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find Keyword "成瘾" 5 results
  • 全身麻醉下超快速脱毒的研究进展

    全身麻醉(全麻)下超快速阿片类脱毒是一种新的脱毒方法,即在全麻患者无意识时运用大剂量的阿片类药物拮抗剂激发戒断症状的发生,使患者安全地渡过脱毒期。与传统的利用美沙酮等脱毒方法相比,它具有近期脱毒成功率高、时间短、患者痛苦少等特点。现就全麻下超快速脱毒的研究进展作一综述。

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  • Research progress of neurobiological function of 1-methyl-6,7-dihydroxy-1,2,3,4-tetrahydroisoquinoline

    1-methyl-6,7-dihydroxy-1,2,3,4-tetrahydroisoquinoline (Sal) is a kind of catechol isoquinoline compound, which mainly exists in mammalian brain and performs a variety of biological functions. Through in vivo metabolism, Sal can be transformed into endogenous neurotoxins and can participate the occurrence of Parkinson’s disease (PD). This has attracted widespread concern of researchers. Recently, many research works have shown that Sal may lead to alcohol addiction and regulate hormone release of the neuroendocrine system, which indicated that it is a potential regulator of dopaminergic neurons. In this paper, we discuss the neural functions of Sal on the above aspects, and wish to provide some theoretical supports for further research on its mechanism.

    Release date:2017-08-21 04:00 Export PDF Favorites Scan
  • Incidence rate of college students’ internet addiction in China: a meta-analysis

    ObjectiveTo systematically review the incidence of internet addiction disorder among college students in China.MethodsPubMed, EMbase, VIP, WanFang Data and CNKI databases were electronically searched to collect cross-sectional studies on incidence rate of college students’ internet addiction in China from inception to February 2020. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies, then, meta-analysis was performed by Stata 16.0 software.ResultsA total of 65 cross-sectional studies involving 87 702 subjects were included. The results of meta-analysis showed that: the overall incidence of college students’ internet addiction in China was 10.7% (95%CI 9.6% to 11.8%). The incidence of internet addiction from 2011 to 2018 (11.7%, 95%CI 10.2% to 13.2%) was higher than that from 2005 to 2010 (9.6%, 95%CI 8.1% to 11.1%). The incidence in male students (14.6%, 95%CI 13.1% to 16.0%) was higher than that in female students (6.9%, 95%CI 5.9% to 7.8%). The incidence of urban students (12.2%, 95%CI 9.3% to 15.2%) was higher than that of rural students (9.0%, 95%CI 7.3% to 10.6%). The incidence of students who were not satisfied with their major (16.2%, 95%CI 5.5% to 26.8%) was higher than that of satisfied (5.0%, 95%CI 1.3% to 8.8%). The incidence of students with poor academic performance (29.4%, 95%CI 11.9% to 47%) was higher than of excellent academic performance (4.1%, 95%CI 1.9% to 6.4%).ConclusionsThe incidence rate of internet addiction among college students in China shows an obvious upward trend. There are differences in the incidence rates of internet addiction among college students in different regions. The incidence rates of internet addiction are different among different genders, degree of satisfaction with their majors and academic achievements.

    Release date:2021-02-05 02:57 Export PDF Favorites Scan
  • Addiction medicine education on massive open online course improves the stigma of substance use disorder patients: a randomized controlled trial

    Objective To explore the relation between stigma and substance use of patients with substance use disorder and explore the impact of learning addiction medicine massive open online course (MOOC) on patients’ stigma, depression and anxiety. Methods Patients with substance use disorder in Meishan Detoxification Center from January 11 to 18, 2020 were selected. The patients were randomly divided into control group and teaching group. Both groups participated in regular labor reform while the teaching group attended extra MOOC course. The general demographic data and the duration and amount of substance use were collected before intervention. Before and after intervention, all the patients completed scales including Chinese Version of Substance Use Stigma Mechanisms Scale (SUSMS-C), Zung Self-Rating Depression Scale (SDS) and Zung Self-Rating Anxiety Scale (SAS). The correlation between stigma and depression, anxiety, substance use characteristics were analyzed, as well as the changes of stigma, depression and anxiety before and after MOOC intervention.Results A total of 78 patients were included, including 41 in the control group and 37 in the teaching group. There was no correlation between the scores of SUSMS-C and the duration or amount of substances use (P>0.05). SAS score and SDS score were positively correlated with the total score of stigma, internalized stigma, enacted stigma (family) and enacted stigma (healthcare providers) (P<0.05). SDS scores and SAS scores had no correlation with the anticipated stigma (P>0.05). After intervention, the total score of stigma, anticipated stigma (family) and anticipated stigma (healthcare providers) in the teaching group decreased (P<0.05). In the control group, only anticipated stigma (family) decreased (P=0.047). There was no significant difference in other SUSMS-C items, SAS scores, or SDS scores between the two groups before and after intervention (P>0.05). Conclusions Stigma may not be able to protect patients with substance use disorder from using substances. Instead, stigma may potentially cause negative emotional consequences like depression and anxiety. The addiction medicine MOOC can be used as an intervention to reduce the stigma of patients with substance use disorder.

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  • Analysis of the influencing factors of internet game addiction among middle school students

    Objective To explore the influencing factors of internet game addiction among middle school students. Methods Students from a certain district in Sichuan between September 2022 and March 2023 were included as participants. Basic information such as gender, age, whether the subjects were only children, place of residence, parental education, and subjective economic status were investigated. The nine-item Internet Gaming Disorder Scale-short form was used to investigate whether participants had internet game addiction, and the Berkman-Syme Social Network Index was used to evaluate the participants’ social level. Multiple linear regression analysis was used to conduct multivariate analysis to explore the influencing factors of internet game addiction. Results A total of 594 questionnaires were distributed, and 592 valid questionnaires were ultimately obtained. The detection rate of internet game addiction was 12.0%. Multiple linear regression analysis showed that gender (t=−8.281, P<0.001), age (t=3.211, P=0.001), subjective economic status in the region (t=2.025, P=0.043), and social level (t=−4.239, P<0.001) were the influencing factors of online game addiction. Due to the P value was close to the set test level (0.05), subjective economic status in the region was not considered an influencing factor of internet game addiction. Conclusion Teenagers with male gender, older age, and lower social skills are more likely to develop addiction to internet games.

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