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This article shares what surfaced during diffractive analysis of data from a participatory arts-engaged research project called Life Lines. Drawing on material feminism, studio-inquiry practices were designed to assist young adults in creatively speculating alongside researchers over varied conceptualizations of identity, including dominant explanations centering on cognitive development and alternative framings emphasizing materiality’s role in subjective formation. Lines as both culturally inscriptive “engines of theory” and as materially sensitive artistic inquiry practices were enlisted to open new insights about how it is for young adult bodies to sustain developmentalism’s “cruel optimism” about coherence, stability, and progression.

Mentorship is vital for early career researchers in training positions, allowing them to navigate the challenges of work and life in research environments. However, the quality of mentorship received by trainees can vary by investigator and by institution. One challenge faced by those hoping to improve trainee mentorship is that the extent to which mentorship is offered to and experienced by research trainees is not well characterized. To address this knowledge gap, we conducted a survey to examine the quality of mentorship received by trainees in research environments, to identify characteristics of positive and negative mentorship, and to highlight best practices to improve trainee mentorship. We received 2,114 responses from researchers at graduate and postdoctoral career stages worldwide. Quantitative analysis showed that at least ∼25-45% of respondents were dissatisfied with some aspects of their mentorship. Qualitative responses revealed that common issues in mentorship include unclear expectations in research and mentoring interactions, lack of guidance, and inadequate support of trainee independence and career goals. Our findings also identified key mentorship elements desired by trainee mentees. Based on trainee suggestions, we describe strategies for individual mentors, departments, and institutions to improve the training experience for graduate and postdoctoral researchers.

BackgroundIntegrating behavioural health care into primary care practices may increase patients’ access to behavioural health services and improve health outcomes. However, few studies have explored factors that influence integration processes.ObjectiveWe sought to better understand contextual factors that support or impede behavioural health integration in primary care practices.MethodsWe conducted 71 semi-structured interviews with providers, staff, and leaders from eight primary care practices in the United States with integrated behavioural health services, which were participating in a randomized control, pragmatic trial: Integrating Behavioural Health and Primary Care. Practices were selected for diversity on geographic location, size, ownership, and experience with integration. We conducted a thematic analysis of the qualitative data derived from the interviews.ResultsWe identified four categories of contextual factors influencing behavioural health integration: leadership commitment to integration, financial considerations, workflow and communication systems, and providers’ perspectives on integration and team-based healthcare. Supportive factors included leaders’ commitment to integration, adequate staffing, customized communication and workflow systems, collaborative practice culture, and healthy working relationships amongst providers. Impediments included staffing issues and payment models that do not reimburse for activities required to support integrated care.ConclusionInterviewees described various benefits of integration, including providers feeling better equipped to address patients’ needs due to collaboration between medical and behavioural providers and resulting interdisciplinary learning. Given concerns about provider burnout, this finding warrants further study.

Faculty at research institutions play a central role in advancing knowledge and careers, as well as promoting the well-being of students and colleagues in research environments. Faculty members must balance a host of activities - such as performing research, teaching, sourcing funds, administrative and service duties - with their roles as educators and mentors. Mentorship from experienced peers has been touted as critical for enabling these myriad roles to allow faculty development, career progression, and satisfaction. However, there is little information available on who supports faculty and best ways to structure a faculty mentorship program for early- and mid-career academics. Furthermore, the extent to which mentorship and mentoring programs have been offered to faculty members has not been widely characterized. It is also unclear what challenges faculty receiving mentorship may face and which aspects could be further improved. In the interest of advocating for increased and enhanced faculty mentoring and mentoring programs, we surveyed faculty (i.e., group leaders) around the world to gather data on whether and how they receive mentoring from peers, senior researchers, informal mentoring programs, or formal mentoring programs at their institutions. We received responses from 457 early- and mid-career faculty and found that a substantial portion of respondents either reported having no mentor or a lack of a formal mentoring scheme. Qualitative responses on the quality of mentorship revealed that the most common complaints regarding mentorship included lack of mentor availability, unsatisfactory commitment to mentorship, and non-specific or non-actionable advice. Our findings further identified key mentorship elements desired by faculty mentees. Based on these suggestions, we identify a need for training for faculty mentors as well as strategies for individual mentors, departments, and institutions for funding and design of more intentional and supportive mentorship programs for early- and mid-career faculty.

