Assessing balance and functional movement among adults participating in a movement program in an Indigenous community: An observational study
Bibliographic record
Abstract
Spine pain and chronic disease disproportionately affect rural populations, women, older adults, and those who experience socioeconomic challenges. This trend is similarly seen in rural Indigenous communities. Movement is a non-pharmacological way to prevent and manage pain. Environmental barriers to physical activity in Indigenous communities include a lack of safe walking/bicycle paths, facilities, and programs. Other barriers may include individual physical function limitations. Assessment of balance and physical function is further complicated in rural regions by the limited availability of professionals to conduct assessments. This study aimed to assess the feasibility of using self-report and observational assessments of balance and physical function in adult participants in a movement program in a Manitoba First Nations community. Self-report measures included the Activities-specific Balance Confidence Scale© (ABC) and PROMIS ® (physical function). Observational measures were assessed offline using video for the four-stage balance test and 30-second chair stand. All measures were administered in-person. Nine adults (ages 21-65) were assessed. Similar patterns were demonstrated between the ABC (34-92; 66% high function) and the PROMIS (29-62; 55% normal range) with a range of scores. Observed assessment scores were more consistent, with all 30-second chair stand scores falling below the average range for physical function, and static four-stage balance performance on the one-foot balance task for 77% of participants was less than 10 seconds (3-8s range). Both types of measurement were feasible. Self-report measures combined with focused observational measures may capture a more comprehensive understanding of individual balance performance and physical function.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".