Evidence map›Paper›PMID 35293871›Full record

ArticleJMIR mHealth and uHealth2022

Integrating Behavioral Science and Design Thinking to Develop Mobile Health Interventions: Systematic Scoping Review.

Paula Voorheis, Albert Zhao, Kerry Kuluski, Quynh Pham, Ted Scott, Peter Sztur, Nityan Khanna, Mohamed Ibrahim, Jeremy Petch

Abstract readScoping Review
In one paragraph

Article in JMIR mHealth and uHealth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing 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

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

  1. Smartphone application-based interventions for cardiometabolic risk factor management: A systematic review and meta-analysis.Hypertension research : official journal of the Japanese Society of Hypertension · 2026
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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

9 authors.

Paula VoorheisInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID 0000-0001-9169-1422
Albert ZhaoCentre for Data Science and Digital Health, Hamilton Health Sciences, Hamilton, ON, Canada.ORCID 0000-0001-9523-195X
Kerry KuluskiInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-6377-6653
Quynh PhamInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID 0000-0002-0540-4181
Ted ScottCentre for Data Science and Digital Health, Hamilton Health Sciences, Hamilton, ON, Canada.ORCID 0000-0002-6190-050X
Peter SzturCentre for Data Science and Digital Health, Hamilton Health Sciences, Hamilton, ON, Canada.ORCID 0000-0001-9843-957X
Nityan KhannaCentre for Data Science and Digital Health, Hamilton Health Sciences, Hamilton, ON, Canada.ORCID 0000-0001-8488-4349
Mohamed IbrahimCentre for Data Science and Digital Health, Hamilton Health Sciences, Hamilton, ON, Canada.ORCID 0000-0003-0259-4888
Jeremy PetchInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID 0000-0003-1614-1046

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile health (mHealth) interventions are increasingly being designed to facilitate health-related behavior change. Integrating insights from behavioral science and design science can help support the development of more effective mHealth interventions. Behavioral Design (BD) and Design Thinking (DT) have emerged as best practice approaches in their respective fields. Until now, little work has been done to examine how BD and DT can be integrated throughout the mHealth design process.

objectiveThe aim of this scoping review was to map the evidence on how insights from BD and DT can be integrated to guide the design of mHealth interventions. The following questions were addressed: (1) what are the main characteristics of studies that integrate BD and DT during the mHealth design process? (2) what theories, models, and frameworks do design teams use during the mHealth design process? (3) what methods do design teams use to integrate BD and DT during the mHealth design process? and (4) what are key design challenges, implementation considerations, and future directions for integrating BD and DT during mHealth design?

methodsThis review followed the Joanna Briggs Institute reviewer manual and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. Studies were identified from MEDLINE, PsycINFO, Embase, CINAHL, and JMIR by using search terms related to mHealth, BD, and DT. Included studies had to clearly describe their mHealth design process and how behavior change theories, models, frameworks, or techniques were incorporated. Two independent reviewers screened the studies for inclusion and completed the data extraction. A descriptive analysis was conducted.

resultsA total of 75 papers met the inclusion criteria. All studies were published between 2012 and 2021. Studies integrated BD and DT in notable ways, which can be referred to as "Behavioral Design Thinking." Five steps were followed in Behavioral Design Thinking: (1) empathize with users and their behavior change needs, (2) define user and behavior change requirements, (3) ideate user-centered features and behavior change content, (4) prototype a user-centered solution that supports behavior change, and (5) test the solution against users' needs and for its behavior change potential. The key challenges experienced during mHealth design included meaningfully engaging patient and public partners in the design process, translating evidence-based behavior change techniques into actual mHealth features, and planning for how to integrate the mHealth intervention into existing clinical systems.

conclusionsBest practices from BD and DT can be integrated throughout the mHealth design process to ensure that mHealth interventions are purposefully developed to effectively engage users. Although this scoping review clarified how insights from BD and DT can be integrated during mHealth design, future research is needed to identify the most effective design approaches.

Indexed as

Behavioral SciencesTelemedicineBehavior TherapyHealth BehaviorHumansbehavior changedesign thinkingdigital healthhealth behaviormobile applicationmobile healthmobile phoneproduct designscoping reviewsystems designtelemedicineuser-centered design

Identifiers

PMID35293871
PMCPMC8968622

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.