Evidence map›Paper›PMID 30649648›Full record

ArticleJournal of behavioral medicine2019

Temporal patterns of self-weighing behavior and weight changes assessed by consumer purchased scales in the Health eHeart Study.

Yaguang Zheng, Susan M Sereika, Lora E Burke, Jeffrey E Olgin, Gregory M Marcus, Kirstin Aschbacher, Geoffrey H Tison, Mark J Pletcher

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of behavioral medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
  4. Article
  5. 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

8 authors.

Yaguang ZhengSchool of Nursing, University of Pittsburgh, 360D Victoria Building, 3500 Victoria Street, Pittsburgh, PA, 15261, USA. yaz100@pitt.edu.ORCID http://orcid.org/0000-0003-3981-9657
Susan M SereikaSchool of Nursing and Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
Lora E BurkeSchool of Nursing and Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
Jeffrey E OlginSchool of Medicine, University of California, San Francisco, CA, USA.
Gregory M MarcusSchool of Medicine, University of California, San Francisco, CA, USA.
Kirstin AschbacherSchool of Medicine, University of California, San Francisco, CA, USA.
Geoffrey H TisonSchool of Medicine, University of California, San Francisco, CA, USA.
Mark J PletcherSchool of Medicine, University of California, San Francisco, CA, USA.

Funding

The Health ePeople Resource for Mobilized ResearchU2CEB021881 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MARCUS, GREGORY M, OLGIN, JEFFREY E · 2015 to 2020
$10.3M
Technology Research in Chronic & Critical IllnessT32NR008857 · NINR · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Young Ji Lee · 2005 to 2026
$4.0M
Dynamic prediction of heart failure using real-time functional status and EHR data in the ambulatory settingK23HL135274 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI TISON, GEOFFREY H · 2018 to 2022
$999k
NHLBI NIH HHS K23 HL135274NIBIB NIH HHS U2C EB021881NIH HHS 1U2CEB021881
6 · The paper itself

Abstract

Self-weighing may promote attainment and maintenance of healthy weight; however, the natural temporal patterns and factors associated with self-weighing behavior are unclear. The aims of this secondary analysis were to (1) identify distinct temporal patterns of self-weighing behaviors; (2) explore factors associated with temporal self-weighing patterns; and (3) examine differences in percent weight changes by patterns of self-weighing over time. We analyzed electronically collected self-weighing data from the Health eHeart Study, an ongoing longitudinal research study coordinated by the University of California, San Francisco. We selected participants with at least 12 months of data since the day of first use of a WiFi- or Bluetooth-enabled digital scale. The sample (N = 1041) was predominantly male (77.5%) and White (89.9%), with a mean age of 46.5 ± 12.3 years and a mean BMI of 28.3 ± 5.9 kg/m

Indexed as

Body WeightAge FactorsFemaleHumansLongitudinal StudiesMaleMiddle AgedMonitoring, PhysiologicObesitySelf CareSex FactorsTime FactorsBehavior changesSelf-weighingTemporal patternWeight change

Identifiers

PMID30649648
PMCPMC6635083

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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.