Evidence map›Paper›PMID 31566400›Full record

ArticleHealth psychology : official journal of the Division of Health Psychology, American Psychological Association2019

Week-to-week predictors of weight loss and regain.

Kathryn M Ross, Peihua Qiu, Lu You, Rena R Wing

Open access · hybridAbstract read
In one paragraph

Article in Health psychology : official journal of the Division of Health Psychology, American Psychological Association, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
6.2field-weighted citation impact, top 4% 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

29 citing papers in PubMed, 38 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Kathryn M RossDepartment of Clinical and Health Psychology.ORCID 0000-0002-3628-766X
Peihua QiuDepartment of Biostatistics, College of Public Health and Health Professions and College of Medicine, University of Florida.
Lu YouDepartment of Biostatistics, College of Public Health and Health Professions and College of Medicine, University of Florida.
Rena R WingDepartment of Psychiatry and Human Behavior, Warren Alpert Medical School, Brown University.
Florida College · USBrown University · US

Funding

University of Florida Older Americans Independence Center (OAIC)P30AG028740 · NIA · UNIVERSITY OF FLORIDA · PI Peihua Qiu · 2007 to 2026
$22.8M
Identification and Prediction of High-Risk Periods for Regain After Weight LossR21DK109205 · NIDDK · UNIVERSITY OF FLORIDA · PI ROSS, KATHRYN MARIE · 2016 to 2017
$335k
Lifespan CorporationNational Institutes of Health; National Institute of Diabetes Digestive and Kidney DiseasesNIA NIH HHS P30 AG028740NIDDK NIH HHS R21 DK109205
6 · The paper itself

Abstract

objectivesDespite increased interest in the development of individually tailored weight management programs, little is known about what factors proximally predict weight change.

methodThe current study investigated proximal (week-to-week) predictors of weight loss and regain in 74 adults during a 3-month, Internet-based behavioral weight loss program followed by a 9-month "maintenance" period (during which no additional intervention was provided). Participants were asked to self-weigh daily using scales that transmitted weight via the cellular network and to answer a brief questionnaire each week querying mood, behaviors, and cognitions hypothesized to be associated with weight loss and regain.

resultsLongitudinal multilevel models demonstrated that weight loss during initial intervention was proximally predicted by (a) greater frequency of self-monitoring weight and caloric intake, consistency between eating choices and weight loss goals, and importance of "staying on track" with these goals and (b) less negative mood, boredom with weight control efforts, hunger, and temptation to eat foods "not on plan" (ps < .05). Greater weight regain after intervention was also proximally predicted by these factors (with effects in the opposite direction) and additionally by less physical activity, less positive mood, more stress, greater temptation to skip planned physical activity, and higher ratings of the amount of effort required to stay on track (ps < .05).

conclusionsResults confirmed the importance of self-monitoring for weight loss and maintenance and identified other key week-to-week predictors of weight change. Results also supported efforts to develop intervention approaches specifically focused on weight loss maintenance. Future research should investigate whether using identified predictors to tailor intervention content and timing can improve weight outcomes. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Indexed as

AdultFemaleHumansMaleMiddle AgedObesityWeight LossWeight Reduction Programs

Identifiers

PMID31566400
PMCPMC6861630
OpenAlexW2978385875

What OpenQuestion holds

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LicenceTDM
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.