Working with cancer: a pilot study of work participation amongst cancer survivors in Western Sydney.
Bibliographic record
Abstract
Background: Around forty percent of cancer diagnoses occur in working-age adults. Improvements in screening and treatment means that most are expected to live years beyond their diagnosis. However, many experience persistent impairments from treatment such as fatigue, cognitive difficulties and emotional distress. Work is a key occupation for this population yet little is understood about working with cancer in the Australian context. Aim: This pilot study aims to investigate work participation amongst cancer survivors in Western Sydney and identify factors associated with returning to work. Methods: A cross-sectional online survey was developed to measure work participation and factors associated with work. Study participants aged 20-65 years, employed at diagnosis, with basic English and computer literacy were recruited from a cancer clinic in Western Sydney over a three-month period. Results: Nineteen survey responses were received and analysed. Participants had returned or remained at work (n=9, 47.4%), unsuccessfully attempted to return to work (RTW) (n=2, 10.5%), or were on leave from work (n=8, 42.1%). Of those on leave most did not plan to RTW (n=6, 31.6%). Fatigue (n=15, 78.9%), difficulty concentrating (n=8, 42.1%), memory issues (n=8, 42.1%), stomach upset (n=7, 36.8%), sleep disturbance, (n=7, 36.8%), and psychological distress (n=7, 36.8%) impacted perceived work ability. Physically demanding work (n=8, 42.1%), length of workday (n=6, 31.6%), productivity demands (n=5, 26.3%) and commuting (n=4, 21.1%) were challenging to manage after cancer. Approximately a quarter of participants reported discussing RTW with people other than their employer (n=5, 26.3%). A supportive workplace was a facilitator for work, whereas a non-supportive workplace was considered a major barrier. Overall participants reported positive attitudes towards work. Conclusion: Cancer survivors in Western Sydney may face challenges engaging in work after treatment. Work participation may be influenced by side effects of treatment, difficulty performing work demands and the work environment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".