Psychological Health and Wellness and the Impact of a Supportive Text Messaging Program (Wellness4MDs) Among Physicians and Medical Learners in Canada: Protocol for a Longitudinal Study
Bibliographic record
Abstract
BACKGROUND: Burnout, anxiety, and depression continue to affect physicians, postgraduate medical trainees, and medical students globally and in Canada particularly after the COVID-19 pandemic. OBJECTIVE: The primary goal of this project is to design, implement, monitor, and evaluate a daily supportive SMS text messaging program (Wellness4MDs, Global Psychological e-Health Foundation). The program aims to reduce the prevalence and severity of burnout, anxiety, and depression symptoms among physicians, postgraduate medical trainees, and medical students in Canada. METHODS: This longitudinal study represents a multistakeholder, mixed methods, multiyear implementation science project. Project evaluation will be conducted through a quantitative prospective longitudinal approach using a paired sample comparison, a naturalistic cross-sectional controlled design, and satisfaction surveys. Prevalence estimates for psychological problems would be based on baseline data from self-completed validated rating scales. Additional data will be collected at designated time points for paired comparison. Outcome measures will be assessed using standardized rating scales, including the Maslach Burnout Inventory for burnout symptoms, the 9-item Patient Health Questionnaire for depression symptoms, the 7-item Generalized Anxiety Disorder scale for anxiety symptoms, and the World Health Organization-Five Well-Being Index. RESULTS: The project launched in the last quarter of 2023, and program evaluation results will become available within 36 months. The Wellness4MDs program is expected to reduce the prevalence and severity of psychological problems among physicians in Canada and achieve high subscriber satisfaction. CONCLUSIONS: The results from the Wellness4MDs project evaluation will provide key information regarding the effectiveness of daily supportive SMS text messages and links to mental health resources on these mental health parameters in Canadian physicians, postgraduate trainees, and medical students. Information will be useful for informing policy and decision-making concerning psychological interventions for physicians in Canada. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/44368.
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 | 0.023 | 0.014 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".