Indiana University-Purdue University Indianapolis

Studies have confirmed what physicians and healthcare providers caring for older adults have always known: many older adults are living with multiple chronic illnesses, geriatric syndromes, and functional limitations. Additionally, this population accounts for a disproportionate share of Medicare expenditures. Unfortunately, older adults receiving their care from primary care settings often fail to receive the recommended standards of care. In response to the need for new delivery models to better address common geriatric conditions and integrate medical and social care, the clinicians and researchers at the Indiana University Center for Aging Research designed and tested a new model of interdisciplinary team care called GRACE, Geriatric Resources for Assessment and Care of Elders. The GRACE model was originally developed to improve the quality and outcomes of care for older adults. The goal of the GRACE model is to optimize health and functional status, decrease excess healthcare use, and prevent long-term nursing home placement.

Over the last two decades, scientists from the Indiana Center for Aging Research (IUCAR) have led or participated in two randomized clinical trials testing comprehensive care models for older adults suffering from dementia and depression. Both studies were conducted in a primary care practice within Eskenazi Health (Eskenazi) [formerly Wishard Health Services], an urban safety net hospital system primarily serving a racially and ethnically diverse population of vulnerable adults [1, 2]. The findings from these two trials provided the justification and the foundation for the Indiana Aging Brain Care Project.

Introduction Rates of substance use are high among youth involved in the legal system (YILS); however, YILS are less likely to initiate and complete substance use treatment compared to their non legally-involved peers. There are multiple steps involved in connecting youth to needed services, from screening and referral within the juvenile legal system to treatment initiation and completion within the behavioral health system. Understanding potential gaps in the care continuum requires data and decision-making from these two systems. The current study reports on the development of data dashboards that integrate these systems’ data to help guide decisions to improve substance use screening and treatment for YILS, focusing on end-user feedback regarding dashboard utility. Methods Three focus groups were conducted with n = 21 end-users from juvenile legal systems and community mental health centers in front-line positions and in decision-making roles across 8 counties to gather feedback on an early version of the data dashboards; dashboards were then modified based on feedback. Results Qualitative analysis revealed topics related to (1) important aesthetic features of the dashboard, (2) user features such as filtering options and benchmarking to compare local data with other counties, and (3) the centrality of consistent terminology for data dashboard elements. Results also revealed the use of dashboards to facilitate collaboration between legal and behavioral health systems. Conclusions Feedback from end-users highlight important design elements and dashboard utility as well as the challenges of working with cross-system and cross-jurisdiction data.

Automatic dense 3D surface registration is a powerful technique for comprehensive 3D shape analysis that has found a successful application in human craniofacial morphology research, particularly within the mandibular and cranial vault regions. However, a notable gap exists when exploring the frontal aspect of the human skull, largely due to the intricate and unique nature of its cranial anatomy. To better examine this region, this study introduces a simplified single-surface craniofacial bone mask comprising of 6707 quasi-landmarks, which can aid in the classification and quantification of variation over human facial bone surfaces. Automatic craniofacial bone phenotyping was conducted on a dataset of 31 skull scans obtained through cone-beam computed tomography (CBCT) imaging. The MeshMonk framework facilitated the non-rigid alignment of the constructed craniofacial bone mask with each individual target mesh. To gauge the accuracy and reliability of this automated process, 20 anatomical facial landmarks were manually placed three times by three independent observers on the same set of images. Intra- and inter-observer error assessments were performed using root mean square (RMS) distances, revealing consistently low scores. Subsequently, the corresponding automatic landmarks were computed and juxtaposed with the manually placed landmarks. The average Euclidean distance between these two landmark sets was 1.5 mm, while centroid sizes exhibited noteworthy similarity. Intraclass coefficients (ICC) demonstrated a high level of concordance (> 0.988), with automatic landmarking showing significantly lower errors and variation. These results underscore the utility of this newly developed single-surface craniofacial bone mask, in conjunction with the MeshMonk framework, as a highly accurate and reliable method for automated phenotyping of the facial region of human skulls from CBCT and CT imagery. This craniofacial template bone mask expansion of the MeshMonk toolbox not only enhances our capacity to study craniofacial bone variation but also holds significant potential for shedding light on the genetic, developmental, and evolutionary underpinnings of the overall human craniofacial structure.

