The prevalence of mental health and addiction concerns and factors associated with depression and anxiety during the COVID-19 pandemic in Ontario, Canada: A cross-sectional study

Oswin Chang; Anthony Levitt; Maida Khalid; Sugy Kodeeswaran; Roula Markoulakis

doi:10.1371/journal.pone.0305229

Abstract

Objective

Higher than expected rates of mental health and/or addiction (MHA) concerns have been documented since the onset of the COVID-19 pandemic. A more up-to-date prevalence of MHA outcomes and the factors associated with the occurrence of MHA concerns remains unclear. This study examined the prevalence of MHA outcomes and factors associated with screening positive for symptoms of depression only, anxiety only, and both depression and anxiety two years into the COVID-19 pandemic in Ontario, Canada.

Method

Ontario adults ≥18 years of age (n = 5000) reported on the presence of symptoms associated with depression, anxiety, and substance use between January and March 2022. Data were also collected on pandemic-related health variables, including COVID-19 infection fear, changes in socioeconomic status and mental health since pandemic onset, satisfaction with social supports, and MHA service needs.

Results

The prevalence of positive screening for depressive or anxiety symptoms only was 8% and 11%, respectively, while 36% screened positive for both. Moderate/high risk levels of substance use were found in 20% of participants for tobacco and 17% for both alcohol and cannabis. Moderate/high risk levels of alcohol use and certain pandemic-related factors (negative change in mental health, unmet MHA service needs) were associated with positive screening for symptoms of depression only, anxiety only, and both depression and anxiety. Satisfaction with social supports was associated with lower likelihoods of being in the depression only and both depression and anxiety groups, and non-White ethnicity was associated with depression only.

Conclusions

There was a continued burden of MHA issues two years into the pandemic. These results underscore the ongoing need for timely and accessible MHA services.

Citation: Chang O, Levitt A, Khalid M, Kodeeswaran S, Markoulakis R (2024) The prevalence of mental health and addiction concerns and factors associated with depression and anxiety during the COVID-19 pandemic in Ontario, Canada: A cross-sectional study. PLoS ONE 19(6): e0305229. https://doi.org/10.1371/journal.pone.0305229

Editor: Guillermo Salinas-Escudero, Hospital Infantil de México Federico Gomez: Hospital Infantil de Mexico Federico Gomez, MEXICO

Received: September 19, 2023; Accepted: May 27, 2024; Published: June 12, 2024

Copyright: © 2024 Chang 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: Data collected for this study, including individual participant data and a data dictionary defining each field in the set, are not publicly available because they contain potentially identifying and sensitive patient information. Data can be made available upon request. Such requests should include a study protocol with clear hypotheses, which will then be reviewed by the study principal investigator and investigator team. If the hypothesis is valid and complies with the authorizations for this study, a data transfer agreement will be developed prior to transfer of de-identified data. Requests should be sent to the Sunnybrook Research Ethics Office at REB@sunnybrook.ca.

Funding: This work was supported by the Canadian Institutes of Health Research (AL, SK, RM; grant number UIP-178831) and the Hurvitz Brain Sciences Summer Student Research Program (OC) through the Sunnybrook Research Institute. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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

Introduction

Globally, depression and anxiety have been estimated to affect 4.4% and 3.6% of the population, respectively [1]. In the early months of the COVID-19 pandemic, increased rates of screening positive for depression and anxiety were well-documented in general population samples, with some prevalence estimates placing depression at 28% and anxiety at 33% [2]. These findings may be unsurprising considering the implementation of various public health measures during the pandemic, from lockdowns to social distancing, which may have upended many lives due to school closures [3], increased caregiving and household responsibilities for parents [4], healthcare services being cut [5], and greater financial difficulties [6]. However, some subsequent studies suggested that screening positive for depression and anxiety increased as the pandemic progressed [7, 8], while others suggested consistent rates or decreases [9, 10]. These heterogeneous findings may be due to varying pandemic severities in different countries, the type/length of societal restrictions, the timing of measurements, methodological differences, availability of vaccines, or the populations themselves [11–13]. Thus, a more up-to-date prevalence of these outcomes from various global jurisdictions is needed to address specific regional needs.

Various factors have been found to be associated with symptoms of depression or anxiety pre-pandemic, such as female gender, younger age, marital challenges, chronic health conditions, poor familial relationships, financial difficulties, unemployment, and family history [14–18]. During the pandemic, some studies reported experiencing symptoms of depression or anxiety was found to be related to younger age, female gender, ethnic minority status, low socioeconomic status (SES), living situation, and non-married marital status [19–22]. However, not all of these factors were found to be significant in all studies, which suggests that additional contextual influences may be an important consideration, so further exploration into people’s experiences with the pandemic itself is warranted. Considering factors such as access to healthcare services, social support, or fear are related to mental health and have been directly impacted due to the pandemic or associated public health measures [5, 23, 24], there is a need to determine how they relate to and influence depression or anxiety in the pandemic context. Thus, understanding which of these factors and what other sociodemographic characteristics or experiences linked to the pandemic are associated with the presence of depressive and/or anxiety symptoms at a later timepoint in the pandemic is necessary because as pandemic conditions change, decision-makers require more data to better distribute mental health and/or addiction (MHA) resources.

Substance use disorders also affect many people as global pre-pandemic prevalence estimates cite heavy alcohol use (18%), daily tobacco use (15%), past-year cannabis use (4%), and past-year use of other substances (<1%) [25]. Similar to mental health concerns, rates of substance use problems during the pandemic have increased [26]. A study from the early months of the pandemic showed 30% of participants reporting harmful and severe levels of alcohol consumption and almost a quarter of adults reported using drugs, with 38% of this group having severe levels of drug use [27]. However, a systematic review suggested the increases in alcohol consumption during the pandemic may be more modest as some studies showed decreased or varied changes in use, although use of other substances has shown more consistent increases overall [28]. A more updated prevalence of substance use in specific regions is required to understand local challenges.

As the pandemic progresses, rates of MHA concerns and factors that promote or sustain them may vary, so there is a continued need for monitoring. This study’s objective was to identify the prevalence of depression, anxiety, and substance use problems in the general population of Ontario, Canada at a time point nearly two years into the pandemic. Furthermore, we sought to determine which demographic characteristics and social determinants of health were independently associated with symptoms of depression only, anxiety only, and both depression and anxiety.

Method

Settings and participants

This study used data from the Phase 3 COVID-19 Mental health & Addictions Service impacts & Care needs (MASC) Study, which aims to examine the mental health and substance use effects of the COVID-19 pandemic on adults in Ontario, Canada [29]. Data reported in this study were collected from January to March 2022, two years after a state of emergency was declared in Ontario [30]. The inclusion criteria for the study were: ≥18 years of age, living in the province of Ontario, Canada, and being registered with Delvinia’s AskingCanadians respondent panel. The exclusion criterion was: respondent’s quota full (based on a priori quotas for age, gender, and region). The interlocking quota’s purpose was to establish representativeness based on age and gender for Ontario residents with differences under five percent of the mean or five percentage points total, as applicable. Despite using regional quotas, less populated regions (outside of Toronto–Ontario’s largest city) were purposely oversampled so that in each area, the known prevalence of depression could be estimated within a 5% margin of error based on sufficient sample size so that appropriate conclusions could be reached [31]. Eligible participants were randomly contacted.

The AskingCanadians panel consists of more than 1 million Canadians. The panel is regularly benchmarked against data from Statistics Canada to ensure representativeness, and more than 500 sociodemographic measures are collected to help ensure panelists meet researchers’ needs [32]. Please see study protocol for further details regarding recruitment and sampling [29]. All procedures involving human subjects/patients were approved by the Sunnybrook Health Sciences Centre Research Ethics Board (Ref # 1931), and written informed consent was obtained from all participants.

Measures

Complete details of the following measures can be found in the study protocol [29]. Data were collected on sociodemographic variables (age, gender, ethnicity, marital status, education level, living situation, and geographic region in Ontario), symptoms of depression and anxiety, substance use, and pandemic-related outcomes (COVID-19 infection fear, impact of pandemic on mental health, social support, SES, and MHA service needs).

