Descriptive cross-sectional survey of tobacco and cannabis restrictions on state and local film incentives in the USA.

BACKGROUND: Reducing tobacco depictions in media has significant health benefits because tobacco placements in films normalise tobacco use and are linked to youth initiation. Cannabis depictions may have similar effects. Placing restrictions on film incentives has been suggested; however, it remains an unexplored strategy for reducing tobacco depictions. We investigated whether states and localities that offer film incentives have established funding restrictions to deter tobacco or cannabis depictions. METHODS: We conducted a descriptive cross-sectional survey of official state and local government websites in the USA that listed film incentives. We coded policy level (ie, state, local), incentive type (ie, tax credit, rebate), incentive amounts, programme qualifiers and presence and characteristics of tobacco and cannabis restrictions. RESULTS: Quantifiable tax incentives at the state level offered over $1.6 billion to producers. Among 50 US states and Washington, DC, 39 provided film incentives: 4 restricted tobacco and 0 restricted cannabis. Among the 238 local film offices we identified, 24 offered incentives; 5 restricted tobacco and 1 restricted cannabis. All the incentive restrictions excluded tobacco or cannabis purchases from reimbursement; there were no penalties for tobacco or cannabis depictions. CONCLUSIONS: Film incentives are large financial commitments that may undermine public health since they allow depictions of tobacco and cannabis that contribute to initiation and use. Few states or localities limit film incentives related to tobacco or cannabis, and the existing restrictions are unlikely to deter depictions or product placement. Restrictions on incentives are an underused tool for deterring tobacco and cannabis depictions in film.

Young Adults' Perceptions of and Intentions to Use Nicotine and Cannabis Vaporizers in Response to e-Cigarette or Vaping-Associated Lung Injury Instagram Posts: Experimental Study.

BACKGROUND: Inhaling aerosolized nicotine and cannabis (colloquially called "vaping") is prevalent among young adults. Instagram influencers often promote both nicotine and cannabis vaporizer products. However, Instagram posts discouraging the use of both products received national media attention during the 2019 outbreak of e-cigarette or vaping-associated lung injury (EVALI). OBJECTIVE: This experiment tested the impact of viewing Instagram posts about EVALI, varying in image and text valence, on young adults' perceived harmfulness of nicotine and cannabis products, perceived risk of nicotine and cannabis vaporizer use, and intentions to use nicotine and cannabis vaporizers in the future. METHODS: Participants (N=1229) aged 18-25 (mean 21.40, SD 2.22) years were recruited through Qualtrics Research Services, oversampling for ever-use of nicotine or cannabis vaporizers (618/1229, 50.3%). Participants were randomly assigned to view Instagram posts from young people portraying their experiences of EVALI in a 2 (image valence: positive or negative) × 2 (text valence: positive or negative) between-subjects experiment. Positive images were attractive and aesthetically pleasing selfies. The positive text was supportive and uplifting regarding quitting the use of vaporized products. Negative images and text were graphic and fear inducing. After viewing 3 posts, participants reported the perceived harmfulness of nicotine and cannabis products, the perceived risk of nicotine and cannabis vaporizer use, and intentions to use nicotine and cannabis vaporizers in the future. Ordinal logistic regression models assessed the main effects and interactions of image and text valence on perceived harmfulness and risk. Binary logistic regression models assessed the main effects and interactions of image and text valence on intentions to use nicotine and cannabis vaporizers. Analyses were adjusted for product use history. RESULTS: Compared to viewing positive images, viewing negative images resulted in significantly greater perceived harm of nicotine (P=.02 for disposable pod-based vaporizers and P=.04 for other e-cigarette "mods" devices) and cannabis vaporized products (P=.01), greater perceived risk of nicotine vaporizers (P<.01), and lower odds of intentions to use nicotine (P=.02) but not cannabis (P=.43) vaporizers in the future. There were no significant main effects of text valence on perceived harm, perceived risk, and intentions to use nicotine and cannabis vaporized products. No significant interaction effects of image and text valence were found. CONCLUSIONS: Negative imagery in Instagram posts about EVALI may convey the risks of vaporized product use and discourage young adults from this behavior, regardless of the valence of the post's text. Public health messaging regarding EVALI on Instagram should emphasize the risk of cannabis vaporizer use, as young adults may otherwise believe that only nicotine vaporizer use increases their risk for EVALI.

Identifying Electronic Nicotine Delivery System Brands and Flavors on Instagram: Natural Language Processing Analysis.

