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.

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.

Ambulatory antibiotic prescription rates for acute respiratory infection rebound two years after the start of the COVID-19 pandemic.

BACKGROUND: During the COVID-19 pandemic, acute respiratory infection (ARI) antibiotic prescribing in ambulatory care markedly decreased. It is unclear if antibiotic prescription rates will remain lowered. METHODS: We used trend analyses of antibiotics prescribed during and after the first wave of COVID-19 to determine whether ARI antibiotic prescribing rates in ambulatory care have remained suppressed compared to pre-COVID-19 levels. Retrospective data was used from patients with ARI or UTI diagnosis code(s) for their encounter from 298 primary care and 66 urgent care practices within four academic health systems in New York, Wisconsin, and Utah between January 2017 and June 2022. The primary measures included antibiotic prescriptions per 100 non-COVID ARI encounters, encounter volume, prescribing trends, and change from expected trend. RESULTS: At baseline, during and after the first wave, the overall ARI antibiotic prescribing rates were 54.7, 38.5, and 54.7 prescriptions per 100 encounters, respectively. ARI antibiotic prescription rates saw a statistically significant decline after COVID-19 onset (step change -15.2, 95% CI: -19.6 to -4.8). During the first wave, encounter volume decreased 29.4% and, after the first wave, remained decreased by 188%. After the first wave, ARI antibiotic prescription rates were no longer significantly suppressed from baseline (step change 0.01, 95% CI: -6.3 to 6.2). There was no significant difference between UTI antibiotic prescription rates at baseline versus the end of the observation period. CONCLUSIONS: The decline in ARI antibiotic prescribing observed after the onset of COVID-19 was temporary, not mirrored in UTI antibiotic prescribing, and does not represent a long-term change in clinician prescribing behaviors. During a period of heightened awareness of a viral cause of ARI, a substantial and clinically meaningful decrease in clinician antibiotic prescribing was observed. Future efforts in antibiotic stewardship may benefit from continued study of factors leading to this reduction and rebound in prescribing rates.

Limited Evidence of Shared Decision Making for Prostate Cancer Screening in Audio-Recorded Primary Care Visits Among Black Men and their Healthcare Providers.

Prostate-specific antigen (PSA)-based prostate cancer screening is a preference-sensitive decision for which experts recommend a shared decision making (SDM) approach. This study aimed to examine PSA screening SDM in primary care. Methods included qualitative analysis of audio-recorded patient-provider interactions supplemented by quantitative description. Participants included 5 clinic providers and 13 patients who were: (1) 40-69 years old, (2) Black, (3) male, and (4) attending clinic for routine primary care. Main measures were SDM element themes and "observing patient involvement in decision making" (OPTION) scoring. Some discussions addressed advantages, disadvantages, and/or scientific uncertainty of screening, however, few patients received all SDM elements. Nearly all providers recommended screening, however, only 3 patients were directly asked about screening preferences. Few patients were asked about prostate cancer knowledge (2), urological symptoms (3), or family history (6). Most providers discussed disadvantages (80%) and advantages (80%) of PSA screening. Average OPTION score was 25/100 (range 0-67) per provider. Our study found limited SDM during PSA screening consultations. The counseling that did take place utilized components of SDM but inconsistently and incompletely. We must improve SDM for PSA screening for diverse patient populations to promote health equity. This study highlights the need to improve SDM for PSA screening.

Barriers to Implementing Registered Nurse-Driven Clinical Decision Support for Antibiotic Stewardship: Retrospective Case Study.

BACKGROUND: Up to 50% of antibiotic prescriptions for upper respiratory infections (URIs) are inappropriate. Clinical decision support (CDS) systems to mitigate unnecessary antibiotic prescriptions have been implemented into electronic health records, but their use by providers has been limited. OBJECTIVE: As a delegation protocol, we adapted a validated electronic health record-integrated clinical prediction rule (iCPR) CDS-based intervention for registered nurses (RNs), consisting of triage to identify patients with low-acuity URI followed by CDS-guided RN visits. It was implemented in February 2022 as a randomized controlled stepped-wedge trial in 43 primary and urgent care practices within 4 academic health systems in New York, Wisconsin, and Utah. While issues were pragmatically addressed as they arose, a systematic assessment of the barriers to implementation is needed to better understand and address these barriers. METHODS: We performed a retrospective case study, collecting quantitative and qualitative data regarding clinical workflows and triage-template use from expert interviews, study surveys, routine check-ins with practice personnel, and chart reviews over the first year of implementation of the iCPR intervention. Guided by the updated CFIR (Consolidated Framework for Implementation Research), we characterized the initial barriers to implementing a URI iCPR intervention for RNs in ambulatory care. CFIR constructs were coded as missing, neutral, weak, or strong implementation factors. RESULTS: Barriers were identified within all implementation domains. The strongest barriers were found in the outer setting, with those factors trickling down to impact the inner setting. Local conditions driven by COVID-19 served as one of the strongest barriers, impacting attitudes among practice staff and ultimately contributing to a work infrastructure characterized by staff changes, RN shortages and turnover, and competing responsibilities. Policies and laws regarding scope of practice of RNs varied by state and institutional application of those laws, with some allowing more clinical autonomy for RNs. This necessitated different study procedures at each study site to meet practice requirements, increasing innovation complexity. Similarly, institutional policies led to varying levels of compatibility with existing triage, rooming, and documentation workflows. These workflow conflicts were compounded by limited available resources, as well as an implementation climate of optional participation, few participation incentives, and thus low relative priority compared to other clinical duties. CONCLUSIONS: Both between and within health care systems, significant variability existed in workflows for patient intake and triage. Even in a relatively straightforward clinical workflow, workflow and cultural differences appreciably impacted intervention adoption. Takeaways from this study can be applied to other RN delegation protocol implementations of new and innovative CDS tools within existing workflows to support integration and improve uptake. When implementing a system-wide clinical care intervention, considerations must be made for variability in culture and workflows at the state, health system, practice, and individual levels. TRIAL REGISTRATION: ClinicalTrials.gov NCT04255303; https://clinicaltrials.gov/ct2/show/NCT04255303.

