Evidence map›Paper›PMID 35373179›Full record

ArticleFrontiers in digital health2022

Momentary Influences on Self-Regulation in Two Populations With Health Risk Behaviors: Adults Who Smoke and Adults Who Are Overweight and Have Binge-Eating Disorder.

Emily A Scherer, Stephen A Metcalf, Cady L Whicker, Sophia M Bartels, Michael Grabinski, Sunny Jung Kim, Mary Ann Sweeney, Shea M Lemley, Hannah Lavoie, Haiyi Xie and 10 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Frontiers in digital health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03352713 (Applying Novel Technologies and Methods to Inform the Ontology of Self-Regulation - Aim 2 Non-lab Study), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.1field-weighted citation impact, top 13% 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.

NCT03352713 nacompletednot on this map

Applying Novel Technologies and Methods to Inform the Ontology of Self-Regulation - Aim 2 Non-lab Study: Using Mobile Technology to Better Understand and Measure Self-Regulation

TypeinterventionalSponsorDartmouth-Hitchcock Medical CenterRan2018 to 2018Enrolled185ConditionsSelf-regulation, Binge Eating, SmokingArmsLaddr
3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 16 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

20 authors at 10 institutions in 2 countries.

Emily A SchererCenter for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.
Stephen A MetcalfCenter for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.
Cady L WhickerCenter for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.
Sophia M BartelsCenter for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.
Michael GrabinskiCenter for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.
Sunny Jung KimDepartment of Health Behavior and Policy, School of Medicine, Virginia Commonwealth University, Richmond, VA, United States.
Mary Ann SweeneyCenter for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.
Shea M LemleyCenter for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.
Hannah LavoieCenter for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.
Haiyi XieCenter for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.
Patrick G BissettDepartment of Psychology, Stanford University, Stanford, CA, United States.
Jesse DalleryDepartment of Psychology, University of Florida, Gainesville, FL, United States.
Michaela KiernanStanford Prevention Research Center, Department of Medicine, Stanford University, Stanford, CA, United States.
Michael R LoweDepartment of Psychological and Brain Sciences, Drexel University, Philadelphia, PA, United States.
Lisa OnkenNational Institute on Aging, National Institutes of Health, Bethesda, MD, United States.
Judith J ProchaskaStanford Prevention Research Center, Department of Medicine, Stanford University, Stanford, CA, United States.
Luke E StoeckelNational Institute on Aging, National Institutes of Health, Bethesda, MD, United States.
Russell A PoldrackDepartment of Psychology, Stanford University, Stanford, CA, United States.
David P MacKinnonDepartment of Psychology, Arizona State University, Tempe, AZ, United States.
Lisa A MarschCenter for Technology and Behavioral Health, Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States.
Dartmouth College · USStanford University · USArizona State University · USDrexel University · USNational Institute on Aging · USNational Institutes of Health · USUniversity of Cambridge · GBUniversity of Florida · USUniversity of North Carolina at Chapel Hill · USVirginia Commonwealth University · US

Funding

Treatment Development & Evaluation CoreP30DA029926 · NIDA · DARTMOUTH COLLEGE · PI Lisa A. Marsch · 2011 to 2026
$21.5M
Applying novel technologies and methods to inform the ontology of self-regulationUH2DA041713 · NIDA · DARTMOUTH COLLEGE · PI MARSCH, LISA A., POLDRACK, RUSSELL A · 2015 to 2017
$2.8M
Applying novel technologies and methods to inform the ontology of self-regulationUH3DA041713 · NIDA · DARTMOUTH COLLEGE · PI MARSCH, LISA A., POLDRACK, RUSSELL A · 2018 to 2019
$2.5M
NIDA NIH HHS P30 DA029926NIDA NIH HHS UH2 DA041713NIDA NIH HHS UH3 DA041713
6 · The paper itself

Abstract

Introduction: Self-regulation has been implicated in health risk behaviors and is a target of many health behavior interventions. Despite most prior research focusing on self-regulation as an individual-level trait, we hypothesize that self-regulation is a time-varying mechanism of health and risk behavior that may be influenced by momentary contexts to a substantial degree. Because most health behaviors (e.g., eating, drinking, smoking) occur in the context of everyday activities, digital technologies may help us better understand and influence these behaviors in real time. Using a momentary self-regulation measure, the current study (which was part of a larger multi-year research project on the science of behavior change) used ecological momentary assessment (EMA) to assess if self-regulation can be engaged and manipulated on a momentary basis in naturalistic, non-laboratory settings. Methods: This one-arm, open-label exploratory study prospectively collected momentary data for 14 days from 104 participants who smoked regularly and 81 participants who were overweight and had binge-eating disorder. Four times per day, participants were queried about momentary self-regulation, emotional state, and social and environmental context; recent smoking and exposure to smoking cues (smoking sample only); and recent eating, binge eating, and exposure to binge-eating cues (binge-eating sample only). This study used a novel, momentary self-regulation measure comprised of four subscales: momentary perseverance, momentary sensation seeking, momentary self-judgment, and momentary mindfulness. Participants were also instructed to engage with Laddr, a mobile application that provides evidence-based health behavior change tools Results: Participants (mean age 35.2; 78% female) in the smoking and binge-eating samples contributed a total of 3,233 and 3,481 momentary questionnaires, respectively. Momentary self-regulation subscales were associated with several momentary contexts, in the combined as well as smoking and binge-eating samples. For example, in the combined sample momentary perseverance was associated with location, positively associated with positive affect, and negatively associated with negative affect, stress, and tiredness. In the smoking sample, momentary perseverance was positively associated with momentary difficulty in accessing cigarettes, caffeine intake, and momentary restraint in smoking, and negatively associated with temptation and urge to smoke. In the binge-eating sample, momentary perseverance was positively associated with difficulty in accessing food and restraint in eating, and negatively associated with urge to binge eat. While recent Laddr use was not associated directly with momentary self-regulation subscales, it did modify several of the contextual associations, including challenging contexts. Conclusions: Overall, this study provides preliminary evidence that momentary self-regulation may vary in response to differing momentary contexts in samples from two exemplar populations with risk behaviors. In addition, the Laddr application may modify some of these relationships. These findings demonstrate the possibility of measuring momentary self-regulation in a trans-diagnostic way and assessing the effects of momentary, mobile interventions in context. Health behavior change interventions may consider measuring and targeting momentary self-regulation in addition to trait-level self-regulation to better understand and improve health risk behaviors. This work will be used to inform a later stage of research focused on assessing the transdiagnostic mediating effect of momentary self-regulation on medical regimen adherence and health outcomes. Clinical Trial Registration: ClinicalTrials.gov, Identifier: NCT03352713.

Indexed as

behavioral healthbinge-eating disorderdigital healthecological momentary assessment (EMA)momentary self-regulationobesityoverweightsmoking

Identifiers

PMID35373179
PMCPMC8971561
OpenAlexW4221014304

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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.