Abstract
Purpose: This study aimed to (1) identify distinct multidimensional fatigue profiles among employed cancer survivors, (2) examine associations between workplace factors and these profiles, and (3) assess how these profiles are associated with occupational outcomes. Methods: Seventy-two employed cancer survivors aged 27 to 64 years (median 9.4 years since diagnosis) from a local government in Japan completed questionnaires in 2023 assessing cancer-related fatigue (Cancer Fatigue Scale), workplace factors (job demands, job control, workplace support), and occupational outcomes (work engagement, presenteeism, cognitive function at work, and quality of life). Fatigue profiles were identified using hierarchical cluster analysis. Associations between workplace factors and profiles were examined using multinomial logistic regression. Occupational outcome differences among profiles were examined using linear regression. Results: Three profiles were identified: Low Global Fatigue (n = 12), Dominant Mental Fatigue (n = 36), and High Global Fatigue (n = 24). Workplace support—particularly supervisor understanding, colleague understanding, and schedule flexibility—was associated with approximately 75% lower odds of belonging to the High Global Fatigue group. Job demands and job control showed no associations. The High Global Fatigue group reported lower work engagement, higher presenteeism, reduced cognitive function at work, and poorer quality of life compared to the other groups. Conclusions: Three multidimensional fatigue profiles were identified among employed cancer survivors. Workplace support factors were more strongly associated with fatigue profiles than job characteristics. These profiles were associated with occupational outcomes. Implication for Cancer Survivors: These distinct fatigue profiles can guide personalized workplace interventions to optimize support for employed cancer survivors.
| Original language | English |
|---|---|
| Journal | Journal of Cancer Survivorship |
| DOIs | |
| Publication status | Accepted/In press - 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Oncology
- Oncology(nursing)
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