[French-Canadian validation of the MOS Social Support Survey].
Bibliographic record
Abstract
BACKGROUND: The MOS Social Support Survey was developed for patients who participated in the Medical Outcomes Study (MOS), a two-year study on persons who suffered from chronic illness. There are a number of advantages to using the MOS Social Support Survey, especially with those persons who suffer from chronic illness: it is easy to understand, is relatively short, is multidimensional, can be completed by the patient without assistance and has good psychometric properties. OBJECTIVE: The goal of this study was to establish a French-Canadian version of the MOS Social Support Survey and to verify its psychometric properties following the cross-cultural translation and validation procedures proposed by Vallerand. METHODS: A first draft of the MOS Social Support Survey was achieved by following the back-to-back translation technique. Next, a committee of four bilingual people reviewed and evaluated the preliminary versions of the questionnaire (English and French) to establish a French experimental version. A pre-test was done with 10 francophone persons. The Haccoun method was used to evaluate the construct validity and test-retest reliability, as well as the internal consistency of the questionnaire. The test-retest was performed with 20 students from the School of Languages from Laval University, Sainte-Foy, Quebec. The present research was approved by the ethics committee of the institution. RESULTS: The results showed acceptable internal consistency and good reliability. The psychometric properties were found to be acceptable and comparable with those obtained by Sherbourne and Stewart with the English version. CONCLUSION: The French-Canadian version of the MOS Social Support Survey should be useful in evaluating social support among patients to allow medical staff to plan rehabilitation programs that would include the necessary consultations and interventions needed to establish a better quality of life for the patient.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".