The impact of a culturally tailored technology-based cancer pain management program on the quality of life by psychosocial factors among Asian American breast cancer survivors

Background: Breast cancer survivors face challenges in maintaining their quality of life during their treatment and survivorship process. Especially, Asian American breast cancer survivors frequently encounter constrained social supports and difficulties in accessing adequate emotional and practical support. Cultural barriers are often the major cause of the difficulties. This study aimed to explore the impact of a culturally tailored technology-based cancer pain management program on the quality of life (QoL) by psychosocial factors among Asian American breast cancer survivors. Methods: This is a part of an ongoing randomized controlled trial among Asian American women breast cancer survivors. Data was collected at T0 (baseline), T1 (after 1 month; during intervention), and T2 (after 3 months; post intervention) during the 3-month intervention process. Only the data from 57 participants who completed the intervention were included in this analysis. The instruments included the Perceived Isolation Scale, (PIS) and the Questions on Attitudes, Self-Efficacy, Perceived Barriers, and Social Influences (QASPS), and the Functional Assessment of Cancer Therapy Scale-Breast Cancer (FACT-B). K-means cluster analysis was conducted using baseline data. The optimal number of clusters (k=2) was selected using NbClust package in R. The participants were classified into two clusters, which were then crossed with the interventions form a total of four groups. Longitudinal trajectories were examined using linear mixed model (LMM) to test interaction effects between Time, Cluster, and Intervention Results: Two clusters emerged from the K-means analysis. Cluster 1 (n=18; CAI=9, CAPA=9) showed higher loneliness, lower social support, less positive attitude and self-efficacy, and more perceived barriers, whereas Cluster 2 (n=39; CAI=26, CAPA=13) showed the opposite pattern. LMM analysis revealed significant effects of Time and Cluster on the QoL. In both groups, the QoL improved over time (T1 vs T0: p =.003, T2 vs T0: p <.001). Cluster 2 reported higher QoL (Cluster 2 vs Cluster 1: p =.002) than Cluster 1. Except Time 2 x Cluster 2 interaction ( p =.040), no other significant interaction effects were found. Conclusion: This study demonstrated that technology-based interventions can positively impact QoL for breast cancer survivors, regardless of participants' level of psychosocial factors. However, caution is required when interpreting the results due to the small sample size and imbalance between clusters. Future studies should include a large enough sample size to confirm the long-term effects of Intervention CAI.