Cited by 264Digital Mental Health InterventionsMobile Health and mHealth ApplicationsBehavioral Health and Interventions

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Just-in-the-Moment Adaptive Interventions (JITAI): A Meta-Analytical Review

Wang, Liyuan, Miller, Lynn Carol·2020·Health Communication

DOI 10.1080/10410236.2019.1652388

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Abstract

A just-in-time, adaptive intervention (JITAI) is an emerging type of intervention that provides tailored support at the exact time of need. It does so using enabling new technologies (e.g., mobile phones, sensors) that capture the changing states of individuals. Extracting effect sizes of primary outcomes produced by 33 empirical studies that used JITAIs, we found moderate to large effect sizes of JITAI treatments compared to (1) waitlist-control conditions (k = 9), Hedges's g = 1.65 and (2) non-JITAI treatments (k = 21), g = 0.89. Also, participants of JITAI interventions showed significant changes (k = 13) in the positive direction (g = 0.79). A series of sensitivity tests suggested that those effects persist. Those effects also persist despite differences in the behaviors of interests (e.g., blood glucose control, recovering alcoholics), duration of the treatments, and participants' age. Two aspects of tailoring, namely: (1) tailoring to what (i.e., both people's previous behavioral patterns and their current need states; with these effects additive) and (2) approach to tailoring (i.e., both using a human agent and an algorithm to decide tailored feedback; with these effects additive), are significantly associated with greater JITAI efficacy.

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Measuring inconsistency in meta-analyses
Higgins, J. P. T., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003) · BMJ · doi:10.1136/bmj.327.7414.557 · Cited by 63,139
Introduction to Meta‐Analysis
Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009) · doi:10.1002/9780470743386 · Cited by 14,225
Just-in-time adaptive interventions (JITAIs) in mobile health: key components and design principles for ongoing health behavior support
Nahum-Shani, I., Smith, S. N., Spring, B. J., Collins, L. M., Witkiewitz, K., Tewari, A., & Murphy, S. A. (2018) · Annals of Behavioral Medicine · doi:10.1007/s12160-016-9830-8 · Cited by 2,171
Ecological Momentary Assessment (Ema) in Behavioral Medicine
Stone, A. A., & Shiffman, S. (1994) · Annals of Behavioral Medicine · doi:10.1093/abm/16.3.199 · Cited by 1,931
Ecological momentary interventions: incorporating mobile technology into psychosocial and health behaviour treatments
Heron, K. E., & Smyth, J. M. (2010) · British Journal of Health Psychology · doi:10.1348/135910709x466063 · Cited by 1,438
A meta-analysis of computer-tailored interventions for health behavior change
Krebs, P., Prochaska, J. O., & Rossi, J. S. (2010) · Preventive Medicine · doi:10.1016/j.ypmed.2010.06.004 · Cited by 854
Comparison of Strategies for Sustaining Weight Loss<subtitle>The Weight Loss Maintenance Randomized Controlled Trial</subtitle>
Svetkey, L. P. (2008) · JAMA · doi:10.1001/jama.299.10.1139 · Cited by 748
Do u smoke after txt? Results of a randomised trial of smoking cessation using mobile phone text messaging
Rodgers, A., Corbett, T., Bramley, D., Riddell, T., Wills, M., Lin, R.-B., & Jones, M. (2005) · Tobacco Control · doi:10.1136/tc.2005.011577 · Cited by 732
Smoking cessation support delivered via mobile phone text messaging (txt2stop): a single-blind, randomised trial
Free, C., