Evidence map›Paper›PMID 24832411›Full record

ArticleAmerican journal of public health2014

Control systems engineering for optimizing a prenatal weight gain intervention to regulate infant birth weight.

Jennifer S Savage, Danielle Symons Downs, Yuwen Dong, Daniel E Rivera

Registry-linked trialOpen access · greenAbstract read
In one paragraph

Article in American journal of public health, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03945266 (Control Systems Engineering for Optimizing a Prenatal Weight Gain Intervention), which is not on this map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
4.2field-weighted citation impact, top 6% 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.

NCT03945266 nacompletednot on this map

Control Systems Engineering for Optimizing a Prenatal Weight Gain Intervention

TypeinterventionalSponsorPenn State UniversityRan2014 to 2018Enrolled31ConditionsOverweight and Obesity, Physical Activity, Weight Change, Body, Eating BehaviorArmsIntervention group, Control group
3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 25 citations in OpenAlex.

  1. Trial
  2. Article
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  4. Article
  5. A Dynamical Systems Model of Intrauterine Fetal Growth.Mathematical and computer modelling of dynamical systems · 2018
    Article
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  11. Patterns of Gestational Weight Gain and Infants Born Large-for-Gestational Age Across Consecutive Pregnancies.Women's health issues : official publication of the Jacobs Institute of Women's Health
    Observational
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.

Jennifer S SavageJennifer S. Savage is with Center for Childhood Obesity Research and Department of Nutritional Sciences, The Pennsylvania State University, University Park. Danielle Symons Downs is with Exercise Psychology Laboratory, Department of Kinesiology and Department of Obstetrics and Gynecology, The Pennsylvania State University. Yuwen Dong and Daniel E. Rivera are with Control Systems Engineering Laboratory, School for Engineering of Matter, Transport, and Energy, Arizona State University, Tempe.
Danielle Symons Downs
Yuwen Dong
Daniel E Rivera
Arizona State University · US

Funding

THE REFINEMENT &APPLICATION OF MEDICAL DECISION MAKING IN PREVENTION SCIENCESP50DA010075 · NIDA · PENNSYLVANIA STATE UNIVERSITY-UNIV PARK · PI LANZA, STEPHANIE T · 1996 to 2014
$24.5M
Control Systems Engineering for Optimizing a Prenatal Weight Gain InterventionR01HL119245 · NHLBI · PENNSYLVANIA STATE UNIVERSITY, THE · PI DOWNS, DANIELLE SYMONS · 2013 to 2017
$1.8M
Dynamical System /Related Engineering Approach /Improving Behavioral InterventionR21DA024266 · NIDA · PENNSYLVANIA STATE UNIVERSITY, THE · PI COLLINS, LINDA M, RIVERA, DANIEL E · 2007 to 2010
$1.1M
Control Engineering Approaches to Adaptive Interventions for Fighting Drug AbuseK25DA021173 · NIDA · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI RIVERA, DANIEL E · 2007 to 2011
$875k
NHLBI NIH HHS R01 HL119245NHLBI NIH HHS R01 HL119245-01NIDA NIH HHS K25 DA021173NIDA NIH HHS P50 DA010075NIDA NIH HHS P50 DA010075-14NIDA NIH HHS R21 DA024266
6 · The paper itself

Abstract

objectivesWe used dynamical systems modeling to describe how a prenatal behavioral intervention that adapts to the needs of each pregnant woman may help manage gestational weight gain and alter the obesogenic intrauterine environment to regulate infant birth weight.

methodsThis approach relies on integrating mechanistic energy balance, theory of planned behavior, and self-regulation models to describe how internal processes can be impacted by intervention dosages, and reinforce positive outcomes (e.g., healthy eating and physical activity) to moderate gestational weight gain and affect birth weight.

resultsA simulated hypothetical case study from MATLAB with Simulink showed how, in response to our adaptive intervention, self-regulation helps adjust perceived behavioral control. This, in turn, changes the woman's intention and behavior with respect to healthy eating and physical activity during pregnancy, affecting gestational weight gain and infant birth weight.

conclusionsThis article demonstrates the potential for real-world applications of an adaptive intervention to manage gestational weight gain and moderate infant birth weight. This model could be expanded to examine the long-term sustainable impacts of an intervention that varies according to the participant's needs on maternal postpartum weight retention and child postnatal eating behavior.

Indexed as

Birth WeightHealth BehaviorWeight GainComputer SimulationDietEnergy IntakeEnergy MetabolismExerciseHumansIntentionModels, PsychologicalPrenatal Care

Identifiers

PMID24832411
PMCPMC4056194
OpenAlexW2122909308

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.