Alterations in cerebral blood flow (CBF) are associated with risk of cognitive decline and Alzheimer’s disease (AD). Although apolipoprotein E (APOE) ε4 and greater vascular risk burden have both been linked to reduced CBF in older adults, less is known about how APOE ε4 status and vascular risk may interact to influence CBF. We aimed to determine whether the effect of vascular risk on CBF varies by gene dose of APOE ε4 alleles (i.e., number of e4 alleles) in older adults without dementia.

144 older adults without dementia from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) underwent arterial spin labeling (ASL) and T1-weighted MRI, APOE genotyping, fluorodeoxyglucose positron emission tomography (FDG-PET), lumbar puncture, and blood pressure assessment. Vascular risk was assessed using pulse pressure (systolic blood pressure -diastolic blood pressure), which is thought to be a proxy for arterial stiffening. Participants were classified by number of APOE ε4 alleles (n0 alleles = 87, m allele = 46, n2 alleles = 11). CBF in six FreeSurfer-derived a priori regions of interest (ROIs) vulnerable to AD were examined: entorhinal cortex, hippocampus, inferior temporal cortex, inferior parietal cortex, rostral middle frontal gyrus, and medial orbitofrontal cortex. Linear regression models tested the interaction between categorical APOE ε4 dose (0, 1, or 2 alleles) and continuous pulse pressure on CBF in each ROI, adjusting for age, sex, cognitive diagnosis (cognitively unimpaired vs. mild cognitive impairment), antihypertensive medication use, cerebral metabolism (FDG-PET composite), reference CBF region (precentral gyrus), and AD biomarker positivity defined using the ADNI-optimized phosphorylated tau/ß-amyloid ratio cut-off of > 0.0251 pg/ml.

A significant pulse pressure X APOE ε4 dose interaction was found on CBF in the entorhinal cortex, hippocampus, and inferior parietal cortex (ps < .005). Among participants with two e4 alleles, higher pulse pressure was significantly associated with lower CBF (ps < .001). However, among participants with zero or one ε4 allele, there was no significant association between pulse pressure and CBF (ps > .234). No significant pulse pressure X APOE ε4 dose interaction was found in the inferior temporal cortex, rostral middle frontal gyrus, or medial orbitofrontal cortex (ps > .109). Results remained unchanged when additionally controlling for general vascular risk assessed via the modified Hachinski Ischemic Scale.

These findings demonstrate that the cross-sectional association between pulse pressure and region-specific CBF differs by APOE ε4 dose. In particular, a detrimental effect of elevated pulse pressure on CBF in AD-vulnerable regions was found only among participants with the e4/e4 genotype. Our findings suggest that pulse pressure may play a mechanistic role in neurovascular unit dysregulation for those genetically at greater risk for AD. Given that pulse pressure is just one of many potentially modifiable vascular risk factors for AD, future studies should seek to examine how these other factors (e.g., diabetes, high cholesterol) may interact with APOE genotype to affect cerebrovascular dysfunction.

Social determinants of health (SDoH) are structural elements of our living and working environments that fundamentally shape health risks and outcomes. The Healthy People 2030 campaign delineated SDoH into five distinct categories that include: economic stability, education access/quality, healthcare access, neighborhood and built environment, and social and community contexts. Recent research has demonstrated that minoritized individuals have greater disadvantage across SDoH domains, which has been linked to poorer cognitive performance in older adulthood. However, the independent effects of SDoH on everyday functioning across and within racial groups remains less clear. The current project explored the association between SDoH factors and 10-year change in everyday functioning in a large sample of community-dwelling Black and White older adults.

Data from 2,505 participants without dementia enrolled in the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study (age M=73.5; 76% women; 28% Black/African American). Sociodemographic, census, and industry classification data were reduced into five SDoH factors: economic stability, education access and quality, healthcare access and quality, neighborhood and built environment, and social and community contexts. The Observed Tasks of Daily Living, a performance-based measure of everyday functioning with tasks involving medication management, finances, and telephone use, was administered at baseline, 1-, 2-, 3-, 5, and 10-year follow up visits. Mixed-effects models with age as the timescale tested (1) racial group differences in OTDL trajectories, (2) race x SDOH interactions on OTDL trajectories, and (3) associations between SDoH and OTDL trajectories stratified within Black and White older adults. Covariates included sex/gender, vocabulary score, Mini-Mental Status Examination, depressive symptoms, visual acuity, general health, training group status, booster status, testing site, and recruitment wave.

