Association between a diagnosis of diabetes mellitus and smoking abstinence: An analysis of the National Health Interview Survey.

OBJECTIVE: Both diabetes and smoking significantly increase the risk of cardiovascular disease (CVD). Understanding whether a diagnosis of diabetes can be leveraged to promote smoking cessation is a gap in the literature. METHODS: We used data from the US National Health Interview Survey, 2006 to 2018, to investigate the relationship between self-report of diagnosis of diabetes and subsequent smoking abstinence among 142,884 respondents who reported regular smoking at baseline. Effect sizes were presented as hazard ratios (HRs) derived from multivariable Cox regression models adjusted for potential confounders using diabetes as a time-dependent covariate. Subgroup-specific estimates were obtained using interaction terms between diabetes and variables of interest. RESULTS: A self-reported diagnosis of diabetes was associated with smoking abstinence (HR: 1.21; 95% CI: 1.16 to 1.27). The strength of the association varied based on race (P for interaction: 0.004), where it was strongest in African Americans (HR: 1.44; 95% CI: 1.29 to 1.60); income (P for interaction <0.001), where it was strongest in those with a yearly income less than $35,000 (HR: 1.45; 95% CI: 1.36 to 1.53); and educational attainment (P for interaction <0.001), where it was strongest in those who did not attend college (HR: 1.48; 95% CI: 1.40 to 1.57). CONCLUSION: Among adults who smoke, a diagnosis of diabetes is significantly associated with subsequent smoking abstinence. The association is strongest in socially disadvantaged demographics, including African Americans, low-income individuals, and those who did not attend college.

Evaluating strategies to recruit health researchers to participate in online survey research.

BACKGROUND: Engaging researchers as research subjects is key to informing the development of effective and relevant research practices. It is important to understand how best to engage researchers as research subjects. METHODS: A 24 factorial experiment, as part of a Multiphase Optimization Strategy, was performed to evaluate effects of four recruitment strategy components on participant opening of an emailed survey link and survey completion. Participants were members of three US-based national health research consortia. A stratified simple random sample was used to assign potential survey participants to one of 16 recruitment scenarios. Recruitment strategy components were intended to address both intrinsic and extrinsic sources of motivation, including: $50 gift, $1,000 raffle, altruistic messaging, and egoistic messaging. Multivariable generalized linear regression analyses adjusting for consortium estimated component effects on outcomes. Potential interactions among components were tested. Results are reported as adjusted odds ratios (aOR) with 95% confidence intervals (95% CI). RESULTS: Surveys were collected from June to December 2023. A total of 418 participants were included from the consortia, with final analytical sample of 400 eligible participants. Out of the final sample, 82% (341) opened the survey link and 35% (147) completed the survey. Altruistic messaging increased the odds of opening the survey (aOR 2.02, 95% CI: 1.35-2.69, p = 0.033), while egoistic messaging significantly reduced the odds of opening the survey (aOR 0.56, 95%CI 0.38-0.75, p = 0.08). The receipt of egoistic messaging increased the odds of completing the survey once opened (aOR 1.81, 95%CI: 1.39-2.23, p < 0.05). There was a significant negative interaction effect between the altruistic appeal and egoistic messaging strategies for survey completion outcome. Monetary incentives did not a have a significant impact on survey completion. CONCLUSION: Intrinsic motivation is likely to be a greater driver of health researcher participation in survey research than extrinsic motivation. Altruistic and egoistic messaging may differentially impact initial interest and survey completion and when combined may lead to improved rates of recruitment, but not survey completion. Further research is needed to determine how to best optimize message content and whether the effects observed are modified by survey burden.

Switching to e-cigarettes as harm reduction among individuals with chronic disease who currently smoke: Results of a pilot randomized controlled trial.

INTRODUCTION: E-cigarettes (ECs) may be an effective harm reduction strategy for individuals with conditions like chronic obstructive pulmonary disease (COPD), asthma, coronary artery disease (CAD), and peripheral arterial disease (PAD) who smoke combustible cigarettes (CCs). Our aim was to examine how individuals with chronic conditions transition from CCs to ECs and its impact on health outcomes. METHODS: In a pilot randomized controlled trial (RCT), patients with COPD, asthma, CAD/PAD who currently smoke CCs and have not used nicotine replacement therapy (NRT) or ECs in the past 14 days were randomized to receive ECs or combination NRT with behavioral counselling. Disease symptoms, acceptability/satisfaction (TSQM-9) and feasibility, and cigarettes per day (CPD), and/or EC use were collected at baseline, 3-, and 6-months. Descriptive statistics and a linear regression were conducted to explore changes in CPD and chronic condition-specific assessments (CAT, SAQ-7, ACT) that assess COPD, asthma, and CAD/PAD symptom change. RESULTS: At 3-months, the EC group (n=63, mean CPD=9±11) reduced their CPD by 54% vs. 60% in the NRT group (n=58, mean CPD=7±6), p=0.56. At 6-months, 17.5% had switched completely to ECs while 23% quit smoking in the NRT arm. CAT scores showed a significant 6-point reduction in the EC arm (p=0.03). Participants scored an average of 69±27 for EC effectiveness, 87±23 for convenience, and 75±27 for overall satisfaction. CONCLUSIONS: This pilot study suggests that ECs may be a safer alternative for chronic condition patients using CCs and warrants further research on expected smoking cessation/reduction among individuals who use ECs. IMPLICATIONS: The findings from this pilot RCT hold significant implications with chronic conditions such as COPD, asthma, CAD and PAD who smoke CCs. The observed reduction in cigarettes per day and improvement in respiratory symptoms suggest that switching to ECs appears feasible and acceptable among those with chronic diseases. These results suggest that ECs may offer an alternative for individuals struggling to quit CC smoking through existing pharmacotherapies. This study supports further exploration of switching to ECs as a harm reduction strategy among CC users who have been unsuccessful at quitting by other means.

Prevalence and factors associated with second hand smoke exposure among a sample of pregnant women in Cairo, Egypt.

PURPOSE: This study estimated the prevalence of and factors associated with secondhand smoke (SHS) exposure, and assessed attitudes and knowledge about SHS among pregnant women in Cairo, Egypt. METHODS: Pregnant women in the third trimester were recruited to participate in a survey assessing tobacco smoking and SHS exposure during their current pregnancy. Participants were recruited from three antenatal clinics in Cairo, Egypt, from June 2015 to May 2016. We examined differences in sociodemographic characteristics and SHS exposure, attitudes, and knowledge by smoking/SHS status. We used multivariable ordinary least squares regression to examine the association between husbands' smoking and pregnant women's mean daily hours of SHS exposure, adjusting for women's smoking status, age group, education, and urban (vs. suburban/rural) residence. RESULTS: Of two hundred pregnant women aged 16-37 years, about two-thirds (69%) had a husband who smoked tobacco. During their current pregnancy, most women reported being non-smokers (71%), and 38% of non-smokers reported being SHS-exposed. Non-smokers exposed to SHS tended to live in more rural areas and have husbands who smoked in the home. In adjusted analyses, having a husband who smoked was significantly associated with a greater mean number of hours of SHS exposure per day exposed, and this difference was driven by husbands who smoked in the home (p < 0.001). Women in the SHS-exposed group were less likely than other groups to agree that SHS exposure was harmful to their own or their future child's health; however, all groups agreed that SHS was harmful to newborn health. CONCLUSION: Among our sample of pregnant women in Cairo, Egypt, there was a high rate of SHS exposure as well as misconceptions about the safety of SHS exposure to a developing fetus. Our findings suggest a need for targeted education and gender-sensitive messaging about SHS exposure, along with improved enforcement of existing tobacco control policies.

Exposure to secondhand smoke (SHS) remains a major contributor to health problems in pregnant women and their children. Using a survey, this study sought to estimate how many pregnant women in Cairo Metropolitan Area, Egypt, were exposed to SHS and the factors contributing to that exposure, and to assess attitudes towards SHS. During their current pregnancy, 38% of non-smokers reported being exposed to SHS. Non-smokers exposed to SHS tended to live in more rural areas and have husbands who smoked in the home. Having a husband who smoked as well as a husband who smoked in the home was significantly associated with a greater average number of SHS exposure hours per day. Women in the SHS-exposed group were less likely than other groups to agree that SHS exposure was harmful to their own or their future child's health; however, all groups agreed that SHS was harmful to newborn health. Among pregnant women in Cairo, Egypt, there is a high rate of SHS exposure­often driven by SHS exposure in the home­as well as misconceptions about the safety of SHS exposure to a developing fetus. There is a need for targeted education and gender-sensitive messaging about SHS exposure along, with improved enforcement of existing tobacco control policies.

