Evidence map›Paper›PMID 39405529›Full record

ArticleJMIR diabetes2024

Implementation of a Technology-Enabled Diabetes Self-Management Peer Coaching Intervention for Patients With Poorly Controlled Diabetes: Quasi-Experimental Case Study.

Marvyn R Arévalo Avalos, Ashwin Patel, Haci Duru, Sanjiv Shah, Madeline Rivera, Eleanor Sorrentino, Marika Dy, Urmimala Sarkar, Kim H Nguyen, Courtney R Lyles and 1 more

Abstract read
In one paragraph

Article in JMIR diabetes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
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

11 authors.

Marvyn R Arévalo AvalosSchool of Social Welfare, University of California Berkeley, Berkeley, CA, United States.ORCID https://orcid.org/0000-0002-6667-4396
Ashwin PatelPyx Health, Tucson, AZ, United States.ORCID https://orcid.org/0009-0007-1891-3392
Haci DuruDepartment of Criminal Justice, State University of New York Brockport, Brockport, NY, United States.ORCID https://orcid.org/0000-0002-9002-4094
Sanjiv ShahMetroPlusHealth, New York, NY, United States.ORCID https://orcid.org/0009-0006-4561-6732
Madeline RiveraMetroPlusHealth, New York, NY, United States.ORCID https://orcid.org/0009-0004-1719-0848
Eleanor SorrentinoMetroPlusHealth, New York, NY, United States.ORCID https://orcid.org/0009-0005-6892-9267
Marika DyDivision of General Internal Medicine at Zuckerberg San Francisco General Hospital, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0001-7592-9998
Urmimala SarkarDivision of General Internal Medicine at Zuckerberg San Francisco General Hospital, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0003-4213-4405
Kim H NguyenAction Research Center for Health Equity, Department of Medicine, University of California San Francisco, San Francisco, CA, United States.ORCID https://orcid.org/0000-0002-9112-0221
Courtney R LylesCenter for Healthcare Research and Policy, University of California Davis Health, Davis, CA, United States.ORCID https://orcid.org/0000-0002-1111-8595
Adrian AguileraSchool of Social Welfare, University of California Berkeley, Berkeley, CA, United States.ORCID https://orcid.org/0000-0003-1773-8768

Funding

Translational Research Core - Health Engagement & Action Translational (HEAT)P30DK092924 · NIDDK · KAISER FOUNDATION RESEARCH INSTITUTE · PI Alyce Sophia Adams, HILARY Kessler SELIGMAN · 2011 to 2026
$9.2M
NIDDK NIH HHS P30 DK092924
6 · The paper itself

Abstract

backgroundPatients with diabetes experience worse health outcomes and greater health care expenditure. Improving diabetes outcomes requires involved self-management. Peer coaching programs can help patients engage in self-management while addressing individual and structural barriers. These peer coaching programs can be scaled with digital platforms to efficiently connect patients with peer supporters who can help with diabetes self-management.

objectiveThis study aimed to evaluate the implementation of a technology-enabled peer coaching intervention to support diabetes self-management among patients with uncontrolled diabetes.

methodsMetroPlusHealth, a predominant Medicaid health maintenance organization based in New York City, partnered with Pyx Health to enroll 300 Medicaid patients with uncontrolled diabetes into its 6-month peer coaching intervention. Pyx Health peer coaches conduct at least 2 evidence-based and goal-oriented coaching sessions per month with their assigned patients. These sessions are focused on addressing both behavioral and social determinants of health (SDoH) with the goal of helping patients increase their diabetes self-management literacy, implement self-management behaviors, and reduce barriers to ongoing self-care. Data analyzed in this study included patient demographic data, clinical data (patient's hemoglobin A

resultsA total of 330 patients enrolled in the peer mentoring program and 2118 patients were considered to be on a waitlist group and used as a comparator. Patients who enrolled in the peer coaching program were older; more likely to be English speakers, female, and African American; and less likely to be White or Asian American or Pacific Islander than those in the waitlist condition, and had similar HbA

conclusionsThis analysis of a technology-enabled 1-on-1 peer coaching program showed improved HbA

Indexed as

behavioral determinants of healthdiabetes experienceseHealthmHealthpeer coachpeer coachingpeer supportself-managementsocial determinants of healthtype 1 diabetestype 2 diabetes

Identifiers

PMID39405529
PMCPMC11522654

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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.