Exploring heterogeneity in learned helplessness among brain tumor survivors during concurrent chemoradiotherapy in China: a latent profile analysis
Year: 2026
Type: article
Study design: Observational Study
Abstract: Objective This study aims to identify the latent profiles of learned helplessness among patients with brain tumors, analyze potential influencing factors, and explore the differences in patient learned helplessness across different profiles. Methods Convenience sampling was conducted. A total of 351 brain tumor survivors received concurrent chemoradiotherapy at a tertiary hospital in Lanzhou City, from January 2024 and March 2025 were selected as the study participants. Using validated scales, we assessed the level of learned helplessness (LH), perceived social support (PSS), general self-efficacy (GSE), and the sense of coherence (SOC). Latent profile analysis (LPA) identified heterogeneous subgroups, and subsequent logistic regression analysis examined the associated factors. Results Following data analysis, Learned helplessness was categorized into three latent profiles: the low learned helplessness group (51.0%), the moderate learned helplessness group (34.5%), and the high learned helplessness group (14.5%). Multinomial logistic regression showed that perceived social support (PSS), sense of coherence (SOC), medical insurance type, and WHO grade were factors independently associated with the latent profiles of learned helplessness. Conclusion The LH of brain tumor survivors (BTS) undergoing concurrent chemoradiotherapy exhibits significant heterogeneity and is influenced by multiple factors. Health care providers should implement personalized interventions to the High learned helplessness group and develop targeted, personalized strategies as early as possible. Addressing these differences may offer new insights for improving patient LH.
Source: Frontiers in Psychology
Institution: Lanzhou University Second Hospital
Language: English
Topic: Cancer survivorship and care
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7225334051