Beyond using composite measures to analyze the effect of unmet supportive care needs on caregivers' anxiety and depression

Objective: Caregiver research has relied on composite measures (eg, count) of unmet supportive care needs to determine relationships with anxiety and depression. Such composite measures assume that all unmet needs have a similar impact on outcomes. The purpose of this study is to identify individual unmet needs most associated with caregivers' anxiety and depression. Methods: Two hundred nineteen caregivers completed the 44-item Supportive Care Needs Survey and the Hospital Anxiety and Depression Scale (minimal clinically important difference = 1.5) at 6 to 8 months and 1, 2, 3.5, and 5 years following the patients' cancer diagnosis. The list of needs was reduced using partial least square regression, and those with a variance importance in projection >1 were analyzed using Bayesian model averaging. Results: Across time, 8 items remained in the top 10 based on prevalence and were labelled “core.” Three additional ones were labelled “frequent,” as they remained in the top 10 from 1 year onwards. Bayesian model averaging identified a maximum of 3 significant unmet needs per time point—all leading to a difference greater than the minimal clinically important difference. For depression, none of the core unmet needs were significant, rather significance was noted for frequent needs and needs that were not prevalent. For anxiety, 3/8 core and 3/3 frequent unmet needs were significant. Conclusions: Those unmet needs that are most prevalent are not necessarily the most significant ones, and findings provide an evidence-based framework to guide the development of caregiver interventions. A broader contribution is proposing a different approach to identify significant unmet needs.