Faculty Bibliography

The COVID-19 pandemic increased maternal depression and anxiety, imperiling both mothers' own wellbeing and that of their children. To date, however, little is known about the extent to which these increases are attributable to economic hardships commonly experienced during the pandemic: income loss, job loss, and loss of health insurance. Few studies have examined the individual impacts of these hardships, and none have lasted beyond the first year of the pandemic. This study harmonizes data from six evaluations of pediatric-based parenting programs for women with young children and low incomes across three U.S. cities (N = 1,254). Low-income mothers are of special interest because their families have been disproportionately affected by economic shocks due to COVID-19, and mothers of young children have been more distressed than other mothers by COVID-19. The studies' combined window of observation lasted from the onset of the pandemic to over three years later. Results indicate that income loss, job loss, and health insurance loss were all significantly associated with depression and anxiety. When each hardship was assessed net of the others, lost income was associated with more than a two-fold increase in the odds of anxiety, and a lost job and lost health insurance were associated with 50% and 90% greater odds of depression, respectively. Associations between hardships and maternal mental health did not diminish over time during the window of observation. These associations are likely to have been even greater in the absence of generous social policies enacted during the pandemic.

BACKGROUND:Prediction models based on machine learning (ML) methods are being increasingly developed and adopted in health care. However, these models may be prone to bias and considered unfair if they demonstrate variable performance in population subgroups. An unfair model is of particular concern in bladder cancer, where disparities have been identified in sex and racial subgroups. OBJECTIVE:This study aims (1) to develop a ML model to predict survival after radical cystectomy for bladder cancer and evaluate for potential model bias in sex and racial subgroups; and (2) to compare algorithm unfairness mitigation techniques to improve model fairness. METHODS:-score. The primary metric for model fairness was the equalized odds ratio (eOR). We compared 3 algorithm unfairness mitigation techniques to improve eOR. RESULTS:-scores of 0.86, 0.904, and 0.824 in the full, Black male, and Asian female test sets, respectively. CONCLUSIONS:The ML model predicting survival after radical cystectomy exhibited bias across sex and racial subgroups. By using algorithm unfairness mitigation techniques, we improved algorithmic fairness as measured by the eOR. Our study highlights the role of not only evaluating for model bias but also actively mitigating such disparities to ensure equitable health care delivery. We also deployed the first web-based fair ML model for predicting survival after radical cystectomy.

BACKGROUND:Measurement-based care (MBC), routinely measuring and reviewing treatment progress with a standardized tool, can inform clinical decision making and improve patient outcomes. Despite potential benefits, implementation of MBC in SUD treatment settings has been limited and little is known about its implementation in SUD settings. The goal of this convergent parallel mixed methods study was to understand staff experiences during early implementation of MBC in SUD treatment clinics. METHODS:The Treatment Progress Assessment-8 (TPA8) is an 8-item measure that supports MBC with an electronic system (eTPA8) allowing client completion on electronic devices and providing staff reports. The study introduced the eTPA8 into 13 clinics using external practice facilitation and implementation teams. Quantitative data examining implementation included eTPA8 system data (1672 administrations) and staff surveys (n = 70) using feasibility, acceptability, and appropriateness measures. Semi-structured interviews (n = 34) were conducted with clinic staff. To analyze data, we classified clinics into adopters, non-adopters, and sustainers using eTPA8 system data. One-way ANOVA compared these classifications on the three implementation outcome measures. Rapid qualitative analysis was used for the interviews. RESULTS:There were significant differences between staff in sustainer (M = 3.90) and non-adopter (M = 3.21) clinics on the feasibility measure (F(2, 68) = [4.28], p = 0.018). SUD program staff found the eTPA8 to be user-friendly, appropriate, and acceptable. There was some variation in perceived feasibility of regular use of the eTPA8, especially given competing demands and time constraints. Staff found the eTPA8 useful to support clinical interactions but varied in embracing new technology and the overall MBC concept. The inner and outer contexts influenced implementation and required attention by clinic champions and implementation teams. External practice facilitators were key to addressing barriers in an ongoing and flexible manner. CONCLUSIONS:Implementing MBC using the eTPA8 showed promise. Staff felt the TPA8 was generally clinically useful, appropriate, and acceptable; yet feasibility was variable. Adoption of MBC faced barriers (e.g., competing demands). Implementation required relatively intensive implementation supports that were dynamic, proactive, and responsive. Findings have implications for guiding development and refinement of responsive, theory-driven implementation strategies to support MBC in SUD treatment settings, with a particular focus on addressing feasibility.

