptoms among young adults in Canada and France.

Methods

From October to December 2020, we conducted a cross-sectional online survey of young adults ages 18–29 years in Canada (n = 3246) and France (n = 2680) to collect demographic data, experiences with COVID-19 preventive measures, and mental health. Depressive symptoms were assessed by the Patient Health Questionnaire-9 (PHQ-9). Compliance profiles were built using cluster analysis. Weighted multivariable logistic regression was used to estimate associations between compliance level and major depressive symptoms (PHQ-9 score≥15) in each country.

Results

One third of respondents reported major depressive symptoms (Canada: 36.4%, France: 23.4%). Four compliance profiles were identified: high (42.5%), medium-high (21.7%), medium-low (18.1%), and low (17.7%), with high levels more frequently observed in Canada compared to France. In both countries, participants in low compliance profile (Canada: Adjusted Odds Ratio (AOR) [95% Confidence Interval] 0.75 [0.58, 0.98], France: AOR 0.60 [0.46, 0.75]), in the medium-low (Canada: AOR 0.58 [0.48, 0.72], France: AOR 0.81 [0.66, 1.01]), and medium-high compliance profiles (Canada: AOR 0.78 [0.65, 0.93], France: AOR 0.77 [0.63, 0.93]) were less likely to report major depressive symptoms compared to the high compliance profile. Ethno-racial minorities, sexual and gender minority, and unemployed young adults had higher odds of reporting such symptoms.

Conclusions

Major depressive symptoms were associated with high compliance with COVID-19 preventive measures among young adults. The implementation of socially-isolating measures should be coupled with mental health interventions to address mental health needs of young adults, with enhanced supports for sub-groups who are structurally disadvantaged (e.g., racialized, unemployed, sexual and gender minority).

Introduction

Since the beginning of the COVID-19 pandemic, various jurisdictions around the world implemented public health preventive measures to prevent the spread of the virus [1]. Depending on the jurisdiction and the level of COVID-19 severity, preventive measures have featured educational guidance (e.g., hygiene recommendations, like frequent handwashing), as well as enforceable public health orders such as bans on social gatherings, closures of schools and non-essential businesses, stay-at-home orders and the use of face masks [24]. Throughout each successive wave of COVID-19, modelling of public compliance with preventive measures suggests the potential for a decrease in the onward spread of the virus and a corresponding flattening of the COVID-19 curve—evidence used by public health officials to justify prevention education and restrictive orders [5, 6].

Preliminary evidence collected in the first months of the COVID-19 pandemic (March-August 2020) highlights that young adults (<30 years) had lower levels of engagement in some preventive behaviors, including physical distancing and hygiene measures, than older adults [711]. Previous research has also identified that COVID-19 preventive measures that require varying degrees of social isolation may be particularly harmful for the mental health and well-being of young adult populations [1215]. Findings from longitudinal studies examining the mental health impacts of COVID-19 on the general population further indicate that young adults (e.g., 18–29 years) were more likely to report higher levels of depressive and anxiety symptoms and suicide ideation compared to older age groups [1618]. As such, there is concern that the psychosocial needs of young adults were not sufficiently addressed during various phases of the pandemic [19].

To date, research examining the association between depression and compliance with COVID-19 preventive measures has been mainly conducted among adults, and these results are equivocal. For example, several studies showed that adherence to distancing behaviors and staying at home was associated with increased risk for depression [2023] while other studies reported no significant association [2426] or that being more compliant was a protective factor for depressive symptoms [7, 27, 28]. In addition, most of these studies only assessed a limited number of preventive measures that were investigated separately for effects on depressive symptoms, leaving questions as to the extent to which complying with multiple concurrent COVID-19 preventive measures may have an additive effect on depressive symptoms.

The objective of this study was therefore to investigate the association between the level of compliance with multiple COVID-19 preventive measures and depressive symptoms among young adults living in Canada and France. We hypothesized that we would observe a significant association between the levels of compliance with COVID-19 preventive measures and depressive symptoms, such that those who report lower levels of compliance will experience lower levels of depressive symptoms. Our hypothesis is based on the assumptions that young adults who were highly compliant to socially restrictive COVID-19 measures would report fewer opportunities to connect with family/friends. As such, they would be less likely to receive and benefit from social supports, which would lead to an increased risk of experiencing depressive symptoms.

Materials and methods

Study design and settings

Data were collected through the France-Canada Observatory on COVID-19, Youth health and Social well-being (FOCUS) study, a cross-sectional, online anonymous survey exploring the impact of the pandemic on social and health outcomes among young adults ages 18–29 years in Canada and France. The survey was conducted from the 8th of October to the 23rd of December 2020.

Canada and France are two high-income countries that have been particularly affected by the COVID-19 pandemic, respectively with 3.8 and 28.8 million total number of cases since March 2020 [29]. In both countries, young adults have experienced high rates of COVID-19 infection (compared to older adults groups), comprised 19% of total cases in Canada [30] and 17% in France [31].

In Canada, the first peak of COVID-19 cases started in mid-March 2020 with a major outbreak in the province of Quebec [32]. Between March and June 2020, the federal and provincial governments implemented a series of public health measures (e.g., stay-at-home orders, closure of schools and pivot to online course delivery) to limit the spread of the pandemic [33]. The second peak was reached in early January 2021. In October-November 2020, each province and territory introduced measures from avoiding non-essential travel and limiting social gatherings to the closure of non-essential businesses. At the end of December 2020, province-wide lockdowns were announced in Quebec and Ontario [34, 35].

In France, the COVID-19 pandemic spiked dramatically in March-April 2020, mainly in the northeast and the region of Paris. Between March and May 2020, a national lockdown was implemented to control the spread of the pandemic before a gradual reopening of activities and businesses over the summer [36]. The peak of the second wave was reached in early November 2020. The Government of France implemented an increasing series of mitigation measures in late September (e.g., limiting social gatherings, closing bar/restaurants) and throughout October, including a curfew in metropolitan areas (October 17–30), a nationwide lockdown (October 30-December 15), and a national curfew that began 15 December 2020 [36, 37]. During this period, schools and universities remained mainly open under certain conditions (e.g., capacity limits, mask mandate) to limit social inequalities.

