Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 143
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 143
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 209
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 994
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3134
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 574
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 488
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Non-medical use of prescription medications is a serious public health crisis. The black market for prescription medications should be routinely surveyed to encourage their appropriate use. Herein, we focused on Twitter to investigate the possibility of illicit drug trading in Japan. From March 1 to 8, 2021, we examined the characteristics of Twitter posts, identified using the search term "Okusuri Mogu Mogu", a Japanese argot used for trading of medications. The captured data included the date of the posts, whether with a hashtag was used, an indication of the trades type (buy, sell, self-administration, and unknown), and the name of the mentioned pharmaceutical products. The number of named medications in the posts was counted and further categorized according to the Anatomical Therapeutic Chemical (ATC) classification. Two hundred and thirty-eight posts were identified with the searching term "Okusuri Mogu Mogu", of which 154 (64.7%) named specific medications. Of note, 73 posts (30.7%) were associated with buying or selling medications. We examined the 73 posts. These posts included 118 medications (26 types), of which 107 (88.4%) were classified as nervous system drugs. Hypnotics and sedatives were the most frequently mentioned medications. The present study sheds light on pharmaceutical medication trading via Twitter. Reinforcing the surveillance practices or cracking down on traders by authorities may be insufficient. We consider the possible effectiveness of socially supportive approaches to help those who lack support to access the appropriate psychiatric care.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1248/yakushi.22-00048 | DOI Listing |
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