Background: We report 10-year follow up data from a well-established Resistant Hypertension Program. Methods and Results: Between January 2012 and December 2021, there were 976 referrals, of which 357 were excluded, due to non-adherence/no-show. Therefore, demographic and clinical data from 619 patients are summarized in Table 1. Average duration of enrollment was 8.1 months with an average of 4.3 visits. The baseline and final data are shown in Table 2. Despite no weight loss, there were significant reductions in systolic BP (150.2 to 129.5 mmHg, p< 0.05) and diastolic BP (84.8 to 76.3 mmHg, p< 0.05). Average number of antihypertensive medications increased from 1.7 to 3.4, p< 0.05). There data are very similar to those from the first year of the program. Conclusions: Ten-year data from a well-established Resistant Hypertension Program maintained significant blood pressure reductions, similar to results from the first year of program.

We aimed to evaluate whether delivering during the early the coronavirus disease 2019 (COVID-19) pandemic was associated with increased risk of maternal death or serious morbidity from common obstetric complications compared with a historical control period.This was a multicenter retrospective cohort study with manual medical-record abstraction performed by centrally trained and certified research personnel at 17 U.S. hospitals. Individuals who gave birth on randomly selected dates in 2019 (before the pandemic) and 2020 (during the pandemic) were compared. Hospital, health care system, and community risk-mitigation strategies for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in response to the early COVID-19 pandemic are described. The primary outcome was a composite of maternal death or serious morbidity from common obstetric complications, including hypertensive disorders of pregnancy (eclampsia, end organ dysfunction, or need for acute antihypertensive therapy), postpartum hemorrhage (operative intervention or receipt of 4 or more units blood products), and infections other than SARS-CoV-2 (sepsis, pelvic abscess, prolonged intravenous antibiotics, bacteremia, deep surgical site infection). The major secondary outcome was cesarean birth.Overall, 12,133 patients giving birth during and 9,709 before the pandemic were included. Hospital, health care system, and community SARS-CoV-2 mitigation strategies were employed at all sites for a portion of 2020, with a peak in modifications from March to June 2020. Of patients delivering during the pandemic, 3% had a positive SARS-CoV-2 test result during pregnancy through 42 days postpartum. Giving birth during the pandemic was not associated with a change in the frequency of the primary composite outcome (9.3% vs 8.9%, adjusted relative risk [aRR] 1.02, 95% CI 0.93-1.11) or cesarean birth (32.4% vs 31.3%, aRR 1.02, 95% CI 0.97-1.07). No maternal deaths were observed.Despite substantial hospital, health care, and community modifications, giving birth during the early COVID-19 pandemic was not associated with higher rates of serious maternal morbidity from common obstetric complications.ClinicalTrials.gov, NCT04519502.

A central challenge of medical imaging studies is to extract quantitative biomarkers that characterize pathology or predict disease outcomes. In high-resolution, high-quality magnetic resonance images (MRI), state-of-the-art approaches have performed well. However, such methods may not translate to low resolution, lower quality images acquired on MRI scanners with lower magnetic field strength. Therefore, in low-resource settings where low field scanners are more common and there is a shortage of available radiologists to manually interpret MRI scans, it is essential to develop automated methods that can accommodate lower quality images and augment or replace manual interpretation. Motivated by a project in which a cohort of children with cerebral malaria were imaged using 0.35 Tesla MRI to evaluate the degree of diffuse brain swelling, we introduce a fully automated framework to translate radiological diagnostic criteria into image-based biomarkers. We integrate multi-atlas label fusion, which leverages high-resolution images from another sample as prior spatial information, with parametric Gaussian hidden Markov models based on image intensities, to create a robust method for determining ventricular cerebrospinal fluid volume. We further propose normalized image intensity and texture measurements to determine the loss of gray-to-white matter tissue differentiation and sulcal effacement. These integrated biomarkers are found to have excellent classification performance for determining severe cerebral edema due to cerebral malaria.

