Exploring Information Needs and Educational Preferences of Individuals Referred to Cardiac Rehabilitation Before Program Start
Bibliographic record
Abstract
PURPOSE: To explore information needs and educational preferences of individuals referred to cardiac rehabilitation (CR) before program start. METHODS: This cross-sectional study was conducted from June 2023 to February 2024. Referred patients were contacted via email, which included a link to a website providing information about the CR program, and instructional videos. Data were collected through surveys that assessed health literacy levels, information needs (using the short version of the Information Needs in CR), frequently asked questions, delivery preferences, and engagement/satisfaction with educational resources. RESULTS: Throughout the study period, the CR center received 2571 referrals, of which 881 individuals were eligible for the study, and 467 (mean age 66.4 ± 12.2 years; 36% women) consented and completed questionnaires. Information needs were highest for CR and diagnosis/treatment and lowest for nutrition and risk factors. The study revealed significant differences in the perceived importance of information needs across various sociodemographic and clinical characteristics, including age ( P = .01), educational level ( P = .009), work status ( P = .04), main reason for CR referral ( P < .001), and health literacy ( P = .02). Moreover, participants identified key areas of interest and concern related to their CR journey. These included inquiries about safe exercise initiation, pre-stress test instructions, and personalized exercise plans, among others. It was also observed that the majority of participants engaged with the educational materials provided and indicated high levels of satisfaction. CONCLUSION: This study revealed patient preferences regarding educational content, delivery format, and areas of interest/concern related to CR prior to program start, providing valuable insights for improving the delivery and effectiveness of such programs.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".