BACKGROUND: Electronic nicotine delivery system (ENDS) brands, such as JUUL, used social media as a key component of their marketing strategy, which led to massive sales growth from 2015 to 2018. During this time, ENDS use rapidly increased among youths and young adults, with flavored products being particularly popular among these groups. OBJECTIVE: The aim of our study is to develop a named entity recognition (NER) model to identify potential emerging vaping brands and flavors from Instagram post text. NER is a natural language processing task for identifying specific types of words (entities) in text based on the characteristics of the entity and surrounding words. METHODS: NER models were trained on a labeled data set of 2272 Instagram posts coded for ENDS brands and flavors. We compared three types of NER models-conditional random fields, a residual convolutional neural network, and a fine-tuned distilled bidirectional encoder representations from transformers (FTDB) network-to identify brands and flavors in Instagram posts with key model outcomes of precision, recall, and F1 scores. We used data from Nielsen scanner sales and Wikipedia to create benchmark dictionaries to determine whether brands from established ENDS brand and flavor lists were mentioned in the Instagram posts in our sample. To prevent overfitting, we performed 5-fold cross-validation and reported the mean and SD of the model validation metrics across the folds. RESULTS: For brands, the residual convolutional neural network exhibited the highest mean precision (0.797, SD 0.084), and the FTDB exhibited the highest mean recall (0.869, SD 0.103). For flavors, the FTDB exhibited both the highest mean precision (0.860, SD 0.055) and recall (0.801, SD 0.091). All NER models outperformed the benchmark brand and flavor dictionary look-ups on mean precision, recall, and F1. Comparing between the benchmark brand lists, the larger Wikipedia list outperformed the Nielsen list in both precision and recall. CONCLUSIONS: Our findings suggest that NER models correctly identified ENDS brands and flavors in Instagram posts at rates competitive with, or better than, others in the published literature. Brands identified during manual annotation showed little overlap with those in Nielsen scanner data, suggesting that NER models may capture emerging brands with limited sales and distribution. NER models address the challenges of manual brand identification and can be used to support future infodemiology and infoveillance studies. Brands identified on social media should be cross-validated with Nielsen and other data sources to differentiate emerging brands that have become established from those with limited sales and distribution.

Reach, Receptivity, And Beliefs Associated With the Fresh Empire Campaign to Prevent and Reduce Cigarette Use Among Youth in the United States.

PURPOSE: To determine the association between exposure to FDA's Fresh Empire tobacco public education campaign and tobacco-related beliefs. DESIGN: Repeated cross-sectional data collection design with embedded longitudinal cohort over six data collection waves. SETTING: 30 US evaluation markets. SAMPLE: Hip Hop peer crowd-identified US youth aged 12-18 (N = 5,378). MEASURES: Self-reported brand and video ad awareness (saw any ad at least sometimes) and perceived effectiveness (1-5 scale) to describe campaign awareness and receptivity. Exogenous exposure was measured using population-adjusted broadcast and digital video impressions. Tobacco-related beliefs included beliefs about smoking risks, attitudes towards tobacco-free people and lifestyles, and normative beliefs about smoking. ANALYSIS: Descriptive analyses of awareness, receptivity, and agreement with tobacco-related beliefs. Logistic regression models to determine the relationship between broadcast and digital video impressions and beliefs. INTERVENTION: Fresh Empire campaign. RESULTS: The campaign generated a high level of reach (71% brand and 66% video ad awareness at final wave) and messages were well-received (across waves 3.5-4.1 mean perceived effectiveness scores). Higher broadcast television exposure was associated with increased agreement with five beliefs related to addiction/control, being a bad influence on family/friends, and cosmetic effects of smoking (breath and attractiveness) (ORs = 1.16-1.27, (Ps < .05)). CONCLUSION: Fresh Empire successfully reached and resonated with Hip Hop-identified youth. The campaign was associated with a limited number of targeted beliefs.

Final Evaluation Findings for This Free Life, a 3-Year, Multi-Market Tobacco Public Education Campaign for Gender and Sexual Minority Young Adults in the United States.

INTRODUCTION: This Free Life was the first multi-market, primarily digital campaign designed to change tobacco-related beliefs among lesbian, gay, bisexual, and transgender (LGBT) young adults. Our evaluation sought to determine whether campaign exposure resulted in changes in tobacco-related beliefs. We summarize awareness and receptivity at the conclusion of the campaign and assess the effect of campaign exposure on tobacco-related beliefs in campaign treatment markets compared with control markets. AIMS AND METHODS: Twenty-four US designated market areas were selected to receive the campaign or serve as control markets. A baseline survey was conducted in 2016, with six follow-up surveys conducted approximately 6 months apart over the course of the 3-year campaign. 12 324 LGBT young adult survey participants were recruited via intercept interviews and social media. Campaign effects on outcomes were estimated using difference-in-difference panel regression models, with p-values corrected for multiple comparisons. RESULTS: Brand and ad awareness peaked in treatment markets approximately 2.5 years into the 3-year campaign and were significantly higher in treatment than control markets. Brand equity and ad receptivity were generally high and similar across LGBT subgroups. There were small but significant campaign effects on five tobacco-related beliefs, with difference-in-difference estimates ranging from 1.9 to 5.6 percentage points. CONCLUSIONS: This Free Life, the first multi-market tobacco public education campaign for LGBT young adults, reached and resonated with a large and diverse population, and had a small effect on beliefs involving social aspects of smoking. These findings should inform future communication efforts aimed at reducing tobacco use among LGBT young adults. IMPLICATIONS: Modest overall campaign effects suggest that further research on effective campaign messaging and delivery to LGBT young adults is needed. Campaign messaging style, delivery channels, and targeted outcomes likely contributed to these findings. Health communication efforts for LGBT young adults should consider the limitations of digital media in achieving sufficient exposure. Ad style and content optimized for a digital environment is an area that will benefit from further development.