Considerations for using predictive models that include race as an input variable: The case study of lung cancer screening.

Indiscriminate use of predictive models incorporating race can reinforce biases present in source data and lead to an exacerbation of health disparities. In some countries, such as the United States, there is therefore a push to remove race from prediction models; however, there are still many prediction models that use race as an input. Biomedical informaticists who are given the responsibility of using these predictive models in healthcare environments are likely to be faced with questions like how to deal with race covariates in these models. Thus, there is a need for a pragmatic framework to help model users think through how to include race in their chosen model so as to avoid inadvertently exacerbating disparities. In this paper, we use the case study of lung cancer screening to propose a simple framework to guide how model users can approach the use (or non-use) of race inputs in the predictive models they are tasked with leveraging in electronic health records and clinical workflows.

Reducing prescribing of antibiotics for acute respiratory infections using a frontline nurse-led EHR-Integrated clinical decision support tool: protocol for a stepped wedge randomized control trial.

BACKGROUND: Overprescribing of antibiotics for acute respiratory infections (ARIs) remains a major issue in outpatient settings. Use of clinical prediction rules (CPRs) can reduce inappropriate antibiotic prescribing but they remain underutilized by physicians and advanced practice providers. A registered nurse (RN)-led model of an electronic health record-integrated CPR (iCPR) for low-acuity ARIs may be an effective alternative to address the barriers to a physician-driven model. METHODS: Following qualitative usability testing, we will conduct a stepped-wedge practice-level cluster randomized controlled trial (RCT) examining the effect of iCPR-guided RN care for low acuity patients with ARI. The primary hypothesis to be tested is: Implementation of RN-led iCPR tools will reduce antibiotic prescribing across diverse primary care settings. Specifically, this study aims to: (1) determine the impact of iCPRs on rapid strep test and chest x-ray ordering and antibiotic prescribing rates when used by RNs; (2) examine resource use patterns and cost-effectiveness of RN visits across diverse clinical settings; (3) determine the impact of iCPR-guided care on patient satisfaction; and (4) ascertain the effect of the intervention on RN and physician burnout. DISCUSSION: This study represents an innovative approach to using an iCPR model led by RNs and specifically designed to address inappropriate antibiotic prescribing. This study has the potential to provide guidance on the effectiveness of delegating care of low-acuity patients with ARIs to RNs to increase use of iCPRs and reduce antibiotic overprescribing for ARIs in outpatient settings. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04255303, Registered February 5 2020, https://clinicaltrials.gov/ct2/show/NCT04255303 .

Recognizing the value of meta-research and making it easier to find.

Meta-research is a bourgeoning field studying topics with significant relevance to health sciences librarianship, such as research reproducibility, peer review, and open access. As a discipline that studies research itself and the practices of researchers, meta-research spans disciplines and encompasses a broad spectrum of topics and methods. The breadth of meta-research presents a significant challenge for identifying published meta-research studies. Introducing a subject heading for meta-research in the controlled vocabularies of literature databases has the potential to increase the visibility of meta-research, further advance the field, and expand its impact on research practices. Given the relatively recent designation of meta-research as a field and its expanding use as a term, now is the time to develop appropriate indexing vocabulary. We seek to call attention to the value of meta-research for health sciences librarianship, describe the challenges of identifying meta-research literature with currently available key terms, and highlight the need to establish controlled vocabulary specific to meta-research.

A targeted approach to using e-cigarettes for harm reduction in adults.

Smoking remains the leading preventable cause of death and disease in the US. While e-cigarettes (EC) are undeniably harmful when used by adolescents and nonsmokers, the perpetuation of the increasing negative perceptions of EC and widespread false belief that EC are equal or more harmful than combustible cigarettes (CC) represents a significant missed public health opportunity. EC have great potential to serve as a mechanism for smoking harm reduction among hard-to-treat populations of smokers who have failed to quit with currently available treatments. In this paper, we outline why we need to overcome the hostile EC research environment to explore the potential use of EC as a harm-reduction strategy in hard-to-treat populations.

Cost-effectiveness of Direct Antiviral Agents for Hepatitis C Virus Infection and a Combined Intervention of Syringe Access and Medication-assisted Therapy for Opioid Use Disorders in an Injection Drug Use Population.

