Faculty Bibliography

BACKGROUND/UNASSIGNED:Magnetic resonance imaging (MRI) and electroencephalography (EEG) are valuable tools for studying neuroanatomical and electrophysiological features of early brain development. Studies implementing neuroimaging tools in low- and middle-income countries are still rare, and there is limited data on the acceptability of such tools among rural communities. The present study explores the perceptions, feasibility, and acceptability of introducing MRI and EEG for child development research in the rural Amhara region of Ethiopia. METHODS/UNASSIGNED:= 16). A semi-structured interview included four themes: (1) Baseline imaging knowledge, (2) Perceptions of MRI and EEG, (3) Facilitators and barriers to acceptability of MRI and EEG, and (4) Recommendations to improve MRI and EEG uptake. Interviews were conducted in Amharic, the local language. All interviews were transcribed verbatim to Amharic, translated into English, and double-coded. We used thematic analysis to organize data according to predefined and emerging themes. RESULTS/UNASSIGNED:Knowledge of MRI and EEG was limited, and none of the community members had previous experiences with either technology. Broadly, participants responded positively to our introductory videos showing MRI and EEG acquisition and expressed high levels of acceptability. However, participants reported concerns about possible harms related to radiation, electrical shock, and injury from MRI/EEG procedures. Those with lesser education were identified to be less accepting of MRI/EEG. In addition, several mothers expressed that consent from their husbands was necessary for their child's participation in neurodevelopmental research. Potential logistical barriers identified included transportation challenges to the neuroimaging study sites, especially for rural-dwelling families. Creating awareness, using explanatory videos, and engaging community members and clinicians were recommended to facilitate acceptance of EEG and MRI. CONCLUSION/UNASSIGNED:In this formative study, MRI and EEG were viewed as acceptable methods for assessing child neurodevelopment in rural areas of Ethiopia. Community members' and clinicians' views were impacted largely by social, religious, educational, and logistical aspects. Concerns related to MRI radiation, electrical shock, and injuries from EEG can be addressed through awareness creation and education. Engaging community leaders and healthcare providers is key to improving acceptability.

The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots when summarizing clinical evidence and providing health advice, referred to as Chatbot Health Advice (CHA) studies. CHART was developed in several phases after performing a comprehensive systematic review to identify variation in the conduct, reporting and methodology in CHA studies. Findings from the review were used to develop a draft checklist that was revised through an international, multidisciplinary modified asynchronous Delphi consensus process of 531 stakeholders, three synchronous panel consensus meetings of 48 stakeholders, and subsequent pilot testing of the checklist. CHART includes 12 items and 39 subitems to promote transparent and comprehensive reporting of CHA studies. These include Title (subitem 1a), Abstract/Summary (subitem 1b), Background (subitems 2ab), Model Identifiers (subitem 3ab), Model Details (subitems 4abc), Prompt Engineering (subitems 5ab), Query Strategy (subitems 6abcd), Performance Evaluation (subitems 7ab), Sample Size (subitem 8), Data Analysis (subitem 9a), Results (subitems 10abc), Discussion (subitems 11abc), Disclosures (subitem 12a), Funding (subitem 12b), Ethics (subitem 12c), Protocol (subitem 12d), and Data Availability (subitem 12e). The CHART checklist and corresponding methodological diagram were designed to support key stakeholders including clinicians, researchers, editors, peer reviewers, and readers in reporting, understanding, and interpreting the findings of CHA studies.

BACKGROUND AND OBJECTIVE/OBJECTIVE:Recent studies highlight an increase in pediatric mental health disorders, amplified by COVID-19. This study examines changes in mental health-related emergency department visits among New York City public school students across the pandemic timeline. METHODS:We employed logistic regression to examine changes in the probability of a student's emergency department visit being mental health-related, and as a secondary outcome, we analyzed the difference in same-day discharge rates between mental health-related visits and other visits. For this analysis, we used the New York City Student Population Health Registry to link public school students' records to emergency department visit data. RESULTS:No significant linear trends were observed in the average monthly probability of a mental health-related visit before March 2020. From March 2020 through June 2021 there was an increase for all groups except male elementary school students. Female middle and high school students experienced the largest increase (0.031 (CI = [0.027, 0.034])) compared to pre-pandemic (0.103 (CI = [0.103, 0.104])). Post-June 2021, all groups experienced a lower probability except for female middle and high school students, who had a 0.009 (CI = [0.007, 0.011]) higher probability than during the pandemic. Compared to the pre-pandemic period and non-mental health-related visits, a 0.043 (CI = [0.029, 0.057]) lower probability of same-day discharge was observed for mental health-related visits during the pandemic period. CONCLUSIONS:The COVID-19 pandemic correlated with a significant increase in mental health-related emergency department visits and longer stays, particularly among female middle and high school students.

