How can I buy cocaine online in Er-Rayyan

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How can I buy cocaine online in Er-Rayyan

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How can I buy cocaine online in Er-Rayyan

Official websites use. Share sensitive information only on official, secure websites. Correspondence , Brienna N. Email: b. We aimed to summarize how content related to substances is portrayed on various social media platforms. A total of Sentiment regarding opiate use however was commonly negative Most studies identified themes relating to Health, Safety and Harms The large public presence of this content may have concerning influences on attitudes, behaviours and risk perceptions relating to substance use, particularly among the most vulnerable and heaviest users of social media—adolescents and young adults. Public access to the internet and digital communication services such as email in the s \[ 4 \] paved the way for social media platforms, which attracted millions of users and changed the way individuals communicate and interact \[ 5 \]. Global social media use has grown from 1 million monthly active users in \[ 6 \] to over 3. Fuelled by the proliferation of smartphones \[ 4 \], social media platforms have become integral to the daily lives of adolescents and young adults \[ 8 \], with research demonstrating that adolescents spend an average of 8 hours per day online \[ 9 \]. Adolescents who are regularly active on social media have a greater likelihood of subsequent tobacco or cannabis use initiation \[ 14 \]. Lower danger perceptions have been associated with increased substance use among adolescents \[ 16 \]. High frequency viewers also had increased perceptions of substance use acceptability and greater likelihood to initiate use \[ 15 \]. The exclusion criteria were: i commentaries, randomised controlled trials, case reports, literature reviews, conference proceedings or letters to the editor; and ii studies only assessing exposure to social media or its content, assessing the efficacy of automated content extraction tools, assessing social network demographics or assessing online reactions to traditional media content or proposed legislation rather than the substance itself. A comprehensive search was conducted in the databases of PubMed, Scopus, PsycINFO and Web of Science in April of to identify relevant research published since reflective of the rise in social media use. Additional relevant research was identified by checking the reference lists of included studies and from other reviews. Search strings can be found in the supporting information. Five reviewers B. Each title and abstract was screened twice, and any discrepancies were resolved through verbal discussion between researchers. Finally, the full text of articles were evaluated by two researchers B. The following study characteristics and outcomes were extracted by two researchers B. These data were independently extracted by two reviewers. Any discrepancies were resolved through discussion until consensus was achieved. For each substance category, reported sentiment data was extracted. The sentiment data was totalled to indicate the percentage of social media content reflective of positive, negative or neutral attitudes Supporting information Table S1 for definitions. We extracted the theme categories identified in the content analyses of included studies and totalled the number of studies, which identified those themes to indicate the proportion of content available on social media that was reflective of these themes. Sentiments and themes were analysed within each of the social media platforms individually. Studies were assessed by one reviewer B. This question set required reviewers to determine whether: i the approach was appropriate given the research question; ii were the data collection methods adequate, iii were the findings adequately derived from data; iv was the interpretation sufficiently substantiated; and v was there coherence between each of these areas? Reviewer responses were tabulated in a Google Sheet document. Consensus was then achieved through discussion. Characteristics of the included studies, and quality, can be found in Supporting information Table S2. Manual coding was the most common method, and typically involved one or more human coders categorizing data thematically and sentimentally using a codebook derived from data subsets. Disagreements between coders were resolved through discussion to reach consensus. Machine learning involved the use of algorithms, refined by manual coding of data subsets, to automatically code data via computer program. There was no difference in findings from manually coded and machine learning samples. Account type was usually informed by data found in account profiles e. Demographics Pro. Commercial accounts were identified in Public health or education organisations were identified as content sources in Government entities were identified in 5. A further Specific values for each sentiment category can be found in Table 1. Further information on the proportion of studies that identified other theme categories can be found in Table 2. Similar trends were identified for alcohol Sentiments toward opiate use were predominantly negative Ultimately, negative sentiment was expressed in Across all substance types, themes relating to Health, Safety and Harms were most prominent Themes relating to Use Similar trends were identified for tobacco Negative sentiment was expressed in only 7. Themes relating to Informative content were most common Negative sentiment was expressed in only 3. Use Health, Safety and Harms Themes relating to Attitudes