Participants and procedures

Survey participants were recruited through non-probability sampling using online posts and advertisements on social media platforms (e.g., Facebook and Instagram) and university websites, and word of mouth. Additional efforts were made to reach underrepresented populations and geographic areas by using targeted ads from demographic criteria available on social media platforms (e.g., age, gender). Participants were eligible if they were: (1) between the age of majority (18 or 19 in Canada depending on the province or territory of residence; 18 in France) and 29 years; resided in Canada or France; and (2) able to complete the survey in English (Canada) or French (either country). The questionnaire comprised four major sections: sociodemographic, social life and experiences during the pandemic (including questions about COVID-19 preventive measures), access to social and health services, and health outcomes (e.g., mental health). In order to ascertain the acceptability of the questionnaire, we invited 10 youth (n = 5 in each country) to pre-test the questionnaires and provide insights about the format, content and sequencing of the questionnaire, including whether questions were clear and the responses available for each question were appropriate. Survey data were collected using Qualtrics. On the first page of the online survey, all participants were provided with the study’s objective and details about how to participate. Prior to accessing the online questionnaire, all participants were informed that the completion of the questionnaire implied informed consent. Participants were also informed that they could stop the survey questionnaire at any time. All participants were also provided with an option to enter a draw to win one of three cash prizes (CAD$100 in Canada, 100€ in France). Ethical approval was granted by the University of British Columbia Behavioural Research Ethics Board (H20-02053).

To ensure survey security and protect our online survey from fraudulent submissions (including duplicate submissions and “bot” attacks), we used several preventive methods including setting up security survey options in our survey tool Qualtrics to access our online questionnaire (e.g., procedures to detect fake IP address), screening time and duration of survey completion, and checking for inconsistencies across each new submission [38]. Furthermore, our survey incentives were relatively small for participants (i.e., a lottery draw to win one of three cash prizes), and our survey promotion activities did not include information about incentives, procedures that are known to reduce duplicate responses and fraudulent submissions [39].

Study population

The population for the present study included participants of the FOCUS study who had complete data on socio-demographics, COVID-19 preventive measures, and mental health questions. Therefore, participants who had missing information on socio-demographics, the questions about the COVID-19 preventive measures or did not complete the depression scale were excluded.

Outcome

Depressive symptoms within the past two weeks were measured using the Patient Health Questionnaire-9 (PHQ-9) [40], a validated scale that has been translated in multiple languages, including French [41]. Because a previous study demonstrated that the English and French PHQ-9 versions did not present substantial differences in scoring metrics [42], we did not perform psychometric analyses to examine the effect of the different languages on depression scores. Each of the 9 items are scores from 0 (not at all) to 3 (nearly every day) with total score ranges from 0 to 27. Scores within 0–4 are considered as having minimal, 5–9 mild depressive symptoms, 10–14 moderate depressive symptoms, 15–19 moderately severe depressive symptoms and 20–27 severe depressive symptoms [43]. To limit overestimation of the prevalence of depression in our study, the higher cut-off score of 15 was used to identify participants with major depressive symptoms [44].

Exposure

Our primary exposure was the level of compliance with COVID-19 preventive measures. Using a multiple-choice question with ten response options, we asked participants whether they took any actions to decrease their risk of getting or transmitting COVID-19 in the past 6 months. The following five socially-isolating preventive measures were used to build a COVID-19 compliance profiles variable (see ‘Statistical analysis’ section): staying home from work or school, only taking essential trips, avoiding social gatherings of over 10 people, avoiding meeting friends, and maintaining a social bubble at home. Five other preventive measures were collected including health behaviors (practicing physical distancing, wearing a face covering), and hygiene practices (washing hands, cleaning frequently touched surfaces and objects, avoiding touching face with unwashed hands); however, we a priori determined that these measures were not conceptually linked to mental health in the same manner as the socially-isolating measures and therefore were not included in the construction of compliance profiles.

Covariates

The covariates included the following socio-demographic characteristics: age, gender identity, sexual orientation, province/region of residence, area of residence (large urban centre 100,000+ people versus medium or small city), highest degree of education, employment status, and living arrangements. In Canada, ethno-racial identity was collected using the Canadian Institute for Health Information standards [45]. In France, where asking about ethno-racial identity is not permitted, participants were asked to provide the country of birth of their parents, and maternal and paternal grand-parents. French participants who reported that at least one of their parents or two of their grandparents from the same side were born outside France or Europe were considered as descendants of immigrants [46].

To best capture the climate of uncertainty regarding the evolution of the COVID-19 pandemic and the economic downturn that young adults experienced at the time of the survey (e.g., COVID-19 vaccines were not yet available in Fall 2020), we included four other covariates in our analysis. Level of concern for COVID-19’s impact was assessed by asking the following questions: “How concerned are you about the impact of COVID-19 on: (1) the economy and businesses; and (2) the uncertainty of the future”. Response options were classified in low (not or a bit concerned) and high level of concern (quite or very concerned). We also asked participants if they have: (3) been tested for COVID-19 in the past 6 months (yes versus no), and (4) lost any individual income (including salary, employment insurance, government assistance, etc.) due to the COVID-19 pandemic. Given the limited number of participants who reported a positive test for COVID-19 (e.g., n = 22, 0.7% in Canada, n = 135, 5% in France), we did not include the results of the tests in our analysis.

All of these covariates were considered as potential confounders in our analysis because: a) they are empirically demonstrated explanatory factors (social determinants) associated with depression [4749], and b) are empirically or conceptually related to our exposure variable of compliance with COVID-19 preventive measures [5052].

Statistical analyses

Using data from both countries, we conducted a cluster analysis to identify COVID-19 compliance profiles. The K-means method of cluster analysis was applied to classify participants into mutually exclusive groups, using Euclidean distances with cluster centers based on least squares estimation (SAS PROC FASTCLUS procedure) [53]. The number of clusters was determined by using the pseudo-F statistic, approximate expected overall R square, and cubic clustering criterion, as well as by considering the most meaningful clusters regarding the compliance to COVID-19 preventive measures. A descriptive analysis was then performed to present the characteristics of each profile in both countries (see S1 Table).

Unadjusted and adjusted associations between major depressive symptoms (PHQ-9 score ≥15) and level of compliance were estimated using multivariable logistic regression, adjusted for all covariates listed above. In our models, participants with high compliance were considered as the reference group because both Canadian and French health authorities recommended at the time of the survey to comply with the COVID-19 preventive measures included in our profile construction (e.g., avoiding meeting friends and social gatherings). In our multivariate logistic regression models (see Table 2), we use listwise deletion to remove participants with missing data across covariates and those who selected the “Prefer not to say” option responses, as they represented a limited number of participants (5% of the total sample). We applied survey weights by age, gender, and province/region of residence using official census data in each country to improve the representativeness of the sample (see here [54] for further details). We also applied a statistical test (i.e., the Fairchild test) to examine how the magnitude of the association between depression and COVID-19 compliance differed between Canada and France (see S2 Table) [55]. All analyses were performed using R version 4.0.3 and SAS University software (SAS Institute Inc., Cary, NC, USA).