IMPORTANCE/UNASSIGNED:The rise in chatbot health advice (CHA) studies is accompanied by heterogeneity in reporting standards, impacting their interpretability. OBJECTIVE/UNASSIGNED:To provide reporting recommendations for studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots when summarizing clinical evidence and providing health advice. DESIGN, SETTING, AND PARTICIPANTS/UNASSIGNED:CHART was developed in several phases after performing a comprehensive systematic review to identify variation in the conduct, reporting, and methodology in CHA studies. Findings from the review were used to develop a draft checklist that was revised through an international, multidisciplinary modified asynchronous Delphi consensus process of 531 stakeholders, 3 synchronous panel consensus meetings of 48 stakeholders, and subsequent pilot testing of the checklist. RESULTS/UNASSIGNED:CHART includes 12 items and 39 subitems to promote transparent and comprehensive reporting of CHA studies. These include title (subitem 1a), abstract or summary (subitem 1b), background (subitems 2ab), model identifiers (subitem 3ab), model details (subitems 4abc), prompt engineering (subitems 5ab), query strategy (subitems 6abcd), performance evaluation (subitems 7ab), sample size (subitem 8), data analysis (subitem 9a), results (subitems 10abc), discussion (subitems 11abc), disclosures (subitem 12a), funding (subitem 12b), ethics (subitem 12c), protocol (subitem 12d), and data availability (subitem 12e). CONCLUSIONS AND RELEVANCE/UNASSIGNED:The CHART checklist and corresponding methodological diagram were designed to support key stakeholders including clinicians, researchers, editors, peer reviewers, and readers in reporting, understanding, and interpreting the findings of CHA studies.

BACKGROUND:The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots when summarizing clinical evidence and providing health advice, referred to as Chatbot Health Advice (CHA) studies. METHODS:CHART was developed in several phases after performing a comprehensive systematic review to identify variation in the conduct, reporting, and methodology in CHA studies. Findings from the review were used to develop a draft checklist that was revised through an international, multidisciplinary modified asynchronous Delphi consensus process of 531 stakeholders, three synchronous panel consensus meetings of 48 stakeholders, and subsequent pilot testing of the checklist. RESULTS:CHART includes 12 items and 39 subitems to promote transparent and comprehensive reporting of CHA studies. These include Title (subitem 1a), Abstract/Summary (subitem 1b), Background (subitems 2ab), Model Identifiers (subitems 3ab), Model Details (subitems 4abc), Prompt Engineering (subitems 5ab), Query Strategy (subitems 6abcd), Performance Evaluation (subitems 7ab), Sample Size (subitem 8), Data Analysis (subitem 9a), Results (subitems 10abc), Discussion (subitems 11abc), Disclosures (subitem 12a), Funding (subitem 12b), Ethics (subitem 12c), Protocol (subitem 12d), and Data Availability (subitem 12e). CONCLUSION/CONCLUSIONS:The CHART checklist and corresponding methodological diagram were designed to support key stakeholders including clinicians, researchers, editors, peer reviewers, and readers in reporting, understanding, and interpreting the findings of CHA studies.

