Evidence map›Paper›PMID 42337161›Full record

ArticlePrevention science : the official journal of the Society for Prevention Research2026

Improvements in Capacity Among Community Coalitions Receiving Technical Assistance Through the Coalition Check-Up.

Yvonne Gaddy, Sarah M Chilenski, Rebecca Wells, Louis D Brown

Abstract read
In one paragraph

Article in Prevention science : the official journal of the Society for Prevention Research, 2026. 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

4 authors.

Yvonne GaddyDepartment of Health Promotion and Behavioral Sciences, The University of Texas Health Science Center at Houston, School of Public Health, El Paso, TX, USA. mary.y.gaddy@uth.tmc.edu.
Sarah M ChilenskiEdna Bennett Pierce Prevention Research Center, Pennsylvania State University, University Park, PA, USA.
Rebecca WellsDepartment of Management, Policy and Community Health, The University of Texas Health Science Center at Houston, School of Public Health, Houston, TX, USA.
Louis D BrownDepartment of Health Promotion and Behavioral Sciences, The University of Texas Health Science Center at Houston, School of Public Health, El Paso, TX, USA.

Funding

Penn State Clinical and Translational Science InstituteUL1TR002014 · NCATS · PENNSYLVANIA STATE UNIV HERSHEY MED CTR · PI KRASCHNEWSKI, JENNIFER L. · 2016 to 2025
$33.7M
NCATS NIH HHS UL1 TR00045NCATS NIH HHS UL1 TR002014NIDA NIH HHS 5R01DA045815
6 · The paper itself

Abstract

Community coalitions are central to the prevention delivery system, yet their ability to implement and sustain effective strategies often depends on technical assistance (TA). TA typically strengthens coalition capacity, but many coalitions lack connection to TA, and it is costly to sustain. Low intensity TA models that support coalition capacity exist but have not been rigorously evaluated. This study examines the Coalition Check-Up (CoCU) as a low intensity TA model to strengthen coalition capacity. Using up to 3 years of data, we tested whether capacities selected by coalitions during each CoCU implementation year improved over time. Thirty-two coalitions in Pennsylvania and Missouri received TA to review their summary report on data collected yearly over 3 years and a follow-up after year 3. Each year, coalitions used their report to prioritize a capacity for action planning following the CoCU TA model. Analyses examined data from multiple baselines (i.e., before action planning at year 1, year 2, and year 3) and subsequent data collection timepoints to test for longitudinal change on prioritized capacities. Coalitions receiving TA through the CoCU model demonstrated measurable improvements over time. Capacities prioritized in year 1 significantly improved across the following years measured (β = 0.13, 95% confidence interval (CI) [0.004, 0.26]; p = .04), as did capacities selected in the second year (β = 0.20, CI [0.02, 0.37]; p = .03) and the third year (β = 0.61, CI [0.16, 1.07]; p = .01). Findings suggest that a low intensity TA model like CoCU has the potential to guide coalitions toward strategic capacity development, ultimately enhancing their ability to deliver impactful prevention initiatives.

Indexed as

Capacity BuildingCommunity NetworksHealth Care CoalitionsHumansMissouriPennsylvaniaCoalition capacityCoalition Check-upCommunity coalitionsLow intensity technical assistanceTA

Identifiers

PMID42337161
PMCPMC13433725

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.