Point-of-sale marketing and context of marijuana retailers: Assessing reliability and generalizability of the marijuana retail surveillance tool

As recreational marijuana expands, standardized surveillance measures examining the retail environment are critical for informing policy and enforcement. We conducted a reliability and generalizability study using a previously developed tool involving assessment of a sample of 25 randomly selected Seattle recreational marijuana retailers (20 recreational; 5 recreational/medical) in 2017. The tool assessed: 1) contextual/neighborhood features (i.e., facilities nearby); 2) compliance/security (e.g., age-of-sale signage, age verification); and 3) marketing (i.e., promotions, product availability, price). We found that retailers were commonly within two blocks of restaurants (n = 23), grocery stores (n = 17), liquor stores (n = 13), and bars/clubs (n = 11). Additionally, two were within two blocks of schools, and four were within two blocks of parks. Almost all (n = 23) had exterior signage indicating the minimum age requirement, and 23 verified age. Two retailers had exterior ads for marijuana, and 24 had interior ads. Overall, there were 76 interior ads (M = 3.04; SD = 1.84), most commonly for edibles (n = 28). At least one price promotion/discount was recorded in 17 retailers, most commonly in the form of loyalty membership programs (n = 10) or daily/weekly deals (n = 10). One retailer displayed potential health harms/warnings, while three posted some health claim. Products available across product categories were similar; we also noted instances of selling retailer-branded apparel/ paraphernalia (which is prohibited). Lowest price/unit across product categories demonstrated low variability across retailers. This study documented high inter-rater reliability of the surveillance tool (Kappas = 0.73 to 1.00). In conclusion, this tool can be used in future research and practice aimed at examining retailers marketing practices and regulatory compliance. Keywords: Marijuana use, Retail environment, Marketing, Recreational marijuana, Measure developmen

Characterizing the Followers and Tweets of a Marijuana-Focused Twitter Handle

BACKGROUND: Twitter is a popular social media forum for sharing personal experiences, interests, and opinions. An improved understanding of the discourse on Twitter that encourages marijuana use can be helpful for tailoring and targeting online and offline prevention messages. OBJECTIVES: The intent of the study was to assess the content of “tweets” and the demographics of followers of a popular pro-marijuana Twitter handle (@stillblazingtho). METHODS: We assessed the sentiment and content of tweets (sent from May 1 to December 31, 2013), as well as the demographics of consumers that follow a popular pro-marijuana Twitter handle (approximately 1,000,000 followers) using Twitter analytics from Demographics Pro. This analytics company estimates demographic characteristics based on Twitter behavior/usage, relying on multiple data signals from networks, consumption, and language and requires confidence of 95% or above to make an estimate of a single demographic characteristic. RESULTS: A total of 2590 tweets were sent from @stillblazingtho during the 8-month period and 305 (11.78%) replies to another Twitter user were excluded for qualitative analysis. Of the remaining 2285 tweets, 1875 (82.06%) were positive about marijuana, 403 (17.64%) were neutral, and 7 (0.31%) appeared negative about marijuana. Approximately 1101 (58.72%) of the positive marijuana tweets were perceived as jokes or humorous, 340 (18.13%) implied that marijuana helps you to feel good or relax, 294 (15.68%) mentioned routine, frequent, or heavy use, 193 (10.29%) mentioned blunts, marijuana edibles, or paraphernalia (eg, bongs, vaporizers), and 186 (9.92%) mentioned other risky health behaviors (eg, tobacco, alcohol, other drugs, sex). The majority (699,103/959,143; 72.89%) of @stillblazingtho followers were 19 years old or younger. Among people ages 17 to 19 years, @stillblazingtho was in the top 10% of all Twitter handles followed. More followers of @stillblazingtho in the United States were African American (323,107/759,407; 42.55%) or Hispanic (90,732/759,407; 11.95%) than the Twitter median average (African American 22.4%, inter-quartile ratio [IQR] 5.1-62.5%; Hispanic 5.4%, IQR 3.0-10.8%) and among Hispanics, @stillblazingtho was in the top 30% of all Twitter handles followed. CONCLUSIONS: Young people are especially responsive to social media influences and often establish substance use patterns during this phase of development. Our findings underscore the need for surveillance efforts to monitor the pro-marijuana content reaching young people on Twitter