BACKGROUND Early, intense rehabilitation is essential to promote recovery after stroke, spinal cord injury (SCI), and traumatic brain injury (TBI). However, intensity of usual care rehabilitation interventions during inpatient rehabilitation are poorly characterized. OBJECTIVE To describe the intensity of usual care rehabilitation interventions completed during the subacute phase of recovery from neurologic injury. DESIGN Observational. SETTING Inpatient rehabilitation facility. INTERVENTIONS Twenty-two usual care physical therapy interventions were grouped into six categories: gait (four activities), functional (two), strengthening (four), aerobic (six), balance (four), and wheelchair (two). PATIENTS Patients admitted to inpatient rehabilitation with a primary diagnosis of stroke, SCI or TBI within 6 months of injury. MAIN OUTCOME MEASURE(S) Cardiovascular intensity (physiological and perceived) was recorded during rehabilitation activity sessions. Physiological intensity was assessed by heart rate reserve (HRR) via a Polar A370 Fitness Watch and characterized as very light (

Pregnant patients with severe or critical coronavirus disease 2019 (COVID-19), but not those with mild or moderate COVID-19, were at increased risk for perinatal complications compared with asymptomatic patients., OBJECTIVE: To describe coronavirus disease 2019 (COVID-19) severity in pregnant patients and evaluate the association between disease severity and perinatal outcomes. METHODS: We conducted an observational cohort study of all pregnant patients with a singleton gestation and a positive test result for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) who delivered at 1 of 33 U.S. hospitals in 14 states from March 1 to July 31, 2020. Disease severity was classified by National Institutes of Health criteria. Maternal, fetal, and neonatal outcomes were abstracted by centrally trained and certified perinatal research staff. We evaluated trends in maternal characteristics and outcomes across COVID-19 severity classes and associations between severity and outcomes by multivariable modeling. RESULTS: A total of 1,219 patients were included: 47% asymptomatic, 27% mild, 14% moderate, 8% severe, 4% critical. Overall, 53% were Hispanic; there was no trend in race–ethnicity distribution by disease severity. Those with more severe illness had older mean age, higher median body mass index, and pre-existing medical comorbidities. Four maternal deaths (0.3%) were attributed to COVID-19. Frequency of perinatal death or a positive neonatal SARS-CoV-2 test result did not differ by severity. Adverse perinatal outcomes were more frequent among patients with more severe illness, including 6% (95% CI 2–11%) incidence of venous thromboembolism among those with severe–critical illness compared with 0.2% in mild–moderate and 0% in asymptomatic (P

SARS-CoV-2 infection during pregnancy is associated with adverse pregnancy outcomes, including fetal death and preterm birth. It is not known whether that risk occurs only during the time of acute infection or whether the risk persists later in pregnancy.This study aimed to evaluate whether the risk of SARS-CoV-2 infection during pregnancy persists after an acute maternal illness.A retrospective cohort study of pregnant patients with and without SARS-CoV-2 infection delivering at 17 hospitals in the United States between March 2020 and December 2020. Patients experiencing a SARS-CoV-2-positive test at or before 28 weeks of gestation with a subsequent delivery hospitalization were compared with those without a positive SAR-CoV-2 test at the same hospitals with randomly selected delivery days during the same period. Deliveries occurring at20 weeks of gestation in both groups were excluded. The study outcomes included fetal or neonatal death, preterm birth at37 weeks of gestation and34 weeks of gestation, hypertensive disorders of pregnancy (HDP), any major congenital malformation, and size for gestational age of5th or10th percentiles at birth based on published standards. HDP that were collected included HDP and preeclampsia with severe features, both overall and with delivery at37 weeks of gestation.Of 2326 patients who tested positive for SARS-CoV-2 during pregnancy and were at least 20 weeks of gestation at delivery from March 2020 to December 2020, 402 patients (delivering 414 fetuses or neonates) were SARS-CoV-2 positive before 28 weeks of gestation and before their admission for delivery; they were compared with 11,705 patients without a positive SARS-CoV-2 test. In adjusted analyses, those with SARS-CoV-2 before 28 weeks of gestation had a subsequent increased risk of fetal or neonatal death (2.9% vs 1.5%; adjusted relative risk, 1.97; 95% confidence interval, 1.01-3.85), preterm birth at37 weeks of gestation (19.6% vs 13.8%; adjusted relative risk, 1.29; 95% confidence interval, 1.02-1.63), and HDP with delivery at37 weeks of gestation (7.2% vs 4.1%; adjusted relative risk, 1.74; 95% confidence interval, 1.19-2.55). There was no difference in the rates of preterm birth at34 weeks of gestation, any major congenital malformation, and size for gestational age of5th or10th percentiles. In addition, there was no significant difference in the rate of gestational hypertension overall or preeclampsia with severe features.There was a modest increase in the risk of adverse pregnancy outcomes after SARS-CoV-2 infection.

