Development of an Instrument for Measuring Self-Care Behaviors After Left Ventricular Assist Device Implantation
Bibliographic record
Abstract
BACKGROUND: Successful long-term left ventricular assist device (LVAD) therapy necessitates a high degree of self-care. We aimed to develop an instrument that measures self-care behaviors in adult patients living with an LVAD. METHODS: We used the method to develop patient-reported outcomes recommended by the US Food and Drug Administration. Prior to developing the instrument, a literature review was conducted to generate items using the middle-range theory of self-care of chronic illness as a guiding framework. A 2-round Delphi method, involving 17 clinicians with expertise in heart failure and assist devices from the Netherlands, Israel, United States, Canada, and Japan, was used to generate and select items. In the first Delphi survey, the levels of importance, relevance, and clarity of items in the instrument were evaluated. The second Delphi survey was performed to gain consensus on the final selection of items. We also examined face validity. RESULTS: A preliminary 37-item version of the Self-Care Behavior Scale was produced. The first panel judged 33 items as important and relevant, taking out 4 items due to vague wording and duplication and adding in 4 items. In the final 33-item version, 19 items address self-care maintenance behaviors, 10 items address self-care monitoring behaviors, and 4 items address self-care management behaviors. Patients (N = 25) did not have any difficulties understanding items and report any missing items. CONCLUSION: The 33-item Self-Care Behavior Scale for patients with heart failure having an LVAD has been developed and is ready for further psychometric testing.
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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 | 0.000 | 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".