Ethno-Cultural Considerations in Cardiac Patients’ Medication Adherence
Bibliographic record
Abstract
We aimed to develop an in-depth understanding about factors that influence cardiac medication adherence among South Asian, Chinese, and European White cardiac patients. Sixty-four patients were purposively sampled from an ongoing study cohort. Interviews were audio-recorded and transcribed for analyses. Physicians' culturally sensitive communication and patients' motivation to live a symptom-free and longer life enhanced adherence. European Whites were motivated to enhance personal well-being and enjoy family life. South Asians' medication adherence was influenced by the desire to fulfill the will of God and family responsibilities. The Chinese were motivated to avoid pain, illness, and death, and to obey a health care provider. The South Asians and Chinese wanted to ultimately reduce medication use. Previous positive experiences, family support, and establishing a routine also influenced medication adherence. Deterrents to adherence were essentially the reverse of the motivators/facilitators. This analysis represents an essential first step forward in developing ethno-culturally tailored interventions to optimize adherence.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".