A concern for falling impacts quality of life for people with a lower limb amputation
Bibliographic record
Abstract
The purpose of this web-based survey study was to comprehensively evaluate subdomains of concern for falling and its association with quality of life (QoL) among people with lower-limb amputations (PLLA). Forty-eight adults (mean 61.8 ± 11.6 years) with a major (i.e. transtibial or transfemoral) amputation participated. Individuals were currently using a prosthesis for ambulation, completed a prosthetic rehabilitation program, had functional use of English and had access to an internet-connected device (e.g. laptop). Five standardized scales assessed a concern for falling: Modified Survey of Activities and Fear of Falling in the Elderly (mSAFFE), Activities-specific Balance Confidence (ABC) Scale, Prosthetic Limb Users Survey - Mobility (PLUS-M), Consequences of Falling Scale and Perceived Ability to Manage Falls Scale. QoL was evaluated using the WHO QoL-100 questionnaire. Spearman correlation analysis evaluated the relationship between the five concerns for falling scales. Five independent linear regression modeling evaluated the association of each concern for falling measure on QoL. Strong statistically significant correlations were found between mSAFFE and PLUS-M (r s = -0.87; P < 0.05). Three scales were significantly associated with QoL: mSAFFE [-1.16 (95% CI, -2.04 to -0.29)], ABC [0.36 (95% CI, 0.11-0.61)] and PLUS-M [0.50 (95% CI, 0.05-0.95)]. This is the first study to evaluate multiple concerns for falling subdomains among PLLA. Concern for falling should be addressed in prosthetic rehabilitation to improve community re-integration and QoL.
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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 | 0.004 |
| 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 | 0.001 |
| 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".