MHA outcomes.

Depression and anxiety. The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, (DSM-5) Self-Rated Level 1 Cross-Cutting Symptom Measure—Adult is a self-reported measure that assesses mental health symptoms from 13 psychiatric domains over the past two weeks [33]. However, only the Depression and Anxiety domains were used for this study. There are two and three items, respectively, from the Depression and Anxiety domains, and all items are scored on a 5-point (0–4) scale with higher scores suggesting greater problems in that domain [33]. If any item receives a score ≥2, the participant screens positive in that psychiatric domain and should be further evaluated.

Substance use. Participants also completed the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) Version 3.0, which is an 8-item measure assessing risky or problematic use for 10 substance categories [34, 35]. Aside from tobacco products, alcoholic beverages, cannabis, and opioids, remaining substances were classified under the “other substances” category (e.g., cocaine, amphetamine type stimulants, inhalants, sedatives/sleeping pills, hallucinogens, and other) for this study. Specific substance involvement (SSI) scores 0–3 indicate low risk, 4–26 signifies moderate risk, and ≥27 is high risk. The exception is alcohol, whose scoring cutoffs (from low to high risk) are 0–10, 11–26, and ≥27 [34, 35]. Scores were classified into low and moderate/high risk for this study.

Pandemic-related outcomes.

COVID-19 infection fear. Participants commented on their fear of catching COVID-19 themselves or someone close to them contracting it in the past week. Options included not worried, slightly, moderately, very, and extremely worried. Responses were dichotomized as not worried versus worried.

Impact of pandemic on mental health. Participants also rated how the pandemic has affected their mental health. Options included unchanged, a little better/worse, a lot better/worse, very much better/worse. Responses were categorized into worse versus no change/better.

Social support. Satisfaction with the availability of natural social supports (e.g., friends, family, romantic partners, community groups, coworkers, pets, etc.) since the onset of the pandemic was rated by participants as neither (dis)satisfied, (dis)satisfied, very (dis)satisfied, or extremely (dis)satisfied. Support was dichotomized into satisfied and neither/dissatisfied.

SES. The MacArthur Scale of Subjective Social Status-Adult Version was used to assess SES [36]. Participants completed two 10-point (1–10) slider scales, one requiring retrospective recall for the months just preceding the pandemic and one for during the pandemic, asking them to compare their own income, education, and jobs to those around them. A score of 1 was worst off and 10 was best off. The change in SES was calculated as the difference between the pandemic and pre-pandemic period, and results were classified as worse off and no change/better off.

MHA service needs. Thoughts of using MHA services since the pandemic was declared were reported by participants. Services encompassed but were not limited to sessions with healthcare providers, crisis supports, residential treatment, support groups, and MHA programs. Responses were grouped into having needs unmet (thought about accessing services but did not) and needs met (not needing services/needing and accessing services).

Statistical analysis.

The whole sample was divided into four groups, namely subjects with depression only, anxiety only, both depression and anxiety, and neither. For categorical variables, 2x4 contingency tables were created, and chi-squared (χ²) tests were used to test for significance. For statistically significant models, 2x2 contingency tables and χ² tests were then performed to identify between-group differences. For continuous variables, one-way analysis of variance (ANOVA) or multivariate analysis of variance (MANOVA) were used. If results were statistically significant, post hoc analyses using Fisher’s least significant difference test were performed to identify between-group differences.

A multinomial logistic regression model was then constructed to determine which variables were independently associated with screening positive for symptoms of depression only, anxiety only, and both depression and anxiety (reference group was those with neither depression nor anxiety). The included variables were sociodemographic characteristics (i.e., age groups, gender, ethnicity, marital status, education level, and living situation), ASSIST substance use risk levels (low versus moderate/high) [34, 35] for tobacco, alcohol, and cannabis, and all pandemic-related outcomes. Independent variables were simultaneously added into the model. Statistical analyses were performed using SPSS Statistics 28 (IBM Corporation). Statistically significant results were defined as p < .05 (two-tailed).

Results

In total, 5000 participants completed the survey. The average age was 47.9 (SD 16.3) years old, with an equal number of male and female participants. Most were White (69.8%), married/in a common-law relationship (61.4%), had some postsecondary education or more (87.0%), and living with others (78.0%). For participant characteristics, there were statistically significant differences between groups for age, gender, ethnicity, and marital status but no consistent pattern was found. Table 1 presents full descriptive characteristics.

Download:

Table 1. Baseline characteristics of participants^¹.

https://doi.org/10.1371/journal.pone.0305229.t001

According to census data from Statistics Canada for 2022, the sample was representative based on age and sex. The mean age of participants was 47.9 years (within 5% of the mean age of those ≥18 years old living in Ontario, which is 48.3 years), and our sample was comprised of 49.3% male and 49.3% female participants (both within 5% of the sex proportions of Ontario, which is 49.1% male and 50.9% female) [37].

Prevalence of MHA concerns and pandemic-related outcomes (Table 2)

Download:

Table 2. Depression, anxiety, substance use, and COVID-19-related outcomes.

https://doi.org/10.1371/journal.pone.0305229.t002

The number of participants screening positive for depression only (8.3%), anxiety only (10.7%), both depression and anxiety (35.7%), and neither (45.3%) are presented in Table 2. Moderate to high risk levels of substance use were found in 19.7% of participants for tobacco, 16.8% for alcohol, 17.0% for cannabis, 3.4% for opioids, and 4.7% for other substances. Overall, 66.1% worried about themselves or someone close contracting COVID-19, 55.0% believed the pandemic negatively impacted their mental health, 48.7% were satisfied with their social supports during the pandemic, 28.3% believed they were worse off socioeconomically since the pandemic began, and 24.9% had unmet MHA service needs during the pandemic.

For both the Depression and Anxiety domain scores as well as the ASSIST SSI scores, the models were statistically significant even with age and gender as covariates in the MANOVA analysis. Each of the four groups’ scores were statistically significantly different from each other for the Depression and Anxiety domains. For both domains, those with both depression and anxiety scored the highest, while those with neither scored the lowest. For ASSIST SSI scores, ASSIST risk levels, and pandemic-related outcomes, there were statistically significant differences in scores between groups, but no consistent pattern was found. However, in general, those with both depression and anxiety had the worst outcomes, followed by those with depression or anxiety only, and finally those with neither.

Factors associated with positive screening for symptoms of depression only, anxiety only, and both depression and anxiety (Table 3)

Download:

Table 3. Associations between independent variables and positive screening in mental health symptoms (with respect to neither depression nor anxiety group) (n = 4930).

https://doi.org/10.1371/journal.pone.0305229.t003

In total, 4930 participants were included in the multinomial logistic regression model. Those with neither depression nor anxiety were used as the reference group. Data from non-binary-identifying participants (n = 70) were not included due to small sample size. The regression model for factors associated with positive screening for symptoms of depression only, anxiety only, and both depression and anxiety was significant (χ²(48) = 2125.590, p < .001), explaining 38.9% of the variance (using Nagelkerke R²) (see Table 3).

Compared to the neither depression nor anxiety group, the depression only group was more likely to be BIPOC (Black, Indigenous, and People of Color) (OR = 1.35, 95% CI = 1.05–1.74, p = .02), have moderate/high risk levels of alcohol use (OR = 1.41, 95% CI = 1.03–1.93, p = .03), have negative change in mental health since the pandemic started (OR = 4.07, 95% CI = 3.22–5.14, p < .001), and have unmet MHA service needs (OR = 2.19, 95% CI = 1.61–2.97, p < .001). Satisfaction with social support decreased the likelihood of being in the depression only group (OR = 0.52, 95% CI = 0.44–0.61, p = .002) as compared to the neither depression nor anxiety group. No other independent variables were significant.

