Gender Differences in Health Information Needs and Decisional Preferences in Patients Recovering From an Acute Ischemic Coronary Event
Bibliographic record
Abstract
OBJECTIVE: This study examined gender differences in health information needs and decisional preferences after an acute ischemic coronary event (ICE). METHODS: Patients with ICE, recruited in 12 coronary intensive care units, completed a questionnaire on demographic, disease-related, and psychosocial topics. Six and 12 months later, they completed mailed follow-up questionnaires. RESULTS: Nine hundred six patients completed the baseline questionnaire, 541 (69%) completed the 6-month questionnaire, and 522 (64%) completed the 12-month questionnaire after hospital discharge. Men reported significantly more information received and greater satisfaction with healthcare practitioners meeting their information needs. Women wanted more information than men concerning angina and hypertension. Men wanted more information about sexual function and reported receiving more information about the role of each doctor, test results, treatments, cardiac rehabilitation, and how their families could support their lifestyle changes. Patients who reported receiving more information reported less depressive symptomatology and greater self-efficacy, healthcare satisfaction, and preventive health behaviors. Although most patients of both sexes preferred a shared decision-making role with their physician, the majority felt their doctor had made the main decisions. CONCLUSIONS: Patients after ICE, especially women, reported receiving much less information than they wanted from all health professionals. Most patients wanted a shared or autonomous treatment decision-making role with their doctor, but only a minority experienced this. Clinicians must do better, because meeting patients' information needs and respecting their decisional preferences are shown to be associated with better self-efficacy, satisfaction, and health-promoting behavior.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".