Factor Structure and Measurement Invariance of the Chinese version of the Snaith-Hamilton Pleasure Scale (SHAPS) in Non-clinical and Clinical populations

Background: Anhedonia, a key symptom of depression and schizophrenia, has emerged as a potential endophenotype. The aim of this study was to evaluate the psychometric properties of a Chinese version of the SnaithHamilton Pleasure Scale(SHAPS), a self-report anhedonia scale, in a non-clinical sample and clinical sample inclusive of major depressive disorder (MDD), schizophrenia, or a personality disorder. Methods: A total of 4,722 undergraduate students and 352 clinical patients participated in this study. Internal consistency was assessed by calculating Cronbach's a and mean inter-item correlation (MIC) values. Test-retest reliability and convergent validity were assessed with Pearson r coefficients. The best fitting of six potential factor-structure models was determined by confirmatory factor analysis (CFA). Measurement invariance across genders and samples was determined by multi-group CFA. Results: Internal consistency of the Chinese version of the SHAPS was acceptable in non-clinical (Cronbach's a = 0.90) and clinical (Cronbach's a = 0.91) samples. Four-week interval test-retest reliability was 0.60. Moreover, the Spanish four-factor structure had the best fit indexes in both samples. Scalar invariance was established across genders as well as across non-clinical sample and clinical sample. SHAPS was significantly related with the Temporal Experience of Pleasure Scale (TEPS) and Beck Depression Inventory (BDI). Limitations: There was a restricted scope of convergent validity and the size of clinical sample is relatively small, psychometric properties in elderly sample is also required. Conclusion: The Chinese version of the SHAPS is a reliable, effective, simple and convenient tool for assessing and screening for anhedonia.

Automated summary

The study evaluated the psychometric properties of the Chinese version of SHAPS in non-clinical and clinical samples including MDD, schizophrenia, or personality disorders. The results showed good internal consistency, best fit structural model in both samples, and significant associations with TEPS and BDI.