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Introduction Alcohol and tobacco are commonly used together. Social influences within online social networking platforms contribute to youth and young adult substance use behaviors. This study used a sample of alcohol- and tobacco-related tweets to evaluate: (1) sentiment toward co-use of alcohol and tobacco, (2) increased susceptibility to tobacco use when consuming alcohol, and (3) the role of alcohol in contributing to a failed attempt to quit tobacco use. Methods Data were collected from the Twitter API from January 1, 2019 through December 31, 2019 using tobacco-related keywords (e.g., vape, ecig, smoking, juul*) and alcohol-related filters (e.g., drunk, blackout*). A total of 78,235 tweets were collected, from which a random subsample (n = 1,564) was drawn for coding. Cohen’s Kappa values ranged from 0.66 to 0.99. Results Most tweets were pro co-use of alcohol and tobacco (75%). One of every ten tweets reported increased susceptibility to tobacco use when intoxicated. Non-regular tobacco users reported cravings for and tobacco use when consuming alcohol despite disliking tobacco use factors such as the taste, smell, and/or negative health effects. Regular tobacco users reported using markedly higher quantities of tobacco when intoxicated. Individuals discussed the role of alcohol undermining tobacco cessation attempts less often (2.0%), though some who had quit smoking for prolonged periods of time reported reinitiating tobacco use during acute intoxication episodes. Conclusions Tobacco cessation interventions may benefit from including alcohol-focused components designed to educate participants about the association between increased susceptibility to tobacco use when consuming alcohol and the role of alcohol in undermining tobacco cessation attempts. Implications Sentiment toward co-use of alcohol and tobacco on Twitter is largely positive. Individuals reported regret about using tobacco, or using more than intended, when intoxicated. Those who had quit smoking or vaping for prolonged periods of time reported reinitiating tobacco use when consuming alcohol. While social media-based tobacco cessation interventions like the Truth Initiative’s “Ditch the Juul” campaign demonstrate potential to change tobacco use behaviors, these campaigns may benefit from including alcohol-focused components designed to educate participants about the association between increased susceptibility to tobacco use when consuming alcohol and the role of alcohol in undermining tobacco cessation attempts.

OBJECTIVE: The purpose of this study was to characterize the content and themes present in user-generated TikTok videos portraying alcohol. METHOD: We captured the 100 most popular videos including the #alcohol hashtag on the popular social networking site TikTok. We used an iterative process to codebook development, resulting in codes for user sentiment toward alcohol, type of alcohol depicted, brand references, degree of alcohol use, and positive/negative associations with alcohol use. Videos were independently double coded, evaluated for inter-rater agreement, and adjudicated if differences were present. RESULTS: The videos in our sample were collectively viewed 291,999,100 times. The vast majority (98%) of videos expressed pro-alcohol sentiment. Nearly half of videos (41%) were guide videos demonstrating drink recipes. The majority of videos (72%) included liquor. Consuming multiple drinks quickly was depicted in more than half of videos (61%), whereas intoxication (13%) was exhibited less frequently. Positive associations with alcohol were prevalent; 69% of videos conveyed positive experiences with alcohol, 55% of videos contained humor, and 45% included associations of alcohol with camaraderie. Negative associations with alcohol were rarely portrayed (4%). CONCLUSIONS: Top alcohol-related videos on TikTok are heavily viewed. Their contents demonstrate a propensity to promote rapid consumption of multiple drinks and to juxtapose alcohol use with positive associations such as humor and camaraderie, while rarely depicting negative outcomes associated with hazardous alcohol use.

INTRODUCTION: Previous studies have demonstrated cross-sectional associations between social media use and depression, but their temporal and directional associations have not been reported. METHODS: In 2018, participants aged 18–30 years were recruited in proportion to U.S. Census characteristics, including age, sex, race, education, household income, and geographic region. Participants self-reported social media use on the basis of a list of the top 10 social media networks, which represent >95% of social media use. Depression was assessed using the 9-Item Patient Health Questionnaire. A total of 9 relevant sociodemographic covariates were assessed. All measures were assessed at both baseline and 6-month follow-up. RESULTS: Among 990 participants who were not depressed at baseline, 95 (9.6%) developed depression by follow-up. In multivariable analyses conducted in 2020 that controlled for all covariates and included survey weights, there was a significant linear association (p

The impact of social media interactions on mental health is not fully understood, despite increasing use. This qualitative investigation explored positive and negative effects of social media for individuals with and without depressive symptoms. The authors conducted an online survey of US adults ages 18–30 in March 2018. Two open-ended questions assessed participants’ self-report of positive and negative effects of social media on their lives. The 9-item Patient Health Questionnaire was used to select a purposeful random subsample of 50 participants with severe depressive symptoms (scores ranging from 20 to 27) and 50 without depressive symptoms (scores ranging from 0 to 4). Authors used content analysis to systematically identify codes in participants’ responses and compare frequency and context between groups. Sixteen themes emerged, of which 9 were positive and 7 were negative. For all participants, connection with others and exposure to negativity were the most frequently mentioned positive and negative effects, respectively. Whereas positive effects of social media were reported with similar frequency between depressed and non-depressed participants, more variation was observed in reports of negative effects between the two groups. Social media was noted as a distraction from real life more often by non-depressed than depressed participants. Judgment was mentioned solely by depressed participants. It may be valuable for future research to utilize more interactive qualitative methodologies such as web-based focus groups or one-on-one semi-structured interviews that allow for elaboration and clarification to more fully understand the nuances related to both positive and negative social media experiences and the effects on young adults’ well-being.

