Evidence map›Paper›PMID 28438726›Full record

ArticleJMIR research protocols2017

Analyzing Unstructured Communication in a Computer-Mediated Environment for Adults With Type 2 Diabetes: A Research Protocol.

Allison A Lewinski, Ruth A Anderson, Allison A Vorderstrasse, Edwin B Fisher, Wei Pan, Constance M Johnson

Abstract read
In one paragraph

Article in JMIR research protocols, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
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

6 authors.

Allison A LewinskiDuke University School of Nursing, Durham, NC, United States.ORCID http://orcid.org/0000-0002-1356-1857
Ruth A AndersonSchool of Nursing, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID http://orcid.org/0000-0001-6640-644X
Allison A VorderstrasseDuke University School of Nursing, Durham, NC, United States.ORCID http://orcid.org/0000-0001-8770-1851
Edwin B FisherGillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States.ORCID http://orcid.org/0000-0003-0234-7465
Wei PanDuke University School of Nursing, Durham, NC, United States.ORCID http://orcid.org/0000-0003-2410-9935
Constance M JohnsonSchool of Nursing, The University of Texas Health Science Center at Houston, Houston, TX, United States.ORCID http://orcid.org/0000-0003-3162-3932

Funding

Research BaseP30DK092926 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARY ELLEN MICHELE HEISLER, ADESUWA B OLOMU · 2011 to 2026
$10.0M
eHealth: Second Life Impacts Diabetes Education & Self-Management (SLIDES)R21LM010727 · NLM · DUKE UNIVERSITY · PI JOHNSON, CONSTANCE MARGARET · 2010 to 2011
$421k
Social Interaction and Support in a Type-2 Diabetes Computer Mediated EnvironmentF31NR016622 · NINR · DUKE UNIVERSITY · PI LEWINSKI, ALLISON · 2016 to 2017
$35k
NIDDK NIH HHS P30 DK092926NINR NIH HHS F31 NR016622NLM NIH HHS R21 LM010727
6 · The paper itself

Abstract

backgroundIndividuals with type 2 diabetes have an increased risk for comorbidities such as heart disease, lower limb amputations, stroke, and renal failure. Multiple factors influence development of complications in a person living with type 2 diabetes; however, an individual's self-management behaviors may delay the onset of, or lessen the severity of, these complications. Social support provides personal, informal advice and knowledge that helps individuals initiate and sustain self-management and adherence.

objectiveOur aim was to gain an understanding of type 2 diabetes social interaction in a virtual environment, one type of computer-mediated environment (CME), and the social support characteristics that increase and sustain self-management in adults living with chronic illness.

methodsThis study is a secondary analysis of longitudinal data collected in a CME study, Second Life Impacts Diabetes Education & Self-Management (1R21-LM010727-01). This virtual environment replicated a real-life community where 6 months of naturalistic synchronous voice conversations, emails, and text chats were recorded among participants and providers. This analysis uses a mixed-methods approach to explore and compare qualitative and quantitative findings. This analysis is guided by two theories: Strong/Weak Ties Theory and Social Penetration Theory. Qualitative data will be analyzed using content analysis, and we will complete descriptive statistics on the quantified variables (eg, average number of ties). Institutional review board approval was obtained in June 2016.

resultsThis study is in progress.

conclusionsInterventions provided through virtual environments are a promising solution to increasing self-management practices. However, little is known of the depth, breadth, and quality of social support that is exchanged and how interaction supports self-management and relates to health outcomes. This study will provide knowledge that will help guide clinical practice and policy to enhance social support for chronic illness via the Internet.

Indexed as

adultsdiabetes type 2Internetmixed methodspeer supportsecondary analysisself-managementsocial interactionsocial support

Identifiers

PMID28438726
PMCPMC5422658

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.