Evidence map›Paper›PMID 26441408›Full record

ArticleIEEE transactions on bio-medical engineering2015

Behavioral Informatics and Computational Modeling in Support of Proactive Health Management and Care.

Misha Pavel, Holly B Jimison, Ilkka Korhonen, Christine M Gordon, Niilo Saranummi

Abstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Adaptive Health Coaching Technology for Tailored Interventions.International journal of environmental research and public health · 2021
    Article
  6. Review
  7. Article
  8. SleepOMICS: How Big Data Can Revolutionize Sleep Science.International journal of environmental research and public health · 2019
    Review
  9. Review
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.

Misha Pavel
Holly B Jimison
Ilkka Korhonen
Christine M Gordon
Niilo Saranummi

Funding

Core B - Pilot StudiesP30AG048785 · NIA · BRANDEIS UNIVERSITY · PI LACHMAN, MARGIE E · 2014 to 2023
$4.5M
Technology-CoreP20NR015320 · NINR · NORTHEASTERN UNIVERSITY · PI GUTHRIE, BARBARA J. · 2014 to 2018
$1.5M
Cognitive Interventions Delivered to Elders in the Home via Coaching TechnologyRC1AG036121 · NIA · OREGON HEALTH & SCIENCE UNIVERSITY · PI JIMISON, HOLLY BRUGGE · 2009 to 2010
$950k
NIA NIH HHS P30 AG048785NIA NIH HHS RC1 AG036121NINR NIH HHS P20 NR015320NINR NIH HHS P20NR015320
6 · The paper itself

Abstract

Health-related behaviors are among the most significant determinants of health and quality of life. Improving health behavior is an effective way to enhance health outcomes and mitigate the escalating challenges arising from an increasingly aging population and the proliferation of chronic diseases. Although it has been difficult to obtain lasting improvements in health behaviors on a wide scale, advances at the intersection of technology and behavioral science may provide the tools to address this challenge. In this paper, we describe a vision and an approach to improve health behavior interventions using the tools of behavioral informatics, an emerging transdisciplinary research domain based on system-theoretic principles in combination with behavioral science and information technology. The field of behavioral informatics has the potential to optimize interventions through monitoring, assessing, and modeling behavior in support of providing tailored and timely interventions. We describe the components of a closed-loop system for health interventions. These components range from fine grain sensor characterizations to individual-based models of behavior change. We provide an example of a research health coaching platform that incorporates a closed-loop intervention based on these multiscale models. Using this early prototype, we illustrate how the optimized and personalized methodology and technology can support self-management and remote care. We note that despite the existing examples of research projects and our platform, significant future research is required to convert this vision to full-scale implementations.

Indexed as

Computer SimulationHealth BehaviorMedical Informatics ApplicationsActivities of Daily LivingAgedAged, 80 and overFemaleHealth PromotionHumansMaleMonitoring, AmbulatorySelf Care

Identifiers

PMID26441408
PMCPMC4809752

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.