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The coronavirus disease (COVID-19) pandemic disrupted healthcare and clinical research, including a suite of 11 pragmatic clinical trials (PCTs), across clinics within the Department of Veterans Affairs (VA) and the Department of Defense (DOD). These PCTs were designed to evaluate an array of nonpharmacological treatments and models of care for treatment of patients with pain and co-occurring conditions. The aims of the study are to (a) describe modifications to PCTs and interventions to address the evolving pandemic and (b) describe the application of implementation science methods for evaluation of those PCT modifications. The project used a two-phase, sequential, mixed-methods design. In Phase I, we captured PCT disruptions and modifications via a Research Electronic Data Capture questionnaire, using Periodic Reflections methods as a guide. In Phase II, we utilized the Framework for Reporting Adaptations and Modifications-Expanded (FRAME) taxonomy to develop a focus group interview guide and checklist that would provide more in-depth data than Phase I. Data were analyzed using directed content analysis. Phase I revealed that all PCTs made between two and six trial modifications. Phase II, FRAME-guided analyses showed that the key goals for modifying interventions were increasing treatment feasibility and decreasing patient exposure to COVID-19, while preserving intervention core elements. Context (format) modifications led eight PCTs to modify parts of the interventions for virtual delivery. Content modifications added elements to enhance patient safety; tailored interventions for virtual delivery (counseling, exercise, mindfulness); and modified interventions involving manual therapies. Implementation science methods identified near-real-time disruptions and modifications to PCTs focused on pain management in veteran and military healthcare settings.

Personal intelligence concerns the ability to understand personality in oneself and others--including the understanding of motives, socioemotional traits, and abilities. We examined if people's scores on the ability-based "Test of Personal Intelligence (TOPI)" would be reflected in their narratives about someone whose personality they had learned about. In a Preliminary Study (N = 220), we collected narratives and open-ended descriptions about their learning. In Study 1 (N = 212), experts rated the respondents' open-ended narratives for their sophistication about personality, defined as their knowledge and complexity of thought around the topic. Respondents also filled out checklists concerning what they learned and their relationship outcomes. Study 2 (N = 299) was a replication and extension in which we added the TOPI. Participants who scored higher on the TOPI produced narratives higher in Sophistication, even after statistical controls for Word Count and Vocabulary (the measures also were largely independent of the Big Five). The findings here may have applications for both testing and training.

The Cattell-Horn-Carroll (CHC) or three-stratum model of intelligence envisions human intelligence as a hierarchy. General intelligence (g) is situated at the top, under which are a group of broad intelligences such as verbal, visuospatial processing, and quantitative knowledge that pertain to more specific areas of reasoning. Some broad intelligences are people-centered, including personal, emotional, and social intelligences; others concern reasoning about things more generally, such as visuospatial and quantitative knowledge. In the present research, we conducted a meta-analysis of 87 studies, including 2322 effect sizes, to examine the average correlation between people-to-people intelligences relative to the average correlation between people-to-thing-centered intelligences (and similar comparisons). Results clearly support the psychometric distinction between people-centered and thing-centered mental abilities. Coupled with evidence for incremental predictions from people-centered intelligences, our findings provide a secure foundation for continued research focused on people-centered mental abilities.

BackgroundDe novo genic and copy number variants are enriched in patients with congenital heart disease, particularly those with extra-cardiac anomalies. The impact of de novo damaging variants on outcomes following cardiac repair is unknown.MethodsWe studied 2517 patients with congenital heart disease who had undergone whole-exome sequencing as part of the CHD GENES study (Congenital Heart Disease Genetic Network).ResultsTwo hundred ninety-four patients (11.7%) had clinically significant de novo variants. Patients with de novo damaging variants were 2.4 times more likely to have extra-cardiac anomalies (P=5.63×10-12). In 1268 patients (50.4%) who had surgical data available and underwent open-heart surgery exclusive of heart transplantation as their first operation, we analyzed transplant-free survival following the first operation. Median follow-up was 2.65 years. De novo variants were associated with worse transplant-free survival (hazard ratio, 3.51; P=5.33×10-04) and longer times to final extubation (hazard ratio, 0.74; P=0.005). As de novo variants had a significant interaction with extra-cardiac anomalies for transplant-free survival (P=0.003), de novo variants conveyed no additional risk for transplant-free survival for patients with these anomalies (adjusted hazard ratio, 1.96; P=0.06). By contrast, de novo variants in patients without extra-cardiac anomalies were associated with worse transplant-free survival during follow-up (hazard ratio, 11.21; P=1.61×10-05) than that of patients with no de novo variants. Using agnostic machine-learning algorithms, we identified de novo copy number variants at 15q25.2 and 15q11.2 as being associated with worse transplant-free survival and 15q25.2, 22q11.21, and 3p25.2 as being associated with prolonged time to final extubation.ConclusionsIn patients with congenital heart disease undergoing open-heart surgery, de novo variants were associated with worse transplant-free survival and longer times on the ventilator. De novo variants were most strongly associated with adverse outcomes among patients without extra-cardiac anomalies, suggesting a benefit for preoperative genetic testing even when genetic abnormalities are not suspected during routine clinical practice. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01196182.

BackgroundPatients undergoing complex pediatric cardiac surgery remain at considerable risk of mortality and morbidity, and variation in outcomes exists across hospitals. The Pediatric Cardiac Critical Care Consortium (PC4) was formed to improve the quality of care for these patients through transparent data sharing and collaborative learning between participants.ObjectivesThe purpose of this study was to determine whether outcomes improved over time within PC4.MethodsThe study analyzed 19,600 hospitalizations (18 hospitals) in the PC4 clinical registry that included cardiovascular surgery from August 2014 to June 2018. The primary exposure was 2 years of PC4 participation; this provided adequate time for hospitals to accrue data and engage in collaborative learning. Aggregate case mix-adjusted outcomes were compared between the first 2 years of participation (baseline) and all months post-exposure. We also evaluated outcomes from the same era in a cohort of similar, non-PC4 hospitals.ResultsDuring the baseline period, there was no evidence of improvement. We observed significant improvement in the post-exposure period versus baseline for post-operative intensive care unit mortality (2.1% vs. 2.7%; 22% relative reduction [RR]; p = 0.001), in-hospital mortality (2.5% vs. 3.3%; 24% RR; p = 0.001), major complications (10.1% vs. 11.5%; 12% RR; p

We employ a new approach for classifying methods of personality measurement such as self-judgment, mental ability, and lifespace measures and the data they produce. We divide these measures into two fundamental groups: personal-source data, which arise from the target person's own reports, and external-source data, which derive from the areas surrounding the person. These two broad classes are then further divided according to what they target and the response processes that produce them. We use the model to organize roughly a dozen kinds of data currently employed in the field. With this classification system in hand, we describe how much we might expect two types of measures of the same attribute to converge—and explain why methods often yield somewhat different results. Given that each measurement method has its own strengths and weaknesses, we examine the pros and cons of selecting a given type of measure to assess a specific area of personality. [ABSTRACT FROM AUTHOR]