<p>Accountability in patient adherence</p>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The accountability inherent in the social interaction between a patient and healthcare provider affects patients' motivation to adhere to treatment. To characterize the role of accountability as a tool to improve self-efficacy and self-management and thereby promote patients' adherence to treatment, a measure of accountability is needed. AIMS: To develop and test the validity, reliability, and sensitivity of a new outcome measure designed to assess accountability. METHODS: The accountability measurement tool was developed from the literature, expert consultation, and focus groups. A focus group and three pilot studies were performed both in clinic and through an online crowdsourcing platform. Principal Component Analysis evaluated constructs, and Cronbach's alpha measured internal consistency. Validity was established using convergent and divergent correlations to other validated scales. RESULTS: A total of 292 participants took part in this study. The 12-item accountability scale demonstrated very good internal consistency (Cronbach's α=0.92). Components of the accountability measurement tool correlated with predicted validated measures, including the Treatment Self-Regulation Questionnaire. Divergent validity was established with no significant difference noted between age, sex, race, and education level. CONCLUSION: Future use of this questionnaire will allow for the assessment of the interaction between accountability and adherence to treatment and lead to the development of new interventions to promote better adherence.
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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) | 0.001 | 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) | 0.005 | 0.003 |
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 it