Recruiting underrepresented people and communities in research is essential for generalizable findings. Ensuring representative participants can be particularly challenging for practice-level dissemination and implementation trials. Novel use of real-world data about practices and the communities they serve could promote more equitable and inclusive recruitment.

We used a comprehensive primary care clinician and practice database, the Virginia All-Payers Claims Database, and the HealthLandscape Virginia mapping tool with community-level socio-ecological information to prospectively inform practice recruitment for a study to help primary care better screen and counsel for unhealthy alcohol use. Throughout recruitment, we measured how similar study practices were to primary care on average, mapped where practices’ patients lived, and iteratively adapted our recruitment strategies.

In response to practice and community data, we adapted our recruitment strategy three times; first leveraging relationships with residency graduates, then a health system and professional organization approach, followed by a community-targeted approach, and a concluding approach using all three approaches. We enrolled 76 practices whose patients live in 97.3% (1844 of 1907) of Virginia’s census tracts. Our overall patient sample had similar demographics to the state for race (21.7% vs 20.0% Black), ethnicity (9.5% vs 10.2% Hispanic), insurance status (6.4% vs 8.0% uninsured), and education (26.0% vs 32.5% high school graduate or less). Each practice recruitment approach uniquely included different communities and patients.

Data about primary care practices and the communities they serve can prospectively inform research recruitment of practices to yield more representative and inclusive patient cohorts for participation.

Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions.

We revised the original model in a sample of n = 8335 observations from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in one of three Army STARRS 2011–2014 baseline surveys while in service and in one or more subsequent panel surveys (LS1: 2016–2018, LS2: 2018–2019) after leaving service. We trained ensemble machine learning models with constrained numbers of item-level survey predictors in a 70% training sample. The outcome was self-reported post-transition suicide attempts (SA). The models were validated in the 30% test sample.

Twelve-month post-transition SA prevalence was 1.0% (s.e. = 0.1). The best constrained model, with only 17 predictors, had a test sample ROC-AUC of 0.85 (s.e. = 0.03). The 10–30% of respondents with the highest predicted risk included 44.9–92.5% of 12-month SAs.

An accurate SA risk calculator based on a short self-report survey can target transitioning soldiers shortly before leaving service for intervention to prevent post-transition SA.

The effectiveness of community-based participatory research (CBPR) partnerships to address health inequities is well documented. CBPR integrates knowledge and perspectives of diverse communities throughout the research process, following principles that emphasize trust, power sharing, co-learning, and mutual benefits. However, institutions and funders seldom provide the time and resources needed for the critical stage of equitable partnership formation and development.

Since 2011, the Detroit Urban Research Center, collaborating with other entities, has promoted the development of new community–academic research partnerships through two grant programs that combine seed funding with capacity building support from community and academic instructors/mentors experienced in CBPR. Process and outcomes were evaluated using mixed methods.

From 2011 to 2021, 50 partnerships received grants ranging from $2,500 to $30,000, totaling $605,000. Outcomes included equitable partnership infrastructure and processes, innovative pilot research, translation of findings to interventions and policy change, dissemination to multiple audiences, new proposals and projects, and sustained community–academic research partnerships. All partnerships continued beyond the program; over half secured additional funding.

Keys to success included participation as community–academic teams, dedicated time for partnership/relationship development, workshops to develop equity-based skills, relationships, and projects, expert community–academic instructor guidance, and connection to additional resources. Findings demonstrate that small amounts of seed funding for newly forming community–academic partnerships, paired with capacity building support, can provide essential time and resources needed to develop diverse, inclusive, equity-focused CBPR partnerships. Building such support into funding initiatives and through academic institutions can enhance impact and sustainability of translational research toward advancing health equity.

Many male prisoners have significant mental health problems, including anxiety and depression. High proportions struggle with homelessness and substance misuse.

This study aims to evaluate whether the Engager intervention improves mental health outcomes following release.

The design is a parallel randomised superiority trial that was conducted in the North West and South West of England (ISRCTN11707331). Men serving a prison sentence of 2 years or less were individually allocated 1:1 to either the intervention (Engager plus usual care) or usual care alone. Engager included psychological and practical support in prison, on release and for 3–5 months in the community. The primary outcome was the Clinical Outcomes in Routine Evaluation Outcome Measure (CORE-OM), 6 months after release. Primary analysis compared groups based on intention-to-treat (ITT).

In total, 280 men were randomised out of the 396 who were potentially eligible and agreed to participate; 105 did not meet the mental health inclusion criteria. There was no mean difference in the ITT complete case analysis between groups (92 in each arm) for change in the CORE-OM score (1.1, 95% CI –1.1 to 3.2, P = 0.325) or secondary analyses. There were no consistent clinically significant between-group differences for secondary outcomes. Full delivery was not achieved, with 77% (108/140) receiving community-based contact.

Engager is the first trial of a collaborative care intervention adapted for prison leavers. The intervention was not shown to be effective using standard outcome measures. Further testing of different support strategies for prison with mental health problems is needed.

The COVID-19 pandemic has disrupted lives and livelihoods, and people already experiencing mental ill health may have been especially vulnerable.

Quantify mental health inequalities in disruptions to healthcare, economic activity and housing.

We examined data from 59 482 participants in 12 UK longitudinal studies with data collected before and during the COVID-19 pandemic. Within each study, we estimated the association between psychological distress assessed pre-pandemic and disruptions since the start of the pandemic to healthcare (medication access, procedures or appointments), economic activity (employment, income or working hours) and housing (change of address or household composition). Estimates were pooled across studies.