Results

Of the 8424 participants of the FOCUS survey, 89.6% completed the initial sociodemographic information. Of these, we excluded those who did not respond to the COVID-19 preventive measures (n = 383), and mental health questions (n = 1286), resulting in a final study sample of 5926 (Canada: n = 3246, 54.8% and France: n = 2680, 45.2%). Participants excluded (n = 1619, 27.3%) were more likely to come from France (61.1% vs. 38.9%), be younger (18–19 years; 26.9% vs. 17.9%), identify as men (38.4% vs. 29.5%) and as straight/heterosexual (65.5% vs. 59.5%), live in medium or small cities (53.5% vs. 46.5%), report a lower education level (high school or college; 50.7% vs. 38.2%) compared to the participants included in this analysis (see S3 Table). Participant characteristics in both countries are described in Table 1. Significant differences were observed between the two study samples in the main sociodemographic characteristics. Compared to the French sample, participants in Canada were more likely to identify as a sexual minority (e.g., bisexual: 19% vs. 12.9%), live in large urban centres (60.5% vs. 51%), and report a lower education level (e.g., university graduate degree: 10% vs. 29.1%). In Canada, young adults were more likely to be employed (40.8% vs. 35% in France) or student-employed (25.7% vs. 17% in France) while participants in France were more likely to be students (35.3% vs. 21.7% in Canada) and report living alone (31.9% vs. 14% in Canada). Overall, one third of the total sample (30.5%) reported major depressive symptoms with a higher prevalence in Canada (36.4%) compared to France (23.4%).

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Table 1. Characteristics of the study population, total and by country.

https://doi.org/10.1371/journal.pone.0289547.t001

Four COVID-19 compliance profiles were identified (Fig 1). In the profile with high compliance (n = 2521, 42.5%), more than 90% reported either maintaining a social bubble, taking only essential trips, and avoiding social gatherings and meeting friends; 72.9% reported staying at home. In the medium-high compliance profile (n = 1288, 21.7%), the vast majority reported staying at home (95.0%), taking only essential trips (88.2%), and avoiding social gatherings (76.4%). Only one third reported maintaining a social bubble (28.5%) and avoiding meeting friends (29.7%). Participants with medium-low compliance (n = 1071, 18.1%) reported maintaining a social bubble (68.4%) and staying at home (70.5%); fewer reported avoiding social gatherings (28.3%), taking only essential trips (17.3%), and avoiding meeting friends (5.2%). Among participants with low compliance (n = 1047, 17.7%), none reported staying at home or maintaining a social bubble and only a limited number reported avoiding meeting friends (6.2%), taking only essential trips (13.0%), or avoiding social gatherings (16.4%). As described in Fig 1, the COVID-19 compliance profiles were distributed differently by country. The majority of participants were highly compliant in Canada (56.2%) while a similar proportion of participants was found in each profile in France (high compliance: 26%, medium-high: 25.7%, medium-low: 21.4%, and low: 26.9%). Higher rates of compliance with COVID-19 health behaviors and hygiene practices were found in high compliance profiles compared to other profiles (see Fig 1C).

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Fig 1.

Description of the four profiles of compliance overall and by country (A), according to the COVID-19 preventive measures (B), and the health behaviours and hygiene practices (C).

https://doi.org/10.1371/journal.pone.0289547.g001

Table 2 presents the prevalence of major depressive symptoms by participants’ characteristics, and the level of compliance with COVID-19 preventive measures. In both countries, major depressive symptoms (Canada: 39.8%, France: 27.9%) were more prevalent among highly compliant participants than those who reported a low level of compliance (Canada: 32.7%, France: 17.7%).

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Table 2. Prevalence of depression and associated factors, multivariable logistic regression, weighted and stratified by country.

https://doi.org/10.1371/journal.pone.0289547.t002

In multivariable analyses (Table 2), compared to the high compliance profile, participants in the low (Canada: Adjusted Odds Ratio (AOR) [95% Confidence Interval] 0.75 [0.58, 0.98], France: AOR 0.60 [0.46, 0.75]), in the medium-low (only in Canada: AOR 0.58 [0.48, 0.72]), and medium-high compliance profiles (Canada: AOR 0.78 [0.65, 0.93], France: AOR 0.77 [0.63, 0.93]) had lower odds of reporting major depressive symptoms. As shown in S2 Table, we found that the association between depression and COVID-19 compliance was significantly smaller in magnitude in Canada, as compared to France.

In both countries, young adults who identified as non-binary or with a gender identity other than man or woman (Canada: AOR 1.65 [1.26, 2.16], France: AOR 2.35 [1.67, 3.33]), and those who identified as bisexual (Canada: AOR 1.52 [1.27, 1.81], France: AOR 1.23 [1.01, 1.50]) or as a sexual minority (Canada: AOR 1.43 [1.19, 1.72], France: AOR 1.38 [1.13, 1.69]) had higher odds of reporting major depressive symptoms. Young adults who self-identified as Indigenous in Canada (AOR 1.45 [1.03, 2.04]), and descendants of immigrants in France (AOR 1.52 [1.22, 1.91]) had higher odds of reporting major depressive symptoms. Furthermore, being unemployed (Canada: AOR 1.58 [1.25, 1.99], France: AOR 2.42 [1.83, 3.20]) was associated with higher odds of reporting major depressive symptoms than those who were employed. Similar associations were found with having a high concern about the uncertainty of the future (Canada: AOR 4.06 [3.34, 4.94], France: AOR 2.75 [2.17, 3.49] or reporting income loss due to COVID-19 (Canada: AOR 1.16 [1.01, 1.33], France: AOR 1.35 [1.13, 1.61]).

