Prioritizing mobility factors for assessment during the transition of older adults from hospital to home: a cross-sectional survey of physiotherapists in Southeastern Nigeria
Bibliographic record
Abstract
BACKGROUND: Assessing all factors influencing older adults' mobility during the hospital-to-home transition is not feasible given the complex and time-sensitive nature of hospital discharge processes. OBJECTIVE: To describe the mobility factors that Nigerian physiotherapists prioritize to be assessed during hospital-to-home transition of older adults and explore the differences in the prioritization of mobility factors across the physiotherapists' demographics and practice variables. METHODS: This cross-sectional study included 121 physiotherapists who completed an online questionnaire, ranking 74 mobility factors using a nine-point Likert scale. A factor was prioritized if ≥ 70% of physiotherapists rated the factor as "Critical" (scores ≥7) and ≤ 15% of physiotherapists rated a factor as "Not Important" (scores ≤3). We assessed the differences in the prioritization of mobility factors across the physiotherapists' demographics/practice variables using Mann Whitney U and Kruskal-Wallis tests. FINDINGS: Forty-three of 74 factors were prioritized: four cognitive, two environmental, one financial, four personal, eighteen physical, seven psychological, and seven social factors. Males and those with self-reported expertise in each mobility determinants more frequently rated factors as critical. CONCLUSION: Prioritizing many mobility factors underscores the complex nature of mobility, suggesting that an interdisciplinary approach to addressing these factors may enhance post-hospital discharge mobility outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".