The ability to remotely monitor cognitive skills is increasing with the ubiquity of smartphones. The Mobile Toolbox (MTB) is a new measurement system that includes measures assessing Executive Functioning (EF) and Processing Speed (PS): Arrow Matching, Shape-Color Sorting, and Number-Symbol Match. The purpose of this study was to assess their psychometric properties.

MTB measures were developed for smartphone administration based on constructs measured in the NIH Toolbox® (NIHTB). Psychometric properties of the resulting measures were evaluated in three studies with participants ages 18 to 90. In Study 1 (N = 92), participants completed MTB measures in the lab and were administered both equivalent NIH TB measures and other external measures of similar cognitive constructs. In Study 2 (N = 1,021), participants completed the equivalent NIHTB measures in the lab and then took the MTB measures on their own, remotely. In Study 3 (N = 168), participants completed MTB measures twice remotely, two weeks apart.

All three measures exhibited very high internal consistency and strong test-retest reliability, as well as moderately high correlations with comparable NIHTB tests and moderate correlations with external measures of similar constructs. Phone operating system (iOS vs. Android) had a significant impact on performance for Arrow Matching and Shape-Color Sorting, but no impact on either validity or reliability.

Results support the reliability and convergent validity of MTB EF and PS measures for use across the adult lifespan in remote, self-administered designs.

Type 2 diabetes (T2DM) poses a significant public health challenge, with pronounced disparities in control and outcomes. Social determinants of health (SDoH) significantly contribute to these disparities, affecting healthcare access, neighborhood environments, and social context. We discuss the design, development, and use of an innovative web-based application integrating real-world data (electronic health record and geospatial files), to enhance comprehension of the impact of SDoH on T2 DM health disparities.

We identified a patient cohort with diabetes from the institutional Diabetes Registry (N = 67,699) within the Duke University Health System. Patient-level information (demographics, comorbidities, service utilization, laboratory results, and medications) was extracted to Tableau. Neighborhood-level socioeconomic status was assessed via the Area Deprivation Index (ADI), and geospatial files incorporated additional data related to points of interest (i.e., parks/green space). Interactive Tableau dashboards were developed to understand risk and contextual factors affecting diabetes management at the individual, group, neighborhood, and population levels.

The Tableau-powered digital health tool offers dynamic visualizations, identifying T2DM-related disparities. The dashboard allows for the exploration of contextual factors affecting diabetes management (e.g., food insecurity, built environment) and possesses capabilities to generate targeted patient lists for personalized diabetes care planning.

As part of a broader health equity initiative, this application meets the needs of a diverse range of users. The interactive dashboard, incorporating clinical, sociodemographic, and environmental factors, enhances understanding at various levels and facilitates targeted interventions to address disparities in diabetes care and outcomes. Ultimately, this transformative approach aims to manage SDoH and improve patient care.

Pediatric medical devices lag behind adult devices due to economic barriers, smaller patient populations, changing anatomy and physiology of patients, regulatory hurdles, and especially difficulties in executing clinical trials. We investigated the requirements, challenges, associated timeline, and costs of conducting a multi-site pivotal clinical trial for a Class II pediatric physiologic monitoring device.

This case study focused on the negotiation of clinical trial agreements (CTAs), budgets, and Institutional Review Board (IRB) processing times for a pediatric device trial. We identified key factors contributing to delays in clinical trial execution and potential best practices to expedite the process while maintaining safety, ethics, and efficacy.

The total time from site contact to first patient enrollment averaged 14 months. CTA and budget negotiations were the most time-consuming processes, averaging nearly 10 and 9 months, respectively. Reliance and local IRB processing also contributed significantly to the timeline, overall adding an average of 6.5 months across institutions. Nearly half of all costs were devoted to regulatory oversight. The COVID-19 pandemic caused significant slowdowns and delays at multiple institutions during study enrollment. Despite these pandemic-induced delays, it is important to note that the issues and themes highlighted remain relevant and have post-pandemic applicability.

