Burnout and Associated Psychological Problems Among Teachers and the Impact of the Wellness4Teachers Supportive Text Messaging Program: Protocol for a Cross-sectional and Program Evaluation Study
Bibliographic record
Abstract
BACKGROUND: Stress, burnout, anxiety, and depression continue to be a problem among teachers worldwide. It is not presently known what the prevalence and correlates for these psychological problems are among teachers in Alberta and Nova Scotia. It is also not known if a supportive text message program (Wellness4Teachers) would be effective in reducing stress, burnout, anxiety, or depression symptoms among teachers. OBJECTIVE: The goal of this study is to evaluate the prevalence and correlates of stress, burnout, symptoms of anxiety, depression, and low resilience among elementary and high school teachers in Alberta and Nova Scotia, Canada. It also aims to determine if daily supportive text messages can help reduce the prevalence of these psychological problems in teachers. METHODS: This is a cross-sessional mixed methods study with data to be collected from subscribers of Wellness4Teachers using a web-based survey at baseline (onset of text messaging), 6 weeks, the program's midpoint (3 months), and end point (6 months). Teachers can subscribe to the Wellness4Teachers program by texting the keyword "TeachWell" to the program phone number. Outcome measures will be assessed using standardized rating scales and key informant interviews. Data will be analyzed with descriptive and inferential statistics using SPSS and thematic analysis using NVivo. RESULTS: The results of this study are expected 24 months after program launch. It is expected that the prevalence of stress, burnout, anxiety, depression, and low resilience among teachers in Alberta and Nova Scotia would be comparable to those reported in other jurisdictions. It is also expected that factors such as gender, number of years teaching, grade of teaching, and school type (elementary vs high school) will have an association with burnout and other psychological disorders among teachers. Furthermore, it is expected that Wellness4Teachers will reduce the prevalence and severity of psychological problems in teachers, and subscriber satisfaction will be high. CONCLUSIONS: The Wellness4Teachers project will provide key information regarding prevalence and correlates of common mental health conditions in teachers in Alberta and Nova Scotia, as well as the impact of daily supportive text messages on these mental health parameters. Information from this study will be useful for informing policy and decision-making concerning psychological interventions for schoolteachers.
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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 | 0.029 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 0.005 |
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".