The validity of the MacNew Quality of Life in heart disease questionnaire.
Bibliographic record
Abstract
BACKGROUND: A previous review suggested that the MacNew Quality of Life Questionnaire was the most appropriate disease-specific measure of health-related quality of life among people with ischaemic heart disease. However, there is ambiguity about the allocation of items to the three factors underlying the MacNew and the factor structure has not been confirmed previously among the people in the UK. METHODS: The MacNew Questionnaire and the SF-36 were administered to 117 newly admitted patients to a tertiary referral centre in Northern Ireland. All patients had been diagnosed with ischaemic heart disease. RESULTS: A confirmatory factor analysis was conducted on the factor structure of the MacNew and the model was found to be an inadequate fit of the data. A quantitative and qualitative analysis of the items suggested that a five factor solution was more appropriate and this was validated by confirmatory factor analysis. This new structure also displayed strong evidence of concurrent validity when compared to the SF-36. CONCLUSION: We recommend that researchers should submit scores obtained from items on the MacNew to secondary analyses after being grouped according to the factor structure proposed in this paper, in order to explore further the most appropriate grouping of items.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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".