ImportanceThe rapid expansion of virtual health care has caused a surge in patient messages concomitant with more work and burnout among health care professionals. Artificial intelligence (AI) assistants could potentially aid in creating answers to patient questions by drafting responses that could be reviewed by clinicians.ObjectiveTo evaluate the ability of an AI chatbot assistant (ChatGPT), released in November 2022, to provide quality and empathetic responses to patient questions.Design, Setting, and ParticipantsIn this cross-sectional study, a public and nonidentifiable database of questions from a public social media forum (Reddit’s r/AskDocs) was used to randomly draw 195 exchanges from October 2022 where a verified physician responded to a public question. Chatbot responses were generated by entering the original question into a fresh session (without prior questions having been asked in the session) on December 22 and 23, 2022. The original question along with anonymized and randomly ordered physician and chatbot responses were evaluated in triplicate by a team of licensed health care professionals. Evaluators chose “which response was better” and judged both “the quality of information provided” (very poor, poor, acceptable, good, or very good) and “the empathy or bedside manner provided” (not empathetic, slightly empathetic, moderately empathetic, empathetic, and very empathetic). Mean outcomes were ordered on a 1 to 5 scale and compared between chatbot and physicians.ResultsOf the 195 questions and responses, evaluators preferred chatbot responses to physician responses in 78.6% (95% CI, 75.0%-81.8%) of the 585 evaluations. Mean (IQR) physician responses were significantly shorter than chatbot responses (52 [17-62] words vs 211 [168-245] words; t = 25.4; P < .001). Chatbot responses were rated of significantly higher quality than physician responses (t = 13.3; P < .001). The proportion of responses rated as good or very good quality (≥ 4), for instance, was higher for chatbot than physicians (chatbot: 78.5%, 95% CI, 72.3%-84.1%; physicians: 22.1%, 95% CI, 16.4%-28.2%;). This amounted to 3.6 times higher prevalence of good or very good quality responses for the chatbot. Chatbot responses were also rated significantly more empathetic than physician responses (t = 18.9; P < .001). The proportion of responses rated empathetic or very empathetic (≥4) was higher for chatbot than for physicians (physicians: 4.6%, 95% CI, 2.1%-7.7%; chatbot: 45.1%, 95% CI, 38.5%-51.8%; physicians: 4.6%, 95% CI, 2.1%-7.7%). This amounted to 9.8 times higher prevalence of empathetic or very empathetic responses for the chatbot.ConclusionsIn this cross-sectional study, a chatbot generated quality and empathetic responses to patient questions posed in an online forum. Further exploration of this technology is warranted in clinical settings, such as using chatbot to draft responses that physicians could then edit. Randomized trials could assess further if using AI assistants might improve responses, lower clinician burnout, and improve patient outcomes.

There is widespread concern that the coronavirus disease 2019 (COVID-19) pandemic may harm population mental health, chiefly owing to anxiety about the disease and its societal fallout. 1 But traditional population mental health surveillance (eg, telephone surveys, medical records) is time consuming, expensive, and may miss persons who do not participate or seek care. To evaluate the association of COVID-19 with anxiety on a population basis, we examined internet searches 2 indicative of acute anxiety during the early stages of the COVID-19 pandemic.

until 2010 but has slowed recently. Although multiple patient characteristics, comorbidities, and treatment factors were associated with the receipt of SCP, these were outweighed by the hospital where the patient received care. Indeed, 1 hospital achieved an administration rate of 64%, but more than 40% of hospitals administered SCP to fewer than 20% of eligible patients. These findings may reflect differences in hospital policies, physician inexperience with prescribing SCP, or lingering concerns about the safety of SCP in patients with CHD.One limitation of our study is that we did not have information about whether patients were offered and refused medications. Another limitation is that our database may not be fully representative of the United States. In addition, the ICD-9-CM code for tobacco use has high specificity but low sensitivity. 5 Although some active smokers could have been missed in our analyses, we are confident that patients included were indeed smokers.

Smokers who have used e-cigarettes may be at increased risk for not being able to quit smoking. These findings, which need to be confirmed by longer-term cohort studies, have important policy and regulation implications regarding the use of e-cigarettes among smokers.

BACKGROUND AND OBJECTIVES: Non-cigarette tobacco marketing is less regulated and may promote cigarette smoking among adolescents. We quantified receptivity to advertising for multiple tobacco products and hypothesized associations with susceptibility to cigarette smoking.