LGBT young adults' awareness of and receptivity to the This Free Life tobacco public education campaign.

PURPOSE: This study measures awareness of and receptivity to the Food and Drug Administration's This Free Life campaign seeking to change tobacco-related attitudes and beliefs among lesbian, gay, bisexual and/or transgender (LGBT) young adults. METHODS: Participants were young adults who self-identify as LGBT. The evaluation uses a treatment-control design. This study includes data from four survey rounds with participants from each round invited to participate in subsequent rounds and new participants invited to account for attrition. Bivariate analyses assess treatment-control differences in campaign awareness by round. We used multivariable logistic regression models with a time×treatment interaction and covariates to assess whether increases in awareness were greater in treatment than control from follow-ups 1 to 4. Descriptive statistics describe perceived effectiveness and models explore covariates of perceived effectiveness. RESULTS: At each round, an increasing number of participants in treatment were brand aware (25%-67%) and reported high (16%-34%) and medium (16%-25%) video awareness compared with control (all p<0.001). Regressions revealed interactions in brand and video awareness, wherein the effect of treatment on awareness increased more over time, with significant treatment-control differences in change from follow-up 1 to 4 (all p<0.05). Reactions to all but one ad were positive (one neutral) with mean perceived effectiveness scores from 3.21 to 3.92 ('neither disagree nor agree' to 'agree' on 5-point scale). Perceived effectiveness differed by LGBT identity (all p<0.05). CONCLUSIONS: At follow-up 4, This Free Life reached most of the campaign audience in treatment markets and has achieved higher awareness in treatment than control markets, at individual survey rounds and over time.

Those who believe they can, do: The relationship between smoking avoidance beliefs, perceived risks of smoking, and behavior in a sexual and gender minority young adult sample.

An individual's beliefs in their perceived risk and ability to resist smoking have been found to be associated with smoking behavior. The current study explores the effects of confidence in one's ability to avoid smoking, measured by avoidance beliefs, on the relationship between perceived risks of smoking and behavior. This analysis was done using 2016 baseline data collected among 4057 participants aged 18-24 for the evaluation of a large-scale public education campaign in the U.S. aimed at reducing tobacco use among sexual and gender minority young adults. The analytic sample included roughly 3493 participants per analysis. Analyses used the following measures: (1) perceived risks of smoking (e.g., smoking cigarettes will shorten my life); (2) confidence to avoid smoking in various situations (i.e., avoidance beliefs), and (3) past 30-day cigarette smoking. Binary logistic regression models with interaction analyses assessed the relationship between perceived risks of smoking and past 30-day smoking behavior using the interaction term of avoidance beliefs. An interaction between perceived risks of smoking and avoidance behaviors interaction emerged, such that the negative relationship between perceived risks of smoking and smoking behavior was stronger for those who believed that they could avoid smoking in various situations. This suggests that the relationship between perceived risk and smoking behavior can be bolstered if one's beliefs about their ability to avoid smoking are strong. Campaigns that build smoking avoidance confidence may enhance the effects of tobacco outcome expectations-related messaging on smoking.

Sponsorship Disclosures and Perceptions of E-cigarette Instagram Posts.

OBJECTIVES: Instagram influencers have many followers and are often paid to promote products, including e-cigarettes. This experimental study assessed effects of sponsorship disclosures on perceptions of e-cigarette Instagram influencer posts. METHODS: Young adult e-cigarette users (age 18-29; N = 917) were randomly assigned to 3 experimental conditions varying the clarity of sponsorship disclosure on simulated Instagram influencer posts: clear (eg, "#sponsored") ambiguous (eg, "#sp"), or no disclosure (ie, vaping-related hashtags only). After viewing each of 4 Instagram posts featuring a fictitious e-cigarette brand, participants reported hashtag recognition, ad recognition, ad trust, influencer credibility, and post engagement intentions. After viewing all posts, participants reported brand attitudes, brand use intentions, and vaping intentions. RESULTS: With greater recognition of clear (but not ambiguous) disclosure hashtags, ad recognition increased (p = .001), perceptions of influencer credibility decreased (p = .022), and intentions to engage with posts decreased (p = .008). Ad trust was lower with greater hashtag recognition regardless of disclosures (p < .001). Sponsorship disclosures did not significantly affect brand attitudes, brand use intentions, or vaping intentions. CONCLUSIONS: Recognizing clear sponsorship disclosures may influence young adults' perceptions of and engagement with e-cigarette Instagram posts but may not affect perceptions or use of products.

