SIT TO STAND ACTIVITY: A LITERATURE REVIEW
Bibliographic record
Abstract
It is common for older adults to have many age related problems such as muscle weakness, slowed performance, fatigue and poor endurance. Focusing on exercises to improve older adults mobility is a potential mechanism to assist their physical capability and performance of activities of daily living. Using Arksey and O’Malley framework a scoping review was conducted to: (1) to explore the breadth of literature on the current state of knowledge about the sit-to-stand activity to improve mobility in the older adult population and (2) to identify gaps for future research. Of 1639 papers, 14 studies met the inclusion criteria, with study dates ranging from 1993 to 2015. The target population of the majority of studies was post-stroke patients. A range of sit-to-stand interventions were described with duration of interventions ranging from two to 24 weeks. The frequency of the sit-to-stand activity ranged from three to seven times/week lasting 15 to 45 minutes on each occasion. Also, the activity was prompted mostly by rehabilitation professionals. Three themes were identified in the studies: (1) positive impact of sit-to-stand activity on patient outcomes; (2) absence of long term follow up in study designs; and (3) gap of theoretical framework guiding the studies. Across most of the studies, participants showed significant improvements in performance of sit-to-stand and motor function, yet most studies lacked adequate methodological rigor and/or experimental design. There was an absence of explicit theoretical frameworks guiding the studies. More research is needed to assess whether the sit-to-stand could benefit groups beyond the post-stroke population.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.022 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".