Objectives We sought to examine the association of positive and negative experiences using social media (SM) and sleep disturbance in a national survey of U.S. young adults. Methods Experiences using SM were assessed with 2 items asking participants about the percentage of time using SM that involved a negative/positive experience that they were personally involved in. Sleep disturbance was assessed using the validated PROMIS 4-item short form. Ordinal logistic regression was used to examine associations between positive and negative SM experiences and high sleep disturbance, while controlling for relevant covariates. Results Although reporting high levels of negative experiences was significantly associated with greater odds of high sleep disturbance (AOR = 1.49, 95%CI = 1.18-1.89), reporting high levels of positive experiences was not associated with sleep disturbance. Conclusions These findings suggest that more robust examinations of negative SM experiences—especially as they relate to sleep disturbance—may be warranted.

Young adults use social media (SM) to share life events, including loss of loved ones. In a national sample of U.S. young adults (n = 1,119), “grievers” were identified as those who had experienced...

We aimed to assess associations between parental social media comparison (PSMC)—the degree to which individuals compare their parenting with others on social media (SM)—and depressive symptoms. In March 2018 we conducted a survey of 528 parents ages 18-30 with children under the age of 18. Participants were asked about SM use, PSMC, and depressive symptoms. PSMC was measured with 7 Likert-type items that asked participants the extent to which they agreed or disagreed with statements such as “Based on their posts, other parents on social media appear to provide a better social life for their children than I do.” Depressive symptoms were measured using the Patient Health Questionnaire (PHQ-9). Multivariable ordered logistic regression models were used to assess the association between PSMC and depressive symptoms while controlling for SM use, parent adverse childhood experiences, parent age, gender, race/ethnicity, relationship status, employment status and household income, age of oldest child, and number of children. The PSMC was internally consistent (α = 0.94). In multivariable models, after adjusting for all covariates, there was 51% greater odds of elevated depressive symptoms (AOR = 1.51, 95% CI [1.33, 1.71]) for every one-point increase on the PSMC scale. In conclusion, the PSMC is independently associated with elevated depressive symptoms among parents. Future research should assess directionality of these associations and further explore parents’ experiences of comparison with others on SM.

Previous research suggests that television programming may influence viewers' health-related knowledge, perceptions, and behaviors but has yet to examine patient-provider interactions on the most popular primetime television programs. We aimed to characterize the frequency and nature of patient-centered communication (PCC) behaviors on these programs, as cultivation and social cognitive theories suggest that these depictions may influence viewers' expectations of real-life health-care experiences. We examined 203 patient-provider interactions across 84 episodes of 22 primetime television programs-both medical and non-medical-that aired during the spring of 2016 and spring of 2017. Each interaction was analyzed for the presence of 21 optimal PCC behaviors. This study found that the most frequently observed PCC behaviors focused on the provider making good eye contact and displaying good manners. However, PCC behaviors related to managing patient uncertainty and self-management were rare. Overall, providers in medical programs were significantly more likely to exhibit certain PCC behaviors, such as asking a patient questions, having good manners, and self-disclosing personal information, compared to providers in non-medical programs. Implications of these findings include the potential for such depictions to influence patient expectations of real-life experiences and health outcomes. Future research is needed to examine these potential influences.

BACKGROUND Electronic nicotine delivery systems (known as electronic cigarettes or e-cigarettes) increase risk for adverse health outcomes among naïve tobacco users, particularly youth and young adults. This vulnerable population is also at risk for exposed brand marketing and advertisement of e-cigarettes on social media. Understanding predictors of how e-cigarette manufacturers conduct social media advertising and marketing could benefit public health approaches to addressing e-cigarette use. OBJECTIVE This study documents factors that predict changes in daily frequency of commercial tweets about e-cigarettes using time series modeling techniques. METHODS We analyzed data on the daily frequency of commercial tweets about e-cigarettes collected between January 1, 2017, and December 31, 2020. We fit the data to an autoregressive integrated moving average (ARIMA) model and unobserved components model (UCM). Four measures assessed model prediction accuracy. Predictors in the UCM include days with events related to the US Food and Drug Administration (FDA), non-FDA-related events with significant importance such as academic or news announcements, weekday versus weekend, and the period when JUUL maintained an active Twitter account (ie, actively tweeting from their corporate Twitter account) versus when JUUL stopped tweeting. RESULTS When the 2 statistical models were fit to the data, the results indicate that the UCM was the best modeling technique for our data. All 4 predictors included in the UCM were significant predictors of the daily frequency of commercial tweets about e-cigarettes. On average, brand advertisement and marketing of e-cigarettes on Twitter was higher by more than 150 advertisements on days with FDA-related events compared to days without FDA events. Similarly, more than 40 commercial tweets about e-cigarettes were, on average, recorded on days with important non-FDA events compared to days without such events. We also found that there were more commercial tweets about e-cigarettes on weekdays than on weekends and more commercial tweets when JUUL maintained an active Twitter account. CONCLUSIONS e-Cigarette companies promote their products on Twitter. Commercial tweets were significantly more likely to be posted on days with important FDA announcements, which may alter the narrative about information shared by the FDA. There remains a need for regulation of digital marketing of e-cigarette products in the United States.

