Evidence map›Paper›PMID 39211727›Full record

ArticlePreventive medicine reports2024

Adapting the National Diabetes Prevention Program: Learning from Lifestyle Coach strategies and adjustments during the COVID-19 pandemic in the United States.

Madelyn Whitaker, Megha Shah, Manuel Gutierrez Chavez, Anu Asnaani, Cassidy A Gutner, Natalie D Ritchie, Katherine J W Baucom

Abstract read
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In one paragraph

Article in Preventive medicine reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Madelyn WhitakerDepartment of Psychology, University of Utah, 380 1530 E, Salt Lake City, UT 84112, USA.
Megha ShahDepartment of Family and Preventive Medicine, Emory University School of Medicine, 100 Woodruff Circle, Atlanta, GA 30322, USA.
Manuel Gutierrez ChavezDepartment of Psychology, University of Utah, 380 1530 E, Salt Lake City, UT 84112, USA.
Anu AsnaaniDepartment of Psychology, University of Utah, 380 1530 E, Salt Lake City, UT 84112, USA.
Cassidy A GutnerDepartment of Psychiatry, Boston University School of Medicine, 720 Harrison Avenue, Room 906, Boston, MA 02118, USA.
Natalie D RitchieKaiser Permanente Center for Health Research, 3800 N. Interstate Avenue, Portland, OR 97227, USA.
Katherine J W BaucomDepartment of Psychology, University of Utah, 380 1530 E, Salt Lake City, UT 84112, USA.

Funding

Couple-based lifestyle intervention to prevent type 2 diabetesK23DK115820 · NIDDK · UNIVERSITY OF UTAH · PI BAUCOM, KATHERINE JANE WILLIAMS · 2018 to 2022
$1.2M
NIDDK NIH HHS K23 DK115820
6 · The paper itself

Abstract

Background: The National Diabetes Prevention Program (National DPP) is an evidence-based lifestyle intervention successfully disseminated across the United States. Some adaptations have been made to address real-world needs, including during the COVID-19 pandemic. This study aims to qualitatively describe adaptations Lifestyle Coaches made in response to the pandemic. Methods: Between May and June 2021, Lifestyle Coaches ( Results: Nearly all coaches transitioned the format of their class from in-person to remote delivery (93.0 %; Conclusions: Maintaining these adaptations may address barriers to engagement in the National DPP and improve access to the program. Increased support for emotional symptoms and ensuring a patient-centered approach to care are particularly promising strategies.

Indexed as

AdaptationsCOVID-19Diabetes prevention programDistance learningLifestyle interventionQualitative analysisRemote delivery

Identifiers

PMID39211727
PMCPMC11357858

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.