BACKGROUND/UNASSIGNED:Social determinants of health (SDoH) contribute to disparities in SARS-CoV-2 infection, but their associations with long COVID are unknown. OBJECTIVE/UNASSIGNED:To determine associations between SDoH at the time of SARS-CoV-2 infection and risk for long COVID. DESIGN/UNASSIGNED:Prospective observational cohort study. SETTING/UNASSIGNED:33 states plus Washington, DC, and Puerto Rico. PARTICIPANTS/UNASSIGNED:Adults (aged ≥18 years) enrolled in RECOVER-Adult (Researching COVID to Enhance Recovery) between October 2021 and November 2023 who were within 30 days of SARS-CoV-2 infection; completed baseline SDoH, comorbidity, and pregnancy questionnaires; and were followed prospectively. MEASUREMENTS/UNASSIGNED:Social risk factors from SDoH baseline questionnaires, ZIP code poverty and household crowding measures, and a weighted score of 11 or higher on the Long COVID Research Index 6 months after infection. RESULTS/UNASSIGNED:Among 3787 participants, 418 (11%) developed long COVID. After adjustment for demographic characteristics, pregnancy, disability, comorbidities, SARS-CoV-2 severity, and vaccinations, financial hardship (adjusted marginal risk ratio [ARR], 2.36 [95% CI, 1.97 to 2.91]), food insecurity (ARR, 2.36 [CI, 1.83 to 2.98]), less than a college education (ARR, 1.60 [CI, 1.30 to 1.97]), experiences of medical discrimination (ARR, 2.37 [CI, 1.94 to 2.83]), skipped medical care due to cost (ARR, 2.87 [CI, 2.22 to 3.70]), and lack of social support (ARR, 1.79 [CI, 1.50 to 2.17]) were associated with increased risk for long COVID. Living in ZIP codes with the highest (vs. lowest) household crowding was also associated with greater risk (ARR, 1.36 [CI, 1.05 to 1.71]). LIMITATION/UNASSIGNED:Selection bias may influence observed associations and generalizability. CONCLUSION/UNASSIGNED:Participants with social risk factors at the time of SARS-CoV-2 infection had greater risk for subsequent long COVID than those without. Future studies should determine whether social risk factor interventions mitigate long-term effects of SARS-CoV-2 infection. PRIMARY FUNDING SOURCE/UNASSIGNED:National Institutes of Health.

OBJECTIVES/OBJECTIVE:Rural residents face unique challenges that contribute to poor diet quality and health. The objective of this study was to assess diet quality using the Alternative Healthy Eating Index (aHEI) among residents of a rural New York county with poor health outcomes, and identify geographic and individual-level factors associated with lower diet quality. DESIGN/METHODS:We performed a cross-sectional study using survey data and multivariable linear regression analyses, supplemented by geographic distribution assessment of aHEI scores. SETTING/METHODS:Sullivan County, New York, a rural county with poor health outcomes. PARTICIPANTS/METHODS:Households in Sullivan County who responded to a dietary and sociodemographic health survey in 2021-2022. OUTCOME MEASURES/METHODS:The primary outcome was the aHEI score and its dietary subscores. Secondary measures included sociodemographic characteristics, receipt of income assistance, financial hardship, food and housing insecurity, primary food store type, distance to food store and frequency of canned or plastic-wrapped food consumption. RESULTS:The overall survey response rate was 42.5%. The mean aHEI score was 56.5 (SD: 11.9), normally distributed across respondents. Lower aHEI scores were associated with not completing high school (10.0 points lower vs college graduates, p<0.01), reporting a disability (3.5 points lower, p<0.01), experiencing food insecurity (3.0 points lower, p<0.01) and frequent consumption of canned foods (6.2 points lower compared with those who never consumed canned foods, p<0.01). Geographic analysis revealed clustering of predictors but no substantial geographic clustering of aHEI scores. CONCLUSIONS:Poor diet quality in rural areas is associated with education level, disability, food insecurity and canned food consumption. These findings highlight potentially modifiable risk factors and support the need for targeted interventions to improve diet quality and reduce health disparities in rural populations.

BACKGROUND AND OBJECTIVE/OBJECTIVE:The health care sector is a significant contributor to greenhouse gas (GHG) emissions, and assessments of the environmental impacts of health services are essential. We aimed to evaluate the environmental impact of a highly common but controversial urology-specific blood test: the prostate-specific antigen (PSA) test. METHODS:e). The secondary outcome was the health impact attributed to the environmental harm of the test. KEY FINDINGS AND LIMITATIONS/UNASSIGNED:e, equivalent to driving 14.5 million miles, with a resulting human health impact of 6.6 disability-adjusted life years annually. This study focused on the PSA test itself, and not on emissions from staff, patient, or sample transportation; building infrastructure; or cleaning. CONCLUSIONS AND CLINICAL IMPLICATIONS/CONCLUSIONS:Although the carbon footprint of a single PSA test is small, the cumulative impact of the estimated total of 30 million PSA tests performed annually in the USA is substantial, especially when considering that a notable proportion of these tests may be performed on men who are unlikely to benefit.