Real-life ankle submovements and computer mouse use reflect patient-reported function in adult ataxias.

Novel disease-modifying therapies are being evaluated in spinocerebellar ataxias and multiple system atrophy. Clinician-performed disease rating scales are relatively insensitive for measuring disease change over time, resulting in large and long clinical trials. We tested the hypothesis that sensors worn continuously at home during natural behaviour and a web-based computer mouse task performed at home could produce interpretable, meaningful and reliable motor measures for potential use in clinical trials. Thirty-four individuals with degenerative ataxias (spinocerebellar ataxia types 1, 2, 3 and 6 and multiple system atrophy of the cerebellar type) and eight age-matched controls completed the cross-sectional study. Participants wore an ankle and wrist sensor continuously at home for 1 week and completed the Hevelius computer mouse task eight times over 4 weeks. We examined properties of motor primitives called 'submovements' derived from the continuous wearable sensors and properties of computer mouse clicks and trajectories in relationship to patient-reported measures of function (Patient-Reported Outcome Measure of Ataxia) and ataxia rating scales (Scale for the Assessment and Rating of Ataxia and the Brief Ataxia Rating Scale). The test-retest reliability of digital measures and differences between ataxia and control participants were evaluated. Individuals with ataxia had smaller, slower and less powerful ankle submovements during natural behaviour at home. A composite measure based on ankle submovements strongly correlated with ataxia rating scale scores (Pearson's r = 0.82-0.88), strongly correlated with self-reported function (r = 0.81), had high test-retest reliability (intraclass correlation coefficient = 0.95) and distinguished ataxia and control participants, including preataxic individuals (n = 4) from controls. A composite measure based on computer mouse movements and clicks strongly correlated with ataxia rating scale total (r = 0.86-0.88) and arm scores (r = 0.65-0.75), correlated well with self-reported function (r = 0.72-0.73) and had high test-retest reliability (intraclass correlation coefficient = 0.99). These data indicate that interpretable, meaningful and highly reliable motor measures can be obtained from continuous measurement of natural movement, particularly at the ankle location, and from computer mouse movements during a simple point-and-click task performed at home. This study supports the use of these two inexpensive and easy-to-use technologies in longitudinal natural history studies in spinocerebellar ataxias and multiple system atrophy of the cerebellar type and shows promise as potential motor outcome measures in interventional trials.

Sex and age differences in "theory of mind" across 57 countries using the English version of the "Reading the Mind in the Eyes" Test.

The "Reading the Mind in the Eyes" Test (Eyes Test) is a widely used assessment of "theory of mind." The NIMH Research Domain Criteria recommends it as one of two tests for "understanding mental states." Previous studies have demonstrated an on-average female advantage on the Eyes Test. However, it is unknown whether this female advantage exists across the lifespan and across a large number of countries. Thus, we tested sex and age differences using the English version of the Eyes Test in adolescents and adults across 57 countries. We also tested for associations with sociodemographic and cognitive/personality factors. We leveraged one discovery dataset (N = 305,726) and three validation datasets (Ns = 642; 5,284; and 1,087). The results show that: i) there is a replicable on-average female advantage in performance on the Eyes Test; ii) performance increases through adolescence and shallowly declines across adulthood; iii) the on-average female advantage is evident across the lifespan; iv) there is a significant on-average female advantage in 36 out of 57 countries; v) there is a significant on-average female advantage on translated (non-English) versions of the Eyes Test in 12 out of 16 countries, as confirmed by a systematic review; vi) D-scores, or empathizing-systemizing, predict Eyes Test performance above and beyond sex differences; and vii) the female advantage is negatively linked to "prosperity" and "autonomy," and positively linked to "collectivism," as confirmed by exploratory country-level analyses. We conclude that the on-average female advantage on the Eyes Test is observed across ages and most countries.

Barriers and Facilitators to the Implementation of Family-Centered Technology in Complex Care: Feasibility Study.

