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.

Characterizing Help-Seeking Searches for Substance Use Treatment From Google Trends and Assessing Their Use for Infoveillance: Longitudinal Descriptive and Validation Statistical Analysis.

BACKGROUND: There is no recognized gold standard method for estimating the number of individuals with substance use disorders (SUDs) seeking help within a given geographical area. This presents a challenge to policy makers in the effective deployment of resources for the treatment of SUDs. Internet search queries related to help seeking for SUDs using Google Trends may represent a low-cost, real-time, and data-driven infoveillance tool to address this shortfall in information. OBJECTIVE: This paper assesses the feasibility of using search query data related to help seeking for SUDs as an indicator of unmet treatment needs, demand for treatment, and predictor of the health harms related to unmet treatment needs. We explore a continuum of hypotheses to account for different outcomes that might be expected to occur depending on the demand for treatment relative to the system capacity and the timing of help seeking in relation to trajectories of substance use and behavior change. METHODS: We used negative binomial regression models to examine temporal trends in the annual SUD help-seeking internet search queries from Google Trends by US state for cocaine, methamphetamine, opioids, cannabis, and alcohol from 2010 to 2020. To validate the value of these data for surveillance purposes, we then used negative binomial regression models to investigate the relationship between SUD help-seeking searches and state-level outcomes across the continuum of care (including lack of care). We started by looking at associations with self-reported treatment need using data from the National Survey on Drug Use and Health, a national survey of the US general population. Next, we explored associations with treatment admission rates from the Treatment Episode Data Set, a national data system on SUD treatment facilities. Finally, we studied associations with state-level rates of people experiencing and dying from an opioid overdose, using data from the Agency for Healthcare Research and Quality and the CDC WONDER database. RESULTS: Statistically significant differences in help-seeking searches were observed over time between 2010 and 2020 (based on P<.05 for the corresponding Wald tests). We were able to identify outlier states for each drug over time (eg, West Virginia for both opioids and methamphetamine), indicating significantly higher help-seeking behaviors compared to national trends. Results from our validation analyses across different outcomes showed positive, statistically significant associations for the models relating to treatment need for alcohol use, treatment admissions for opioid and methamphetamine use, emergency department visits related to opioid use, and opioid overdose mortality data (based on regression coefficients having P≤.05). CONCLUSIONS: This study demonstrates the clear potential for using internet search queries from Google Trends as an infoveillance tool to predict the demand for substance use treatment spatially and temporally, especially for opioid use disorders.

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.

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.

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.

#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.

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.

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.

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.

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.

"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.

Tweet Classification to Assist Human Moderation for Suicide Prevention.

Social media platforms are already engaged in leveraging existing online socio-technical systems to employ just-in-time interventions for suicide prevention to the public. These efforts primarily rely on self-reports of potential self-harm content that is reviewed by moderators. Most recently, platforms have employed automated models to identify self-harm content, but acknowledge that these automated models still struggle to understand the nuance of human language (e.g., sarcasm). By explicitly focusing on Twitter posts that could easily be misidentified by a model as expressing suicidal intent (i.e., they contain similar phrases such as "wanting to die"), our work examines the temporal differences in historical expressions of general and emotional language prior to a clear expression of suicidal intent. Additionally, we analyze time-aware neural models that build on these language variants and factors in the historical, emotional spectrum of a user's tweeting activity. The strongest model achieves high (statistically significant) performance (macro F1=0.804, recall=0.813) to identify social media indicative of suicidal intent. Using three use cases of tweets with phrases common to suicidal intent, we qualitatively analyze and interpret how such models decided if suicidal intent was present and discuss how these analyses may be used to alleviate the burden on human moderators within the known constraints of how moderation is performed (e.g., no access to the user's timeline). Finally, we discuss the ethical implications of such data-driven models and inferences about suicidal intent from social media. Content warning: this article discusses self-harm and suicide.

Demographic Representation and Collective Storytelling in the Me Too Twitter Hashtag Activism Movement.

The #MeToo movement on Twitter has drawn attention to the pervasive nature of sexual harassment and violence. While #MeToo has been praised for providing support for self-disclosures of harassment or violence and shifting societal response, it has also been criticized for exemplifying how women of color have been discounted for their historical contributions to and excluded from feminist movements. Through an analysis of over 600,000 tweets from over 256,000 unique users, we examine online #MeToo conversations across gender and racial/ethnic identities and the topics that each demographic emphasized. We found that tweets authored by white women were overrepresented in the movement compared to other demographics, aligning with criticism of unequal representation. We found that intersected identities contributed differing narratives to frame the movement, co-opted the movement to raise visibility in parallel ongoing movements, employed the same hashtags both critically and supportively, and revived and created new hashtags in response to pivotal moments. Notably, tweets authored by black women often expressed emotional support and were critical about differential treatment in the justice system and by police. In comparison, tweets authored by white women and men often highlighted sexual harassment and violence by public figures and weaved in more general political discussions. We discuss the implications of this work for digital activism research and design, including suggestions to raise visibility by those who were under-represented in this hashtag activism movement. Content warning: this article discusses issues of sexual harassment and violence.

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.

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.

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.