Meeting the Goals of Service Learning in Pharmacy Education through Community Campus Partnerships

Healthy People 2010, published by the US Department of Health and Human Services, is a statement of health objectives for the nation to be achieved by the end of this decade. The goals are to increase quality and years of healthy life and to eliminate health disparities. In 2006, the West Virginia University School of Pharmacy began a revision to its Doctor of Pharmacy curriculum to include pharmacy practice experiences that would provide students with experience in developing disease prevention and health promotion programming in the community. Thus, the School of Pharmacy began a three-semester longitudinal service learning program which focused on advancing the objectives of Healthy People 2010 through service learning. The experiences of the School of Pharmacy service learning program from 2006 to the present are detailed

Revisiting the Role of the Amygdala in Posttraumatic Stress Disorder

Over the past 20 years, the reactivity of amygdala to emotive stimuli has been explored by emerging neuroimaging techniques in an effort to understand the role of amygdala in the pathophysiology of posttraumatic stress disorder (PTSD). A fear neurocircuitry model, whereby the amygdala is hyperactive due to poor top-down control from the anterior cingulate and ventromedial prefrontal cortices, has been supported by numerous experimental studies and meta-analyses. However, this model has not always been upheld by experimental data and clinical observations. In particular, many neuroimaging studies find that the amygdala fails to activate in response to negative stimuli in individuals with PTSD. Several technical and design issues may explain disparate results regarding amygdala reactivity in PTSD. However, biological and symptom-based factors emerge as possible mediators of amygdala function in PTSD, leading to the conclusion that symptoms of emotional disengagement and dissociation are associated with amygdala hyporeactivity, and symptoms of hypervigilance/hyperarousal and problems with fear conditioning and extinction are reflected by amygdala hyperactivity. Therefore, treatment of PTSD should take into account the nature of amygdala dysfunction in the individual to optimize treatment outcomes

Forward Thinking and Adaptability to Sustain and Advance IPECP in Healthcare Transformation Following the COVID-19 Pandemic

The proliferation of the novel SARS-CoV-2 (COVID-19) virus across the globe in 2020 produced a shared trauma internationally of unprecedented devastation, disruption, and death. At the same time, the pandemic has been a transformation catalyst accelerating the implementation and adoption of long overdue changes in healthcare education and practice, including telehealth and virtual learning. The COVID-19 pandemic has placed healthcare at a crossroads, either viewing it as a temporary situation that requires short-term solutions, or as a major disruption that presents opportunities for innovation for sustainable development and transformation. As COVID-19 transitions from pandemic to endemic, we have a unique opportunity to leverage lessons learned that can foster healthcare transformation through innovation, forward thinking, and interprofessional education and collaborative practice (IPECP). With the changing landscape of higher education and healthcare, IPECP leaders need to reflect on and implement ‘Forward Thinking and Adaptability’ and ‘Sustainability and Growth’ in their IPECP approaches and strategies to achieve the Quintuple Aim. To capitalize on this opportunity and based on a recent publication by InterprofessionalResearch Global, this paper explores and debates (from a global perspective) the impact and application of healthcare education and practice transformation on IPECP with the goal to identify best practices in integrating and sustaining IPECP and building a resilient workforce

Interprofessional Education and Collaborative Practice (IPECP) in Post-COVID Healthcare Education and Practice Transformation Era – Discussion Paper. Joint Publication by InterprofessionalResearch.Global, American Interprofessional Health Collaborative & Canadian Interprofessional Health Collaborative

