Leisure and Productivity in Older Adults with Cancer: A Systematic Review
Bibliographic record
Abstract
Introduction. Self-care, leisure, and productivity are important occupational domains for older adults’ quality of life, which might be affected by cancer and its treatment. A great number of publications about older adults focus on function or self-care, so we aimed to analyse how cancer and its treatments affect leisure and productivity. Secondary objectives were to identify whether particular clinical and/or sociodemographic factors were associated with occupational disruptions and to assess the impact of rehabilitation approaches on leisure and productivity in this population. Methods. A systematic review of the 2009-2019 literature performed on Medline, Embase, and the Cochrane Central Register of Controlled Trials. Results. 1471 publications were retrieved: 48 full texts were assessed; seven of these (four cross-sectional studies, two cohort studies, and a case report) were reviewed, including data on 16668 people (12649 healthy controls, 3918 cancer survivors, and 101 ill patients). Older adults with comorbidities and a low level of activity before cancer diagnosis may be more at risk of occupational disruptions. However, studies focused more on physical activity than leisure and productivity. Two studies mentioned occupational therapy. Discussion. As cancer can become a chronic disease, it appears important to also offer occupation-centred assessments and follow-up. Conclusion. An occupation-centred approach could be developed; its effectiveness must be assessed.
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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".