Are we ready for measurement-based care? Examining organizational readiness for change among Canadian Armed Forces mental health care providers
Bibliographic record
Abstract
LAY SUMMARY The Client-Reported Outcomes Monitoring Information System (CROMIS) uses regular feedback from patients to guide mental health treatment and to improve mental health outcomes. Since 2018, CROMIS has been implemented in stages across Canadian Forces (CF) Health Services Centres. In this study, an online survey was administered to examine how prepared mental health care providers feel in terms of using CROMIS in their practice. The results from 55 providers revealed generally positive attitudes towards CROMIS and its evidence. However, providers also felt that material to educate patients about this new system was limited and that the needs of patients themselves needed to be considered. Several providers reported not knowing about the roles and responsibilities of CROMIS leaders who were expected to guide others in using this new system. In addition, there was uncertainty about how CROMIS would be evaluated and improved in the future. This study helped to identify factors that could be helping or impairing CF mental health care providers in using CROMIS to improve patient care.
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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 | 0.021 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| 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".