The anxiety only group was more likely to be in the 18–34 (OR = 2.87, 95% CI = 2.09–3.94, p < .001) and 35–48 age groups (OR = 1.88, 95% CI = 1.39–2.56, p < .001), be female (OR = 1.64, 95% CI = 1.34–2.02, p < .001), have moderate/high risk levels of alcohol use (OR = 1.53, 95% CI = 1.15–2.05, p = .004), have COVID-19 infection fear (OR = 1.45, 95% CI = 1.16–1.81, p < .001), have negative change in mental health since the pandemic started (OR = 3.12, 95% CI = 2.52–3.85, p < .001), and have unmet MHA service needs (OR = 3.01, 95% CI = 2.32–3.91, p < .001) compared to the neither depression nor anxiety group. No other independent variables were significant.

Compared to the group with neither depression nor anxiety, the group screening positive for both depression and anxiety was more likely to be in the 18–34 (OR = 3.06, 95% CI = 2.38–3.94, p < .001), 35–48 (OR = 2.10, 95% CI = 1.65–2.67, p < .001), and 49–61 (OR = 1.69, 95% CI = 1.34–2.13, p < .001) age groups; be female (OR = 1.27, 95% CI = 1.09–1.49, p = .003); have moderate/high risk levels of tobacco (OR = 1.40, 95% CI = 1.13–1.72, p = .002), alcohol (OR = 1.98, 95% CI = 1.59–2.47, p < .001), and cannabis (OR = 1.80, 95% CI = 1.43–2.27, p < .001) use; have COVID-19 infection fear (OR = 1.53, 95% CI = 1.29–1.82, p < .001); have negative change in mental health since the pandemic started (OR = 6.91, 95% CI = 5.83–8.20, p < .001); have negative change in SES since the pandemic started (OR = 1.44, 95% CI = 1.21–1.71, p < .001); and have unmet MHA service needs (OR = 5.32, 95% CI = 4.33–6.55, p < .001). Positive screening for symptoms of both depression and anxiety was less likely to occur for those more satisfied with social supports during the pandemic (OR = 0.71, 95% CI = 0.57–0.88, p < .001) as compared to the neither depression nor anxiety group. No other independent variables were significant.

Discussion

This study suggests that the number of people screening positive for symptoms of depression and anxiety, and experiencing substance use problems remained concerning two years into the pandemic. Results from the multinomial logistic regression indicate that for those with depression only, being BIPOC, having moderate/high risk levels of alcohol use, negative change in mental health since the pandemic started, and unmet MHA service needs were predictors, while for those with anxiety only, younger age, female gender, moderate/high risk levels of alcohol use, and all pandemic-related factors (except for negative change in SES and satisfaction with social supports) were predictors. Meanwhile, younger age, female gender, moderate/high risk levels of substance use, and negative pandemic-related variable outcomes were significantly and independently associated with positive screening for symptoms of both depression and anxiety. Increased satisfaction with social supports reduced the likelihood of being in the depression only and both depression and anxiety groups, but not the anxiety only group. Remaining demographic characteristics were not significantly independently associated with the depression only, anxiety only, or both depression and anxiety groups.

The prevalence rate of screening positive for depressive and anxiety symptoms regardless of comorbidity in this study was higher than many findings reported early in the pandemic, suggesting mental health concerns remained a substantial problem for many people [19–21]. While there is evidence that mental health symptoms may have subsided in the first half year of the pandemic after an initial spike [9, 19], more long-term studies have found symptom increases [7, 8]. Prevalence rates in this study may be greater than previous reports because the data collection period (January to March 2022) coincided with the 5^th wave of COVID-19 in Canada, which saw the greatest weekly case counts of the entire pandemic to that point [38]. This circumstance may have contributed to heightened rates of symptoms of depression and anxiety, such as from fear of COVID-19 infection to the re-introduction of restrictive public health measures. Thus, this study may have captured a temporary increase in rates of screening positive for depression and anxiety. Another potential explanation for the higher prevalence rates in the present study compared to studies from earlier in the pandemic may be the use of the DSM-5 measurement tool in the current study. A prior study that administered the same measure in a general population sample in Brazil during the pandemic found very high prevalence rates of screening positive for symptoms of depression (68%) and anxiety (82%) [39]. Nevertheless, this tool was designed to aid clinicians in identifying people at risk for various adverse mental health outcomes, so the present study may have identified a pressing need regardless. Concurrently, increased prevalence rates in the present study may be due to increased awareness and visibility surrounding mental health issues during the pandemic.

Risky substance use, suggesting harmful substance use and/or dependence, was also identified. Moderate/high risk levels of alcohol and tobacco use in our study were comparable to pre-pandemic estimates of heavy alcohol and tobacco use identified by Peacock et al. [25], although moderate/high risk levels of cannabis, opioids, and other substance use were higher in our study. Elevated rates of risky cannabis use in this study may have resulted from this substance being legal to purchase and use recreationally in Canada (as of fall 2018). With regards to opioids, poisonings and substance use disorders have steadily increased in recent years in Canada [40]. Alternatively, it may be that greater risk levels with substance use are related to experiencing more social isolation that resulted from lockdowns [41]. Substance use problems may have increased or remained at concerning levels because in Ontario, various severity levels of public health measures were implemented due to emerging SARS-CoV-2 variants and changing COVID-19 case counts, with certain regions experiencing some of the longest-standing restrictions in the world at the time [42]. Moreover, with millions of healthcare services being backlogged and harm reduction/treatment services being disrupted by the pandemic [43], an accumulation of patients from earlier in the pandemic may have delayed the ability to access addiction services and exacerbated increasing trends of substance use problems. That said, although this study identified rates of risky substance use that were higher than pre-pandemic levels, these rates were lower than reports from the early stages of the pandemic [26, 27], perhaps because people may have been using substances to cope with the uncertainty initially surrounding the pandemic [44]. However, as more information was available on the pandemic and public health measures were lifted, other forms of enduring the adversities of the pandemic became more available, such as social gatherings, so the way people interacted with substances may have changed.

The multinomial logistic regression results in this study did not support previous research that identified associations between demographic characteristics (including age, gender, ethnicity, living situation, and marital status) and depression or anxiety [19–22]. With the exception of younger age and female gender, which was associated with higher likelihood of being in the anxiety only and both depression and anxiety groups, and ethnicity, which was associated with the depression only group, other demographic characteristics (i.e., marital status, education level, and living situation) were not statistically significantly associated. Perhaps these characteristics were important initially during the pandemic in identifying those at risk for depressive and/or anxiety symptoms, but the impact of these factors may have changed over time. It may be that the pandemic disproportionately impacted people with certain demographic characteristics at the onset of the pandemic, compared with during the so-called 5^th wave. For instance, COVID-19 infection risk was increased among racialized and/or marginalized groups [45], and isolation/loneliness may have been more pronounced for single individuals and those living alone during social distancing and lockdown measures [46, 47]. However, as the pandemic progressed, vaccines became more readily available and restrictions were lifted [48, 49], so these disparities from the early part of the pandemic may have been reduced. Alternatively, many pandemic-related variables, which prior studies have not all examined, were added into the regression model. Thus, statistical power may have shifted from demographic characteristics to these additional variables. Female gender may have been associated with being in the anxiety only and both anxiety and depression groups because women were disproportionately impacted by such things as job losses during the pandemic, and women with children were more likely to have dropped out of the workforce [4]. Female caregivers are known to have taken on more caregiving and household responsibilities during the pandemic [4]; thus, stress from worrying about their children’s schooling and health or the health of elderly family members may have contributed to increased rates of anxiety symptoms [50]. Moderate/high risk levels of all substance use were also associated with the group that had both depression and anxiety, while only moderate/high risk levels of alcohol use were also associated with the depression only and anxiety only groups. Considering mental health issues and substance use problems are highly comorbid, it is unsurprising to see this association in our findings [51]. In addition, pandemic-related variables were all independently associated with the group that had both depression and anxiety but not the groups with depression or anxiety alone. Of note, those who were satisfied with their social supports were less likely to be in the depression only and both depression and anxiety groups, while those with unmet MHA needs were much more likely to be in the depression only, anxiety only, or both depression and anxiety groups. More perceived social supports has been found to be associated with greater psychological resilience [52], which may explain how social support can act as a protective factor. Meanwhile, unmet MHA service needs indicate people are not receiving the treatment and care they require, so existing mental health concerns may worsen. Understanding the specific reasons people could not/did not access services should be explored in future studies and will be helpful in addressing those barriers. Lastly, it appears that for the most part, the group with both depression and anxiety was more severely impacted both in terms of the number of outcomes and the strength of association. This finding is in keeping with prior studies which have found that those with both depression and anxiety experience worse outcomes (e.g., greater symptom severity, more disability, poorer work performance, etc.) compared to those with either depression or anxiety only or neither [53–55]. Perhaps these participants were experiencing a greater number of symptoms due to an additive effect from depression and anxiety.