BACKGROUND: Care coordination is challenging but crucial for children with medical complexity (CMC). Technology-based solutions are increasingly prevalent but little is known about how to successfully deploy them in the care of CMC. OBJECTIVE: The aim of this study was to assess the feasibility and acceptability of GoalKeeper (GK), an internet-based system for eliciting and monitoring family-centered goals for CMC, and to identify barriers and facilitators to implementation. METHODS: We used the Consolidated Framework for Implementation Research (CFIR) to explore the barriers and facilitators to the implementation of GK as part of a clinical trial of GK in ambulatory clinics at a children's hospital (NCT03620071). The study was conducted in 3 phases: preimplementation, implementation (trial), and postimplementation. For the trial, we recruited providers at participating clinics and English-speaking parents of CMC<12 years of age with home internet access. All participants used GK during an initial clinic visit and for 3 months after. We conducted preimplementation focus groups and postimplementation semistructured exit interviews using the CFIR interview guide. Participant exit surveys assessed GK feasibility and acceptability on a 5-point Likert scale. For each interview, 3 independent coders used content analysis and serial coding reviews based on the CFIR qualitative analytic plan and assigned quantitative ratings to each CFIR construct (-2 strong barrier to +2 strong facilitator). RESULTS: Preimplementation focus groups included 2 parents (1 male participant and 1 female participant) and 3 providers (1 in complex care, 1 in clinical informatics, and 1 in neurology). From focus groups, we developed 3 implementation strategies: education (parents: 5-minute demo; providers: 30-minute tutorial and 5-minute video on use in a clinic visit; both: instructional manual), tech support (in-person, virtual), and automated email reminders for parents. For implementation (April 1, 2019, to December 21, 2020), we enrolled 11 providers (7 female participants, 5 in complex care) and 35 parents (mean age 38.3, SD 7.8 years; n=28, 80% female; n=17, 49% Caucasian; n=16, 46% Hispanic; and n=30, 86% at least some college). One parent-provider pair did not use GK in the clinic visit, and few used GK after the visit. In 18 parent and 9 provider exit interviews, the key facilitators were shared goal setting, GK's internet accessibility and email reminders (parents), and GK's ability to set long-term goals and use at the end of visits (providers). A key barrier was GK's lack of integration into the electronic health record or patient portal. Most parents (13/19) and providers (6/9) would recommend GK to their peers. CONCLUSIONS: Family-centered technologies like GK are feasible and acceptable for the care of CMC, but sustained use depends on integration into electronic health records. TRIAL REGISTRATION: ClinicalTrials.gov NCT03620071; https://clinicaltrials.gov/ct2/show/NCT03620071.

Free-Living Motor Activity Monitoring in Ataxia-Telangiectasia.

With disease-modifying approaches under evaluation in ataxia-telangiectasia and other ataxias, there is a need for objective and reliable biomarkers of free-living motor function. In this study, we test the hypothesis that metrics derived from a single wrist sensor worn at home provide accurate, reliable, and interpretable information about neurological disease severity in children with A-T.A total of 15 children with A-T and 15 age- and sex-matched controls wore a sensor with a triaxial accelerometer on their dominant wrist for 1 week at home. Activity intensity measures, derived from the sensor data, were compared with in-person neurological evaluation on the Brief Ataxia Rating Scale (BARS) and performance on a validated computer mouse task.Children with A-T were inactive the same proportion of each day as controls but produced more low intensity movements (p < 0.01; Cohen's d = 1.48) and fewer high intensity movements (p < 0.001; Cohen's d = 1.71). The range of activity intensities was markedly reduced in A-T compared to controls (p < 0.0001; Cohen's d = 2.72). The activity metrics correlated strongly with arm, gait, and total clinical severity (r: 0.71-0.87; p < 0.0001), correlated with specific computer task motor features (r: 0.67-0.92; p < 0.01), demonstrated high reliability (r: 0.86-0.93; p < 0.00001), and were not significantly influenced by age in the healthy control group.Motor activity metrics from a single, inexpensive wrist sensor during free-living behavior provide accurate and reliable information about diagnosis, neurological disease severity, and motor performance. These low-burden measurements are applicable independent of ambulatory status and are potential digital behavioral biomarkers in A-T.

Outcomes from Returning Individual versus Only Study-Wide Biomonitoring Results in an Environmental Exposure Study Using the Digital Exposure Report-Back Interface (DERBI).

BACKGROUND: Study participants want to receive their biomonitoring results for environmental chemicals, and ethics guidelines encourage reporting back. However, few studies have quantitively assessed participants' responses to individual exposure reports, and digital methods have not been evaluated. OBJECTIVES: We isolated effects of receiving personal results vs. only study-wide findings and investigated whether effects differed for Black participants. METHODS: We randomly assigned a subset of 295 women from the Child Health and Development Studies, half of whom were Black, to receive a report with personal environmental chemical results or only study-wide (aggregate) findings. Reports included results for 42 chemicals and lipids and were prepared using the Digital Exposure Report-Back Interface (DERBI). Women were interviewed before and after viewing their report. We analyzed differences in website activity, emotional responses, and intentions to participate in future research by report type and race using Wilcoxon rank sum tests, Wilcoxon-Pratt signed ranks tests, and multiple regression. RESULTS: The personal report group spent approximately twice as much time on their reports as the aggregate group before the post-report-back interview. Among personal-report participants (n=93), 84% (78) viewed chemical group information for at least one personal result highlighted on their home page; among aggregate-report participants (n=94), 66% (62) viewed any chemical group page. Both groups reported strong positive feelings (curious, informed, interested, respected) about receiving results before and after report-back and mild negative feelings (helpless, scared, worried). Although most participants remained unworried after report-back, worry increased by a small amount in both groups. Among Black participants, higher post report-back worry was associated with having high levels of chemicals. CONCLUSIONS: Participants were motivated by their personal results to access online information about chemical sources and potential health effects. Report-back was associated with a small increase in worry, which could motivate appropriate action. Personal report-back increased engagement with exposure reports among Black participants. https://doi.org/10.1289/EHP9072.

How machine-learning recommendations influence clinician treatment selections: the example of the antidepressant selection.

