Assessing Dynamic Cognitive Function in the Daily Lives of Youths With and Without Type 1 Diabetes: Usability Study.

Studies have shown a relationship between worse glycemic control and lower cognitive scores in youths with type 1 diabetes (T1D). However, most studies assess long-term glucose control (eg, years-decades) and cognition at a single time point. Understanding this relationship at a higher temporal resolution (eg, minutes-hours) and in naturalistic settings has potential clinical implications. Newer technology (eg, continuous glucose monitoring [CGM] and ecological momentary assessment) provides a unique opportunity to explore the glucose dynamics that influence dynamic cognition; that is, cognitive functions that fluctuate short-term and are influenced by environmental factors. Before we can assess this relationship, we need to determine the feasibility of measuring cognition in youths in daily life and determine the plausibility of obtaining glucose variation with CGM to be integrated with real-time cognition measures. This study's purpose was to assess the acceptability of measuring dynamic cognition using a smartphone app and adherence to cognitive testing in daily life in youths with and without T1D. Further, we assessed CGM-derived glucose measures at temporally related timeframes to cognitive testing in naturalistic settings. Data were obtained from 3 studies including one in-laboratory study and 2 remote studies. For all studies, youths were asked to complete cognitive tests on the Ambulatory Research in Cognition (ARC) smartphone app that measured processing speed, associative memory, and working memory. For the in-laboratory study, youths completed testing 4 times during 1 session. For the remote studies, youths were asked to complete cognitive tests 5 times per day for either 10 or 14 consecutive days in daily life. Youths were asked to rate their impressions of the app. Youths with T1D wore a CGM. 74 youths (n=53 control; n=21 T1D) aged 4-16 years participated. Youths generally reported liking or understanding the ARC app tasks in a laboratory and remote setting. Youths had high testing adherence in daily life (2350/3080 to 721/900, 76.3%-80.2%) and none dropped out. The percentage of measurements within each glycemic range taken immediately before the app's cognitive testing was 3% (28/942) low glucose, 51% (484/942) euglycemia, 23% (221/942) high glucose, and 22% (210/942) very high glucose. In the 2-hour window before each cognitive task, mean glucose was 182.5 (SD 76.2) mg/dL, SD in glucose was 27.1 mg/dL (SD 18.7), and the mean maximum difference between the highest and lowest glucose was 85.5 (SD 53.7) mg/dL. The results suggest that using the ARC smartphone app to assess dynamic cognitive functions in youths with and without T1D is feasible. Further, we showed CGM-derived glycemic variability at temporally associated timeframes of dynamic cognitive assessments. The next steps include using ecological momentary assessment in a fully powered study to determine the relationship between short-term glycemic control and cognition in youths with T1D.

Ray MK ，Fleming J ，Aschenbrenner A ，Hassenstab J ，Redwine B ，Burns C ，Arbelaez AM ，Vajravelu ME ，Hershey T ... -  《-》

Characterizing Performance on a Suite of English-Language NeuroUX Mobile Cognitive Tests in a US Adult Sample: Ecological Momentary Cognitive Testing Study.

Mobile cognitive testing is growing in popularity, with numerous advantages over traditional cognitive testing; however, the field lacks studies that deeply examine mobile cognitive test data from general adult samples. This study characterized performance for a suite of 8 mobile cognitive tests from the NeuroUX platform in a sample of US adults across the adult lifespan. Overall, 393 participants completed 8 NeuroUX cognitive tests and a brief ecological momentary assessment survey once per day on their smartphones for 10 consecutive days; each test was administered 5 times over the testing period. The tests tapped the domains of executive function, processing speed, reaction time, recognition memory, and working memory. Participants also completed a poststudy usability feedback survey. We examined alternate form test-retest reliability; practice effects; and associations between scores (averages and intraindividual variability) and demographics as well as test-taking context (ie, smartphone type, being at home vs not at home, and being alone vs not alone). Our final sample consisted of 393 English-speaking US residents (aged 20-79 y; female: n=198, 50.4%). Of the 367 participants who provided responses about their race and ethnicity, 258 (70.3%) were White. Of the 393 participants, 181 (46.1%) were iOS users, and 212 (53.9%) were Android users. Of 12 test scores derived from the 8 tests, 9 (75%) showed good to excellent test-retest reliability (intraclass correlation coefficients >0.76). Practice effects (ie, improvements in performance) were observed for 4 (33%) of the 12 scores. Older age was associated with worse performance on most of the test scores (9/12, 75%) and greater within-person variability for nearly all reaction time scores (3/4, 75%). Relationships with smartphone type showed better performance among iOS users and those with newer Android software versions compared to those with older software. Being at home (vs not at home) was associated with better performance on tests of processing speed. Being alone (vs not alone) was associated with better performance on tests of recognition and working memory. Poststudy feedback indicated that participants found NeuroUX easy to learn and use, an enjoyable experience, and an app that would be helpful in understanding their thinking skills. Only 4.2% (16/379) endorsed privacy concerns, and 77.3% (293/379) reported that they would be willing to share their results with their health care provider. Older age-but not other demographics-was associated with finding the tests more challenging. In a sample of adults across a wide age range, this study characterized features that are particularly important for the interpretation of remote, repeated mobile cognitive testing performance, including test-retest reliability, practice effects, smartphone type, and test-taking context. These data enhance the understanding and application of mobile cognitive testing, paving the way for improved clinical decision-making, personalized interventions, and advancements in cognitive research.

