Designing and Testing a Treatment Adherence Model Based on the Roy Adaptation Model in Patients With Heart Failure: Protocol for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Adherence to treatment is an important factor to decrease repeated and costly hospitalization owing to heart failure (HF). The explanation and prediction of medication adherence and other lifestyle recommendations in chronic diseases, including HF, are complex. Theories lead to a better understanding of complex situations as well as the process of changing behavior and explain the reasons for the existence of a problem. OBJECTIVE: The aim of this study is to report a protocol for a mixed methods study setting out to investigate the empirical validity of the Roy Adaptation Model as a conceptual framework for explaining and predicting adherence to treatment in patients with HF in Iran. METHODS: This mixed methods study consists of an exploratory sequential design to be conducted in 2 phases. The first phase involves identifying the factors associated with treatment adherence in patients with HF through content analysis of the literature and elucidating the perception of participants in the context of Iranian health care where the model of adherence to treatment is designed based on the Roy Adaptation Model. The second phase addresses the interrelationships among variables in the model through a descriptive study using structural equation modeling. Finally, following the summarization and separate interpretation of the qualitative findings and quantitative results, a decision is made about the extent to and ways in which the results of the quantitative stage can be generalized or tested for the qualitative findings. RESULTS: Content analysis of the literature in part 1 of the first phase was completed in 2017. Collection and analysis of qualitative data in part 2 of the first phase will be completed soon. The results are expected to be submitted for publication in 2019. Then, the second phase-the quantitative study-will be conducted. CONCLUSIONS: The results of this study will provide valuable information about the empirical validity of the Roy Adaptation Model as a conceptual framework for explaining and predicting adherence to treatment in patients with HF, which, to date, have received little attention. The results can be used as a guide for nursing practice and care provision to patients with HF and also to design and implement effective interventions to improve treatment adherence in these patients. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13317.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".