National Consortium Research Articles

A Countrywide Assessment of Omani Undergraduate Nursing Students' Palliative Care Knowledge and Attitudes Towards End-of-Life Care.

Palliative care (PC) is a vital part of the responses needed to address the outcomes of cancer and other non-communicable diseases such as chronic pain, terminal illnesses, and end-of-life situations. Until today, there is a significant lack of access to PC in most developing countries, where the majority of the global population lives. Deficiencies in nurses' knowledge and attitudes exacerbate the lack of access to PC and end-of-life care (EOLC) in these countries. This study was conducted in Oman to assess undergraduate nursing students' (NS) PC knowledge and attitudes towards EOLC. A cross-sectional design was used to collect data from 276 NS in all undergraduate programs in Oman. The PC knowledge and attitude towards EOLC were measured using the PEACE-Q and FATCOD-B. The NS had a borderline level of PC knowledge but favorable attitudes towards EOLC. The NS were least knowledgeable about the philosophy of PC, delirium, side effects of opioids, cancer pain, and dyspnea. There were differences in PC knowledge and attitudes across programs. The findings highlight potential deficiencies and opportunities that can be utilized to augment future nursing human resources for PC and EOLC in Oman. We recommend a national interdisciplinary PC education and training consortium (NIPCET-C) to dialogue, develop, promote, monitor, and evaluate PC and EOLC education in Oman.

0192 Effects of emerging alcohol use on developmental trajectories of functional sleep measures in adolescents

Abstract Introduction Adolescence is characterized by developmental changes in sleep timing and architecture as well as alcohol use initiation. While the effects of acute and chronic alcohol use on sleep in adults are well-documented, much less is known in adolescents. We used longitudinal data from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) to examine how emerging alcohol use affected sleep architecture in adolescents. Methods Overnight polysomnographic recordings were made each year, for 4 years, in 94 adolescents (12–21 years at baseline, 43% female) from the NCANDA cohort. All participants were no or low (youth adjusted Cahalan score of zero) alcohol users at baseline. These data were used to examine developmental trajectories of sleep macro-architecture and sleep electroencephalographic (EEG) measures using linear mixed effect models (LMMs), considering age, sex, family history of alcohol use, body mass index, ethnicity, and alcohol use class (i.e., no-to-low, moderate or heavy) at each annual assessment. Results There were strong developmental changes in sleep macro-structure and EEG, most notably, a decrease in slow wave sleep percentage and slow wave (delta) EEG activity with advancing age (p=0.02)​. Compared to those who remained no-to-low drinkers, participants who became moderate/heavy drinkers during the follow-up period, had different sleep trajectories, especially those older at baseline at baseline, including higher slow wave activity (p = 0.04), higher REM sleep percentage (p = 0.03), poorer sleep efficiency​ (p=0.003), and longer latency to sustained sleep (p = 0.03). The effects of alcohol use depended on sex, with male heavy drinkers having more REM sleep than female heavy drinkers (p = 0.04). Overall, a positive family history of alcohol use was associated with less NREM sleep and shorter sleep duration. Conclusion Our results present novel findings showing that emerging alcohol use during adolescence exerts complex effects on sleep macro- and micro-structure, over and above normal developmental changes in sleep. These effects could, in part, be alcohol effects on brain maturation processes underlying sleep regulation. Support (If Any) AA021696, AA021690

A Scalable Service to Improve Health Care Quality Through Precision Audit and Feedback: Proposal for a Randomized Controlled Trial.

