Evidence map›Paper›PMID 30932869›Full record

ArticleJMIR formative research2019

Using Text Messaging, Social Media, and Interviews to Understand What Pregnant Youth Think About Weight Gain During Pregnancy.

Melissa DeJonckheere, Lauren P Nichols, V G Vinod Vydiswaran, Xinyan Zhao, Kevyn Collins-Thompson, Kenneth Resnicow, Tammy Chang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JMIR formative research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 25% 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

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. 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

7 authors at 1 institution in 1 country.

Melissa DeJonckheereDepartment of Family Medicine, University of Michigan, Ann Arbor, MI, United States.ORCID http://orcid.org/0000-0002-2660-3358
Lauren P NicholsDepartment of Family Medicine, University of Michigan, Ann Arbor, MI, United States.ORCID http://orcid.org/0000-0002-9915-2308
V G Vinod VydiswaranDepartment of Learning Health Sciences, University of Michigan, Ann Arbor, MI, United States.ORCID http://orcid.org/0000-0002-3122-1936
Xinyan ZhaoSchool of Information, University of Michigan, Ann Arbor, MI, United States.ORCID http://orcid.org/0000-0001-5937-0688
Kevyn Collins-ThompsonSchool of Information, University of Michigan, Ann Arbor, MI, United States.ORCID http://orcid.org/0000-0002-8178-5035
Kenneth ResnicowSchool of Public Health, University of Michigan, Ann Arbor, MI, United States.ORCID http://orcid.org/0000-0003-1416-9627
Tammy ChangDepartment of Family Medicine, University of Michigan, Ann Arbor, MI, United States.ORCID http://orcid.org/0000-0002-3580-9438
University of Michigan · US

Funding

Research BaseP30DK092926 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MARY ELLEN MICHELE HEISLER, ADESUWA B OLOMU · 2011 to 2026
$10.0M
Speaking Their Language: Using Social Media and Texting to Create an Adolescent-Centered Approach to Healthy Weight Gain During PregnancyK23HD083527 · NICHD · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI CHANG, TAMMY · 2016 to 2020
$817k
NICHD NIH HHS K23 HD083527NIDDK NIH HHS P30 DK092926
6 · The paper itself

Abstract

backgroundThe majority of pregnant youth gain more weight than recommended by the National Academy of Medicine guidelines. Excess weight gain during pregnancy increases the risk of dangerous complications during delivery, including operative delivery and stillbirth, and contributes to the risk of long-term obesity in both mother and child. Little is known regarding youth's perceptions of and knowledge about weight gain during pregnancy.

objectiveThe aim of this study was to describe the feasibility and acceptability of 3 novel data collection and analysis strategies for use with youth (social media posts, text message surveys, and semistructured interviews) to explore their experiences during pregnancy. The mixed-methods analysis included natural language processing and thematic analysis.

methodsTo demonstrate the feasibility and acceptability of this novel approach, we used descriptive statistics and thematic qualitative analysis to characterize participation and engagement in the study.

resultsRecruitment of 54 pregnant women aged between 16 and 24 years occurred from April 2016 to September 2016. All participants completed at least 1 phase of the study. Semistructured interviews had the highest rate of completion, yet all 3 strategies were feasible and acceptable to pregnant youth.

conclusionsThis study has described a novel youth-centered strategy of triangulating 3 sources of mixed-methods data to gain a deeper understanding of a health behavior phenomenon among an at-risk population of youth.

Indexed as

adolescentsmethodsnatural language processingpregnancysocial mediatext messagingweight gain

Identifiers

PMID30932869
PMCPMC6462892
OpenAlexW2914668557

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.