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.

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.

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.

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.

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 .

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.

Implementation of a relapse prevention program among smokers undergoing arthroplasty: lessons learned.

BACKGROUND: Surgery is a potent motivator to help people quit smoking to reduce the risk of complications. Many patients who smoke receive tobacco cessation counseling prior to surgery and are able to quit, but do not receive the same resources after surgery and often resume smoking. METHODS: We present a case study describing the recruitment process, study components, and lessons learned from StayQuit, a comprehensive relapse prevention program designed to prevent relapse after arthroplasty. Lessons learned were examined post hoc to determine challenges related to program implementation, using existing study procedures and information collected. RESULTS: While a comprehensive postoperative relapse prevention program may be beneficial to patients, implementation of StayQuit is unlikely to be feasible under current circumstances. The primary challenges to successful implementation of StayQuit focused on themes of lack of engagement in the preoperative Orthopedic Surgery Quit Smoking Program (OSQSP) and an environment unfavorable to in-person enrollment on the day of surgery. CONCLUSIONS: Postoperative relapse prevention programs may be beneficial for patients who quit smoking prior to elective surgery. To help guide implementation, it is important to consider surgeon behavior, the collaboration of clinical and non-clinical teams, and best practices for study enrollment in surgical settings.

Using meta-research to foster diverse, equitable, and inclusive collaborative research networks.

Fostering diverse, equitable, and inclusive collaborative research networks is important for advancing the field of aging research. Despite sizeable investment in research consortia and career development programs, there has been only moderate progress toward diversifying the research workforce studying aging. Without critically examining what works and what does not, continuing to place more resources into these same strategies may not result in a substantial improvement in diversity or the creation of collaborative networks. Using meta-research to rigorously evaluate potential strategies to promote diversity and collaboration may yield important insights that can be used to improve upon current efforts. For this reason, we sought to describe meta-research and highlight how its principles can be used to achieve the aging research community's collaboration and diversity goals.

Youth E-Cigarette Use and Functionally Important Respiratory Symptoms: The Population Assessment of Tobacco and Health (PATH) Study Waves 3 and 4.

Respiratory effects of e-cigarette use among youth are not fully understood. This study investigated the longitudinal association between e-cigarette use and a validated index of functionally important respiratory symptoms among US youth. Data from Waves 3-4 of the Population Assessment of Tobacco and Health Study were analyzed. The sample included youth (aged 12-17) without asthma at baseline (Wave 3), who completed a follow-up survey (Wave 4), and were not missing data for analytic variables (n = 3899). Exposure was e-cigarette use status (never, former, or current) at baseline. The outcome was a respiratory symptom index based on responses for seven wheezing items at Wave 4. An index of ≥2 was defined as having functionally important respiratory symptoms. Lagged logistic regression models examined the association between baseline e-cigarette use and functionally important respiratory symptoms at follow-up by combustible tobacco use status (never or ever), and controlling for baseline covariates. At baseline, 13.7% of participants reported former e-cigarette use, and 4.3% reported current use. Baseline e-cigarette use did not increase the odds of having functionally important respiratory symptoms at follow-up regardless of combustible tobacco use status. Future research on larger populations of e-cigarette users with longer follow-up periods will improve our understanding of the respiratory risks associated with e-cigarette use among youth.

Behavioral Economics and Tobacco Control: Current Practices and Future Opportunities.

Despite considerable progress, smoking remains the leading preventable cause of death in the United States. To address the considerable health and economic burden of tobacco use, the development of improved tobacco control and treatment interventions is critical. By combining elements of economics and psychology, behavioral economics provides a framework for novel solutions to treat smokers who have failed to quit with traditional smoking cessation interventions. The full range of behavioral economic principles, however, have not been widely utilized in the realm of tobacco control and treatment. Given the need for improved tobacco control and treatment, the limited use of other behavioral economic principles represents a substantial missed opportunity. For this reason, we sought to describe the principles of behavioral economics as they relate to tobacco control, highlight potential gaps in the behavioral economics tobacco research literature, and provide examples of potential interventions that use each principle.