Working after cancer: Psychological Flexibility and the quality of working life
Bibliographic record
Abstract
Abstract Purpose: Our purpose was to examine associations between the pillars of psychological flexibility (Valued Action, Behavioural Awareness, Openness to Experience) and aspects of quality of working life after a cancer. We examined how the pillars of psychological flexibility mediated relationships between quality of working life and anxiety, depression, and overall life satisfaction. Examining psychological flexibility allows interventions to be targeted for cancer survivors and account for unique, individual needs. Methods In this cross-sectional study, 230 cancer survivors who were currently employed completed a questionnaire package that included demographic information and measures of Physical Health Problems, Satisfaction with Life, Quality of Working Life in Cancer Survivors, Psychological Flexibility, Anxiety, and Depression. Results The mediational analyses illustrated how specific pillars of psychological flexibility mediated the relationships between quality of working life and anxiety, depression, and overall satisfaction with life. Overall, psychological flexibility mediated the relationships between physical health and health-related work problems, quality of working life, and satisfaction with life. Further, the Valued Action pillar of psychological flexibility fully mediated the relationship between Quality of Working Life and reported symptoms of depression and anxiety. Conclusions:Higher psychological flexibility was related to higher satisfaction with working life. Physical and psychological challenges during employment may be improved through interventions that improve psychological flexibility. Actively engagement with activities aligned with personal values is related to more positive outcomes. Implications for Cancer Survivors: The value of examining the pillars of psychological flexibility is that interventions can be targeted for this population, considering this population's unique 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".