Structural equation models (SEM) are a method of latent variable analysis that offer a high degree of flexibility in terms of modeling methods for applied research questions. Recent advancements associated with longitudinal SEM have unlocked innovative ways to decompose variance and to estimate mean trends over time (e.g., Allison et al., 2017; Berry & Willoughby, 2017; Hamaker et al., 2015; McArdle & Nesselroade, 2014). However, these longitudinal methods are not necessarily readily accessible to scholars seeking to advance theory and practice in school psychology. Importantly, not all longitudinal data are the same and not all longitudinal SEMs are the same; thus, analytic approaches must be appropriately matched to specific research aims to meaningfully inform school psychology theory and practice. The present article highlights recent advances in longitudinal SEMs, clarifies their similarities to other—perhaps more familiar—methods, and matches their applications to specific types of research questions. The intent of this work is to promote careful thinking about the correspondence between estimands, developmental theory, and practical applications to foster specificity in testing quantitative questions in school psychology research and advance a more rigorous evaluation of longitudinal trends relevant to research and practice in the field.

IMPORTANCE: It remains unknown whether SARS-CoV-2 infection specifically increases the risk of serious obstetric morbidity. OBJECTIVE: To evaluate the association of SARS-CoV-2 infection with serious maternal morbidity or mortality from common obstetric complications. DESIGN, SETTING, AND PARTICIPANTS: Retrospective cohort study of 14 104 pregnant and postpartum patients delivered between March 1, 2020, and December 31, 2020 (with final follow-up to February 11, 2021), at 17 US hospitals participating in the Eunice Kennedy Shriver National Institute of Child Health and Human Development’s Gestational Research Assessments of COVID-19 (GRAVID) Study. All patients with SARS-CoV-2 were included and compared with those without a positive SARS-CoV-2 test result who delivered on randomly selected dates over the same period. EXPOSURES: SARS-CoV-2 infection was based on a positive nucleic acid or antigen test result. Secondary analyses further stratified those with SARS-CoV-2 infection by disease severity. MAIN OUTCOMES AND MEASURES: The primary outcome was a composite of maternal death or serious morbidity related to hypertensive disorders of pregnancy, postpartum hemorrhage, or infection other than SARS-CoV-2. The main secondary outcome was cesarean birth. RESULTS: Of the 14 104 included patients (mean age, 29.7 years), 2352 patients had SARS-CoV-2 infection and 11 752 did not have a positive SARS-CoV-2 test result. Compared with those without a positive SARS-CoV-2 test result, SARS-CoV-2 infection was significantly associated with the primary outcome (13.4% vs 9.2%; difference, 4.2% [95% CI, 2.8%-5.6%]; adjusted relative risk [aRR], 1.41 [95% CI, 1.23-1.61]). All 5 maternal deaths were in the SARS-CoV-2 group. SARS-CoV-2 infection was not significantly associated with cesarean birth (34.7% vs 32.4%; aRR, 1.05 [95% CI, 0.99-1.11]). Compared with those without a positive SARS-CoV-2 test result, moderate or higher COVID-19 severity (n = 586) was significantly associated with the primary outcome (26.1% vs 9.2%; difference, 16.9% [95% CI, 13.3%-20.4%]; aRR, 2.06 [95% CI, 1.73-2.46]) and the major secondary outcome of cesarean birth (45.4% vs 32.4%; difference, 12.8% [95% CI, 8.7%-16.8%]; aRR, 1.17 [95% CI, 1.07-1.28]), but mild or asymptomatic infection (n = 1766) was not significantly associated with the primary outcome (9.2% vs 9.2%; difference, 0% [95% CI, −1.4% to 1.4%]; aRR, 1.11 [95% CI, 0.94-1.32]) or cesarean birth (31.2% vs 32.4%; difference, −1.4% [95% CI, −3.6% to 0.8%]; aRR, 1.00 [95% CI, 0.93-1.07]). CONCLUSIONS AND RELEVANCE: Among pregnant and postpartum individuals at 17 US hospitals, SARS-CoV-2 infection was associated with an increased risk for a composite outcome of maternal mortality or serious morbidity from obstetric complications.