Discussion

One third of young adults who participated in our study reported major depressive symptoms. In both countries, participants with lower levels of compliance with COVID-19 preventive measures were less likely to experience major depressive symptoms. Similar high prevalence trends of moderate-to-severe depressive symptoms (PHQ-9 score≥10) were observed elsewhere among young adults in Canada (67%) [56] and among students in France (43%) [57]. In our study, we found a higher prevalence of major depressive symptoms in Canada compared to France (36.4% vs. 23.4%). This difference may be partially explained by socio-cultural differences with regards to expressing mental health concerns. For example, data collected before the pandemic indicated that Canadian adults were more likely to self-report experiences of emotional distress than French adults (27% vs. 12%) [58]. While significant efforts in mental health promotion and prevention interventions have been made in Canada in the last two decades [59], prior surveys in France documented persistent negative attitudes toward and perceptions of mental health issues (e.g., feelings of fear and shame, poor mental health literacy) before and during the pandemic [60, 61]. As such, there is a possibility that the terminology that we used in our questionnaire, including the term “mental health”, is viewed as a far more stigmatized condition in France versus Canada.

Our study also identifies an association between the level of COVID-19 preventive measure compliance and depressive symptoms. During the first year of the pandemic (March-December 2020), young adults who were highly compliant with socially-isolating preventive measures had less opportunities to engage with peers and to reduce time in isolation. These experiences may have been particularly challenging for young people ages 18–29, a period of the life course in which key social and professional developments are occurring. For example, several studies in the US identified multiple COVID-19-related stressors that may have contributed to the increased levels of depressive thoughts among students, such as decreased social interactions, disruptions to sleeping patterns, decline in physical activity, or spending more time on screens [6265]. In parallel, several studies documented the negative impacts of the COVID-19 preventive measures on mental health services (e.g., disruptions, increased waiting times) which limited opportunities for young adults to find support to address depressive symptoms [66].

Furthermore, this association between compliance to COVID-19 preventive measures and depressive symptoms may partly be explained due to the differences in prevalence of depression between Canada and France, given that a higher proportion of participants with low levels of compliance were found in the French sample. This may be related to a higher prevalence of attitudes of distrust in the government actions and communication toward preventive measures in France compared to Canada, two contextual factors which are known to be critical determinants when designing and implementing campaign of prevention that requires a large-scale behavioral change [67]. In France, the communication about the COVID-19 pandemic and related public health measures has been mainly led by members of the Government of France with an independent committee of scientific experts, while in Canada, federal and provincial public health agencies integrated scientific advisors and experts as key representatives to promote the implementation of public health measures within each provincial and territorial jurisdiction [36, 68]. In a global survey assessing public attitudes towards governmental actions against the COVID-19 pandemic [69], the authors found lower levels of approval regarding the government communication about the pandemic (66% versus 81%) and the trust in governmental decisions (63% versus 77%) in France compared to Canada. Other contextual factors may explain the cross-country difference in COVID-19 compliance observed between Canada and France, including factors related to the implementation of socially restrictive COVID-19 measures (e.g., stringency, duration, enforcement) and the timing of the infection waves. For example, an analysis of a global database showed that the level of the strictness of COVID-19 governmental policies (i.e., assessed by a composite measure based on nine policy responses including school closures, workplace closures, and travel bans) was lower in France compared to Canada during the period of mid-June to mi-October 2020 [70, 71]. Further research is needed to investigate which and how contextual factors may play a role here.

Our findings also highlight that specific sub-groups of young adults reported higher rates of depressive symptoms. In both countries, sexual and gender minority youth were more likely to report major depressive symptoms compared to their heterosexual counterparts. Previous studies showed that sexual and gender minority youth experienced financial difficulties, limited access to gender-affirming resources, and increased experiences of discrimination, which therefore may increase the risk for depression [7275]. Our analysis suggests that ethno-racial minorities had higher odds of experiencing major depressive symptoms. Similar high depression rates were found in diverse ethnic minority groups of students and adolescents [76, 77]. Previous research in the US reported that ethno-racial minorities have experienced several forms of discrimination during the pandemic [78, 79]. Such findings reinforce the need to strengthen access to mental health services for racialized youth. Depression was also more prevalent among students (only in France) and unemployed youth, among those who reported concerns about the uncertainty of the future, and among those who lost income due to COVID-19 (in both countries). As described in previous surveys [80, 81], the pandemic and related public health measures have created unprecedented conditions of stress and uncertainty regarding academic success, job opportunities, and future careers, that may explain these findings. Participants who had been tested for COVID-19 had higher risk for depression, a result in line with previous studies showing association between depression and COVID-19 contact, symptoms or diagnosis [50, 82].

Strengths and limitations

Our study was conducted among a large and diverse sample of young adults, which allowed us to compare some population characteristics (e.g., men vs non-binary, unemployed vs employed) that have been rarely explored in previous COVID-19 studies among young adults. Our findings enabled us to further discuss the contextual and social-cultural factors that may have influenced the prevalence of depressive symptoms and the level of compliance in two high-income countries significantly impacted by the pandemic.

There are also several limitations. First, we used a non-probability sampling design and most participants were recruited via advertisements on social media. To reduce this bias, we then conducted analyses in each country on a sample that was weighted by age, gender, and province/region of residence. While this weighting procedure enables us to present greater extrapolation of our findings to the Canadian and French young adults’ population, our weighted samples are still not fully representative of the young adult population in Canada and France, which limits our ability to generalize these findings to all young adults living in both countries. Furthermore, our recruitment process might have led to the self-selection of respondents more concerned with COVID-19 than the general population. Second, our cross-sectional design does not allow us to clarify underlying causal mechanisms onto the association between compliance and depression. Third, we did not assess the participants’ history of mental health diagnostics.

Public health implications

These findings provide critical insights into the association of socially-isolating public health measures and depressive symptoms among young adults. The implementation of such measures should be coupled with mental health support interventions to address the timely mental health needs of young adults, with recognition that those who are highly compliant with these measures may be more likely to experience depression. These kinds of interventions should be designed in a way to support the mental health needs of young adults who are structurally disadvantaged (e.g., unemployed, sexual and gender minority, ethno-racial minorities), as these are the mostly likely to be negatively impacted by public health restrictions.

Conclusions

Our findings showed that young adults were engaged in COVID-19 preventive behaviors and also experienced high levels of depressive symptoms in Canada and France. Those who were more likely to be compliant with COVID-19 preventive measures reported higher prevalence of depressive symptoms. As such, this study provides new evidence in favour of the development and promotion of strategies that enhance access of young adults to equitable and non-judgemental mental health services. This is especially important for young adults who experienced various forms of social exclusion (e.g., poverty, racism, homophobia) during the COVID-19 pandemic.