BackgroundHealth care delivery organizations lack evidence-based strategies for using quality measurement data to improve performance. Audit and feedback (A&F), the delivery of clinical performance summaries to providers, demonstrates the potential for large effects on clinical practice but is currently implemented as a blunt one size fits most intervention. Each provider in a care setting typically receives a performance summary of identical metrics in a common format despite the growing recognition that precisionizing interventions hold significant promise in improving their impact. A precision approach to A&F prioritizes the display of information in a single metric that, for each recipient, carries the highest value for performance improvement, such as when the metric’s level drops below a peer benchmark or minimum standard for the first time, thereby revealing an actionable performance gap. Furthermore, precision A&F uses an optimal message format (including framing and visual displays) based on what is known about the recipient and the intended gist meaning being communicated to improve message interpretation while reducing the cognitive processing burden. Well-established psychological principles, frameworks, and theories form a feedback intervention knowledge base to achieve precision A&F. From an informatics perspective, precision A&F requires a knowledge-based system that enables mass customization by representing knowledge configurable at the group and individual levels.ObjectiveThis study aims to implement and evaluate a demonstration system for precision A&F in anesthesia care and to assess the effect of precision feedback emails on care quality and outcomes in a national quality improvement consortium.MethodsWe propose to achieve our aims by conducting 3 studies: a requirements analysis and preferences elicitation study using human-centered design and conjoint analysis methods, a software service development and implementation study, and a cluster randomized controlled trial of a precision A&F service with a concurrent process evaluation. This study will be conducted with the Multicenter Perioperative Outcomes Group, a national anesthesia quality improvement consortium with >60 member hospitals in >20 US states. This study will extend the Multicenter Perioperative Outcomes Group quality improvement infrastructure by using existing data and performance measurement processes.ResultsThe proposal was funded in September 2021 with a 4-year timeline. Data collection for Aim 1 began in March 2022. We plan for a 24-month trial timeline, with the intervention period of the trial beginning in March 2024.ConclusionsThe proposed aims will collectively demonstrate a precision feedback service developed using an open-source technical infrastructure for computable knowledge management. By implementing and evaluating a demonstration system for precision feedback, we create the potential to observe the conditions under which feedback interventions are effective.International Registered Report Identifier (IRRID)PRR1-10.2196/34990

A Longitudinal Examination of Alcohol-Related Blackouts as a Predictor of Changes in Learning, Memory, and Executive Function in Adolescents.

IntroductionIn adolescents, the relationship between alcohol-related blackouts (ARBs) and distinct cognitive changes lasting beyond intoxication is unclear. We examined ARBs as a predictor of persistent changes in the development of learning, memory, and executive function in participants from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study.MethodsDescriptive analyses of the NCANDA sample (N = 831, 50.9% female, 12–21 years at baseline) identified ARB patterns within participants with an ARB history (n = 106). Latent growth curve modeling evaluated ARB-related performance changes on four neuropsychological measures across five years, excluding baseline data to reduce the magnitude of practice effects over time (n = 790). Measures included the Penn Conditional Exclusion Test (PCET), Penn Letter N-back Test (PLBT), Penn Facial Memory Test immediate (PFMTi), and delayed (PFMTd) recognition trials, and the Rey Complex Figure Test copy (RCFTc), immediate recall (RCFTi), and delayed recall (RCFTd) trials. Multivariate models were fit for raw accuracy scores from each measure, with ARB history (i.e., presence of past-year ARBs) as the main independent variable. Age, sex, race, socioeconomic status, assessment site, and alcohol use (i.e., past-year frequency) were included as covariates. Interaction effects between ARB history and alcohol use frequency were tested.ResultsBy year five, 16% of participants had experienced at least one ARB (59% of whom reported > 1 ARB and 57% of whom had an ARB lasting > 1 h). After controlling for demographics and alcohol use, ARB history predicted attenuated PFMTd performance growth at year one. Interaction effects between ARB history and alcohol use frequency predicted attenuated PFMTd performance growth at years one and two. ARB history predicted attenuated RCFTi and RCFTd performance growth by year four, but not PCET or PLBT performance over time. By contrast, greater past-year alcohol use predicted attenuated PFMTi and PFMTd performance growth between years two and four in adolescents without an ARB history.ConclusionWe found that ARBs predict distinct, lasting changes in learning and memory for visual information, with results suggesting that the developing brain is vulnerable to ARBs during adolescence and emerging adulthood.

Self-reported sleep and circadian characteristics predict alcohol and cannabis use: A longitudinal analysis of the National Consortium on Alcohol and Neurodevelopment in Adolescence Study.

Growing evidence indicates that sleep characteristics predict future substance use and related problems. However, most prior studies assessed a limited range of sleep characteristics, studied a narrow age span, and included few follow-up assessments. Here, we used six annual assessments from the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) study, which spans adolescence and young adulthood with an accelerated longitudinal design, to examine whether multiple sleep characteristics in any year predict alcohol and cannabis use the following year. The sample included 831 NCANDA participants (423 females; baseline age 12-21years). Sleep variables included circadian preference, sleep quality, daytime sleepiness, the timing of midsleep (weekday/weekend), and sleep duration (weekday/weekend). Using generalized linear mixed models (logistic for cannabis; ordinal for binge severity), we tested whether each repeatedly measured sleep characteristic (years 0-4) predicted substance use (alcohol binge severity or cannabis use) the following year (years 1-5), covarying for age, sex, race, visit, parental education, and previous year's substance use. Greater eveningness, more daytime sleepiness, later weekend sleep timing, and shorter sleep duration (weekday/weekend) all predicted more severe alcohol binge drinking the following year. Only greater eveningness predicted a greater likelihood of any cannabis use the following year. Post-hoc stratified exploratory analyses indicated that some associations (e.g., greater eveningness and shorter weekend sleep duration) predicted binge severity only in female participants, and that middle/high school versus post-high school adolescents were more vulnerable to sleep-related risk for cannabis use. Our findings support the relevance of multiple sleep/circadian characteristics in the risk for future alcohol binge severity and cannabis use. Preliminary findings suggest that these risk factors vary based on developmental stage and sex. Results underscore a need for greater attention to sleep/circadian characteristics as potential risk factors for substance use in youth and may inform new avenues to prevention and intervention.

