Inferring sleep disturbance from text messages of suicide attempt survivors: A pilot study.

OBJECTIVE: Identifying digital markers of sleep disturbance-a known suicide risk factor-may aid in the detection of imminent suicide risk. This study examined sleep-related communication and texting patterns in personal text messages (N = 86,705) of suicide attempt survivors. METHOD: Twenty-six participants provided dates of past suicide attempts and 2-week periods of positive mood, depressed mood, or suicidal ideation. Linguistic Inquiry Word Count was used to identify sleep-related texts via a custom dictionary. Mixed effect models were fitted to test the association between suicide/mood episode type (e.g., attempt versus ideation) and three outcomes: likelihood of a text including sleep-related content, nightly count of texts sent from midnight to 5:00 AM, and sum of unique hour bins from midnight to 5:00 AM with outgoing texts. RESULTS: Analyses with a sleep dictionary that was manually revised to be more accurate (but not the original unedited dictionary) showed sleep-related communication was more likely during depressed mood episodes than positive mood episodes. Otherwise, there were no significant differences in sleep-related communication or objective texting patterns across episode type. CONCLUSIONS: Although we did not detect differences in sleep-related communication tied to suicidal thoughts or behaviors, sleep-related communication may differ as a function of within-person mood level.

Types and Sources of Stigma on Opioid Use Treatment and Recovery Communities on Reddit.

Background: Digitally-mediated peer support may improve opioid use disorder (OUD) recovery. Our objective was to examine the types and sources of stigma that people seek support for in online OUD recovery communities (subreddits) on Reddit. Methods: We extracted all posts containing stigma keywords from three subreddits as well as a random sample that do not contain stigma keywords. We conducted deductive content analysis to confirm that the post self-described an experience of stigma and identify the type (condition, intervention) and source (provider-based, public, self, structural) of stigma. Results: Two-hundred and fifty-nine posts self-reported a stigmatizing experience. The majority of posts described an intervention stigma associated with medications for OUD. Posts discussing intervention stigma acknowledged the role of stigma in their treatment decision-making and quality of their treatment program. The most frequent sources of stigma were the public (including family members), provider-based (healthcare and pharmacy workers), structural (workplace, law enforcement, child protective services, and abstinence-based self-help groups), and self. No posts mentioned courtesy stigma. Posts sought assistance in navigating their experiences and participating in advocacy to counter stigmatized narratives. Conclusions: Our study indicates that people in online communities seek support to disclose and manage experiences of stigma on Reddit in similar ways to people in offline communities with the noted exception of an absence of discussions of courtesy stigma. Since each subreddit is a microcosm of varying needs, we suggest areas of future work for collaborative resources developed between stakeholders of these subreddits and public health that work within the preexisting Reddit social norms.

"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.

Public interest in ∆8-Tetrahydrocannabinol (delta-8-THC) increased in US states that restricted ∆9-Tetrahydrocannabinol (delta-9-THC) use.

BACKGROUND: There is an expanding unregulated market for a psychotropic compound called ∆8-Tetrahydrocannabinol (delta-8-THC) that is being derived from hemp, but there are no empirical estimates of public interest in this compound. METHODS: To measure public interest, we obtained yearly Google query fractions (QFs) that mentioned delta-8-THC (i.e., "delta 8," "delta-8," or "Δ8") for the past decade (from January 2011 through August 2021) for every country and territory in the world and every state in the United States (US) from Google Trends. We also obtained the same trends for the last complete month of data for all US states (July 2021) to compare across cannabis use policies. We summarized QFs across years, countries, US states and cannabis policies in US states using linear regression, means and ratios. We estimated raw search counts for the US using comscore.com. RESULTS: The global rate of delta-8-THC searches was stable between 2011 and 2019 before increasing by 257.0% from 2019 to 2020 and 705.0% from 2020 to 2021. In 2021, the rate of delta-8-THC searches in the US was at least 10 times higher than the rates in other countries or territories. In absolute terms, there were 22.3 million delta-8-THC searches in the US in the first 8 months of 2021 alone. Increases in delta-8-THC searches from 2020 to 2021 occurred in all 50 US states and the District of Columbia (Mean 854.2%; range = 256.4% - 2831.2%) but continued to vary substantially between states in 2021. In July 2021, the legal status of delta-9-THC use across US states explained 49.0% of the variance in delta-8-THC QFs between US states (R2 = 0.490; p < 0.001) and was inversely associated, where delta-8-THC QFs were higher in jurisdictions with stricter cannabis use policies. CONCLUSION: Public interest in delta-8-THC increased rapidly in 2020 and 2021 and was particularly high in US states that restricted delta-9-THC use. Jurisdictions should clarify whether delta-8-THC can be sold as a hemp product.

Characterizing Self-Reports of Self-Identified Patient Experiences with Methadone Maintenance Treatment on an Online Community during COVID-19.

