Predictors of time to complete toileting for children with spina bifida
Bibliographic record
Abstract
BACKGROUND/AIM: Previous research has shown that children with spina bifida use clean intermittent catheterisation for urination, a rather complex procedure that increases the time taken to completion. However, no studies have analysed the factors impacting on the time taken to complete the urination that could inform occupational therapy practice. Therefore, the aim was to identify the variables that predict extended time children with spina bifida take to complete urination. METHODS: Fifty children, aged 5-18 years old with spina bifida using clean intermittent catheterisation, were observed while toileting and responding to a set of assessments tools, among them the Canadian Occupational Performance Measure. A logistic regression was used to identify which variables were independently associated with an extended toileting time. RESULTS: Children with spina bifida do take long time to urinate. More than half of this study's participants required more than five minutes completing urination, but not all required extended times. Ambulant, independent girls were more likely to perform toileting in less than six minutes compared with other children with spina bifida. However, age, IQ, maintained focus on the task, Canadian Occupational Performance Measure, time processing abilities and self-reported ratings of independence appeared to be of no relevance, to predict extended toileting times. CONCLUSION: To minimise occupational disruption caused by extended toileting times, occupational therapists should utilise the relevant predictors: gender, independence and ambulation when they prioritise children for relevant interventions.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".