Black older adults had a steeper decline of OTDL performance compared to Whites (linear: b = -.25, quadratic b=-.009, ps < .001). There was a significant race x social and community context interaction on linear OTDL trajectories (b =.06, p=.01), but no other significant race x SDoH interactions were observed (bs =-.007-.05, ps=.73-.11). Stratified analyses revealed lower levels of social and community context were associated with steeper age-related linear declines in OTDL performance in Black (b = .08, p=.001), but not White older adults (b =.004, p=.64). Additionally, lower levels of economic stability were associated with steeper age-related linear declines in OTDL performance in Black (b =.07, p=.04), but not White older adults (b =.01, p=.35). Finally, no significant associations between other SDoH and OTDL trajectories were observed in Black (bs = -.04-.01, ps =.09-.80) or White (bs = -.02-.003, ps=.07-.96) older adults.

SDoH, which measure aspects of structural racism, play an important role in accelerating age-related declines in everyday functioning. Lower levels of economic and community-level social resources are two distinct SDoH domains associated with declines in daily functioning that negatively impact Black, but not White, older adults. It is imperative that future efforts focus on both identifying and acting upon upstream drivers of SDoH-related inequities. Within the United States, this will require addressing more than a century of antiBlack sentiment, White supremacy, and unjust systems of power and policies designed to intentionally disadvantage minoritized groups.

Prior work on associations between self-reported cognition and objective cognitive performance in Veterans has yielded mixed findings, with some evidence indicating that mild traumatic brain injury (TBI) may not impact the associations between subjective and objective cognition. However, few studies have examined these relationships in both mild and moderate-to-severe TBI, in older Veterans, and within specific cognitive domains. Therefore, we assessed the moderating effect of TBI severity on subjective and objective cognition across multiple cognitive domains.

This study included 246 predominately male Vietnam-Era Veterans (age M=69.61, SD=4.18, Range = 60.87 – 85.16) who completed neuropsychological testing and symptom questionnaires as part of the Department of Defense-Alzheimer’s Disease Neuroimaging Initiative (DoD-ADNI). Participants were classified as having history of no TBI (n=81), mild TBI (n=80), or moderate-tosevere TBI (n=85). Neuropsychological composite scores in the domains of memory, attention/executive functioning, and language were included as the outcome variables. The Everyday Cognition (ECog) measure was used to capture subjective cognition and, specifically, the ECog domain scores of memory, divided attention, and language were chosen as independent variables to mirror the objective cognitive domains. General linear models, adjusting for age, education, apolipoprotein E ε4 carrier status, pulse pressure, depressive symptom severity, and PTSD symptom severity, tested whether TBI severity moderated the associations of domain-specific subjective and objective cognition.

Across the sample, subjective memory was associated with objective memory (β=-.205, 95% CI [-.332, -.078], p=.002) and subjective language was associated with objective language (β=-.267, 95% CI [-.399, -.134], p<.001). However, the main effect of subjective divided attention was not associated with objective attention/executive functioning (p=.124). The main effect of TBI severity was not associated with any of the objective cognitive domain scores after adjusting for the other variables in the model. The TBI severity x subjective cognition interaction was significant for attention/executive functioning [F(2,234)=5.18, p=.006]. Specifically, relative to Veterans without a TBI, participants with mild TBI (β=-.311, 95% CI [-.620, -.002], p=.048) and moderate-to-severe TBI (β=-.499, 95% CI [-.806, -.193], p=.002) showed stronger negative associations between subjective divided attention and objective attention/executive functioning. TBI severity did not moderate the associations between subjective and objective cognition for memory or language domains. The pattern of results did not change when the total number of TBIs was included in the models.