Our case study results underscore the importance of establishing efficient and standardized processing of CTAs, budget negotiations, and use of reliance IRBs to expedite clinical trial execution for pediatric devices. The findings also highlight the need for a national clinical trials network to streamline the clinical trial process.

To present validation evidence for the first eight cognitive measures available through Mobile Toolbox (MTB). These measures use a remote self-administered platform to assess language, working memory, episodic memory, executive function, and processing speed.

We used two separate samples, recruited as part of a larger study, to validate MTB measures. Sample I, comprised of 92 English-speaking adults ages 18-85, was used to assess internal consistency and construct validity. Participants were first administered “gold standard” cognitive measures (Wechsler Memory Scale-IV Verbal Paired Associates I and II; Wechsler Adult Intelligence Scale-IV Symbol Search, Digit Span, Coding, and Letter-Number Sequencing; Delis-Kaplan Executive Function System Color-Word Interference Test, Peabody Picture Vocabulary Test, Wechsler Individual Achievement Test-4 Spelling, and the Wisconsin Card Sorting Test), after which they completed MTB (pre-loaded on a study-provided smartphone) on their own. Internal consistency was evaluated using measure-appropriate indices (split-half reliability, Cronbach’s alpha or IRT-based indices). Pearson correlation coefficients between MTB tests and measures of similar constructs were used to evaluate concurrent validity. For two tests with timing-dependent scores, Arrow Matching and Shape-Color Sorting, separate analyses were performed for iOS and Android devices. Sample II, with 1,120 English-speaking participants ages 18-90, was used to evaluate age-related change. Participants completed MTB measures remotely on their own smartphones, in a preset order, within a 14-day period. Spearman correlation coefficients, corrected for education, were calculated to evaluate relationships between age and test scores.

Sample I participants were 67% female, 52% white, 99% non-Hispanic; average age=48 (SD= 17). Education was: < high school (1%); high school (55%); some college (21%); college (15%); graduate degree (8%). Internal consistency estimates ranged from 0.81 to 0.99. Pearson correlations between MTB and external measures ranged from 0.41 to 0.86 (all p < .01). Of the timed tests, only Shape-Color sorting showed significant score differences between Android and iOS devices. Sample II was 57% female, 13% Hispanic, 72% white, mean age = 45 (SD = 21). Education distribution was: < high school (2%); high school (34%); some college (34%), college (20%); graduate degree (11%). Measures of executive function (r = -0.50; r=-0.57) and processing speed (r= -0.61) showed the expected negative correlation with age (all p <0.001). Negative correlations, although weaker, were also seen on measures of working memory (r=-0.2) and episodic memory (r=-0.2, r=-0.37; p.<.001). Vocabulary performance improved with age (r=0.4; p<.001), while spelling scores remained stable (r=0.09).

Initial studies support the validity and reliability of the first eight MTB cognitive measures in two diverse samples. MTB tests showed satisfactory construct validity, as demonstrated by the associations between MTB and well-established tests. Furthermore, most MTB measures correlated with age in the expected directions. Executive function, processing speed and memory typically decrease with age and this decrease was reflected in MTB test performance. In contrast, spelling and vocabulary, typically preserved as we age, did not decrease in our sample. Our results support the use of MTB in cognitive aging research.

A critical need in the neuropsychology field is development and validation of efficient, scalable assessments of cognition. The Mobile Toolbox (MTB), a novel suite of mobile device-compatible, app-based cognitive assessments, was developed to address this need. The goals of this study were (1) To collect longitudinal normative data for the MTB assessments in a large, ethnoculturally and educationally diverse cohort; (2) To assess the feasibility and usability of remote assessment using MTB.