Supporting information

S1 Table. Characteristics of the study population according to profiles of compliance with COVID-19 preventive measures.

https://doi.org/10.1371/journal.pone.0289547.s001

(DOCX)

S2 Table. Cross-country difference in the magnitude of the association between depression and COVID-19 compliance profiles: Results of the Fairchild test.

https://doi.org/10.1371/journal.pone.0289547.s002

(DOCX)

S3 Table. Comparative analysis of the sociodemographic characteristics between the study FOCUS participants included and participants excluded.

https://doi.org/10.1371/journal.pone.0289547.s003

(DOCX)

Acknowledgments

We are thankful to the young adults who took part in the FOCUS survey, as well as the current and past researchers and staff involved with these studies.

References

  1. 1. World Health Organization. Coronavirus disease (COVID-19) advice for the public [Internet]. 2020 [cited 2021 Aug 29]. Available from: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/advice-for-public
  2. 2. Brauner JM, Mindermann S, Sharma M, Johnston D, Salvatier J, Gavenčiak T, et al. Inferring the effectiveness of government interventions against COVID-19. Science (80-). 2021 Feb 19;371(6531). pmid:33323424
  3. 3. Hartley DM, Perencevich EN. Public Health Interventions for COVID-19: Emerging Evidence and Implications for an Evolving Public Health Crisis. Vol. 323, JAMA—Journal of the American Medical Association. American Medical Association; 2020. p. 1908–9.
  4. 4. Krishnamachari B, Morris A, Zastrow D, Dsida A, Harper B, Santella AJ. The role of mask mandates, stay at home orders and school closure in curbing the COVID-19 pandemic prior to vaccination. Am J Infect Control. 2021 Aug 1;49(8):1036–42. pmid:33577824
  5. 5. Flaxman S, Mishra S, Gandy A, Unwin HJT, Mellan TA, Coupland H, et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe. Nature. 2020 Aug 13;584(7820):257–61. pmid:32512579
  6. 6. Giordano G, Colaneri M, Di Filippo A, Blanchini F, Bolzern P, De Nicolao G, et al. Modeling vaccination rollouts, SARS-CoV-2 variants and the requirement for non-pharmaceutical interventions in Italy. Nat Med. 2021 Jun 1;27(6):993–8. pmid:33864052
  7. 7. Solomou I, Constantinidou F. Prevalence and Predictors of Anxiety and Depression Symptoms during the COVID-19 Pandemic and Compliance with Precautionary Measures: Age and Sex Matter. Int J Environ Res Public Health [Internet]. 2020 Jul 8 [cited 2021 Jul 27];17(14):4924. Available from: https://www.mdpi.com/1660-4601/17/14/4924 pmid:32650522
  8. 8. Faria de Moura Villela E, López RVM, Sato APS, de Oliveira FM, Waldman EA, Van den Bergh R, et al. COVID-19 outbreak in Brazil: adherence to national preventive measures and impact on people’s lives, an online survey. BMC Public Health [Internet]. 2021 Dec 1 [cited 2021 Aug 29];21(1):152. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-021-10222-z pmid:33461508
  9. 9. Wright L, Fancourt D. Do predictors of adherence to pandemic guidelines change over time? A panel study of 22,000 UK adults during the COVID-19 pandemic. Prev Med (Baltim). 2021 Dec 1;153:106713.
  10. 10. Smail E, Schneider KE, DeLong SM, Willis K, Arrington-Sanders R, Yang C, et al. Health Beliefs and Preventive Behaviors Among Adults During the Early COVID-19 Pandemic in the United States: a Latent Class Analysis. Prev Sci. 2021; pmid:34275054
  11. 11. Nivette A, Ribeaud D, Murray A, Steinhoff A, Bechtiger L, Hepp U, et al. Non-compliance with COVID-19-related public health measures among young adults in Switzerland: Insights from a longitudinal cohort study. Soc Sci Med. 2021 Jan 1;268:113370. pmid:32980677
  12. 12. Wathelet M, Duhem S, Vaiva G, Baubet T, Habran E, Veerapa E, et al. Factors Associated With Mental Health Disorders Among University Students in France Confined During the COVID-19 Pandemic. JAMA Netw open. 2020 Oct 1;3(10):e2025591. pmid:33095252
  13. 13. Elmer T, Mepham K, Stadtfeld C. Students under lockdown: Comparisons of students’ social networks and mental health before and during the COVID-19 crisis in Switzerland. PLoS One. 2020 Jul 1;15(7 July).
  14. 14. Liu CH, Zhang E, Wong GTF, Hyun S, Hahm H “Chris”. Factors associated with depression, anxiety, and PTSD symptomatology during the COVID-19 pandemic: Clinical implications for U.S. young adult mental health. Psychiatry Res. 2020 Aug 1;290:113172. pmid:32512357
  15. 15. Daly Z, Slemon A, Richardson CG, Salway T, McAuliffe C, Gadermann AM, et al. Associations between periods of COVID-19 quarantine and mental health in Canada. Psychiatry Res. 2021 Jan 1;295. pmid:33310417
  16. 16. O’Connor RC, Wetherall K, Cleare S, McClelland H, Melson AJ, Niedzwiedz CL, et al. Mental health and well-being during the COVID-19 pandemic: Longitudinal analyses of adults in the UK COVID-19 Mental Health & Wellbeing study. Br J Psychiatry. 2021 Jun 1;218(6):326–33.
  17. 17. Daly M, Sutin A, Robinson E. Longitudinal changes in mental health and the COVID-19 pandemic: Evidence from the UK Household Longitudinal Study. Psychol Med. 2020; pmid:33183370
  18. 18. Ramiz L, Contrand B, Rojas Castro MY, Dupuy M, Lu L, Sztal-Kutas C, et al. A longitudinal study of mental health before and during COVID-19 lockdown in the French population. Global Health. 2021 Dec;17(1).
  19. 19. Jauffret-Roustide M, Coulaud P, Jesson J, Filipe E, Bolduc N, Knight R. Les oubliés de la pandémie: Santé mentale et bien-être social des jeunes adultes. ESPRIT [Internet]. 2021 [cited 2022 Jun 12]; Available from: https://esprit.presse.fr/article/marie-jauffret-roustide-et-pierre-julien-coulaud-et-julie-jesson-et-estelle-filipe-et-naseeb-bolduc-et-rod-knight/les-oublies-de-la-pandemie-43389