IMPORTANCE Cigarette marketing contributes to initiation of cigarette smoking among young people, which has led to restrictions on use of cigarette advertising. However, little is known about other tobacco advertising and progression to tobacco use in youth and young adults. OBJECTIVE To investigate whether receptivity to tobacco advertising among youth and young adults is associated with progression (being a susceptible never user or ever user) to use of the product advertised, as well as conventional cigarette smoking. DESIGN, SETTING, AND PARTICIPANTS The Population Assessment of Tobacco and Health (PATH) Study at wave 1 (2013-2014) and 1-year follow-up at wave 2 (2014-2015) was conducted in a US population-based sample of never tobacco users aged 12 to 24 years from wave 1 of the PATH Study (N = 10 989). Household interviews using audio computer-assisted self-interviews were conducted. EXPOSURES Advertising for conventional cigarettes, electronic cigarettes (e-cigarettes), cigars, and smokeless tobacco products at wave 1. MAIN OUTCOMES AND MEASURES Progression to susceptibility or ever tobacco use at 1-year follow-up in wave 2. RESULTS Of the 10 989 participants (5410 male [weighted percentage, 48.3%]; 5579 female [weighted percentage, 51.7%]), receptivity to any tobacco advertising at wave 1 was high for those aged 12 to 14 years (44.0%; 95% confidence limit [CL], 42.6%-45.4%) but highest for those aged 18 to 21 years (68.7%; 95% CL, 64.9%-72.2%). e-Cigarette advertising had the highest receptivity among all age groups. For those aged 12 to 17 years, susceptibility to use a product at wave 1 was significantly associated with product use at wave 2 for conventional cigarettes, e-cigarettes, cigars, and smokeless tobacco products. Among committed never users aged 12 to 17 years at wave 1, any receptivity was associated with progression toward use of the product at wave 2

The reasons for using electronic nicotine delivery systems (ENDS) are poorly understood and are primarily documented by expensive cross-sectional surveys that use preconceived close-ended response options rather than allowing respondents to use their own words. We passively identify the reasons for using ENDS longitudinally from a content analysis of public postings on Twitter. All English language public tweets including several ENDS terms (e.g., “e-cigarette” or “vape”) were captured from the Twitter data stream during 2012 and 2015. After excluding spam, advertisements, and retweets, posts indicating a rationale for vaping were retained. The specific reasons for vaping were then inferred based on a supervised content analysis using annotators from Amazon’s Mechanical Turk. During 2012 quitting combustibles was the most cited reason for using ENDS with 43% (95%CI 39–48) of all reason-related tweets cited quitting combustibles, e.g., “I couldn’t quit till I tried ecigs,” eclipsing the second most cited reason by more than double. Other frequently cited reasons in 2012 included ENDS’s social image (21%; 95%CI 18–25), use indoors (14%; 95%CI 11–17), flavors (14%; 95%CI 11–17), safety relative to combustibles (9%; 95%CI 7–11), cost (3%; 95%CI 2–5) and favorable odor (2%; 95%CI 1–3). By 2015 the reasons for using ENDS cited on Twitter had shifted. Both quitting combustibles and use indoors significantly declined in mentions to 29% (95%CI 24–33) and 12% (95%CI 9–16), respectively. At the same time, social image increased to 37% (95%CI 32–43) and lack of odor increased to 5% (95%CI 2–5), the former leading all cited reasons in 2015. Our data suggest the reasons people vape are shifting away from cessation and toward social image. The data also show how the ENDS market is responsive to a changing policy landscape. For instance, smoking indoors was less frequently cited in 2015 as indoor smoking restrictions became more common. Because the data and analytic approach are scalable, adoption of our strategies in the field can inform follow-up survey-based surveillance (so the right questions are asked), interventions, and policies for ENDS.

Many smokers believe that electronic nicotine delivery systems (ENDS) and pharmaceutical cessation aids can help them quit smoking or reduce cigarette consumption, but the evidence for e-cigarettes to aid quitting is limited. Examining 3,093 quit attempters in the nationally representative US Population Assessment of Tobacco and Health (PATH) Study, using data from 2013-2015, we evaluated the influence of ENDS and pharmaceutical cessation aids on persistent abstinence (≥30 days) from cigarettes and reduced cigarette consumption, using propensity score matching to balance comparison groups on potential confounders and multiple imputation to handle missing data. At PATH Wave 2, 25.2% of quit attempters reported using ENDS to quit during the previous year, making it the most popular cessation aid in 2014-2015. More quit attempters were persistently cigarette abstinent than were persistently tobacco abstinent (15.5% (standard error, 0.8) vs. 9.6% (standard error, 0.6)). Using ENDS to quit cigarettes increased the probability of persistent cigarette abstinence at Wave 2 (risk difference (RD) = 6%, 95% confidence interval (CI): 2, 10), but using approved pharmaceutical aids did not (for varenicline, RD = 2%, 95% CI: -6, 13; for bupropion, RD = 4%, 95% CI: -6, 17; for nicotine replacement therapy, RD = -3%, 95% CI: -8, 2). Among quit attempters who relapsed, ENDS did not reduce the average daily cigarette consumption (cigarettes per day, -0.18, 95% CI: -1.87, 1.51).