Validation d’une version française du Outcome Questionnaire et évaluation d’un service de counselling en milieu clinique
Bibliographic record
Abstract
Abstract: The first purpose of this study was to assess the psychometric quality and validity of the Mesure d’Impact-45 (MI-45) and the Mesure d’Impact-22 (MI-22), French translations of 45-item and 22-item versions, respectively, of the Outcome Questionnaire. The second purpose was to evaluate, by means of the MI-22, a French-language counselling program located in a clinical setting in Quebec, which provided additional information on the sensitivity to change and clinical utility of the MI-22. Eleven counsellors served a total of 216 clients (80% women) during the period of the study. The MI-22 had good internal consistency (coefficient alpha = .88) and correlated well with a criterion measure, the SCL-10, a short form of the SCL-90-R. Ninety clients who had taken part in at least eight counselling sessions made clinically and statistically significant progress. Of 107 clients completing counselling during the study period, 37% recovered, 29% improved, 24% experienced no change in functioning, and 10% deterioriated. Seventy clients who had completed a post-counselling telephone interview expressed a high level of satisfaction with the program, while also making suggestions for service improvement. The MI-22 was seen as useful by both clients and counsellors.
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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 | 0.040 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".