  20. 20. Coroiu A, Moran C, Campbell T, Geller AC. Barriers and facilitators of adherence to social distancing recommendations during COVID-19 among a large international sample of adults. Capraro V, editor. PLoS One [Internet]. 2020 Oct 7 [cited 2021 Sep 3];15(10):e0239795. Available from: pmid:33027281
  21. 21. Zhao SZ, Wong JYH, Wu Y, Choi EPH, Wang MP, Lam TH. Social distancing compliance under covid-19 pandemic and mental health impacts: A population-based study. Int J Environ Res Public Health. 2020 Sep 2;17(18):1–11. pmid:32937929
  22. 22. Marroquín B, Vine V, Morgan R. Mental health during the COVID-19 pandemic: Effects of stay-at-home policies, social distancing behavior, and social resources. Psychiatry Res. 2020 Nov 1;293:113419. pmid:32861098
  23. 23. Czeisler M, Howard ME, Robbins R, Barger LK, Facer-Childs ER, Rajaratnam SMW, et al. Early public adherence with and support for stay-at-home COVID-19 mitigation strategies despite adverse life impact: a transnational cross-sectional survey study in the United States and Australia. BMC Public Health. 2021 Dec 1;21(1). pmid:33722226
  24. 24. Liu J, Tong Y, Li S, Tian Z, He L, Zheng J. Compliance with COVID-19-preventive behaviours among employees returning to work in the post-epidemic period. BMC Public Health. 2022 Dec 1;22(1). pmid:35189862
  25. 25. Magson NR, Freeman JYA, Rapee RM, Richardson CE, Oar EL, Fardouly J. Risk and Protective Factors for Prospective Changes in Adolescent Mental Health during the COVID-19 Pandemic. J Youth Adolesc. 2021 Jan 1;50(1):44–57. pmid:33108542
  26. 26. Benke C, Autenrieth LK, Asselmann E, Pané-Farré CA. Lockdown, quarantine measures, and social distancing: Associations with depression, anxiety and distress at the beginning of the COVID-19 pandemic among adults from Germany. Psychiatry Res. 2020 Nov 1;293:113462. pmid:32987222
  27. 27. Martinelli N, Gil S, Chevalère J, Belletier C, Dezecache G, Huguet P, et al. The Impact of the COVID-19 Pandemic on Vulnerable People Suffering from Depression: Two Studies on Adults in France. Int J Environ Res Public Health [Internet]. 2021 Mar 21 [cited 2021 Sep 9];18(6):3250. Available from: https://www.mdpi.com/1660-4601/18/6/3250 pmid:33801095
  28. 28. Wang C, Pan R, Wan X, Tan Y, Xu L, Ho CS, et al. Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. Int J Environ Res Public Health. 2020 Mar 1;17(5). pmid:32155789
  29. 29. World Health Organization. WHO Coronavirus Disease (COVID-19) Dashboard [Internet]. World Health Organization. 2021 [cited 2022 May 15]. p. 1–5. Available from: https://covid19.who.int/%0Ahttps://covid19.who.int/%0Ahttps://covid19.who.int/region/searo/country/bd
  30. 30. Government of Canada. Epidemiological summary of COVID-19 cases in Canada [Internet]. 2021 [cited 2021 Mar 3]. Available from: https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html
  31. 31. Santé Publique France. Géodes—Santé publique France—Indicateurs: cartes, données et graphiques [Internet]. 2021 [cited 2020 Oct 2]. Available from: https://geodes.santepubliquefrance.fr/#c=indicator&f=09&i=sp_pe_tb_heb.tx_pe_hebdo&s=2020-S30&t=a01&view=map2
  32. 32. Governement of Canada. COVID-19 Daily Epidemiology Update [Internet]. 2021 [cited 2021 Aug 23]. Available from: https://health-infobase.canada.ca/covid-19/epidemiological-summary-covid-19-cases.html
  33. 33. Boire-Schwab D, Goldenberg A, Castonguay J-S, Hillstrom M, Landry-Plouffe L. COVID-19: Emergency Measures Tracker | McCarthy Tétrault [Internet]. 2021 [cited 2021 Feb 24]. Available from: https://www.mccarthy.ca/en/insights/articles/covid-19-emergency-measures-tracker
  34. 34. Ontario News Room. Ontario Announces Provincewide Shutdown to Stop Spread of COVID-19 and Save Lives [Internet]. 2020 [cited 2021 Apr 26]. Available from: https://news.ontario.ca/en/release/59790/ontario-announces-provincewide-shutdown-to-stop-spread-of-covid-19-and-save-lives
  35. 35. Gouvernement du Québec. COVID-19-related instructions for the holiday season [Internet]. Québec.ca. 2020 [cited 2021 Apr 26]. Available from: https://www.quebec.ca/en/health/health-issues/a-z/2019-coronavirus/covid-19-related-instructions-holiday-season/
  36. 36. Gouvernement Français. Info Coronavirus COVID-19—Les actions du Gouvernement [Internet]. Gouvernement.fr. 2021 [cited 2021 Apr 24]. Available from: https://www.gouvernement.fr/info-coronavirus/les-actions-du-gouvernement
  37. 37. Spaccaferri G, Larrieu S, Pouey J, Calba C, Benet T, Sommen C, et al. Early assessment of the impact of mitigation measures to control COVID-19 in 22 French metropolitan areas, October to November 2020. Eurosurveillance [Internet]. 2020 Dec 17 [cited 2021 Apr 24];25(50):2001974. Available from: https://www.eurosurveillance.org/content/10.2807/1560-7917.ES.2020.25.50.2001974 pmid:33334399
  38. 38. Storozuk A, Ashley M, Delage V, Maloney EA. Got Bots? Practical Recommendations to Protect Online Survey Data from Bot Attacks. Quant Methods Psychol. 2020 May 1;16(5):472–81.
  39. 39. Teitcher JEF, Bockting WO, Bauermeister JA, Hoefer CJ, Miner MH, Klitzman RL. Detecting, preventing, and responding to “fraudsters” in internet research: Ethics and tradeoffs. J Law, Med Ethics. 2015 Mar 1;43(1):116–33. pmid:25846043
  40. 40. Kroenke K, Spitzer RL. The PHQ-9: A new depression diagnostic and severity measure. Vol. 32, Psychiatric Annals. Slack Incorporated; 2002. p. 509–15.