Across the analysed data-sets, 28% to 77% of participants experienced at least one disruption, with 2.3–33.2% experiencing disruptions in two or more domains. We found 1 s.d. higher pre-pandemic psychological distress was associated with (a) increased odds of any healthcare disruptions (odds ratio (OR) 1.30, 95% CI 1.20–1.40), with fully adjusted odds ratios ranging from 1.24 (95% CI 1.09–1.41) for disruption to procedures to 1.33 (95% CI 1.20–1.49) for disruptions to prescriptions or medication access; (b) loss of employment (odds ratio 1.13, 95% CI 1.06–1.21) and income (OR 1.12, 95% CI 1.06 –1.19), and reductions in working hours/furlough (odds ratio 1.05, 95% CI 1.00–1.09) and (c) increased likelihood of experiencing a disruption in at least two domains (OR 1.25, 95% CI 1.18–1.32) or in one domain (OR 1.11, 95% CI 1.07–1.16), relative to no disruption. There were no associations with housing disruptions (OR 1.00, 95% CI 0.97–1.03).

People experiencing psychological distress pre-pandemic were more likely to experience healthcare and economic disruptions, and clusters of disruptions across multiple domains during the pandemic. Failing to address these disruptions risks further widening mental health inequalities.

The adult population of repaired tetralogy of Fallot is increasing and at risk of pre-mature death and arrhythmia. This study evaluates risk factors for adverse outcome and the effect of pulmonary valve replacement within a national cohort.

A retrospective cohort study of 341 adult repaired tetralogy of Fallot (16–72 years) managed through a single national service was undertaken incorporating over 1200 patient-years of follow-up. Demographics, cardiopulmonary exercise testing, cardiac magnetic resonance, reintervention (including pulmonary valve replacement), and clinical events were analysed. The influence of these parameters on a primary outcome (death or arrhythmia) was evaluated.

Compared with an age-/gender-matched population, patients experienced a reduced survival, particularly males over 55 years (standardised mortality ratio : 6.12, 95% CI: 1.64–15.66, p = 0.004). Cox proportional hazards modelling identified increased indexed right ventricle (RV) end-diastolic volume (hazard ratio (HR): 2.86, 95% CI: 1.4–5.85, p = 0.004) and female gender (HR (male): 0.37, 95% CI: 0.14–0.98, p = 0.045) to be predictors significantly associated with the primary outcome. Pulmonary valve replacement undertaken at indexed RV end-diastolic volume = 145 ml/m2 reduced RV volumes and QRS duration but did not improve cardiopulmonary exercise testing nor NYHA class. Pulmonary valve replacement during cohort period was associated with increased risk of primary outcome (HR: 2.82, 95% CI: 1.36–5.86, p = 0.005).

Although the majority of adult tetralogy of Fallot were asymptomatic in NYHA 1, cardiopulmonary exercise testing revealed important deficits. Tetralogy of Fallot survival was reduced compared to the general population. Female gender and increasing RV end-diastolic volume predicted adverse events. Pulmonary valve replacement reduced RV volumes and QRS duration but did not improve primary outcome.

Head impact exposure (HIE) in youth football is a public health concern. The objective of this study was to determine if one season of HIE in youth football was related to cognitive changes.

Over 200 participants (ages 9–13) wore instrumented helmets for practices and games to measure the amount of HIE sustained over one season. Pre- and post-season neuropsychological tests were completed. Test score changes were calculated adjusting for practice effects and regression to the mean and used as the dependent variables. Regression models were calculated with HIE variables predicting neuropsychological test score changes.

For the full sample, a small effect was found with season average rotational values predicting changes in list-learning such that HIE was related to negative score change: standardized beta (β) = -.147, t(205) = -2.12, and p = .035. When analyzed by age clusters (9–10, 11–13) and adding participant weight to models, the R2 values increased. Splitting groups by weight (median split), found heavier members of the 9–10 cohort with significantly greater change than lighter members. Additionaly, significantly more participants had clinically meaningful negative changes: X2 = 10.343, p = .001.

These findings suggest that in the 9–10 age cluster, the average seasonal level of HIE had inverse, negative relationships with cognitive change over one season that was not found in the older group. The mediation effects of age and weight have not been explored previously and appear to contribute to the effects of HIE on cognition in youth football players.

The ‘jumping to conclusions’ (JTC) bias is associated with both psychosis and general cognition but their relationship is unclear. In this study, we set out to clarify the relationship between the JTC bias, IQ, psychosis and polygenic liability to schizophrenia and IQ.

A total of 817 first episode psychosis patients and 1294 population-based controls completed assessments of general intelligence (IQ), and JTC, and provided blood or saliva samples from which we extracted DNA and computed polygenic risk scores for IQ and schizophrenia.

The estimated proportion of the total effect of case/control differences on JTC mediated by IQ was 79%. Schizophrenia polygenic risk score was non-significantly associated with a higher number of beads drawn (B = 0.47, 95% CI −0.21 to 1.16, p = 0.17); whereas IQ PRS (B = 0.51, 95% CI 0.25–0.76, p < 0.001) significantly predicted the number of beads drawn, and was thus associated with reduced JTC bias. The JTC was more strongly associated with the higher level of psychotic-like experiences (PLEs) in controls, including after controlling for IQ (B = −1.7, 95% CI −2.8 to −0.5, p = 0.006), but did not relate to delusions in patients.

Our findings suggest that the JTC reasoning bias in psychosis might not be a specific cognitive deficit but rather a manifestation or consequence, of general cognitive impairment. Whereas, in the general population, the JTC bias is related to PLEs, independent of IQ. The work has the potential to inform interventions targeting cognitive biases in early psychosis.