Evidence map›Paper›PMID 26883282›Full record

Trial reportContemporary clinical trials2016

Distance learning strategies for weight management utilizing social media: A comparison of phone conference call versus social media platform. Rationale and design for a randomized study.

Erik A Willis, Amanda N Szabo-Reed, Lauren T Ptomey, Felicia L Steger, Jeffery J Honas, Eyad M Al-Hihi, Robert Lee, Lisa Vansaghi, Richard A Washburn, Joseph E Donnelly

Abstract readComparative StudyRandomized Controlled Trial
In one paragraph

Trial report in Contemporary clinical trials, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
–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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  7. Review
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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

10 authors.

Erik A WillisUniversity of Kansas Medical Center, Cardiovascular Research Institute, Division of Internal Medicine, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA. Electronic address: ewillis@ku.edu.
Amanda N Szabo-ReedUniversity of Kansas Medical Center, Cardiovascular Research Institute, Division of Internal Medicine, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA. Electronic address: aszabo2@ku.edu.
Lauren T PtomeyUniversity of Kansas Medical Center, Cardiovascular Research Institute, Division of Internal Medicine, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA. Electronic address: lptomey@kumc.edu.
Felicia L StegerUniversity of Kansas Medical Center, Cardiovascular Research Institute, Division of Internal Medicine, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA. Electronic address: fsteger@ku.edu.
Jeffery J HonasUniversity of Kansas Medical Center, Cardiovascular Research Institute, Division of Internal Medicine, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA. Electronic address: jhonas@ku.edu.
Eyad M Al-HihiUniversity of Kansas Medical Center, Cardiovascular Research Institute, General and Geriatric Medicine, Division of Internal Medicine, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA. Electronic address: eal-hihi@kumc.edu.
Robert LeeUniversity of Kansas Medical Center, Department of Health Policy and Management, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA. Electronic address: rlee2@kumc.edu.
Lisa VansaghiUniversity of Kansas Medical Center, Cardiovascular Research Institute, General and Geriatric Medicine, Division of Internal Medicine, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA. Electronic address: lvansaghi@kumc.edu.
Richard A WashburnUniversity of Kansas Medical Center, Cardiovascular Research Institute, Division of Internal Medicine, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA. Electronic address: rwashburn@ku.edu.
Joseph E DonnellyUniversity of Kansas Medical Center, Cardiovascular Research Institute, Division of Internal Medicine, 3901 Rainbow Boulevard, Kansas City, KS 66160, USA. Electronic address: jdonnelly@ku.edu.

Funding

Prevention of weight regain (POWeR) and cognitive funtionF32DK103493 · NIDDK · UNIVERSITY OF KANSAS MEDICAL CENTER · PI SZABO-REED, AMANDA N. · 2014 to 2016
$172k
NIDDK NIH HHS F32 DK103493
6 · The paper itself

Abstract

Management of obesity in the context of the primary care physician visit is of limited efficacy in part because of limited ability to engage participants in sustained behavior change between physician visits. Therefore, healthcare systems must find methods to address obesity that reach beyond the walls of clinics and hospitals and address the issues of lifestyle modification in a cost-conscious way. The dramatic increase in technology and online social networks may present healthcare providers with innovative ways to deliver weight management programs that could have an impact on health care at the population level. A randomized study will be conducted on 70 obese adults (BMI 30.0-45.0 kg/m(2)) to determine if weight loss (6 months) is equivalent between weight management interventions utilizing behavioral strategies by either a conference call or social media approach. The primary outcome, body weight, will be assessed at baseline and 6 months. Secondary outcomes including waist circumference, energy and macronutrient intake, and physical activity will be assessed on the same schedule. In addition, a cost analysis and process evaluation will be completed.

Indexed as

Social MediaAdultAgedClinical ProtocolsEducation, DistanceFeasibility StudiesFemaleHumansMaleMiddle AgedObesityResearch DesignTreatment OutcomeWeight LossWeight Reduction ProgramsDistance learningMethodsObesitySocial media

Identifiers

PMID26883282
PMCPMC4889333

What OpenQuestion holds

Textmetadata
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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.