Entertainment Personal accounts typically expressed positive sentiments toward substance use and shared content relating to Informative or Entertaining themes. This is likely attributable to increased perceptions of source credibility and authenticity in comparison to commercial information sources \[ 93 , 94 \]. Activity from public health and educational organisation account types represented less than These accounts primarily shared content that was thematically Informative or related to Health, Safety and Harms associated with substance use. Public health and educational organisations were the predominant account type responsible for the disseminating content coded under these themes. The availability of information discussing the potential health effects of substance use is likely to influence individuals' risk perceptions regarding substance use \[ 95 \]. Content relating to Health, Safety, and Harms was identified across all social media platforms, indicating that public health and educational messaging regarding the potential health impacts of substance use is becoming more broadly accessible online. Although the substances depicted are classified as legal, this does not mean that there are no risks associated with regular use. Given the large presence of youth on social media \[ 12 \] and the popularity of YouTube, Instagram, TikTok and Facebook among this population \[ 96 , 97 \], promotional content may encourage youth to experiment with or initiate substance use behaviours without appropriately recognising associated risks of use. Themes categorised as Informative included tutorial style content such as DIYs, vape modification and recipes, as well as dosage recommendations, use guidelines and discussions of personal use experiences. Research has shown that exposure to social media content that informs on shared interests such as substance use has significant influence on personal and societal risk perceptions, as well as behavioural intentions \[ 98 \]. The pattern of positive sentiment was evident across all platforms and substance types, excluding opiate use, which was predominantly depicted negatively. Accounts with vested interests in the promotion of substance use e. As previously stated, viewers are more likely to be persuaded by peers and view their messages as more credible than other online sources \[ 92 , 93 , 94 \]. Negative sentiments were more common in content produced by medical professionals or media accounts. Public health and educational organisations and government entities were predominantly neutral in their sentiments toward substance use, most likely because of the desire not to villainise substance use, but to educate the public about possible associated risks \[ 99 \]. Promotional material was identified in nearly all included studies. Further research should investigate whether intrapersonal factors of viewers and content format may moderate the relationship between exposure and influence on psychosocial factors associated with substance use. In comparison to other social media platform data, Twitter data is relatively easy for researchers to access using its academic research application portal \[ \]. Licit substances are also more likely to be discussed openly on social media platforms because of the unlikely risk of criminal or legal consequences from posting content relating to these substances. A further limitation of the current body of literature is many of the included studies did not collect metadata information e. Content with high metadata values is more likely to be seen and shared among social media users, and therefore, may have a higher influence regardless of whether it is promoting or discouraging substance use. The large public presence of this content may have negative influences on attitudes, behaviours and risk perceptions relating to substance use, particularly among adolescents and young adults who are the primary users of social media. Social media platforms should consider introducing regulations regarding the marketing of substances online that enhance current practices. Although many platforms take an official zero tolerance policy to content that promotes or attempts to distribute drugs, tobacco and alcohol \[ \], promotional content continues to proliferate on social media \[ \]. Current regulatory efforts, such as the removal of explicit hashtags e. Carmen Lim: Conceptualization; data curation; investigation; methodology. Benjamin Johnson: Formal analysis; investigation. Brandon Cheng: Data curation; investigation; methodology. Jack Chung: Data curation; investigation. Sandy Huang: Data curation; formal analysis. Janni Leung: Supervision. Gary Chan: Conceptualization; project administration; supervision. TurntTrending: a systematic review of substance use portrayals on social media platforms. This section collects any data citations, data availability statements, or supplementary materials included in this article. As a library, NLM provides access to scientific literature. Find articles by Brienna N Rutherford. Find articles by Carmen C W Lim. Find articles by Benjamin Johnson. Find articles by Brandon Cheng. Find articles by Jack Chung. Find articles by Sandy Huang. Find articles by Tianze Sun. Find articles by Janni Leung. Find articles by Gary C K Chan. Open in a new tab. NS indicates that data for this column was not stated. Theme categories Studies, No. Click here for additional data file. Similar articles. Add to Collections. Create a new collection. Add to an existing collection. Choose a collection Unable to load your collection due to an error Please try again. Add Cancel.

How can I buy cocaine online in Er-Rayyan