2024
Personal and Social‐Built Environmental Factors of Glucose Variability Among Multiethnic Groups of Adults With Type 2 Diabetes: Research Protocol Using Ecological Momentary Assessment, Continuous Glucose Monitoring, and Actigraphy
Nam S, Jeon S, Ash G, Weinzimer S, Dunton G, Parekh N, Grey M, Chen K, Lee M, Sajdlowska A, Whittemore R. Personal and Social‐Built Environmental Factors of Glucose Variability Among Multiethnic Groups of Adults With Type 2 Diabetes: Research Protocol Using Ecological Momentary Assessment, Continuous Glucose Monitoring, and Actigraphy. Research In Nursing & Health 2024, 47: 608-619. PMID: 39243147, DOI: 10.1002/nur.22420.Peer-Reviewed Original ResearchEmotional well-beingType 2 diabetesImprove diabetes outcomesDietary recall dataWell-beingSelf-report toolMultilevel risk factorsEcological momentary assessmentLifestyle behaviorsOnline video callsContinuous glucose monitoringPhysical activityDiabetes outcomesGroup of adultsLifestyle factorsJust-in-time interventionsBaseline surveyDiverse adultsDiabetes InterventionsHigh-risk groupRecall dataMomentary assessmentActigraphy deviceStructural equation modelingGlucose monitoring
2023
Personalized Digital Health Information to Substantiate Human-Delivered Exercise Support for Adults With Type 1 Diabetes
Ash G, Nally L, Stults-Kolehmainen M, De Los Santos M, Jeon S, Brandt C, Gulanski B, Spanakis E, Baker J, Weinzimer S, Fucito L. Personalized Digital Health Information to Substantiate Human-Delivered Exercise Support for Adults With Type 1 Diabetes. Clinical Journal Of Sport Medicine 2023, 33: 512-520. PMID: 36715983, PMCID: PMC10898917, DOI: 10.1097/jsm.0000000000001078.Peer-Reviewed Original ResearchConceptsContinuous glucose monitoringExercise supportHealth informationDigital health informationBody mass indexType 1 diabetesCommunity-based sampleSevere hypoglycemiaMass indexPsychosocial assessmentCGM useHigh satisfaction ratingsPhysician oversightType 1Future interventionsGlucose monitoringMedical readinessMolecular biomarkersBaseline observationsInterventionSatisfaction ratingsAdultsExerciseBehavioral skillsSingle group
2021
Youth and Parent Perspectives on the Acceptability of a Group Physical Activity and Coping Intervention for Adolescents With Type 1 Diabetes
DeJonckheere M, Joiner KL, Ash GI, Savoye M, Adams M, Weinzimer SA, Sadler LS, Grey M. Youth and Parent Perspectives on the Acceptability of a Group Physical Activity and Coping Intervention for Adolescents With Type 1 Diabetes. The Science Of Diabetes Self-Management And Care 2021, 47: 367-381. PMID: 34610760, DOI: 10.1177/26350106211040429.Peer-Reviewed Original ResearchConceptsGroup physical activityParents' perspectivesCoping interventionsSelf-management behaviorsSocial interactionWeekly sessionsGroup aspectsAdolescentsMultiple domainsPhysical activitySurvey subscalesSemistructured interviewsParticipant engagementFuture interventionsParentsYouthProgram componentsInterventionVigorous physical activityMean scoreAcceptabilityLikert scaleSubscalesPeersExit surveyEstablishing a Global Standard for Wearable Devices in Sport and Exercise Medicine: Perspectives from Academic and Industry Stakeholders
Ash GI, Stults-Kolehmainen M, Busa MA, Gaffey AE, Angeloudis K, Muniz-Pardos B, Gregory R, Huggins RA, Redeker NS, Weinzimer SA, Grieco LA, Lyden K, Megally E, Vogiatzis I, Scher L, Zhu X, Baker JS, Brandt C, Businelle MS, Fucito LM, Griggs S, Jarrin R, Mortazavi BJ, Prioleau T, Roberts W, Spanakis EK, Nally LM, Debruyne A, Bachl N, Pigozzi F, Halabchi F, Ramagole DA, Janse van Rensburg DC, Wolfarth B, Fossati C, Rozenstoka S, Tanisawa K, Börjesson M, Casajus JA, Gonzalez-Aguero A, Zelenkova I, Swart J, Gursoy G, Meyerson W, Liu J, Greenbaum D, Pitsiladis YP, Gerstein MB. Establishing a Global Standard for Wearable Devices in Sport and Exercise Medicine: Perspectives from Academic and Industry Stakeholders. Sports Medicine 2021, 51: 2237-2250. PMID: 34468950, PMCID: PMC8666971, DOI: 10.1007/s40279-021-01543-5.Peer-Reviewed Original ResearchBayesian structural time series for biomedical sensor data: A flexible modeling framework for evaluating interventions
Liu J, Spakowicz DJ, Ash GI, Hoyd R, Ahluwalia R, Zhang A, Lou S, Lee D, Zhang J, Presley C, Greene A, Stults-Kolehmainen M, Nally LM, Baker JS, Fucito LM, Weinzimer SA, Papachristos AV, Gerstein M. Bayesian structural time series for biomedical sensor data: A flexible modeling framework for evaluating interventions. PLOS Computational Biology 2021, 17: e1009303. PMID: 34424894, PMCID: PMC8412351, DOI: 10.1371/journal.pcbi.1009303.Peer-Reviewed Original ResearchEvaluation of Web-Based and In-Person Methods to Recruit Adults With Type 1 Diabetes for a Mobile Exercise Intervention: Prospective Observational Study
Ash GI, Griggs S, Nally LM, Stults-Kolehmainen M, Jeon S, Brandt C, Gulanski BI, Spanakis EK, Baker JS, Whittemore R, Weinzimer SA, Fucito LM. Evaluation of Web-Based and In-Person Methods to Recruit Adults With Type 1 Diabetes for a Mobile Exercise Intervention: Prospective Observational Study. JMIR Diabetes 2021, 6: e28309. PMID: 34047700, PMCID: PMC8299346, DOI: 10.2196/28309.Peer-Reviewed Original ResearchType 1 diabetesEligible volunteersExercise interventionClinical trialsIncremental costProspective observational studyGreater New HavenCharacteristics of enrolleesHigh-risk participantsOlder patientsOverall cohortPatients 18Clinical visitsUncommon conditionAdults 18Observational studySnowball samplingActive adultsT1DEligibility screeningPrior trialsLower click ratesPatientsActive individualsEligibility rates
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