Evidence map›Paper›PMID 41885884›Full record

ArticleHealth psychology : official journal of the Division of Health Psychology, American Psychological Association2026

Do routinized eating behaviors support weight loss? An examination of food logs from behavioral weight loss participants.

Charlotte J Hagerman, Asher E Hong, Nicole T Crane, Meghan L Butryn, Evan M Forman

Abstract read
In one paragraph

Article in Health psychology : official journal of the Division of Health Psychology, American Psychological Association, 2026. 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
–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

1 citing paper in PubMed.

  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

5 authors.

Charlotte J HagermanCenter for Weight, Eating, and Lifestyle Science, Drexel University.ORCID 0000-0002-9386-8444
Asher E HongCenter for Weight, Eating, and Lifestyle Science, Drexel University.
Nicole T CraneCenter for Weight, Eating, and Lifestyle Science, Drexel University.
Meghan L ButrynCenter for Weight, Eating, and Lifestyle Science, Drexel University.
Evan M FormanCenter for Weight, Eating, and Lifestyle Science, Drexel University.

Funding

Using Artificial Intelligence to Optimize Delivery of Weight Loss TreatmentR01DK125641 · NIDDK · DREXEL UNIVERSITY · PI LAFATA, ERICA M · 2021 to 2024
$2.4M
NIDDK NIH HHS R01 DK125641
6 · The paper itself

Abstract

objectiveWeight loss requires constant effortful decision-making. Following a more routine (vs. varied) diet may allow healthy choices to become more habitual, that is, automatic. The current study examined whether routinized eating patterns predicted success for 112 participants in a behavioral weight loss program.

methodUsing daily food logs from the first 12 weeks of the program, we examined whether

resultsGreater dietary repetition (both metrics) and more daily calorie stability were associated with higher weight loss. However, contrary to hypotheses, participants with higher weekend-weekday deviations also had greater weight loss.

conclusionOverall, findings suggest that more routinized eating patterns during a weight loss attempt may facilitate success. Future work should confirm these findings with experimental manipulations and identify potential mechanisms of action. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Indexed as

Diet RecordsFeeding BehaviorWeight LossWeight Reduction ProgramsAdultEnergy IntakeFemaleHumansMale

Identifiers

PMID41885884
PMCPMC13335809

What OpenQuestion holds

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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.