Intimate partner violence, substance use, and health comorbidities among women: A narrative review

Exposure to intimate partner violence (IPV), including physical, sexual, and psychological violence, aggression, and/or stalking, impacts overall health and can have lasting mental and physical health consequences. Substance misuse is common among individuals exposed to IPV, and IPV-exposed women (IPV-EW) are at-risk for transitioning from substance misuse to substance use disorder (SUD) and demonstrate greater SUD symptom severity; this too can have lasting mental and physical health consequences. Moreover, brain injury is highly prevalent in IPV-EW and is also associated with risk of substance misuse and SUD. Substance misuse, mental health diagnoses, and brain injury, which are highly comorbid, can increase risk of revictimization. Determining the interaction between these factors on the health outcomes and quality of life of IPV-EW remains a critical need. This narrative review uses a multidisciplinary perspective to foster further discussion and research in this area by examining how substance use patterns can cloud identification of and treatment for brain injury and IPV. We draw on past research and the knowledge of our multidisciplinary team of researchers to provide recommendations to facilitate access to resources and treatment strategies and highlight intervention strategies capable of addressing the varied and complex needs of IPV-EW

A global collaboration to study intimate partner violence-related head trauma: The ENIGMA consortium IPV working group

Intimate partner violence includes psychological aggression, physical violence, sexual violence, and stalking from a current or former intimate partner. Past research suggests that exposure to intimate partner violence can impact cognitive and psychological functioning, as well as neurological outcomes. These seem to be compounded in those who suffer a brain injury as a result of trauma to the head, neck or body due to physical and/or sexual violence. However, our understanding of the neurobehavioral and neurobiological effects of head trauma in this population is limited due to factors including difficulty in accessing/recruiting participants, heterogeneity of samples, and premorbid and comorbid factors that impact outcomes. Thus, the goal of the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium Intimate Partner Violence Working Group is to develop a global collaboration that includes researchers, clinicians, and other key community stakeholders. Participation in the working group can include collecting harmonized data, providing data for meta- and mega-analysis across sites, or stakeholder insight on key clinical research questions, promoting safety, participant recruitment and referral to support services. Further, to facilitate the mega-analysis of data across sites within the working group, we provide suggestions for behavioral surveys, cognitive tests, neuroimaging parameters, and genetics that could be used by investigators in the early stages of study design. We anticipate that the harmonization of measures across sites within the working group prior to data collection could increase the statistical power in characterizing how intimate partner violence-related head trauma impacts long-term physical, cognitive, and psychological health

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15-90. The effects of dementia, mild cognitive impairment, Parkinson\u27s disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis.

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15–90. The effects of dementia, mild cognitive impairment, Parkinson’s disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p \u3c 0.001), while neither depression nor ADHD showed consistent associations with VLM scores (p \u3e 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders

Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis.

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15-90. The effects of dementia, mild cognitive impairment, Parkinson's disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

Prevention of mental illness within public health: An analysis of progress via systematic literature review and a pathway forward

Primary prevention is the cornerstone of public health. Prevention is especially important for chronic diseases of significant burden such as mental illnesses because many of them have limited treatment options, an onset in childhood or in adolescence, and are linked to adverse childhood experiences requiring a focus on early childhood and maternal-child health (MCH). Despite this need, there appears to be a paucity of research into prevention of mental illnesses within public health. To confirm this, we performed a systematic literature review to quantify the proportion of articles in public health that focus on prevention of mental illness versus intervention for these illnesses after their onset, and the proportion of published articles within MCH that focus on mental health. Between November 2019 and August 2021, we reviewed 211,794 published articles from 147 Scimago-ranked English public health journals with no limit on year of publication. As hypothesized, a very small portion (2.2%) of mental health articles included primary prevention and a small portion of MCH articles (7.8%) included mental health. These results are consistent with the existence of a research gap in mental illness prevention within the public health field. Given the early onset of mental illness, the importance of early childhood experiences in the later development of mental illness, and the importance of the social-emotional connection between mother and child for building resilience, public health professionals must incorporate evidence from the field of MCH to develop and assess more primary prevention programs for mental illness

Orthopaedic Surgeons Should Consider Online and E-publication Resources for the Most Current Evidence-Based Medicine Following the COVID-19 Pandemic

Purpose: To compare the time to publication of accepted manuscripts and content in orthopaedic sports medicine journals during the first 2 years of the COVID-19 pandemic. Methods: A convenience sample of articles published in January, May, and September during the years 2019−2021 was taken from Arthroscopy, American Journal of Sports Medicine (AJSM), and Knee Surgery, Sports Traumatology, Arthroscopy (KSSTA). The duration between the aspects of the article publication process was compared between journals and years. Results: Overall, 826 journal articles were included. Arthroscopy demonstrated no significant differences in the time from manuscript submission to journal publication from 2019 to 2021, a significant decrease in time from acceptance to e-Pub (140 vs 74 vs 16 days; P < .001), but an increase from e-Pub to journal publication (23 vs 74 vs 130 days; P < .001). In AJSM, there was an overall increase in time from submission to journal publication significant between 2019 and 2021 (P = .05) and 2020 and 2021 (P = .001). KSSTA demonstrated the longest timelines in 2020. There was a trend toward a greater number of systematic reviews and meta-analyses. Conclusion: Changes in various aspects of the time to publication and journal content occurred in orthopaedic sports medicine journals in the years surrounding the peak of the COVID-19 pandemic in 2020. Although it is not possible to know whether these delays are caused by journal or author-related factors, orthopaedic surgeons should be aware of the possible delay in time to publication and consider online and e-publication resources for the most current evidence-based medicine, while journals may take this information into account to consider ways of improving the publication process and when determining journal content. Clinical Relevance: It is important to understand the impact the COVID-19 pandemic had on the publications which orthopaedic sports medicine surgeons rely on for clinical knowledge and the practice of evidence-based medicine

The Study of Intimate Partner Violence-Related Head Trauma: Recommendations from the Enhancing Neuroimaging and Genetics through Meta-Analysis Consortium Intimate Partner Violence Working Group

Intimate partner violence includes psychological aggression, physical violence, sexual violence, and stalking from a current or former intimate partner. Experiencing intimate partner violence is associated with impaired neurocognitive and psychosocial functioning, mental illness, as well as structural brain alterations. These impairments seem to be compounded by exposure to physical trauma to the head. Importantly, up to 90% of women exposed to intimate partner violence also experience some form of head trauma or even repetitive head trauma. However, research on this topic is sparse, and the neurobehavioral and neurobiological effects of head trauma in this population have not been systematically investigated. A key aim of the Enhancing Neuroimaging and Genetics through Meta-Analysis Consortium Intimate Partner Violence Working Group is to provide recommendations for the harmonization of measures collected to facilitate the meta-analysis of neuropsychological, neuroimaging, and genetic data across studies. Here, we review the current literature on the impact of intimate partner violence-related head trauma in men and women. We further provide recommendations for studies examining the effects of intimate partner violence-related head trauma on neuronal, cognitive, and psychological functioning, as well as the influence of genetic variation. We anticipate that the harmonization of measures across studies will increase the statistical power in characterizing how IPV-related head trauma impacts long-term physical and psychological health, as well as in determining the influence of common comorbidities and genetic variation