Faculty Bibliography

We present a hierarchical integrated model of self-regulation in which executive function is the cognitive component of the model, together with emotional, behavioral, physiological, and genetic components. These five components in the model are reciprocally and recursively related. The model is supported by empirical evidence, primarily from a single longitudinal study with good measurement at each level of the model. We also find that the model is consistent with current thinking on related topics such as cybernetic theory, the theory of allostasis and allostatic load, and the theory of skill development in harsh and unpredictable environments, referred to as "hidden talents." Next, we present literature that the integrative processes are susceptible to environmental adversity, poverty-related risk in particular, while positive social interactions with caregivers (e.g., maternal sensitivity) would promote self-regulatory processes or mitigate the adverse effect of early risk on the processes. A hierarchical integrative model of self-regulation advances our understanding of self-regulatory processes. Future research may consider broader social contexts of the integrative self-regulation system, such as neighborhood/community contexts and structural racism. This can be an integral step to provide children with equitable opportunities to thrive, even among children living in socioeconomically and psychosocially disadvantaged environments.

BACKGROUND:Older adults account for a large proportion of emergency department visits, but those with serious life-limiting illness may benefit most from referral to home and community services instead of hospitalization. We aim to document emergency provider perspectives on facilitators and barriers to accessing home and community services for older adults with serious life-limiting illness. METHODS:We conducted interviewer-administered semi-structured interviews with emergency providers from health systems across the United States to obtain provider perspectives on facilitators and barriers to accessing home and community services. We completed qualitative thematic analysis using an iterative process to develop themes and subthemes to summarize provider responses. RESULTS:We interviewed 8 emergency nurses and 10 emergency physicians across 11 health systems. Emergency providers were familiar with local home and community services. Facilitators to accessing these services include care management and social workers. Barriers include services that are not accessible full-time to receive referrals, insurance/payment, and the busy nature of the emergency department. The most helpful reported services were hospice, physical therapy, occupational therapy, and visiting nursing services. Home-based palliative care and full-time emergency department-based care management and social work were the services most desired by providers. Providers expressed support for improving access to home and community services in the hopes of decreasing unnecessary emergency visits and inpatient admissions, and to provide patients with greater options for supportive care. CONCLUSION/CONCLUSIONS:Obtaining the perspective of emergency providers highlights important considerations to accessing HCS for older-adults with serious life-limiting illness from the emergency department. This study provides foundational information for futures studies and initiatives for improving access to home and community services directly from the emergency department.

Background: Mobile health cardiac rehabilitation (mHealth-CR) may improve outcomes among older adults with ischemic heart disease, but variable engagement is not yet understood. We therefore analyzed preliminary data from the RESILIENT trial, an ongoing randomized trial of mHealth-CR vs. usual care in patients age >= 65.
Method(s): Data from the first 50 intervention participants were analyzed. Weekly engagement was scored from 0-11 based on exercise completion, therapist communication, video viewing, and BP self-measurement. Participants were classified as high or low engagement based on median engagement scores. Groups were compared by age, sex, social support (living alone), depression (PHQ-8), and Charlson Comorbidity Index (CCI).
Result(s): There was widely varying engagement with mHealth-CR that ranged from nearly zero to nearly perfect engagement (Figure). There were no significant differences between high and low engagement groups based on mean age (72.6 vs. 72.8, P=0.8), sex (76% male vs. 80%, P=0.7), living alone (28% vs. 44%, P=0.2), depression (mean 3.9 vs. 4.6, P=0.5), or comorbidity burden (mean 4.4 vs. 4.8, P=0.3), although the sample size was small.
Conclusion(s): Our early findings show wide variation in mHealth-CR engagement among older adults

Background: We recently implemented the Age-Friendly Health System's 4Ms (What Matters, Medication, Mentation, and Mobility) framework in New York City Health + Hospitals/Bellevue Hospital Center's Geriatrics clinic to improve care of older adults.
Method(s): We examined the impact of 4Ms assessment on patient care and changes in care processes through specific interventions triggered after assessment. We conducted chart reviews of patient visits during March 2021, the first month of 4Ms implementation and identified interventions made during these visits. To assess "What Matters" providers asked "What Matters the most to you;" potentially inappropriate Medications (PIM) were identified using the Beers list; Mentation was evaluated using the Mini-Cog; and Mobility was determined using timed up and go (TUG) test. We used descriptive statistics to characterize findings.
Result(s): Among the 121 patients who had 4Ms assessment in March 2021, 85% (n=103) were asked "What Matters;" providers reviewed Medications for almost all (n=118; 98%) and conducted a Mini-Cog for 64% (n=78). Most not cognitively assessed were either previously screened (n=11; 9%) or had dementia (n=12; 10%). Providers used the TUG test for 87% (n=105). What Mattered to patients most commonly was "getting better" (n=24; 23%). There were 39 (33%) patients with potentially inappropriate Medications (including proton pump inhibitors, gabapentinoids, and NSAIDS) of which 10 (26%) Medications were either discontinued or reduced. Other interventions included further cognitive evaluation (n=2) and home care referrals (n=2) among 14 (18%) with an abnormal Mini- Cog. Among the 51 (42%) patients with an abnormal TUG, providers intervened for 19 (37%) with devices, referrals or home services.
Conclusion(s): The adoption of 4Ms assessment during routine visits identified issues with Medications, Mentation and Mobility, triggering several interventions for common geriatric conditions. 4Ms assessment is a helpful strategy to organize geriatric care, routinely assess patients for common geriatric syndromes, and improve care. Future directions include prioritizing interventions integrated with "What Matters" to maintain patient-centered care

