VALIDATION STUDY OF HEALTH BELIEFS SCALE
Bibliographic record
Abstract
Introduction: The Health Belief Scale is a questionnaire used to assess a wide range of beliefs related to health. The objective of this study was to undertake construction and culturally adapt the Health Belief Scale (HBS) to the Portuguese language and to test its reliability and validity. Methods: This new version was obtained with forward/backward translations, consensus panels and a pre-test, having been inspired by some of the items from “Canada’s Health Promotion Survey” and the “European Health and Behaviour Survey”, with the inclusion of new items about food-related beliefs. The Portuguese version of Health Belief Scale and a form for the characteristics of the participants were applied to 849 Portuguese adolescents. Results: Reliability was good with a Cronbach’s alpha coeficient of 0.867, and an intraclass correlation coeficient (ICC) of 0.95. Corrected item-total coeficients ranged from 0.301 to 0.620 and weighted kappa coeficients ranged from 0.72 to 0.93 for the total scale items. We obtained a scale composed of 13 items divided into ive factors (smoking and alcohol belief, food belief, sexual belief, physical and sporting belief, and social belief), which explain 57.97% of the total variance. Conclusions: The scale exhibited suitable psychometric properties, in terms of internal consistency, reproducibility and construct validity. It can be used in various areas of research.
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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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".