An Experimental Study of Nicotine Warning Statements in E-cigarette Tweets.

INTRODUCTION: It is unclear whether warnings on electronic cigarette (e-cigarette) advertisements required by the US Food and Drug Administration (FDA) will apply to social media. Given the key role of social media in marketing e-cigarettes, we seek to inform FDA decision making by exploring how warnings on various tweet content influence perceived healthiness, nicotine harm, likelihood to try e-cigarettes, and warning recall. METHODS: In this 2 × 4 between-subjects experiment participants viewed a tweet from a fictitious e-cigarette brand. Four tweet content versions (e-cigarette product, e-cigarette use, e-cigarette in social context, unrelated content) were crossed with two warning versions (absent, present). Adult e-cigarette users (N = 994) were recruited via social media ads to complete a survey and randomized to view one of eight tweets. Multivariable regressions explored effects of tweet content and warning on perceived healthiness, perceived harm, and likelihood to try e-cigarettes, and tweet content on warning recall. Covariates were tobacco and social media use and demographics. RESULTS: Tweets with warnings elicited more negative health perceptions of the e-cigarette brand than tweets without warnings (p < .05). Tweets featuring e-cigarette products (p < .05) or use (p < .001) elicited higher warning recall than tweets featuring unrelated content. CONCLUSIONS: This is the first study to examine warning effects on perceptions of e-cigarette social media marketing. Warnings led to more negative e-cigarette health perceptions, but no effect on perceived nicotine harm or likelihood to try e-cigarettes. There were differences in warning recall by tweet content. Research should explore how varying warning content (text, size, placement) on tweets from e-cigarette brands influences health risk perceptions. IMPLICATIONS: FDA's 2016 ruling requires warnings on advertisements for nicotine-containing e-cigarettes, but does not specify whether this applies to social media. This study is the first to examine how e-cigarette warnings in tweets influence perceived healthiness and harm of e-cigarettes, which is important because e-cigarette brands are voluntarily including warnings on Twitter and Instagram. Warnings influenced perceived healthiness of the e-cigarette brand, but not perceived nicotine harm or likelihood to try e-cigarettes. We also saw higher recall of warning statements for tweets featuring e-cigarettes. Findings suggest that expanding warning requirements to e-cigarette social media marketing warrants further exploration and FDA consideration.

Effect of menthol cigarette and other menthol tobacco product bans on tobacco purchases in the RTI iShoppe virtual convenience store.

OBJECTIVE: To test how a potential US ban of menthol products or replacement with 'green' products and ads could influence tobacco purchases. METHODS: US adult menthol smokers (N=1197) were recruited via an online panel and randomly assigned to complete a shopping task in one of four versions (experimental conditions) of the RTI iShoppe virtual store: (1) no ban, (2) replacement of menthol cigarettes and ads with green replacement versions, (3) menthol cigarette ban and (4) all menthol tobacco product ban. Logistic regressions assessed the effect of condition on tobacco purchases. RESULTS: Participants in the menthol cigarette ban (OR=0.67, 95% CI 0.48 to 0.92) and all menthol product ban conditions (OR=0.60, 95% CI 0.43 to 0.83) were less likely to purchase cigarettes of any type than participants in the no ban condition. Participants in the green replacement (OR=1.74, 95% CI 1.13 to 2.70), menthol cigarette ban (OR=3.40, 95% CI 2.14 to 5.41) and all menthol product ban conditions (OR=3.14, 95% CI 1.97 to 5.01) were more likely to purchase a cigarette brand different from their usual brand than participants in the no ban condition. CONCLUSIONS: Our findings suggest that menthol bans could have great public health impact by reducing cigarette purchases. However, tobacco marketing strategies, such as creating green (or other replacement) versions of menthol cigarettes, may undermine public health benefits of a menthol ban by prompting purchases of non-menthol cigarettes. Our findings highlight the importance of taking tobacco marketing tactics into consideration in tobacco product regulation.

Awareness of and Receptivity to the Fresh Empire Tobacco Public Education Campaign Among Hip Hop Youth.

