56 Citations (Scopus)

Abstract

Evidence-based practice is important for behavioral interventions but there is debate on how best to support real-world behavior change. The purpose of this paper is to define products and a preliminary process for efficiently and adaptively creating and curating a knowledge base for behavior change for real-world implementation. We look to evidence-based practice suggestions and draw parallels to software development. We argue to target three products: (1) the smallest, meaningful, self-contained, and repurposable behavior change modules of an intervention; (2) “computational models” that define the interaction between modules, individuals, and context; and (3) “personalization” algorithms, which are decision rules for intervention adaptation. The “agile science” process includes a generation phase whereby contender operational definitions and constructs of the three products are created and assessed for feasibility and an evaluation phase, whereby effect size estimates/casual inferences are created. The process emphasizes early-and-often sharing. If correct, agile science could enable a more robust knowledge base for behavior change.

Original languageEnglish (US)
Pages (from-to)317-328
Number of pages12
JournalTranslational Behavioral Medicine
Volume6
Issue number2
DOIs
StatePublished - Jun 1 2016

Fingerprint

Knowledge Bases
Evidence-Based Practice
Software

Keywords

  • Behavior change
  • Implementation science
  • Research methods

ASJC Scopus subject areas

  • Behavioral Neuroscience
  • Applied Psychology

Cite this

Agile science : creating useful products for behavior change in the real world. / Hekler, Eric B.; Klasnja, Predrag; Riley, William T.; Buman, Matthew; Huberty, Jennifer; Rivera, Daniel; Martin, Cesar A.

In: Translational Behavioral Medicine, Vol. 6, No. 2, 01.06.2016, p. 317-328.

Research output: Contribution to journalArticle

Hekler, Eric B. ; Klasnja, Predrag ; Riley, William T. ; Buman, Matthew ; Huberty, Jennifer ; Rivera, Daniel ; Martin, Cesar A. / Agile science : creating useful products for behavior change in the real world. In: Translational Behavioral Medicine. 2016 ; Vol. 6, No. 2. pp. 317-328.
@article{d43608571d3e411e932ff0d873103fa5,
title = "Agile science: creating useful products for behavior change in the real world",
abstract = "Evidence-based practice is important for behavioral interventions but there is debate on how best to support real-world behavior change. The purpose of this paper is to define products and a preliminary process for efficiently and adaptively creating and curating a knowledge base for behavior change for real-world implementation. We look to evidence-based practice suggestions and draw parallels to software development. We argue to target three products: (1) the smallest, meaningful, self-contained, and repurposable behavior change modules of an intervention; (2) “computational models” that define the interaction between modules, individuals, and context; and (3) “personalization” algorithms, which are decision rules for intervention adaptation. The “agile science” process includes a generation phase whereby contender operational definitions and constructs of the three products are created and assessed for feasibility and an evaluation phase, whereby effect size estimates/casual inferences are created. The process emphasizes early-and-often sharing. If correct, agile science could enable a more robust knowledge base for behavior change.",
keywords = "Behavior change, Implementation science, Research methods",
author = "Hekler, {Eric B.} and Predrag Klasnja and Riley, {William T.} and Matthew Buman and Jennifer Huberty and Daniel Rivera and Martin, {Cesar A.}",
year = "2016",
month = "6",
day = "1",
doi = "10.1007/s13142-016-0395-7",
language = "English (US)",
volume = "6",
pages = "317--328",
journal = "Translational Behavioral Medicine",
issn = "1869-6716",
publisher = "Springer Publishing Company",
number = "2",

}

TY - JOUR

T1 - Agile science

T2 - creating useful products for behavior change in the real world

AU - Hekler, Eric B.

AU - Klasnja, Predrag

AU - Riley, William T.

AU - Buman, Matthew

AU - Huberty, Jennifer

AU - Rivera, Daniel

AU - Martin, Cesar A.

PY - 2016/6/1

Y1 - 2016/6/1

N2 - Evidence-based practice is important for behavioral interventions but there is debate on how best to support real-world behavior change. The purpose of this paper is to define products and a preliminary process for efficiently and adaptively creating and curating a knowledge base for behavior change for real-world implementation. We look to evidence-based practice suggestions and draw parallels to software development. We argue to target three products: (1) the smallest, meaningful, self-contained, and repurposable behavior change modules of an intervention; (2) “computational models” that define the interaction between modules, individuals, and context; and (3) “personalization” algorithms, which are decision rules for intervention adaptation. The “agile science” process includes a generation phase whereby contender operational definitions and constructs of the three products are created and assessed for feasibility and an evaluation phase, whereby effect size estimates/casual inferences are created. The process emphasizes early-and-often sharing. If correct, agile science could enable a more robust knowledge base for behavior change.

AB - Evidence-based practice is important for behavioral interventions but there is debate on how best to support real-world behavior change. The purpose of this paper is to define products and a preliminary process for efficiently and adaptively creating and curating a knowledge base for behavior change for real-world implementation. We look to evidence-based practice suggestions and draw parallels to software development. We argue to target three products: (1) the smallest, meaningful, self-contained, and repurposable behavior change modules of an intervention; (2) “computational models” that define the interaction between modules, individuals, and context; and (3) “personalization” algorithms, which are decision rules for intervention adaptation. The “agile science” process includes a generation phase whereby contender operational definitions and constructs of the three products are created and assessed for feasibility and an evaluation phase, whereby effect size estimates/casual inferences are created. The process emphasizes early-and-often sharing. If correct, agile science could enable a more robust knowledge base for behavior change.

KW - Behavior change

KW - Implementation science

KW - Research methods

UR - http://www.scopus.com/inward/record.url?scp=84976594606&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84976594606&partnerID=8YFLogxK

U2 - 10.1007/s13142-016-0395-7

DO - 10.1007/s13142-016-0395-7

M3 - Article

C2 - 27357001

AN - SCOPUS:84976594606

VL - 6

SP - 317

EP - 328

JO - Translational Behavioral Medicine

JF - Translational Behavioral Medicine

SN - 1869-6716

IS - 2

ER -