Evidence map›Paper›PMID 29632227›Full record

Trial reportAnnals of family medicine2018

A Community Engagement Method to Design Patient Engagement Materials for Cardiovascular Health.

Aimee F English, L Miriam Dickinson, Linda Zittleman, Donald E Nease, Alisha Herrick, John M Westfall, Matthew J Simpson, Douglas H Fernald, Robert L Rhyne, W Perry Dickinson

Open access · diamondAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Annals of family medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
6.8field-weighted citation impact, top 4% 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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Pooled it
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  7. Engaging with Rural Communities for Colorectal Cancer Screening Outreach Using Modified Boot Camp Translation.Progress in community health partnerships : research, education, and action · 2024
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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

10 authors at 2 institutions in 1 country.

Aimee F EnglishDepartment of Family Medicine, University of Colorado School of Medicine, Aurora, Colorado aimee.english@ucdenver.edu.
L Miriam DickinsonDepartment of Family Medicine, University of Colorado School of Medicine, Aurora, Colorado.
Linda ZittlemanDepartment of Family Medicine, University of Colorado School of Medicine, Aurora, Colorado.
Donald E NeaseDepartment of Family Medicine, University of Colorado School of Medicine, Aurora, Colorado.
Alisha HerrickDepartment of Family Medicine, University of New Mexico, Albuquerque, New Mexico.
John M WestfallDepartment of Family Medicine, University of Colorado School of Medicine, Aurora, Colorado.
Matthew J SimpsonDepartment of Family Medicine, University of Colorado School of Medicine, Aurora, Colorado.
Douglas H FernaldDepartment of Family Medicine, University of Colorado School of Medicine, Aurora, Colorado.
Robert L RhyneDepartment of Family Medicine, University of New Mexico, Albuquerque, New Mexico.
W Perry DickinsonDepartment of Family Medicine, University of Colorado School of Medicine, Aurora, Colorado.
University of Colorado Denver · USUniversity of New Mexico · US

Funding

Southwest Health Extension Partnership to Enhance Research Dissemination (SHEPERD)R18HS023904 · AHRQ · UNIVERSITY OF COLORADO DENVER · PI DICKINSON, WALTER PERRY · 2015 to 2017
$14.9M
AHRQ HHS R18 HS023904
6 · The paper itself

Abstract

purposeEvidenceNOW Southwest is a cluster-randomized trial evaluating the differential impact on cardiovascular disease (CVD) care of engaging patients and communities in practice transformation in addition to standard practice facilitation support. The trial included development of locally tailored CVD patient engagement materials through Boot Camp Translation (BCT), a community engagement process that occurred before practice recruitment but after cluster randomization.

methodsWe introduce a cluster randomization method performed before recruitment of small to medium-size primary care practices in Colorado and New Mexico, which allowed for balanced study arms while minimizing contamination. Engagement materials for the enhanced study arm were developed by means of BCT, which included community members, practice members, and public health professionals from (1) metropolitan Denver, (2) rural northeast Colorado, (3) Albuquerque, and (4) rural southeast New Mexico. Outcome measures were messages and materials from BCTs and population characteristics of study arms after using geographic-based covariate constrained randomization.

resultsThe 4 BCTs' messages and materials developed by the BCT groups uniquely reflected each community and ranged from family or spiritual values to early prevention or adding relevance to CVD risk. The geographic-based covariate of a cluster randomization method constrained randomization-assigned regions to study arms, allowing BCTs to precede practice recruitment, reduce contamination, and balance populations.

conclusionsCluster-randomized trials with community-based interventions present study design and implementation challenges. The BCTs elicited unique contextual messages and materials, suggesting that interventions designed to help primary care practices decrease CVD risk may not be one size fits all.

Indexed as

Cardiovascular DiseasesCluster AnalysisColoradoCommunity ParticipationHumansNew MexicoPatient Education as TopicPatient ParticipationPrimary Health CareQuality Improvementcardiovascular disease risk reductioncommunity engagementpatient engagementpractice transformationprimary health care

Identifiers

PMID29632227
PMCPMC5891315
OpenAlexW2797669777

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.