This study has several strengths and some limitations. Participants were recruited based on predetermined quotas for age, gender, and geographic region to ensure a representative sample of Ontario residents, improving the generalizability of the findings. Additionally, the large sample size allowed improved power over previous studies in the field. Many pandemic-related variables were simultaneously captured in the survey, which allowed for an investigation into various factors that predispose people to increased likelihood for screening positive for symptoms of depression and/or anxiety. However, differences in rates of depression, anxiety, and substance use compared to pre-pandemic/early pandemic estimates should be interpreted with caution. As these previous reports relied on different methodologies and sampled in other geographic regions, discrepancies in results may be a function of different assessment tools and/or populations. Furthermore, populations anticipated to have lower response rates (such as in Northern Ontario which is more rural) were oversampled so that the prevalence of mental health symptoms could be estimated within a 5% margin of error. However, this oversampling may also reduce the representativeness of our results, and there may also have been self-selection bias, so caution should be exercised when interpreting these findings. Moreover, the reliance on retrospective recall for pre-pandemic variables may have introduced bias. Additionally, only individual and not contextual variables were explored, which may lead to an individualistic fallacy whereby an assumption is made that individual-level outcomes can only be explained by individual-level variables [56]. Lastly, the cross-sectional design of the study did not allow for a longitudinal investigation, meaning this study can provide insight into associations only and cannot comment on or assign causality. As prevalence estimates of MHA concerns and the factors associated with positive screening for depression and/or anxiety are likely to change over time, investigations should be repeated as the pandemic progresses.

MHA concerns continued to be a burden two years into the pandemic. Risky alcohol use and certain pandemic-related factors (e.g., negative change in mental health, unmet MHA service needs) were associated with positive screening for symptoms of depression only, anxiety only, and both depression and anxiety more so than demographic characteristics. Front-line providers working with patients and their families should remain aware of the potential for elevated MHA concerns, particularly among those who have unmet MHA service needs.

