Patients' experiences with learning a complex medical device for the self-administration of nocturnal home hemodialysis.
Bibliographic record
Abstract
UNLABELLED: The purpose of this study was to explore patient training experiences related to the self-administration of hemodialysis at home. Researchers used a qualitative study using semi-structured interviews and a focus group. The setting was a hospital-based patient education program in Toronto, Ontario, Canada. Qualitative interviews and focus group study were conducted with 23 patients (who had end stage renal disease) and caregivers who have participated in Toronto General Hospital's Nocturnal Home Hemodialysis training program to learn how to operate a hemodialysis machine and to administer their own treatments at home without the supervision of clinicians. RESULTS: Experience as a trainee in the Nocturnal Home Hemodialysis program was framed by 5 diverse themes: patients' perceptions of anxiety, peer support, clinician empathy and understanding learning while ill, and the compatibility of learning preferences with training practices employed. CONCLUSIONS: The study revealed the complexity of the patients' experience with being prepared for a self-treatment regime at home. Although it was anticipated that the most important barrier to patient preparation would be the challenges of managing complex medical technology, psychosocial dimensions of their experiences were the primary factors impacting on the patients' ability to learn and to take on self-care responsibility. If the trend of patient self-treatment at home continues to increase, it is important for clinician educators to be attentive to self-treatment as a socially situated activity.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".