Development and Validation of an Instrument Measuring Individual Empowerment in Relation to Personal Health Care: The Health Care Empowerment Questionnaire (HCEQ)
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to develop and validate a questionnaire that measures the degree of individual empowerment in relation to personal health care and services. DESIGN: The questionnaire was developed by identifying individual empowerment indicators from the literature, generating corresponding items, and pretesting the tool with older persons. SETTING: The Health Care Empowerment Questionnaire (HCEQ) was developed and validated with subjects participating in the Program of Research to Integrate Services for the Maintenance of Autonomy (PRISMA) in the Sherbrooke and Quebec City area. SUBJECTS: Eight hundred seventy-three subjects agreed to participate, for a response rate of 56.28%. The mean ages of men and women were 81.1 and 82.4 years, respectively. Analysis. Factor analysis (exploratory and confirmatory) determined the validity of the questionnaire, and the reliability was assessed using measures of internal consistency and temporal stability (test-retest). RESULTS: The multidimensional nature of the concept of individual empowerment was confirmed by three factors that explain more than 68% of the total variance. The Cronhbach's alpha coefficient of internal consistency was .83 and the intraclass correlation coefficients (test-retest) was .70 (95% CI: .48-.83). CONCLUSION: In light of these findings, the characteristics and multidimensional perspective of the HCEQ appear to be useful in advancing knowledge about individual empowerment in relation to personal health care and services.
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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 | 0.022 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".