A content analysis of vaping advertisements on Twitter, November 2014

INTRODUCTION: Vaping has increased in popularity, and the potential harms and benefits are largely unknown. Vaping-related advertising is expected to grow as the vaping industry grows; people are exposed primarily to vaping advertisements on the Internet, and Twitter is an especially popular social medium among young people. The primary objective of our study was to describe the characteristics of vaping-related advertisements on Twitter. METHODS: We collected data on 403,079 English-language tweets that appeared during November 2014 and contained vaping-related keywords. Using crowdsourcing services, we identified vaping-related advertisements in a random sample of 5,000 tweets. The advertisement tweets were qualitatively coded for popular marketing tactics by our research team. We also inferred the demographic characteristics of followers of 4 Twitter handles that advertised various novel vape products. RESULTS: The random sample of 5,000 vaping-related tweets included 1,156 (23%) advertisement tweets that were further analyzed. Vape pens were advertised in nearly half of the advertisement tweets (47%), followed by e-juice (21%), which commonly mentioned flavors (42%). Coupons or price discounts were frequently observed (32%); only 3% of tweets mentioned vaping as a way to quit smoking or as an alternative to smoking. One handle had a disproportionately high percentage of racial/ethnic minority followers. CONCLUSION: Vaping poses a threat to smoking prevention progress, and it is important for those in tobacco control to understand and counter the tactics used by vaping companies to entice their consumers, especially on social media where young people can easily view the content

“I just want to be skinny.”: A content analysis of tweets expressing eating disorder symptoms

There is increasing concern about online communities that promote eating disorder (ED) behaviors through messages and/or images that encourage a “thin ideal” (i.e., promotion of thinness as attractive) and harmful weight loss/weight control practices. The purpose of this paper is to assess the content of body image and ED-related content on Twitter and provide a deeper understanding of EDs that may be used for future studies and online-based interventions. Tweets containing ED or body image-related keywords were collected from January 1-January 31, 2015 (N = 28,642). A random sample (n = 3000) was assessed for expressions of behaviors that align with subscales of the Eating Disorder Examination (EDE) 16.0. Demographic characteristics were inferred using a social media analytics company. The comprehensive research that we conducted indicated that 2,584 of the 3,000 tweets were ED-related; 65% expressed a preoccupation with body shape, 13% displayed issues related to food/eating/calories, and 4% expressed placing a high level of importance on body weight. Most tweets were sent by girls (90%) who were ≤19 years old (77%). Our findings stress a need to better understand if and how ED-related content on social media can be used for targeting prevention and intervention messages towards those who are in-need and could potentially benefit from these efforts.</div

Declines in prevalence of adolescent substance use disorders and delinquent behaviors in the USA: A unitary trend?

AbstractBackgroundDownward trends in a number of adolescent risk behaviors including violence, crime, and drug use have been observed in the USA in recent years. It is unknown whether these are separate trends or whether they might relate to a general reduction in propensity to engage in such behaviors. Our objectives were to quantify trends in substance use disorders (SUDs) and delinquent behaviors over the 2003–2014 period and to determine whether they might reflect a single trend in an Externalizing-like trait.MethodsWe analyzed data from 12 to 17 year old participants from the National Survey on Drug Use and Health, a representative survey of the household dwelling population of the USA, across the 2003–2014 period (N = 210 599). Outcomes included past-year prevalence of six categories of substance use disorder and six categories of delinquent behavior.ResultsTrend analysis suggested a net decline of 49% in mean number of SUDs and a 34% decline in delinquent behaviors over the 12-year period. Item Response Theory models were consistent with the interpretation that declines in each set of outcomes could be attributed to changes in mean levels of a latent, Externalizing-like trait.ConclusionsOur findings suggest that declines in SUDs and some delinquent behaviors reflect a single trend related to an Externalizing-like trait. Identifying the factors contributing to this trend may facilitate continued improvement across a spectrum of adolescent risk behaviors.</jats:sec

Text messages exchanged between individuals with opioid use disorder and their mHealth e-coaches: Content analysis study

BACKGROUND: Opioid use disorder (OUD) has affected 2.2 million people in the United States. About 7.2 million people reported using illicit drugs in 2019, which contributed to over 70,000 overdose deaths. SMS text messaging interventions have been shown to be effective in OUD recovery. However, the interpersonal communication between individuals in OUD treatment and a support team on digital platforms has not been well examined. OBJECTIVE: This study aims to understand the communication between participants undergoing OUD recovery and their e-coaches by examining the SMS text messages exchanged from the lens of social support and the issues related to OUD treatment. METHODS: A content analysis of messages exchanged between individuals recovering from OUD and members of a support team was conducted. Participants were enrolled in a mobile health intervention titled uMAT-R, a primary feature of which is the ability for patients to instantly connect with a recovery support staff or an e-coach via in-app messaging. Our team analyzed dyadic text-based messages of over 12 months. In total, 70 participants\u27 messages and 1196 unique messages were analyzed using a social support framework and OUD recovery topics. RESULTS: Out of 70 participants, 44 (63%) were between the ages of 31 and 50 years, 47 (67%) were female, 41 (59%) were Caucasian, and 42 (60%) reported living in unstable housing conditions. An average of 17 (SD 16.05) messages were exchanged between each participant and their e-coach. Out of 1196 messages, 64% (n=766) messages were sent by e-coaches and 36% (n=430) by participants. Messages of emotional support occurred the most, with 196 occurrences (n=9, 0.8%) and e-coaches (n=187, 15.6%). Messages of material support had 110 occurrences (participants: n=8, 0.7%; e-coaches: n=102, 8.5%). With OUD recovery topics, opioid use risk factors appeared in most (n=72) occurrences (patient: n=66, 5.5%; e-coach: n=6, 0.5%), followed by a message of avoidance of drug use 3.9% (n=47), which occurred mainly from participants. Depression was correlated with messages of social support (r=0.27; P=.02). CONCLUSIONS: Individuals with OUD who had mobile health needs tended to engage in instant messaging with the recovery support staff. Participants who are engaged in messaging often engage in conversations around risk factors and avoidance of drug use. Instant messaging services can be instrumental in providing the social and educational support needs of individuals recovering from OUD