Participants were recruited from the UCSF Brain Health Registry (BHR), an online cohort (N>100,000) that collects longitudinal cognitive, functional, behavioral, and health data using online neuropsychological tests and self- and study-partner report surveys. BHR participants who opted to learning about additional research opportunities were sent automated email invitations to enroll in the MTB study. Those who indicated study interest were provided instructions within the BHR online portal for downloading the MTB app. All participants had the opportunity to complete a single baseline administration of MTB (Word Meaning, Sequences, Spelling, Arranging Pictures, Arrow Matching, Faces and Names, Shape-Color Sorting, Number Match). Those who completed the baseline assessment within three days were invited to continue into the longitudinal study, where they complete MTB assessments at a single, short-term timepoint (day 7, 14, or 21; study arms sequentially assigned), and then at 6-month intervals. Enrollment across demographic groups was monitored, and study invitations were sent to specific demographic groups, with the goal of enrolling a sample of 800 participants in the longitudinal study: equal distribution across eight, 10-year age bands (ages 18-80+); 60% with <16 years of education; 10% non-Latinx Black, 15% Latinx, and 5% non-White other ethnocultural identity.

Between January-June 2022, 48,110 BHR participants were invited to the MTB study. Of those, 8294 (17%) expressed interest, 3401 (7%) completed the baseline assessment, 850 (1.8%) were assigned to the longitudinal study, and 782 (1.6%) completed a short-term longitudinal assessment. Study staff received 797 help tickets submitted by participants asking for email support to complete MTB. The baseline cohort had and average age of 64 years and an average of 16.6 years of education, 76.2% female, 2.1% non-Latinx Black, 7.1% Latinx, 86.8% non-Latinx White, and 4% from other ethnocultural groups. The longitudinal cohort had an average age of 62.3 years and an average of 16.1 years of education, 80% female, 2.8% non-Latinx Black, 8.5% Latinx, 83.5% non-Latinx White; and 5% other ethnocultural group. Compared to those invited to the study, those who enrolled in the longitudinal study were older, had higher educational attainment, and were more likely to be female and self-identify as non-Latinx White (p<0.05 for all).

Efficient enrollment and task completion of a large cohort in a novel, app-based mobile cognitive assessment is feasible in a completely remote setting. Most participants were able to complete MTB without individual support, indicating good usability. This approach can be scaled up to efficiently assess cognition in many research and healthcare settings. A remaining challenge is achieving robust ethnocultural and educational diversity.

The cardiovascular adaptations associated with structured exercise training in Fontan patients remain unknown. We hypothesised that short-term training causes cardiac remodelling and parallel improvement in maximal exercise capacity (VO2 max) in these patients.

Five patients, median age 19.5 (17.6–21.3) years, with a history of Fontan operation meeting inclusion/exclusion criteria, participated in a 3-month training programme designed to improve endurance. Magnetic resonance images for assessment of cardiac function, fibrosis, cardiac output, and liver elastography to assess stiffness were obtained at baseline and after training. Maximal exercise capacity (VO2 max) and cardiac output Qc (effective pulmonary blood flow) at rest and during exercise were measured (C2H2 rebreathing) at the same interval. VO2 max increased from median (IQR) 27.2 (26–28.7) to 29.6 (28.5–32.2) ml/min/kg (p = 0.04). There was an improvement in cardiac output (Qc) during maximal exercise testing from median (IQR) 10.3 (10.1–12.3) to 12.3 (10.9–14.9) l/min, but this change was variable (p = 0.14). Improvement in VO2 max correlated with an increase in ventricular mass (r = 0.95, p = 0.01), and improvement in Quality-of-life inventory (PedsQL) Cardiac scale scores for patient-reported symptoms (r = 0.90, p = 0.03) and cognitive problems (r = 0.89, p = 0.04). The correlation between VO2 max and Qc showed a positive trend but was not significant (r = 0.8, p = 0.08). No adverse cardiac or liver adaptations were noted.

Short-term training improved exercise capacity in this Fontan pilot without any adverse cardiac or liver adaptations. These results warrant further study in a larger population and over a longer duration of time.

NCT03263312, Unique Protocol ID: STU 122016-037; Registration Date: 18 January, 2017.

Determination of whether vascular catheter disinfecting antiseptic-containing caps alone are effective at decreasing microbial colonization of connectors compared to antiseptic-containing caps plus a 5-second alcohol manual disinfection.