In this DoD-ADNI sample, stronger associations between subjective and objective attention were evident among individuals with mild and moderate-to-severe TBI compared to Veterans without a TBI history. Attention/executive functioning measures (Trails A and B) may be particularly sensitive to detecting subtle cognitive difficulties related to TBI and/or comorbid psychiatric symptoms, which may contribute to these attention-specific findings. The strongest associations were among those with moderate-to-severe TBI, potentially because the extent to which their attention difficulties are affecting their daily lives are more apparent despite no significant differences in objective attention performance by TBI group. This study highlights the importance of assessing both subjective and objective cognition in older Veterans and the particular relevance of the attention domain within the context of TBI.

While loss of insight into one’s cognitive impairment (anosognosia) is a feature in Alzheimer’s disease dementia, less is known about memory self-awareness in cognitively unimpaired (CU) older adults or mild cognitive impairment (MCI) or factors that may impact self-awareness. Locus of control, specifically external locus of control, has been linked to worse cognitive/health outcomes, though little work has examined locus of control as it relates to self-awareness of memory functioning or across cognitive impairment status. Therefore, we examined associations between locus of control and memory self-awareness and whether MCI status impacted these associations.

Participants from the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study (mean age=73.51; 76% women; 26% Black/African American) were classified as CU (n=2177) or MCI (amnestic n=313; non-amnestic n=170) using Neuropsychological Criteria. A memory composite score measured objective memory performance and the Memory Functioning Questionnaire measured subjective memory. Memory self-awareness was defined as objective memory minus subjective memory, with positive values indicating overreporting of memory difficulties relative to actual performance (hypernosognosia) and negative values indicating underreporting (hyponosognosia). Internal (i.e., personal skills/attributes dictate life events) and external (i.e., environment/others dictate life events) locus of control scores came from the Personality in Intellectual Aging Contexts Inventory. General linear models, adjusting for age, education, sex/gender, depressive symptoms, general health, and vocabulary examined the effects of internal and external locus of control on memory self-awareness and whether MCI status moderated these associations.

Amnestic and non-amnestic MCI participants reported lower internal and higher external locus of control than CU participants. There was a main effect of MCI status on memory self-awareness such that amnestic MCI participants showed the greatest degree of hyponosognosia/underreporting, followed by non-amnestic MCI, and CU participants slightly overreported their memory difficulties. While, on average, participants were fairly accurate at reporting their degree of memory difficulty, internal locus of control was negatively associated with self-awareness such that higher internal locus of control was associated with greater underreporting (ß=-.127, 95% CI [-.164, -.089], p<.001). MCI status did not moderate this association. External locus of control was positively associated with self-awareness such that higher external locus of control was associated with greater hypernosonosia/overreporting (ß=.259, 95% CI [.218, .300], p<.001). Relative to CU, amnestic, but not non-amnestic, MCI showed a stronger association between external locus of control and memory self-awareness. Specifically, higher external locus of control was associated with less underreporting of cognitive difficulties in amnestic MCI (ß=.107, 95% CI [.006, .208], p=.038).

In CU participants, higher external locus of control was associated with greater hypernosognosia/overreporting. In amnestic MCI, the lower external locus of control associations with greater underreporting of objective cognitive difficulties suggests that perhaps reduced insight in some people with MCI may result in not realizing the need for external supports, and therefore not asking for help from others. Alternatively, in amnestic participants with greater external locus of control, perhaps the environmental cues/feedback translate to greater accuracy in their memory self-perceptions. Longitudinal analyses are needed to determine how memory self-awareness is related to future cognitive declines.

Choosing an appropriate electronic data capture system (EDC) is a critical decision for all randomized controlled trials (RCT). In this paper, we document our process for developing and implementing an EDC for a multisite RCT evaluating the efficacy and implementation of an enhanced primary care model for individuals with opioid use disorder who are returning to the community from incarceration.

Informed by the Knowledge-to-Action conceptual framework and user-centered design principles, we used Claris Filemaker software to design and implement CRICIT, a novel EDC that could meet the varied needs of the many stakeholders involved in our study.

