Barriers to Education and Shared Decision Making in the Chronic Kidney Disease Population: A Narrative Review
Bibliographic record
Abstract
PURPOSE OF REVIEW: Provision of education to inform decision making for renal replacement therapy (RRT) is a key component in the management of chronic kidney disease (CKD), yet patients report suboptimal satisfaction with the process of selecting a dialysis modality. Our purpose is to review the influencers of RRT decision making in the CKD population, which will better inform the process of shared decision making between clinicians and patients. SOURCES OF INFORMATION: PubMed and Google Scholar. METHODS: A narrative review was performed using the main terms "chronic kidney disease," "CKD," "dialysis," "review," "decision-making," "decision aids," "education," and "barriers." Only articles in English were accessed. The existing literature was critically analyzed from a theoretical and contextual perspective and thematic analysis was performed. KEY FINDINGS: Eight common themes were identified as influencers for decision making. "Patient-focused" themes including social influence, values and beliefs, comprehension, autonomy and sociodemographics, and "clinician-focused" themes including screening, communication, and engagement. Early predialysis education and decision aids can effectively improve decision making. Patient-valued outcomes need to be more fully integrated into clinical guidelines. LIMITATIONS: This is not a systematic review; therefore, no formal tool was utilized to evaluate the rigor and quality of studies included and findings may not be generalizable. IMPLICATIONS: Standardized comprehensive RRT education programs through multidisciplinary health teams can help optimize CKD patient education and shared decision making. Involving patients in the research process itself and implementing patient values and preferences into clinical guidelines can help to achieve a patient-centered model of care.
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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 | 0.012 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".