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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 2 of 2 Research Studies DisplayedFeinberg E, Kuhn J, Eilenberg JS
Improving family navigation for children with autism: a comparison of two pilot randomized controlled trials.
This study looked at impacts of a modification to a pilot program called Family Navigation to help low-income, minority children needing autism-related diagnostic services receive those services. An advisory group recommended modifications to recruitment criteria and study conditions. 40 parent-child dyad participants were randomized between the two pilots to receive usual care (UC) or modified FN. Participant enrollment, satisfaction with clinical care, and timely completion of the diagnostic assessment were compared. Recruitment improved significantly with the modified protocol (4.8% vs. 19.5%) and no participants were excluded from study enrollment compared to the first pilot (43.6%). Families in the second pilot were more likely to complete diagnostic assessment and report greater satisfaction with clinical care.
AHRQ-funded; HS022155; HS022242.
Citation: Feinberg E, Kuhn J, Eilenberg JS .
Improving family navigation for children with autism: a comparison of two pilot randomized controlled trials.
Acad Pediatr 2021 Mar;21(2):265-71. doi: 10.1016/j.acap.2020.04.007..
Keywords: Children/Adolescents, Autism, Patient-Centered Healthcare, Care Coordination, Racial and Ethnic Minorities, Low-Income, Patient and Family Engagement, Chronic Conditions
Aguilera A, Figueroa CA, Hernandez-Ramos R
mHealth app using machine learning to increase physical activity in diabetes and depression: clinical trial protocol for the DIAMANTE study.
In this randomized controlled trial, the researchers’ goal is to examine the effect of a text-messaging smartphone application to encourage physical activity in low-income ethnic minority patients with comorbid diabetes and depression. They will compare passively collected daily step counts, self-reported PHQ-8 and most recent hemoglobin A1c from medical records at baseline and at intervention completion at 6-month follow-up. They plan to submit manuscripts describing their user-designed methods and testing of the adaptive learning algorithm and will submit the results of the trial for publication in peer-reviewed journals and presentations at scientific meetings.
AHRQ-funded; HS025429.
Citation: Aguilera A, Figueroa CA, Hernandez-Ramos R .
mHealth app using machine learning to increase physical activity in diabetes and depression: clinical trial protocol for the DIAMANTE study.
BMJ Open 2020 Aug 20;10(8):e034723. doi: 10.1136/bmjopen-2019-034723..
Keywords: Telehealth, Health Information Technology (HIT), Diabetes, Chronic Conditions, Racial and Ethnic Minorities, Low-Income, Health Promotion