BACKGROUND: There are too many plausible permutations and scale-up scenarios of combination hepatitis C virus (HCV) interventions for exhaustive testing in experimental trials. Therefore, we used a computer simulation to project the health and economic impacts of alternative combination intervention scenarios for people who inject drugs (PWID), focusing on direct antiviral agents (DAA) and medication-assisted treatment combined with syringe access programs (MAT+). METHODS: We performed an allocative efficiency study, using a mathematical model to simulate the progression of HCV in PWID and its related consequences. We combined 2 previously validated simulations to estimate the cost-effectiveness of intervention strategies that included a range of coverage levels. Analyses were performed from a health-sector and societal perspective, with a 15-year time horizon and a discount rate of 3%. RESULTS: From a health-sector perspective (excluding criminal justice system-related costs), 4 potential strategies fell on the cost-efficiency frontier. At 20% coverage, DAAs had an incremental cost-effectiveness ratio (ICER) of $27 251/quality-adjusted life-year (QALY). Combinations of DAA at 20% with MAT+ at 20%, 40%, and 80% coverage had ICERs of $165 985/QALY, $325 860/QALY, and $399 189/QALY, respectively. When analyzed from a societal perspective (including criminal justice system-related costs), DAA at 20% with MAT+ at 80% was the most effective intervention and was cost saving. While DAA at 20% with MAT+ at 80% was more expensive (eg, less cost saving) than MAT+ at 80% alone without DAA, it offered a favorable value compared to MAT+ at 80% alone ($23 932/QALY). CONCLUSIONS: When considering health-sector costs alone, DAA alone was the most cost-effective intervention. However, with criminal justice system-related costs, DAA and MAT+ implemented together became the most cost-effective intervention.

Does Reducing Drinking in Patients with Unhealthy Alcohol Use Improve Pain Interference, Use of Other Substances, and Psychiatric Symptoms?

BACKGROUND: We aimed to investigate the impact of reducing drinking in patients with unhealthy alcohol use on improvement of chronic pain interference, substance use, and psychiatric symptoms. METHODS: We analyzed longitudinal data from 2003 to 2015 in the Veterans Aging Cohort Study, a prospective, multisite observational study of US veterans, by emulating a hypothetical randomized trial (a target trial). Alcohol use was assessed using the Alcohol Use Disorders Identification Test (AUDIT) questionnaire, and outcome conditions were assessed via validated survey items. Individuals were followed from the first time their AUDIT score was ≥ 8 (baseline), a threshold consistent with unhealthy alcohol use. We compared individuals who reduced drinking (AUDIT < 8) at the next follow-up visit with individuals who did not (AUDIT ≥ 8). We fit separate logistic regression models to estimate odds ratios for improvement of each condition 2 years postbaseline among individuals who had that condition at baseline: moderate or severe pain interference symptoms, tobacco smoking, cannabis use, cocaine use, depressive symptoms, and anxiety symptoms. Inverse probability weighting was used to account for potential selection bias and confounding. RESULTS: Adjusted 2-year odds ratios (95% confidence intervals) for associations between reducing drinking and improvement or resolution of each condition were as follows: 1.49 (0.91, 2.42) for pain interference symptoms, 1.57 (0.93, 2.63) for tobacco smoking, 1.65 (0.92, 2.95) for cannabis use, 1.83 (1.03, 3.27) for cocaine use, 1.11 (0.64, 1.92) for depressive symptoms, and 1.33 (0.80, 2.22) for anxiety symptoms. CONCLUSIONS: We found some evidence for improvement of pain interference symptoms and substance use after reducing drinking among US veterans with unhealthy alcohol use, but confidence intervals were wide.

Stroke Warning Information and Faster Treatment (SWIFT): Cost-Effectiveness of a Stroke Preparedness Intervention.

