کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
13425533 | 1841952 | 2019 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Social cognition and interaction training (SCIT) for partially remitted patients with bipolar disorder in China
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
روانپزشکی بیولوژیکی
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چکیده انگلیسی
Bipolar disorder (BD) is associated with functional impairment. Social Cognition and Interaction Training (SCIT) has been shown to be feasible and effective at improving social functioning in patients with schizophrenia. We aimed to explore the association between SCIT and improvements in the clinical symptoms and functioning of partially remitted patients with BD in China. Seventy-four BD patients were randomly assigned to the SCIT and psychoeducation (Control) groups. All subjects participated in group interventions weekly for 8 weeks. Furthermore, the participants were administered the Young Mania Rating Scale (YMRS), the 17-item Hamilton Depression Rating Scale (HDRS-17), the Function Assessment Short Test (FAST) and neurocognitive measures at baseline and after eight weeks. There were no differences in demographics, the HDRS-17, YRMS, and FAST scores or neurocognitive measures between the groups at baseline (p>0.05). The repeated-measures analysis revealed that SCIT resulted in greater improvement in the HDRS, YMRS, and FAST scores (including six domains) (p<0.01) and two neurocognitive measures (p<0.05) compared to psychoeducation. Our findings suggest that SCIT is a feasible and promising intervention for the clinical symptoms and functioning of partially remitted patients with BD. Further longitudinal studies are needed to observe the long-term impact of SCIT on emotional and functional improvement in these patients.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Psychiatry Research - Volume 274, April 2019, Pages 377-382
Journal: Psychiatry Research - Volume 274, April 2019, Pages 377-382
نویسندگان
Yong Zhang, Xiaojuan Ma, Sixiang Liang, Wenwen Yu, Qianqian He, Jian Zhang, Yanhui Bian,