Reliability and Validity of THINC-it in Evaluating Cognitive Function of Patients with Bipolar Depression

Abstract

Purpose: The THINC-integrated tool (THINC-it) as a brief screening tool can assesses cognitive impairment in patients with major depressive depression (MDD). Here, we aim to evaluate the reliability and validity of the THINC-it in a bipolar depression (BD-D) group in comparison with a healthy control (HC) group. Materials and Methods: Both groups were matched according to age, gender, years of education, and IQ. All participants completed the THINC-it test, including Spotter, Symbol Check, Codebreaker, Trails, and the Perceived Deficits Questionnaire for Depression-5-item (PDQ-5-D). The concurrent validity and internal consistency of the THINC-it test were analyzed, and 30 healthy controls were randomly sampled to retest THINC-it to verify the reliability of the THINC-it retest. The correlation between THINC-it and Hamilton Depression Scale (HAMD-17) and Sheehan Disability Scale (SDS) was also analyzed. Results: Fifty-eight patients with BD-D and 61 HCs were included for final analysis. There were significant mean difference (MD) standard errors (SE) between two groups in PDQ-5-D, Spotter and Codebreaker (all P<0.01), Trails (P=0.015). There was no significant difference in Symbol Check (MD (SE)=-0.01 (0.18), P=0.938; 95% CI=-0.38 to 0.35). The Cronbach's α of PDQ-5-D was 0.640. The intraclass correlation coefficient (ICC) was between 0.440 and 0.757. The highest concurrent validity was PDQ-5-D (r=0.812, P<0.001). PDQ-5-D was positively correlated with HAMD-17 and SDS score (P<0.01). The objective test had no significant correlation with HAMD-17 and SDS scores (P>0.05). Conclusion: This study found that THINC-it can accurately present the cognitive impairment of patients with BD-D. It can be potentially applied in assessing the cognitive function of patients with BD-D although Symbol Check may not accurately reflect the level of cognitive function. The concurrent validity and retest reliability are lower than expected, we need to further increase the sample size to study.