Advancing the Surgical Treatment of Intracerebral Hemorrhage: Study Design and Research Directions

In this narrative review, we discuss aspects of study design for research in the surgical treatment of patients with spontaneous acute intracerebral hemorrhage (ICH). We emphasize the importance of carefully defining the primary end point relevant to the intervention under investigation, whether this is technical (i.e., residual hematoma volume) or clinical (i.e., mortality or functional outcome), and the timing of its assessment. Compared with patients with acute ischemic stroke, patients with spontaneous acute ICH may take longer to fully recover. Efficient patient recruitment is essential for all research studies and deferred consent is an option to allow disabled and critically ill patients to be included. Although central concealment of the randomization process, often with a method of stratification to ensure that prognostic variables are balanced between groups, it is often appropriate to undertake analysis of the treatment effect adjusted for various predefined covariables. The definition of minimally invasive surgery, and its use and timing in relation to ICH, requires urgent assessment. Future studies could be better designed and executed as part of a large (inter)national ICH trials consortium, consisting of dedicated interdisciplinary teams of neurologists, neurosurgeons, intensivists, and epidemiologists. We advocate studies to be pragmatic and adhere to the IDEAL recommendations and CONSORT guidelines.

Quantitative MRI Harmonization to Maximize Clinical Impact: The RIN-Neuroimaging Network.

Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures.

Post-COVID recovery and renewal through whole-of-society resilience in cities

This paper explores and extends understanding of the role and significance of whole-of-society resilience programmes that support cities when dealing with complex crises, like the COVID-19 pandemic. Highlighting the complexity of whole-of-society resilience as different actors locally shape it, we ask the question: How can collaboration between formal and informal resilience practices help to enhance resilience across the ‘whole-of-society’? We answer this question by reviewing the importance of whole-of-society resilience and its complexity in a city’s governance of the COVID-19 crisis. We argue that the necessity of renewing approaches to building local resilience capabilities across the whole-of-society requires synchronisation across and between formal and informal approaches – that is, “bottom-up” and governmental initiatives – to meet the diverse needs of communities. Secondly, we detail two recent practice-orientated initiatives that have taken a renewal approach to building resilience through the involvement of whole-of-society in planning recovery from COVID-19 using international standard ISO/TS 22393; and a new initiative called the National Consortium for Societal Resilience [UK+]. Finally, we signpost a set of critical questions for whole-of-society resilience practice.

Did the acute impact of the COVID-19 pandemic on drinking or nicotine use persist? Evidence from a cohort of emerging adults followed for up to nine years

ObjectiveThis study examined the impact of the COVID-19 pandemic on drinking and nicotine use through June of 2021 in a community-based sample of young adults. MethodData were from 348 individuals (49% female) enrolled in a long-term longitudinal study with an accelerated longitudinal design: the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) Study. Individuals completed pre-pandemic assessments biannually from 2016 to early 2020, then completed up to three web-based, during-pandemic surveys in June 2020, December 2020, and June 2021. Assessments when individuals were 18.8–22.4 years old (N = 1,458) were used to compare drinking and nicotine use pre-pandemic vs. at each of the three during-pandemic timepoints, adjusting for the age-related increases expected over time. ResultsCompared to pre-pandemic, participants were less likely to report past-month drinking in June or December 2020, but there was an increase in drinking days among drinkers in June 2020. By June 2021, both the prevalence of past-month drinking and number of drinking days among drinks were similar to pre-pandemic levels. On average, there were no statistically significant differences between pre-pandemic and during-pandemic time points for binge drinking, typical drinking quantity, or nicotine use. Young adults who reported an adverse financial impact of the pandemic showed increased nicotine use while their peers showed stable or decreased nicotine use. ConclusionInitial effects of the pandemic on alcohol use faded by June 2021, and on average there was little effect of the pandemic on nicotine use.