BACKGROUND:Evidence suggests historical redlining shaped the built environment and health outcomes in urban areas. Only a handful of studies have examined redlining's association with air pollution and adverse birth outcomes in New York City (NYC). Additionally, no NYC-specific studies have examined the impact of redlining on birth weight. METHODS:) exposure during pregnancy using multivariable regression models. Additionally, we examined how maternal residence in a historically redlined neighbourhood during pregnancy influenced birth weight z-score, preterm birth and low birth weight. RESULTS:in our models assessing the relationship between redlining grade and birth outcome, our results did not change. DISCUSSION/CONCLUSIONS:levels today.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Race and ethnicity are proxy measures of sociocultural factors that influence cognitive test performance. Our objective was to compare different regression-based cognitive normative models adjusting for demographics and different combinations of easily accessible/commonly used social determinants of health (SDoH) factors, which may help describe cognitive performance variability historically captured by ethnoracial differences. METHODS:We performed cross-sectional analyses on data from Black and White participants without mild cognitive impairment/dementia in the Atherosclerosis Risk in Communities Study who attended visit 5 in 2011-2013. Participants underwent a battery of 11 cognitive tests (3 domains: memory, executive function, language). We fit 6 separate normative models for each cognitive test, all including age and education, with different combinations of race, the Wide Range of Achievement Test (education quality proxy), and area deprivation index (neighborhood deprivation) associated with current residence. We compared model fits and calculated concordances/discordances between models using z-scores derived from each normative model and a z-score <-1.5 threshold for impairment. RESULTS:Participants (n = 2,392) had a mean age of 74.4 years, 60.4% were female, and 17.1% were of self-reported Black race. The "Full" model with race alongside demographic and SDoH measures consistently outperformed other nested submodels (likelihood ratios ≥ 100) for all domains/tests except Delayed Word Recall. Models with education quality alone ("WRAT") generally outperformed models with neighborhood deprivation ("ADI") or race ("Race") alone for memory and language tests while "Race" models performed better for executive function tests. Adding neighborhood deprivation to education quality ("WRAT + ADI") did not improve models vs using "WRAT" alone. Across all domains/tests, the concordance compared with the "Full" model was lower for "Education" and "ADI" models than for other nested models. Although numbers were small, there was greater discordance among Black (range = 8.2%-23.2%) compared with White (range = 2.2%-3.4%) participants, particularly for Boston Naming Test and executive function tests. DISCUSSION/CONCLUSIONS:Education quality outperformed neighborhood disadvantage as an additional/alternative SDoH measure in normative models and may be useful to collect in cognitive aging studies. While performance varied across cognitive domains and tests, routinely reported SDoH variables (education level, education quality, late-life neighborhood deprivation) did not fully account for observed ethnoracial variability; future work should evaluate SDoH across the lifespan in more ethnoracially diverse populations.

Early adversity increases risk for child mental health difficulties. Stressors in the home environment (e.g., parental mental illness, household socioeconomic challenges) may be particularly impactful. Attending out-of-home childcare may buffer or magnify negative effects of such exposures. Using a longitudinal observational design, we leveraged data from the NIH Environmental influences on Child Health Outcomes Program to test whether number of hours in childcare, defined as 1) any type of nonparental care and 2) center-based care specifically, was associated with child mental health, including via buffering or magnifying associations between early exposure to psychosocial and socioeconomic risks (age 0-3 years) and later internalizing and externalizing symptoms (age 3-5.5 years), in a diverse sample of N = 2,024 parent-child dyads. In linear regression models, childcare participation was not associated with mental health outcomes, nor did we observe an impact of childcare attendance on associations between risk exposures and symptoms. Psychosocial and socioeconomic risks had interactive effects on internalizing and externalizing symptoms. Overall, the findings did not indicate that childcare attendance positively or negatively influenced child mental health and suggested that psychosocial and socioeconomic adversity may need to be considered as separate exposures to understand child mental health risk in early life.