Public libraries are an important resource for emergent literacy development. Emergent literacy is the behavior a child exhibits relative to books and reading before the child is able to decode wor...

Background Chronic diseases that drive morbidity, mortality, and health care costs are largely influenced by human behavior. Behavioral health conditions such as anxiety, depression, and substance use disorders can often be effectively managed. The majority of patients in need of behavioral health care are seen in primary care, which often has difficulty responding. Some primary care practices are providing integrated behavioral health care (IBH), where primary care and behavioral health providers work together, in one location, using a team-based approach. Research suggests there may be an association between IBH and improved patient outcomes. However, it is often difficult for practices to achieve high levels of integration. The Integrating Behavioral Health and Primary Care study responds to this need by testing the effectiveness of a comprehensive practice-level intervention designed to improve outcomes in patients with multiple chronic medical and behavioral health conditions by increasing the practice’s degree of behavioral health integration. Methods Forty-five primary care practices, with existing onsite behavioral health care, will be recruited for this study. Forty-three practices will be randomized to the intervention or usual care arm, while 2 practices will be considered “Vanguard” (pilot) practices for developing the intervention. The intervention is a 24-month supported practice change process including an online curriculum, a practice redesign and implementation workbook, remote quality improvement coaching services, and an online learning community. Each practice’s degree of behavioral health integration will be measured using the Practice Integration Profile. Approximately 75 patients with both chronic medical and behavioral health conditions from each practice will be asked to complete a series of surveys to measure patient-centered outcomes. Change in practice degree of behavioral health integration and patient-centered outcomes will be compared between the two groups. Practice-level case studies will be conducted to better understand the contextual factors influencing integration. Discussion As primary care practices are encouraged to provide IBH services, evidence-based interventions to increase practice integration will be needed. This study will demonstrate the effectiveness of one such intervention in a pragmatic, real-world setting. Trial registration ClinicalTrials.gov NCT02868983. Registered on August 16, 2016.

Highlights • Paramagnetic rim lesions are an important subtype of multiple sclerosis lesion. • Automated methods can accelerate the assessment of paramagnetic rim lesions. • APRL automatically identifies and accurately classifies paramagnetic rim lesions., Background and Purpose The presence of a paramagnetic rim around a white matter lesion has recently been shown to be a hallmark of a particular pathological type of multiple sclerosis lesion. Increased prevalence of these paramagnetic rim lesions is associated with a more severe disease course in MS, but manual identification is time-consuming. We present APRL, a method to automatically detect paramagnetic rim lesions on 3T T2*-phase images. Methods T1-weighted, T2-FLAIR, and T2*-phase MRI of the brain were collected at 3T for 20 subjects with MS. The images were then processed with automated lesion segmentation, lesion center detection, lesion labelling, and lesion-level radiomic feature extraction. A total of 951 lesions were identified, 113 (12%) of which contained a paramagnetic rim. We divided our data into a training set (16 patients, 753 lesions) and a testing set (4 patients, 198 lesions), fit a random forest classification model on the training set, and assessed our ability to classify paramagnetic rim lesions on the test set. Results The number of paramagnetic rim lesions per subject identified via our automated lesion labelling method was highly correlated with the gold standard count per subject, r = 0.86 (95% CI [0.68, 0.94]). The classification algorithm using radiomic features classified lesions with an area under the curve of 0.82 (95% CI [0.74, 0.92]). Conclusion This study develops a fully automated technique, APRL, for the detection of paramagnetic rim lesions using standard T1 and FLAIR sequences and a T2*phase sequence obtained on 3T MR images.

