Dataset Information

Personalized Digital Health Information to Substantiate Human-Delivered Exercise Support for Adults With Type 1 Diabetes.

ABSTRACT:

Objective

Pilot-test personalized digital health information to substantiate human-delivered exercise support for adults with type 1 diabetes (T1D).

Design

Single-group, 2-week baseline observation, then 10-week intervention with follow-up observation.

Setting

Community-based sample participating remotely with physician oversight.

Participants

Volunteers aged 18 to 65 years with T1D screened for medical readiness for exercise intervention offerings. N = 20 enrolled, and N = 17 completed all outcomes with 88% to 91% biosensor adherence.

Intervention

Feedback on personalized data from continuous glucose monitoring (CGM), its intersection with other ecological data sets (exercise, mood, and sleep), and other informational and motivational elements (exercise videos, text-based exercise coach, and self-monitoring diary).

Main outcome measures

Feasibility (use metrics and assessment completion), safety (mild and severe hypoglycemia, and diabetic ketoacidosis), acceptability (system usability scale, single items, and interview themes), and standard clinical and psychosocial assessments.

Results

Participants increased exercise from a median of 0 (Interquartile range, 0-21) to 64 (20-129) minutes per week ( P = 0.001, d = 0.71) with no severe hypoglycemia or ketoacidosis. Body mass index increased (29.5 ± 5.1 to 29.8 ± 5.4 kg/m 2 , P = 0.02, d = 0.57). Highest satisfaction ratings were for CGM use (89%) and data on exercise and its intersection with CGM and sleep (94%). Satisfaction was primarily because of improved exercise management behavioral skills, although derived motivation was transient.

Conclusions

The intervention was feasible, safe, and acceptable. However, there is a need for more intensive, sustained support. Future interventions should perform analytics upon the digital health information and molecular biomarkers (eg, genomics) to make exercise support tools that are more personalized, automated, and intensive than our present offerings.

SUBMITTER: Ash GI

PROVIDER: S-EPMC10898917 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Publications

Personalized Digital Health Information to Substantiate Human-Delivered Exercise Support for Adults With Type 1 Diabetes.

Ash Garrett I GI Nally Laura M LM Stults-Kolehmainen Matthew M De Los Santos Melissa M Jeon Sangchoon S Brandt Cynthia C Gulanski Barbara I BI Spanakis Elias K EK Baker Julien S JS Weinzimer Stuart A SA Fucito Lisa M LM

Clinical journal of sport medicine : official journal of the Canadian Academy of Sport Medicine 20230127 5

<h4>Objective</h4>Pilot-test personalized digital health information to substantiate human-delivered exercise support for adults with type 1 diabetes (T1D).<h4>Design</h4>Single-group, 2-week baseline observation, then 10-week intervention with follow-up observation.<h4>Setting</h4>Community-based sample participating remotely with physician oversight.<h4>Participants</h4>Volunteers aged 18 to 65 years with T1D screened for medical readiness for exercise intervention offerings. N = 20 enrolled, ...[more]

PMID: 36715983

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Project description:BackgroundThe COVID-19 pandemic created unprecedented shifts in the way health programs and services are delivered. A national lockdown to prevent the spread of COVID-19 in Australia was introduced in March 2020. This lockdown included the closure of exercise clinics, fitness centers, and other community spaces, which, before the pandemic, were used to deliver Beat It. Beat It is an 8-week in-person, community-based, and clinician-led group exercise and education program for adults self-managing diabetes. To continue offering Beat It, it was adapted from an in-person program to a fully web-based supervised group exercise program for adults with type 2 diabetes (T2DM).ObjectiveThis study aims to assess whether the Beat It Online program produced comparable health outcomes to the Beat It in-person program in terms of improving physical fitness (muscular strength and power, aerobic endurance, balance, and flexibility) and waist circumference in older adults with T2DM.MethodsAustralians with T2DM who were aged ≥60 years were included. They were enrolled in Beat It Online, a twice-weekly supervised group exercise and education program conducted via videoconference over 8 weeks. Anthropometric measurements and physical fitness parameters were assessed at baseline and completion. The adaptations to Beat It are reported using the Model for Adaptation, Design, and Impact, including the type of changes (what, where, when, and for whom), the criteria for making those changes (why and how), and the intended and unintended outcomes. The intended outcomes were comparable functional fitness as well as physical and mental health improvements across demographics and socioeconomic status.ResultsA total of 171 adults (mean 71, SD 5.6 years; n=54, 31.6% male) with T2DM were included in the study, with 40.4% (n=69) residing in lower socioeconomic areas. On the completion of the 8-week program, significant improvements in waist circumference, aerobic capacity, muscular strength, flexibility, and balance were observed in both male and female participants (all P<.001). The Model for Adaptation, Design, and Impact reports on 9 clinical, practical, and technical aspects of Beat It that were adapted for web-based delivery.ConclusionsThis study found that Beat It Online was just as effective as the in-person program. This adapted program produced comparable health benefits across demographics and socioeconomic status. This study offers important findings for practitioners and policy makers seeking to maintain independence of older people with T2DM, reversing frailty and maximizing functional and physical fitness, while improving overall quality of life. Beat It Online offers a flexible and inclusive solution with significant physical and mental health benefits to individuals. Further evaluation of Beat It (both in-person and Online) adapted for culturally and linguistically diverse communities will provide greater insights into the efficacy of this promising program.

Dataset Information

Personalized Digital Health Information to Substantiate Human-Delivered Exercise Support for Adults With Type 1 Diabetes.

Objective

Design

Setting

Participants

Intervention

Main outcome measures

Results

Conclusions

Publications

Personalized Digital Health Information to Substantiate Human-Delivered Exercise Support for Adults With Type 1 Diabetes.

Similar Datasets

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