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Exclusion of special populations (older adults; pregnant women, children, and adolescents; individuals of lower socioeconomic status and/or who live in rural communities; people from racial and ethnic minority groups; individuals from sexual or gender minority groups; and individuals with disabilities) in research is a pervasive problem, despite efforts and policy changes by the National Institutes of Health and other organizations. These populations are adversely impacted by social determinants of health (SDOH) that reduce access and ability to participate in biomedical research. In March 2020, the Northwestern University Clinical and Translational Sciences Institute hosted the “Lifespan and Life Course Research: integrating strategies” “Un-Meeting” to discuss barriers and solutions to underrepresentation of special populations in biomedical research. The COVID-19 pandemic highlighted how exclusion of representative populations in research can increase health inequities. We applied findings of this meeting to perform a literature review of barriers and solutions to recruitment and retention of representative populations in research and to discuss how findings are important to research conducted during the ongoing COVID-19 pandemic. We highlight the role of SDOH, review barriers and solutions to underrepresentation, and discuss the importance of a structural competency framework to improve research participation and retention among special populations.
Research suggests that there have been inequalities in the impact of the coronavirus disease 2019 (COVID-19) pandemic and related non-pharmaceutical interventions on population mental health. We explored generational, sex, and socioeconomic inequalities during the first year of the pandemic using nationally representative cohorts from the UK.
Methods
We analysed data from 26772 participants from five longitudinal cohorts representing generations born between 1946 and 2000, collected in May 2020, September–October 2020, and February–March 2021 across all five cohorts. We used a multilevel growth curve modelling approach to investigate generational, sex, and socioeconomic differences in levels of anxiety and depressive symptomatology, loneliness, and life satisfaction (LS) over time.
Results
Younger generations had worse levels of mental and social wellbeing throughout the first year of the pandemic. Whereas these generational inequalities narrowed between the first and last observation periods for LS [−0.33 (95% CI −0.51 to −0.15)], they became larger for anxiety [0.22 (0.10, 0.33)]. Generational inequalities in depression and loneliness did not change between the first and last observation periods, but initial depression levels of the youngest cohort were worse than expected if the generational inequalities had not accelerated. Women and those experiencing financial difficulties had worse initial mental and social wellbeing levels than men and those financially living comfortably, respectively, and these gaps did not substantially differ between the first and last observation periods.
Conclusions
By March 2021, mental and social wellbeing inequalities persisted in the UK adult population. Pre-existing generational inequalities may have been exacerbated with the pandemic onset. Policies aimed at protecting vulnerable groups are needed.
Despite an elevated risk of psychopathology stemming from COVID-19-related stress, many essential workers stigmatise and avoid psychiatric care. This randomised controlled trial was designed to compare five versions of a social-contact-based brief video intervention for essential workers, differing by protagonist gender and race/ethnicity.
Aims
We examined intervention efficacy on treatment-related stigma (‘stigma’) and openness to seeking treatment (‘openness’), especially among workers who had not received prior mental healthcare. We assessed effectiveness and whether viewer/protagonist demographic concordance heightened effectiveness.
Method
Essential workers (N = 2734) randomly viewed a control video or brief video of an actor portraying an essential worker describing hardships, COVID-related anxiety and depression, and psychotherapy benefits. Five video versions (Black/Latinx/White and male/female) followed an identical 3 min script. Half the intervention group participants rewatched their video 14 days later. Stigma and openness were assessed at baseline, post-intervention, and at 14- and 30-day follow-ups. Trial registration: NCT04964570.
Results
All video intervention groups reported immediately decreased stigma (P < 0.0001; Cohen's d = 0.10) and increased openness (P < 0.0001; d = 0.23). The initial increase in openness was largely maintained in the repeated-video group at day 14 (P < 0.0001; d = 0.18), particularly among viewers without history of psychiatric treatment (P < 0.0001; d = 0.32). Increases were not sustained at follow-up. Female participants viewing a female protagonist and Black participants viewing a Black protagonist demonstrated greater openness than other demographic pairings.
