Evaluating the Prevalence and predictors of anxiety and depression among elementary and high school educators in Canada.
Bibliographic record
Abstract
Introduction Globally, anxiety and depression are primary contributors to work disability and are associated with the mental and physical well-being of educators.Anxiety and depressive disorders result in poor mental health, great human misery, enormous loss in economic output and increased public health and economic burden. Objectives To determine the prevalence and independent predictors of likely Generalized Anxiety Disorder (GAD) and likely Major Depressive Disorder (MDD) among teachers in Newfoundland and Labrador, Alberta, and Nova Scotia. Methods The study utilized a cross-sectional design. Educators in the three Canadian provinces completed an online survey after enrolling on the Wellness4Teachers program, a daily supportive text messaging program. Likely GAD and likely MDD among subscribers were respectively assessed using the Generalized Anxiety Disorder-7 scale and Patient Health Questionnaire-9. Data was analyzed with SPSS version 28. Results Overall,763 out of the 1912 subscribers of the Wellness4Teachers program completed the survey, resulting in a 39.91% response rate. The prevalence of likely MDD was 55.7%, and likely GAD was 46.0%. Participants who experience high stress were 7.24 times more likely to experience MDD (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. Again, 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 who did not. Similarly, respondents with low resilience were 3.01 times more likely to experience likely GAD compared to those with normal to high resilience (OR =3.01; 95% CI: 2.03-7.62). Sociodemographic and work-related variables did not independently predict the presence of likely GAD and likely MDD. Conclusions The current study reinforces the need for governments and policymakers in the education sector to implement appropriate and comprehensive mental health support programs to address the unique stressors faced by educators, reduce emotional exhaustion and improve resilience as a way to reduce anxiety and depression, promote their well-being and enhance the quality of educational delivery. Disclosure of Interest None Declared
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".