Background: The coronavirus disease (COVID-19) pandemic has impacted patients receiving methadone maintenance treatment (MMT) through opioid treatment programs (OTPs), especially because of the unique challenges of the care delivery model. Previously, documentation of patient experiences during emergencies often comes years after the fact, in part because there is a substantial data void in real-time. Methods: We extracted 308 posts that mention COVID-19 keywords on r/methadone, an online community for patients receiving MMT to share information, on Reddit occurring between January 31, 2020 and September 30, 2020. 215 of these posts self-report an impact to their MMT. Using qualitative content analysis, we characterized the impacts described in these posts and identified four emergent themes describing patients' experience of impacts to MMT during COVID-19. Results: The themes included (1) 54.4% of posts reporting impediments to accessing their methadone, (2) 28.4% reporting impediments to accessing physicial OTPs, (3) 19.5% reporting having to self-manage their care, and (4) 4.7% reporting impediments to accessing OTP providers and staff. Conclusions: Patients described unanticipated consequences to one-size-fits-all policies that are unevenly applied resulting in suboptimal dosing, increased perceived risk of acquiring COVID-19 at OTPs, and reduced interaction with OTP providers and staff. While preliminary, these results are formative for follow-up surveillance metrics for patients of OTPs as well as digitally-mediated resource needs for this online community. This study serves as a model of how social media can be employed during and after emergencies to hear the lived experiences of patients for informed emergency preparedness and response.

Monitoring HIV testing and pre-exposure prophylaxis information seeking by combining digital and traditional data.

BACKGROUND: Public health is increasingly turning to non-traditional digital data to inform HIV prevention and control strategies. We demonstrate a parsimonious method using both traditional survey and internet search histories to provide new insights into HIV testing and pre-exposure prophylaxis (PrEP) information seeking that can be easily extended to other settings. METHOD: We modeled how US internet search volumes from 2019 for HIV testing and PrEP compared against expected search volumes for HIV testing and PrEP using state HIV prevalence and socioeconomic characteristics as predictors. States with search volumes outside the upper and lower bound confidence interval were labeled as either over or under performing. State performance was evaluated by (a) Centers for Disease Control and Prevention designation as a hotspot for new HIV diagnoses (b) expanding Medicaid coverage. RESULTS: Ten states over-performed in models assessing information seeking for HIV testing, while eleven states under-performed. Thirteen states over-performed in models assessing internet searches for PrEP information, while thirteen states under-performed. States that expanded Medicaid coverage were more likely to over perform in PrEP models than states that did not expand Medicaid coverage. While states that were hotspots for new HIV diagnoses were more likely to over perform on HIV testing searches. CONCLUSION: Our study derived a method of measuring HIV and PrEP information seeking that is comparable across states. Several states exhibited information seeking for PrEP and HIV testing that deviated from model assessments. Statewide search volume for PrEP information was affected by a state's decision to expand Medicaid coverage. Our research provides health officials with an innovative way to monitor statewide interest in PrEP and HIV testing using a metric for information-seeking that is comparable across states.

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.

Quantifying Public Interest in Police Reforms by Mining Internet Search Data Following George Floyd's Death.

BACKGROUND: The death of George Floyd while in police custody has resurfaced serious questions about police conduct that result in the deaths of unarmed persons. OBJECTIVE: Data-driven strategies that identify and prioritize the public's needs may engender a public health response to improve policing. We assessed how internet searches indicative of interest in police reform changed after Mr Floyd's death. METHODS: We monitored daily Google searches (per 10 million total searches) that included the terms "police" and "reform(s)" (eg, "reform the police," "best police reforms," etc) originating from the United States between January 1, 2010, through July 5, 2020. We also monitored searches containing the term "police" with "training," "union(s)," "militarization," or "immunity" as markers of interest in the corresponding reform topics. RESULTS: The 41 days following Mr Floyd's death corresponded with the greatest number of police "reform(s)" searches ever recorded, with 1,350,000 total searches nationally. Searches increased significantly in all 50 states and Washington DC. By reform topic, nationally there were 1,220,000 total searches for "police" and "union(s)"; 820,000 for "training"; 360,000 for "immunity"; and 72,000 for "militarization." In terms of searches for all policy topics by state, 33 states searched the most for "training," 16 for "union(s)," and 2 for "immunity." States typically in the southeast had fewer queries related to any police reform topic than other states. States that had a greater percentage of votes for President Donald Trump during the 2016 election searched more often for police "union(s)" while states favoring Secretary Hillary Clinton searched more for police "training." CONCLUSIONS: The United States is at a historical juncture, with record interest in topics related to police reform with variability in search terms across states. Policy makers can respond to searches by considering the policies their constituencies are searching for online, notably police training and unions. Public health leaders can respond by engaging in the subject of policing and advocating for evidence-based policy reforms.

Self-reported Cannabidiol (CBD) Use for Conditions With Proven Therapies.

