Developing and Validating a Self-Care Self-Efficacy Scale for Oral Anticoagulation Therapy in Patients With Nonvalvular Atrial Fibrillation: Protocol for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Oral anticoagulation therapy (OAC) is the cornerstone treatment for preventing venous thromboembolism and stroke in patients with nonvalvular atrial fibrillation (NVAF). Despite its significance, challenges in adherence and persistence to OAC regimens have been reported, leading to severe health complications. Central to addressing these challenges is the concept of self-efficacy (SE) in medication management. Currently, there is a noticeable gap in available tools specifically designed to measure SE in OAC self-care management, while such tools are crucial for enhancing patient adherence and overall treatment outcomes. OBJECTIVE: This study aims to develop and validate a novel scale aimed to measure self-care self-efficacy (SCSE) in patients with NVAF under OAC, which is the patients' Self-Care Self-Efficacy Index in Oral Anticoagulation Therapy Management (SCSE-OAC), for English- and Italian-speaking populations. We also seek to assess patients' SE in managing their OAC treatment effectively and to explore the relationship between SE levels and sociodemographic and clinical variables. METHODS: Using a multiphase, mixed methods observational study design, we first conceptualize the SCSE-OAC through literature reviews, patient focus groups, and expert consensus. The scale's content validity will be evaluated through patient and expert reviews, while its construct validity is assessed using exploratory and confirmatory factor analyses, ensuring cross-cultural applicability. Criterion validity will be examined through correlations with clinical outcomes. Reliability will be tested via internal consistency and test-retest reliability measures. The study will involve adult outpatients with NVAF on OAC treatment for a minimum of 3 months, using both e-surveys and paper forms for data collection. RESULTS: It is anticipated that the SCSE-OAC will emerge as a reliable and valid tool for measuring SE in OAC self-care management. It will enable identifying patients at risk of poor adherence due to low SE, facilitating targeted educational interventions. The scale's validation in both English and Italian-speaking populations will underscore its applicability in diverse clinical settings, contributing significantly to personalized patient-centered care in anticoagulation management. CONCLUSIONS: The development and validation of the SCSE-OAC represent a significant advancement in the field of anticoagulation therapy. Validating the index in English- and Italian-speaking populations will enable personalized patient-centered educational interventions, ultimately improving OAC treatment outcomes. The SCSE-OAC's focus on SCSE introduces a novel approach to identifying and addressing individual patient needs, promoting adherence, and ultimately improving health outcomes. Future endeavors will seek to extend the validation of the SCSE-OAC across diverse cultural and linguistic landscapes, broadening its applicability in global clinical and research settings. This scale-up effort is crucial for establishing a universal standard for measuring SCSE in OAC management, empowering clinicians and researchers worldwide to tailor effective and culturally sensitive interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT05820854; https://tinyurl.com/2mmypey7. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/51489.
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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 | 0.067 | 0.055 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.031 | 0.007 |
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".