Adolescent substance use, externalizing and attention problems, and early life stress (ELS) commonly co-occur. These psychopathologies show overlapping neural dysfunction in the form of reduced recruitment of reward processing neuro-circuitries. However, it is unclear to what extent these psychopathologies show common v. different neural dysfunctions as a function of symptom profiles, as no studies have directly compared neural dysfunctions associated with each of these psychopathologies to each other.

In study 1, a latent profile analysis (LPA) was conducted in a sample of 266 adolescents (aged 13–18, 41.7% female, 58.3% male) from a residential youth care facility and the surrounding community to investigate substance use, externalizing and attention problems, and ELS psychopathologies and their co-presentation. In study 2, we examined a subsample of 174 participants who completed the Passive Avoidance learning task during functional magnetic resonance imaging to examine differential and/or common reward processing neuro-circuitry dysfunctions associated with symptom profiles based on these co-presentations.

In study 1, LPA identified profiles of substance use plus rule-breaking behaviors, attention-deficit hyperactivity disorder, and ELS. In study 2, the substance use/rule-breaking profile was associated with reduced recruitment of reward processing and attentional neuro-circuitries during the Passive Avoidance task (p < 0.05, corrected for multiple comparisons).

Findings indicate that there is reduced responsivity of striato-cortical regions when receiving outcomes on an instrumental learning task within a profile of adolescents with substance use and rule-breaking behaviors. Mitigating reward processing dysfunction specifically may represent a potential intervention target for substance-use psychopathologies accompanied by rule-breaking behaviors.

To evaluate the impact of a diagnostic stewardship intervention on Clostridioides difficile healthcare-associated infections (HAI).

Quality improvement study.

Two urban acute care hospitals.

All inpatient stool testing for C. difficile required review and approval prior to specimen processing in the laboratory. An infection preventionist reviewed all orders daily through chart review and conversations with nursing; orders meeting clinical criteria for testing were approved, orders not meeting clinical criteria were discussed with the ordering provider. The proportion of completed tests meeting clinical criteria for testing and the primary outcome of C. difficile HAI were compared before and after the intervention.

The frequency of completed C. difficile orders not meeting criteria was lower [146 (7.5%) of 1,958] in the intervention period (January 10, 2022–October 14, 2022) than in the sampled 3-month preintervention period [26 (21.0%) of 124; P < .001]. C. difficile HAI rates were 8.80 per 10,000 patient days prior to the intervention (March 1, 2021–January 9, 2022) and 7.69 per 10,000 patient days during the intervention period (incidence rate ratio, 0.87; 95% confidence interval, 0.73–1.05; P = .13).

A stringent order-approval process reduced clinically nonindicated testing for C. difficile but did not significantly decrease HAIs.

The Mini International Neuropsychiatric Inventory 7.0.2 (MINI-7) is a widely used tool and known to have sound psychometric properties; but very little is known about its use in low and middle-income countries (LMICs). This study aimed to examine the psychometric properties of the MINI-7 psychosis items in a sample of 8609 participants across four countries in Sub-Saharan Africa.

We examined the latent factor structure and the item difficulty of the MINI-7 psychosis items in the full sample and across four countries.

Multiple group confirmatory factor analyses (CFAs) revealed an adequate fitting unidimensional model for the full sample; however, single group CFAs at the country level revealed that the underlying latent structure of psychosis was not invariant. Specifically, although the unidimensional structure was an adequate model fit for Ethiopia, Kenya, and South Africa, it was a poor fit for Uganda. Instead, a 2-factor latent structure of the MINI-7 psychosis items provided the optimal fit for Uganda. Examination of item difficulties revealed that MINI-7 item K7, measuring visual hallucinations, had the lowest difficulty across the four countries. In contrast, the items with the highest difficulty were different across the four countries, suggesting that MINI-7 items that are the most predictive of being high on the latent factor of psychosis are different for each country.

The present study is the first to provide evidence that the factor structure and item functioning of the MINI-7 psychosis vary across different settings and populations in Africa.

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.

This study examined associations between multiple dietary supplement (DS) categories and medical conditions diagnosed by health professionals.

Cross-sectional.