Introduction Aging is associated with subtle cognitive decline in attention, memory, executive function, processing speed, and reasoning. Although lower brain-derived neurotrophic factor (BDNF) has been linked to cognitive decline among older adults, it is not known if the association differs among individuals with various BDNF Val66Met (rs6265) genotypes. In addition, it is not clear whether these associations vary by hand grip strength or physical activity (PA). Methods A total of 2904 older adults were included in this study using data from the Health and Retirement Study. Associations between serum BDNF and measures of cognitive function were evaluated using multivariable linear regression models stratified by Met allele status. PA and hand grip strength were added to the model to evaluate whether including these variables altered associations between serum BDNF and cognition. Results Mean age was 71.4 years old, and mean body mass index was 28.3 kg/m2. Serum BDNF levels were positively associated with higher total cognitive score (beta = 0.34, p = .07), mental status (beta = 0.16, p = .07), and word recall (beta = 0.22, p =.04) among Met carriers, while serum BDNF levels were negatively associated with mental status (beta = −0.09, p = .07) among non-Met carriers. Furthermore, associations changed when hand grip strength was added to the model but not when PA was added to the model. Conclusions The BDNF Val66Met variant may moderate the association between serum BDNF levels and cognitive function in older adults. Furthermore, such associations differ according to hand grip strength but not PA.

To combat the e-cigarette epidemic among young audiences, a federal law was passed in the US that raised the minimum legal sales age of tobacco to 21 years (commonly known as Tobacco 21). Little is known about sentiment toward this law. Thus, the purpose of our study was to systematically explore trends about Tobacco 21 discussions and comparisons to other age-restriction behaviors on Twitter. Twitter data (n = 4628) were collected from September to December of 2019 that were related to Tobacco 21. A random subsample of identified tweets was used to develop a codebook. Two trained coders independently coded all data, with strong inter-rater reliability (κ = 0.71 to 0.93) found for all content categories. Associations between sentiment and content categories were calculated using χ2 analyses. Among relevant tweets (n = 955), the most common theme—the disjunction between ages for military enlistment and tobacco use—was found in 17.8% of all tweets. Anti-policy sentiment was strongly associated with the age of military enlistment, alcohol, voting, and adulthood (p < 0.001 for all). Opposition to Tobacco 21 propagates on social media because the US federal law does not exempt military members. However, the e-cigarette epidemic may have fueled some support for this law.

Social media (SM) can be defined as "a group of Internet-based applications that allow the creation and exchange of user-generated content." This includes formation of online communities and sharing of information, ideas, opinions, messages, images, and videos. Therefore, although all online video games would not necessarily count as SM, video games that allow for substantial sharing of information and development of online communities do fit this definition. SM has become an integral component of how people worldwide connect with friends and family, share personal content, and obtain news and entertainment. Use of SM is particularly prevalent among transitional-age youth, usually defined as individuals aged 16 to 24 years, who are at critical junctures around developmental tasks such as identity development and establishment of social norms.

BACKGROUND Twitter provides a valuable platform for the surveillance and monitoring of public health topics; however, manually categorizing large quantities of Twitter data is labor intensive and presents barriers to identify major trends and sentiments. Additionally, while machine and deep learning approaches have been proposed with high accuracy, they require large, annotated data sets. Public pretrained deep learning classification models, such as BERTweet, produce higher-quality models while using smaller annotated training sets. OBJECTIVE This study aims to derive and evaluate a pretrained deep learning model based on BERTweet that can identify tweets relevant to vaping, tweets (related to vaping) of commercial nature, and tweets with provape sentiment. Additionally, the performance of the BERTweet classifier will be compared against a long short-term memory (LSTM) model to show the improvements a pretrained model has over traditional deep learning approaches. METHODS Twitter data were collected from August to October 2019 using vaping-related search terms. From this set, a random subsample of 2401 English tweets was manually annotated for relevance (vaping related or not), commercial nature (commercial or not), and sentiment (positive, negative, or neutral). Using the annotated data, 3 separate classifiers were built using BERTweet with the default parameters defined by the Simple Transformer application programming interface (API). Each model was trained for 20 iterations and evaluated with a random split of the annotated tweets, reserving 10% (n=165) of tweets for evaluations. RESULTS The relevance, commercial, and sentiment classifiers achieved an area under the receiver operating characteristic curve (AUROC) of 94.5%, 99.3%, and 81.7%, respectively. Additionally, the weighted F1 scores of each were 97.6%, 99.0%, and 86.1%, respectively. We found that BERTweet outperformed the LSTM model in the classification of all categories. CONCLUSIONS Large, open-source deep learning classifiers, such as BERTweet, can provide researchers the ability to reliably determine if tweets are relevant to vaping; include commercial content; and include positive, negative, or neutral content about vaping with a higher accuracy than traditional natural language processing deep learning models. Such enhancement to the utilization of Twitter data can allow for faster exploration and dissemination of time-sensitive data than traditional methodologies (eg, surveys, polling research).

