Evidence map›Paper›PMID 36340265›Full record

ArticleProceedings of the ... American Control Conference. American Control Conference2022

Enhanced Social Cognitive Theory Dynamic Modeling and Simulation Towards Improving the Estimation of "Just-In-Time" States.

Mohamed El Mistiri, Daniel E Rivera, Predrag Klasnja, Junghwan Park, Eric Hekler

Open access · greenAbstract read
In one paragraph

Article in Proceedings of the ... American Control Conference. American Control Conference, 2022. 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
0.6field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  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 at 3 institutions in 1 country.

Mohamed El MistiriControl Systems Engineering Laboratory, School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85287 USA.
Daniel E RiveraControl Systems Engineering Laboratory, School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe, AZ 85287 USA.
Predrag KlasnjaDivision of Biomedical and Health Informatics, School of Information, University of Michigan, Ann Arbor, MU 48109 USA.
Junghwan ParkCenter for Wireless & Population Health Systems, Univeristy of California, San Diego (UCSD), La Jolla, CA 92093 USA.
Eric HeklerCenter for Wireless & Population Health Systems, Univeristy of California, San Diego (UCSD), La Jolla, CA 92093 USA.
Arizona State University · USUnity Health System · USUniversity of Michigan–Ann Arbor · US

Funding

Operationalizing Behavioral Theory for mHealth: Dynamics, Context, and PersonalizationU01CA229445 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI KLASNJA, PREDRAG, MARLIN, BENJAMIN M. · 2018 to 2022
$2.1M
SCH: Control Systems Engineering for Counteracting Notification Fatigue: An Examination of Health Behavior Change R01LM013107 · NLM · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HEKLER, ERIC, KLASNJA, PREDRAG · 2019 to 2022
$995k
NCI NIH HHS U01 CA229445NLM NIH HHS R01 LM013107
6 · The paper itself

Abstract

Insufficient physical activity (PA) is commonplace in society, in spite of its significant impact on personal health and well-being. Improved interventions are clearly needed. One of the challenges faced in behavioral interventions is a lack of understanding of multi-timescale dynamics. In this paper we rely on a dynamical model of Social Cognitive Theory (SCT) to gain insights regarding a control-oriented experimental design for a behavioral intervention to improve PA. The intervention (

Identifiers

PMID36340265
PMCPMC9634811
OpenAlexW4294690895

What OpenQuestion holds

Textmetadata
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.