BACKGROUND: Less than 25% of stroke patients arrive to an emergency department within the 3-hour treatment window. OBJECTIVE: We evaluated the cost-effectiveness of a stroke preparedness behavioral intervention study (Stroke Warning Information and Faster Treatment [SWIFT]), a stroke intervention demonstrating capacity to decrease race-ethnic disparities in ED arrival times. METHODS: Using the literature and SWIFT outcomes for 2 interventions, enhanced educational (EE) materials, and interactive intervention (II), we assess the cost-effectiveness of SWIFT in 2 ways: (1) Markov model, and (2) cost-to-outcome ratio. The Markov model primary outcome was the cost per quality-adjusted life-year (QALY) gained using the cost-effectiveness threshold of $100 000/QALY. The primary cost-to-outcome endpoint was cost per additional patient with ED arrival <3 hours, stroke knowledge, and preparedness capacity. We assessed the ICER of II and EE versus standard care (SC) from a health sector and societal perspective using 2015 USD, a time horizon of 5 years, and a discount rate of 3%. RESULTS: The cost-effectiveness of the II and EE programs was, respectively, $227.35 and $74.63 per additional arrival <3 hours, $440.72 and $334.09 per additional person with stroke knowledge proficiency, and $655.70 and $811.77 per additional person with preparedness capacity. Using a societal perspective, the ICER for EE versus SC was $84 643 per QALY gained and the ICER for II versus EE was $59 058 per QALY gained. Incorporating fixed costs, EE and II would need to administered to 507 and 1693 or more patients, respectively, to achieve an ICER of $100 000/QALY. CONCLUSION: II was a cost-effective strategy compared with both EE and SC. Nevertheless, high initial fixed costs associated with II may limit its cost-effectiveness in settings with smaller patient populations.

Quality of health economic evaluations for the ACC/AHA stable ischemic heart disease practice guideline: A systematic review.

BACKGROUND: The American College of Cardiology/American Heart Association (ACC/AHA) recently published a rigorous framework to guide integration of economic data into clinical guidelines. We assessed the quality of economic evaluations in a major ACC/AHA clinical guidance report. METHODS: We systematically identified cost-effectiveness analyses (CEAs) of RCTs cited in the ACC/AHA 2012 Guideline for the Diagnosis and Management of Patients with Stable Ischemic Heart Disease. We extracted: (1) study identifiers; (2) parent RCT information; (3) economic analysis characteristics; and (4) study quality using the Quality of Health Economic Studies instrument (QHES). RESULTS: Quality scores were categorized as high (≥75 points) or low (<75 points). Of 1,266 citations in the guideline, 219 were RCTs associated with 77 CEAs. Mean quality score was 81 (out of 100) and improved over time, though 29.9% of studies were low-quality. Cost-per-QALY was the most commonly reported primary outcome (39.0%). Low-quality studies were less likely to report study perspective, use appropriate time horizons, or address statistical and clinical uncertainty. Funding was overwhelmingly private (83%). A detailed methodological assessment of high-quality studies revealed domains of additional methodological issues not identified by the QHES. CONCLUSIONS: Economic evaluations of RCTs in the 2012 ACC/AHA ischemic heart disease guideline largely had high QHES scores but methodological issues existed among "high-quality" studies. Because the ACC/AHA has generally been more systematic in its integration of scientific evidence compared to other professional societies, it is likely that most societies will need to proceed more cautiously in their integration of economic evidence.

Using value of information methods to determine the optimal sample size for effectiveness trials of alcohol interventions for HIV-infected patients in East Africa.

BACKGROUND: Unhealthy alcohol consumption exacerbates the HIV epidemic in East Africa. Potential benefits of new trials that test the effectiveness of alcohol interventions could not be evaluated by traditional sampling methods. Given the competition for health care resources in East Africa, this study aims to determine the optimal sample size given the opportunity cost of potentially re-allocating trial funds towards cost-effective alcohol treatments. METHODS: We used value of information methods to determine the optimal sample size by maximizing the expected net benefit of sampling for a hypothetical 2-arm intervention vs. control randomized trial, across ranges of policymaker's willingness-to-pay for the health benefit of an intervention. Probability distributions describing the relative likelihood of alternative trial results were imputed based on prior studies. In the base case, policymaker's willingness-to-pay was based on a simultaneously resource-constrained priority (routine HIV virological testing). Sensitivity analysis was performed for various willingness-to-pay thresholds and intervention durations. RESULTS: A new effectiveness trial accounting for the benefit of more precise decision-making on alcohol intervention implementation would benefit East Africa $67,000 with the optimal sample size of 100 persons per arm under the base case willingness-to-pay threshold and intervention duration of 20 years. At both a conservative willingness-to-pay of 1 x GDP/capita and a high willingness-to-pay of 3 x GDP/capita for an additional health gain added by an alcohol intervention, a new trial was not recommended due to limited decision uncertainty. When intervention duration was 10 or 5 years, there was no return on investment across suggested willingness-to-pay thresholds. CONCLUSIONS: Value of information methods could be used as an alternative approach to assist the efficient design of alcohol trials. If reducing unhealthy alcohol use is a long-term goal for HIV programs in East Africa, additional new trials with optimal sample sizes ranging from 100 to 250 persons per arm could save the opportunity cost of implementing less cost-effective alcohol strategies in HIV prevention. Otherwise, conducting a new trial is not recommended.

