Prevalence and Independent Predictors of Anxiety and Depression Among Elementary and High School Educators: Cross-Sectional Study (Preprint)
Bibliographic record
Abstract
BACKGROUND Globally, anxiety and depression are primary contributors to work disability and impact the mental and physical well-being of educators. OBJECTIVE This study aims to determine the prevalence and independent predictors of likely generalized anxiety disorder (GAD) and likely major depressive disorder (MDD) among teachers in the Canadian provinces of Newfoundland and Labrador, Alberta, and Nova Scotia. METHODS The study used a cross-sectional design. Educators from the 3 Canadian provinces participated by completing a web-based survey after enrolling in the Wellness4Teachers program, a free, self-subscription, daily, supportive SMS text messaging initiative. The program was launched at the beginning of the 2022-2023 academic year, and all teachers in the 3 provinces were eligible to enroll. Likely GAD and likely MDD among subscribers were assessed using the Generalized Anxiety Disorder-7 scale and the Patient Health Questionnaire-9, respectively. Data analysis was conducted using SPSS (version 28.0). RESULTS Of the 1912 Wellness4Teachers subscribers, 763 (39.9%) completed the survey. The prevalence of likely MDD was 55.7% (425/763) and that of likely GAD was 46% (349/759). After controlling for all other variables in the regression model, participants who reported high stress were 7.24 times more likely to experience MDD (odds ratio [OR] 7.24, 95% CI 4.22-12.42) and 7.40 times more likely to experience GAD (OR 7.40, 95% CI 4.63-11.80) than those with mild to moderate stress. Participants with emotional exhaustion were 4.92 times more likely to experience MDD (OR 4.92, 95% CI 3.01-8.05) and 4.34 times more likely to experience GAD (OR 4.34, 95% CI 2.47-7.62) than those without. Moreover, respondents with a lack of professional accomplishment were 2.13 times as likely to have MDD symptoms (OR 2.13, 95% CI 1.41-3.23) and 1.52 times more likely to experience GAD symptoms (OR 1.524, 95% CI 1.013-2.293) than those without. Similarly, respondents with low resilience were 1.82 times more likely to have likely MDD than those with normal to high resilience (OR 1.82, 95% CI 1.24-2.66). In addition, respondents with low resilience were 3.01 times more likely to experience likely GAD than those with normal to high resilience (OR 3.01, 95% CI 2.03-7.62). Participants with >20 years of teaching experience were 0.28 times less likely to experience GAD symptoms than those with ≤5 years of teaching experience (OR 0.28, 95% CI 0.12-0.64). Sociodemographic and work-related variables did not independently predict likely GAD and likely MDD. CONCLUSIONS This study underscores the need for governments and policy makers in the education sector to implement comprehensive mental health support programs. Addressing the unique stressors faced by educators, reducing emotional exhaustion, and enhancing resilience are crucial steps toward mitigating anxiety and depression, promoting educators’ well-being, and improving the quality of educational delivery. INTERNATIONAL REGISTERED REPORT RR2-10.2196/37934.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".