Background and PurposeThe presence of a paramagnetic rim around a white matter lesion has recently been shown to be a hallmark of a particular pathological type of multiple sclerosis (MS) lesion. Increased prevalence of these paramagnetic rim lesions (PRLs) is associated with a more severe disease course in MS. The identification of these lesions is time-consuming to perform manually. We present a method to automatically detect PRLs on 3T T2*-phase images.MethodsT1-weighted, T2-FLAIR, and T2*-phase MRI of the brain were collected at 3T for 19 subjects with MS. The images were then processed with lesion segmentation, lesion center detection, lesion labelling, and lesion-level radiomic feature extraction. A total of 877 lesions were identified, 118 (13%) of which contained a paramagnetic rim. We divided our data into a training set (15 patients, 673 lesions) and a testing set (4 patients, 204 lesions). We fit a random forest classification model on the training set and assessed our ability to classify lesions as PRL on the test set.ResultsThe number of PRLs per subject identified via our automated lesion labelling method was highly correlated with the gold standard count of PRLs per subject, r = 0.91 (95% CI [0.79, 0.97]). The classification algorithm using radiomic features can classify a lesion as PRL or not with an area under the curve of 0.80 (95% CI [0.67, 0.86]).ConclusionThis study develops a fully automated technique for the detection of paramagnetic rim lesions using standard T1 and FLAIR sequences and a T2*phase sequence obtained on 3T MR images.HighlightsA fully automated method for both the identification and classification of paramagnetic rim lesions is proposed.Radiomic features in conjunction with machine learning algorithms can accurately classify paramagnetic rim lesions.Challenges for classification are largely driven by heterogeneity between lesions, including equivocal rim signatures and lesion location.

Top-down policymaking approaches (expert-driven, excluding the end-user in the process) for at-risk youth in Baltimore City is one reason for the underuse of government-funded programs, i.e. the Summer Meals program which provides free food to youth workers.This is an unfortunate missed opportunity: more than 42% of West Baltimore youth live in poverty and within a ‘food desert.’ One method for improving this top-down approach, especially in the public health sector, is to include the end-user (i.e. youth) on teams with public health scientists and policymakers to co-create evidence-informed policies. While there is an interest in Baltimore City to do this, there remains little guidance for success.To fill this need, we describe a novel curriculum and research strategy, B’More Engaged Youth Leadership Program, on the competencies needed for at-risk youth, public health scientists, and policymakers to form collaborative, policymaking teams. This course focuses on developing ‘21st century skills,’ such as adapting to change, working in diverse groups, interacting professionally with others, communicating effectively, and managing time and goals. By the end of the course, the youth will co-create an evidence-informed policy recommendation with scientists and policymakers. The initial pilot study will enroll youth from The Food Project, an afterschool non-profit that provides nutrition- and skills-based programming as well as access to healthy foods. To best align with The Food Project, the pilot study curriculum and project focuses on food security in West Baltimore. In parallel, an exploratory case study will describe the experiences of the co-creation team using a series of strategies (observation, surveys, and interviews) and document activity engagement, 21st century skill development, and the best teaching practices for this team. The outcomes of this program will provide valuable insights into 21st century skill development, what activities are effective for this at-risk group in West Baltimore. This information could be of great value in restructuring future youth civic and science engagement programming in West Baltimore and similar communities around the globe.

In this article, the authors illustrate efforts toward adopting methods germane to the emerging field of sociomaterial studies while examining the integration of schoolwide mindfulness practices. Informed by a posthumanist perspective, sociomaterial studies in education work to reveal the ways in which the bodily and other material aspects of educational practice are entangled with the social contexts of schooling. Significance of this discussion includes the ways in which aspects of the study’s methodology shift conventional humanist models for researching educational meanings held by students, teachers, and researchers, to include a perspective that promotes a focus on the social- with-material dimensions of data, analysis and their multisensory productions.

Neck pain affects 15.1% of the United States' general population every 3 months, and ranks fourth in global disability. Because of the tendency for neck pain to become a chronic issue, it is important to identify risk factors that could encourage prevention and early diagnosis. The purpose of this systematic review was to identify risk factors for a first episode of neck pain. Three databases were searched with key words such as "neck pain" and "first incidence." Risk factors from the resulting articles were reported as either a physical or psychosocial risk factor and ranked by the strength of their odds/risk/hazard ratio