  41. 41. Pfizer Patient health questionnaire (PHQ) screeners [Internet]. [cited 2022 Dec 8]. Available from: https://www.phqscreeners.com/
  42. 42. Arthurs E, Steele RJ, Hudson M, Baron M, Thombs BD. Are Scores on English and French Versions of the PHQ-9 Comparable? An Assessment of Differential Item Functioning. Laks J, editor. PLoS One [Internet]. 2012 Dec 14 [cited 2022 Dec 8];7(12):e52028. Available from: pmid:23251676
  43. 43. Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med [Internet]. 2001 Sep [cited 2017 Oct 23];16(9):606–13. Available from: http://www.ncbi.nlm.nih.gov/pubmed/11556941 pmid:11556941
  44. 44. Levis B, Benedetti A, Ioannidis JPA, Sun Y, Negeri Z, He C, et al. Patient Health Questionnaire-9 scores do not accurately estimate depression prevalence: individual participant data meta-analysis. J Clin Epidemiol. 2020 Jun 1;122:115–128.e1. pmid:32105798
  45. 45. Canadian Institute for Health Information. Proposed Standards for Race-Based and Indigenous Identity Data Collection and Health Reporting in Canada [Internet]. 2020 [cited 2021 Apr 22]. Available from: https://www.cihi.ca/sites/default/files/document/proposed-standard-for-race-based-data-en.pdf
  46. 46. INSEE. Immigrés et descendants d’immigrés [Internet]. 2020 [cited 2022 May 3]. Available from: https://www.insee.fr/fr/statistiques/4238373?sommaire=4238781#documentation
  47. 47. Silva M, Loureiro A, Cardoso G. Social determinants of mental health: A review of the evidence. Eur J Psychiatry [Internet]. 2016 [cited 2022 Jul 3];30(4):259–92. Available from: https://scielo.isciii.es/scielo.php?pid=S0213-61632016000400004&script=sci_arttext&tlng=en
  48. 48. McQuaid RJ, Cox SML, Ogunlana A, Jaworska N. The burden of loneliness: Implications of the social determinants of health during COVID-19. Psychiatry Res. 2021 Feb 1;296:113648. pmid:33348199
  49. 49. Jenkins EK, McAuliffe C, Hirani S, Richardson C, Thomson KC, McGuinness L, et al. A portrait of the early and differential mental health impacts of the COVID-19 pandemic in Canada: Findings from the first wave of a nationally representative cross-sectional survey. Prev Med (Baltim). 2021 Jan 26;106333. pmid:33509605
  50. 50. Gallagher MW, Zvolensky MJ, Long LJ, Rogers AH, Garey L. The Impact of Covid-19 Experiences and Associated Stress on Anxiety, Depression, and Functional Impairment in American Adults. Cognit Ther Res. 2020 Dec 1;44(6):1043–51. pmid:32904454
  51. 51. Crowley JP, Bleakley A, Silk K, Young DG, Lambe JL. Uncertainty Management and Curve Flattening Behaviors in the Wake of COVID-19’s First Wave. Health Commun [Internet]. 2021 Jan 2 [cited 2022 Jul 21];36(1):32–41. Available from: https://www.tandfonline.com/doi/full/10.1080/10410236.2020.1847452 pmid:33256466
  52. 52. Valle MV Del, Andrés ML, Urquijo S, Yerro-Avincetto M, López-Morales H, Canet-Juric L. Intolerance of uncertainty over covid-19 pandemic and its effect on anxiety and depressive symptoms. Interam J Psychol. 2020 Aug 31;54(2):1–17.
  53. 53. Steinley D. K-means clustering: A half-century synthesis. Br J Math Stat Psychol [Internet]. 2006 May 1 [cited 2022 Jul 21];59(1):1–34. Available from: http://doi.wiley.com/10.1348/000711005X48266 pmid:16709277
  54. 54. Coulaud P julien, Ablona A, Bolduc N, Fast D, Bertrand K, Ward JK, et al. COVID-19 vaccine intention among young adults: Comparative results from a cross-sectional study in Canada and France. Vaccine [Internet]. 2022 Mar 3 [cited 2022 Mar 9];40(16):2442–56. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0264410X22002602 pmid:35305823
  55. 55. Fairchild AJ, MacKinnon DP. A General Model for Testing Mediation and Moderation Effects. Prev Sci. 2009 Jun 12;10(2):87–99. pmid:19003535
  56. 56. Nwachukwu I, Nkire N, Shalaby R, Hrabok M, Vuong W, Gusnowski A, et al. COVID-19 Pandemic: Age-Related Differences in Measures of Stress, Anxiety and Depression in Canada. Int J Environ Res Public Health [Internet]. 2020 Sep 1 [cited 2021 Jul 23];17(17):6366. Available from: https://www.mdpi.com/1660-4601/17/17/6366 pmid:32882922
  57. 57. Essadek A, Rabeyron T. Mental health of French students during the Covid-19 pandemic. Vol. 277, Journal of Affective Disorders. Elsevier B.V.; 2020. p. 392–3.
  58. 58. Tikkanen R, Fields K, II RDW, Abrams MK. Mental Health Conditions and Substance Use: Comparing U.S. Needs and Treatment Capacity with Those in Other High-Income Countries. Commonw Fund [Internet]. 2020 [cited 2021 Sep 9]; Available from: https://www.commonwealthfund.org/publications/issue-briefs/2020/may/mental-health-conditions-substance-use-comparing-us-other-countries
  59. 59. Centre for Addiction and Mental Health. Mental health promotion for youth in Canada [Internet]. 2013. Available from: http://hclinkontario.ca/images/Youth_MHP_Report_FINAL.pdf
  60. 60. Rondet C, Parizot I, Cadwallader JS, Lebas J, Chauvin P. Why underserved patients do not consult their general practitioner for depression: Results of a qualitative and a quantitative survey at a free outpatient clinic in Paris, France. BMC Fam Pract [Internet]. 2015 May 8 [cited 2022 May 2];16(1):57. Available from: https://bmcfampract.biomedcentral.com/articles/10.1186/s12875-015-0273-2
  61. 61. Theurel A, Witt A. Identifying Barriers to Mental Health Help-Seeking in French University Students during the Covid-19 Pandemic. Creat Educ. 2022 Feb 11;13(02):437–49.
  62. 62. Son C, Hegde S, Smith A, Wang X, Sasangohar F. Effects of COVID-19 on college students’ mental health in the United States: Interview survey study. Vol. 22, Journal of Medical Internet Research. JMIR Publications Inc.; 2020. p. e21279.
