Psychosocial determinants of adherence to oral antidiabetic medication among people with type 2 diabetes
Bibliographic record
Abstract
AIMS AND OBJECTIVES: The aim of this study was to identify the psychosocial determinants of adherence to oral antidiabetic medication, according to the Theory of Planned Behaviour (TPB). BACKGROUND: Appropriate adherence to oral antidiabetic medication contributes to long-term glycaemic control. However, glycaemic control is often poor in people with type 2 diabetes, mainly due to the poor adherence to oral antidiabetic agents. DESIGN: Prospective study with 2 waves of data collection, based on STROBE checklist was conducted. One hundred and fifty-seven adults with type 2 diabetes, in chronic use of oral antidiabetic agents, composed the sample. At baseline, self-reported measures of medication adherence (proportion and global evaluation of adherence) and of metabolic control (glycated haemoglobin) of diabetes were obtained. METHODS: The TPB main constructs (attitude, subjective norm and perceived control) and related beliefs were measured. Adherence and metabolic control measurements were obtained in a two-month follow-up (n = 157). RESULTS: Attitude and subjective norm, together, explained 30% of the variability in intention; their underlying belief-based measures (behavioural and normative beliefs) explained 28% of the variability in intention. In addition, intention predicted behaviour at follow-up. However, when added to the prediction model, past behaviour was the only explanatory factor of adherence behaviour. CONCLUSION: Adherence behaviour to oral antidiabetic medication was predicted by intention, which, in turn, was determined by attitude and subjective norm. In order to promote adherence to oral antidiabetic agents, health professionals should include motivational strategies as well as strategies targeted to attitude and subjective norm when designing interventions. RELEVANCE TO CLINICAL PRACTICE: The nonadherence to antidiabetic medication contributes to lack of control of diabetes and ensuing complications. The comprehension of the factors explaining the variability in medication adherence can inform the design of theory-based interventions aimed at promoting this behaviour.
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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 | 0.001 | 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 | 0.000 | 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".