Unknown

Dataset Information

0

Evaluation of a digital diabetes prevention program adapted for the Medicaid population: Study design and methods for a non-randomized, controlled trial.


ABSTRACT: Previous studies have shown that lifestyle modification can successfully prevent or delay development of type 2 diabetes. This trial aimed to test if an underserved, low-income population would engage in a digital diabetes prevention program and successfully achieve lifestyle changes to reduce their risk of type 2 diabetes. Participants were recruited from three health care facilities serving low-income populations. The inclusion criteria were: a recent blood test indicating prediabetes, body mass index (BMI)?>?24?kg/m2, age 18-75 years, not pregnant, not insured, Medicaid insured or Medicaid-eligible, internet or smartphone access, and comfort reading and writing in English or Spanish. A total of 230 participants were enrolled and started the intervention. Participants' average age was 48 years, average BMI?=?34.8, average initial HbA1c?=?5.8, 81% were female, and 45% were Spanish speaking. Eighty percent had Medicaid insurance, 18% were uninsured, and 2% were insured by a medical safety net plan. Participants completed a health assessment including measured anthropometrics, HbA1c test, and self-report questionnaires at baseline, 6 and 12 months. The 52-week digital diabetes prevention program included weekly educational curriculum, human health coaching, connected tracking tools, and peer support from a virtual group. Qualitative data on implementation was collected with semi-structured interviews with key informants to understand the barriers, keys to success, and best practices in the adoption of the program within the clinical setting. This paper describes the study design and methodology of a digital diabetes prevention program and early lessons learned related to recruitment, enrollment, and data collection.

SUBMITTER: Kim SE 

PROVIDER: S-EPMC6052649 | BioStudies | 2018-01-01T00:00:00Z

REPOSITORIES: biostudies

Similar Datasets

2019-01-01 | S-EPMC6803884 | BioStudies
2019-01-01 | S-EPMC6896833 | BioStudies
2018-01-01 | S-EPMC6289051 | BioStudies
2017-01-01 | S-EPMC5540355 | BioStudies
2015-01-01 | S-EPMC4478175 | BioStudies
2017-01-01 | S-EPMC5606313 | BioStudies
2020-01-01 | S-EPMC7243744 | BioStudies
2015-01-01 | S-EPMC4674352 | BioStudies
2020-01-01 | S-EPMC7518987 | BioStudies
2019-01-01 | S-EPMC6429636 | BioStudies