Development of depression assessment tools using humanoid robots -Can tele-operated robots talk with depressive persons like humans?

BACKGROUND: Depression is a common mental disorder and causes significant social loss. Early intervention for depression is important. Nonetheless, depressed patients tend to conceal their symptoms from others based on shame and stigma, thus hesitate to visit psychiatrists especially during early phase. We hypothesize that application of humanoid robots would be a novel solution. Depressed patients may feel more comfortable talking with such robots than humans. METHODS: We recruited 13 patients with major depressive disorder (MDD) and 27 healthy volunteers as controls. Participants took both tele-operated humanoid robot and human interviews to evaluate severity of depression using the Hamilton Depression Rating Scale (HDRS). In addition, participants completed a self-administered questionnaire asking about their impressions of the robot interview. RESULTS: Confidence interval and t-test analysis have revealed that the HDRS scores are equally reliable between robot and human interviews. No significant differences were observed between the two interviews regarding "nervousness about the interview" and "hesitancy to talk about depressed moods and suicidal ideation." Compared to human interviews, robot interviews yielded significantly lower scores on shame-related factors especially among patients with MDD. LIMITATION: Small sample size, and the evaluator is male only. CONCLUSIONS: This is the first report to show the reliability of tele-operated humanoid robot interviews for assessment of depression. Robot interviews are potentially equally reliable as human interviews. Robot interviews are suggested to be more appropriate in assessing shame-related suppressed emotions and hidden thoughts of depressed patients in clinical practice, which may reduce the stigma associated with depression.

Relevance of hoarding behavior and the traits of developmental disorders among university students: a self-reported assessment study.

BACKGROUND: Previous studies have shown that hoarding behavior usually starts at a subclinical level in early adolescence and gradually worsens; however, a limited number of studies have examined the prevalence of hoarding behavior and its association with developmental disorders in young adults. The aims of this study were to estimate the prevalence of hoarding behavior and to identify correlations between hoarding behavior and developmental disorder traits in university students. METHODS: The study participants included 801 university students (616 men, 185 women) who completed questionnaires (ASRS: Adult ADHD Self-Report Scale version 1.1, AQ16: Autism-Spectrum Quotient with 16 items, and CIR: Clutter Image Rating). RESULTS: Among 801 participants, 27 (3.4%) exceeded the CIR cut-off score. Moreover, the participants with hoarding behavior had a significantly higher percentage of ADHD traits compared to participants without hoarding behavior (HB(+) vs HB(-), 40.7% vs 21.7%). In addition, 7.4% of HB(+) participants had autism spectrum disorder (ASD) traits, compared to 4.1% of HB(-) participants. A correlation analysis revealed that the CIR composite score had a stronger correlation with the ASRS inattentive score than with the hyperactivity/impulsivity score (CIR composite vs ASRS IA, r = 0.283; CIR composite vs ASRS H/I, r = 0.147). CONCLUSIONS: The results showed a high prevalence of ADHD traits in the university students with hoarding behavior. Moreover, we found that the hoarding behavior was more strongly correlated with inattentive symptoms rather than with hyperactivity/impulsivity symptoms. Our results support the concept of a common pathophysiology behind hoarding behavior and ADHD in young adults.

Biological heterogeneity of obsessive-compulsive disorder: A voxel-based morphometric study based on dimensional assessment.

AIM: Although many neuroimaging studies of obsessive-compulsive disorder (OCD) have reported broad abnormalities in gray matter (GM), their results remain inconsistent. One reason for this inconsistency could be the heterogeneity of OCD. In the present study, we aimed to classify alterations in brain anatomy by OCD subtype. METHODS: Magnetic resonance imaging examinations of 37 OCD patients and 37 matched healthy controls were conducted using a 3.0-Tesla scanner. In the voxel-based morphometric procedure, preprocessed GM structural images were used to compare the two groups, and multiple regression analysis was used to investigate the correlation between regional GM volume in OCD patients and the OCD symptom dimension type assessed by using the Dimensional Yale-Brown Obsessive-Compulsive Scale. RESULTS: We found significant reductions in GM volume in broad areas of the left prefrontal, right orbitofrontal, right parietal, right temporal, and right posterior cingulate cortex in the OCD patients compared to healthy controls. In addition, we found specific negative correlations between symptomatic dimension scores and regional GM volumes, mainly as decreased right cerebellum in 'aggression/checking' and decreased right insula in 'contamination/washing'. CONCLUSION: The pathophysiology of OCD may involve widely distributed neural systems. Moreover, there are distinct correlations among symptomatic dimensions and structural abnormalities.