Prevalence of Perceived Stress, Anxiety, Depression, and Obsessive-Compulsive Symptoms in Health Care Workers and Other Workers in Alberta During the COVID-19 Pandemic: Cross-Sectional Survey
Bibliographic record
Abstract
BACKGROUND: During pandemics, effective containment and mitigation measures may also negatively influence psychological stability. As knowledge about COVID-19 rapidly evolves, global implementation of containment and mitigation measures has varied greatly, with impacts to mental wellness. Assessing the impact of COVID-19 on the mental health needs of health care workers and other workers may help mitigate mental health impacts and secure sustained delivery of health care and other essential goods and services. OBJECTIVE: This study assessed the self-reported prevalence of stress, anxiety, depression, and obsessive-compulsive symptoms in health care workers and other workers seeking support through Text4Hope, an evidence-based SMS text messaging service supporting the mental health of residents of Alberta, Canada, during the COVID-19 pandemic. METHODS: An online cross-sectional survey gathered demographic (age, gender, ethnicity, education, relationship, housing and employment status, employment type, and isolation status) and clinical characteristics using validated tools (self-reported stress, anxiety, depression, and contamination/hand hygiene obsessive-compulsive symptoms). Descriptive statistics and chi-square analysis were used to compare the clinical characteristics of health care workers and other workers. Post hoc analysis was conducted on variables with >3 response categories using adjusted residuals. Logistic regression determined associations between worker type and likelihood of self-reported symptoms of moderate or high stress, generalized anxiety disorder, and major depressive disorder, while controlling for other variables. RESULTS: Overall, 8267 surveys were submitted by 44,992 Text4Hope subscribers (19.39%). Of these, 5990 respondents were employed (72.5%), 958 (11.6%) were unemployed, 454 (5.5%) were students, 559 (6.8%) were retired, 234 (2.8%) selected "other," and 72 (0.9%) did not indicate their employment status. Most employed survey respondents were female (n=4621, 86.2%). In the general sample, the 6-week prevalence rates for moderate or high stress, anxiety, and depression symptoms were 85.6%, 47.0%, and 44.0%, respectively. Self-reported symptoms of moderate or high stress, anxiety, and depression were all statistically significantly higher in other workers than in health care workers (P<.001). Other workers reported higher obsessive-compulsive symptoms (worry about contamination and compulsive handwashing behavior) after the onset of the pandemic (P<.001), while health care worker symptoms were statistically significantly higher before and during the COVID-19 pandemic (P<.001). This finding should be interpreted with caution, as it is unclear the extent to which the adaptive behavior of health care workers or the other workers might be misclassified by validated tools during a pandemic. CONCLUSIONS: Assessing symptoms of prevalent stress, anxiety, depression, and obsessive-compulsive behavior in health care workers and other workers may enhance our understanding of COVID-19 mental health needs. Research is needed to understand more fully the relationship between worker type, outbreak phase, and mental health changes over time, as well as the utility of validated tools in health care workers and other workers during pandemics. Our findings underscore the importance of anticipating and mitigating the mental health effects of pandemics using integrated implementation strategies. Finally, we demonstrate the ease of safely and rapidly assessing mental health needs using an SMS text messaging platform during a pandemic. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/19292.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".