The clinical experiences of Nigerian physiotherapists in managing environmental and socioeconomic determinants of mobility for older adults
Bibliographic record
Abstract
Study Aim: To describe how physiotherapists in northern Nigeria managed the environmental and socioeconomic determinants of mobility for older adults.Methods: We adopted a qualitative description approach, purposely selected and conducted telephone interviews with 20 physiotherapists from Abuja [the Federal Capital Territory], four of the six states in North-central, and one state in the North-west regions of Nigeria. Data were analyzed using qualitative content and constant comparative analyses.Result: The physiotherapists had between 5 and 11 years practice experience in managing older adults with mobility limitations. Three iterative stages of identification, intervention, and documentation emerged as clinical experiences of Nigerian physiotherapists in managing environmental and socioeconomic determinants of mobility for older adults. Identification stages included determining older adults with mobility limitation through patients’/physiotherapists’ reports and identifying the environmental (e.g. staircase location, floor types, furniture, and the urban built environment) and socioeconomic (e.g. education, income, and occupation) factors. The clinical decision of the “best” individualized approach to intervention, providing reassurance and education during and after the intervention were sub-stages for the intervention stage. There is a potential gap in the documentation process of these stages as most of the physiotherapists (n = 15; 75%) reported not doing so.Conclusion: This study suggested three iterative stages of identification, intervention, and documentation of the environmental and socioeconomic determinants of mobility for older adults. While there was a potential gap in regard to documentation of these stages in patients' case notes, physiotherapists especially in North-central Nigeria believed that co-developing a pragmatic set of clinical questions focusing on these determinants of mobility could encourage physiotherapists to explicitly document them. As the approach used in our research is purely descriptive, a grounded theory approach would potentially provide more detailed sub-stages that could be a more effective guide for physiotherapists to use during clinical practice.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".