The study was conducted in a 718-bed, tertiary-care, academic hospital.

A convenience sample of adult patients across intensive care units and acute care wards with peripheral and central venous catheters covered with antiseptic-containing caps.

Quality improvement study completed over 5 days. The standard-of-care group consisted of catheter connectors with antiseptic-containing caps cleaned with a 5-second alcohol wipe scrub prior to culture. The comparison group consisted of catheter connectors with antiseptic-containing caps without a 5-second alcohol wipe scrub prior to culture. The connectors were pressed directly onto blood agar plates and incubated. Plates were assessed for growth after 48-72 hours.

In total, 356 catheter connectors were cultured: 165 in the standard-of-care group, 165 in the comparison group, and 26 catheters connectors without an antiseptic-containing cap, which were designated as controls. Overall, 18 catheter connectors (5.06%) yielded microbial growth. Of the 18 connectors with microbial growth, 2 (1.21%) were from the comparison group, 1 (0.61%) was from the standard-of-care group, and 15 were controls without an antiseptic-containing cap.

Bacterial colonization rates were similar between the catheter connectors cultured with antiseptic-containing caps alone and catheter connectors with antiseptic-containing caps cultured after a 5-second scrub with alcohol. This finding suggests that the use of antiseptic-containing caps precludes the need for additional disinfection.

Mental health problems are elevated in autistic individuals but there is limited evidence on the developmental course of problems across childhood. We compare the level and growth of anxious-depressed, behavioral and attention problems in an autistic and typically developing (TD) cohort.

Latent growth curve models were applied to repeated parent-report Child Behavior Checklist data from age 2–10 years in an inception cohort of autistic children (Pathways, N = 397; 84% boys) and a general population TD cohort (Wirral Child Health and Development Study; WCHADS; N = 884, 49% boys). Percentile plots were generated to quantify the differences between autistic and TD children.

Autistic children showed elevated levels of mental health problems, but this was substantially reduced by accounting for IQ and sex differences between the autistic and TD samples. There was small differences in growth patterns; anxious-depressed problems were particularly elevated at preschool and attention problems at late childhood. Higher family income predicted lower base-level on all three dimensions, but steeper increase of anxious-depressed problems. Higher IQ predicted lower level of attention problems and faster decline over childhood. Female sex predicted higher level of anxious-depressed and faster decline in behavioral problems. Social-affect autism symptom severity predicted elevated level of attention problems. Autistic girls' problems were particularly elevated relative to their same-sex non-autistic peers.

Autistic children, and especially girls, show elevated mental health problems compared to TD children and there are some differences in predictors. Assessment of mental health should be integrated into clinical practice for autistic children.

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.

Current psychiatric diagnoses, although heritable, have not been clearly mapped onto distinct underlying pathogenic processes. The same symptoms often occur in multiple disorders, and a substantial proportion of both genetic and environmental risk factors are shared across disorders. However, the relationship between shared symptoms and shared genetic liability is still poorly understood.

Well-characterised, cross-disorder samples are needed to investigate this matter, but few currently exist. Our aim is to develop procedures to purposely curate and aggregate genotypic and phenotypic data in psychiatric research.

As part of the Cardiff MRC Mental Health Data Pathfinder initiative, we have curated and harmonised phenotypic and genetic information from 15 studies to create a new data repository, DRAGON-Data. To date, DRAGON-Data includes over 45 000 individuals: adults and children with neurodevelopmental or psychiatric diagnoses, affected probands within collected families and individuals who carry a known neurodevelopmental risk copy number variant.

We have processed the available phenotype information to derive core variables that can be reliably analysed across groups. In addition, all data-sets with genotype information have undergone rigorous quality control, imputation, copy number variant calling and polygenic score generation.

DRAGON-Data combines genetic and non-genetic information, and is available as a resource for research across traditional psychiatric diagnostic categories. Algorithms and pipelines used for data harmonisation are currently publicly available for the scientific community, and an appropriate data-sharing protocol will be developed as part of ongoing projects (DATAMIND) in partnership with Health Data Research UK.