Communicating With Breast Imaging Patients During the COVID-19 Pandemic: Impact on Patient Care and Physician Wellness.

ObjectiveAssess the impact of COVID-19 on patient-breast radiologist interactions and evaluate the relationship between safety measure–constrained communication and physician wellbeing.MethodsA 41-question survey on the perceived effect of COVID-19 on patient care was distributed from June 2020 to September 2020 to members of the Society of Breast Imaging and the National Consortium of Breast Centers. Non-radiologists and international members were excluded. Anxiety and psychological distress scores were calculated. A multivariable logistic model was used to identify demographic and mental health factors associated with responses.ResultsFive hundred twenty-five surveys met inclusion criteria (23% response rate). Diminished ability to fulfill patients’ emotional needs was reported by 46% (221/479), a response associated with younger age (OR, 0.8 per decade; P < 0.01), higher anxiety (OR, 2.3; P < 0.01), and higher psychological distress (OR, 2.2; P = 0.04). Personal protective equipment made patient communication more difficult for 88% (422/478), a response associated with younger age (OR, 0.8 per decade; P = 0.008), female gender (OR, 1.9; P < 0.01), and greater anxiety (OR, 2.6; P = 0.001). The inability to provide the same level of care as prior to COVID-19 was reported by 37% (177/481) and was associated with greater anxiety (OR, 3.4; P < 0.001) and psychological distress (OR, 1.7; P = 0.03).ConclusionThe majority of breast radiologists reported that COVID-19 has had a negative impact on patient care. This perception was more likely among younger radiologists and those with higher levels of anxiety and psychological distress.

Matching Access to Need: New Perspective on Nurse Practitioner Residency Programs

Although nurse practitioner (NP) residency and fellowship programs constitute a new phenomenon in the area of postgraduate nurse education training, the concept of postgraduate training for NPs has been evolving for over a decade. Since the inception of the first program begun by Margaret Flinter at Community Health Center in 2007, over 100 programs in a variety of specialty and primary care settings have been developed and continue to thrive.1 In addition, the establishment of a nationally recognized accreditation body for postgraduate NP education, the national Nurse Practitioner Residency and Fellowship Training Consortium, continues to encourage the expansion of existing programs and the development of new programs (https://www.nppostgradtraining.com/about-us/).

A semi-parametric Bayesian model for semi-continuous longitudinal data.

Semi-continuous data present challenges in both model fitting and interpretation. Parametric distributions may be inappropriate for extreme long right tails of the data. Mean effects of covariates, susceptible to extreme values, may fail to capture relevant information for most of the sample. We propose a two-component semi-parametric Bayesian mixture model, with the discrete component captured by a probability mass (typically at zero) and the continuous component of the density modeled by a mixture of B-spline densities that can be flexibly fit to any data distribution. The model includes random effects of subjects to allow for application to longitudinal data. We specify prior distributions on parameters and perform model inference using a Markov chain Monte Carlo (MCMC) Gibbs-sampling algorithm programmed in R. Statistical inference can be made for multiple quantiles of the covariate effects simultaneously providing a comprehensive view. Various MCMC sampling techniques are used to facilitate convergence. We demonstrate the performance and the interpretability of the model via simulations and analyses on the National Consortium on Alcohol and Neurodevelopment in Adolescence study (NCANDA) data on alcohol binge drinking.

Breast Cancer Management During the COVID-19 Pandemic: the Radiation Oncology Perspective.

Purpose of ReviewThe coronavirus disease 19 (COVID-19) pandemic has caused disruption in healthcare throughout the world. The limitations placed on hospital resources and the need to limit potential exposure to SARS-CoV-2 for both patients and healthcare staff have affected oncologic care for patients with breast cancer (BC), including radiation therapy (RT). This review highlights published guidelines regarding the provision of radiotherapy for BC patients and their adoption by radiation oncology centers.Recent FindingsMultiple international and national consortiums plus select institutions have published formal recommendations regarding radiation therapy for BC during the COVID-19 pandemic. They embody the principles of limiting in-person visits, proper triage, and the judicious use of delay, abbreviation, or omission of RT as appropriate.SummarySince the start of the pandemic, multiple publications have provided guidance regarding RT for BC during this challenging time. The pandemic has led to increased use of telemedicine and abbreviated radiation therapy courses in the setting of BC, which are likely to persist. Future research is needed to establish the effect of these changes on oncologic outcomes.

