Evaluation of patient education in spinal cord injury rehabilitation: Knowledge, problem-solving and perceived importance
Bibliographic record
Abstract
PURPOSE: Through inpatient education programmes the person with spinal cord injury (SCI) learns to understand and monitor his or her own physical, emotional and social well-being. The purpose of this study was to determine the patients' knowledge and problem-solving skills regarding SCI at admission, discharge and follow-up at 6 months after discharge; and to determine the perceived importance of each content topic included in the education programme. METHODS: A one-group repeated measures design was used to evaluate the outcomes. Knowledge was evaluated with a Multiple Choice Questionnaire (MCQ). Problem-solving ability based on participants' responses to Life Situation Scenarios relevant to each topic area was rated on a standardized four-point criterion reference scale. Perceived importance for each topic area was rated on a five-point Likert scale. RESULTS: Twenty-three participants completed all assessments. There was significant improvement in MCQ scores from admission to discharge (P = 0.04) and admission to follow-up (P = 0.02). For problem-solving ability, there was a trend toward improvement in all content topics with significant improvement from admission to follow-up for the topic of bowel care (P = 0.004). However, many participants continued to demonstrate poor problem-solving ability. Bowel, Bladder and Skin Care were consistently perceived as the most important education topics. CONCLUSIONS: Improvements in knowledge do not necessarily translate to improvements in problem-solving ability even for the topics perceived as important. This may indicate the need to incorporate more active learning strategies or contextually based strategies within patient education programmes to facilitate the transfer of knowledge within life situations.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".