Patients’ beliefs about adherence to oral antidiabetic treatment: a qualitative study
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to elicit patients' beliefs about taking their oral antidiabetic drugs (OADs) as prescribed to inform the development of sound adherence-enhancing interventions. METHODS: A qualitative study was performed. Adults with type 2 diabetes who had been taking an OAD for >3 months were solicited to participate in one of six focus groups. Discussions were facilitated using a structured guide designed to gather beliefs related to important constructs of the theory of planned behavior. Four coders using this theory as the theoretical framework analyzed the videotaped discussions. RESULTS: Forty-five adults participated. The most frequently mentioned advantages for OAD-taking as prescribed were to avoid long-term complications and to control glycemia. Family members were perceived as positively influential. Carrying the OAD at all times, having the OAD in sight, and having a routine were important facilitating factors. Being away from home, not accepting the disease, and not having confidence in the physician's prescription were major barriers to OAD-taking. CONCLUSION: This study elicited several beliefs regarding OAD-taking behavior. Awareness of these beliefs may help clinicians adjust their interventions in view of their patients' beliefs. Moreover, this knowledge is crucial to the planning, development, and evaluation of interventions that aim to improve medication 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 | 0.013 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".