Translation and Psychometric Evaluation of the Partners in Health Scale Among Iranian Adults With Chronic Diseases
Bibliographic record
Abstract
Objectives: Characterizing the psychometric attributes of the Persian variant of partners in health (PIH) in multiple sclerosis (MS), Diabetes, and Low Back Pain (LBP) patients. Methods: In this cross-sectional study, 183 MS, diabetes, and LBP patients (70 male, 113 female) were treated with PIH post-forward-backward translation. Confirmatory factor analysis was used for studying the factor structure. Cronbach’s α and McDonald’s Ω coefficients were used to analyze PIH internal consistency. We used an interclass correlation coefficient to evaluate test-retest reliability. Criterion validity was determined by studying the correlation of PIH and Short Form (36) Health Survey (SF-36), Diabetes Self-Management Scale (DSMS), and Self-Efficacy in Chronic Disease Self-Management (SES6G). Results: The median age of the participants was 49.73±15.16 years, 113 (61.75%) of them were female, 64 (35.0%) had MS, 66 (36.1%) had diabetes, and 53 (29.0%) had LBP. Content validity was determined across all areas (clarity, relevancy, simplicity) by a content validity index ≥0.82. Additionally, all items were confirmed via a content validity ratio ≥0.78. The outcome of CFA depicts that the statistics presented as model fit were as follows: CFI= 0.938, NFI= 0.899, and RMSEA= 0.085. All PIH items exhibited valid internal consistency (0.886-0.893). The PIH showed sufficient test-retest reliability regarding its corresponding subscales (0.554-0.679). The construct validity was confirmed by the total scores of PIH correlated with the total score of SF-36, SES6G, and DSMS. Discussion: The Persian variant of the PIH showed sufficient validity and reliability as a measure to assess self-management in patients suffering from chronic disease (MS, diabetes, and LBP).
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".