Awareness and use of Canadian Armed Forces mental wellbeing programs and resources among Regular Force personnel
Bibliographic record
Abstract
Abstract To support broader efforts to empower military personnel to improve their health and wellbeing, the Canadian Armed Forces (CAF) have implemented numerous mental wellbeing programs and resources. The aim of the present study was to better understand factors that may drive awareness and use of these programs/resources. Data from the Your Say Survey, which is routinely administered to CAF members to assess their perceptions of policies and programs, were analyzed to identify key predictors of awareness and use of programs and resources promoting positive mental health at the individual, unit leader, and organizational levels. The survey was completed in 2021 by a stratified random sample of 1,743 Regular Force members, which was weighted to be representative of the CAF Regular Force population. Awareness of most programs/resources that were considered was found to be quite high, whereas use was comparatively low. Results of logistic regression analyses revealed that program/resource awareness was generally lower among younger CAF members, those who were single and had no dependent children, and those who indicated their supervisors infrequently demonstrated positive behaviours around mental health. Awareness also varied depending on the organizational command in which CAF members worked. It was found that CAF members were generally more likely to have used the program/resource if they reported poorer self-rated mental health and were older. Similar to program/resource awareness, use varied significantly depending on CAF members’ organizational command. The potential implications of these findings for enhancing awareness of mental wellbeing programs and resources in the CAF, and in occupational settings as a whole, are discussed.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".