Determining cut-off values and predictors for the Snaith–Hamilton Pleasure Scale: comparison between clinical and school settings

Abstract

Background Few previous studies have established Snaith–Hamilton Pleasure Scale (SHAPS) cut-off values using receiver operating characteristic curve analysis and applied these values to compare predictors of anhedonia between clinical and nonclinical groups. Aims To determine the optimal cut-off values for the SHAPS and use them to identify predictors of anhedonia in clinical and nonclinical groups in Taiwan. Method This cross-sectional and correlational study used convenience sampling to recruit 160 patients from three hospitals and 412 students from two universities in northern Taiwan. Data analysis included receiver operating characteristic curve, univariate and multivariate analyses. Results The optimal SHAPS cut-off values were 29.5 and 23.5 for the clinical and nonclinical groups, respectively. Moreover, two-stage analysis revealed that participants in the clinical group who perceived themselves as nondepressed, and participants in the nonclinical group who did not skip classes and whose fathers exhibited higher levels of care and protection were less likely to attain the cut-off values. Conversely, participants in the nonclinical group who reported lower academic satisfaction and were unwilling to seek help from family or friends were more likely to attain the cut-off values. Conclusions Our findings highlight the importance of optimal cut-off values in screening for depression risk within clinical and nonclinical groups. Accordingly, the development of comprehensive, individualised programmes to monitor variation trends in SHAPS scores and relevant predictors of anhedonia across different target populations is crucial.

Keywords

• Anhedonia
• depression
• ROC curve
• SHAPS