Predictors of Psychological Distress and Confidence Negotiating Physical and Social Environments Among Mobility Device Users
Bibliographic record
Abstract
OBJECTIVE: We conducted an intersectional analysis to explore how demographic characteristics and mobility device use were associated with psychological distress (depression and anxiety) and confidence negotiating physical and social environments. DESIGN: Cross-sectional data were collected using the Hospital Anxiety and Depression Scale, modified Wheelchair Use Confidence Scale, and self-reported functional independence scale. PARTICIPANTS: The sample included 105 participants. Primary mobility devices used included mobility scooters (27%), power wheelchairs (26%), manual wheelchairs (25%), walkers (11%), and cane or crutch (12%). The mean age of participants was 58 yrs, 53% were female, and 52% lived alone and were functionally independent with the use of assistive technology. RESULTS: We were able to explain between 39% and 65% of the variance (adjusted R2) in the dependent variables with parsimonious regression models. Age was an independent predictor of all outcomes. Women were less confident negotiating the physical environment, and walker use was associated with depression and lower confidence negotiating physical environments, but increased confidence negotiating social environments. CONCLUSIONS: Age is associated with psychosocial outcomes for assistive device users, and those who use walkers may experience increased challenges with depression and negotiating the physical environment. Pending confirmatory research, the findings may have important implications for targeted interventions related to device provision.
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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 | 0.005 |
| 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) | 0.002 | 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".