Topics and sentiment surrounding vaping on Twitter and Reddit during the 2019 e-cigarette and vaping use-associated lung injury outbreak: Comparative study

BACKGROUND: Vaping or e-cigarette use has become dramatically more popular in the United States in recent years. e-Cigarette and vaping use-associated lung injury (EVALI) cases caused an increase in hospitalizations and deaths in 2019, and many instances were later linked to unregulated products. Previous literature has leveraged social media data for surveillance of health topics. Individuals are willing to share mental health experiences and other personal stories on social media platforms where they feel a sense of community, reduced stigma, and empowerment. OBJECTIVE: This study aimed to compare vaping-related content on 2 popular social media platforms (ie, Twitter and Reddit) to explore the context surrounding vaping during the 2019 EVALI outbreak and to support the feasibility of using data from both social platforms to develop in-depth and intelligent vaping detection models on social media. METHODS: Data were extracted from both Twitter (316,620 tweets) and Reddit (17,320 posts) from July 2019 to September 2019 at the peak of the EVALI crisis. High-throughput computational analyses (sentiment analysis and topic analysis) were conducted. In addition, in-depth manual content analyses were performed and compared with computational analyses of content on both platforms (577 tweets and 613 posts). RESULTS: Vaping-related posts and unique users on Twitter and Reddit increased from July 2019 to September 2019, with the average post per user increasing from 1.68 to 1.81 on Twitter and 1.19 to 1.21 on Reddit. Computational analyses found the number of positive sentiment posts to be higher on Reddit (P\u3c.001, 95% CI 0.4305-0.4475) and the number of negative posts to be higher on Twitter (P\u3c.001, 95% CI -0.4289 to -0.4111). These results were consistent with the clinical content analyses results indicating that negative sentiment posts were higher on Twitter (273/577, 47.3%) than Reddit (184/613, 30%). Furthermore, topics prevalent on both platforms by keywords and based on manual post reviews included mentions of youth, marketing or regulation, marijuana, and interest in quitting. CONCLUSIONS: Post content and trending topics overlapped on both Twitter and Reddit during the EVALI period in 2019. However, crucial differences in user type and content keywords were also found, including more frequent mentions of health-related keywords on Twitter and more negative health outcomes from vaping mentioned on both Reddit and Twitter. Use of both computational and clinical content analyses is critical to not only identify signals of public health trends among vaping-related social media content but also to provide context for vaping risks and behaviors. By leveraging the strengths of both Twitter and Reddit as publicly available data sources, this research may provide technical and clinical insights to inform automatic detection of social media users who are vaping and may benefit from digital intervention and proactive outreach strategies on these platforms

The utility of Google Trends data to examine interest in cancer screening

OBJECTIVES: We examined the utility of January 2004 to April 2014 Google Trends data from information searches for cancer screenings and preparations as a complement to population screening data, which are traditionally estimated through costly population-level surveys. SETTING: State-level data across the USA. PARTICIPANTS: Persons who searched for terms related to cancer screening using Google, and persons who participated in the Behavioral Risk Factor Surveillance System (BRFSS). PRIMARY AND SECONDARY OUTCOME MEASURES: (1) State-level Google Trends data, providing relative search volume (RSV) data scaled to the highest search proportion per week (RSV100) for search terms over time since 2004 and across different geographical locations. (2) RSV of new screening tests, free/low-cost screening for breast and colorectal cancer, and new preparations for colonoscopy (Prepopik). (3) State-level breast, cervical, colorectal and prostate cancer screening rates. RESULTS: Correlations between Google Trends and BRFSS data ranged from 0.55 for ever having had a colonoscopy to 0.14 for having a Pap smear within the past 3 years. Free/low-cost mammography and colonoscopy showed higher RSV during their respective cancer awareness months. RSV for Miralax remained stable, while interest in Prepopik increased over time. RSV for lung cancer screening, virtual colonoscopy and three-dimensional mammography was low. CONCLUSIONS: Google Trends data provides enormous scientific possibilities, but are not a suitable substitute for, but may complement, traditional data collection and analysis about cancer screening and related interests