Longitudinal Changes in Stress and Isolation Among Multi‐Ethnic Breast Cancer Survivors Throughout COVID‐19

Stress and Health · 2025-06-01 · 2 citations

As COVID-19 transitions to a more manageable phase, it remains unclear whether its impact on mental health has similarly eased among cancer survivors. This longitudinal study tracked how the levels of stress and isolation experienced by breast cancer survivors (BCS) of different racial/ethnic groups have changed as the pandemic evolved. BCS enroled in the Chicago Multiethnic Epidemiologic Breast Cancer Cohort were surveyed between July and September of 2020, 2021, and 2022. An 11-item isolation/stress score was repeatedly measured in each survey. Mixed-effects linear regression models were used to analyse changes in the isolation/stress scores over time across different racial/ethnic groups and to identify the socioeconomic factors associated with the racial disparities observed. In total, 1899 BCS responded (response rate: 62.8%), of whom 69% were White and 24% Black. The median time from diagnosis to first survey was 5.1 years (IQR: 2.3-9.2). The isolation/stress score decreased continuously for White BCS (P-trend < 0.001), but only began declining for Black BCS in the last wave of survey. Black BCS had significantly higher isolation/stress scores in 2021 and 2022 compared to Whites (both p < 0.01). The racial differences became insignificant after adjusting for certain socioeconomic factors. Notably, BCS who were single, on Medicaid, without a high school degree, or with annual household income less than $35,000 had significantly higher isolation/stress scores (all p < 0.05). The findings remained consistent in sensitivity analysis using inverse probability weighting to account for non-response. Our findings suggested that the levels of stress and isolation of BCS did not improve equally across different racial/ethnic groups as the pandemic subsided. This may be associated with disparities in socioeconomic factors like insurance coverage, education level, income level and family composition. Understanding these barriers and challenges is crucial for developing targeted interventions and support systems for vulnerable populations as we recover from the pandemic and prepare for future health challenges.

Assessing Change in Medical Management of Early Pregnancy Loss before and after Implementation of a Learning Collaborative for Initiation of Mifepristone Use

Maternal and Child Health Journal · 2025-07-21 · 1 citations

Demonstration of Interoperability Between MIDRC and N3C: A COVID-19 Severity Prediction Use Case

Journal of Imaging Informatics in Medicine · 2025-08-14

Interoperability between data sources, one of the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management, can enable multi-modality research. The purpose of our study was to investigate the potential for interoperability between an imaging resource, the Medical Imaging and Data Resource Center (MIDRC), and a clinical record resource, the National COVID Cohort Collaborative (N3C). The use case was the prediction of COVID-19 severity, defined as evidence for invasive ventilatory support, extracorporeal membrane oxygenation, death, or discharge to hospice in the N3C clinical record. Patient-level matching between MIDRC and N3C was identified using Privacy Preserving Record Linking via an honest broker. We identified positive COVID-19 tests and chest radiograph procedures in N3C and used the interval between them to identify images with matching intervals in MIDRC. Of the 236 patients (306 unique images) meeting initial inclusion criteria in MIDRC, 117 patients (and 139 unique images) remained after date interval matching between repositories and exclusion of patients with multiple potential matches. The Charlson Comorbidity Index (CCI) and the minimum mean arterial pressure (MAP) on the day of the chest radiograph were used as clinical indicators. The AUC in the task of predicting severe COVID-19 was evaluated using the computer-extracted imaging index alone (MIDRC), clinical indicators alone (N3C), and both together. Our model combining imaging and clinical indicators (CCI over 2 and MAP below 70) to predict severe COVID had an AUC of 0.73 (95% CI 0.62-0.84), and the models including imaging or clinical indicators alone were 0.67 (95% CI 0.56-0.79) and 0.69 (95% CI 0.59-0.80), respectively. This study highlights the potential for cross-platform data sharing to facilitate future multi-modality research and broader collaborative studies.

Sleep timing and duration for working adults in the United States before and since the beginning of the COVID-19 pandemic