PURPOSE: The aim of the study was to assess awareness of and receptivity to the U.S. Food and Drug Administration's Fresh Empire tobacco public education campaign designed to reach Hip Hop-identified youth, who are at higher smoking risk. METHODS: The evaluation uses a randomized treatment-control design with 15 campaign-targeted treatment and 15 control markets. We conducted surveys among 12- to 17-year-olds before campaign launch and at approximately 6-month intervals. Analyses explore treatment-control differences in Fresh Empire brand and video advertisement awareness at individual survey rounds and over time and perceived effectiveness of advertisements. RESULTS: Awareness of the Fresh Empire brand was higher among youth in treatment than control markets following campaign launch (ps < .01). Awareness of the Fresh Empire brand increased more in treatment than control over time (adjusted odds ratio = 3.26, 95% confidence interval = 1.90-5.58). At follow-ups 1 and 3, youth in treatment (vs. control) were more likely to report high and less likely to report low awareness of video advertisements (ps < .05). There were no treatment-control differences in video awareness at follow-up 2 (not significant). Fresh Empire video advertisements had perceived effectiveness scores ranging from 3.66 to 4.11 (1-5 scale) across three survey rounds. CONCLUSIONS: Among the campaign audience of Hip Hop-identified youth, awareness of the Fresh Empire campaign was higher in treatment than control markets at individual survey rounds, and increases in campaign awareness were greater in treatment than control markets over time. Campaign advertisements also elicited positive audience reactions. Findings suggest that heavily digital campaigns may take longer to achieve Centers for Disease Control and Prevention-recommended 75% quarterly awareness.

Antismoking Advertisements and Price Promotions and Their Association With the Urge to Smoke and Purchases in a Virtual Convenience Store: Randomized Experiment.

BACKGROUND: Point of sale (POS) advertising is associated with smoking initiation, current smoking, and relapse among former smokers. Price promotion bans and antismoking advertisements (ads) are 2 possible interventions for combating POS advertising. OBJECTIVE: The purpose of this analysis was to determine the influence of antismoking ads and promotions on urges to smoke and tobacco purchases. METHODS: This analysis examined exposure to graphic (graphic images depicting physical consequences of tobacco use) and supportive (pictures of and supportive messages from former smokers) antismoking ads and promotions in a virtual convenience store as predictors of urge to smoke and buying tobacco products among 1200 current cigarette smokers and 800 recent quitters recruited via a Web-based panel (analytical n=1970). We constructed linear regression models for urge to smoke and logistic regression models for the odds of purchasing tobacco products, stratified by smoking status. RESULTS: The only significant finding was a significant negative relationship between exposure to supportive antismoking ads and urge to smoke among current smokers (beta coefficient=-5.04, 95% CI -9.85 to -0.22; P=.04). There was no significant relationship between graphic antismoking ads and urge to smoke among current smokers (coefficient=-3.77, 95% CI -8.56 to 1.02; P=.12). Neither relationship was significant for recent quitters (graphic: coefficient=-3.42, 95% CI -8.65 to 1.81; P=.15 or supportive: coefficient=-3.82, 95% CI -8.99 to 1.36; P=.20). There were no significant differences in urge to smoke by exposure to promotions for current smokers (coefficient=-1.06, 95% CI -4.53 to 2.41; P=.55) or recent quitters (coefficient=1.76, 95% CI -2.07 to 5.59; P=.37). There were also no differences in tobacco purchases by exposure to graphic (current smokers: coefficient=0.93, 95% CI 0.67 to 1.29; P=.66 and recent quitters: coefficient=0.73, 95% CI 0.44 to 1.19; P=.20) or supportive (current smokers: coefficient=1.05, 95% CI 0.75 to 1.46; P=.78 and recent quitters: coefficient=0.73, 95% CI 0.45 to 1.18; P=.20) antismoking ads or price promotions (current smokers: coefficient=1.09, 95% CI 0.86 to 1.38; P=.49 and recent quitters: coefficient=0.90, 95% CI 0.62 to 1.31; P=.60). CONCLUSIONS: The results of this analysis support future research on the ability of supportive antismoking ads to reduce urges to smoke among current cigarette smokers. Research on urges to smoke has important tobacco control implications, given the relationship between urge to smoke and smoking cigarettes, time to next smoke, and amount smoked.

Tobacco use among lesbian, gay, bisexual and transgender young adults varies by sexual and gender identity.

BACKGROUND: Research shows that tobacco products are disproportionately used by sexual and gender minorities, known collectively as those who are lesbian, gay, bisexual, and transgender (LGBT). While usage varies within this population by identity, differences in tobacco use patterns are not well understood. The present study uses evaluation data for This Free Life, a tobacco public education campaign from the FDA, to examine differences in tobacco use among LGBT young adults by subgroups based on sex at birth, gender and sexual identity. METHODS: Data are from 4,057 18-24 LGBT young adults who completed the baseline This Free Life evaluation survey in 2016. Multivariable logistic regression models examined differences in tobacco use (cigarettes, cigars, hookah and electronic nicotine products) and poly use (2+ of any product, 2+ combustibles, at least one combustible and one noncombustible) between LGBT subgroups (cisgender gay males, cisgender bisexual males, cisgender lesbian/gay females, cisgender bisexual females and gender minorities). RESULTS: Sexual minority females were more likely than gay males to use any tobacco product, electronic nicotine products and hookah. Cisgender bisexuals were more likely than gay males and gender minorities to use electronic nicotine products. Cisgender bisexual males were less likely than all other groups to use cigarettes. Cisgender sexual minority females were more likely than gender minorities to engage in poly use. CONCLUSIONS: Findings suggest that sexual minority females are more likely to use tobacco than other subgroups. More research can help campaign developers better understand reasons for intragroup differences in tobacco use among LGBT subgroups.