Conclusions
Brief video-based interventions improved immediate stigma and openness. Greater effects among female and Black individuals viewing demographically matched protagonists emphasise the value of tailored interventions, especially for socially oppressed groups. This easily disseminated intervention may proactively increase care-seeking, encouraging treatment among workers in need. Future studies should examine intervention mechanisms and whether linking referrals to psychiatric services generates treatment-seeking.
Researchers have spent decades investigating factors in attraction; biological variables, cultural norms, and social pressures have all had their time in the spotlight. Humans are complicated animals and each of these realms have shown measurable effects. However, evolutionary approaches provide a unifying theory that subsumes and explains each of these factors and how they interact to create intricate yet predictable patterns in human mating behavior. In this chapter, we give a brief summary of major factors influencing attractiveness as perceived by men, including biological factors such as age and ovulatory status but also social factors such as exposure to highly attractive, or simply novel, women. Understanding how attractiveness can vary over time and within relationships can be useful, not only to research but also in applied clinical fields such as couples’ and marital therapy.
Bloodstream infections (BSIs) are a frequent cause of morbidity in patients with acute myeloid leukemia (AML), due in part to the presence of central venous access devices (CVADs) required to deliver therapy.
Objective:
To determine the differential risk of bacterial BSI during neutropenia by CVAD type in pediatric patients with AML.
Methods:
We performed a secondary analysis in a cohort of 560 pediatric patients (1,828 chemotherapy courses) receiving frontline AML chemotherapy at 17 US centers. The exposure was CVAD type at course start: tunneled externalized catheter (TEC), peripherally inserted central catheter (PICC), or totally implanted catheter (TIC). The primary outcome was course-specific incident bacterial BSI; secondary outcomes included mucosal barrier injury (MBI)-BSI and non-MBI BSI. Poisson regression was used to compute adjusted rate ratios comparing BSI occurrence during neutropenia by line type, controlling for demographic, clinical, and hospital-level characteristics.
Results:
The rate of BSI did not differ by CVAD type: 11 BSIs per 1,000 neutropenic days for TECs, 13.7 for PICCs, and 10.7 for TICs. After adjustment, there was no statistically significant association between CVAD type and BSI: PICC incident rate ratio [IRR] = 1.00 (95% confidence interval [CI], 0.75–1.32) and TIC IRR = 0.83 (95% CI, 0.49–1.41) compared to TEC. When MBI and non-MBI were examined separately, results were similar.
Conclusions:
In this large, multicenter cohort of pediatric AML patients, we found no difference in the rate of BSI during neutropenia by CVAD type. This may be due to a risk-profile for BSI that is unique to AML patients.
Background: Mean arterial pressure augmentation is one current established practice for management of patients with SCI. We present the first data investigating the effectiveness of Intrathecal Pressure (ITP) reduction through CSF drainage (CSFD) in managing patients with acute traumatic SCI at a large academic center. Methods: Data from 6 patients with acute traumatic SCI were included. A lumbar intrathecal catheter was used to monitor ITP and volume of CSFD. CSFD was performed and recorded hourly. ITP recordings were collected hourly and the change in ITP was calculated (hour after minus before CSFD). 369 data points were collected and change in ITP was plotted against volume of CSFD. Results: Data across all patients showed variability in the ITP over time without a significant trend (slope=0.016). We found no significant change in ITP with varying amounts of CSFD (slope=0.007, r2=0.00, p=0.88). Changes in ITP were not significantly different across groups of CSFD but the variation in the data decreased with increasing levels of CSFD. Conclusions: We present the first known data on changes in ITP with varying degrees of CSFD in patients with acute traumatic SCI. These results may provide insight into the complexity of ITP changes in patients post-injury and help inform future SCI management.
