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Social support is widely recognized as a protective factor against psychological distress, especially for the elderly with chronic diseases. Therefore, effective tools for measuring social support are of great significance for both research and clinical practice. This study aims to cross-culturally adapt the German Social Support Scale (F-SozU) into Chinese and assess its psychometric properties among older adults with chronic diseases. A cross-sectional study was conducted in a Chinese tertiary hospital. Four hundred ninety-six older adults that were approached via a convenience sampling method completed the Chinese version of the F-SozU. Content validity was evaluated using the two-round Delphi method. Psychometric properties, including item analysis, content validity, structure validity, convergent and discriminant validity and reliability were examined. The final version of C-F-SozU is a three-factor structure consisting of 23 items. All indicators of item analysis are acceptable. Adequate content validity was ensured by the expert panel (I-CVI = 0.80–1.00, S-CVI = 0.965) and participants. The confirmatory factor analysis model revealed that the factor structure of the C-F-SozU fitted the original scale (χ 2 /df = 2.088, CFI = 0.998, GFI = 0.943, TLI = 0.997, IFI = 0.998, RMSEA = 0.064 and SRMR = 0.043). The total Cronbach’s α was 0.956, and the test–retest reliability coefficient was 0.887. The convergent validity (average variance extracted = 0.517–0.995) and discriminant validity were found to be satisfactory. No floor/ceiling effect was found. The 23-item C-F-SozU demonstrates robust reliability and validity, rendering it a valuable instrument for evaluating social support among older adults with chronic diseases in China. The three-factor structure of the scale allows for a more detailed assessment of the social support, with the scores of each dimension and the total score being of significant reference value. More comprehensive studies may be required to confirm its effectiveness and applicability.

High-resolution dynamic imaging and quantitative analysis of lung cancer xenografts in nude mice using clinical PET/CT