Predictors of adherence to insulin therapy in type 2 diabetes mellitus: an application of the theory of planned behavior
Bibliographic record
Abstract
Background: Non-adherence to medication therapy in type 2 diabetes mellitus (DM2) is prevalent. Theoretical models have been used to identify the proximal determinants of behavior. Aim: To identify the direct psychosocial predictors of adherence to insulin therapy based on Theory of Planned Behavior (TPB), among outpatients with DM2. Methods: = 70), measurements of insulin adherence and A1C were again measured. Multiple linear regression, via generalized linear models and Multiple Poisson regression, with robust variance analysis were used, for quantitative and categorical outcomes, respectively. Results: One point in the Intention score led to a mean increase of 12.5% in the proportion of insulin doses, and there was a mean increase of 25% in the probability of the person taking insulin every day or practically every day. Attitude was a predictor of Intention. The moderation analysis demonstrated that higher levels of Perceived Behavioral Control weakened the effect of Attitude on Intention. Conclusions: The results showed that Intention was predictor of behavioral measure of adherence and the proportion of insulin doses. Attitude was predictor of Intention and Perceived Behavioral Control moderated the effect of Attitude and Subjective Norm on Intention. These findings highlight the importance of developing interventions that prioritize motivational strategies to enhance insulin adherence in the clinical practice. However, future studies with larger sample sizes and the inclusion of belief assessments are recommended to optimize the understanding of the psychosocial determinants of insulin adherence among outpatients with DM2.
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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 | 0.000 |
| 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) | 0.000 | 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".