Background: Length of stay (LOS) is a surrogate for care complexity and a determinant of occupancy and service provision. Our primary goal was to assess changes in and determinants of LOS at a quaternary spinal care center. Secondary goals included identifying opportunities for improvement and determinants of future service planning. Methods: This is a prospective study of patients admitted from 2006 to 2019. Data included demographics, diagnostic category (degenerative, oncology, deformity, trauma, other), LOS (mean, median, interquartile range, standard deviation) and in-hospital adverse events (AEs). Results: 13,493 admissions were included. Mean age has increased from 48.4 (2006) to 58.1 years (2019) (p=<0.001). Mean age increased overtime for patients treated for deformity (p=<0.001), degenerative pathology (p=<0.001) and trauma (p=<0.001), but not oncology (p=0.702). Overall LOS has not changed over time (p=0.451). LOS increased in patients with degenerative pathology (p=0.019) but not deformity (p=0.411), oncology (p=0.051) or trauma (p=0.582). Emergency admissions increased overtime for degenerative pathologies (p=<0.001). AEs and SSIs have decreased temporally (p=<0.001). Conclusions: This is the first North American study to analyze temporal trends in LOS for spine surgery in an academic center. Understanding temporal trends in LOS and patient epidemiology can provide opportunities for intervention, targeted at the geriatric populations, to reduce LOS.
Background: Prolonged length of stay (LOS) is associated with increased resource utilization and worse outcomes. The goal of this study is identifying patient, surgical and systemic factors associated with prolonged LOS overall and per diagnostic category for adults admitted to a quaternary spinal care center. Methods: We performed a retrospective analysis on 13,493 admissions from 2006 to 2019. Factors analyzed included patient age, sex, emergency vs elective admission, diagnostic category (degenerative, deformity, oncology, trauma), presence of neurological deficits in trauma patients, ASIA score, operative management and duration, blood loss, and adverse events (AEs). Univariate and multivariate analyses determined factors associated with prolonged LOS. Results: Overall mean LOS (±SD) was 15.80 (±34.03) days. Through multivariate analyses, predictors of prolonged LOS were advanced age (p<0.001), emergency admission (p<0.001), advanced ASIA score (p<0.001), operative management (p=0.043), and presence of AEs (p<0.001), including SSI (p=0.001), other infections (systemic and UTI) (p<0.001), delirium (p=0.006), and pneumonia (p<0.001). The effects of age, emergency admission, and AEs on LOS differed by diagnostic category. Conclusions: Understanding patient and disease factors that affect LOS provides opportunities for QI intervention and allows for an informed preoperative discussion with patients. Future interventions can be targeted to maximize patient outcomes, optimize care quality, and decrease costs.
Predicting future states of psychopathology such as depressive episodes has been a hallmark initiative in mental health research. Dynamical systems theory has proposed that rises in certain ‘early warning signals’ (EWSs) in time-series data (e.g. auto-correlation, temporal variance, network connectivity) may precede impending changes in disorder severity. The current study investigates whether rises in these EWSs over time are associated with future changes in disorder severity among a group of patients with major depressive disorder (MDD).
Methods
Thirty-one patients with MDD completed the study, which consisted of daily smartphone-delivered surveys over 8 weeks. Daily positive and negative affect were collected for the time-series analyses. A rolling window approach was used to determine whether rises in auto-correlation of total affect, temporal standard deviation of total affect, and overall network connectivity in individual affect items were predictive of increases in depression symptoms.
Results
Results suggested that rises in auto-correlation were significantly associated with worsening in depression symptoms (r = 0.41, p = 0.02). Results indicated that neither rises in temporal standard deviation (r = −0.23, p = 0.23) nor in network connectivity (r = −0.12, p = 0.59) were associated with changes in depression symptoms.
Conclusions
This study more rigorously examines whether rises in EWSs were associated with future depression symptoms in a larger group of patients with MDD. Results indicated that rises in auto-correlation were the only EWS that was associated with worsening future changes in depression.
