Medication adherence among community dwelling elderly in Selangor / Saliza Ibrahim
Bibliographic record
Abstract
Background: Medication adherence is an important factor that influences the therapeutic outcomes. An elderly will generally receive more prescriptions than the other age groups in the population. Due to cognitive impairment in elderly, as well as multiple and complex medication regimens, this leads to the risk of medication nonadherence. Accordingly, this study aimed to determine medication adherence among multi-ethnic community-dwelling elderly in Selangor. Barriers and belief towards medication as well as awareness towards the use of medicine were also assessed. Besides that, this study evaluated the correlation between medication adherence and cognitive functions of the community-dwelling elderly people in Malaysia. The predictors of non-adherence were also determined in this study. Materials and Methods: A cross-sectional study, involving the elderly prescribed with medicines, was conducted in Selangor from September to December 2016. A 71-item validated questionnaire, including eight items Morisky Medication Adherence Scale (MMAS-8), belief about medicine (BaMQ), Ministry Mental Examination State (MMSE) and Montreal Cognitive Assessment (MoCA), was employed. Results: One hundred and fifty elderly with a median age of 70 were recruited in this study. Thirty-two percent (n=48) of the respondents received at least five prescribed medications. About 58.7% (n=88) of the elderly reported with low adherence level with a mean score of 4.37 ± 1.46. More than three quarter (80%, n=121) of the elderly had a problem to differentiate between active ingredient and brand name of a medication. Mean necessity score was significantly higher than mean concern score (p < 0.001). The medication adherence score was negatively correlated (r=-0.220) with the concerns score (p=0.007). Age (r=0.289, p<0.001) also found to had positive but poor correlation between medication adherence. There was no significant correlation between medication adherence and cognitive functions either using Mini Mental State Examination (MMSE) score or Montreal Cognitive Assessment (MoCA) score. Concern score in belief towards medication and age were identified as the predictors of medication adherence among the community-dwelling elderly in Selangor. Conclusion: Medication adherence among elderly is a complex process. It is essential to understand the determinants and barriers to medication adherence in order to optimise medication adherence and provide education if necessary.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".