Employment outcomes of adolescent and young adult (AYA) cancer survivors and their partners: A Dutch population-based study.

Abstract

BACKGROUND

The aim of this population-based registry study was to examine the impact of cancer on employment outcomes in adolescent and young adult (AYA) survivors and their partners and associated sociodemographic and clinical characteristics.

CONCLUSIONS

A cancer diagnosis significantly affects employment outcomes of AYA patients with cancer. Patients at risk should have access to services such as job counseling to help them return into society in the best possible way. No objective impact on partners' employment outcomes was found; however, subjective well-being was not taken into account.

PLAIN LANGUAGE SUMMARY

This study estimated the causal effect of a cancer diagnosis on employment outcomes. Adolescent and young adult cancer survivors face a reduction in both employment probability and the number of hours worked when employed. Partners that were unemployed or worked the least number of hours a year before diagnosis had a 5.5 percentage-point increased employment probability, but for other partners effects are small.

RESULTS

Patients suffered a reduced employment probability (3.8 percentage points) and number of hours worked when employed (3.8%). This effect was larger for females, and individuals with a migration background, high tumor stage, or diagnosed with a central nervous system tumor/hematologic malignancy. In regard to employment, no significant effect could be found for the patients' partners, although a 5.5 percentage-point increase in employment probability was found in partners who were either unemployed or worked fewer than 400 hours.

METHODS

A total of 2456 AYA cancer patients, diagnosed in 2013 and aged 18 through 39 years old, were selected from the Netherlands Cancer Registry and linked to employment data from Statistics Netherlands, from which 1252 partners of AYAs could be identified. For both patients and their partners, a control group with same age, migration background, and sex was selected. The impact (i.e., causal effect) was estimated by implementing a doubly robust difference-in-differences method, from 3 years before to 5 years after cancer diagnosis.

More about this publication

Cancer
  • Publication date 23-02-2024

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