We summarize some of the past year's most important findings within climate change-related research. New research has improved our understanding about the remaining options to achieve the Paris Agreement goals, through overcoming political barriers to carbon pricing, taking into account non-CO2 factors, a well-designed implementation of demand-side and nature-based solutions, resilience building of ecosystems and the recognition that climate change mitigation costs can be justified by benefits to the health of humans and nature alone. We consider new insights about what to expect if we fail to include a new dimension of fire extremes and the prospect of cascading climate tipping elements.
Technical summary
A synthesis is made of 10 topics within climate research, where there have been significant advances since January 2020. The insights are based on input from an international open call with broad disciplinary scope. Findings include: (1) the options to still keep global warming below 1.5 °C; (2) the impact of non-CO2 factors in global warming; (3) a new dimension of fire extremes forced by climate change; (4) the increasing pressure on interconnected climate tipping elements; (5) the dimensions of climate justice; (6) political challenges impeding the effectiveness of carbon pricing; (7) demand-side solutions as vehicles of climate mitigation; (8) the potentials and caveats of nature-based solutions; (9) how building resilience of marine ecosystems is possible; and (10) that the costs of climate change mitigation policies can be more than justified by the benefits to the health of humans and nature.
Social media summary
How do we limit global warming to 1.5 °C and why is it crucial? See highlights of latest climate science.
Growing evidence suggests that air pollution exposure may adversely affect the brain and increase risk for psychiatric disorders such as schizophrenia and depression. However, little is known about the potential role of air pollution in severity and relapse following illness onset.
Aims
To examine the longitudinal association between residential air pollution exposure and mental health service use (an indicator of illness severity and relapse) among individuals with first presentations of psychotic and mood disorders.
Method
We identified individuals aged ≥15 years who had first contact with the South London and Maudsley NHS Foundation Trust for psychotic and mood disorders in 2008–2012 (n = 13 887). High-resolution (20 × 20 m) estimates of nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM2.5 and PM10) levels in ambient air were linked to residential addresses. In-patient days and community mental health service (CMHS) events were recorded over 1-year and 7-year follow-up periods.
Results
Following covariate adjustment, interquartile range increases in NO2, NOx and PM2.5 were associated with 18% (95% CI 5–34%), 18% (95% CI 5–34%) and 11% (95% CI 3–19%) increased risk for in-patient days after 1 year. Similarly, interquartile range increases in NO2, NOx, PM2.5 and PM10 were associated with 32% (95% CI 25–38%), 31% (95% CI 24–37%), 7% (95% CI 4–11%) and 9% (95% CI 5–14%) increased risk for CMHS events after 1 year. Associations persisted after 7 years.
Conclusions
Residential air pollution exposure is associated with increased mental health service use among people recently diagnosed with psychotic and mood disorders. Assuming causality, interventions to reduce air pollution exposure could improve mental health prognoses and reduce healthcare costs.
We present an overview of the Middle Ages Galaxy Properties with Integral Field Spectroscopy (MAGPI) survey, a Large Program on the European Southern Observatory Very Large Telescope. MAGPI is designed to study the physical drivers of galaxy transformation at a lookback time of 3–4 Gyr, during which the dynamical, morphological, and chemical properties of galaxies are predicted to evolve significantly. The survey uses new medium-deep adaptive optics aided Multi-Unit Spectroscopic Explorer (MUSE) observations of fields selected from the Galaxy and Mass Assembly (GAMA) survey, providing a wealth of publicly available ancillary multi-wavelength data. With these data, MAGPI will map the kinematic and chemical properties of stars and ionised gas for a sample of 60 massive (
${>}7 \times 10^{10} {\mathrm{M}}_\odot$
) central galaxies at
$0.25 < z <0.35$
in a representative range of environments (isolated, groups and clusters). The spatial resolution delivered by MUSE with Ground Layer Adaptive Optics (
$0.6-0.8$
arcsec FWHM) will facilitate a direct comparison with Integral Field Spectroscopy surveys of the nearby Universe, such as SAMI and MaNGA, and at higher redshifts using adaptive optics, for example, SINS. In addition to the primary (central) galaxy sample, MAGPI will deliver resolved and unresolved spectra for as many as 150 satellite galaxies at
$0.25 < z <0.35$
, as well as hundreds of emission-line sources at
$z < 6$
. This paper outlines the science goals, survey design, and observing strategy of MAGPI. We also present a first look at the MAGPI data, and the theoretical framework to which MAGPI data will be compared using the current generation of cosmological hydrodynamical simulations including EAGLE, Magneticum, HORIZON-AGN, and Illustris-TNG. Our results show that cosmological hydrodynamical simulations make discrepant predictions in the spatially resolved properties of galaxies at
$z\approx 0.3$
. MAGPI observations will place new constraints and allow for tangible improvements in galaxy formation theory.
