Photo Credit: Doucefleur

The Hopkins Symptom Check-10 (HSCL-10) shows potential in the diagnosis of psychiatric disorders, including anxiety and depression, in patients with SUD.

Although comorbid psychiatric disorders are common in patients with substance use disorder (SUD), studies show that these mental health concerns are underreported, underassessed, and underdiagnosed in this patient population. A complete diagnosis that includes these comorbidities is essential in establishing individualized care and may lead to better outcomes. However, healthcare professionals face challenges receiving information regarding diagnostic tools that could potentially aid the evaluation process. One such tool is the Hopkins Symptom Check-10 (HSCL-10), a brief symptoms self-report inventory that has been shown to have potential in the diagnosis of psychiatric disorders, including anxiety and depression, in patients with SUD.

Due to the limited availability of studies examining the application of HSCL-10 (ie, a single study), Helle Wessel Andersson, PhD, and colleagues developed a receiver operating characteristic (ROC) analysis drawing from data in a cohort study of SUD patients. They published their findings in the Nordic Journal of Psychiatry.

“Using the HSCL-10, our aims were to evaluate the probability of correctly identifying patients with 1) any diagnosis of anxiety (and post-traumatic stress disorder [PTSD] exclusively) or 2) any diagnosis of depression (and major depressive disorder [MDD] exclusively), and to test 3) whether the predictive accuracy of the HSCL-10 is enhanced by relevant covariates,” the authors wrote.

Prevalent Comorbidities

After the researchers made appropriate exclusions, the study sample included 606 patients with SUD who had undergone a valid HSCL-10 test. Of these identified patient participants, 29% were female, 12% had attained a high level of education, and 31% had a low level of education. A medical specialist or clinical psychologist diagnosed psychiatric disorders in this group (in addition to SUD). An anxiety disorder was detected in 22% of the patients—the most common of which were phobias (8.5%) and PTSD (7%). Up to 17% of patients were diagnosed with a mood disorder; MDD was diagnosed in 13% of the whole group.

Multilayered Analysis

The research team applied both the Kaiser–Meyer–Olkin (KMO) and Bartlett’s test of sphericity to determine that the assumptions for principal component analysis (PCA) were met (KMO=0.90, χ²=3025.01, P<0.001). Based on PCA, two HSCL-10 subscales were developed. The study team analyzed the internal consistency of the HSCL-10 and the corresponding subscales (ie, anxiety and depression) using Cronbach’s alpha. Independent samples t-tests established a comparison of the mean HSCL-10 and subscale scores between patients with each of the targeted psychological disorders and all other patients combined.

The study team also applied ROC to investigate the success of the HSCL-10 as a screener for any anxiety disorder, mood disorder, PTSD, and/or MDD. They also considered covariates and performed bivariate analyses accordingly.

Overall HSCL-10 scores and subscale scores that researchers observed during the study were deemed consistent with expert psychological diagnosis with a Cronbach’s alpha of 0.893 for the total scale, 0.798 for the anxiety subscale, and 0.871 for the depression subscale.

Overall, the mean HSCL-10 score was 2.15 for the patient participants. The mean score for anxiety was 2.10, and the mean score for depression was 2.20.

Those patients who received a diagnosis of any anxiety disorder attained a mean score of 2.41, and those patients who received a diagnosis of any mood disorder attained a mean score of 2.43. For PTSD, the mean HSCL-10 score was 2.48; for those with MDD, the mean score was 2.43.

The discriminatory accuracy of the HSCL-10 for diagnosing the presence of any anxiety disorder was 0.640 (95% CI = 0.589–0.691). Researchers noted that the accuracy of HSCL-10 increased to 0.772 (95% CI = 0.729–0.815) with the application of appropriate covariates such as gender, age, use of multiple drugs, and the treatment facility at which they received care.