<p>Development of a Culturally Tailored Motivational Interviewing-Based Intervention to Improve Medication Adherence in South Asian Patients</p>
Bibliographic record
Abstract
BACKGROUND: South Asians (SAs) are among the fastest growing ethnic population in Western countries and have a higher risk of cardiovascular diseases relative to the general population. SAs living in Canada also have poorer adherence to medical regimens for treating cardiovascular disease, relative to other ethnic groups. Motivational interviewing (MI) maybe effective in improving health-related behaviour change in patients; however, the research is nascent on the effectiveness of MI in SAs and may also require cultural adaptation. AIM: To develop a culturally tailored MI-based intervention to improve medication adherence in hypertensive SA patients living in Canada. METHODS: Previous literature about medication adherence in SAs was reviewed, along with transcripts and responses to open-ended survey questions from our previous studies with SAs, to draft an MI intervention manual. The manual received extensive feedback from the study team, SA community members and health-care providers who work with SA patients. The feedback was used to refine the manual and make it culturally tailored and relevant to SA hypertensive patients living in Canada. RESULTS: A culturally tailored MI-based manual which we called a "motivational communication manual" was developed to support a study focused on improving medication adherence in SA hypertensive patients. The development process, components (eg, being culturally sensitive, family involvement, providing education about medications, reminders, etc.) and cultural nuances included in the manual are described in this paper. CONCLUSION: This is the first culturally tailored MI-based intervention manual that has been developed with the aim of improving medication adherence in hypertensive SA patients and that includes direct feedback from SA community members. Use of this manual may improve the accessibility and adoption of MI-based practices in improving health behaviours in SAs living in Canada as well as encourage further research studies and clinical trials with SA patients.
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 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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".