Evidence map›Paper›PMID 34806995›Full record

SynthesisJMIR mHealth and uHealth2021

Smartphone-Delivered Ecological Momentary Interventions Based on Ecological Momentary Assessments to Promote Health Behaviors: Systematic Review and Adapted Checklist for Reporting Ecological Momentary Assessment and Intervention Studies.

Kim Phuong Dao, Katrien De Cocker, Huong Ly Tong, A Baki Kocaballi, Clara Chow, Liliana Laranjo

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in JMIR mHealth and uHealth, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
82citing papers in PubMed, 9 pooled it
10.6field-weighted citation impact, top 1% 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.

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

82 citing papers in PubMed, 9 syntheses or guidelines pooled it, 119 citations in OpenAlex.

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22 more citing papers are in PubMed but not listed here.

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

6 authors at 3 institutions in 1 country.

Kim Phuong DaoWestmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.ORCID 0000-0001-5628-5453
Katrien De Cocker *Institute for Resilient Regions, Centre for Health Research, University of Southern Queensland, Springfield Central, Australia.ORCID 0000-0001-7510-4419
Huong Ly Tong *Westmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.ORCID 0000-0002-8462-0105
A Baki KocaballiSchool of Computer Science, Faculty of Engineering & Information Technology, University of Technology Sydney, Sydney, Australia.ORCID 0000-0002-8328-5317
Clara ChowWestmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.ORCID 0000-0003-4693-0038
Liliana LaranjoWestmead Applied Research Centre, Faculty of Medicine and Health, The University of Sydney, Sydney, Australia.ORCID 0000-0003-1020-3402
The University of Sydney · AUUniversity of Southern Queensland · AUUniversity of Technology Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealthy behaviors are crucial for maintaining a person's health and well-being. The effects of health behavior interventions are mediated by individual and contextual factors that vary over time. Recently emerging smartphone-based ecological momentary interventions (EMIs) can use real-time user reports (ecological momentary assessments [EMAs]) to trigger appropriate support when needed in daily life.

objectiveThis systematic review aims to assess the characteristics of smartphone-delivered EMIs using self-reported EMAs in relation to their effects on health behaviors, user engagement, and user perspectives.

methodsWe searched MEDLINE, Embase, PsycINFO, and CINAHL in June 2019 and updated the search in March 2020. We included experimental studies that incorporated EMIs based on EMAs delivered through smartphone apps to promote health behaviors in any health domain. Studies were independently screened. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. We performed a narrative synthesis of intervention effects, user perspectives and engagement, and intervention design and characteristics. Quality appraisal was conducted for all included studies.

resultsWe included 19 papers describing 17 unique studies and comprising 652 participants. Most studies were quasi-experimental (13/17, 76%), had small sample sizes, and great heterogeneity in intervention designs and measurements. EMIs were most popular in the mental health domain (8/17, 47%), followed by substance abuse (3/17, 18%), diet, weight loss, physical activity (4/17, 24%), and smoking (2/17, 12%). Of the 17 studies, the 4 (24%) included randomized controlled trials reported nonstatistically significant effects on health behaviors, and 4 (24%) quasi-experimental studies reported statistically significant pre-post improvements in self-reported primary outcomes, namely depressive (P<.001) and psychotic symptoms (P=.03), drinking frequency (P<.001), and eating patterns (P=.01). EMA was commonly used to capture subjective experiences as well as behaviors, whereas sensors were rarely used. Generally, users perceived EMIs to be helpful. Common suggestions for improvement included enhancing personalization, multimedia and interactive capabilities (eg, voice recording), and lowering the EMA reporting burden. EMI and EMA components were rarely reported and were not described in a standardized manner across studies, hampering progress in this field. A reporting checklist was developed to facilitate the interpretation and comparison of findings and enhance the transparency and replicability of future studies using EMAs and EMIs.

conclusionsThe use of smartphone-delivered EMIs using self-reported EMAs to promote behavior change is an emerging area of research, with few studies evaluating efficacy. Such interventions could present an opportunity to enhance health but need further assessment in larger participant cohorts and well-designed evaluations following reporting checklists. Future research should explore combining self-reported EMAs of subjective experiences with objective data passively collected via sensors to promote personalization while minimizing user burden, as well as explore different EMA data collection methods (eg, chatbots).

trial registrationPROSPERO CRD42019138739; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=138739.

Indexed as

ChecklistEcological Momentary AssessmentHealth BehaviorHealth PromotionHumansSmartphonebehavior changeecological momentary assessmentecological momentary interventionhealth behaviormHealthmobile healthmobile phonesmartphone apps

Identifiers

PMID34806995
PMCPMC8663593
OpenAlexW3183602896

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.