Older people’s perceptions and experiences of older people with the Sit-to-stand activity: An ethnographic pre-feasibility study
Bibliographic record
Abstract
OBJECTIVE: the purpose of this pre-feasibility study was to examine perceptions and experiences of a Sit-to-stand activity with urban Brazilian community-dwelling older people in their homes. METHOD: the exploration method was focused ethnography. Purposive sampling was used to recruit 20 older people. Five means of data generation were used, namely: socio-demographic surveys, participant observations, informal interviews, formal semi-structured interviews, and field notes. Data analysis was qualitative content analysis. RESULTS: the experience of mobility-challenged older people with the Sit-to-stand activity was dependent on their mobility expectations involving many factors that worked together to influence their beliefs and attitudes towards the activity, preferences, behaviors, and cultural perceptions. The participants of this study seemed to find the activity enjoyable; however, the most noticeable shortcomings for their engagement in the Sit-to-stand activity emerged as gaps in their personal and intrapersonal needs. CONCLUSION: the recommendations generated from the study findings call for the design of implementation strategies for the Sit-to-stand intervention that are tailored to this particular population's needs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".