CRICIT was deployed in May 2021 and has been continuously iterated and adapted since. CRICIT’s features include extensive participant tracking capabilities, site-specific adaptability, integrated randomization protocols, and the ability to generate both site-specific and study-wide summary reports.

CRICIT is highly customizable, adaptable, and secure. Its implementation has enhanced the quality of the study’s data, increased fidelity to a complicated research protocol, and reduced research staff’s administrative burden. CRICIT and similar systems have the potential to streamline research activities and contribute to the efficient collection and utilization of clinical research data.

RCHIS is an Electronic Medical Record (EMR) and Health Information System (HIS) that has been purpose-built for use by Red Cross Red Crescent (RCRC) Emergency Response Units (ERUs), which are the equivalent of Type 1 (fixed and mobile) and Type 2 facilities in the Emergency Medical Teams (EMT) classification.

A three day in-person super user training was held with 13 participants: 9 first aid volunteers, 2 nurses and 2 medical doctors. Seven of the delegates had experience using an EMR. These super users served as trainers for staff at the pilot.

The pilot occurred with the Portuguese Red Cross (PRC) for the Peregrinação de Fátima, where 200,000 people were in attendance. The PRC was part of a wider coordination cell with the civil defense authority, who required live reporting from the three Type 1 fixed clinics PRC had set up.

In total there were 77 user accounts, of which, 243 patients were consulted with and either discharged or referred throughout the four day pilot.

The delegates shared feedback directly and through a survey. 88% stated that RCHIS was ‘very easy’ to use with the majority of delegates requiring less than 20 minutes of training to be using the application and inputting patient data related to their user role. Additionally, after their training 95% of delegates stated they had sufficient training to use RCHIS to its full extent. Informal feedback from delegates was hugely positive, indicating that it was improving patient care and also continuity of care when a patient returned the next day.

The civil defense authorities were able to utilize the real-time reporting to assist in their operational response. The application was well received by the wider civil defense authority.

The first RCHIS pilot was very successful from both a technical and organizational perspective.

Standardization of data collection and reporting within EMT’s is challenging. In past deployments, the Red Cross Red Crescent Type one and two facilities (Emergency Response Units- ERU’s) have collected data by hand using paper-based form and Excel spreadsheets. This process can be laborious, time consuming and often inaccurate.

RCHIS is both an electronic medical record (EMR) and health information system (HIS). RCHIS has been designed to produce pre-made reports including the MDS in seconds extracting data from the patient records. Through significant testing and pilot deployments in a domestic type one fixed clinic, the rapid production of reports such as the MDS has increased compliance and accuracy with reporting.

The utilization of an EMR and integrated HIS system for increasing compliance and accuracy with the MDS has been hugely successful. An in-depth analysis of the export data was done to confirm the 100% accuracy within the MDS report.

Furthermore, feedback from users and managers within the ERU’s expressed the excitement for the ease of reporting not only to the EMTCC, but also to IFRC and back-donors. Moving forwards, this data collection will also be used to collect essential data to audit and improve the quality of care provided within the RCRC ERU’s.

In conclusion, the utilization of RCHIS within a domestic ERU (equivalent to an EMT type one or two) has been hugely successful. The next steps will involve the deployment of RCHIS within an international deployment.

Standardization of data collection and reporting within EMTs is challenging. In past deployments, the Red Cross Red Crescent Type 1 and Type 2 facilities have collected data by hand using paper-based form and Excel spreadsheets. This process can be laborious, time-consuming, and often inaccurate.

To combat this issue with reporting, RCHIS (Red Cross Red Crescent Health Information System) has been designed to ensure that reporting is accurate and also very easy to complete, increasing compliance with the EMT-MDS reporting.

RCHIS is both an electronic medical record (EMR) and health information system (HIS). RCHIS has been designed to produce pre-made reports including the MDS in seconds, extracting data from the patient records. Through significant testing and pilot deployments in a domestic Type 1 fixed clinic, the rapid production of reports such as the MDS has increased compliance and accuracy with reporting.