Decision support systems embodying machine learning models offer the promise of an improved standard of care for major depressive disorder, but little is known about how clinicians' treatment decisions will be influenced by machine learning recommendations and explanations. We used a within-subject factorial experiment to present 220 clinicians with patient vignettes, each with or without a machine-learning (ML) recommendation and one of the multiple forms of explanation. We found that interacting with ML recommendations did not significantly improve clinicians' treatment selection accuracy, assessed as concordance with expert psychopharmacologist consensus, compared to baseline scenarios in which clinicians made treatment decisions independently. Interacting with incorrect recommendations paired with explanations that included limited but easily interpretable information did lead to a significant reduction in treatment selection accuracy compared to baseline questions. These results suggest that incorrect ML recommendations may adversely impact clinician treatment selections and that explanations are insufficient for addressing overreliance on imperfect ML algorithms. More generally, our findings challenge the common assumption that clinicians interacting with ML tools will perform better than either clinicians or ML algorithms individually.

Conducting online virtual environment experiments with uncompensated, unsupervised samples.

Web-based experimentation with uncompensated and unsupervised samples allows for a larger and more diverse sample population, more generalizable results, and faster theory to experiment cycle. Given that participants are unsupervised, it is still unknown whether the data collected in such settings would be of sufficiently high quality to support robust conclusions. Therefore, we investigated the feasibility of conducting such experiments online using virtual environment technologies. We conducted a conceptual replication of two prior experiments that have been conducted in virtual environments. Our results replicate findings previously obtained in conventional laboratory settings. These results hold across different device types of participants (ranging from desktop, through mobile devices to immersive virtual reality headsets), suggesting that experiments can be conducted online with uncompensated samples in virtual environments.

Computer mouse use captures ataxia and parkinsonism, enabling accurate measurement and detection.

BACKGROUND: Objective assessments of movement impairment are needed to support clinical trials and facilitate diagnosis. The objective of the current study was to determine if a rapid web-based computer mouse test (Hevelius) could detect and accurately measure ataxia and parkinsonism. METHODS: Ninety-five ataxia, 46 parkinsonism, and 29 control participants and 229,017 online participants completed Hevelius. We trained machine-learning models on age-normalized Hevelius features to (1) measure severity and disease progression and (2) distinguish phenotypes from controls and from each other. RESULTS: Regression model estimates correlated strongly with clinical scores (from r = 0.66 for UPDRS dominant arm total to r = 0.83 for the Brief Ataxia Rating Scale). A disease change model identified ataxia progression with high sensitivity. Classification models distinguished ataxia or parkinsonism from healthy controls with high sensitivity (≥0.91) and specificity (≥0.90). CONCLUSIONS: Hevelius produces a granular and accurate motor assessment in a few minutes of mouse use and may be useful as an outcome measure and screening tool. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Evaluation of filesystem provenance visualization tools.

Having effective visualizations of filesystem provenance data is valuable for understanding its complex hierarchical structure. The most common visual representation of provenance data is the node-link diagram. While effective for understanding local activity, the node-link diagram fails to offer a high-level summary of activity and inter-relationships within the data. We present a new tool, InProv, which displays filesystem provenance with an interactive radial-based tree layout. The tool also utilizes a new time-based hierarchical node grouping method for filesystem provenance data we developed to match the user's mental model and make data exploration more intuitive. We compared InProv to a conventional node-link based tool, Orbiter, in a quantitative evaluation with real users of filesystem provenance data including provenance data experts, IT professionals, and computational scientists. We also compared in the evaluation our new node grouping method to a conventional method. The results demonstrate that InProv results in higher accuracy in identifying system activity than Orbiter with large complex data sets. The results also show that our new time-based hierarchical node grouping method improves performance in both tools, and participants found both tools significantly easier to use with the new time-based node grouping method. Subjective measures show that participants found InProv to require less mental activity, less physical activity, less work, and is less stressful to use. Our study also reveals one of the first cases of gender differences in visualization; both genders had comparable performance with InProv, but women had a significantly lower average accuracy (56%) compared to men (70%) with Orbiter.

Evaluation of artery visualizations for heart disease diagnosis.

Heart disease is the number one killer in the United States, and finding indicators of the disease at an early stage is critical for treatment and prevention. In this paper we evaluate visualization techniques that enable the diagnosis of coronary artery disease. A key physical quantity of medical interest is endothelial shear stress (ESS). Low ESS has been associated with sites of lesion formation and rapid progression of disease in the coronary arteries. Having effective visualizations of a patient's ESS data is vital for the quick and thorough non-invasive evaluation by a cardiologist. We present a task taxonomy for hemodynamics based on a formative user study with domain experts. Based on the results of this study we developed HemoVis, an interactive visualization application for heart disease diagnosis that uses a novel 2D tree diagram representation of coronary artery trees. We present the results of a formal quantitative user study with domain experts that evaluates the effect of 2D versus 3D artery representations and of color maps on identifying regions of low ESS. We show statistically significant results demonstrating that our 2D visualizations are more accurate and efficient than 3D representations, and that a perceptually appropriate color map leads to fewer diagnostic mistakes than a rainbow color map.