Evidence map›Paper›PMID 35544298›Full record

ArticleJMIR formative research2022

A Social Media-Based Diabetes Intervention for Low-Income Mandarin-Speaking Chinese Immigrants in the United States: Feasibility Study.

Lu Hu, Nadia Islam, Chau Trinh-Shevrin, Bei Wu, Naumi Feldman, Kosuke Tamura, Nan Jiang, Sahnah Lim, Chan Wang, Omonigho M Bubu and 3 more

Open access · goldAbstract read
In one paragraph

Article in JMIR formative research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 7% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

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  14. Diabetes Distress and Associated Factors Among Chinese Americans with Type 2 Diabetes in New York City.Diabetes, metabolic syndrome and obesity : targets and therapy · 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

13 authors at 3 institutions in 1 country.

Lu HuCenter for Healthful Behavior Change, Institute for Excellence in Health Equity, NYU Langone Health, New York, NY, United States.ORCID https://orcid.org/0000-0001-6465-6779
Nadia IslamDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0003-1470-2073
Chau Trinh-ShevrinDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0001-9635-0512
Bei WuRory Meyers College of Nursing, New York University, New York, NY, United States.ORCID https://orcid.org/0000-0002-6891-244X
Naumi FeldmanCharles B Wang Community Health Center, New York, NY, United States.ORCID https://orcid.org/0000-0003-0548-8677
Kosuke TamuraSocio-Spatial Determinants of Health (SSDH) Laboratory, Population and Community Health Sciences Branch, Intramural Research Program, National Institute on Minority Health and Health Disparities, National Institute of Health, Bethesda, MD, United States.ORCID https://orcid.org/0000-0002-4920-2856
Nan JiangDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0003-0714-750X
Sahnah LimDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0001-7406-5235
Chan WangDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0002-1718-5414
Omonigho M BubuDepartment of Population Health, NYU Grossman School of Medicine, New York, NY, United States.ORCID https://orcid.org/0000-0001-7438-2628
Antoinette SchoenthalerCenter for Healthful Behavior Change, Institute for Excellence in Health Equity, NYU Langone Health, New York, NY, United States.ORCID https://orcid.org/0000-0003-4905-5136
Gbenga OgedegbeCenter for Healthful Behavior Change, Institute for Excellence in Health Equity, NYU Langone Health, New York, NY, United States.ORCID https://orcid.org/0000-0002-3628-1751
Mary Ann SevickCenter for Healthful Behavior Change, Institute for Excellence in Health Equity, NYU Langone Health, New York, NY, United States.ORCID https://orcid.org/0000-0002-5482-7535
New York University · USCommunity Health Center · USNational Institute on Minority Health and Health Disparities · US

Funding

Research Education ComponentP30AG066512 · NIA · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI REBECCA A. BETENSKY · 2020 to 2026
$28.4M
Scaling Community-Clinical Linkage Models to Address Diabetes and Hypertension Disparities in the Southeastern U.S.U54MD000538 · NIMHD · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI KWON, SIMONA, TRINH-SHEVRIN, CHAU · 2017 to 2022
$11.3M
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
A Mobile Health Intervention to Reduce Diabetes Disparities in Chinese AmericansR00MD012811 · NIMHD · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI HU, LU · 2020 to 2022
$737k
A Mobile Health Intervention to Reduce Diabetes Disparities in Chinese AmericansK99MD012811 · NIMHD · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI HU, LU · 2018 to 2019
$207k
NIA NIH HHS P30 AG066512NIDDK NIH HHS P30 DK111022NIMHD NIH HHS K99 MD012811NIMHD NIH HHS R00 MD012811NIMHD NIH HHS U54 MD000538
6 · The paper itself

Abstract

backgroundChinese immigrants bear a high diabetes burden and face significant barriers to accessing diabetes self-management education (DSME) and counseling programs.

objectiveThe goal of this study was to examine the feasibility and acceptability and to pilot test the potential efficacy of a social media-based DSME intervention among low-income Chinese immigrants with type 2 diabetes (T2D) in New York City.

methodsThis was a single group pretest and posttest study in 30 Chinese immigrants with T2D. The intervention included 24 culturally and linguistically tailored DSME videos, focusing on diabetes education and behavioral counseling techniques. Over 12 weeks, participants received 2 brief videos each week via WeChat, a free social media app popular among Chinese immigrants. Primary outcomes included the feasibility and acceptability of the intervention. Feasibility was evaluated by recruitment processes, retention rates, and the video watch rate. Acceptability was assessed via a satisfaction survey at 3 months. Secondary outcomes, that is, hemoglobin A

resultsThe sample population (N=30) consisted of mostly females (21/30, 70%) who were married (19/30, 63%), with limited English proficiency (30/30, 100%), and the mean age was 61 (SD 7) years. Most reported an annual household income of <US $25,000 (24/30, 80%) and a high school education or less (19/30, 63%). Thirty participants were recruited within 2 months (January and February 2020), and 97% (29/30) of the participants were retained at 6 months. A video watch rate of 92% (28/30) was achieved. The mean baseline HbA

conclusionsThis pilot study demonstrated that a social media-based DSME intervention is feasible, acceptable, and potentially efficacious in a low-income Chinese immigrant population with T2D. Future studies need to examine the efficacy in an adequately powered clinical trial.

Indexed as

access to carecounselingdiabetesdiabetes educationdigital healthdisease managementeducation videofeasibilityhealth educationhealth equityhealth interventionhealth videoimmigrant healthimmigrant populationlow incomemessaging appmigrantminoritymobile healthmobile phonepatient educationpilot studyself managementsocial mediaWeChat

Identifiers

PMID35544298
PMCPMC9492091
OpenAlexW4225815552

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.