SLEEP Advances · 2025-01-01

Abstract Study Objectives Diverse studies have reported longer sleep durations and later circadian timing during the initial COVID-19 lockdown period. Little is known about whether effects persisted after 2020. This analysis addresses three questions: (1) How did sleep timing and duration change from 2017 to 2023? (2) Did working from home explain trends? (3) Did effects differ by education, income, or race/ethnicity groups? Methods The American Time Use Survey is a nationally representative survey conducted by the US Bureau of Labor Statistics that collects 24-hour time diaries. These data are used to identify respondents who worked on the sampled day, their work location (home or not), and three sleep variables: wake-up time, bedtime, and 24-hour sleep total. Ordinary least squares regression is used to answer the study questions, comparing the COVID time period (May 2020 to December 2023) to PRECOVID (January 2017 to March 2020). Results Sleep duration was longer in the COVID time period compared to PRECOVID, by 0.23 hours (95% confidence interval = 0.17, 0.29), with earlier average bedtimes and later average waking times. There were no significant secular trends in sleep outcomes within the COVID time period, suggesting that these changes have continued through 2023. Controlling for working from home modestly attenuated, but did not eliminate, the COVID effects. Effects were generally similar across sociodemographic groups. Conclusions COVID-related changes in sleep for working adults in the United States, specifically later circadian timing and increased duration, seem to be sustained through 2023. Statement of Significance Evidence from different locations and diverse types of sleep data found that the initial months of lockdown following the beginning of the COVID-19 pandemic in March 2020 saw increased sleep durations across populations. Using a nationally representative sample of 24-hour time diaries in the United States from 2017 to 2023, this study confirms with national data that there were longer average sleep durations and later waking times after the beginning of the pandemic and that they have continued through 2023. These effects are not fully explained by working from home (WFH). While the pandemic-related increase in WFH varied greatly by education, income, and race/ethnicity groups, the COVID-19 effect on sleep characteristics was similar across these groups.

Multimodal data curation via interoperability: use cases with the Medical Imaging and Data Resource Center

Scientific Data · 2025-08-01 · 3 citations

Interoperability (the ability of data or tools from non-cooperating resources to integrate or work together with minimal effort) is particularly important for curation of multimodal datasets from multiple data sources. The Medical Imaging and Data Resource Center (MIDRC), a multi-institutional collaborative initiative to collect, curate, and share medical imaging datasets, has made interoperability with other data commons one of its top priorities. The purpose of this study was to demonstrate the interoperability between MIDRC and two other data repositories, BioData Catalyst (BDC) and National Clinical Cohort Collaborative (N3C). Using interoperability capabilities of the data repositories, we built two cohorts for example use cases, with each containing clinical and imaging data on matched patients. The representativeness of the cohorts is characterized by comparing with CDC population statistics using the Jensen-Shannon distance. The process and methods of interoperability demonstrated in this work can be utilized by MIDRC, BDC, and N3C users to create multimodal datasets for development of artificial intelligence/machine learning models.

Risk Factors for Hospital Readmission in Patients With Interstitial Lung Disease

Respiratory Care · 2024-01-10 · 4 citations

BACKGROUND: Little is known about the rates, causes, or risk factors for hospital readmission among patients with interstitial lung disease (ILD). We investigated the prevalence, features, and comorbidities of subjects hospitalized with ILD and their subsequent re-hospitalizations in this retrospective study. METHODS: A retrospective analysis of subjects enrolled in the University of Chicago ILD Natural History registry was conducted. Demographic data, comorbidities, and timing and cause of subsequent hospitalizations were collected from the medical record. The primary outcome was time to first readmission via a cause-specific Cox hazards model with a sensitivity analysis with the Fine-Gray cumulative hazard model; the secondary outcome was the number of hospitalizations per subject via a Poisson multivariable model. RESULTS: Among 1,796 patients with ILD, 443 subjects were hospitalized, with 978 total hospitalizations; 535 readmissions were studied, 282 (53%) for a respiratory indication. For the outcome of time to readmission, Black race was the only subject characteristic associated with an increased hazard of readmission in the Cox model (hazard ratio 1.50, P = .03) while Black race, hypersensitivity pneumonitis, and sarcoidosis were associated with increased hazard of readmission in the Fine-Gray model. Black race, female sex, atrial fibrillation, obstructive lung disease, and pulmonary hypertension were associated with an increased number of hospitalizations in the Poisson model. CONCLUSIONS: We demonstrated that hospital readmission from any cause was a common occurrence in subjects with ILD. Further efforts to improve quality of life among these subjects could focus on risk scores for readmission, mitigating racial health disparities, and treatment of comorbidities.

Use of Medications With Somnolence Adverse Effects and Somnolence Symptoms Among Older Adults in the U.S.

Journal of Aging and Health · 2024-11-26

ObjectivesNearly half of older adults experience somnolence, but the link between medications with somnolence as an adverse effect and somnolence is unclear. This study investigated the association between polypharmacy and somnolence symptoms (excessive sleepiness or long sleep duration).MethodsData from the National Social Life, Health, and Aging Project (NSHAP) 2010-2011 was used to examine the concurrent use of medications with potential somnolence as an adverse effect and the prevalence of somnolence symptoms.ResultsAmong the 2638 older adults (mean, 71 years), 49.0% used medications with potential somnolence adverse effects. The adjusted prevalence of somnolence symptoms was significantly higher among those using three or more medications (58%) than those not using such medications (31.2%) (difference, 20.4%; 95% CI 12.5, 28.4).DiscussionIn this cross-sectional study, medications with somnolence as a potential adverse effect were commonly used, and the findings suggest a link between polypharmacy and the increased risk of somnolence symptoms.