References

1. World Health Organization. Depression and Other Common Mental Disorders: Global Health Estimates. Geneva: World Health Organization; 2017 [Cited 2022 Jun 30]. https://iris.who.int/bitstream/handle/10665/254610/WHO-MSD-MER-2017.2-eng.pdf?sequence=1
2. Luo M, Guo L, Yu M, Jiang W, Wang H. The psychological and mental impact of coronavirus disease 2019 (COVID-19) on medical staff and general public—A systematic review and meta-analysis. Psychiatry Res. 2020;291: 113190. pmid:32563745
- View Article
- PubMed/NCBI
- Google Scholar
3. UNICEF. COVID-19 and School Closures: One year of education disruption. 2021 [Cited 2022 Jun 28]. https://data.unicef.org/resources/one-year-of-covid-19-and-school-closures/
4. Sevilla A, Phimister A, Krutikova S, Kraftman L, Farquharson C, Dias MC, et al. How are mothers and fathers balancing work and family under lockdown? 2020. (IFS Briefing Note; 290).
5. World Health Organization. COVID-19 disrupting mental health services in most countries, WHO survey; 2020 Oct 5 [Cited 2021 Oct 14];[about 3 screens]. https://www.who.int/news/item/05-10-2020-covid-19-disrupting-mental-health-services-in-most-countries-who-survey
6. Wilson JM, Lee J, Fitzgerald HN, Oosterhoff B, Sevi B, Shook NJ. Job Insecurity and Financial Concern During the COVID-19 Pandemic Are Associated With Worse Mental Health. J Occup Environ Med. 2020;62(9): 686–691. pmid:32890205
- View Article
- PubMed/NCBI
- Google Scholar
7. Efstathiou V, Papadopoulou A, Pomini V, Yotsidi V, Kalemi G, Chatzimichail K, et al. A one-year longitudinal study on suicidal ideation, depression and anxiety during the COVID-19 pandemic. Asian J Psychiatr. 2022;73: 103175. pmid:35644079
- View Article
- PubMed/NCBI
- Google Scholar
8. Zaninotto P, Iob E, Demakakos P, Steptoe A. Immediate and Longer-Term Changes in the Mental Health and Well-being of Older Adults in England During the COVID-19 Pandemic. JAMA Psychiatry. 2022;79(2):151–159. pmid:34935862
- View Article
- PubMed/NCBI
- Google Scholar
9. Fancourt D, Steptoe A, Bu F. Trajectories of anxiety and depressive symptoms during enforced isolation due to COVID-19 in England: a longitudinal observational study. Lancet Psychiatry. 2021;8(2): 141–149. pmid:33308420
- View Article
- PubMed/NCBI
- Google Scholar
10. Hajek A, Sabat I, Neumann-Böhme S, Schreyögg J, Barros PP, Stargardt T, et al. Prevalence and determinants of probable depression and anxiety during the COVID-19 pandemic in seven countries: Longitudinal evidence from the European COvid Survey (ECOS). J Affect Disord. 2022;299: 517–524. pmid:34920039
- View Article
- PubMed/NCBI
- Google Scholar
11. Dewi A, Nurmandi A, Rochmawati E, Purnomo EP, Dimas Rizqi M, Azzahra A, et al. Global policy responses to the COVID-19 pandemic: proportionate adaptation and policy experimentation: a study of country policy response variation to the COVID-19 pandemic. Health Promot Perspect. 2020;10(4): 359–365. pmid:33312931
- View Article
- PubMed/NCBI
- Google Scholar
12. Middelburg RA, Rosendaal FR. COVID-19: How to make between-country comparisons. Int J Infect Dis. 2020;96: 477–481. pmid:32470605
- View Article
- PubMed/NCBI
- Google Scholar
13. Silberzahn R, Uhlmann EL, Martin DP, Anselmi P, Aust F, Awtrey E, et al. Many Analysts, One Data Set: Making Transparent How Variations in Analytic Choices Affect Results. Adv Methods Pract Psychol Sci. 2018;1(3): 337–356.
- View Article
- Google Scholar
14. K Maideen SF, Sidik SM, Rampal L, Mukhtar F. Prevalence, Associated Factors and Predictors of Depression among Adults in the Community of Selangor, Malaysia. PLoS One. 2014;9(4): e95395. pmid:24755607
- View Article
- PubMed/NCBI
- Google Scholar
15. K Maideen SF, M Sidik S, Rampal L, Mukhtar F. Prevalence, associated factors and predictors of anxiety: a community survey in Selangor, Malaysia. BMC Psychiatry. 2015;15: 262. pmid:26497745
- View Article
- PubMed/NCBI
- Google Scholar
16. Salk RH, Hyde JS, Abramson LY. Gender differences in depression in representative national samples: Meta-analyses of diagnoses and symptoms. Psychol Bull. 2017;143(8): 783–822. pmid:28447828
- View Article
- PubMed/NCBI
- Google Scholar
17. Wang J, Williams J, Lavorato D, Schmitz N, Dewa C, Patten SB. The incidence of major depression in Canada: the National Population Health Survey. J Affect Disord. 2010;123(1–3): 158–163. pmid:19720400
- View Article
- PubMed/NCBI
- Google Scholar
18. Xu W-Q, Tan W-Y, Li X-L, Huang Z-H, Zheng H-R, Hou C-L, et al. Prevalence and correlates of depressive and anxiety symptoms among adults in Guangdong Province of China: A population-based study. J Affect Disord. 2022;308: 535–544. pmid:35460741
- View Article
- PubMed/NCBI
- Google Scholar
19. Betini GS, Hirdes JP, Adekpedjou R, Perlman CM, Huculak N, Hébert P. Longitudinal Trends and Risk Factors for Depressed Mood Among Canadian Adults During the First Wave of COVID-19. Front Psychiatry. 2021;12: 666261. pmid:34335324
- View Article
- PubMed/NCBI
- Google Scholar
20. Czeisler MÉ, Lane RI, Petrosky E, Wiley JF, Christensen A, Njai R, et al. Mental Health, Substance Use, and Suicidal Ideation During the COVID-19 Pandemic—United States, June 24–30, 2020. MMWR Morb Mortal Wkly Rep. 2020;69(32): 1049–1057. pmid:32790653
- View Article
- PubMed/NCBI
- Google Scholar
21. Ettman CK, Abdalla SM, Cohen GH, Sampson L, Vivier PM, Galea S. Prevalence of Depression Symptoms in US Adults Before and During the COVID-19 Pandemic. JAMA Netw Open. 2020;3(9): e2019686. pmid:32876685
- View Article
- PubMed/NCBI
- Google Scholar
22. Shah SMA, Mohammad D, Qureshi MFH, Abbas MZ, Aleem S. Prevalence, Psychological Responses and Associated Correlates of Depression, Anxiety and Stress in a Global Population, During the Coronavirus Disease (COVID-19) Pandemic. Community Ment Health J. 2021;57(1): 101–110. pmid:33108569
- View Article
- PubMed/NCBI
- Google Scholar
23. Luo F, Ghanei Gheshlagh R, Dalvand S, Saedmoucheshi S, Li Q. Systematic Review and Meta-Analysis of Fear of COVID-19. Front Psych. 2021;12: 661078. pmid:34177712
- View Article
- PubMed/NCBI
- Google Scholar
24. Banerjee D, Rai M. Social isolation in Covid-19: The impact of loneliness. Int J Soc Psychiatry. 2020;66(6): 525–527. pmid:32349580
- View Article
- PubMed/NCBI
- Google Scholar
25. Peacock A, Leung J, Larney S, Colledge S, Hickman M, Rehm J, et al. Global statistics on alcohol, tobacco and illicit drug use: 2017 status report. Addiction. 2018;113(10): 1905–1926. pmid:29749059
- View Article
- PubMed/NCBI
- Google Scholar
26. Dodge KA, Skinner AT, Godwin J, Bai Y, Lansford JE, Copeland WE, et al. Impact of the COVID-19 pandemic on substance use among adults without children, parents, and adolescents. Addict Behav Rep. 2021;14: 100388. pmid:34938846
- View Article
- PubMed/NCBI
- Google Scholar
27. Horigian VE, Schmidt RD, Feaster DJ. Loneliness, Mental Health, and Substance Use among US Young Adults during COVID-19. J Psychoactive Drugs. 2021;53(1): 1–9. pmid:33111650
- View Article
- PubMed/NCBI
- Google Scholar
28. Roberts A, Rogers J, Mason R, Siriwardena AN, Hogue T, Whitley GA, et al. Alcohol and other substance use during the COVID-19 pandemic: A systematic review. Drug Alcohol Depend. 2021;229(Pt A): 109150. pmid:34749198
- View Article
- PubMed/NCBI
- Google Scholar
29. Markoulakis R, Khalid M, Silva AD, Kodeeswaran S, Sinyor M, Cheung A, et al. Cross-sectional survey of the Mental health and Addictions effects, Service impacts and Care needs of children, youth and families during the COVID-19 pandemic: the COVID-19 MASC study protocol. BMJ Open. 2022;12(10): e066190. pmid:36288837
- View Article
- PubMed/NCBI
- Google Scholar
30. Nielsen K. A timeline of COVID-19 in Ontario. Global News. 2020 Apr 24 [Cited 2022 Jun 1]. https://globalnews.ca/news/6859636/ontario-coronavirus-timeline/
31. Levitt AJ, Boyle MH, Joffe RT, Baumal Z. Estimated prevalence of the seasonal subtype of major depression in a Canadian community sample. Can J Psychiatry. 2000;45(7): 650–654. pmid:11056828
- View Article
- PubMed/NCBI
- Google Scholar
32. Delvinia [Internet]. AskingCanadians; [Cited 2024 Feb 12];[about 2 screens]. https://www.delvinia.com/solutions/askingcanadians/
33. Narrow WE, Clarke DE, Kuramoto SJ, Kraemer HC, Kupfer DJ, Greiner L, et al. DSM-5 field trials in the United States and Canada, Part III: development and reliability testing of a cross-cutting symptom assessment for DSM-5. Am J Psychiatry. 2013;170(1): 71–82. pmid:23111499
- View Article
- PubMed/NCBI
- Google Scholar
34. Humeniuk R, Dennington V, Ali R. The Effectiveness of a Brief Intervention for Illicit Drugs Linked to the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) in Primary Health Care Settings: A Technical Report of Phase III Findings of the WHO ASSIST Randomized Controlled Trial. Geneva: World Health Organization; 2008 [Cited 2022 Aug 19]. https://www.drugsandalcohol.ie/28120/1/assist_technicalreport_phase3_final.pdf
35. WHO ASSIST Working Group. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): development, reliability and feasibility. Addiction. 2002;97(9): 1183–1194. pmid:12199834
- View Article
- PubMed/NCBI
- Google Scholar
36. Stanford University | SPARQtools [Internet]. MacArthur Scale of Subjective Social Status–Adult Version; [Cited 2023 Nov 14];[about 3 screens]. https://sparqtools.org/mobility-measure/macarthur-scale-of-subjective-social-status-adult-version/
37. Statistics Canada [Internet]. Population estimates on July 1, by age and gender; [Cited 2024 Jan 27];[about 3 screens].
38. Johns Hopkins University Center for Systems Science and Engineering [Internet]. COVID-19 Map; 2020 Jan 22 [Cited 2022 Jun 28];[about 1 screen]. https://coronavirus.jhu.edu/map.html
39. Goularte JF, Serafim SD, Colombo R, Hogg B, Caldieraro MA, Rosa AR. COVID-19 and mental health in Brazil: Psychiatric symptoms in the general population. J Psychiatr Res. 2021;132: 32–37. pmid:33038563
- View Article
- PubMed/NCBI
- Google Scholar
40. Grywacheski V, Sabad A, Kushtova L, Bender M, Rennie N, Cheng R, et al. Opioids in Canada. Healthc Q. 2019;22(1): 11–13. pmid:31244462
- View Article
- PubMed/NCBI
- Google Scholar
41. Bonny-Noach H, Cohen-Louck K, Levy I. Substances use between early and later stages of the COVID-19 pandemic in Israel. Isr J Health Policy Res. 2021;10(1): 46. pmid:34384483
- View Article
- PubMed/NCBI
- Google Scholar
42. Levinson-King R. Toronto lockdown—one of the world’s longest? BBC News. 2021 May 23 [Cited 2022 Dec 19]. https://www.bbc.com/news/world-us-canada-57079577
43. Ontario Medical Association [Internet]. OMA estimates pandemic backlog of almost 16 million health-care services; 2021 Jun 9 [Cited 2022 Dec 19];[about 2 screens]. https://www.oma.org/newsroom/news/2021/jun/oma-estimates-pandemic-backlog-of-almost-16-million-health-care-services/
44. Greenglass E, Chiacchia D, Fiskenbaum L. Investigating COVID-19 stress and coping: Substance use and behavioural disengagement. Int J Psychol. 2022;57(3): 325–335. pmid:34792195
- View Article
- PubMed/NCBI
- Google Scholar
45. Sze S, Pan D, Nevill CR, Gray LJ, Martin CA, Nazareth J, et al. Ethnicity and clinical outcomes in COVID-19: A systematic review and meta-analysis. EClinicalMedicine. 2020;29:100630. pmid:33200120
- View Article
- PubMed/NCBI
- Google Scholar
46. O’Sullivan R, Burns A, Leavey G, Leroi I, Burholt V, Lubben J, et al. Impact of the COVID-19 Pandemic on Loneliness and Social Isolation: A Multi-Country Study. Int J Environ Res Public Health. 2021;18(19): 9982. pmid:34639283
- View Article
- PubMed/NCBI
- Google Scholar
47. Rosenberg M, Luetke M, Hensel D, Kianersi S, Fu T, Herbenick D. Depression and loneliness during April 2020 COVID-19 restrictions in the United States, and their associations with frequency of social and sexual connections. Soc Psychiatry Psychiatr Epidemiol. 2021;56(7): 1221–1232. pmid:33386873
- View Article
- PubMed/NCBI
- Google Scholar
48. Public Health Agency of Canada. From risk to resilience: An equity approach to COVID-19 [The Chief Public Health Officer’s report on the state of public health in Canada on the Internet]. Ottawa: Public Health Agency of Canada; 2020 [Cited 2023 Apr 13]. https://publications.gc.ca/collections/collection_2020/aspc-phac/HP2-10-2020-eng.pdf
49. Kriss JL, Hung M-C, Srivastav A, Black CL, Lindley MC, Lee JT, et al. COVID-19 Vaccination Coverage, by Race and Ethnicity—National Immunization Survey Adult COVID Module, United States, December 2020–November 2021. MMWR Morb Mortal Wkly Rep. 2022;71(23): 757–763. pmid:35679179
- View Article
- PubMed/NCBI
- Google Scholar
50. Adams EL, Smith D, Caccavale LJ, Bean MK. Parents Are Stressed! Patterns of Parent Stress Across COVID-19. Front Psychiatry. 2021;12: 626456. pmid:33897489
- View Article
- PubMed/NCBI
- Google Scholar
51. Santucci K. Psychiatric disease and drug abuse. Curr Opin Pediatr. 2012;24(2): 233–237. pmid:22327950
- View Article
- PubMed/NCBI
- Google Scholar
52. Li F, Luo S, Mu W, Li Y, Ye L, Zheng X, et al. Effects of sources of social support and resilience on the mental health of different age groups during the COVID-19 pandemic. BMC Psychiatry. 2021;21(1): 16. pmid:33413238
- View Article
- PubMed/NCBI
- Google Scholar
53. Deady M, Collins DAJ, Johnston DA, Glozier N, Calvo RA, Christensen H, et al. The impact of depression, anxiety and comorbidity on occupational outcomes. Occup Med (Lond). 2022;72(1): 17–24. pmid:34693972
- View Article
- PubMed/NCBI
- Google Scholar
54. Teesson M, Mitchell PB, Deady M, Memedovic S, Slade T, Baillie A. Affective and Anxiety Disorders and their Relationship with Chronic Physical Conditions in Australia: Findings of the 2007 National Survey of Mental Health and Wellbeing. Aust N Z J Psychiatry 2011;45(11): 939–946. pmid:21967412
- View Article
- PubMed/NCBI
- Google Scholar
55. Klein Hofmeijer-Sevink M, Batelaan NM, van Megen HJGM, Penninx BW, Cath DC, van den Hout MA, et al. Clinical relevance of comorbidity in anxiety disorders: A report from the Netherlands Study of Depression and Anxiety (NESDA). J Affect Disord. 2012;137(1–3): 106–112. pmid:22240085
- View Article
- PubMed/NCBI
- Google Scholar
56. Diez-Roux AV. Bringing context back into epidemiology: variables and fallacies in multilevel analysis. Am J Public Health. 1998;88:216–222. pmid:9491010
- View Article
- PubMed/NCBI
- Google Scholar