Volunteers completed an online questionnaire on DS use and demographic/lifestyle factors. Medical diagnoses were obtained from a comprehensive military electronic medical surveillance system and grouped into twenty-four clinically diagnosed medical conditions (CDMC).

A stratified random sample of US service members (SM) from all military services (n 26 680).

After adjustment for demographic/lifestyle factors (logistic regression), higher risk was found for 92 % (22/24) of CDMC among individual vitamins/minerals users, 58 % (14/24) of CDMC among herbal users, 50 % (12/24) of CDMC among any DS users and 46 % (11/24) of CDMC among multivitamins/multiminerals (MVM) users. Among protein/amino acid (AA) users, risk was lower in 25 % (6/24) of CDMC. For combination products, risk was higher in 13 % (3/24) of CDMC and lower in 8 % (2/24). The greater the number of CDMC, the higher the prevalence of DS use in most DS categories except proteins/AA where prevalence decreased.

Users in many DS categories had a greater number of CDMC, but protein/AA users had fewer CDMC; results for combination products were mixed. These data indicate those with certain CDMC were also users in some DS categories, especially individual vitamins/minerals, herbals and MVM. Data are consistent with the perception that use of DS enhances health, especially in those with CDMC. Protein/AA and combination product users were more likely to be younger, more physically active men, factors that likely reduced CDMC.

The aim of this study was to analyze congestive heart failure (CHF) discharges in Florida (USA) post tropical cyclones from 2007 through 2017.

This was a retrospective longitudinal time series analysis of hospital CHF quarterly discharges across Florida using the Healthcare Cost and Utilization Project (HCUP) database. The autoregressive integrated moving average (ARIMA) model was used with correlated seasonal regressor variables such as cyclone frequency, maximum cyclone wind speed, average temperature, and reports of influenza-like illness (ILI).

A total of 3,372,993 patients were identified, with average age in each quarter ranging 72.2 to 73.9 years and overall mortality ranging 4.3% to 6.4%. The CHF discharges within each year peaked from October through December and nadired from April through June with an increasing overall time trend. Significant correlation was found between CHF discharge and the average temperature (P <.001), with approximately 331.8 less CHF discharges (SE = 91.7) per degree of increase in temperature. However, no significant correlation was found between CHF discharges and frequency of cyclones, the maximum wind speed, and reported ILI.

This study suggests that with the current methods and the HCUP dataset, there is no significant increase in overall CHF discharges in Florida as a result of recent previous cyclone occurrences.

Although multiple studies have revealed that coronavirus disease 2019 (COVID-19) vaccines can reduce COVID-19–related outcomes, little is known about their impact on post–COVID-19 conditions. We performed a systematic literature review and meta-analysis on the effectiveness of COVID-19 vaccination against post–COVID-19 conditions (ie, long COVID).

We searched PubMed, CINAHL, EMBASE, Cochrane Central Register of Controlled Trials, Scopus, and Web of Science from December 1, 2019, to April 27, 2022, for studies evaluating COVID-19 vaccine effectiveness against post–COVID-19 conditions among individuals who received at least 1 dose of Pfizer/BioNTech, Moderna, AstraZeneca, or Janssen vaccine. A post–COVID-19 condition was defined as any symptom that was present 3 or more weeks after having COVID-19. Editorials, commentaries, reviews, study protocols, and studies in the pediatric population were excluded. We calculated the pooled diagnostic odds ratios (DORs) for post–COVID-19 conditions between vaccinated and unvaccinated individuals. Vaccine effectiveness was estimated as 100% × (1 − DOR).

In total, 10 studies with 1,600,830 individuals evaluated the effect of vaccination on post–COVID-19 conditions, of which 6 studies were included in the meta-analysis. The pooled DOR for post–COVID-19 conditions among individuals vaccinated with at least 1 dose was 0.708 (95% confidence interval (CI), 0.692–0.725) with an estimated vaccine effectiveness of 29.2% (95% CI, 27.5%–30.8%). The vaccine effectiveness was 35.3% (95% CI, 32.3%–38.1%) among those who received the COVID-19 vaccine before having COVID-19, and 27.4% (95% CI, 25.4%–29.3%) among those who received it after having COVID-19.

COVID-19 vaccination both before and after having COVID-19 significantly decreased post–COVID-19 conditions for the circulating variants during the study period although vaccine effectiveness was low.