PURPOSE/OBJECTIVE:The aim of this study was to identify successful recruitment strategies and obstacles reported by principal investigators (PIs) of the Zoster Eye Disease Study (ZEDS). METHODS:A web-based survey was created by a subset of ZEDS PIs and distributed to ZEDS PIs after study enrollment was closed. The survey queried investigators about recruitment strategies and obstacles, use of prophylactic oral antiviral medication, electronic medical records, telemedicine, COVID-19 effect, turnover of research staff, and recruitment outreach to minority and underserved populations. The survey allowed objective measures and free-text options. Analysis from centers with higher enrollment was compared with centers with lower enrollment to identify successful strategies and common obstacles. RESULTS:The most frequently cited helpful strategies were participation from ophthalmologists within the PI's institution (33/63, 52%), ophthalmology resident referrals (23/63, 37%), and chart review (23/63, 37%). Travel to participating clinical center (42/63, 67%) and ongoing prophylactic use of oral systemic antiviral medication (39/63, 62%) were common obstacles. Research coordinator turnover was identified as a contributor to reduced recruitment success by 49% (31/63) of PIs and made recruitment much harder for 22% (14/63). A small number of investigators used telemedicine (18/63, 29%) and few made efforts to recruit from minority and underserved populations (10/63, 16%). CONCLUSIONS:Our survey highlights the importance of internal ophthalmologist referral, chart review, and research coordinator commitment for successful clinical trial recruitment. We discuss the impact of prophylactic use of oral antiviral medication on recruitment. Future randomized clinical trials should mobilize the helpful recruitment strategies and improve outreach to underserved populations.

INTRODUCTION/BACKGROUND:The relationship between food insecurity and access to healthcare in low-resource settings remains unclear. Some studies find that food insecurity is a barrier to accessing care, while others report that food insecurity is associated with a greater need for care, leading to more care utilisation. We use data from the Harambee study in western Kenya to assess the association between food insecurity and difficulty accessing care among people living with HIV (PLWH) with or without comorbid non-communicable diseases (NCDs). METHODS:The Harambee study is a cluster randomised trial that tested the effectiveness of delivering integrated HIV and NCD care for PLWH. In this cross-sectional analysis, we examined baseline data from Harambee participants to investigate the relationship between household food insecurity and difficulty accessing care, using multivariable logistic regression models, controlling for sociodemographic factors and care satisfaction. We tested for effect measure modification by gender and household wealth and stratified analyses by NCD status. RESULTS:Among 1039 participants, 11.1% reported difficulty accessing care, and 18.9% and 51.9% of participants had moderate and severe food insecurity, respectively. Among those with difficulty accessing care, 73.9% cited transportation issues as the major barrier. Difficulty accessing care was greater with higher levels of food insecurity: among participants with low, moderate and severe food insecurity, 5.9%, 9.7% and 14.4% reported difficulty accessing care, respectively. After adjusting for confounders, severe food insecurity was independently associated with difficulty accessing care (adjusted OR=2.5, 95% CI 1.4 to 4.4). There was no statistical evidence for effect measure modification by gender or wealth. CONCLUSIONS:We found that greater food insecurity was associated with greater difficulty accessing care among PLWH with or without NCDs in rural western Kenya. These findings suggest that addressing social determinants of health may be necessary when implementing integrated HIV and NCD care programmes.

Electronic health record proficiency is critical for health professionals to deliver and document patient care. There is scarce research on this topic within undergraduate nursing student populations. The purpose of this study is to describe the psychometric evaluation of the Digital Literacy, Usability, and Acceptability of Technology Instrument for Healthcare. A cross-sectional pilot study for psychometric evaluation of the instrument was conducted using data collected through an emailed survey. Exploratory factor analysis, inter-item and adjusted item-total correlations, and Cronbach's α calculated subscale reliability. A total of 297 nursing students completed the survey. A seven-factor structure best fit the data: technology use-engagement, technology use-confidence, technology use-history, electronic health record-ease of use, electronic health record-comparability, and electronic health record-burden. Cronbach's α indicated good to very good internal consistency (α = .68 to .89). The instrument effectively measured digital literacy, acceptance, and usability of an electronic health record and may be implemented with good to very good reliability across varied healthcare simulation and training experiences.