BACKGROUND: The Food and Drug Administration (FDA) has targeted the JUUL nicotine vaporizer as particularly appealing to young people. Initial reports suggest that JUUL is being used in schools and other locations in which cigarette smoking is illegal or discouraged. However, there is little scholarly research documenting this. We aimed to systematically analyze JUUL use themes and sentiment on Twitter. METHODS: Data were collected from Twitter’s Filtered Streams Application Programming Interface from April 12 to May 10, 2018. Excluding re-tweets, this yielded 67,934 tweets, from which a random sample of 2% was selected for coding. After removing irrelevant tweets, the final dataset included 1209 tweets. Inter-rater reliability ranged κ = 0.64–0.85. RESULTS: The majority (71.5%) of tweets expressed positive sentiment toward JUUL, while 14.1% expressed negative sentiment. JUUL use in places where cigarette smoking is illegal or discouraged appeared in 111 tweets (9.2%), with approximately one-third of these tweets referring to using the device in school. Nearly 20% of tweets mentioned using the device at home and/or directly in front of responsible adults. CONCLUSIONS: This study confirms anecdotal reports of JUUL use in places where cigarette smoking is illegal or discouraged. Positive sentiment about use of JUUL in these places suggests that the product is being normalized among young people. It may be valuable for educators and other responsible adults to discuss the addictive nature of nicotine delivered through JUUL with younger populations. This study supports policy implications introduced by the FDA aimed at curbing youth use.

Purpose:Although there is evidence of associations between social media (SM) use and mental well-being among the general population, these associations among lesbian, gay, and bisexual (LGB) persons are poorly understood. This study compared the influence of SM experiences on mental well-being between LGB and non-LGB persons.Design and Setting:Online cross-sectional survey.Participants:National sample of 2408 US adults aged 18 to 30 years.Method:We asked participants to provide examples of when SM affected their well-being separately in good and bad ways. We coded, summed, and used rate ratios (RRs) to compare responses of LGB and non-LGB individuals. Thematically similar codes were described and grouped into categories.Results:Most responses described positive SM effects. However, of 6 codes that were significantly more frequent among LGB respondents, only social capital (RR = 1.58, 95% confidence interval [CI], 1.17-2.12) described a positive effect. Five codes described negative effects of SM for LGB users: negative emotional contagion (RR = 1.28, 95% CI, 1.04-1.58), comparison with others (RR = 1.28, 95% CI, 1.01-1.62), real-life repercussions (RR = 1.86, 95% CI, 1.18-2.94), envy (RR = 2.49, 95% CI, 1.48-4.19), and need for profile management (RR = 2.32, 95% CI, 1.07-5.03).Conclusion:These findings suggest that, for LGB persons, gaining social capital from SM is valuable for establishing and maintaining connections. Increased negative SM experiences may pose a risk for the mental well-being of LGB individuals.

Purpose: To examine the association between positive and negative experiences on social media (SM) and perceived social isolation (PSI). Design: Cross-sectional survey. Setting: One large mid-Atlantic University. Participants: A total of 1178 students aged 18 to 30 were recruited in August 2016. Measures: Participants completed an online survey assessing SM use and PSI. We assessed positive and negative experiences on SM by directly asking participants to estimate what percentage of their SM experiences involved positive and negative experiences, respectively. Social isolation was measured using the established Patient-Reported Outcomes Measures Information System scale. Analysis: We used multivariable logistic regression to assess associations between both positive and negative experiences on SM and PSI. Primary models controlled for sex, age, race/ethnicity, educational status, relationship status, and living situation. Results: Participants had an average age of 20.9 (standard deviation = 2.9) and were 62% female. Just over one-quarter (28%) were nonwhite. After controlling for all sociodemographic covariates, each 10% increase in positive experiences was not significantly associated with social isolation (adjusted odds ratio [AOR] = 0.97; 95% confidence interval [CI]: 0.93-1.005). However, each 10% increase in negative experiences was associated with a 13% increase in odds of PSI (AOR = 1.13; 95% CI: 1.05-1.21). Conclusion: Having positive experiences on SM is not associated with lower social isolation, whereas having negative experiences on SM is associated with higher social isolation. These findings are consistent with the concept of negativity bias, which suggests that humans tend to give greater weight to negative entities compared with positive ones.