Informed consent forms (ICFs) and practices vary widely across institutions. This project expands on previous work at the University of Arkansas for Medical Sciences (UAMS) Center for Health Literacy to develop a plain language ICF template. Our interdisciplinary team of researchers, comprised of biomedical informaticists, health literacy experts, and stakeholders in the Institutional Review Board (IRB) process, has developed the ICF Navigator, a novel tool to facilitate the creation of plain language ICFs that comply with all relevant regulatory requirements.

Our team first developed requirements for the ICF Navigator tool. The tool was then implemented by a technical team of informaticists and software developers, in consultation with an informed consent legal expert. We developed and formalized a detailed knowledge map modeling regulatory requirements for ICFs, which drives workflows within the tool.

The ICF Navigator is a web-based tool that guides researchers through creating an ICF as they answer questions about their project. The navigator uses those responses to produce a clear and compliant ICF, displaying a real-time preview of the final form as content is added. Versioning and edits can be tracked to facilitate collaborative revisions by the research team and communication with the IRB. The navigator helps guide the creation of study-specific language, ensures compliance with regulatory requirements, and ensures that the resulting ICF is easy to read and understand.

The ICF Navigator is an innovative, customizable, open-source software tool that helps researchers produce custom readable and compliant ICFs for research studies involving human subjects.

Cognitive development after schizophrenia onset can be shaped by interventions such as cognitive remediation, yet no study to date has investigated whether patterns of early behavioral development may predict later cognitive changes following intervention. We therefore investigated the extent to which premorbid adjustment trajectories predict cognitive remediation gains in schizophrenia.

In a total sample of 215 participants (170 first-episode schizophrenia participants and 45 controls), we classified premorbid functioning trajectories from childhood through late adolescence using the Cannon-Spoor Premorbid Adjustment Scale. For the 62 schizophrenia participants who underwent 6 months of computer-assisted, bottom-up cognitive remediation interventions, we identified MATRICS Consensus Cognitive Battery scores for which participants demonstrated mean changes after intervention, then evaluated whether developmental trajectories predicted these changes.

Growth mixture models supported three premorbid functioning trajectories: stable-good, deteriorating, and stable-poor adjustment. Schizophrenia participants demonstrated significant cognitive remediation gains in processing speed, verbal learning, and overall cognition. Notably, participants with stable-poor trajectories demonstrated significantly greater improvements in processing speed compared to participants with deteriorating trajectories.

This is the first study to our knowledge to characterize the associations between premorbid functioning trajectories and cognitive remediation gains after schizophrenia onset, indicating that 6 months of bottom-up cognitive remediation appears to be sufficient to yield a full standard deviation gain in processing speed for individuals with early, enduring functioning difficulties. Our findings highlight the connection between trajectories of premorbid and postmorbid functioning in schizophrenia and emphasize the utility of considering the lifespan developmental course in personalizing therapeutic interventions.

Health workforce development is essential for achieving the goals of an effective health system, as well as establishing national Health Emergency and Disaster Risk Management (Health EDRM).

The objective of this Delphi consensus study was to identify strategic recommendations for strengthening the workforce for Health EDRM in low- and middle-income countries (LMIC) and high-income countries (HIC).

A total of 31 international experts were asked to rate the level of importance (one being strongly unimportant to seven being strongly important) for 46 statements that contain recommendations for strengthening the workforce for Health EDRM. The experts were divided into a LMIC group and an HIC group. There were three rounds of rating, and statements that did not reach consensus (SD ≥ 1.0) proceeded to the next round for further ranking.

In total, 44 statements from the LMIC group and 34 statements from the HIC group attained consensus and achieved high mean scores for importance (higher than five out of seven). The components of the World Health Organization (WHO) Health EDRM Framework with the highest number of recommendations were “Human Resources” (n = 15), “Planning and Coordination” (n = 7), and “Community Capacities for Health EDRM” (n = 6) in the LMIC group. “Policies, Strategies, and Legislation” (n = 7) and “Human Resources” (n = 7) were the components with the most recommendations for the HIC group.

The expert panel provided a comprehensive list of important and actionable strategic recommendations on workforce development for Health EDRM.