Prefrontal tDCS fails to modulate memory retrieval in younger and older adults

Current Biology · 2024-12-06

Adaptive measurement of cognitive function based on multidimensional item response theory

Alzheimer s & Dementia Translational Research & Clinical Interventions · 2024-10-01 · 4 citations

Abstract INTRODUCTION Up to 20% of older adults in the United States have mild cognitive impairment (MCI), and about one‐third of people with MCI are predicted to transition to Alzheimer's disease (AD) within 5 years. Standard cognitive assessments are long and require a trained technician to administer. We developed the first computerized adaptive test (CAT) based on multidimensional item response theory (MIRT) to more precisely, rapidly, and repeatedly assesses cognitive abilities across the adult lifespan. We present results for a prototype CAT (pCAT‐COG) for assessment of global cognitive function. METHODS We sampled items across five cognitive domains central to neuropsychological testing (episodic memory [EM], semantic memory/language [SM], working memory [WM], executive function/flexible thinking, and processing speed [PS]). The item bank consists of 54 items, with 9 items of varying difficulty drawn from six different cognitive tasks. Each of the 54 items has 3 response trials, yielding an ordinal score (0–3 trials correct). We also include three long‐term memory items not designed for adaptive administration, for a total bank of 57 items. Calibration data were collected in‐person and online, calibrated using a bifactor MIRT model, and pCAT‐COG scores validated against a technician‐administered neuropsychological battery. RESULTS The bifactor MIRT model improved fit over a unidimensional IRT model ( p &lt; 0.0001). The global pCAT‐COG scores were inversely correlated with age ( r = –0.44, p &lt; 0.0001). Simulated adaptive administration of 11 items maintained a correlation of r = 0.94 with the total item bank scores. Significant differences between mild and no cognitive impairment (NCI) were found (effect size of 1.08 SD units). The pCAT‐COG correlated with clinician‐based global measure ( r = 0.64). DISCUSSION MIRT‐based CAT is feasible and valid for the assessment of global cognitive impairment, laying the foundation for the development of a full CAT‐COG that will draw from a much larger item bank with both global and domain specific measures of cognitive impairment. Highlights As Americans age, numbers at risk for developing cognitive impairment are increasing. Aging‐related declines in cognition begins decades prior to the onset of obvious cognitive impairment. Traditional assessment is burdensome and requires trained clinicians. We developed an adaptive testing framework using multidimensional item response theory. It is comparable to lengthier in‐person assessments that require trained psychometrists.

MENTAL AND PHYSICAL HEALTH CONDITIONS LIMITING ACTIVITIES IN A NATIONAL SAMPLE OF OLDER LGBT ADULTS

Innovation in Aging · 2024-12-01

Abstract AIMS: Research suggests that the proportion of LGBT older adults experiencing disabilities and limitations in activities may be high compared with cisgender straight older adults, but we know little about these limitations. We aimed to understand the type and reasons for limitations in LGBT older adults. METHODS: Using a national probability sample of 210 LGBT adults 45 years and older we conducted in-person or zoom interviews and asked respondents if they were “limited in activities because of physical, mental, or emotional problems?” We followed with an open-ended question about the reason for endorsing having limitations. RESULTS: 36% of respondents reported 1 or more limitations. We categorized these limitations as related to mental health (17%), mobility (72%), pulmonary conditions (7%), sensory/cognition (8%), or cardiovascular including diabetes and obesity (8%). Overall limitations were more prevalent among respondents 65 years or older vs. 45-64 years old (47% vs. 30%), women vs. men (48% vs. 28%), White vs. POC (38% vs. 31%), bisexual and other sexual identities vs. LG (50% vs. 31%), and people with incomes below $49K vs. $50k or higher (48% vs. 32%). Reporting a chronic disease diagnosis (e.g., asthma, hypertension) vs. none was not associated with prevalence of limitations (37% vs. 36%) but self-rated poor/fair health was (58% vs. 31%). In age-adjusted analyses, being a woman, identifying as other than LG, lower income, and reporting poor/fair health were all associated with having limitations (RRR = 2.7, 3.3, 2.1, and 3.5, respectively). We will discuss predictors of observed high prevalence of limitations.