BACKGROUND Puff Bars are e-cigarettes that continued marketing flavored products by exploiting the US Food and Drug Administration exemption for disposable devices. OBJECTIVE This study aimed to examine discussions related to Puff Bar on Twitter to identify tobacco regulation and policy themes as well as unanticipated outcomes of regulatory loopholes. METHODS Of 8519 original tweets related to Puff Bar collected from July 13, 2020, to August 13, 2020, a random 20% subsample (n=2661) was selected for qualitative coding of topics related to nicotine dependence and tobacco policy. RESULTS Of the human-coded tweets, 2123 (80.2%) were coded as relevant to Puff Bar as the main topic. Of those tweets, 698 (32.9%) discussed tobacco policy, including flavors (n=320, 45.9%), regulations (n=124, 17.8%), purchases (n=117, 16.8%), and other products (n=110, 15.8%). Approximately 22% (n=480) of the tweets referenced dependence, including lack of access (n=273, 56.9%), appetite suppression (n=59, 12.3%), frequent use (n=47, 9.8%), and self-reported dependence (n=110, 22.9%). CONCLUSIONS This study adds to the growing evidence base that the US Food and Drug Administration ban of e-cigarette flavors did not reduce interest, but rather shifted the discussion to brands utilizing a loophole that allowed flavored products to continue to be sold in disposable devices. Until comprehensive tobacco policy legislation is developed, new products or loopholes will continue to supply nicotine demand.

Background: The growing use of electronic nicotine delivery systems (ENDS) among adolescents is a public health concern. Taxation of these products is a viable approach to reduce ENDS use, particularly among adolescents. Opponents of taxation posit that it puts specialty retailers (ie, vape shops) out of business, thereby reducing availability of ENDS for adult smokers seeking harm reduction. Pennsylvania enacted substantial ENDS taxes in October 2016. This study sought to examine (1) the prevalence of Pennsylvania vape shops before and after ENDS taxes were enacted and (2) ENDS retail licensing compliance among vape shops. Methods: We employed standardized searches for vape shops in Pennsylvania on the Yelp business-listing platform a month prior to and for 18 consecutive months following the imposition of ENDS taxes. We then compared listings to a public database of ENDS-related retail licenses to determine compliance status. Results: The number of listed vape shops increased in a linear fashion by a magnitude of 23%. In addition, when we compared a final listing of retailers to data from the state tax authority, we found roughly a quarter (22%-29%) of vape shops to be noncompliant with maintaining a valid ENDS retail license. Conclusions: Overall, ENDS taxation in Pennsylvania has not appeared to reduce prevalence of vape shops as anticipated. However, stricter enforcement of the tax law is necessary to ensure compliance among retailers. These findings have implications for implementation and enforcement of ENDS tax policy nationwide, including states that currently lack such policies.

Background. The use of electronic cigarettes (e-cigarette) offers potential to facilitate cigarette smoking cessation, yet potentially increases risk of cigarette smoking initiation. This relationship has been primarily modeled in mathematical ways that often do not represent real-world complexities, which could inform decisions regarding local prevention programs or policies. Aims. To develop a model of cigarette and e-cigarette use that combines current research on tobacco use and incorporates real-world geographic and demographic data. Method. We used a platform for developing agent-based models with demographic information representative of the population in Pennsylvania. We developed three models of cigarette and e-cigarette use. The primary outcome for each was the total number of users for cigarette, e-cigarette, and total nicotine. The first model applied current cigarette and e-cigarette data, the second tested the effect of implementing a program of e-cigarette education and policies, and the third considered a social contagion factor, where local schools functioned as a transmission vector. Results. The baseline and social contagion models found an overall decline in cigarette use but an increase in e-cigarette and total nicotine use. The education/policies model had declines in all categories. Sensitivity analysis suggested the importance of nuanced e-cigarette/cigarette interactions when modeling tobacco use. Discussion. Public health campaigns that focus on reducing youth e-cigarette usage can have a large effect. Social contagion should be strongly considered when studying e-cigarette spread. Conclusion. Targeted public health campaigns focused on reducing school prevalence of e-cigarette use may be particularly valuable.

ObjectiveTobacco 21 is a law that sets the minimum legal sales age of tobacco products to 21. On 20 December 2019, the USA passed a federal Tobacco 21 law. The objective of this study is to explore Twitter discussions about the federal Tobacco 21 law in the USA leading up to enacted.MethodsTwitter messages about Tobacco 21 posted between September and December 2019 were collected via RITHM software. A 2% sample of all collected tweets were double coded by independent coders using a content analysis approach.ResultsFindings included three content categories of tweets (news, youth and young adults and methods of avoiding the law) with eight subcodes. Most news tweets incorrectly described the law as a purchase law (54.7%). However, Tobacco 21 is in fact a sales law—it only includes penalties for tobacco retailers who sell to under-age purchasers. About one-fourth (27%) of the tweets involved youth and young adults, with some claiming the law would reduce youth smoking and others doubting its ability to limit youth access to tobacco products. Few tweets (2.5%) mentioned methods of circumventing the policy, such as having an older peer purchase tobacco.ConclusionsAs several countries explore raising their age of sale of tobacco laws to 21, they should couple policy enactment with clear and accurate communication about the law. Compliance agencies at all levels (eg, local, regional, national) can use social media to identify policy loopholes and support vulnerable populations throughout the policy implementation process.

