A taxonomy of work-related outcomes in cancer survivors to advance systematic assessments in research and practice
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ID: 321183
2026
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Abstract
Capturing consistent and reliable data about work disruption as a part of research and clinical care of cancer survivors is key to building an evidence base to understand how different treatment regimens and care plans impact survivors' work lives. While the impact of cancer on employment is well recognized, there remains a lack of consensus regarding which work-related constructs should be used in research and clinical practice. This commentary proposes a comprehensive taxonomy of work-related outcomes and provides standardized definitions, recommended metrics, and guidance for researchers seeking to evaluate work-related outcomes, design interventions to optimize these outcomes, and assess the effectiveness of such interventions. To help investigators prioritize which work-related outcomes to include in different types of research studies, we classify work outcomes as essential (work status, work hours), important (assets/income, productivity, absenteeism), and supporting (job demands/activities, access/types of accommodations, access to leave/protected time off, workplace discrimination/relationships with coworkers, job lock, impact on role/career trajectory), with tailored recommendations for their assessment across various research and clinical contexts. Work disruption should be assessed in virtually all studies of cancer survivors using consistent metrics and PROMs, such as those recommended in this review. The assessment battery should be tailored to the research questions under study and clinical context, with the timing adapted to treatment phases. Use of standardized measures to study work-related outcomes will advance this emerging field of study, allowing for more rigorous testing of interventions and informed patient-clinician decision-making.
| Reference Key |
openalex_W7168625838
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| Authors | Victoria S Blinder, Yashasvini Sampathkumar, Courtney P Williams, Antonia V Bennett, Janet S. de Moor |
| Journal | JNCI Journal of the National Cancer Institute |
| Year | 2026 |
| DOI |
10.1093/jnci/djag232
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| URL | |
| Keywords | Keywords not found |
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