A217 TREATMENT ADHERENCE OF CHRONIC HEPATITIS B PATIENTS WITH HEPATOCELLULAR CARCINOMA FROM THE CANHEPB NETWORK

BackgroundChronic hepatitis B (CHB) is the most common cause of hepatocellular carcinoma (HCC) worldwide.AimsThe primary aim of this study is to explore the degree of treatment adherence to the American Association For The Study of Liver Disease (AASLD) HCC treatment guidelines for patients with CHB-HCC.MethodsThis is a retrospective, cross-sectional study of available data (2005–2020) in patients mono-infected with CHB collected from the Canadian HBV Network; a national consortium across 8 Canadian provinces. We analyzed data using descriptive statistics along with parametric and nonparametric statistical methods with a significance level of p < 0.05.ResultsOf the 6500 patients, 132 (2.0%) patients met inclusion criteria. The median age was 64 (IQR: 53.5- 71.5) with 101 (76%) being male. The median ALT was 40 (IQR: 26–59.5) and the median tumor number was 1(IQR: 1- 2) with a median tumor size of 2.6 cm (IQR: 1.9- 4.5). 98 (74.5%) patients were HBeAg negative with a median viral load of 3.8 logs (IQR 1.9 – 5.8). 58 (43%) patients had cirrhosis at diagnosis. 36% of patients were diagnosed with HCC on their first screening imaging whereas 39% were found to have HCC on repeated surveillance imaging. 116 (87.9%) were on treatment at the time of diagnosis or after (70 (60.3%) NA and 46 (39%) Combination therapy with double NA or NA plus interferon). Out of the 132 patients, BCLC stage 0, A, B, and C represented 30 (23%), 42 (32%), 17 (13%), and 5 (4%) patients, respectively, with 38 (28%) patients with unknown BCLC stage. The overall adherence to AASLD guidelines was 61%. The HCC treatment adherence rate for patients with BCLC stage 0, A, B were 63%, 97.5%, and 23.5%, respectively. BCLC stages C and D did not have a sufficient sample size for analysis. The adherence rate ranged from 53% (Eastern Canada) to 71% (Western Canada) across Canada.ConclusionsIn this retrospective nationwide cohort study of patients with CHB-related HCC, the overall treatment adherence rate to AASLD guidelines was low with notable regional differences. Further analysis will determine the cause of regional differences.Funding AgenciesNone

CIBERER: Spanish national network for research on rare diseases: A highly productive collaborative initiative.

CIBER (Center for Biomedical Network Research; Centro de Investigación Biomédica En Red) is a public national consortium created in 2006 under the umbrella of the Spanish National Institute of Health Carlos III (ISCIII). This innovative research structure comprises 11 different specific areas dedicated to the main public health priorities in the National Health System. CIBERER, the thematic area of CIBER focused on rare diseases (RDs) currently consists of 75 research groups belonging to universities, research centers, and hospitals of the entire country. CIBERER's mission is to be a center prioritizing and favoring collaboration and cooperation between biomedical and clinical research groups, with special emphasis on the aspects of genetic, molecular, biochemical, and cellular research of RDs. This research is the basis for providing new tools for the diagnosis and therapy of low‐prevalence diseases, in line with the International Rare Diseases Research Consortium (IRDiRC) objectives, thus favoring translational research between the scientific environment of the laboratory and the clinical setting of health centers. In this article, we intend to review CIBERER's 15‐year journey and summarize the main results obtained in terms of internationalization, scientific production, contributions toward the discovery of new therapies and novel genes associated to diseases, cooperation with patients' associations and many other topics related to RD research.

History, Development, and Enlightenment of Adapted Physical Education National Standards