The increasing popularity of the JUUL electronic nicotine delivery system among youth poses several potential public health concerns. Social media can be used to better understand the spread of information related to JUUL. This study examined whether adolescents (age18) are following JUUL's official Twitter account and subsequently sharing (retweeting) JUUL's posts to their followers. We also assessed various patterns in which adolescents share information on JUUL with each other.We collected 3,239 tweets from JUUL's official Twitter account (@JUULVapor) for one full year from February 2017 to January 2018. These tweets were shared by Twitter users to their followers 1,124times by 721 unique users. Users were determined to be either adolescent (age18) or adult (≥18) based on a systematic procedure involving double coding. We used social network analysis to explore the relationships between users retweeting JUUL.One-quarter (25%) of users were determined to be adolescents. Social network analysis revealed a maximum path length of 4 and a positive assortativity (r = .29). There were 25 (9%) instances of an adolescent retweeting content from another adolescent, 35 (12%) of an adolescent retweeting from an adult, and 30 (11%) of an adult retweeting from an adolescent.JUUL's official Twitter account is being followed-and its messages are being shared-by adolescents. Rigorous policies and prevention programs are needed to curb adolescent exposure to JUUL content and discussions online.

There is growing interest in conducting public health research using data from social media. In particular, Twitter “infoveillance” has demonstrated utility across health contexts. However, rigorous and reproducible methodologies for using Twitter data in public health are not yet well articulated, particularly those related to content analysis, which is a highly popular approach. In 2014, we gathered an interdisciplinary team of health science researchers, computer scientists, and methodologists to begin implementing an open-source framework for real-time infoveillance of Twitter health messages (RITHM). Through this process, we documented common challenges and novel solutions to inform future work in real-time Twitter data collection and subsequent human coding. The RITHM framework allows researchers and practitioners to use well-planned and reproducible processes in retrieving, storing, filtering, subsampling, and formatting data for health topics of interest. Further considerations for human coding of Twitter data include coder selection and training, data representation, codebook development and refinement, and monitoring coding accuracy and productivity. We illustrate methodological considerations through practical examples from formative work related to hookah tobacco smoking, and we reference essential methods literature related to understanding and using Twitter data.

Social media allows users to explore self-identity and express emotions or thoughts. Research looking into the association between social media use (SMU) and mental health outcomes, such as anxiety or depressive symptoms, have produced mixed findings. These contradictions may best be addressed by examining different patterns of SMU as they relate to depressive symptomatology. We sought to assess the independent associations between active versus passive SMU and depressive symptoms. For this, we conducted an online survey of adults 18-49 of age. Depressive symptoms were measured using the Patient-Reported Outcomes Measurement Information System brief depression scale. We measured active and passive SMU with previously developed items. Factor analysis was used to explore the underlying factor structure. Then, we used ordered logistic regression to assess associations between both passive and active SMU and depressive symptoms while controlling for sociodemographic covariates. Complete data were received from 702 participants. Active and passive SMU items loaded on separate factors. In multivariable analyses that controlled for all covariates, each one-point increase in passive SMU was associated with a 33 percent increase in depressive symptoms (adjusted odds ratio [AOR] = 1.33, 95 percent confidence interval [CI] = 1.17-1.51). However, in the same multivariable model, each one-point increase in active SMU was associated with a 15 percent decrease in depressive symptoms (AOR = 0.85, 95 percent CI = 0.75-0.96). To inform interventions, future research should determine directionality of these associations and investigate related factors.

Introduction. Hookah smoking is becoming increasingly popular worldwide, especially among young adults. The growth of social media has also enabled sharing of opinions, experiences, and marketing related to hookah via user-generated content. Aim. To evaluate the portrayal and promotion of hookah on Instagram and to highlight public health challenges created by this content. Method. A qualitative content analysis was performed on a sample of 301 Instagram posts made with the hashtags #hookah or #shisha in October 2016. Results. Of the 301 coded posts, 279 were relevant to hookah. These posts were most commonly made by hookah lounges/bars (29.2%) and individual users (27.6%). Posters were most commonly from Russia (38.5%), the United States (18.6%), and Germany (10.7%). A total of 63.8% of the posts were promotional in nature; 19.7% of posts contained hashtags that expressed hookah identity or community (e.g., #hookahlife); 35.5% of posts associated nightlife activities with hookah smoking and 33.0% portrayed hookah smoking as a social activity. Only one post (0.4%) mentioned that hookah might have negative health effects. Likes were more common on posts depicting novel rather than traditional hookah designs ( p = .027). Conclusions. Images from Instagram may help in understanding health behaviors such as hookah smoking. Our results suggest that domestic and international hookah promotion is common on Instagram. Instagram posts cast hookah in an overwhelmingly positive light and may normalize hookah use through associations with nightlife, community, and hookah identity. Policy makers and researchers should explore approaches for reducing the volume of promotional posts and tailoring counter-marketing to the specific themes presented on social media.

