Measurement of family‐centred care: translation, adaptation and validation of the Measure of Processes of Care (MPOC‐56 and ‐20) for use in Japan
Bibliographic record
Abstract
BACKGROUND: The Measure of Processes of Care (MPOC) that was developed in Canada is a widely used quantitative measure of parents' perceptions of the extent to which family-centred care is conducted. The purpose of this study was to assess the validity and reliability of the Japanese version of the MPOC. METHODS: The translation of the MPOC was performed according to international standards for translation of questionnaires. The Canadian validation procedures were followed, consisting of concurrent validity, construct validity and test-retest reliability. The Japanese version of the MPOC was completed by 261 families with children receiving rehabilitation services. RESULTS: The Japanese version of the MPOC showed adequate internal consistency with Cronbach's alpha, varying between 0.76 and 0.94. The construct validity was examined with confirmative analysis of each scale structure. Correlations between the MPOC scale scores and satisfaction questions scores were positive, and that to a question about parents' stress was negative. For test-retest reliability, the intraclass correlation coefficients were between 0.76 and 0.89. CONCLUSIONS: The Japanese version of the MPOC has good psychometric properties and can be recommended for evaluation of the processes of child rehabilitation in Japan.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".