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

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

Hookah-related Twitter chatter: A content analysis

INTRODUCTION: Hookah smoking is becoming increasingly popular among young adults and is often perceived as less harmful than cigarette use. Prior studies show that it is common for youth and young adults to network about substance use behaviors on social media. Social media messages about hookah could influence its use among young people. We explored normalization or discouragement of hookah smoking, and other common messages about hookah on Twitter. METHODS: From the full stream of tweets posted on Twitter from April 12, 2014, to May 10, 2014 (approximately 14.5 billion tweets), all tweets containing the terms hookah, hooka, shisha, or sheesha were collected (n = 358,523). The hookah tweets from Twitter users (tweeters) with high influence and followers were identified (n = 39,824) and a random sample of 5,000 tweets was taken (13% of tweets with high influence and followers). The sample of tweets was qualitatively coded for normalization (ie, makes hookah smoking seem common and normal or portrays positive experiences with smoking hookah) or discouragement of hookah smoking, and other common themes using crowdsourcing. RESULTS: Approximately 87% of the sample of tweets normalized hookah use, and 7% were against hookah or discouraged its use. Nearly half (46%) of tweets that normalized hookah indicated that the tweeter was smoking hookah or wanted to smoke hookah, and 19% were advertisements/promotions for hookah bars or products. CONCLUSION: Educational campaigns about health harms from hookah use and policy changes regarding smoke-free air laws and tobacco advertising on the Internet may be useful to help offset the influence of pro-hookah messages seen on social media

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

It\u27s way more than just writing a prescription : A qualitative study of preferences for integrated versus non-integrated treatment models among individuals with opioid use disorder

BACKGROUND: Increasingly, treatment for opioid use disorder (OUD) is offered in integrated treatment models addressing both substance use and other health conditions within the same system. This often includes offering medications for OUD in general medical settings. It remains uncertain whether integrated OUD treatment models are preferred to non-integrated models, where treatment is provided within a distinct treatment system. This study aimed to explore preferences for integrated versus non-integrated treatment models among people with OUD and examine what factors may influence preferences. METHODS: This qualitative study recruited participants (n = 40) through Craigslist advertisements and flyers posted in treatment programs across the United States. Participants were 18 years of age or older and scored a two or higher on the heroin or opioid pain reliever sections of the Tobacco, Alcohol, Prescription Medications, and Other Substances (TAPS) Tool. Each participant completed a demographic survey and a telephone interview. The interviews were coded and content analyzed. RESULTS: While some participants preferred receiving OUD treatment from an integrated model in a general medical setting, the majority preferred non-integrated models. Some participants preferred integrated models in theory but expressed concerns about stigma and a lack of psychosocial services. Tradeoffs between integrated and non-integrated models were centered around patient values (desire for anonymity and personalization, fear of consequences), the characteristics of the provider and setting (convenience, perceived treatment effectiveness, access to services), and the patient-provider relationship (disclosure, trust, comfort, stigma). CONCLUSIONS: Among this sample of primarily White adults, preferences for non-integrated versus integrated OUD treatment were mixed. Perceived benefits of integrated models included convenience, potential for treatment personalization, and opportunity to extend established relationships with medical providers. Recommendations to make integrated treatment more patient-centered include facilitating access to psychosocial services, educating patients on privacy, individualizing treatment, and prioritizing the patient-provider relationship. This sample included very few minorities and thus findings may not be fully generalizable to the larger population of persons with OUD. Nonetheless, results suggest a need for expansion of both OUD treatment in specialty and general medical settings to ensure access to preferred treatment for all

Risky sexual behaviors and sexually transmitted diseases: a comparison study of cocaine-dependent individuals in treatment versus a community-matched sample

Cocaine users routinely engage in high-risk sexual behaviors that place them at an elevated risk of contracting HIV and other blood-borne infections. The purpose of the present study was to compare trading sex for drugs and/or money, having 10 or more sexual partners in 1 year, and sexually transmitted diseases (STDs) of cocaine-dependent individuals in treatment for their dependence across race and gender and against participants who live in their community. Cocaine-dependent individuals (n = 459) were identified through nine publicly and privately funded inpatient and outpatient chemical dependency treatment centers in the St. Louis area during 2001–2006. Community-based participants (n = 459) were matched to cocaine-dependent participants on age, ethnicity, gender, and zip code of residence. Mean age of the sample was 36 years old, 50% were Caucasians, 50% were African American, and 47% were male. Nearly half of cocaine-dependent participants in treatment had traded sex for drugs and/or money and over one-third had more than 10 sexual partners in 1 year with a risk concentrated among African Americans even after controlling for income and educational attainment. Participants recruited from the community with some exposure to cocaine reported similar rates of high risk sexual behaviors as the cocaine dependent subjects from treatment settings. It is important for clinicians to recognize that once released from treatment, cocaine-dependent individuals may be returning to high-risk environments where sexual risk behaviors are occurring in the context of cocaine use

“It’s way more than just writing a prescription”: A qualitative study of preferences for integrated versus non-integrated treatment models among individuals with opioid use disorder

Background: Increasingly, treatment for opioid use disorder (OUD) is offered in integrated treatment models addressing both substance use and other health conditions within the same system. This often includes offering medications for OUD in general medical settings. It remains uncertain whether integrated OUD treatment models are preferred to non-integrated models, where treatment is provided within a distinct treatment system. This study aimed to explore preferences for integrated versus non-integrated treatment models among people with OUD and examine what factors may influence preferences. Methods: This qualitative study recruited participants (n = 40) through Craigslist advertisements and flyers posted in treatment programs across the United States. Participants were 18 years of age or older and scored a two or higher on the heroin or opioid pain reliever sections of the Tobacco, Alcohol, Prescription Medications, and Other Substances (TAPS) Tool. Each participant completed a demographic survey and a telephone interview. The interviews were coded and content analyzed. Results: While some participants preferred receiving OUD treatment from an integrated model in a general medical setting, the majority preferred non-integrated models. Some participants preferred integrated models in theory but expressed concerns about stigma and a lack of psychosocial services. Tradeoffs between integrated and non-integrated models were centered around patient values (desire for anonymity and personalization, fear of consequences), the characteristics of the provider and setting (convenience, perceived treatment effectiveness, access to services), and the patient-provider relationship (disclosure, trust, comfort, stigma). Conclusions: Among this sample of primarily White adults, preferences for non-integrated versus integrated OUD treatment were mixed. Perceived benefits of integrated models included convenience, potential for treatment personalization, and opportunity to extend established relationships with medical providers. Recommendations to make integrated treatment more patient-centered include facilitating access to psychosocial services, educating patients on privacy, individualizing treatment, and prioritizing the patient-provider relationship. This sample included very few minorities and thus findings may not be fully generalizable to the larger population of persons with OUD. Nonetheless, results suggest a need for expansion of both OUD treatment in specialty and general medical settings to ensure access to preferred treatment for all

Exploring social media recruitment strategies and preliminary acceptability of an mHealth tool for teens with eating disorders

(1) Background: The current study leveraged social media to connect with teens with EDs to identify population specific characteristics and to gather feedback on an mHealth intervention. (2) Methods: We recruited teens with EDs from social media in two phases: (1) Discovery Group, (2) Testing Group. The Discovery Group