Evidence map›Paper›PMID 37463017›Full record

ArticleJMIR mHealth and uHealth2023

Patterns and Predictors of Engagement With Digital Self-Monitoring During the Maintenance Phase of a Behavioral Weight Loss Program: Quantitative Study.

Nicole Crane, Charlotte Hagerman, Olivia Horgan, Meghan Butryn

Open access · goldAbstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
4.8field-weighted citation impact, top 5% 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
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  5. Do routinized eating behaviors support weight loss? An examination of food logs from behavioral weight loss participants.Health psychology : official journal of the Division of Health Psychology, American Psychological Association · 2026
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  6. Observational
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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 1 institution in 1 country.

Nicole CraneCenter for Weight, Eating, and Lifestyle Science, Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA, United States.ORCID 0000-0003-0378-670X
Charlotte HagermanCenter for Weight, Eating, and Lifestyle Science, Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA, United States.ORCID 0000-0002-9386-8444
Olivia HorganCenter for Weight, Eating, and Lifestyle Science, Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA, United States.ORCID 0000-0003-2385-4319
Meghan ButrynCenter for Weight, Eating, and Lifestyle Science, Department of Psychological and Brain Sciences, Drexel University, Philadelphia, PA, United States.ORCID 0000-0001-5573-5707
Drexel University · US

Funding

Improving Weight Loss Maintenance by Using Digital Data Sharing to Provide Responsive Support and AccountabilityR21DK112741 · NIDDK · DREXEL UNIVERSITY · PI BUTRYN, MEGHAN · 2017 to 2018
$425k
NIDDK NIH HHS R21 DK112741
6 · The paper itself

Abstract

backgroundLong-term self-monitoring (SM) of weight, diet, and exercise is commonly recommended by behavioral weight loss (BWL) treatments. However, sustained SM engagement is notoriously challenging; therefore, more must be learned about patterns of engagement with digital SM tools during weight loss maintenance (WLM). In addition, insight into characteristics that may influence SM engagement could inform tailored approaches for participants at risk for poor adherence.

objectiveThis study explored patterns of digital SM of weight, diet, and exercise during WLM (aim 1) and examined timing, patterns, and rates of disengagement and reengagement (aim 2). This study also assessed relationships between individual-level factors (weight-related information avoidance and weight bias internalization) and SM engagement (aim 3).

methodsParticipants were 72 adults enrolled in a BWL program consisting of a 3-month period of weekly treatment designed to induce weight loss (phase I), followed by a 9-month period of less frequent contact to promote WLM (phase II). Participants were prescribed daily digital SM of weight, diet, and exercise. At baseline, self-report measures assessed weight-related information avoidance and weight bias internalization. SM adherence was objectively measured with the days per month that participants tracked weight, diet, and exercise. Repeated-measures ANOVA examined differences in adherence across SM targets. Multilevel modeling examined changes in adherence across phase II. Relationships between individual-level variables and SM adherence were assessed with Pearson correlations, 2-tailed independent samples t tests, and multilevel modeling.

resultsDuring WLM, consistently high rates of SM (≥50% of the days in each month) were observed for 61% (44/72) of the participants for exercise, 40% (29/72) of the participants for weight, and 21% (15/72) of the participants for diet. Adherence for SM of exercise was higher than that for weight or diet (P<.001). Adherence decreased over time for all SM targets throughout phase II (P<.001), but SM of exercise dropped off later in WLM (mean 10.07, SD 2.83 months) than SM of weight (mean 7.92, SD 3.23 months) or diet (mean 7.58, SD 2.92 months; P<.001). Among participants with a period of low SM adherence (ie, <50% of the days in a month), only 33% (17/51 for weight, 19/57 for diet) to 46% (13/28 for exercise) subsequently had ≥1 months with high adherence. High weight-related information avoidance predicted a faster rate of decrease in dietary SM (P<.001). Participants with high weight bias internalization had the highest rates of weight SM (P=.03).

conclusionsParticipants in BWL programs have low adherence to the recommendation to sustain daily SM during WLM, particularly for SM of diet and weight. Weight-related information avoidance and weight bias internalization may be relevant indicators for SM engagement. Interventions may benefit from innovative strategies that target participants at key moments of risk for disengagement.

Indexed as

ObesityWeight LossAdultDietExerciseHumansOverweightbehavior changedietdigital technologyexercisemobile phoneweight loss

Identifiers

PMID37463017
PMCPMC10394603
OpenAlexW4377085620

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.