Importance: Use of cannabidiol (CBD) has markedly increased in the past 5 years, concurrent with marketing claims that over-the-counter CBD can be used to treat almost any health condition. However, the reasons why individuals use CBD remain unclear. Objective: To assess whether individuals are using CBD for diagnosable conditions that have evidence-based therapies. Design, Setting, and Participants: This case series assessed claimed treatment applications reported by CBD users in public testimonials shared on the Reddit forum r/CBD. The r/CBD forum was selected because it includes a large, naturally occurring sample of 104 917 registered individuals who publicly discuss their experiences using CBD. All r/CBD posts were obtained from January 1, 2014, through August 31, 2019. A random sample of posts was drawn (n = 3000) and filtered to include posts in which self-identified CBD users testified why they take CBD (n = 376). Exposures: Self-reported use of CBD for medicinal purposes. Main Outcomes and Measures: Cannabidiol testimonials were divided into 11 subcategories corresponding with the condition's medical subspecialty and 2 subcategories corresponding with wellness benefits. Posts were allowed to receive more than 1 label. Results: Of the 376 posts labeled as testimonials, 90.0% (95% CI, 86.8%-92.8%) of testimonials claimed that CBD treated the individual's diagnosable conditions. Psychiatric conditions (eg, autism or depression) were the most frequently cited subcategory, mentioned in 63.9% (95% CI, 59.0%-69.1%) of testimonials, followed by orthopedic (26.4%; 95% CI, 21.8%-31.1%), sleep (14.6%; 95% CI, 11.3%-18.5%), and neurological (6.9%; 95% CI, 4.4%-9.6%) conditions. Testimonials also claimed that CBD treated gastroenterological conditions (3.9%; 95% CI, 1.9%-6.1%), as well as addiction, cardiological, dermatological, ophthalmological, oral health, and sexual health conditions (<2.0% each). By contrast, just 29.5% (95% CI, 24.8%-34.2%) of testimonies claimed any wellness benefit, with most citing mental wellness (eg, "quieting my mind") (29.5% [95% CI, 24.2%-34.4%]); 1.4% (95% CI, 0.3%-2.8%) claimed a physical wellness benefit (eg, "exercise performance"). Conclusions and Relevance: The findings of this case series suggest a need for regulation of factors associated with CBD being used to treat diagnosable conditions, engagement of health care professionals with patients on their potential CBD use, and implementation of public health campaigns that encourage the public to seek treatment advice from health care professionals regarding evidence-based therapies.

Examining Peer-to-Peer and Patient-Provider Interactions on a Social Media Community Facilitating Ask the Doctor Services.

Ask the Doctor (AtD) services provide patients the opportunity to seek medical advice using online platforms. While these services represent a new mode of healthcare delivery, study of these online health communities and how they are used is limited. In particular, it is unknown if these platforms replicate existing barriers and biases in traditional healthcare delivery across demographic groups. We present an analysis of AskDocs, a subreddit that functions as a public AtD platform on social media. We examine the demographics of users, the health topics discussed, if biases present in offline healthcare settings exist on this platform, and how empathy is expressed in interactions between users and physicians. Our findings suggest a number of implications to enhance and support peer-to-peer and patient-provider interactions on online platforms.

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.

#HIV: Alignment of HIV-Related Visual Content on Instagram with Public Health Priorities in the US.

Instagram, with more than 1 billion monthly users, is the go-to social media platform to chronicle one's life via images, but how are people using the platform to present visual content about HIV? We analyzed public Instagram posts containing the hashtag "#HIV" (because they are self-tagged as related to HIV) between January 2017 and July 2018. We described the prevalence of co-occurring hashtags and explored thematic concepts in the images using automated image recognition and topic modeling. Twenty-eight percent of all #HIV posts included hashtags focused on awareness, followed by LGBTQ (24.5%) and living with HIV (17.9%). However, specific strategies were rarely cited, including testing (10.8%), treatment (10.3%), PrEP (6.2%) and condoms (4.1%). Image analyses revealed 44.5% of posts included infographics followed by people (21.3%) thereby humanizing HIV and stigmatized populations and promoting community mobilization. Novel content such as the handwriting image-theme (3.8%) where posters shared their HIV test results appeared. We discuss how this visual content aligns with public health priorities to reduce HIV in the US and the novel, organic messages that public health could help amplify.

Can Text Messages Identify Suicide Risk in Real Time? A Within-Subjects Pilot Examination of Temporally Sensitive Markers of Suicide Risk.

Objective tools to assess suicide risk are needed to determine when someone is at imminent risk. This pilot laboratory investigation utilized a within-subjects design to identify patterns in text messaging (SMS) unique to high-risk periods preceding suicide attempts. Individuals reporting a history of suicide attempt (N=33) retrospectively identified past attempts and periods of lower risk (e.g., suicide ideation). Language analysis software scored 189,478 text messages to capture three psychological constructs: self-focus, sentiment, and social engagement. Mixed-effects models tested whether these constructs differed in general (means) and over time (slopes) two weeks before a suicide attempt, relative to lower-risk periods. Regarding mean differences, no language features uniquely differentiated suicide attempts from other episodes. However, when examining patterns over time, anger increased and positive emotion decreased to a greater extent as one approached a suicide attempt. Results suggest private electronic communication has the potential to provide real-time digital markers of suicide risk.