  63. 63. Lee J, Solomon M, Stead T, Kwon B, Ganti L. Impact of COVID-19 on the mental health of US college students. BMC Psychol [Internet]. 2021 Dec 1 [cited 2021 Sep 15];9(1):95. Available from: https://bmcpsychology.biomedcentral.com/articles/10.1186/s40359-021-00598-3 pmid:34103081
  64. 64. Coughenour C, Gakh M, Pharr JR, Bungum T, Jalene S. Changes in Depression and Physical Activity Among College Students on a Diverse Campus After a COVID-19 Stay-at-Home Order. J Community Health. 2021 Aug 1;46(4):758–66. pmid:33165765
  65. 65. Browning MHEM, Larson LR, Sharaievska I, Rigolon A, McAnirlin O, Mullenbach L, et al. Psychological impacts from COVID-19 among university students: Risk factors across seven states in the United States. PLoS One. 2021;16(1):e0245327. pmid:33411812
  66. 66. Takino S, Hewlett E, Nishina Y, Prinz C. Supporting young people ‘ s mental health through the COVID-19 crisis [Internet]. 2021 [cited 2021 Jul 23]. Available from: https://www.oecd.org/coronavirus/policy-responses/supporting-young-people-s-mental-health-through-the-covid-19-crisis-84e143e5/
  67. 67. Bavel JJV, Baicker K, Boggio PS, Capraro V, Cichocka A, Cikara M, et al. Using social and behavioural science to support COVID-19 pandemic response. Vol. 4, Nature Human Behaviour. Nature Research; 2020. p. 460–71.
  68. 68. Nouaille-Degorce L. L’expertise scientifique au défi de la crise sanitaire [Internet]. 2020 [cited 2021 Sep 13]. Available from: https://www.ena.fr/Recherche/Publications/Collection-Les-papiers-de-recherche-de-l-ENA
  69. 69. Vardavas C, Odani S, Nikitara K, El Banhawi H, Kyriakos C, Taylor L, et al. Public perspective on the governmental response, communication and trust in the governmental decisions in mitigating COVID-19 early in the pandemic across the G7 countries. Prev Med Reports. 2021 Mar 1;21. pmid:33364149
  70. 70. Hale T, Angrist N, Goldszmidt R, Kira B, Petherick A, Phillips T, et al. A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker). Nat Hum Behav. 2021 Apr 1;5(4):529–38. pmid:33686204
  71. 71. Mathieu E, Ritchie H, Rodes-Guirao L, Appel C, Giattino C, Ortiz-Ospina E, et al. Coronavirus pandemic (COVID-19) [Internet]. OurWorldInData.org. 2020. Available from: https://ourworldindata.org/coronavirus
  72. 72. Kidd JD, Jackman KB, Barucco R, Dworkin JD, Dolezal C, Navalta T V., et al. Understanding the Impact of the COVID-19 Pandemic on the Mental Health of Transgender and Gender Nonbinary Individuals Engaged in a Longitudinal Cohort Study. J Homosex [Internet]. 2021 Mar 21 [cited 2021 Mar 2];68(4):592–611. Available from: https://www.tandfonline.com/doi/full/10.1080/00918369.2020.1868185 pmid:33502286
  73. 73. Kneale D, Bécares L. Discrimination as a predictor of poor mental health among LGBTQ+ people during the COVID-19 pandemic: Cross-sectional analysis of the online Queerantine study. BMJ Open. 2021 Jun 25;11(6):e049405. pmid:34172551
  74. 74. Moore SE, Wierenga KL, Prince DM, Gillani B, Mintz LJ. Disproportionate Impact of the COVID-19 Pandemic on Perceived Social Support, Mental Health and Somatic Symptoms in Sexual and Gender Minority Populations. J Homosex [Internet]. 2021 Mar 21 [cited 2021 Mar 1];68(4):577–91. Available from: https://www.tandfonline.com/doi/full/10.1080/00918369.2020.1868184 pmid:33399504
  75. 75. Akré ER, Anderson A, Stojanovski K, Chung KW, VanKim NA, Chae DH. Depression, Anxiety, and Alcohol Use Among LGBTQ+ People During the COVID-19 Pandemic. Am J Public Health. 2021 Sep 1;111(9):1610–9. pmid:34410817
  76. 76. Fruehwirth JC, Biswas S, Perreira KM. The Covid-19 pandemic and mental health of first-year college students: Examining the effect of Covid-19 stressors using longitudinal data. Lin C-Y, editor. PLoS One [Internet]. 2021 Mar 5 [cited 2021 Aug 27];16(3):e0247999. Available from: https://dx.plos.org/10.1371/journal.pone.0247999 pmid:33667243
  77. 77. Mayne SL, Hannan C, Davis M, Young JF, Kelly MK, Powell M, et al. COVID-19 and Adolescent Depression and Suicide Risk Screening Outcomes. Pediatrics. 2021 Jun 17;e2021051507. pmid:34140393
  78. 78. Blake H, Brown N, Follette C, Morgan J, Yu H. Black, indigenous, people of color, and international students: Experiences and resolutions beyond COVID-19. Vol. 111, American Journal of Public Health. American Public Health Association Inc.; 2021. p. 384–6.
  79. 79. Strassle PD, Stewart AL, Quintero SM, Bonilla J, Alhomsi A, Santana-Ufret V, et al. COVID-19-Related Discrimination Among Racial/Ethnic Minorities and Other Marginalized Communities in the United States. Am J Public Health [Internet]. 2022 Mar 1 [cited 2022 Aug 30];112(3):453–66. Available from: https://ajph.aphapublications.org/doi/full/10.2105/AJPH.2021.306594 pmid:35196054
  80. 80. Glowacz F, Schmits E. Psychological distress during the COVID-19 lockdown: The young adults most at risk. Psychiatry Res. 2020 Nov 1;293:113486. pmid:33007682
  81. 81. Voltmer E, Köslich-Strumann S, Walther A, Kasem M, Obst K, Kötter T. The impact of the COVID-19 pandemic on stress, mental health and coping behavior in German University students–a longitudinal study before and after the onset of the pandemic. BMC Public Health [Internet]. 2021 Dec 1 [cited 2021 Aug 30];21(1):1385. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-021-11295-6 pmid:34256717
  82. 82. Généreux M, Landaverde E. Psychological symptoms associated with self-reported events of COVID-19 contact, symptoms, or diagnosis: a large community-based survey among adults in Quebec, Canada. Can J Public Heal. 2022 Jun 1;113(3):394–404. pmid:35437697