The ILHBN: challenges, opportunities, and solutions from harmonizing data under heterogeneous study designs, target populations, and measurement protocols.


Journal

Translational behavioral medicine
ISSN: 1613-9860
Titre abrégé: Transl Behav Med
Pays: England
ID NLM: 101554668

Informations de publication

Date de publication:
20 01 2023
Historique:
pubmed: 24 11 2022
medline: 24 1 2023
entrez: 23 11 2022
Statut: ppublish

Résumé

The ILHBN is funded by the National Institutes of Health to collaboratively study the interactive dynamics of behavior, health, and the environment using Intensive Longitudinal Data (ILD) to (a) understand and intervene on behavior and health and (b) develop new analytic methods to innovate behavioral theories and interventions. The heterogenous study designs, populations, and measurement protocols adopted by the seven studies within the ILHBN created practical challenges, but also unprecedented opportunities to capitalize on data harmonization to provide comparable views of data from different studies, enhance the quality and utility of expensive and hard-won ILD, and amplify scientific yield. The purpose of this article is to provide a brief report of the challenges, opportunities, and solutions from some of the ILHBN's cross-study data harmonization efforts. We review the process through which harmonization challenges and opportunities motivated the development of tools and collection of metadata within the ILHBN. A variety of strategies have been adopted within the ILHBN to facilitate harmonization of ecological momentary assessment, location, accelerometer, and participant engagement data while preserving theory-driven heterogeneity and data privacy considerations. Several tools have been developed by the ILHBN to resolve challenges in integrating ILD across multiple data streams and time scales both within and across studies. Harmonization of distinct longitudinal measures, measurement tools, and sampling rates across studies is challenging, but also opens up new opportunities to address cross-cutting scientific themes of interest. Health behavior changes, such as prevention of suicidal thoughts and behaviors, smoking, drug use, and alcohol use; and the promotion of mental health, sleep, and physical activities, and decreases in sedentary behavior, are difficult to sustain. The ILHBN is a cooperative agreement network funded jointly by seven participating units within the National Institutes of Health to collaboratively study how factors that occur in individuals’ everyday life and in their natural environment influence the success of positive health behavior changes. This article discusses how information collected using smartphones, wearables, and other devices can provide helpful active and passive reflections of the participants’ extent of risk and resources at the moment for an extended period of time. However, successful engagement and retention of participants also require tailored adaptations of study designs, measurement tools, measurement intervals, study span, and device choices that create hurdles in integrating (harmonizing) data from multiple studies. We describe some of the challenges, opportunities, and solutions that emerged from harmonizing intensive longitudinal data under heterogeneous study and participant characteristics within the ILHBN, and share some tools and recommendations to facilitate future data harmonization efforts.

Autres résumés

Type: plain-language-summary (eng)
Health behavior changes, such as prevention of suicidal thoughts and behaviors, smoking, drug use, and alcohol use; and the promotion of mental health, sleep, and physical activities, and decreases in sedentary behavior, are difficult to sustain. The ILHBN is a cooperative agreement network funded jointly by seven participating units within the National Institutes of Health to collaboratively study how factors that occur in individuals’ everyday life and in their natural environment influence the success of positive health behavior changes. This article discusses how information collected using smartphones, wearables, and other devices can provide helpful active and passive reflections of the participants’ extent of risk and resources at the moment for an extended period of time. However, successful engagement and retention of participants also require tailored adaptations of study designs, measurement tools, measurement intervals, study span, and device choices that create hurdles in integrating (harmonizing) data from multiple studies. We describe some of the challenges, opportunities, and solutions that emerged from harmonizing intensive longitudinal data under heterogeneous study and participant characteristics within the ILHBN, and share some tools and recommendations to facilitate future data harmonization efforts.

Identifiants

pubmed: 36416389
pii: 6843119
doi: 10.1093/tbm/ibac069
pmc: PMC9853092
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

7-16

Subventions

Organisme : NCI NIH HHS
ID : U24 CA264369
Pays : United States
Organisme : NIMH NIH HHS
ID : U01 MH116928
Pays : United States
Organisme : NIDA NIH HHS
ID : R01 DA039901
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL125440
Pays : United States
Organisme : NIAAA NIH HHS
ID : U24 AA027684
Pays : United States
Organisme : NIMH NIH HHS
ID : U01 MH116925
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA229437
Pays : United States
Organisme : NIMH NIH HHS
ID : U01 MH116923
Pays : United States
Organisme : NIDA NIH HHS
ID : U01 DA046413
Pays : United States
Organisme : NIDA NIH HHS
ID : P50 DA054039
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA229445
Pays : United States
Organisme : NHLBI NIH HHS
ID : U01 HL146327
Pays : United States

Investigateurs

Yosef Bodovski (Y)
Shirlene Wang (S)
Jonathan Kaslander (J)
Daniel Chu (D)
Aditya Ponnada (A)
Rebecca Braga De Braganca (R)
Dana Schloesser (D)
Guanqing Chi (G)
Daniel Rivera (D)
Einat Liebenthal (E)

Commentaires et corrections

Type : ErratumIn

Informations de copyright

© The Author(s) 2022. Published by Oxford University Press on behalf of the Society of Behavioral Medicine.

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Auteurs

Sy-Miin Chow (SM)

Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA 16802, USA.

Inbal Nahum-Shani (I)

Institute for Social Research, University of Michigan, Ann Arbor, MI, USA.

Justin T Baker (JT)

Department of Psychiatry, McLean Hospital, Boson, MA, USA.
Department of Psychiatry, Harvard Medical School, Boson, MA, USA.

Donna Spruijt-Metz (D)

Department of Psychology, University of Southern California, Los Angeles, CA, USA.
Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA.

Nicholas B Allen (NB)

Department of Psychology, University of Oregon, Eugene, OR, USA.

Randy P Auerbach (RP)

Department of Psychiatry, Columbia University, New York, NY, USA.

Genevieve F Dunton (GF)

Department of Psychology, University of Southern California, Los Angeles, CA, USA.
Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA.

Naomi P Friedman (NP)

Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA.
Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA.

Stephen S Intille (SS)

Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA.
Bouvé College of Health Sciences, Northeastern University, Boston, MA, USA.

Predrag Klasnja (P)

School of Information, University of Michigan, Ann Arbor, MI, USA.

Benjamin Marlin (B)

College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, MA, USA.

Matthew K Nock (MK)

Department of Psychology, Harvard University, Cambridge, MA, USA.
Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
Franciscan Children's, Boston, MA, USA.
Children's Hospital, Boston, MA, USA.

Scott L Rauch (SL)

Department of Psychiatry, McLean Hospital, Boson, MA, USA.
Department of Psychiatry, Harvard Medical School, Boson, MA, USA.

Misha Pavel (M)

Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA.
Bouvé College of Health Sciences, Northeastern University, Boston, MA, USA.

Scott Vrieze (S)

Department of Psychology, University of Minnesota, Minneapolis, MN, USA.

David W Wetter (DW)

Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA.
Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.

Evan M Kleiman (EM)

Department of Psychology, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.

Timothy R Brick (TR)

Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA 16802, USA.
Institute for Computational and Data Sciences, The Pennsylvania State University, University Park, PA, USA.

Heather Perry (H)

Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA 16802, USA.

Dana L Wolff-Hughes (DL)

National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.

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