The effect of dual‐task testing on the balance and gait of people with lower limb amputations: A systematic review
Bibliographic record
Abstract
OBJECTIVE: To systematically review the literature on the effect of dual-task testing on the balance and gait of people with lower limb amputations (PLLA). LITERATURE SURVEY: Databases MEDLINE, EMBASE, CINAHL, PsycINFO, Web of Science, and Scopus were searched in duplicate (inception to December 1, 2020). METHODOLOGY: Inclusion criteria: participants were adults with transtibial, knee-disarticulation, transfemoral, or bilateral lower limb amputations; balance or gait was paired with a secondary task; and studies were peer-reviewed and published in English. Two authors independently reviewed articles and consensus was required. A standardized data extraction sheet was used to gather study relevant information in duplicate. Methodological quality of reporting was examined using the Downs and Black Scale. A meta-analysis was unable to be performed owing to substantial participant and protocol heterogeneity among the studies included. SYNTHESIS: Of 3950 articles screened, 22 met inclusion criteria. Four assessed dual-task balance and 18 dual-task gait. During single-task standing, PLLA demonstrated higher sway distance and sway velocity than controls (CN); however, a greater dual-task effect was observed only for sway velocity. Gait pace, rhythm, variability, asymmetry, and postural control were observed to be worse in PLLA relative to CN during single-task. Dual-task gait testing resulted in a disproportionally reduced pace and rhythm and increased asymmetry in PLLA compared to CN. CONCLUSIONS: People with lower limb amputations have impaired balance and gait, which is affected by dual-task to a greater degree compared to healthy adults. An examination of how PLLA-specific factors such as level of amputation, reason for amputation, and experience with a prosthesis affect dual-task performance has not yet been thoroughly explored. Future research should continue to characterize the cognitive-mobility link to better understand the challenges associated with the use of a prosthesis.
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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 | 0.006 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".