Clinicians and individuals with acquired brain injury perspectives about factors that influence mobility: creating a core set of mobility domains among individuals with acquired brain injury
Bibliographic record
Abstract
OBJECTIVES: To identify factors which may influence mobility and could be considered during the evaluation of mobility in individuals with acquired brain injury (ABI) following qualitative focus groups with both clinicians and individuals with ABI, to assess their needs and preferences in order to individualize their care management plans. METHODS: = 5). Focus group discussions were transcribed and analyzed using inductive and deductive thematic content approaches. RESULTS: Four themes were identified: considering mobility holistically and individual needs, preferences, and unique experiences; assessment and intervention guidelines; support network; and uncertainty about symptoms and recovery. Using the ten-rule International Classification, Functioning, Disability, and Health framework linking process, codes were categorized into Body Functions Activity and Participation, and Environmental Factors exploring the prominent domains that mostly identify factors influencing mobility. CONCLUSIONS: Comprehensive measurement of mobility remains an ongoing challenge owing to multiple contributing factors, ranging from personal and psychosocial factors to the influence of a myriad of environmental and community considerations. Preparing individuals with ABI for community mobility can be substantially improved if healthcare professionals employ communicative tools to facilitate shared decision making with patients and to deliver patient-centred rehabilitation care.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.006 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".