In April 2019, the U.S. Fish and Wildlife Service (USFWS) released its recovery plan for the jaguar Panthera onca after several decades of discussion, litigation and controversy about the status of the species in the USA. The USFWS estimated that potential habitat, south of the Interstate-10 highway in Arizona and New Mexico, had a carrying capacity of c. six jaguars, and so focused its recovery programme on areas south of the USA–Mexico border. Here we present a systematic review of the modelling and assessment efforts over the last 25 years, with a focus on areas north of Interstate-10 in Arizona and New Mexico, outside the recovery unit considered by the USFWS. Despite differences in data inputs, methods, and analytical extent, the nine previous studies found support for potential suitable jaguar habitat in the central mountain ranges of Arizona and New Mexico. Applying slightly modified versions of the USFWS model and recalculating an Arizona-focused model over both states provided additional confirmation. Extending the area of consideration also substantially raised the carrying capacity of habitats in Arizona and New Mexico, from six to 90 or 151 adult jaguars, using the modified USFWS models. This review demonstrates the crucial ways in which choosing the extent of analysis influences the conclusions of a conservation plan. More importantly, it opens a new opportunity for jaguar conservation in North America that could help address threats from habitat losses, climate change and border infrastructure.
Efforts to move community engagement in research from marginalized to mainstream include the NIH requiring community engagement programs in all Clinical and Translational Science Awards (CTSAs). However, the COVID-19 pandemic has exposed how little these efforts have changed the dominant culture of clinical research. When faced with the urgent need to generate knowledge about prevention and treatment of the novel coronavirus, researchers largely neglected to involve community stakeholders early in the research process. This failure cannot be divorced from the broader context of systemic racism in the US that has contributed to Black, Indigenous, and People of Color (BIPOC) communities bearing a disproportionate toll from COVID-19, being underrepresented in COVID-19 clinical trials, and expressing greater hesitancy about COVID-19 vaccination. We call on research funders and research institutions to take decisive action to make community engagement obligatory, not optional, in all clinical and translational research and to center BIPOC communities in this process. Recommended actions include funding agencies requiring all research proposals involving human participants to include a community engagement plan, providing adequate funding to support ongoing community engagement, including community stakeholders in agency governance and proposal reviews, promoting racial and ethnic diversity in the research workforce, and making a course in community engaged research a requirement for Masters of Clinical Research curricula.
We summarize some of the past year's most important findings within climate change-related research. New research has improved our understanding of Earth's sensitivity to carbon dioxide, finds that permafrost thaw could release more carbon emissions than expected and that the uptake of carbon in tropical ecosystems is weakening. Adverse impacts on human society include increasing water shortages and impacts on mental health. Options for solutions emerge from rethinking economic models, rights-based litigation, strengthened governance systems and a new social contract. The disruption caused by COVID-19 could be seized as an opportunity for positive change, directing economic stimulus towards sustainable investments.
