The Reddit cannabis subjective highness rating scale: Applying computational social science to explore psychological and environmental correlates of naturalistic cannabis use.

Social media data provide unprecedented access to discussions of active, naturalistic, and often real-time cannabis use in an era of cannabis policy liberalization. The aim of this study was to explore psychological and environmental correlates of cannabis effects by applying computational social science approaches to a large dataset of unprompted reports of naturalistic cannabis use with corresponding self-reported numerical ratings of subjective highness. Post title text was extracted via the Pushshift dataset from N = 328,865 posts to the r/trees Reddit community, where posters self-assess and disclose how high they feel on a scale from 1 to 10 (M = 6.9, SD = 1.8). Structural topic modelling and Linguistic Inquiry and Word Count (LIWC) dictionary-based approaches were applied to identify (1) frequently discussed topics and (2) text indicative of 5 psychological processes (affective, social, cognitive, perceptual, biological), respectively, as well as to examine relationships between subjective highness and (1) topic prevalence and (2) psychological process word counts. A 40-topic model was selected for interpretation based on semantic coherence and exclusivity. The most discussed topics in a 40-topic model were characterized by references to smoking places, social contexts, positive affect, cognitive states, as well as food and media consumed. In LIWC dictionary analyses, words mentioning affective, social, and cognitive processes were referenced more often than perceptual or body processes. Posters reported greater subjective highness when using language that referred to in-person social environments and lower subjective highness when using language that referred to online social environments and positive affect psychological states. This examination of unprompted online reports of naturalistic cannabis use identified textual content referring to affect and to other people as being associated with perceived effects of cannabis. These affective and social aspects of the cannabis use experience were salient to active posters in this online community and should be integrated into experience sampling methods and behavioral pharmacology research, as well as public health messaging.

"I got a bunch of weed to help me through the withdrawals": Naturalistic cannabis use reported in online opioid and opioid recovery community discussion forums.

A growing body of research has reported on the potential opioid-sparing effects of cannabis and cannabinoids, but less is known about specific mechanisms. The present research examines cannabis-related posts in two large online communities on the Reddit platform ("subreddits") to compare mentions of naturalistic cannabis use by persons self-identifying as actively using opioids versus persons in recovery. We extracted all posts mentioning cannabis-related keywords (e.g., "weed", "cannabis", "marijuana") from December 2015 through August 2019 from an opioid use subreddit and an opioid recovery subreddit. To investigate how cannabis is discussed at-scale, we identified and compared the most frequent phrases in cannabis-related posts in each subreddit using term-frequency-inverse document frequency (TF-IDF) weighting. To contextualize these findings, we also conducted a qualitative content analysis of 200 random posts (100 from each subreddit). Cannabis-related posts were about twice as prevalent in the recovery subreddit (n = 908; 5.4% of 16,791 posts) than in the active opioid use subreddit (n = 4,224; 2.6% of 159,994 posts, p < .001). The most frequent phrases from the recovery subreddit referred to time without using opioids and the possibility of using cannabis as a "treatment." The most frequent phrases from the opioid subreddit referred to concurrent use of cannabis and opioids. The most common motivations for using cannabis were to manage opioid withdrawal symptoms in the recovery subreddit, often in conjunction with anti-anxiety and GI-distress "comfort meds," and to enhance the "high" when used in combination with opioids in the opioid subreddit. Despite limitations in generalizability from pseudonymous online posts, this examination of reports of naturalistic cannabis use in relation to opioid use identified withdrawal symptom management as a common motivation. Future research is warranted with more structured assessments that examines the role of cannabis and cannabinoids in addressing both somatic and affective symptoms of opioid withdrawal.

Google shopping queries for vaping products, JUUL and IQOS during the E-cigarette, or Vaping, product use Associated Lung Injury (EVALI) outbreak.

