A Nurse-Led Self-Management Support Intervention (ZENN) for Kidney Transplant Recipients Using Intervention Mapping: Protocol for a Mixed-Methods Feasibility Study
Bibliographic record
Abstract
BACKGROUND: Optimal self-management in kidney transplant recipients is essential for patient and graft survival, reducing comorbidity and health care costs while improving the quality of life. However, there are few effective interventions aimed at providing self-management support after kidney transplantation. OBJECTIVE: This study aims to systematically develop a nurse-led, self-management (support) intervention for kidney transplant recipients. METHODS: The Intervention Mapping protocol was used to develop an intervention that incorporates kidney transplant recipients' and nurses' needs, and theories as well as evidence-based methods. The needs of recipients and nurses were assessed by reviewing the literature, conducting focus groups, individual interviews, and observations (step 1). Based on the needs assessment, Self-Regulation Theory, and the "5A's" model, change objectives were formulated (step 2). Evidence-based methods to achieve these objectives were selected and subsequently translated into practical implementation strategies (step 3). Then, program materials and protocols were developed accordingly (step 4). The implementation to test the feasibility and acceptability was scheduled for 2015-2017 (step 5). The last step of Intervention Mapping, evaluation of the intervention, falls outside the scope of this paper (step 6). RESULTS: The intervention was developed to optimize self-management (support) after kidney transplantation and targeted both kidney transplant recipients and nurse practitioners who delivered the intervention. The intervention was clustered into four 15-minute sessions that were combined with regular appointments at the outpatient clinic. Nurses received a training syllabus and were trained in communication techniques based on the principles of Solution-Focused Brief Therapy and Motivational Interviewing; this entailed guiding the patients to generate their own goals and solutions and focus on strengths and successes. Kidney transplant recipients were encouraged to assess self-management challenges using the Self-Management Web and subsequently develop specific goals, action plans, and pursuit skills to solve these challenges. CONCLUSIONS: The Intervention Mapping protocol provided a rigorous framework to systematically develop a self-management intervention in which nurses and kidney transplant recipients' needs, evidence-based methods, and theories were integrated. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/11856.
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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 | 0.012 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".