Long-Term Knowledge Retention following Predialysis Psychoeducational Intervention
Bibliographic record
Abstract
BACKGROUND/AIMS: Early identification and predialysis psychoeducation are gaining acceptance. Although research supports the immediate value of predialysis interventions, long-term benefits remain unknown. We examined long-term knowledge retention following a psychoeducational intervention. METHODS: 47 progressive renal failure patients completed the Kidney Disease Questionnaire at baseline and 18, 30, 42, and 54 months after initiating renal replacement therapy (RRT; the 'longitudinal' sample). A larger cohort provided data at one or more of these points (n = 132, 117, 101, and 70 at 18, 30, 42, and 54 months, respectively; the 'cross-sectional' sample). RESULTS: Initial knowledge gains among psychoeducation recipients were followed by a significant knowledge advantage for three groups throughout follow-up. Patients who received predialysis psychoeducation either before or after starting dialysis demonstrated superior Kidney Disease Questionnaire scores as compared with those identified before the initiation of RRT who received the usual standard of practice. Patients identified after the initiation of RRT and who received standard education, however, demonstrated the same level of knowledge retention as produced by psychoeducation. The results were identical across the longitudinal and cross-sectional samples. CONCLUSIONS: Patient education produces important benefits in end-stage renal disease, but the incremental value of early intervention remains to be demonstrated.
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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 | 0.002 | 0.009 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".