Background: Neighborhood disadvantage influences health outcomes regardless of personal economic status, illustrating the importance of neighborhood context on health. The Area Deprivation index (ADI) establishes a ranking system of U.S. neighborhoods on state and national levels based on 17 neighborhood factors. Using data from an ongoing study of patients with dual diagnoses of diabetes and dementia, we investigated the relationship between ADI and diabetic outcomes, including glycemic control, blood pressure, and dementia severity.
Method(s): We conducted descriptive and bivariate statistics using 3 years of health record data from patients of NYU Langone Health. We included patients >=65 years, with ADRD and DM, and on DM medication. In addition to demographic measures and NY home addresses, we collected hemoglobin A1c, blood pressure, and assessed dementia severity, surveying proxies with the dementia severity rating scale (DSRS). We used ArcGIS and ADI data to link patient addresses to an ADI score. We stratified the sample into two groups: a low deprivation group with ADI scores 1-5, and a high deprivation group with ADI scores 6-10.
Result(s): Of those meeting inclusion criteria (n=996), most were over 75 years (73.5%), female (60.1%), white (71.2%), and not Hispanic or Latino (72.4%). Mean patient age was 81.3; standard deviation (SD): 7.6. More than 50% of patients had an NY state ADI score of 1, 2 or 3 out of 10, indicating that the majority of the population lived in neighborhoods of less disadvantage. 83.4% (n=831) of the population fell into the low deprivation group. There were no differences in hemoglobin A1c (7.09 vs. 7.01) or dementia severity (25.5 +/- 0.8 vs. 22.4 +/- 2.0) between low and high deprivation groups, respectively. However, systolic blood pressure was greater in high deprivation individuals (132.4 +/- 19.3 mm Hg vs. 128.6 +/- 18.2; p=0.02).
Conclusion(s): The ADI in this study was associated with blood pressure but not diabetic control or dementia severity. Less heterogeneity in disadvantage limited our ability to detect this potential social determinant of health. In a city, where neighborhood disadvantage changes from block to block, the influence of environment on health may be more difficult to detect

Background: Clinical trials are important to improve evidencebased care for persons living with dementia (PLWD) and for their care partners (dyads). Barriers to research recruitment are numerous, including care partners concerns' of ill health, cognitive impairment (CI) severity, and denial of need. The aim of this study is to determine whether a performance- or informant-based screening test for CI is associated with trial enrollment and whether mode of administration influences one's decision to participate.
Method(s): We used cross-sectional data from patients and caregivers who visited the EDs of New York University (NYU) and Indianapolis University (IU) during screening for the Program of Intensive Support in Emergency Departments (ED) for Care Partners of Cognitively Impaired Patients (POISED), which is testing a care management intervention. We offered CI screening to patients >75 years using the Mini-Cog and if unable to do this, we offered their care partners the Short Portable Informant Questionnaire of Cognitive Decline (IQ-CODE). We used chi-square tests and logistic regression to determine whether likelihood of enrollment differed between screening tests and mode of administration: in-person versus telephone.
Result(s): We screened 8860 patients or care partners (dyads) between 3/3/2018-4/1/2021, of which n=2840 at NYU and n=660 at IU had positive screens. Of these 3500 dyads, 2142 had a positive Mini-Cog (<2) and 1358 had a positive IQ-CODE (>3.40). We enrolled 13.9% (n=297) of positive Mini-Cogs and 14.5% (n=309) of positive in-person IQ-CODEs. During the pandemic we conducted all IQCODEs by phone and enrolled 34% (n=196) of those who screened positive. Adjusting for age, sex, and gender, compared to Mini-Cog screening, only those having positive IQCODES by phone were more likely to enroll (adjusted odds ratio (AOR): 3.75 (95% CI: 2.76, 5.11).
Conclusion(s): Higher enrollment using informant-based telephone screening after discharge suggests that care partner recognition of a problem and perhaps having less distraction from the ED visit may increase trial enrollment. Whether the pandemic was the predomant factor encouraging enrollment is unknown

INTRODUCTION/UNASSIGNED:In order to obtain FDA Marketing Authorization for aid in the diagnosis of concussion, an eye tracking study in an intended use population was conducted. METHODS/UNASSIGNED:Potentially concussed subjects recruited in emergency department and concussion clinic settings prospectively underwent eye tracking and a subset of the Sport Concussion Assessment Tool 3 at 6 sites. The results of an eye tracking-based classifier model were then validated against a pre-specified algorithm with a cutoff for concussed vs. non-concussed. The sensitivity and specificity of eye tracking were calculated after plotting of the receiver operating characteristic curve and calculation of the AUC (area under curve). RESULTS/UNASSIGNED:= 282) was 31.6%. CONCLUSION/UNASSIGNED:A pre-specified algorithm and cutoff for diagnosis of concussion vs. non-concussion has a sensitivity and specificity that is useful as a baseline-free aid in diagnosis of concussion. Eye tracking has potential to serve as an objective "gold-standard" for detection of neurophysiologic disruption due to brain injury.