The French adaptation and validation of the Partners in Health (PIH) scale among patients with chronic conditions seen in primary care
Bibliographic record
Abstract
OBJECTIVE: Measuring self-management helps identify the degree of participation of people in the management of their chronic conditions and guides clinicians in determining person-centred priorities for providing support. The Partners in Health scale, a self-report generic questionnaire, was developed to capture the self-management of patients with chronic conditions. This study aimed to translate the Partners in Health scale into French and to examine its psychometric properties in French-speaking people with chronic conditions followed in primary care. METHODS: The Partners in Health scale was translated into French using Hawkins and Osborne's method (2012). Content validity was evaluated through cognitive interviews (Think Aloud Method). Internal consistency was measured at baseline with Cronbach's alpha. Test-retest reliability was evaluated at baseline and two weeks later using the intraclass correlation coefficient. Concurrent validity was measured at baseline with the Self-efficacy for Managing Chronic Disease (SEM-CD) and the Patient Activation Measure (PAM), using Spearman correlations. RESULTS: Cognitive interviews were conducted with 10 participants. During these interviews, most items were clearly understood and accepted as formulated; only a few terms were modified. To evaluate the psychometric properties of the French-language version of the Partners in Health scale, 168 participants (male = 34.5%; mean age = 58 years; mean number of chronic conditions = 4.1) completed the questionnaire at baseline and 47 of them completed the questionnaire two weeks later by telephone. Cronbach's alpha for internal consistency was 0.85 (95% confidence interval: 0.81-0.88). The intraclass correlation coefficient for test-retest reliability was 0.77 (95% confidence interval: 0.58-0.87). Concurrent validity with spearman's coefficient correlation of Self-efficacy for Managing Chronic Disease and Patient Activation Measure was 0.68 and 0.61 respectively. CONCLUSION: The French-language version of the Partners in Health scale is a reliable and valid questionnaire for the measure of self-management in persons with chronic conditions seen in primary 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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".