Psychometric properties of the Persian version of the somatic symptom disorder-B Criteria Scale (SSD-12) in community and clinical samples

Objective: In the DSM-5's diagnostic criteria of somatic symptom disorders (SSD), the presence of psychological problems (i.e., excessive thoughts, feelings, or behaviors) is emphasized more than the absence of the medical causes of patients' bothersome symptoms. In this regard, the Somatic Symptom Disorder-B Criteria Scale (SSD12) is a screening tool for assessing these psychological features in somatic symptom disorder. This study aimed to validate the Persian version of SSD-12 in the Iranian community (non-clinical) and clinical samples. Methods: Data was gathered from 291 individuals in a community sample (aged 18 to 54, M-age = 36.62, SD = 10.56, 79.7% females) and from clinical setting, including 118 patients diagnosed with major depressive disorder (MDD, aged 18 to 60, M-age = 36.52, SD = 11.39, 75.8% females) and 120 patients diagnosed with somatic symptom disorders (aged 18 to 60, M-age = 35.17, SD = 8.77, 73.7% females). To assess the convergent validity of SSD-12 in the clinical samples, participants were asked to complete measures assessing anxiety, depression, somatic symptoms, health anxiety, and emotional regulation. Results: Confirmatory Factor Analyses (CFAs) showed that the three-factor model of the SSD-12 reached acceptable fit in the community and clinical samples and yielded excellent internal consistency across the samples. Also, test-retest reliability analysis results were good in the community sample. Convergent validity could be shown in the clinical samples. A cut-off score greater than 14 was in the optimal state with a sensitivity of 70.83 and a specificity of 70.07. Conclusion: The current study provides evidence on the factor structure, reliability, and validity of the Persian SSD-12 in the Iranian community and clinical samples. A sum score of 14 can be recommended as the cut-off point. Further studies are needed to assess SSD-12 in different clinical populations and larger samples.