In the past two years the world has experienced unprecedented devastation, disruption, and death due to the COVID-19 global Pandemic. At the same time, the Pandemic acts as a transformation catalyst that accelerated the implementation and adoption of long overdue changes in healthcare education and practice, including telehealth and virtual learning.Interprofessional collaboration during the pandemic was able to foster healthcare transformation in several ways at the policy and legislative level, such as the fast-tracking of internationally trained professions. The role and use of digital technologies in healthcare education and practice have been extended and solidified by the pandemic. Macro-level policies acknowledging the importance ofpopulation health are key for future interprofessional collaboration of stakeholders to address inequalities. Similarly, interprofessional collaboration is key to addressing the proliferation of misinformation. Interprofessional education and collaborative practice (IPECP) can be effectively utilized to combat misinformation by increasing health literacy amongst health professions and the communities they serve.Despite IPECP being an integral component of promoting patient safety, and holistic, quality care, silos continue to exist. Furthermore, implementation of the Quintuple Aim (better health, better care, better value, better work experience, and better health equity), particularly through the lens of equity, remains elusive. Going forward, the integration and sustainability of IPECP are crucial and the experience of IPECP within the context of the COVID-19 pandemic should be reflected on, researched, and evaluated to inform future global healthcare systems and the workforce to provide and achieve the Quintuple Aim; the goal ofall in healthcare.As we are emerging out of the Pandemic, we have a unique opportunity to leverage on the lessons learned from the pandemic in fostering the healthcare transformation through innovation and IPECP. To capitalize on this opportunity and in a collaborative effort, the InterprofessionalResearch.Global (IPR.Global), the American Interprofessional Health Collaborative (AIHC), and the CanadianInterprofessional Health Collaborative (CIHC) have developed this e-book as a Discussion Paper to explore and discuss (from a global perspective) the impact and application of healthcare education and practice transformation on IPECP as we emerge from the COVID Pandemic with the goal to identify best practicesto integrate and sustain IPECP. We call the interprofessional educators, practitioners, leaders, scholars, and policy makers to utilize ‘Forward Thinking and Adaptability’ and ‘Sustainability and Growth’ in their IPECP approaches and strategies, to achieve Quintuple Aim. As learned during the Pandemic, working together – across professions, institutions, nationally, and globally – is essential in emerging stronger and in transforming our healthcare education and practice

Neuroimaging-Based Classification of PTSD Using Data-Driven Computational Approaches:A Multisite Big Data Study from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality.RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60% test AUC for s-MRI, 59% for rs-fMRI and 56% for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75% AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance.CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.</p

Assessment of Brain Age in Posttraumatic Stress Disorder: Findings from the ENIGMA PTSD and Brain Age Working Groups

Background Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD. Method Adult subjects (N = 2229; 56.2% male) aged 18–69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA-PGC PTSD sites underwent T1-weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel-wise (brainageR) and region-of-interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age − chronological age) controlling for chronological age, sex, and scan site. Results BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three-way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages. Discussion Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age-related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan

Remodeling of the Cortical Structural Connectome in Posttraumatic Stress Disorder:Results from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Posttraumatic stress disorder (PTSD) is accompanied by disrupted cortical neuroanatomy. We investigated alteration in covariance of structural networks associated with PTSD in regions that demonstrate the case-control differences in cortical thickness (CT) and surface area (SA). METHODS: Neuroimaging and clinical data were aggregated from 29 research sites in >1,300 PTSD cases and >2,000 trauma-exposed controls (age 6.2-85.2 years) by the ENIGMA-PGC PTSD working group. Cortical regions in the network were rank-ordered by effect size of PTSD-related cortical differences in CT and SA. The top-n (n = 2 to 148) regions with the largest effect size for PTSD > non-PTSD formed hypertrophic networks, the largest effect size for PTSD < non-PTSD formed atrophic networks, and the smallest effect size of between-group differences formed stable networks. The mean structural covariance (SC) of a given n-region network was the average of all positive pairwise correlations and was compared to the mean SC of 5,000 randomly generated n-region networks. RESULTS: Patients with PTSD, relative to non-PTSD controls, exhibited lower mean SC in CT-based and SA-based atrophic networks. Comorbid depression, sex and age modulated covariance differences of PTSD-related structural networks. CONCLUSIONS: Covariance of structural networks based on CT and cortical SA are affected by PTSD and further modulated by comorbid depression, sex, and age. The structural covariance networks that are perturbed in PTSD comport with converging evidence from resting state functional connectivity networks and networks impacted by inflammatory processes, and stress hormones in PTSD

A Comparison of Methods to Harmonize Cortical Thickness Measurements Across Scanners and Sites

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants’ demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LME INT), (2) LME that models both site-specific random intercepts and age-related random slopes (LME INT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2–81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3–85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ 2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ 2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ 2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder:a mega-analysis by the ENIGMA-PGC PTSD workgroup

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p -FDR &lt; 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.</p

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder:a mega-analysis by the ENIGMA-PGC PTSD workgroup

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p -FDR &lt; 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.</p