Panel count regression is often required in recurrent event studies, where the interest is to model the event rate. Existing rate models are unable to handle time-varying covariate effects due to theoretical and computational difficulties. Mean models provide a viable alternative but are subject to the constraints of the monotonicity assumption, which tends to be violated when covariates fluctuate over time. In this paper, we present a new semiparametric rate model for panel count data along with related theoretical results. For model fitting, we present an efficient EM algorithm with three different methods for variance estimation. The algorithm allows us to sidestep the challenges of numerical integration and difficulties with the iterative convex minorant algorithm. We showed that the estimators are consistent and asymptotically normally distributed. Simulation studies confirmed an excellent finite sample performance. To illustrate, we analyzed data from a real clinical study of behavioral risk factors for sexually transmitted infections.

Objectives To develop a prediction model for hypertensive disorders in pregnancy (HDP) and gestational diabetes (GDM) in twin pregnancies utilizing characteristics at the prenatal care entry level. Methods Cross‐sectional study using the US national live birth data between 2016 and 2021. The association of all prenatal candidate variables with HDP and GDM was tested with uni‐ and multi‐variable logistic regression analyses. Prediction models were built with generalized linear models using the logit link function and classification and regression tree approach (XGboost) machine learning (ML) algorithm. Performance was assessed with repeated 2‐fold cross‐validation and performance metrics we considered were area under the curve (AUC). P value <0.001 was considered statistically significant. Results A total of 707,198 twin pregnancies were included in the HDP analysis and 723,882 twin pregnancies for the GDM analysis. The incidence of HDP and GDM significantly increased from 12.2% in 2016 to 15.4% in 2021 and from 8.1% in 2016 to 10.7% in 2021, respectively. Factors that increase the risk of HDP in twin gestations are maternal age <20, age≥35, infertility, prepregnancy DM, non‐Hispanic Black population, obesity, and those with Medicaid insurance (p<0.001). Factors that more than doubled the risk are obesity class II and III (p<0.001). Factors that increase the risk of GDM in twin gestations are age <25, age≥30, history of infertility, prepregnancy hypertension, non‐Hispanic Asian population, non‐US nativity, and obesity (p<0.001). Factors that more than doubled the risk are maternal age ≥ 30 years, non‐Hispanic Asian, and class I, II, and III maternal obesity ( p<0.001). For both HDP and GDM, the performance of the ML and logistic regression model was mostly similar with negligible difference in terms of all tested performance domains. The AUC of the final ML model for HDP and GDM were 0.62±0.004, and 0.67±0.004, respectively. Conclusions The incidence of HDP and GDM in twin gestations is increasing. The predictive accuracy of the machine learning model for both HDP and GDM in twin gestations is similar to that of the logistic regression model. Both models had modest performance, well‐calibrated, and neither had a poor fit. This article is protected by copyright. All rights reserved.

An increasing number of people identify as feminists, but there is disagreement about whom and what feminism should be fighting for. Using a multi-method approach, across three studies (total N = 3,387), we examine (1) disagreements in today’s feminist movement and how these disagreements come together to form different ideological groups as well as (2) psychological variables associated with different feminist beliefs and ideologies. In doing so we establish a nuanced picture of contemporary feminism in the UK and the US. Study 1 used open-response data to identify topics on which today’s feminists disagree. Study 2 used exploratory factor analyses to examine how views on these topics hang together, resulting in eight feminist beliefs scales. Finally, Study 3 used cluster analysis to determine what ideological groups of feminists exist in quasi-representative samples from the US and the UK and explored the associations of these beliefs with relevant psychological constructs. Transgender issues, sex work, and the importance of marginalized perspectives were the most polarizing issues across studies, highlighting that feminists are more divided on the issue of who feminism should fight for, than what feminism should fight for. These studies show the heterogeneity of feminist ideologies and the continued barriers to a truly inclusive and intersectional feminist movement.

Introduction Numerous tools have been developed to measure constructs related to wheelchair use. Currently, no toolkit comprehensively details assessments of wheeled mobility device use based on the quality of their measurement properties. The current review aims to systematically identify high-quality assessment tools that measure different aspects of wheeled mobility use. Objective The objectives are two-fold: (1) to synthesize outcome measures that assess use of wheeled mobility devices, and (2) to evaluate measurement properties of the assessment tools. Inclusion criteria The populations of interest are manual wheelchair users, power wheelchair users, and scooter users of any age, diagnosis, or setting. Instruments of any type will be included. Method The JBI methodology for systematic reviews of measurement properties will guide this review. A search strategy will be developed to search the following databases: MEDLINE (Ovid), Embase, CINAHL (EBSCOhost), PsycINFO (EBSCOhost), PsycTests (EBSCOhost), Web of Science, and Google Scholar. The article selection process, data extraction, and quality appraisal will be performed by 2 independent reviewers, with a third reviewer being consulted to achieve consensus. The methodological quality of the studies will be assessed through the Consensus Standards for the Selection of Measurement Instruments (COSMIN) Risk of Bias tool and the COSMIN Checklist. The quality of the pooled evidence and individual measurement properties will be graded using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach and the COSMIN Criteria for Good Measurement Properties recommendations. Measurement properties of each instrument will be described, with the goal of developing a toolkit that identifies appropriate assessment tools for wheeled mobility use outcomes. Systematic review registration PROSPERO: CRD4202276169

