Cross-Cultural Adaptation and Psychometric Validation of the Cancer Survivors’ Unmet Needs Measure (CaSUN) in Russian- and Kazakh-Speaking Cancer Survivors in Kazakhstan

G. KARABASOVA, Kerbez Kimatova, Nurgul Abdullayevna Abenova, Anar Balkashevna Tulyayeva, Zalika Klemenc–Ketiš, Perizat Aitmaganbet

2026

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.3390/healthcare14183012
Data confidence 70 medium
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Abstract

Background/Objectives: The growing population of cancer survivors has increased the need for reliable, culturally appropriate instruments to identify unmet supportive care needs. The Cancer Survivors’ Unmet Needs Measure (CaSUN) is a survivorship-specific assessment tool, but validated Russian and Kazakh versions have not previously been available. This study aimed to translate and culturally adapt CaSUN, evaluate its psychometric properties in cancer survivors in Kazakhstan, and examine unmet needs relevant to survivorship care. Methods: This cross-sectional psychometric validation study included 404 cancer survivors (Russian version, n = 201; Kazakh version, n = 203). Translation and cultural adaptation involved forward- and back-translation, expert review, cognitive debriefing, and pilot testing. Internal consistency was assessed using Cronbach’s alpha. Construct validity was evaluated using exploratory (EFA) and confirmatory factor analysis (CFA), with measurement invariance examined across language versions. Unmet needs and associated demographic and clinical factors were also examined. Results: Both versions demonstrated excellent internal consistency (Cronbach’s alpha: Russian = 0.966; Kazakh = 0.978). KMO values were 0.920 and 0.940, respectively (Bartlett’s tests, p < 0.001). EFA yielded a five-factor solution explaining 68.1% and 64.2% of the variance in the Russian and Kazakh versions, respectively; however, parallel analysis supported five factors in the Russian sample but suggested three in the Kazakh sample, indicating greater structural uncertainty for the Kazakh version. CFA demonstrated good incremental fit in both language groups (Russian: CFI = 0.975, TLI = 0.973; Kazakh: CFI = 0.973, TLI = 0.971), although RMSEA (0.096 and 0.102, respectively) and SRMR (0.116 and 0.099, respectively) indicated residual model misfit. Metric invariance was supported, while scalar invariance was supported by conventional fit index criteria but should be regarded as provisional. The most frequent unmet needs concerned medical care, up-to-date information, and involvement in health management. Younger age, male sex, urban residence, a history of cancer recurrence, and Kazakh language completion were independently associated with more unmet needs. Conclusions: The Russian and Kazakh CaSUN versions demonstrated high internal consistency and evidence supporting construct validity and cross-language comparability. These culturally adapted versions may support systematic needs assessment and patient-centered survivorship care in multilingual oncology services in Kazakhstan.