[ref1] 1. World Health Organization. Depression and Other Common Mental Disorders: Global Health Estimates. Geneva: World Health Organization; 2017 [Cited 2022 Jun 30]. https://iris.who.int/bitstream/handle/10665/254610/WHO-MSD-MER-2017.2-eng.pdf?sequence=1

[ref2] 2. Luo M, Guo L, Yu M, Jiang W, Wang H. The psychological and mental impact of coronavirus disease 2019 (COVID-19) on medical staff and general public—A systematic review and meta-analysis. Psychiatry Res. 2020;291: 113190. pmid:32563745
View Article
PubMed/NCBI
Google Scholar

[3] View Article

[4] PubMed/NCBI

[5] Google Scholar

[ref3] 3. UNICEF. COVID-19 and School Closures: One year of education disruption. 2021 [Cited 2022 Jun 28]. https://data.unicef.org/resources/one-year-of-covid-19-and-school-closures/

[ref4] 4. Sevilla A, Phimister A, Krutikova S, Kraftman L, Farquharson C, Dias MC, et al. How are mothers and fathers balancing work and family under lockdown? 2020. (IFS Briefing Note; 290).

[ref5] 5. World Health Organization. COVID-19 disrupting mental health services in most countries, WHO survey; 2020 Oct 5 [Cited 2021 Oct 14];[about 3 screens]. https://www.who.int/news/item/05-10-2020-covid-19-disrupting-mental-health-services-in-most-countries-who-survey

[ref6] 6. Wilson JM, Lee J, Fitzgerald HN, Oosterhoff B, Sevi B, Shook NJ. Job Insecurity and Financial Concern During the COVID-19 Pandemic Are Associated With Worse Mental Health. J Occup Environ Med. 2020;62(9): 686–691. pmid:32890205
View Article
PubMed/NCBI
Google Scholar

[10] View Article

[11] PubMed/NCBI

[12] Google Scholar

[ref7] 7. Efstathiou V, Papadopoulou A, Pomini V, Yotsidi V, Kalemi G, Chatzimichail K, et al. A one-year longitudinal study on suicidal ideation, depression and anxiety during the COVID-19 pandemic. Asian J Psychiatr. 2022;73: 103175. pmid:35644079
View Article
PubMed/NCBI
Google Scholar

[14] View Article

[15] PubMed/NCBI

[16] Google Scholar

[ref8] 8. Zaninotto P, Iob E, Demakakos P, Steptoe A. Immediate and Longer-Term Changes in the Mental Health and Well-being of Older Adults in England During the COVID-19 Pandemic. JAMA Psychiatry. 2022;79(2):151–159. pmid:34935862
View Article
PubMed/NCBI
Google Scholar

[18] View Article

[19] PubMed/NCBI

[20] Google Scholar

[ref9] 9. Fancourt D, Steptoe A, Bu F. Trajectories of anxiety and depressive symptoms during enforced isolation due to COVID-19 in England: a longitudinal observational study. Lancet Psychiatry. 2021;8(2): 141–149. pmid:33308420
View Article
PubMed/NCBI
Google Scholar

[22] View Article

[23] PubMed/NCBI

[24] Google Scholar

[ref10] 10. Hajek A, Sabat I, Neumann-Böhme S, Schreyögg J, Barros PP, Stargardt T, et al. Prevalence and determinants of probable depression and anxiety during the COVID-19 pandemic in seven countries: Longitudinal evidence from the European COvid Survey (ECOS). J Affect Disord. 2022;299: 517–524. pmid:34920039
View Article
PubMed/NCBI
Google Scholar

[26] View Article

[27] PubMed/NCBI

[28] Google Scholar

[ref11] 11. Dewi A, Nurmandi A, Rochmawati E, Purnomo EP, Dimas Rizqi M, Azzahra A, et al. Global policy responses to the COVID-19 pandemic: proportionate adaptation and policy experimentation: a study of country policy response variation to the COVID-19 pandemic. Health Promot Perspect. 2020;10(4): 359–365. pmid:33312931
View Article
PubMed/NCBI
Google Scholar

[30] View Article

[31] PubMed/NCBI

[32] Google Scholar

[ref12] 12. Middelburg RA, Rosendaal FR. COVID-19: How to make between-country comparisons. Int J Infect Dis. 2020;96: 477–481. pmid:32470605
View Article
PubMed/NCBI
Google Scholar

[34] View Article

[35] PubMed/NCBI

[36] Google Scholar

[ref13] 13. Silberzahn R, Uhlmann EL, Martin DP, Anselmi P, Aust F, Awtrey E, et al. Many Analysts, One Data Set: Making Transparent How Variations in Analytic Choices Affect Results. Adv Methods Pract Psychol Sci. 2018;1(3): 337–356.
View Article
Google Scholar

[38] View Article

[39] Google Scholar

[ref14] 14. K Maideen SF, Sidik SM, Rampal L, Mukhtar F. Prevalence, Associated Factors and Predictors of Depression among Adults in the Community of Selangor, Malaysia. PLoS One. 2014;9(4): e95395. pmid:24755607
View Article
PubMed/NCBI
Google Scholar