Background Utilizing expanded endoscopic approaches to the maxillary sinus for the endonasal management of a variety of tumors is increasing in popularity. The nasolacrimal duct (NLD) may be injured inadvertantly or need to be removed during tumor resection or to augment visualization. Management of the NLD can take the form of transection alone, transection with stenting, or performing a formal dacryocystorhinostomy to avoid postoperative sequelae of injury. The purpose of this study was to review the literature and determine the optimal management of the NLD during expanded maxillary sinus approaches. Methods A systematic review of Ovid, Embase, Medline, and Cochrane databases was performed to identify studies involving expanded approaches to the maxillary sinus and that explicitly reported the status of the NLD and postoperative outcomes. Results Nineteen studies were included in the analysis and divided into two groups: NLD-preserving (n = 9 studies; n = 191 patients in aggregate) and NLD-involving (n = 10 studies; n = 296 patients in aggregate). In the NLD-preserving subgroup, one patient out of a subgroup aggregate of 191 patients (0.5%) developed epiphora. In the NLD-involving subgroup, sharp transection alone was the most common method of NLD removal and was associated with a low rate of epiphora (study rates: 0 to 18.2%; aggregated subgroup rate: 7.0%, 21 / 296). Spontaneous resolution of symptoms was common (60%-100% cases). Conclusions The NLD should be preserved when feasible from an exposure and tumor-control perspective. When pathology or approach requires the removal of the NLD, rates of persistent epiphora are very low, regardless of surgical technique. When expanded maxillary approaches are employed, particularly for benign tumors, and require removal of the NLD, sharp transection is the simplest method of removal, provides a low rate of postoperative epiphora, and is supported by the available literature.

Particle erosion is a major failure mechanism in thermal barrier coatings. In this work, a discrete element model is developed to simulate the crack propagation due to particle erosion. The effects of the interface bond layer roughness and pre-crack are focused. The results show that with the increasing roughness of the bonding layer, the extension length of the delamination cracks is reduced. The delamination cracks are suppressed when the roughness increases. The initial vertical TC defects can effectively inhibit the nucleation and extension of the new cracks. This study provides a theoretical foundation for understanding the crack failure mechanism in thermal barrier coatings.

The purpose of this study was to examine the relationships between social factors of stigma and loneliness, in rural communities, that may differ in people with self-reported opioid use disorder (OUD) and those without self-reported OUD. The study’s purpose also includes an exploration of the relationships between knowledge and stigma. A cross-sectional descriptive study via survey methods was used. A convenience sample was recruited from Southern Indiana (IN) rural counties with zip codes that had some of the highest opioid use and reported overdoses in IN. Data was analyzed using logistic regression and mean/median difference-based statistics. The odds of having an OUD were significantly lower for persons who endorsed more self-stigmatization for illicit opioid use. Having less than a high school education was associated with a statistically significant, 8.5 times increase in the likelihood that rural participants would report having symptoms consistent with an OUD diagnosis. The present study advances the understanding of rural perceptions of and experiences with OUD and Stigma related HIV outbreaks and psychosocial factors which differentiate persons reporting OUD consistent symptoms.

Music therapy interventions target biopsychosocial outcomes and are a non-pharmacological option for integrated pain management. To date, most music and pain studies have focused on acute pain, passive music experiences, and in-person delivery. The purpose of this study was to examine feasibility and acceptability and determine proof-of-concept for a newly developed telehealth music imagery (MI) intervention for Veterans with chronic pain. A single-group proof-of-concept pilot study was conducted with Veterans with chronic pain (n = 8). Feasibility was assessed through examination of recruitment, retention, and session/measure completion rates; acceptability through participant interviews; and whether the intervention resulted in clinically meaningful change scores (pre- to post-intervention) on measures of pain, anxiety, and depression at the individual level. For Veterans who passed eligibility screening, we had an enrollment rate of 89%, with good retention (75%). Overall, participating Veterans found the intervention acceptable, identified specific challenges with technology, and recommended an increased number of sessions. Preliminary outcome data for pain, anxiety, and depression were mixed, with some Veterans reporting clinically meaningful improvements and others reporting no change or worsening symptoms. Findings informed modifications to the telehealth MI intervention and the design of a larger pilot randomized controlled trial to assess feasibility and acceptability of the modified intervention in a larger population of Veterans with chronic pain using additional measures and a control condition.

