神经反射
康复
生活质量(医疗保健)
心理学
类阿片
上瘾
心理干预
美沙酮
随机对照试验
认知
生物反馈
美沙酮维持
临床心理学
物理医学与康复
物理疗法
医学
精神科
脑电图
内科学
心理治疗师
受体
作者
Alireza Faridi,Farhad Taremian,Robert W. Thatcher
标识
DOI:10.1177/15500594241283069
摘要
Background. Previous studies has shown that conventional neurofeedback and cognitive rehabilitation can improve psychological outcomes in people with opioid use disorders. However, the effectiveness of LORETA Z-score neurofeedback (LZNFB) and attention bias modification training on quality of life and inhibitory control of these people has not been investigated yet. LZNFB targets deeper brain structures with higher precision, compared to conventional neurofeedback that typically focuses on surface EEG activity. The present study aims to compare the effect of these two methods on quality of life and response inhibition in men with opioid use disorders under methadone maintenance therapy (MMT). Methods. In this randomized controlled clinical trial with a pre-test, post-test, follow-up design, 30 men with opioid use disorders under MMT were randomly assigned into three groups of LZNFB, attention bias modification training, and control (MMT alone). The LZNFB and Cognitive Rehabilitation groups received 20 and 15 sessions of treatment, respectively. The Persian versions WHO Quality of Life-BREEF questionnaire and the Go/No-Go test were completed by the participants before, immediately after, and one month after interventions. The collected data were analyzed in SPSS v.22 software. Results. Both intervention groups showed a significant improvement in quality-of-life score and a significant reduction in response time at the post-test phase ( P < .05), where LZNFB group showed more improvement in quality of life and more reduction in response inhibition. After one month, the increase in quality of life continued in both groups, while the decrease in response time continued only in the LZNFB group. Conclusion. Both LZNFB and attention bias modification training are effective in improving quality of life and response inhibition of men with OUD under MMT, however, LZNFB is more effective.
科研通智能强力驱动
Strongly Powered by AbleSci AI