LGBT Identity and Its Influence on Perceived Effectiveness of Advertisements from a LGBT Tobacco Public Education Campaign.

Lesbian, gay, bisexual, and transgender (LGBT) individuals are at increased risk for tobacco use compared to those who are not LGBT. The Food and Drug Administration's Center for Tobacco Products launched the first U.S. large-scale tobacco public education campaign for LGBT young adults aged 18-24, This Free Life. The current study, using data from the evaluation of the This Free Life campaign, investigated the role of LGBT Identity Affirmation (i.e., the development of positive feelings or attachment to being LGBT), LGBT Identity Centrality (i.e., the degree to which an aspect of a person's identity shapes their overall identity), and Identification with the LGBT Community (i.e., an individual's relationship with the LGBT community) on perceived effectiveness of four This Free Life advertisements. The current study sample included 2,788 LGBT young adults. For the "Our Story" and "Flawless" advertisements, all three identity constructs were statistically significant positive predictors of perceived advertisement effectiveness. For female-centric and male-centric "Tip the Scale" advertisements, LGBT Identity Centrality and Identification with the LGBT Community were significant positive predictors. An additional secondary analysis found differences in identity constructs between sexual and gender minority subgroups. These results support that identity constructs may be leveraged in health interventions.

Recruiting Hard-to-Reach Populations for Survey Research: Using Facebook and Instagram Advertisements and In-Person Intercept in LGBT Bars and Nightclubs to Recruit LGBT Young Adults.

BACKGROUND: Tobacco public education campaigns focus increasingly on hard-to-reach populations at higher risk for smoking, prompting campaign creators and evaluators to develop strategies to reach hard-to-reach populations in virtual and physical spaces where they spend time. OBJECTIVE: The aim of this study was to describe two novel recruitment strategies (in-person intercept interviews in lesbian, gay, bisexual, and transgender [LGBT] social venues and targeted social media ads) and compares characteristics of participants recruited via these strategies for the US Food and Drug Administration's This Free Life campaign evaluation targeting LGBT young adults who smoke cigarettes occasionally. METHODS: We recruited LGBT adults aged 18-24 years in the United States via Facebook and Instagram ads (N=1709, mean age 20.94, SD 1.94) or intercept in LGBT social venues (N=2348, mean age 21.98, SD 1.69) for the baseline evaluation survey. Covariates related to recruitment strategy were age; race or ethnicity; LGBT identity; education; pride event attendance; and alcohol, cigarette, and social media use. RESULTS: Lesbian or gay women (adjusted odds ratio, AOR 1.88, 95% CI 1.54-2.29, P<.001), bisexual men and women (AOR 1.46, 95% CI 1.17-1.82, P=.001), gender minorities (AOR 1.68, 95% CI 1.26-2.25, P<.001), and other sexual minorities (AOR 2.48, 95% CI 1.62-3.80, P<.001) were more likely than gay men to be recruited via social media (than intercept). Hispanic (AOR 0.73, 95% CI 0.61-0.89, P=.001) and other or multiracial, non-Hispanic participants (AOR 0.70, 95% CI 0.54-0.90, P=.006) were less likely than white, non-Hispanic participants to be recruited via social media. As age increased, odds of recruitment via social media decreased (AOR 0.76, 95% CI 0.72-0.80, P<.001). Participants with some college education (AOR 1.27, 95% CI 1.03-1.56, P=.03) were more likely than those with a college degree to be recruited via social media. Participants reporting past 30-day alcohol use were less likely to be recruited via social media (AOR 0.33, 95% CI 0.24-0.44, P<.001). Participants who reported past-year pride event attendance were more likely to be recruited via social media (AOR 1.31, 95% CI 1.06-1.64, P=.02), as well as those who used Facebook at least once daily (AOR 1.43, 95% CI 1.14-1.80, P=.002). Participants who reported using Instagram at least once daily were less likely to be recruited via social media (AOR 0.73, 95% CI 0.62-0.86, P<.001). Social media recruitment was faster (incidence rate ratio, IRR=3.31, 95% CI 3.11-3.52, P<.001) and less expensive (2.2% of combined social media and intercept recruitment cost) but had greater data quality issues-a larger percentage of social media respondents were lost because of duplicate and low-quality responses (374/4446, 8.41%) compared with intercept respondents lost to interviewer misrepresentation (15/4446, 0.34%; P<.001). CONCLUSIONS: Social media combined with intercept provided access to important LGBT subpopulations (eg, gender and other sexual minorities) and a more diverse sample. Social media methods have more data quality issues but are faster and less expensive than intercept. Recruiting hard-to-reach populations via audience-tailored strategies enabled recruitment of one of the largest LGBT young adult samples, suggesting these methods' promise for accessing hard-to-reach populations.