Introduction Transdiagnostic self-help cognitive behavioral therapy (CBT) approaches may help ease the burden of untreated symptoms of internalizing distress, especially in geographic areas with relatively small numbers of mental health providers. Methods Over the course of 12 months, we conducted a six-week randomized controlled trial (N = 275) across Indiana, a state with high unmet need for mental health care. All participants were given immediate access to a single-session intervention (SSI) followed by randomization to either guided or unguided CBT-based bibliotherapy. We used mixed models to model change over time in distress, well-being, and emotion regulation as a piecewise function of study week. Results The sample was in their early 30s (M = 34.10, SD = 11.68), mostly female (75.64%, n = 208) and, consistent with the demographics of the state, mostly Non-Hispanic White (80.36%, n = 221). Less than half of participants accessed the SSI (39.27%, n = 108). There was no evidence that completing the SSI was associated with improved outcomes, though it improved study engagement. Participants randomized to the guided (vs. unguided) condition experienced greater overall improvements in internalizing distress (SMD=-0.44, 95% CI: -0.74, -0.13) and cognitive reappraisal (SMD = 0.32, 95% CI: 0.06, 0.58). The differences between groups in improvements in well-being (SMD = 0.25, 95% CI: -0.13, 0.63) and expressive suppression (SMD=-0.24, 95% CI: -0.55, 0.07) were smaller and not statistically significant. Virtually all participants expressed some interest in more therapy via telehealth (89.74%, n = 140). Findings were sensitive to multiple imputation using random forests as well as propensity score matching. Discussion Self-help approaches are scalable interventions for individuals in under-served states. As in previous work, guided self-help was more effective than unguided self-help. More work should focus on adding additional treatment steps past self-help.

Hematopoietic cell transplantation (HCT) uses cytotoxic chemotherapy and/or radiation followed by intravenous infusion of stem cells to cure malignancies, bone marrow failure and inborn errors of immunity, hemoglobin and metabolism. Lung injury is a known complication of the process, due in part to disruption in the pulmonary microenvironment by insults such as infection, alloreactive inflammation and cellular toxicity. How microorganisms, immunity and the respiratory epithelium interact to contribute to lung injury is uncertain, limiting the development of prevention and treatment strategies. Here we used 278 bronchoalveolar lavage (BAL) fluid samples to study the lung microenvironment in 229 pediatric patients who have undergone HCT treated at 32 children’s hospitals between 2014 and 2022. By leveraging paired microbiome and human gene expression data, we identified high-risk BAL compositions associated with in-hospital mortality (P = 0.007). Disadvantageous profiles included bacterial overgrowth with neutrophilic inflammation, microbiome contraction with epithelial fibroproliferation and profound commensal depletion with viral and staphylococcal enrichment, lymphocytic activation and cellular injury, and were replicated in an independent cohort from the Netherlands (P = 0.022). In addition, a broad array of previously occult pathogens was identified, as well as a strong link between antibiotic exposure, commensal bacterial depletion and enrichment of viruses and fungi. Together these lung–immune system–microorganism interactions clarify the important drivers of fatal lung injury in pediatric patients who have undergone HCT. Further investigation is needed to determine how personalized interpretation of heterogeneous pulmonary microenvironments may be used to improve pediatric HCT outcomes.

Periplasmic nitrate reductase NapA from Campylobacter jejuni (C. jejuni) contains a molybdenum cofactor (Moco) and a 4Fe–4S cluster and catalyzes the reduction of nitrate to nitrite. The reducing equivalent required for the catalysis is transferred from NapC → NapB → NapA. The electron transfer from NapB to NapA occurs through the 4Fe–4S cluster in NapA. C. jejuni NapA has a conserved lysine (K79) between the Mo-cofactor and the 4Fe–4S cluster. K79 forms H-bonding interactions with the 4Fe–4S cluster and connects the latter with the Moco via an H-bonding network. Thus, it is conceivable that K79 could play an important role in the intramolecular electron transfer and the catalytic activity of NapA. In the present study, we show that the mutation of K79 to Ala leads to an almost complete loss of activity, suggesting its role in catalytic activity. The inhibition of C. jejuni NapA by cyanide, thiocyanate, and azide has also been investigated. The inhibition studies indicate that cyanide inhibits NapA in a non-competitive manner, while thiocyanate and azide inhibit NapA in an uncompetitive manner. Neither inhibition mechanism involves direct binding of the inhibitor to the Mo-center. These results have been discussed in the context of the loss of catalytic activity of NapA K79A variant and a possible anion binding site in NapA has been proposed.