Paolillo EW ，Bomyea J ，Depp CA ，Henneghan AM ，Raj A ，Moore RC ... -  《JOURNAL OF MEDICAL INTERNET RESEARCH》

Mortality impact, risks, and benefits of general population screening for ovarian cancer: the UKCTOCS randomised controlled trial.

Menon U ，Gentry-Maharaj A ，Burnell M ，Ryan A ，Kalsi JK ，Singh N ，Dawnay A ，Fallowfield L ，McGuire AJ ，Campbell S ，Skates SJ ，Parmar M ，Jacobs IJ ... -  《-》

Defining the optimum strategy for identifying adults and children with coeliac disease: systematic review and economic modelling.

Elwenspoek MM ，Thom H ，Sheppard AL ，Keeney E ，O'Donnell R ，Jackson J ，Roadevin C ，Dawson S ，Lane D ，Stubbs J ，Everitt H ，Watson JC ，Hay AD ，Gillett P ，Robins G ，Jones HE ，Mallett S ，Whiting PF ... -  《-》

Examining Share plus-A Continuous Glucose Monitoring Plus Data-Sharing Intervention in Older Adults and Their Care Partners: Protocol for a Randomized Control Study.

Older adults with type 1 diabetes (T1D) are increasingly turning to care partners (CPs) as resources to support their diabetes management. With the rise in diabetes technologies, such as continuous glucose monitoring (CGM), there is great potential for CGM data sharing to increase CP involvement in a way that improves persons with diabetes' glucose management and reduces distress. The specific aims of this paper are to (1) evaluate the feasibility, usability, and acceptability of the Share plus intervention compared to the CGM Follow app plus diabetes self-management education and support; (2) evaluate the effect of the Share plus intervention on time-in-range (TIR; primary outcome) and diabetes distress (secondary outcome); and (3) explore differences between groups in person with diabetes and CP dyadic appraisal and coping, quality of life, diabetes self-care, and CP burden at 12 and 24 weeks and associations of dyadic variables on outcomes. This is a protocol for a feasibility, pilot randomized controlled trial. Older adults with T1D and their CP (N=80 dyads) will be randomized 1:1 to the Share plus intervention or Follow app plus diabetes self-management education. The trial will include a 12-week active intervention to determine the change in primary (TIR) and secondary (diabetes distress) outcomes, followed by a 12-week, observation-only phase to examine maintenance effects. The evaluation is guided by the Dyadic Coping Model. Patient-level effectiveness outcomes (TIR, hemoglobin A1c [HbA1c], diabetes distress, diabetes appraisal, coping, quality of life, diabetes self-care behaviors, and CP burden) will be assessed, using patient-reported outcomes measures and a home HbA1c test kit. Patient- and CP-level acceptability and feasibility will be assessed using surveys and interviews. Quantitative feasibility, acceptability, and usability data will be described using frequencies and percentages. Acceptability will be summarized based on Likert questions and open-ended questions. Usability will be examined separately for the intervention and control groups based on the System Usability Scale, with a study benchmark of ≥68 indicating good usability. TIR will be computed based on 2 weeks' worth of data at baseline (prior to intervention) and 2 weeks each after the intervention (week 12) and at follow-up (week 24). Recruitment started in August 2023 and enrollment began in November 2023. To date, 24 participants have been enrolled in this study. We expect to conclude this study in March 2026 and expect to disseminate results in March 2026. To our knowledge, this will be the first pilot randomized controlled trial to evaluate both feasibility and effectiveness outcomes for the web-based, platform-delivered Share plus intervention for older adults with T1D and their CP. This research has implications for CGM data sharing in other age groups with T1D and type 2 diabetes. ClinicalTrials.gov NCT05937321; https://clinicaltrials.gov/study/NCT05937321. DERR1-10.2196/60004.

Allen NA ，Berg CA ，Iacob E ，Gonzales BR ，Butner JE ，Litchman ML ... -  《JMIR Research Protocols》