The Needs and Barriers of Medication-Taking Self-Efficacy Among Poststroke Patients: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Stroke is one of the top 10 leading diseases worldwide, with high mortality and morbidity rates. There is an incomplete understanding of the various types of self-efficacy involved in the prevention of recurrent stroke, and one of them is medication-taking self-efficacy. OBJECTIVE: This study aimed to explore the fundamental needs and barriers of medication-taking self-efficacy in poststroke patients in Malaysia. METHODS: We performed in-depth individual interviews with poststroke patients (N=10) from the Outpatient Neurology Clinic, Hospital Kuala Lumpur. All interviews were transcribed verbatim, and an inductive thematic analysis was performed on the data collected from the interviews. RESULTS: Two key themes were identified: (1) self-efficacy in taking the effort to understand stroke and its preventative treatment for recurrent stroke and (2) self-efficacy in taking prescribed medication to prevent stroke. Patients needed to be proactive in seeking reliable information about stroke and the perceived benefits of preventative treatment for stroke. The discussion was focused on eliciting the needs and barriers related to medication-taking self-efficacy. Patients needed to develop independence and self-reliance to overcome barriers such as dependency and low motivation. External factors such as limited information resources, low perceived severity, poor social environment, and poor communication add to the challenges of poststroke patients to improve their self-efficacy of managing their medications. CONCLUSIONS: The study identified potential key findings related to the needs of patients in a localized setting, which are also related to several health behavioral concepts and constructs, indicating the importance of overcoming barriers to improve the quality of life in poststroke patients. We anticipate that the results will be taken into consideration for future personalized patient education interventions.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".