Validity of the Ghent Multidimensional Somatic Complaints Scale in a clinical sample

Development and Validation of a Symptom Scale for Indian Patients With Medically Unexplained Physical Symptoms

Introduction Patients with medically unexplained physical symptoms (MUPS) account for a substantial proportion of patients visiting the outpatient department. Diagnosis of MUPS is a challenge for most physicians. An accurate diagnosis relies on obtaining a detailed history from patients regarding the nature of their symptoms, their onset, and any associated aggravating or relieving factors. This study aims to develop a symptom scale for Indian patients with MUPS. Methods The study had a mixed-method study design. Phase 1 involved designing the questionnaire using qualitative techniques, such as literature reviews, focus-group discussions, expert evaluation, and pre-testing of a Hindi and English language Likert-rated interviewer-administered scale. In phase 2, the construct validity of the questionnaire was established using quantitative approaches among 116 patients diagnosed with MUPS. Results The final questionnaire consists of 38 items, with good internal consistency (Cronbach 𝛂 = 0.916). Confirmation sampling adequacy for factor analysis was done using the Kaiser-Meyer-Olkin test (KMO value = 0.792) and Bartlett's test of sphericity (p < 0.001). The newly developed scale showed a Pearson correlation coefficient of 0.568 (p < 0.001) with Patient Health Questionnaire (PHQ)-15 scores. Conclusion A reliable and valid tool has been developed to assess patients' symptoms with MUPS in English and Hindi languages. This questionnaire can be used for assessment, screening, and diagnostic purposes as well as to chart longitudinal changes in patients with MUPS.

Network Analysis of Persistent Somatic Symptoms in Two Clinical Patient Samples

OBJECTIVE

Previous attempts to group persistent somatic symptoms (PSSs) with factor-analytic approaches have obtained heterogeneous results. An alternative approach that seems to be more suitable is the network theory. Compared with factor analysis, which focuses on the underlying factor of symptoms, network analysis focuses on the dynamic relationships and interactions among different symptoms. The main aim of this study is to apply the network approach to examine the heterogeneous structure of PSS within two clinical samples.

METHODS

The first data set consisted of n = 254 outpatients who were part of a multicenter study. The second data set included n = 574 inpatients, both with somatoform disorders. Somatic symptom severity was assessed with the Screening of Somatoform Disorder (SOMS-7T).

RESULTS

Results indicate that there are five main symptom groups that were found in both samples: neurological, gastrointestinal, urogenital, cardiovascular, and musculoskeletal symptoms. Although patterns of symptoms with high connection to each other look quite similar in both networks, the order of the most central symptoms (e.g., symptoms with a high connection to other symptoms in the network) differs.

CONCLUSIONS

This work is the first to estimate the structure of PSS using network analysis. A next step could be first to replicate our findings before translating them into clinical practice. Second, results may be useful for generating hypotheses to be tested in future studies, and the results open new opportunities for a better understanding for etiology, prevention, and intervention research.