Smokers' Attention to Point-of-Sale Antismoking Ads: An Eye-tracking Study.

OBJECTIVES: We used eye-tracking to examine smokers' visual attention in one of 4 antismoking ad contexts (alone, next to cigarette ad, tobacco display, or cooler). Participants viewed 4 ad types (graphic, intended emotive, and benefits of quitting-graphic ads, and benefits of quitting-informational ads), each with 3 areas of interest (AOI) (anti-ad image, anti-ad text, and other text). METHODS: Current smokers (N = 153) viewed ads for 10 seconds each. Multivariable random effect linear regressions with post-test comparisons (with sidak-adjusted p-values) were used to test for differences in fixations and dwell time by ad context and type while adjusting for covariates. Visual attention was adjusted by percentage of anti-ad area taken up by each AOI. RESULTS: Adjusting for covariates, there were no differences by ad context (p > .05). Fixations and dwell time were greatest for the image of the benefits of quitting-graphic ad, the text of the graphic ad, and the other text of the intended emotive ad (all ps < .005). Conclusions: Visual attention to antismoking ads did not vary by ad context but varied significantly by ad type.

Antismoking Ads at the Point of Sale: The Influence of Ad Type and Context on Ad Reactions.

Efforts are underway to educate consumers about the dangers of smoking at the point of sale (POS). Research is limited about the efficacy of POS antismoking ads to guide campaign development. This study experimentally tests whether the type of antismoking ad and the context in which ads are viewed influence people's reactions to the ads. A national convenience sample of 7,812 adult current smokers and recent quitters was randomized to 1 of 39 conditions. Participants viewed one of the four types of antismoking ads (negative health consequences-graphic, negative social consequences-intended emotive, benefits of quitting-informational, benefits of quitting-graphic) in one of the three contexts (alone, next to a cigarette ad, POS tobacco display). We assessed participants' reactions to the ads, including perceived effectiveness, negative emotion, affective dissonance, and motivational reaction. Graphic ads elicited more negative emotion and affective dissonance than benefits of quitting ads. Graphic ads elicited higher perceived effectiveness and more affective dissonance than intended emotive ads. Antismoking ads fared best when viewed alone, and graphic ads were least influenced by the context in which they were viewed. These results suggest that in developing POS campaigns, it is important to consider the competitive pro-tobacco context in which antismoking ads will be viewed.

Phantom smoking among young adult bar patrons.

OBJECTIVE: To explore the prevalence and sociodemographic makeup of smokers who do not self-identify as smokers (ie, phantom smokers) compared with self-identifying smokers in a sample of bar-going young adults aged 18-30 years to more accurately assess young adult prevalence of smoking and inform cessation message targeting. METHODS: Cross-sectional surveys of smokers (n=3089) were conducted in randomly selected bars/nightclubs in seven US cities. Logistic regression models assessed associations between phantom smoking (past 30-day smoking and denial of being a smoker), tobacco and alcohol use behaviours (eg, social smoking, nicotine dependence, smoking while drinking, past 30-day alcohol use) and demographics. RESULTS: Compared with smokers, phantom smokers were more likely to be college graduates (OR=1.43, 95% CI 1.03 to 1.98) and to identify themselves as social smokers (OR=1.60, 95% CI 1.27 to 2.12). Phantom smokers had lower odds of smoking while drinking (OR=0.28, 95% CI 0.25 to 0.32), being nicotine dependent (OR=0.36, 95% CI 0.22 to 0.76) and having quit for at least 1 day in the last year (OR=0.46, 95% CI 0.36 to 0.69) compared with smokers. CONCLUSIONS: This research extends phantom smoking literature on college students to provide a broader picture of phantom smoking among young adults in high-risk contexts and of varying levels of educational attainment. Phantom smokers may be particularly sensitive to social pressures against smoking, suggesting the importance of identifying smoking as a behaviour (rather than identity) in cessation messaging to ensure that phantom smokers are reached.

Comparing Twitter and Online Panels for Survey Recruitment of E-Cigarette Users and Smokers.