Overall, the utilization of an electronic medical system for increasing compliance and accuracy with the MDS has been hugely successful. An in-depth analysis of the export data was done to confirm the 100% accuracy within the MDS report.

The utilization of RCHIS within a domestic ERU (equivalent to an EMT Type 1 or Type 2) has been hugely successful. The next steps will involve the deployment of RCHIS within an international deployment.

RCHIS is an Electronic Medical Record (EMR) and Health Information System (HIS) that has been purpose built for use by Red Cross Red Crescent (RCRC) Emergency Response Units (ERUs), which are the equivalent of Type 1 (fixed and mobile) and Type 2 facilities in the Emergency Medical Teams (EMT) classification.

To share the main lessons learned from the pilot to inform development and implementation of similar systems in other EMTs.

A three-day, in-person super user training was held with 13 participants: nine first aid volunteers, two nurses, and two medical doctors; seven delegates had experience using an EMR. These super users served as trainers for staff at the pilot.

The pilot occurred with the Portuguese Red Cross (PRC) for the Peregrinação de Fátima, where 200,000 people were in attendance. The PRC was part of a wider coordination cell with the civil defense authority, who required live reporting from the three clinics PRC had set up.

77 user accounts and 243 patient files were created during the four-day pilot.

The delegates shared feedback directly and through a survey. 88% stated that RCHIS was very easy to use with the majority of delegates requiring less than 30 minutes of training. 95% of delegates stated that they had sufficient training to use RCHIS to its full extent.

The civil defense authority was able to utilize the real-time reporting to assist in their operational response.

The first RCHIS pilot was very successful from both a technical and organizational perspective.

Effective incident management is essential for coordinating efforts of multiple disciplines and stakeholders when responding to emergencies, including public health disasters such as the ongoing coronavirus disease 2019 (COVID-19) pandemic.

Existing research frameworks tend to focus on formal structures and doctrine (eg, ICS-NIMS); however, organizational processes that underlie incident management have not been systematically assessed and synthesized into a coherent conceptual framework.

The lack of a framework has hindered the development of measures of performance that could be used to further develop the evidence base and facilitate process improvement. To address this gap, we present a conceptual framework of incident management drawn from expert feedback and a review of literature on incident management and related fields. The framework features 23 measurement constructs grouped into 5 domains: (1) situational awareness and information sharing, (2) incident action and implementation planning, (3) resource management and mobilization, (4) coordination and collaboration, and (5) feedback and continuous quality improvement.

As such, the article provides a first step toward the development of robust measures for assessing the performance and effectiveness of incident management systems.

Automated virtual reality therapies are being developed to increase access to psychological interventions. We assessed the experience with one such therapy of patients diagnosed with psychosis, including satisfaction, side effects, and positive experiences of access to the technology. We tested whether side effects affected therapy.

In a clinical trial 122 patients diagnosed with psychosis completed baseline measures of psychiatric symptoms, received gameChange VR therapy, and then completed a satisfaction questionnaire, the Oxford-VR Side Effects Checklist, and outcome measures.

79 (65.8%) patients were very satisfied with VR therapy, 37 (30.8%) were mostly satisfied, 3 (2.5%) were indifferent/mildly dissatisfied, and 1 (0.8%) person was quite dissatisfied. The most common side effects were: difficulties concentrating because of thinking about what might be happening in the room (n = 17, 14.2%); lasting headache (n = 10, 8.3%); and the headset causing feelings of panic (n = 9, 7.4%). Side effects formed three factors: difficulties concentrating when wearing a headset, feelings of panic using VR, and worries following VR. The occurrence of side effects was not associated with number of VR sessions, therapy outcomes, or psychiatric symptoms. Difficulties concentrating in VR were associated with slightly lower satisfaction. VR therapy provision and engagement made patients feel: proud (n = 99, 81.8%); valued (n = 97, 80.2%); and optimistic (n = 96, 79.3%).

Patients with psychosis were generally very positive towards the VR therapy, valued having the opportunity to try the technology, and experienced few adverse effects. Side effects did not significantly impact VR therapy. Patient experience of VR is likely to facilitate widespread adoption.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.