Technical summary
A synthesis is made of ten fields within climate science where there have been significant advances since mid-2019, through an expert elicitation process with broad disciplinary scope. Findings include: (1) a better understanding of equilibrium climate sensitivity; (2) abrupt thaw as an accelerator of carbon release from permafrost; (3) changes to global and regional land carbon sinks; (4) impacts of climate change on water crises, including equity perspectives; (5) adverse effects on mental health from climate change; (6) immediate effects on climate of the COVID-19 pandemic and requirements for recovery packages to deliver on the Paris Agreement; (7) suggested long-term changes to governance and a social contract to address climate change, learning from the current pandemic, (8) updated positive cost–benefit ratio and new perspectives on the potential for green growth in the short- and long-term perspective; (9) urban electrification as a strategy to move towards low-carbon energy systems and (10) rights-based litigation as an increasingly important method to address climate change, with recent clarifications on the legal standing and representation of future generations.
Social media summary
Stronger permafrost thaw, COVID-19 effects and growing mental health impacts among highlights of latest climate science.
Associations of socioenvironmental features like urbanicity and neighborhood deprivation with psychosis are well-established. An enduring question, however, is whether these associations are causal. Genetic confounding could occur due to downward mobility of individuals at high genetic risk for psychiatric problems into disadvantaged environments.
Methods
We examined correlations of five indices of genetic risk [polygenic risk scores (PRS) for schizophrenia and depression, maternal psychotic symptoms, family psychiatric history, and zygosity-based latent genetic risk] with multiple area-, neighborhood-, and family-level risks during upbringing. Data were from the Environmental Risk (E-Risk) Longitudinal Twin Study, a nationally-representative cohort of 2232 British twins born in 1994–1995 and followed to age 18 (93% retention). Socioenvironmental risks included urbanicity, air pollution, neighborhood deprivation, neighborhood crime, neighborhood disorder, social cohesion, residential mobility, family poverty, and a cumulative environmental risk scale. At age 18, participants were privately interviewed about psychotic experiences.
Results
Higher genetic risk on all indices was associated with riskier environments during upbringing. For example, participants with higher schizophrenia PRS (OR = 1.19, 95% CI = 1.06–1.33), depression PRS (OR = 1.20, 95% CI = 1.08–1.34), family history (OR = 1.25, 95% CI = 1.11–1.40), and latent genetic risk (OR = 1.21, 95% CI = 1.07–1.38) had accumulated more socioenvironmental risks for schizophrenia by age 18. However, associations between socioenvironmental risks and psychotic experiences mostly remained significant after covariate adjustment for genetic risk.
Conclusion
Genetic risk is correlated with socioenvironmental risk for schizophrenia during upbringing, but the associations between socioenvironmental risk and adolescent psychotic experiences appear, at present, to exist above and beyond this gene-environment correlation.
Subjective cognitive difficulties are common in mental illness and have a negative impact on role functioning. Little is understood about subjective cognition and the longitudinal relationship with depression and anxiety symptoms in young people.
Aims
To examine the relationship between changes in levels of depression and anxiety and changes in subjective cognitive functioning over 3 months in help-seeking youth.
Method
This was a cohort study of 656 youth aged 12–25 years attending Australian headspace primary mental health services. Subjective changes in cognitive functioning (rated as better, same, worse) reported after 3 months of treatment was assessed using the Neuropsychological Symptom Self-Report. Multivariate multinomial logistic regression analysis was conducted to evaluate the impact of baseline levels of and changes in depression (nine-item Patient Health Questionnaire; PHQ9) and anxiety symptoms (seven-item Generalised Anxiety Disorder scale; GAD7) on changes in subjective cognitive function at follow-up while controlling for covariates.
Results
With a one-point reduction in PHQ9 at follow-up, there was an estimated 11–18% increase in ratings of better subjective cognitive functioning at follow-up, relative to stable cognitive functioning. A one-point increase in PHQ9 from baseline to follow-up was associated with 7–14% increase in ratings of worse subjective cognitive functioning over 3 months, relative to stable cognitive functioning. A similar attenuated pattern of findings was observed for the GAD7.
Conclusions
A clear association exists between subjective cognitive functioning outcomes and changes in self-reported severity of affective symptoms in young people over the first 3 months of treatment. Understanding the timing and mechanisms of these associations is needed to tailor treatment.