Potential return on investment of a family-centered early childhood intervention: a cost-effectiveness analysis.

BACKGROUND: ParentCorps is a family-centered enhancement to pre-kindergarten programming in elementary schools and early education centers. When implemented in high-poverty, urban elementary schools serving primarily Black and Latino children, it has been found to yield benefits in childhood across domains of academic achievement, behavior problems, and obesity. However, its long-term cost-effectiveness is unknown. METHODS: We determined the cost-effectiveness of ParentCorps in high-poverty, urban schools using a Markov Model projecting the long-term impact of ParentCorps compared to standard pre-kindergarten programming. We measured costs and quality adjusted life years (QALYs) resulting from the development of three disease states (i.e., drug abuse, obesity, and diabetes); from the health sequelae of these disease states; from graduation from high school; from interaction with the judiciary system; and opportunity costs of unemployment with a lifetime time horizon. The model was built, and analyses were performed in 2015-2016. RESULTS: ParentCorps was estimated to save $4387 per individual and increase each individual's quality adjusted life expectancy by 0.27 QALYs. These benefits were primarily due to the impact of ParentCorps on childhood obesity and the subsequent predicted prevention of diabetes, and ParentCorps' impact on childhood behavior problems and the subsequent predicted prevention of interaction with the judiciary system and unemployment. Results were robust on sensitivity analyses, with ParentCorps remaining cost saving and health generating under nearly all assumptions, except when schools had very small pre-kindergarten programs. CONCLUSIONS: Effective family-centered interventions early in life such as ParentCorps that impact academic, behavioral and health outcomes among children attending high-poverty, urban schools have the potential to result in longer-term health benefits and substantial cost savings.

Is risk stratification ever the same as 'profiling'?

Physicians engage in risk stratification as a normative part of their professional duties. Risk stratification has the potential to be beneficial in many ways, and implicit recognition of this potential benefit underlies its acceptance as a cornerstone of the medical profession. However, risk stratification also has the potential to be harmful. We argue that 'profiling' is a term that corresponds to risk stratification strategies in which there is concern that ethical harms exceed likely or proven benefits. In the case of risk stratification for health goals, this would occur most frequently if benefits were obtained by threats to justice, autonomy or privacy. We discuss implications of the potential overlap between risk stratification and profiling for researchers and for clinicians, and we consider whether there are salient characteristics that make a particular risk stratification algorithm more or less likely to overlap with profiling, such as whether the risk stratification algorithm is based on voluntary versus non-voluntary characteristics, based on causal versus non-causal characteristics, or based on signifiers of historical disadvantage. We also discuss the ethical challenges created when a risk stratification scheme helps all subgroups but some more than others, or when risk stratification harms some subgroups but benefits the aggregate group.

Identifying meta-research with researchers as study subjects: Protocol for a scoping review.

BACKGROUND: Meta-research in which researchers are the study subjects can illuminate how to better support researchers and enhance the development of research capacity. Comprehensively compiling the literature in this area can help define best practices for research capacity development and reveal gaps in the literature. However, there are challenges to assessing and synthesizing the breadth of the meta-research literature produced. METHODS: In this article, we discuss the current barriers to conducting literature reviews on meta-research and strategies to address these barriers. We then outline proposed methods for conducting a scoping review on meta-research with researchers as study subjects. DISCUSSION: Due to its interdisciplinary nature, broad scope, and difficult to pinpoint terminology, little is known about the state of meta-research with researchers as the study subjects. For this reason, there is a need for a scoping review that will identify research performed in which researchers were the study subjects.

Mixed methods assessment of the influence of demographics on medical advice of ChatGPT.