Background Waterpipe tobacco smoking (WTS or 'hookah') is common among adolescents and college students in the USA. However, there has not yet been a large-scale, nationally representative study independently examining WTS among young adults who are not in college. Objective This study sought to examine associations between attitudes, normative beliefs, certain socio-demographic factors and current WTS among young adults not in college and compare them to young adults in college. Methods A total of 3131 US adults ages 18-30 completed an online survey about WTS behaviour, attitudes, normative beliefs and relevant socio-demographic factors. Multivariable logistic regression was used to examine independent associations between these variables and current WTS stratified by student status. Results Ever WTS was reported by 29% of young adults not in college and by 35% of those in college, and current use rates were 3 and 7%, respectively. Multivariable models demonstrated that positive attitudes and perceived peer acceptability of WTS were significantly associated with increased current WTS for both young adults not in college [adjusted odds ratio (AOR) = 2.72; 95% CI: 2.00-3.71 and AOR = 2.02; 95% CI: 1.50-2.71, respectively] and young adults in college (AOR = 3.37; 95% CI: 2.48-4.58 and AOR = 2.05; 95% CI: 1.49-2.83, respectively). The magnitude of these associations was not significantly different when comparing individuals in college and not in college. Conclusions Among young adults, WTS is common in non-college-based populations as well as in college-based populations. Therefore, prevention programming should extend to all young adults, not only to those in college.

Although increased social media use (SMU) has been linearly associated with increased real-life social isolation (SI), it is unknown whether these associations differ by personality characteristics. With a nationally-representative sample of 1768 U.S. young adults aged 19–32, we assessed SI using a 4-item Patient-Reported Outcomes Measurement Information System scale, and personality using the 10-item Big Five Inventory. Using ordered logistic regression, we evaluated multivariable associations between SMU, personality characteristics, and SI. Extraversion and agreeableness were associated with lower odds of SI, while neuroticism was associated with higher odds. A significant interaction term demonstrated that the association between SMU and SI differed by conscientiousness. Among those with low conscientiousness, compared with the lowest quartile of SMU, those in the highest quartile had more than three times the odds (AOR = 3.20, 95% CI = 1.99, 5.15) for increased SI, but there was no significant association among the high conscientiousness group. Interaction terms between SMU and the other four personality characteristics were not significant. Conscientious individuals may approach social media in a way that helps maintain good face-to-face social interactions, reducing perceived SI.

To examine the association between degree of real-life closeness of social media (SM) contacts and depressive symptoms.Students ages 18-30 (N = 1124) were recruited in August 2016.Participants completed an online survey assessing SM use and depression. We used multivariable logistic regression to assess associations between real-life closeness of SM contacts and depressive symptoms.After controlling for covariates, each 10% increase in the proportion of SM friends with whom participants had no face-to-face relationship was associated with a 9% increase in odds of depressive symptoms (AOR = 1.09; 95% CI = 1.05-1.13). However, each 10% increase in the proportion of SM friends with whom participants had a close face-to-face relationship was associated with a 7% decrease in depressive symptoms (AOR = 0.93; 95% CI = 0.89-0.97).Having no in-person relationship with SM contacts is associated with increased depressive symptoms; however, having close in-person relationships with SM contacts is associated with decreased depressive symptoms.

Background Congestive heart failure is the leading cause of hospital readmissions. We aimed to assess adherence to and effectiveness of a telehealth protocol designed to prevent hospital admissions for congestive heart failure. Methods We recruited a random sample of 50 patients with congestive heart failure (mean age 61 years) from a managed care organization. We developed a telehealth platform allowing for daily, real-time reporting of health status and video conferencing. We defined adherence as the percentage of days on which the patient completed the daily check-in protocol. To assess efficacy, we compared admission and readmission rates between the 6-month intervention period and the prior 6 months. Primary outcomes were admissions and readmissions due to congestive heart failure, and secondary outcomes were admissions and readmissions due to any cause. Results Forty-eight patients (96%) completed the protocol. Approximately half (46%) were at high risk for readmission according to standardized measures. Median 120-day adherence was 96% (interquartile range, 92%-98%), and adherence did not significantly differ across sex, race, age, living situation, depression, cognitive ability, or risk for readmission. Approximately equal proportions of patients were admitted for all causes during the 6-month intervention period versus the comparison period (37% vs 43%; P = .32). Half as many patients were admitted for congestive heart failure during the 6-month intervention period compared with the comparison period (12% vs 25%; P = .11). Conclusion Adherence to this telehealth protocol was excellent and consistent, even among high-risk patients. Future research should test the protocol using a more rigorous randomized design.

We characterized leading YouTube videos featuring alcohol brand references and examined video characteristics associated with each brand and video category.We systematically captured the 137 most relevant and popular videos on YouTube portraying alcohol brands that are popular among underage youth. We used an iterative process to codebook development. We coded variables within domains of video type, character sociodemographics, production quality, and negative and positive associations with alcohol use. All variables were double coded, and Cohen's kappa was greater than .80 for all variables except age, which was eliminated.There were 96,860,936 combined views for all videos. The most common video type was "traditional advertisements," which comprised 40% of videos. Of the videos, 20% were "guides" and 10% focused on chugging a bottle of distilled spirits. While 95% of videos featured males, 40% featured females. Alcohol intoxication was present in 19% of videos. Aggression, addiction, and injuries were uncommonly identified (2%, 3%, and 4%, respectively), but 47% of videos contained humor. Traditional advertisements represented the majority of videos related to Bud Light (83%) but only 18% of Grey Goose and 8% of Hennessy videos. Intoxication was most present in chugging demonstrations (77%), whereas addiction was only portrayed in music videos (22%). Videos containing humor ranged from 11% for music-related videos to 77% for traditional advertisements.YouTube videos depicting the alcohol brands favored by underage youth are heavily viewed, and the majority are traditional or narrative advertisements. Understanding characteristics associated with different brands and video categories may aid in intervention development.