[41] View Article

[42] PubMed/NCBI

[43] Google Scholar

[ref15] 15. K Maideen SF, M Sidik S, Rampal L, Mukhtar F. Prevalence, associated factors and predictors of anxiety: a community survey in Selangor, Malaysia. BMC Psychiatry. 2015;15: 262. pmid:26497745
View Article
PubMed/NCBI
Google Scholar

[45] View Article

[46] PubMed/NCBI

[47] Google Scholar

[ref16] 16. Salk RH, Hyde JS, Abramson LY. Gender differences in depression in representative national samples: Meta-analyses of diagnoses and symptoms. Psychol Bull. 2017;143(8): 783–822. pmid:28447828
View Article
PubMed/NCBI
Google Scholar

[49] View Article

[50] PubMed/NCBI

[51] Google Scholar

[ref17] 17. Wang J, Williams J, Lavorato D, Schmitz N, Dewa C, Patten SB. The incidence of major depression in Canada: the National Population Health Survey. J Affect Disord. 2010;123(1–3): 158–163. pmid:19720400
View Article
PubMed/NCBI
Google Scholar

[53] View Article

[54] PubMed/NCBI

[55] Google Scholar

[ref18] 18. Xu W-Q, Tan W-Y, Li X-L, Huang Z-H, Zheng H-R, Hou C-L, et al. Prevalence and correlates of depressive and anxiety symptoms among adults in Guangdong Province of China: A population-based study. J Affect Disord. 2022;308: 535–544. pmid:35460741
View Article
PubMed/NCBI
Google Scholar

[57] View Article

[58] PubMed/NCBI

[59] Google Scholar

[ref19] 19. Betini GS, Hirdes JP, Adekpedjou R, Perlman CM, Huculak N, Hébert P. Longitudinal Trends and Risk Factors for Depressed Mood Among Canadian Adults During the First Wave of COVID-19. Front Psychiatry. 2021;12: 666261. pmid:34335324
View Article
PubMed/NCBI
Google Scholar

[61] View Article

[62] PubMed/NCBI

[63] Google Scholar

[ref20] 20. Czeisler MÉ, Lane RI, Petrosky E, Wiley JF, Christensen A, Njai R, et al. Mental Health, Substance Use, and Suicidal Ideation During the COVID-19 Pandemic—United States, June 24–30, 2020. MMWR Morb Mortal Wkly Rep. 2020;69(32): 1049–1057. pmid:32790653
View Article
PubMed/NCBI
Google Scholar

[65] View Article

[66] PubMed/NCBI

[67] Google Scholar

[ref21] 21. Ettman CK, Abdalla SM, Cohen GH, Sampson L, Vivier PM, Galea S. Prevalence of Depression Symptoms in US Adults Before and During the COVID-19 Pandemic. JAMA Netw Open. 2020;3(9): e2019686. pmid:32876685
View Article
PubMed/NCBI
Google Scholar

[69] View Article

[70] PubMed/NCBI

[71] Google Scholar

[ref22] 22. Shah SMA, Mohammad D, Qureshi MFH, Abbas MZ, Aleem S. Prevalence, Psychological Responses and Associated Correlates of Depression, Anxiety and Stress in a Global Population, During the Coronavirus Disease (COVID-19) Pandemic. Community Ment Health J. 2021;57(1): 101–110. pmid:33108569
View Article
PubMed/NCBI
Google Scholar

[73] View Article

[74] PubMed/NCBI

[75] Google Scholar

[ref23] 23. Luo F, Ghanei Gheshlagh R, Dalvand S, Saedmoucheshi S, Li Q. Systematic Review and Meta-Analysis of Fear of COVID-19. Front Psych. 2021;12: 661078. pmid:34177712
View Article
PubMed/NCBI
Google Scholar

[77] View Article

[78] PubMed/NCBI

[79] Google Scholar

[ref24] 24. Banerjee D, Rai M. Social isolation in Covid-19: The impact of loneliness. Int J Soc Psychiatry. 2020;66(6): 525–527. pmid:32349580
View Article
PubMed/NCBI
Google Scholar

[81] View Article

[82] PubMed/NCBI

[83] Google Scholar

[ref25] 25. Peacock A, Leung J, Larney S, Colledge S, Hickman M, Rehm J, et al. Global statistics on alcohol, tobacco and illicit drug use: 2017 status report. Addiction. 2018;113(10): 1905–1926. pmid:29749059
View Article
PubMed/NCBI
Google Scholar

[85] View Article

[86] PubMed/NCBI

[87] Google Scholar

[ref26] 26. Dodge KA, Skinner AT, Godwin J, Bai Y, Lansford JE, Copeland WE, et al. Impact of the COVID-19 pandemic on substance use among adults without children, parents, and adolescents. Addict Behav Rep. 2021;14: 100388. pmid:34938846
View Article
PubMed/NCBI
Google Scholar

[89] View Article

[90] PubMed/NCBI

[91] Google Scholar

[ref27] 27. Horigian VE, Schmidt RD, Feaster DJ. Loneliness, Mental Health, and Substance Use among US Young Adults during COVID-19. J Psychoactive Drugs. 2021;53(1): 1–9. pmid:33111650
View Article
PubMed/NCBI
Google Scholar

[93] View Article

[94] PubMed/NCBI

[95] Google Scholar

[ref28] 28. Roberts A, Rogers J, Mason R, Siriwardena AN, Hogue T, Whitley GA, et al. Alcohol and other substance use during the COVID-19 pandemic: A systematic review. Drug Alcohol Depend. 2021;229(Pt A): 109150. pmid:34749198
View Article
PubMed/NCBI
Google Scholar

[97] View Article

[98] PubMed/NCBI

[99] Google Scholar

[ref29] 29. Markoulakis R, Khalid M, Silva AD, Kodeeswaran S, Sinyor M, Cheung A, et al. Cross-sectional survey of the Mental health and Addictions effects, Service impacts and Care needs of children, youth and families during the COVID-19 pandemic: the COVID-19 MASC study protocol. BMJ Open. 2022;12(10): e066190. pmid:36288837
View Article
PubMed/NCBI
Google Scholar

[101] View Article

[102] PubMed/NCBI

[103] Google Scholar

[ref30] 30. Nielsen K. A timeline of COVID-19 in Ontario. Global News. 2020 Apr 24 [Cited 2022 Jun 1]. https://globalnews.ca/news/6859636/ontario-coronavirus-timeline/

[ref31] 31. Levitt AJ, Boyle MH, Joffe RT, Baumal Z. Estimated prevalence of the seasonal subtype of major depression in a Canadian community sample. Can J Psychiatry. 2000;45(7): 650–654. pmid:11056828
View Article
PubMed/NCBI
Google Scholar

[106] View Article

[107] PubMed/NCBI

[108] Google Scholar

[ref32] 32. Delvinia [Internet]. AskingCanadians; [Cited 2024 Feb 12];[about 2 screens]. https://www.delvinia.com/solutions/askingcanadians/

[ref33] 33. Narrow WE, Clarke DE, Kuramoto SJ, Kraemer HC, Kupfer DJ, Greiner L, et al. DSM-5 field trials in the United States and Canada, Part III: development and reliability testing of a cross-cutting symptom assessment for DSM-5. Am J Psychiatry. 2013;170(1): 71–82. pmid:23111499
View Article
PubMed/NCBI
Google Scholar

[111] View Article

[112] PubMed/NCBI

[113] Google Scholar

[ref34] 34. Humeniuk R, Dennington V, Ali R. The Effectiveness of a Brief Intervention for Illicit Drugs Linked to the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) in Primary Health Care Settings: A Technical Report of Phase III Findings of the WHO ASSIST Randomized Controlled Trial. Geneva: World Health Organization; 2008 [Cited 2022 Aug 19]. https://www.drugsandalcohol.ie/28120/1/assist_technicalreport_phase3_final.pdf

[ref35] 35. WHO ASSIST Working Group. The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST): development, reliability and feasibility. Addiction. 2002;97(9): 1183–1194. pmid:12199834
View Article
PubMed/NCBI
Google Scholar

[116] View Article

[117] PubMed/NCBI

[118] Google Scholar

[ref36] 36. Stanford University | SPARQtools [Internet]. MacArthur Scale of Subjective Social Status–Adult Version; [Cited 2023 Nov 14];[about 3 screens]. https://sparqtools.org/mobility-measure/macarthur-scale-of-subjective-social-status-adult-version/

[ref37] 37. Statistics Canada [Internet]. Population estimates on July 1, by age and gender; [Cited 2024 Jan 27];[about 3 screens].

