Evidence map›Paper›PMID 40286938›Full record

ArticlePreventive medicine2025

Social network characteristics and type 2 diabetes self-management among Black/African American men: A cross-sectional analysis of support quality and communication patterns.

Tyler Prochnow, Megan S Patterson, Jeong-Hui Park, Ledric D Sherman, Matthew Lee Smith

Abstract read
In one paragraph

Article in Preventive medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. 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

5 authors.

Tyler ProchnowSchool of Public Health, Texas A&M Health Science Center, 212 Adriance Lab Rd., College Station, TX 77843, USA; Center for Health Equity and Evaluation Research, Texas A&M University, College Station, TX 77843, USA; Center for Community Health and Aging, Texas A&M University, College Station, TX 77843, USA. Electronic address: tprochnow@tamu.edu.
Megan S PattersonSchool of Public Health, Texas A&M Health Science Center, 212 Adriance Lab Rd., College Station, TX 77843, USA; Center for Community Health and Aging, Texas A&M University, College Station, TX 77843, USA.
Jeong-Hui ParkSchool of Public Health, Texas A&M Health Science Center, 212 Adriance Lab Rd., College Station, TX 77843, USA; Center for Health Equity and Evaluation Research, Texas A&M University, College Station, TX 77843, USA.
Ledric D ShermanSchool of Public Health, Texas A&M Health Science Center, 212 Adriance Lab Rd., College Station, TX 77843, USA; Center for Health Equity and Evaluation Research, Texas A&M University, College Station, TX 77843, USA.
Matthew Lee SmithSchool of Public Health, Texas A&M Health Science Center, 212 Adriance Lab Rd., College Station, TX 77843, USA; Center for Health Equity and Evaluation Research, Texas A&M University, College Station, TX 77843, USA; Center for Community Health and Aging, Texas A&M University, College Station, TX 77843, USA.

Funding

Making the Connection: Understanding the dynamic social connections impacting type 2 diabetes management among Black/African American menR21MD019048 · NIMHD · TEXAS A&M UNIVERSITY HEALTH SCIENCE CTR · PI PROCHNOW, TYLER, SHERMAN, LEDRIC DERRELL · 2023 to 2025
$419k
NIMHD NIH HHS R21 MD019048
6 · The paper itself

Abstract

objectiveSocial networks and social support are critically important for Black/African American men managing Type 2 diabetes (T2D). This study aims to examine how social network characteristics are associated with T2D self-management among Black/African American men.

methodsCross-sectional survey data were collected from Black/African American men with T2D (n = 1225) from February to June 2024. Network composition included percentages of spouses, children, parents, siblings, friends, extended family, and healthcare providers. Network interaction measures included communication frequency, support quality, and perceptions of network members' health behaviors. Self-care activities were measured using the Summary of Diabetes Self-Care Activities scale across diet, physical activity, blood sugar testing, and foot care domains. Multiple regression analyses examined associations between network characteristics and each self-management domain while controlling for demographics.

resultsDiabetes-specific communication frequency was consistently positively associated with all self-care activities (β from 0.09 to 0.18,p < .05). Having very supportive network members was positively associated with diet (β = 0.17,p < .01) and physical activity (β = 0.20,p < .01), though mean social network support showed negative associations with these behaviors (β = -0.13,p = .03; β = -0.14,p = .03). Higher percentages of children were associated with better dietary behaviors (β = 0.06,p = .04), while having spouses (β = 0.06,p = .04), friends (β = 0.06,p = .03), and siblings (β = 0.06,p = .04) was associated with better foot care.

conclusionsThe quality and content of network interactions appear more important than network size for T2D self-management among Black/African American men. Interventions should focus on fostering quality, disease-specific support rather than expanding social networks. Future programs should leverage existing relationships while considering how different network members influence specific aspects of diabetes management.

Indexed as

Black or African AmericanCommunicationDiabetes Mellitus, Type 2Self-ManagementSocial NetworkingSocial SupportAdultAgedCross-Sectional StudiesHealth BehaviorHumansMaleMiddle AgedSelf CareSurveys and QuestionnairesAfrican American menSelf-managementSocial networksType 2 diabetes

Identifiers

PMID40286938
PMCPMC13181843

What OpenQuestion holds

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LicenceCC BY
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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.