Evidence map›Paper›PMID 34791499›Full record

Trial reportTranslational behavioral medicine2022

Process evaluation of a medical assistant health coaching intervention for type 2 diabetes in diverse primary care settings.

Taylor L Clark, Addie L Fortmann, Athena Philis-Tsimikas, Thomas Bodenheimer, Kimberly L Savin, Haley Sandoval, Julia I Bravin, Linda C Gallo

Open access · greenAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Translational behavioral medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.0field-weighted citation impact, top 22% of its field
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

6 citing papers in PubMed, 9 citations in OpenAlex.

  1. Trial
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  3. Article
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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

8 authors at 3 institutions in 1 country.

Taylor L ClarkJoint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA, USA.ORCID 0000-0002-3689-0071
Addie L FortmannScripps Whittier Diabetes Institute, Scripps Health, San Diego, CA, USA.
Athena Philis-TsimikasScripps Whittier Diabetes Institute, Scripps Health, San Diego, CA, USA.
Thomas BodenheimerDepartment of Family and Community Medicine, University of California at San Francisco School of Medicine, San Francisco, CA, USA.
Kimberly L SavinJoint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA, USA.
Haley SandovalScripps Whittier Diabetes Institute, Scripps Health, San Diego, CA, USA.
Julia I BravinJoint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA, USA.
Linda C GalloDepartment of Psychology, San Diego State University, San Diego, CA, USA.ORCID 0000-0002-3678-5888
San Diego State University · USScripps Health · USUniversity of California, San Francisco · US

Funding

Scripps Translational Science InstituteUL1TR002550 · NCATS · SCRIPPS RESEARCH INSTITUTE, THE · PI TOPOL, ERIC JEFFREY · 2018 to 2022
$28.9M
New York Regional Center for Diabetes Translation Research - Translational Intervention Methodology CoreP30DK111022 · NIDDK · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI JEFFREY GONZALEZ · 2016 to 2026
$7.8M
UCSD Integrated Cardiovascular Epidemiology FellowshipT32HL079891 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Matthew A Allison · 2007 to 2026
$6.7M
Medical Assistant Health Coaching for Diabetes in Diverse Primary Care SettingsR18DK104250 · NIDDK · SCRIPPS HEALTH · PI GALLO, LINDA C, PHILIS-TSIMIKAS, ATHENA · 2015 to 2019
$2.3M
NCATS NIH HHS UL1 TR002550NHLBI NIH HHS T32 HL079891NIDDK NIH HHS P30 DK111022NIDDK NIH HHS R18 DK104250
6 · The paper itself

Abstract

Team-based models that use medical assistants (MAs) to provide self-management support for adults with type 2 diabetes (T2D) have not been pragmatically tested in diverse samples. This cluster-randomized controlled trial compares MA health coaching with usual care in adults with T2D and poor clinical control ("MAC Trial"). The purpose was to conduct a multi-method process evaluation of the MAC Trial using the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework. Reach was assessed by calculating the proportion of enrolled participants out of the eligible pool and examining representativeness of those enrolled. Key informant interviews documented adoption by MA Health Coaches. We examined implementation from the research and patient perspectives by evaluating protocol adherence and the Patient Perceptions of Chronic Illness Care (PACIC-SF) measure, respectively. Findings indicate that the MAC Trial was efficient and effective in reaching patients who were representative of the target population. The acceptance rate among those approached for health coaching was high (87%). Both MA Health Coaches reported high satisfaction with the program and high levels of confidence in their role. The intervention was well-implemented, as evidenced by the protocol adherence rate of 79%; however, statistically significant changes in PACIC-SF scores were not observed. Overall, if found to be effective in improving clinical and patient-reported outcomes, the MAC model holds potential for wider-scale implementation given its successful adoption and implementation and demonstrated ability to reach patients with poorly controlled T2D who are at-risk for diabetes complications in diverse primary care settings.

Indexed as

Diabetes Mellitus, Type 2MentoringSelf-ManagementAdultHumansPrimary Health CareHealth coachingMedical assistantProcess evaluationRE-AIM frameworkSelf-management supportType 2 diabetes

Identifiers

PMID34791499
PMCPMC8849003
OpenAlexW3211681552

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.