Faculty Bibliography

PURPOSE/OBJECTIVE: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/CONCLUSIONS: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.

BACKGROUND/UNASSIGNED: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/UNASSIGNED: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/UNASSIGNED: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/UNASSIGNED: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/UNASSIGNED: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.

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.

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/CONCLUSIONS: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.

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.

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 .

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.

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.

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.