[ref38] 38. Johns Hopkins University Center for Systems Science and Engineering [Internet]. COVID-19 Map; 2020 Jan 22 [Cited 2022 Jun 28];[about 1 screen]. https://coronavirus.jhu.edu/map.html

[ref39] 39. Goularte JF, Serafim SD, Colombo R, Hogg B, Caldieraro MA, Rosa AR. COVID-19 and mental health in Brazil: Psychiatric symptoms in the general population. J Psychiatr Res. 2021;132: 32–37. pmid:33038563
View Article
PubMed/NCBI
Google Scholar

[123] View Article

[124] PubMed/NCBI

[125] Google Scholar

[ref40] 40. Grywacheski V, Sabad A, Kushtova L, Bender M, Rennie N, Cheng R, et al. Opioids in Canada. Healthc Q. 2019;22(1): 11–13. pmid:31244462
View Article
PubMed/NCBI
Google Scholar

[127] View Article

[128] PubMed/NCBI

[129] Google Scholar

[ref41] 41. Bonny-Noach H, Cohen-Louck K, Levy I. Substances use between early and later stages of the COVID-19 pandemic in Israel. Isr J Health Policy Res. 2021;10(1): 46. pmid:34384483
View Article
PubMed/NCBI
Google Scholar

[131] View Article

[132] PubMed/NCBI

[133] Google Scholar

[ref42] 42. Levinson-King R. Toronto lockdown—one of the world’s longest? BBC News. 2021 May 23 [Cited 2022 Dec 19]. https://www.bbc.com/news/world-us-canada-57079577

[ref43] 43. Ontario Medical Association [Internet]. OMA estimates pandemic backlog of almost 16 million health-care services; 2021 Jun 9 [Cited 2022 Dec 19];[about 2 screens]. https://www.oma.org/newsroom/news/2021/jun/oma-estimates-pandemic-backlog-of-almost-16-million-health-care-services/

[ref44] 44. Greenglass E, Chiacchia D, Fiskenbaum L. Investigating COVID-19 stress and coping: Substance use and behavioural disengagement. Int J Psychol. 2022;57(3): 325–335. pmid:34792195
View Article
PubMed/NCBI
Google Scholar

[137] View Article

[138] PubMed/NCBI

[139] Google Scholar

[ref45] 45. Sze S, Pan D, Nevill CR, Gray LJ, Martin CA, Nazareth J, et al. Ethnicity and clinical outcomes in COVID-19: A systematic review and meta-analysis. EClinicalMedicine. 2020;29:100630. pmid:33200120
View Article
PubMed/NCBI
Google Scholar

[141] View Article

[142] PubMed/NCBI

[143] Google Scholar

[ref46] 46. O’Sullivan R, Burns A, Leavey G, Leroi I, Burholt V, Lubben J, et al. Impact of the COVID-19 Pandemic on Loneliness and Social Isolation: A Multi-Country Study. Int J Environ Res Public Health. 2021;18(19): 9982. pmid:34639283
View Article
PubMed/NCBI
Google Scholar

[145] View Article

[146] PubMed/NCBI

[147] Google Scholar

[ref47] 47. Rosenberg M, Luetke M, Hensel D, Kianersi S, Fu T, Herbenick D. Depression and loneliness during April 2020 COVID-19 restrictions in the United States, and their associations with frequency of social and sexual connections. Soc Psychiatry Psychiatr Epidemiol. 2021;56(7): 1221–1232. pmid:33386873
View Article
PubMed/NCBI
Google Scholar

[149] View Article

[150] PubMed/NCBI

[151] Google Scholar

[ref48] 48. Public Health Agency of Canada. From risk to resilience: An equity approach to COVID-19 [The Chief Public Health Officer’s report on the state of public health in Canada on the Internet]. Ottawa: Public Health Agency of Canada; 2020 [Cited 2023 Apr 13]. https://publications.gc.ca/collections/collection_2020/aspc-phac/HP2-10-2020-eng.pdf

[ref49] 49. Kriss JL, Hung M-C, Srivastav A, Black CL, Lindley MC, Lee JT, et al. COVID-19 Vaccination Coverage, by Race and Ethnicity—National Immunization Survey Adult COVID Module, United States, December 2020–November 2021. MMWR Morb Mortal Wkly Rep. 2022;71(23): 757–763. pmid:35679179
View Article
PubMed/NCBI
Google Scholar

[154] View Article

[155] PubMed/NCBI

[156] Google Scholar

[ref50] 50. Adams EL, Smith D, Caccavale LJ, Bean MK. Parents Are Stressed! Patterns of Parent Stress Across COVID-19. Front Psychiatry. 2021;12: 626456. pmid:33897489
View Article
PubMed/NCBI
Google Scholar

[158] View Article

[159] PubMed/NCBI

[160] Google Scholar

[ref51] 51. Santucci K. Psychiatric disease and drug abuse. Curr Opin Pediatr. 2012;24(2): 233–237. pmid:22327950
View Article
PubMed/NCBI
Google Scholar

[162] View Article

[163] PubMed/NCBI

[164] Google Scholar

[ref52] 52. Li F, Luo S, Mu W, Li Y, Ye L, Zheng X, et al. Effects of sources of social support and resilience on the mental health of different age groups during the COVID-19 pandemic. BMC Psychiatry. 2021;21(1): 16. pmid:33413238
View Article
PubMed/NCBI
Google Scholar

[166] View Article

[167] PubMed/NCBI

[168] Google Scholar

[ref53] 53. Deady M, Collins DAJ, Johnston DA, Glozier N, Calvo RA, Christensen H, et al. The impact of depression, anxiety and comorbidity on occupational outcomes. Occup Med (Lond). 2022;72(1): 17–24. pmid:34693972
View Article
PubMed/NCBI
Google Scholar

[170] View Article

[171] PubMed/NCBI

[172] Google Scholar

[ref54] 54. Teesson M, Mitchell PB, Deady M, Memedovic S, Slade T, Baillie A. Affective and Anxiety Disorders and their Relationship with Chronic Physical Conditions in Australia: Findings of the 2007 National Survey of Mental Health and Wellbeing. Aust N Z J Psychiatry 2011;45(11): 939–946. pmid:21967412
View Article
PubMed/NCBI
Google Scholar

[174] View Article

[175] PubMed/NCBI

[176] Google Scholar

[ref55] 55. Klein Hofmeijer-Sevink M, Batelaan NM, van Megen HJGM, Penninx BW, Cath DC, van den Hout MA, et al. Clinical relevance of comorbidity in anxiety disorders: A report from the Netherlands Study of Depression and Anxiety (NESDA). J Affect Disord. 2012;137(1–3): 106–112. pmid:22240085
View Article
PubMed/NCBI
Google Scholar

[178] View Article

[179] PubMed/NCBI

[180] Google Scholar

[ref56] 56. Diez-Roux AV. Bringing context back into epidemiology: variables and fallacies in multilevel analysis. Am J Public Health. 1998;88:216–222. pmid:9491010
View Article
PubMed/NCBI
Google Scholar

[182] View Article

[183] PubMed/NCBI

[184] Google Scholar

Figures

Abstract

Objective

Method

Results

Conclusions

Introduction

Method

Settings and participants

Measures

MHA outcomes.

Pandemic-related outcomes.

Statistical analysis.

Results

Prevalence of MHA concerns and pandemic-related outcomes (Table 2)

Factors associated with positive screening for symptoms of depression only, anxiety only, and both depression and anxiety (Table 3)

Discussion

References