Ethical and Policy Implications of Financial Burden in Family Caregivers

Comparisons of financial hardship in cancer care by family structure and among those with and without minor children using nationally representative data

INTRODUCTION

While demographic risk factors of cancer-related financial hardships have been studied, having minor children or being single have rarely been assessed in the context of healthcare-related financial hardships.

METHODS

Using data from the 2015 to 2018 National Health Interview Survey, we assessed financial hardship (material and psychological hardship; behavioral coping due to costs: delaying/foregoing care, reducing prescription costs, or skipping specialists or follow-up care) among adults aged 18-59 years with cancer (N = 2844) by minor child parenting status and family structure. In a secondary analysis, we compared this group with individuals without cancer. Using logistic regression models, we compared those with and without children aged <18 years, further distinguishing between those who were single versus one of two or more adults in the family.

RESULTS

Compared to individuals from families with two or more adults/without children, single adults with children more often reported cancer-related financial hardships, for example material hardship (45.9% vs. 38.8%), and reducing prescription costs, (50.7% vs. 34.4%, adjusted OR 1.57, 95% CI 1.07-2.28). Single adults without minor children and those from families with two or more adults/with minor children also reported greater financial hardships on some dimensions. Associations were similar among those without cancer, but the overall magnitude of financial hardships was lower compared to those with cancer.

CONCLUSIONS

Our findings suggest that having minor children, and being a single adult are risk factors for cancer-related financial hardship. Financial vulnerability associated with family structure should be taken into consideration in healthcare, and especially cancer care.

Complex identities, intersectionality and research approaches in millennial family caregivers in the United States

AIMS

A discussion of the personal and social contexts for Millennial family caregivers and the value of including complex identity and intersectionality in Millennial family caregiving research with practical application.

DESIGN

Discussion paper.

DATA SOURCES

This discussion paper is based on our own experiences and supported by literature and theory.

IMPLICATIONS FOR NURSING

Millennial family caregivers have distinct generational, historical and developmental experiences that contribute to the care they provide as well as their own well-being. Complex identity, the integration of multiple identities, and intersectionality, systems and structures that disempower and oppress individuals with multiple identities, need to be addressed in nursing research so intervention tailoring and health equity can be better supported in this population. From research conceptualization and design to data analysis, data must be used intentionally to promote equity and reduce bias. The inclusion of diverse Millennial caregivers throughout all stages of the research process and having a diverse nursing research workforce will support these efforts.

CONCLUSION

Millennial family caregivers comprise one-quarter of the family caregiving population in the United States, and they are more diverse than previous family caregiving generational cohorts. Their needs will be more fully supported by nursing scientists with the adoption of methods and techniques that address complex identity and intersectionality.

IMPACT

Nursing researchers can use the following research approaches to address complex identity and intersectionality in Millennial caregivers: inclusion of qualitative demographic data collection (participants can self-describe); data disaggregation; data visualization techniques to augment or replace frequencies and descriptive statistics for demographic reporting; use of researcher reflexivity throughout the research process; advanced statistical modelling techniques that can handle complex demographic data and test for interactions and differential effects of health outcomes; and qualitative approaches such as phenomenology that centre the stories and experiences of individuals within the population of interest.