OBJECTIVES: To evaluate demographic biases in diagnostic accuracy and health advice between generative artificial intelligence (AI) (ChatGPT GPT-4) and traditional symptom checkers like WebMD. MATERIALS AND METHODS: Combination symptom and demographic vignettes were developed for 27 most common symptom complaints. Standardized prompts, written from a patient perspective, with varying demographic permutations of age, sex, and race/ethnicity were entered into ChatGPT (GPT-4) between July and August 2023. In total, 3 runs of 540 ChatGPT prompts were compared to the corresponding WebMD Symptom Checker output using a mixed-methods approach. In addition to diagnostic correctness, the associated text generated by ChatGPT was analyzed for readability (using Flesch-Kincaid Grade Level) and qualitative aspects like disclaimers and demographic tailoring. RESULTS: ChatGPT matched WebMD in 91% of diagnoses, with a 24% top diagnosis match rate. Diagnostic accuracy was not significantly different across demographic groups, including age, race/ethnicity, and sex. ChatGPT's urgent care recommendations and demographic tailoring were presented significantly more to 75-year-olds versus 25-year-olds (P < .01) but were not statistically different among race/ethnicity and sex groups. The GPT text was suitable for college students, with no significant demographic variability. DISCUSSION: The use of non-health-tailored generative AI, like ChatGPT, for simple symptom-checking functions provides comparable diagnostic accuracy to commercially available symptom checkers and does not demonstrate significant demographic bias in this setting. The text accompanying differential diagnoses, however, suggests demographic tailoring that could potentially introduce bias. CONCLUSION: These results highlight the need for continued rigorous evaluation of AI-driven medical platforms, focusing on demographic biases to ensure equitable care.

Longitudinal association between e-cigarette use and respiratory symptoms among US adults: Findings from the Population Assessment of Tobacco and Health Study Waves 4-5.

BACKGROUND: We assessed longitudinal effects of e-cigarette use on respiratory symptoms in a nationally representative sample of US adults by combustible tobacco smoking status. METHODS: We analyzed Waves 4-5 public-use data from the Population Assessment of Tobacco and Health Study. Study sample included adult respondents who reported no diagnosis of respiratory diseases at Wave 4, and completed Waves 4-5 surveys with no missing data on analytic variables (N = 15,291). Outcome was a validated index of functionally important respiratory symptoms based on 7 wheezing/cough questions (range 0-9). An index score of ≥2 was defined as having important respiratory symptoms. Weighted lagged logistic regression models were performed to examine the association between e-cigarette use status at Wave 4 (former/current vs. never use) and important respiratory symptoms at Wave 5 by combustible tobacco smoking status (i.e., never/former/current smokers), adjusting for Wave 4 respiratory symptom index, sociodemographic characteristics, secondhand smoke exposure, body mass index, and chronic disease. RESULTS: Among current combustible tobacco smokers, e-cigarette use was associated with increased odds of reporting important respiratory symptoms (former e-cigarette use: adjusted odds ratio [AOR] = 1.39, 95% confidence interval [CI]: 1.07-1.81; current e-cigarette use: AOR = 1.55, 95% CI: 1.17-2.06). Among former combustible tobacco smokers, former e-cigarette use (AOR = 1.51, 95% CI: 1.06-2.15)-but not current e-cigarette use (AOR = 1.59, 95% CI: 0.91-2.78)-was associated with increased odds of important respiratory symptoms. Among never combustible tobacco smokers, no significant association was detected between e-cigarette use and important respiratory symptoms (former e-cigarette use: AOR = 1.62, 95% CI: 0.76-3.46; current e-cigarette use: AOR = 0.82, 95% CI: 0.27-2.56). CONCLUSIONS: The association between e-cigarette use and respiratory symptoms varied by combustible tobacco smoking status. Current combustible tobacco smokers who use e-cigarettes have an elevated risk of respiratory impairments.

Trial Participants' Perceptions of the Impact of Ecological Momentary Assessment on Smoking Behaviors: Qualitative Analysis.