Background: Waterpipe tobacco smoking (WTS) is increasing in popularity despite evidence of harm and potential for dependence. Intervention development has been hampered by a lack of longitudinal, nationally representative data on usage patterns and factors independently associated with WTS initiation. Therefore, we aimed to characterize key transitions between WTS states in a nationally representative group of young adults, with particular attention to factors independently associated with initiation. Methods: Participants were randomly selected from a national probability-based panel representing 97% of the United States. A total of 1,785 adults ages 18 to 30 at baseline completed two Web-based surveys 18 months apart in 2013 and 2014. Assessments included knowledge of waterpipe tobacco smoke composition, positive and negative attitudes toward WTS, normative beliefs, intention to use waterpipe, and WTS behavior. We used multivariable logistic regression to assess the association between predictive factors and subsequent WTS initiation. Results: In fully adjusted models, overall knowledge about toxicants associated with WTS was not associated with subsequent WTS initiation. Similarly, negative attitudes and normative beliefs were not associated with WTS uptake. However, baseline positive attitudes were strongly and significantly associated with WTS initiation [adjusted OR (AOR) = 1.7; 95% confidence interval (CI), 1.2–2.3]. Similarly, baseline intention to use WTS was strongly associated with subsequent initiation (AOR = 7.0; 95% CI, 3.5–13.7). Conclusions: Prevention efforts may be most successful if they target individuals with clear intentions to use WTS and challenge positive attitudes surrounding WTS. Impact: Surveillance of WTS trajectories will help inform health care and policy surrounding this emerging risk behavior among U.S. young adults. Cancer Epidemiol Biomarkers Prev; 26(5); 748–55. ©2017 AACR.

Few studies have demonstrated the use of mixed methods research to contextualize health topics using primary data from social media. To address this gap in the methodological literature, we present research about electronic nicotine delivery systems, using Twitter data from “World Vaping Day.” To engage with the quantitative breadth and qualitative depth of 5,149 collected tweets, we utilized a convergent parallel mixed methods framework, integrating thematic prevalence estimates with phenomenological contextualization. Sentiment was more positive than negative across all categories except policy related. A total of 23% of tweets were promotional and relatively few tweets related to tobacco use (4.9%) or health concerns (4.2%). Salient themes included modifying or upgrading electronic nicotine delivery systems devices, and general mistrust of public health advocates and tobacco companies.

IntroductionWhile increased time spent on social media (TSSM) has been associated with depression and anxiety, the independent role of using multiple social media (SM) platforms is unclear. MethodsWe surveyed a nationally-representative sample of 1787 U.S. young adults ages 1932. Depression and anxiety symptoms were measured using the Patient-Reported Outcomes Measurement Information System (PROMIS). We assessed use of multiple SM platforms with an adapted Pew Internet Research scale. We used ordered logistic regression models to assess associations between use of multiple SM platforms and mental health outcomes while controlling for eight covariates, including overall TSSM. ResultsCompared to those who used 02 social media platforms, participants who used 711 social media platforms had substantially higher odds of having increased levels of both depression (Adjusted Odds Ratio [AOR]=3.0, 95% CI=1.94.8) and anxiety symptoms (AOR=3.2, 95% CI=2.05.1). Associations were linear (p

While medical television programs are popular among health profession trainees, it is not clear to what extent these programs affect their knowledge, perceptions, and/or behaviors. Therefore, we conducted a systematic review of research evaluating associations between program exposure and outcomes. We conducted systematic literature searches in Pubmed, CINAHL, and PsycINFO. Selected studies were required to be scholarly research, involve exposure to fictionalized medical television programming by health professional students, and assess associations between exposure and outcomes. Studies were classified according to quality and factors related to population, exposure, and outcomes. Of 3541 studies identified, 13 met selection criteria. Six studies involved undergraduate medical students, one involved nursing students, two involved both medical and nursing students, two involved medical residents, one involved medical students, residents and attending physicians, and one involved graduate epidemiology students. Mean study quality according to the MERSQI was 8.27. The most commonly assessed television programs were ER and Grey's Anatomy (six each). Five studies assessed regular viewing habits, and found that fictional medical programs are popular among students and that students recall health topics from episodes. The eight studies that assessed the association with outcomes when using clips as educational tools reported high satisfaction and increased knowledge of the presented health topics. While relatively few published studies have explored influences of fictional medical television on health professional students, those conducted suggest that students often view these television programs independently and that integration of this programming into medical education is feasible and acceptable.