A Systematic Review of the Qualitative Research on Barriers and Facilitators to Home Hemodialysis
Bibliographic record
Abstract
INTRODUCTION: The growing prevalence of chronic kidney disease has led to an increased demand for kidney replacement therapies. Although a kidney transplant is the preferred treatment for patients, many patients require dialysis temporarily before receiving a transplant or are unsuitable transplant candidates requiring long-term dialysis. Home hemodialysis (home HD) is cost-effective and associated with improved patient outcomes; however, its adoption remains low. There is a need to understand the factors that may support or hinder the use of home HD. Accordingly, a systematic review of the qualitative literature was conducted to identify barriers and facilitators to home HD for patients, their carers/family, and healthcare professionals. METHODS: This systematic review was carried out following ENTREQ guidelines. Electronic searches were conducted on Medline (OVID), EMBASE, CINAHL (EBSCO), and PsycINFO. The COM-B and Theoretical Domains Framework (TDF) were used to collate the barriers and enablers identified within the papers through deductive content analysis. RESULTS: Thirteen studies met the inclusion criteria. Within the capability component of the COM-B model, lack of knowledge of home HD was identified as a barrier by healthcare professionals and patients. Within the opportunity component, the suitability of patients' homes (e.g., home modifications) and the healthcare system was identified as barriers to home HD. Fostering an environment of support and community was seen as a facilitator of home HD. Within the motivation component of the model, a lack of confidence and reluctance of patients to burden their family members with the responsibility of treatment were perceived as barriers. Improvements in the quality of life for the person receiving home HD were regarded as a motivator. CONCLUSION: To encourage widespread home HD use, understanding its barriers and facilitators for patients and the healthcare system is key to developing and implementing effective interventions to increase uptake.
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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 | 0.052 | 0.111 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.013 | 0.018 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".