OBJECTIVES: To assess whether the late 2019 US outbreak of pulmonary disease linked to vaping ('E-cigarette, or Vaping, product use Associated Lung Injury' (EVALI)) impacted online shopping queries for vaping products and the Philip Morris 'IQO' brand of heated tobacco. METHODS: We tracked online shopping queries for vape(s), JUUL and IQOS by analysing rates of Google queries indicative of shopping (eg, buy IQOS) after news of the outbreak was first reported (the week of 29 July 2019) until hospitalisations ceased (the week of 16 February 2020). We compared observed rates of shopping during the outbreak to counterfactual expected rates that were predicted using an autoregressive iterative moving average model fit to queries from 1 January 2014 to the week of 21 July 2019. RESULTS: During the outbreak, vape shopping queries were 34% (95% CI 30% to 38%) lower than expected and JUUL shopping queries were 39% (95% CI 34% to 45%) lower than expected, translating into about 7.2 and 1.0 million fewer searches. IQOS shopping queries were 58% (95% prediction interval (PI): 34-87) higher than expected, translating into 35 000 more searches. Moreover, IQOS shopping queries reached a historic high the week they were discussed as a potentially safe alternative to vaping (the week of 29 September 2019), when they were 382% (95% PI: 219-881) above expected rates for the week. CONCLUSIONS: These results suggest that unplanned events, such as the EVALI outbreak, can provoke changes in the epidemiology of product usage. Tobacco companies should be prohibited from using events such as disease outbreaks to position their products as less harmful without prior approval.

News coverage of the E-cigarette, or Vaping, product use Associated Lung Injury (EVALI) outbreak and internet searches for vaping cessation.

BACKGROUND: In the latter half of 2019, an outbreak of pulmonary disease in the USA resulted in 2807 hospitalisations and 68 deaths, as of 18 February 2020. Given the severity of the outbreak, we assessed whether articles during the outbreak era more frequently warned about the dangers of vaping and whether internet searches for vaping cessation increased. METHODS: Using Tobacco Watcher, a media monitoring platform that automatically identifies and categorises news articles from sources across the globe, we obtained all articles that (a) discussed the outbreak and (b) primarily warned about the dangers of vaping. We obtained internet search trends originating from the USA that mentioned 'quit' or 'stop' and 'e cig(s),' 'ecig(s),' 'e-cig(s),' 'e cigarette(s),' 'e-cigarette(s),' 'electronic cigarette(s),' 'vape(s),' 'vaping' or 'vaper(s)' from Google Trends (eg, 'how do I quit vaping?'). All data were obtained from 1 January 2014 to 18 February 2020 and ARIMA models were used with historical trends to forecast the ratio of observed to expected search volumes during the outbreak era. RESULTS: News of the vaping-induced pulmonary disease outbreak was first reported on 25 July 2019 with 195 articles, culminating in 44 512 articles by 18 February 2020. On average, news articles warning about the dangers of vaping were 130% (95% prediction interval (PI): -15 to 417) and searches for vaping cessation were 76% (95% PI: 28 to 182) higher than expected levels for the days during the period when the sources of the outbreak were unknown (25 July to 27 September 2019). News and searches stabilised just after the US Centers for Disease Control and Prevention reported that a primary source of the outbreak was an additive used in marijuana vapes on 27 September 2019. In sum, there were 12 286 articles archived in Tobacco Watcher primarily warning about the dangers of vaping and 1 025 000 cessation searches following the outbreak. CONCLUSION: The vaping-induced pulmonary disease outbreak spawned increased coverage about the dangers of vaping and internet searches for vaping cessation. Resources and strategies that respond to this elevated interest should become a priority among public health leaders.

Automated image analysis of instagram posts: Implications for risk perception and communication in public health using a case study of #HIV.