Background: Ecological momentary assessment (EMA) is an increasingly used tool for data collection in behavioral research, including smoking cessation studies. As previous addiction research suggests, EMA has the potential to elicit cue reactivity by triggering craving and increasing behavioral awareness. However, there has been limited evaluation of its potential influence on behavior. Objective: By examining the perspectives of research participants enrolled in a tobacco treatment intervention trial, this qualitative analysis aims to understand the potential impact that EMA use may have had on smoking behaviors that may not have otherwise been captured through other study measures. Methods: We performed a qualitative analysis of in-depth interviews with participants enrolled in a pilot randomized controlled trial of a tobacco treatment intervention that used SMS text messaging to collect EMA data on smoking behaviors. In the pilot randomized controlled trial, combustible cigarette and e-cigarette use and smoking-related cravings were measured as part of an EMA protocol, in which SMS text messaging served as a smoking diary. SMS text messaging was intended for data collection only and not designed to serve as part of the intervention. After a baseline assessment, participants were asked to record daily nicotine use for 12 weeks by responding to text message prompts that they received 4 times per day. Participants were prompted to share their experiences with the EMA text messaging component of the trial but were not directly asked about the influence of EMA on their behaviors. Transcripts were coded according to the principles of the framework for applied research. The codes were then examined, summarized, and grouped into themes based on the principles of grounded theory. Results: Interviews were analyzed for 26 participants. The themes developed from the analysis suggested the potential for EMA, in the form of an SMS text messaging smoking diary, to influence participants' smoking behaviors. The perceived impacts of EMA text messaging on smoking behaviors were polarized; some participants emphasized the positive impacts of text messages on their efforts to reduce smoking, while others stressed the ways that text messaging negatively impacted their smoking reduction efforts. These contrasting experiences were captured by themes reflecting the positive impacts on smoking behaviors, including increased awareness of smoking behaviors and a sense of accountability, and the negative impacts on emotions and smoking behaviors, including provoking a sense of guilt and triggering smoking behaviors. Conclusions: The collection of EMA smoking behavior data via SMS text messaging may influence the behaviors and perceptions of participants in tobacco treatment interventions. More research is needed to determine the magnitude of impact and mechanisms, to account for the potential effects of EMA. A broader discussion of the unintended effects introduced by EMA use is warranted among the research community.

Large Language Model-Based Responses to Patients' In-Basket Messages.

Importance: Virtual patient-physician communications have increased since 2020 and negatively impacted primary care physician (PCP) well-being. Generative artificial intelligence (GenAI) drafts of patient messages could potentially reduce health care professional (HCP) workload and improve communication quality, but only if the drafts are considered useful. Objectives: To assess PCPs' perceptions of GenAI drafts and to examine linguistic characteristics associated with equity and perceived empathy. Design, Setting, and Participants: This cross-sectional quality improvement study tested the hypothesis that PCPs' ratings of GenAI drafts (created using the electronic health record [EHR] standard prompts) would be equivalent to HCP-generated responses on 3 dimensions. The study was conducted at NYU Langone Health using private patient-HCP communications at 3 internal medicine practices piloting GenAI. Exposures: Randomly assigned patient messages coupled with either an HCP message or the draft GenAI response. Main Outcomes and Measures: PCPs rated responses' information content quality (eg, relevance), using a Likert scale, communication quality (eg, verbosity), using a Likert scale, and whether they would use the draft or start anew (usable vs unusable). Branching logic further probed for empathy, personalization, and professionalism of responses. Computational linguistics methods assessed content differences in HCP vs GenAI responses, focusing on equity and empathy. Results: A total of 16 PCPs (8 [50.0%] female) reviewed 344 messages (175 GenAI drafted; 169 HCP drafted). Both GenAI and HCP responses were rated favorably. GenAI responses were rated higher for communication style than HCP responses (mean [SD], 3.70 [1.15] vs 3.38 [1.20]; P = .01, U = 12 568.5) but were similar to HCPs on information content (mean [SD], 3.53 [1.26] vs 3.41 [1.27]; P = .37; U = 13 981.0) and usable draft proportion (mean [SD], 0.69 [0.48] vs 0.65 [0.47], P = .49, t = -0.6842). Usable GenAI responses were considered more empathetic than usable HCP responses (32 of 86 [37.2%] vs 13 of 79 [16.5%]; difference, 125.5%), possibly attributable to more subjective (mean [SD], 0.54 [0.16] vs 0.31 [0.23]; P < .001; difference, 74.2%) and positive (mean [SD] polarity, 0.21 [0.14] vs 0.13 [0.25]; P = .02; difference, 61.5%) language; they were also numerically longer (mean [SD] word count, 90.5 [32.0] vs 65.4 [62.6]; difference, 38.4%), but the difference was not statistically significant (P = .07) and more linguistically complex (mean [SD] score, 125.2 [47.8] vs 95.4 [58.8]; P = .002; difference, 31.2%). Conclusions: In this cross-sectional study of PCP perceptions of an EHR-integrated GenAI chatbot, GenAI was found to communicate information better and with more empathy than HCPs, highlighting its potential to enhance patient-HCP communication. However, GenAI drafts were less readable than HCPs', a significant concern for patients with low health or English literacy.