As the total number and proportion of individuals with disabilities worldwide are increasing, the international community is paying more and more attention to the equal education rights of individuals with disabilities. Since the Individuals with Disabilities Education Act issued in 1975, physical education (PE) played a significant part in special education. According to the requirements of the United States federal legislation, a national certification examination system has been established and developed subsequently to better promote the development of physical education for children with disabilities. The National Consortium for Physical Education for Individuals with Disabilities (NCPEID) has formulated the Adapted Physical Education National Standards (APENS). The first version of APENS was developed in 1995 to certify adaptive sports professionals across the United States. The second edition came out in 2006. In addition, many undergraduate and graduate teacher education programs use APENS as a basis for preparatory courses. At some universities, completion of APENS has become a graduation requirement. The NCPEID reviews APENS every few years to keep it up to date, and it also reviews national tests as needed to reflect current knowledge and practice. This paper was to understand the primary contents of APENS. We found that the APENS include Human Development, Motor Behavior, Exercise Science, Measurement and Evaluation, History and Philosophy, Unique Attributes of Learners, Curriculum Theory and Development, Instructional Design and Planning, Teaching, Consultation and Staff Development, Student and Program Evaluation, Continuing Education, Ethics and Communication. These standard fields guide teachers, administrators, and families in basic knowledge, skills, and attitudes. In addition, the establishment of APENS has reference value and significance for the system construction, legal regulations, discipline construction, personnel training, peer education, community support, and other aspects of PE for individuals with disabilities in China.

Intensive Perinatal Mental Health Programs in the United States: A Call to Action.

Despite the growth of intensive perinatal mental health programs in the United States, too few programs serve women with perinatal mood and anxiety disorders (PMADs). Furthermore, little is known about program operations, services, the women served, and the methods of collecting outcome data. With this Open Forum, the authors aimed to share their investigation of intensive perinatal mental health programs in the United States and offer recommendations to improve services for women with PMADs. The authors recommend forming a national consortium that can foster collaboration to expand existing services and establish a national database to inform program development, evaluation, policies, and funding.

Developmental trajectories of Big Five personality traits among adolescents and young adults: Differences by sex, alcohol use, and marijuana use.

Individual differences in adolescent personality are related to a variety of long-term health outcomes. While previous studies have demonstrated sex differences and non-linear changes in personality development, these results remain equivocal. The current study utilized longitudinal data (n=831) from the National Consortium on Alcohol and Neurodevelopment in Adolescence to examine sex differences in the development of personality and the association between substance use and personality. Participants (ages 12-21 at baseline) completed the Ten-Item Personality Inventory and self-reported past year alcohol and marijuana use at up to 7 yearly visits. Data were analyzed using generalized additive mixed-effects models and linear mixed-effects models. Findings support linear increases in agreeableness and conscientious and decreases in openness with age and inform on timing of sex-specific non-linear development of extraversion and emotional stability. Further, results provide novel information regarding the timing of the association between substance use and personality, and replicate past reporting of differential associations between alcohol and marijuana use and extraversion, and sex-dependent effects of marijuana use on emotional stability. These findings highlight the importance of modeling sex differences in personality development using flexible non-linear modeling strategies, and accounting for sex- and age-specific effects of alcohol and marijuana use.

Multiple Instance Neuroimage Transformer.

For the first time, we propose using a multiple instance learning based convolution-free transformer model, called Multiple Instance Neuroimage Transformer (MINiT), for the classification of T1-weighted (T1w) MRIs. We first present several variants of transformer models adopted for neuroimages. These models extract non-overlapping 3D blocks from the input volume and perform multi-headed self-attention on a sequence of their linear projections. MINiT, on the other hand, treats each of the non-overlapping 3D blocks of the input MRI as its own instance, splitting it further into non-overlapping 3D patches, on which multi-headed self-attention is computed. As a proof-of-concept, we evaluate the efficacy of our model by training it to identify sex from T1w-MRIs of two public datasets: Adolescent Brain Cognitive Development (ABCD) and the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA). The learned attention maps highlight voxels contributing to identifying sex differences in brain morphometry. The code is available at https://github.com/singlaayush/MINIT.

Joint Graph Convolution for Analyzing Brain Structural and Functional Connectome.

The white-matter (micro-)structural architecture of the brain promotes synchrony among neuronal populations, giving rise to richly patterned functional connections. A fundamental problem for systems neuroscience is determining the best way to relate structural and functional networks quantified by diffusion tensor imaging and resting-state functional MRI. As one of the state-of-the-art approaches for network analysis, graph convolutional networks (GCN) have been separately used to analyze functional and structural networks, but have not been applied to explore inter-network relationships. In this work, we propose to couple the two networks of an individual by adding inter-network edges between corresponding brain regions, so that the joint structure-function graph can be directly analyzed by a single GCN. The weights of inter-network edges are learnable, reflecting non-uniform structure-function coupling strength across the brain. We apply our Joint-GCN to predict age and sex of 662 participants from the public dataset of the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) based on their functional and micro-structural white-matter networks. Our results support that the proposed Joint-GCN outperforms existing multi-modal graph learning approaches for analyzing structural and functional networks.