People's perceptions about health risks, including their risk of acquiring HIV, are impacted in part by who they see portrayed as at risk in the media. Viewers in these cases are asking themselves "do those portrayed as at risk look like me?" An accurate perception of risk is critical for high-risk populations, who already suffer from a range of health disparities. Yet, to date no study has evaluated the demographic representation of health-related content from social media. The objective of this case study was to apply automated image recognition software to examine the demographic profile of faces in Instagram posts containing the hashtag #HIV (obtained from January 2017 through July 2018) and compare this to the demographic breakdown of those most at risk of a new HIV diagnosis (estimates of incidence of new HIV diagnoses from the 2017 US Centers for Disease Control HIV Surveillance Report). We discovered 26,766 Instagram posts containing #HIV authored in American English with 10,036 (37.5%) containing a detectable human face with a total of 18,227 faces (mean = 1.8, standard deviation [SD] = 1.7). Faces skewed older (47% vs. 11% were 35-39 years old), more female (41% vs. 19%), more white (43% vs. 26%), less black (31% vs 44%), and less Hispanic (13% vs 25%) on Instagram than for new HIV diagnoses. The results were similarly skewed among the subset of #HIV posts mentioning pre-exposure prophylaxis (PrEP). This disparity might lead Instagram users to potentially misjudge their own HIV risk and delay prophylactic behaviors. Social media managers and organic advocates should be encouraged to share images that better reflect at-risk populations so as not to further marginalize these populations and to reduce disparity in risk perception. Replication of our methods for additional diseases, such as cancer, is warranted to discover and address other misrepresentations.

Responses to addiction help-seeking from Alexa, Siri, Google Assistant, Cortana, and Bixby intelligent virtual assistants.

We investigated how intelligent virtual assistants (IVA), including Amazon's Alexa, Apple's Siri, Google Assistant, Microsoft's Cortana, and Samsung's Bixby, responded to addiction help-seeking queries. We recorded if IVAs provided a singular response and if so, did they link users to treatment or treatment referral services. Only 4 of the 70 help-seeking queries presented to the five IVAs returned singular responses, with the remainder prompting confusion (e.g., "did I say something wrong?"). When asked "help me quit drugs" Alexa responded with a definition for the word drugs. "Help me quit…smoking" or "tobacco" on Google Assistant returned Dr. QuitNow (a cessation app), while on Siri "help me quit pot" promoted a marijuana retailer. IVAs should be revised to promote free, remote, federally sponsored addiction services, such as SAMSHA's 1-800-662-HELP helpline. This would benefit millions of IVA users now and more to come as IVAs displace existing information-seeking engines.

A Social Cognitive Theory-based Framework for Monitoring Medication Adherence Applied to Endocrine Therapy in Breast Cancer Survivors.

Poor adherence to long-term therapies for chronic diseases, such as cancer, compromises effectiveness of treatment and increases the likelihood of disease progression, making medication adherence a critical issue in population health. While the field has documented many eers to adherence to medication, it has also come up with few efficacious solutions to medication adherence, indicating that new and innovative approaches are needed. In this paper, we evaluate medication-taking behaviors based on social cognitive theory (SCT), presenting patterns of adherence stratified across SCT constructs in 33 breast cancer survivors over an 8-month period. Findings indicate that medication adherence is a very personal experience influenced by many simultaneously interacting factors, and a deeper contextual understanding is needed to understand and develop interventions targeting non-adherence.

"Is this a STD? Please help!": Online Information Seeking for Sexually Transmitted Diseases on Reddit.

Increasing incidence of sexually transmitted diseases (STDs) has prompted the public health and technology communities to innovate new measures to understand how individuals use Internet resources to attain relevant information, particularly for sensitive or stigmatized conditions. The purpose of this study is to examine recent health information seeking and needs of the r/STD community, a subreddit focused exclusively on STDs. We found that the majority of posts crowd-source information about intermediate, non-reportable STDs such as human papillomavirus (HPV). Crowdsourced information in this community focused on symptoms, treatment, as well as the social and emotional aspects of sexual health such as fear of misdiagnosis. From our analysis, it is clear that online communities focused on discussion of health symptoms have the ripe potential to influence information-seeking behavior and consumer action.