Quality of life following non-dysvascular lower limb amputation is contextualized through occupations: a qualitative study
Bibliographic record
Abstract
PURPOSE: To understand how persons with non-dysvascular lower limb amputation (LLA) use occupations to contextualize their quality of life (QoL). METHODS: A qualitative study using an interpretative description approach was conducted. Analysis of the interviews was guided by an occupational perspective, which considers the day-to-day activities that are important to an individual. RESULTS: Twenty adults with an adult-acquired non-dysvascular amputation (e.g., trauma, cancer or infection) were interviewed. Following thematic analysis, two main themes were developed: (1) sense of self expressed through occupations; and (2) sense of belonging with others influenced by occupations. Participants expressed the way they felt about themselves through their activities and placed high value on whether they could participate in certain occupations. Participants also described how their sense of belonging was changed through the context of their changing occupations. CONCLUSION: The findings from this work can be leveraged by clinicians and researchers alike to improve care for this population. Rehabilitation programs should consider interventions and programming that help to restore occupations or develop new ones given the importance placed on occupations by persons with non-dysvascular LLA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".