BACKGROUND: E-cigarettes have rapidly increased in popularity in recent years, driven, at least in part, by marketing and word-of-mouth discussion on Twitter. Given the rapid proliferation of e-cigarettes, researchers need timely quantitative data from e-cigarette users and smokers who may see e-cigarettes as a cessation tool. Twitter provides an ideal platform for recruiting e-cigarette users and smokers who use Twitter. Online panels offer a second method of accessing this population, but they have been criticized for recruiting too few young adults, among whom e-cigarette use rates are highest. OBJECTIVE: This study compares effectiveness of recruiting Twitter users who are e-cigarette users and smokers who have never used e-cigarettes via Twitter to online panelists provided by Qualtrics and explores how users recruited differ by demographics, e-cigarette use, and social media use. METHODS: Participants were adults who had ever used e-cigarettes (n=278; male: 57.6%, 160/278; age: mean 34.26, SD 14.16 years) and smokers (n=102; male: 38.2%, 39/102; age: mean 42.80, SD 14.16 years) with public Twitter profiles. Participants were recruited via online panel (n=190) or promoted tweets using keyword targeting for e-cigarette users (n=190). Predictor variables were demographics (age, gender, education, race/ethnicity), e-cigarette use (eg, past 30-day e-cigarette use, e-cigarette puffs per day), social media use behaviors (eg, Twitter use frequency), and days to final survey completion from survey launch for Twitter versus panel. Recruitment method (Twitter, panel) was the dependent variable. RESULTS: Across the total sample, participants were recruited more quickly via Twitter (incidence rate ratio=1.30, P=.02) than panel. Compared with young adult e-cigarette users (age 18-24 years), e-cigarette users aged 25 to 34 years (OR 0.01, 95% CI 0.00-0.60, P=.03) and 35 to 44 years (OR 0.01, 95% CI 0.00-0.51, P=.02) were more likely to be recruited via Twitter than panel. Smokers aged 35 to 44 years were less likely than those aged 18 to 24 years to be recruited via Twitter than panel (35-44: OR 0.03, 95% CI 0.00-0.49, P=.01). E-cigarette users who reported a greater number of e-cigarette puffs per day were more likely to be recruited via Twitter than panel compared to those who reported fewer puffs per day (OR 1.12, 95% CI 1.05-1.20, P=.001). With each one-unit increase in Twitter usage, e-cigarette users were 9.55 times (95% CI 2.28-40.00, P=.002) and smokers were 4.91 times (95% CI 1.90-12.74, P=.001) as likely to be recruited via Twitter than panel. CONCLUSIONS: Twitter ads were more time efficient than an online panel in recruiting e-cigarette users and smokers. In addition, Twitter provided access to younger adults, who were heavier users of e-cigarettes and Twitter. Recruiting via social media and online panel in combination offered access to a more diverse population of participants.

Using Twitter Data to Gain Insights into E-cigarette Marketing and Locations of Use: An Infoveillance Study.

BACKGROUND: Marketing and use of electronic cigarettes (e-cigarettes) and other electronic nicotine delivery devices have increased exponentially in recent years fueled, in part, by marketing and word-of-mouth communications via social media platforms, such as Twitter. OBJECTIVE: This study examines Twitter posts about e-cigarettes between 2008 and 2013 to gain insights into (1) marketing trends for selling and promoting e-cigarettes and (2) locations where people use e-cigarettes. METHODS: We used keywords to gather tweets about e-cigarettes between July 1, 2008 and February 28, 2013. A randomly selected subset of tweets was manually coded as advertising (eg, marketing, advertising, sales, promotion) or nonadvertising (eg, individual users, consumers), and classification algorithms were trained to code the remaining data into these 2 categories. A combination of manual coding and natural language processing methods was used to indicate locations where people used e-cigarettes. Additional metadata were used to generate insights about users who tweeted most frequently about e-cigarettes. RESULTS: We identified approximately 1.7 million tweets about e-cigarettes between 2008 and 2013, with the majority of these tweets being advertising (93.43%, 1,559,508/1,669,123). Tweets about e-cigarettes increased more than tenfold between 2009 and 2010, suggesting a rapid increase in the popularity of e-cigarettes and marketing efforts. The Twitter handles tweeting most frequently about e-cigarettes were a mixture of e-cigarette brands, affiliate marketers, and resellers of e-cigarette products. Of the 471 e-cigarette tweets mentioning a specific place, most mentioned e-cigarette use in class (39.1%, 184/471) followed by home/room/bed (12.5%, 59/471), school (12.1%, 57/471), in public (8.7%, 41/471), the bathroom (5.7%, 27/471), and at work (4.5%, 21/471). CONCLUSIONS: Twitter is being used to promote e-cigarettes by different types of entities and the online marketplace is more diverse than offline product offerings and advertising strategies. E-cigarettes are also being used in public places, such as schools, underscoring the need for education and enforcement of policies banning e-cigarette use in public places. Twitter data can provide new insights on e-cigarettes to help inform future research, regulations, surveillance, and enforcement efforts.