背景:非医疗使用处方药会导致用药过量;这代表了全球严重的公共卫生危机。在这个数字时代,社交网络服务是非法获取过量药物的可行平台,包括处方药。在日本,这种非法毒品交易是通过流行的跳蚤市场应用进行的,社交媒体,和拍卖网站,大多数交易都是非处方药(OTC)。最近,一个新兴的独特的黑市,个人交易处方药-主要是神经系统药物-使用特定关键字(“OkusuriMoguMogu”),已经出现在X(以前的Twitter)上。因此,应定期监测这些动态的非法贸易方法,以鼓励适当使用药物。
目的:本研究旨在使用搜索词“OkusuriMoguMogu”指定在X上交易的药物的特征,并分析与X帖子相关的个人行为,包括交易的药物类型和标签用法。
方法:我们在2022年9月18日至10月1日之间对X上的公开帖子进行了横断面研究。在此期间,对包括“OkusuriMoguMogu”一词的帖子进行了审查。帖子根据内容进行了分类:购买,出售,自我管理,抬头,和其他人。在分类为购买的帖子中,出售,和自我管理,使用解剖学治疗化学(ATC)分类法对药物名称进行系统列举和分类.此外,所有分析帖子中的标签都被计数并分为6类:药物名称,精神障碍,自我伤害,买卖,社区形成,和其他人。
结果:在961个确定的帖子中,包括549个用于分析。在这些帖子中,119(21.7%)参考自我管理,和237(43.2%;买入:n=67,12.2%;卖出:n=170,31.0%)参考交易。在这237个职位中,提到了1041个药物名称,比2021年3月的研究增加了>5倍。基于ATC分类的分类主要显示神经系统药物,代表上述药物的82.1%(n=855),与之前的调查一致。值得注意的是,药物的多样性已经扩大到包括未经日本政府批准的药物。有趣的是,OTC药物在自我给药职位中经常被提及(比值比23.6,95%CI6.93-80.15)。对标签的分析(n=866)揭示了在用户之间促进社区联系的努力。
结论:这项研究强调了X个帖子促成的非法处方药交易的复杂性不断升级。应考虑采取规管措施,以提高公众的认识,防止非法交易,这最终可能导致滥用或滥用,如过量。除了这些药物警戒措施,社会方法,可以指导个人适当的医疗或精神资源也将是有益的,因为我们的标签分析揭示了形成一个有凝聚力或封闭的社区在用户之间。
BACKGROUND: Nonmedical use of prescription drugs can cause overdose; this represents a serious public health crisis globally. In this digital era, social networking services serve as viable platforms for illegal acquisition of excessive amounts of medications, including prescription medications. In Japan, such illegal drug transactions have been conducted through popular flea market applications, social media, and auction websites, with most of the trades being over-the-counter (OTC) medications. Recently, an emerging unique black market, where individuals trade prescription medications-predominantly nervous system drugs-using a specific keyword (\"Okusuri Mogu Mogu\"), has emerged on X (formerly Twitter). Hence, these dynamic methods of illicit trading should routinely be monitored to encourage the appropriate use of medications.
OBJECTIVE: This study aimed to specify the characteristics of medications traded on X using the search term \"Okusuri Mogu Mogu\" and analyze individual behaviors associated with X posts, including the types of medications traded and hashtag usage.
METHODS: We conducted a cross-sectional study with publicly available posts on X between September 18 and October 1, 2022. Posts that included the term \"Okusuri Mogu Mogu\" during this period were scrutinized. Posts were categorized on the basis of their contents: buying, selling, self-administration, heads-up, and others. Among posts categorized as buying, selling, and self-administration, medication names were systematically enumerated and categorized using the Anatomical Therapeutic Chemical (ATC) classification. Additionally, hashtags in all the analyzed posts were counted and classified into 6 categories: medication name, mental disorder, self-harm, buying and selling, community formation, and others.
RESULTS: Out of 961 identified posts, 549 were included for analysis. Of these posts, 119 (21.7%) referenced self-administration, and 237 (43.2%; buying: n=67, 12.2%; selling: n=170, 31.0%) referenced transactions. Among these 237 posts, 1041 medication names were mentioned, exhibiting a >5-fold increase from the study in March 2021. Categorization based on the ATC classification predominantly revealed nervous system drugs, representing 82.1% (n=855) of the mentioned medications, consistent with the previous survey. Of note, the diversity of medications has expanded to include medications that have not been approved by the Japanese government. Interestingly, OTC medications were frequently mentioned in self-administration posts (odds ratio 23.6, 95% CI 6.93-80.15). Analysis of hashtags (n=866) revealed efforts to foster community connections among users.
CONCLUSIONS: This study highlighted the escalating complexity of trading of illegal prescription medication facilitated by X posts. Regulatory measures to enhance public awareness should be considered to prevent illegal transactions, which may ultimately lead to misuse or abuse such as overdose. Along with such pharmacovigilance measures, social approaches that could direct individuals to appropriate medical or psychiatric resources would also be beneficial as our hashtag analysis shed light on the formation of a cohesive or closed community among users.