Illicit Trade of Prescription Medications Through X (Formerly Twitter) in Japan: Cross- Sectional Study

被引:1
作者
Hakariya, Hayase [1 ,2 ]
Yokoyama, Natsuki [2 ,3 ]
Lee, Jeonse [2 ,4 ]
Hakariya, Arisa [2 ,5 ]
Ikejiri, Tatsuki [2 ]
机构
[1] Univ Tubingen, Interfac Inst Biochem, Morgenstelle 15, Tubingen D-72076, Germany
[2] Lab Human Nat Cultures & Med, Hikone, Shiga, Japan
[3] Chubu Tokushukai Hosp, Dept Pharm, Kitanakagusuku, Okinawa, Japan
[4] Kyoto Prefectural Univ Med, Sch Med, Kyoto, Japan
[5] Minami Seikyo Hosp, Gen Hosp, Nagoya, Aichi, Japan
关键词
illegal trading; pharmacovigilance; social networking service; SNS; overdose; social support; antipsychotics; Japan; prescriptionmedication; cross-sectional study; prescription drug; social networking; medication; pharmaceutical; pharmaceutical drugs; Japanese; psychiatric; support; PHARMACEUTICAL PRODUCTS; RESPONSES; MISUSE;
D O I
10.2196/54023
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
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 marketapplications, 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-usinga specific keyword ("Okusuri Mogu Mogu"), has emerged on X (formerly Twitter). Hence, these dynamic methods of illicittrading 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 MoguMogu" 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 oftheir contents: buying, selling, self-administration, heads-up, and others. Among posts categorized as buying, selling, andself-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: medicationname, 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 medicationnames were mentioned, exhibiting a >5-fold increase from the study in March 2021. Categorization based on the ATC classificationpredominantly revealed nervous system drugs, representing 82.1% (n=855) of the mentioned medications, consistent with theprevious survey. Of note, the diversity of medications has expanded to include medications that have not been approved by theJapanese 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 Xposts. Regulatory measures to enhance public awareness should be considered to prevent illegal transactions, which may ultimatelylead to misuse or abuse such as overdose. Along with such pharmacovigilance measures, social approaches that could directindividuals to appropriate medical or psychiatric resources would also be beneficial as our hashtag analysis shed light on theformation of a cohesive or closed community among users
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页数:11
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