Psychometric validation of the short version of the Information Needs in Cardiac Rehabilitation scale through a first global assessment
Bibliographic record
Abstract
AIMS: Tailored education is recommended for cardiac patients, yet little is known about information needs in areas of the world where it is most needed. This study aims to assess (i) the measurement properties of the Information Needs in Cardiac Rehabilitation short version (INCR-S) scale and (ii) patient's information needs globally. METHODS AND RESULTS: In this cross-sectional study, English, simplified Chinese, Portuguese, or Korean versions of the INCR-S were administered to in- or out-patients via Qualtrics (January 2022-November 2023). Members of the International Council of Cardiovascular Prevention and Rehabilitation community facilitated recruitment. Importance and knowledge sufficiency of 36 items were rated. Links to evidence-based lay education were provided where warranted. A total of 1601 patients from 19 middle- and high-income countries across the world participated. Structural validity was supported upon factor analysis, with five subscales extracted: symptom response/medication, heart diseases/diagnostic tests/treatments, exercise and return-to-life roles/programmes to support, risk factors, and healthy eating/psychosocial management. Cronbach's alpha was 0.97. Construct validity was supported through significantly higher knowledge sufficiency ratings for all items and information importance ratings for all subscales in cardiac rehabilitation (CR) enrolees vs. non-enrolees (all P < 0.001). All items were rated as very important-particularly regarding cardiac events, nutrition, exercise benefits, medications, symptom response, risk factor control, and CR-but more so in high-income countries in the Americas and Western Pacific. Knowledge sufficiency ranged from 30.0 to 67.4%, varying by region and income class. Ratings were highest for medications and lowest for support groups, resistance training, and alternative medicine. CONCLUSION: Identification of information needs using the valid and reliable INCR-S can inform educational approaches to optimize patients' health outcomes across the globe.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".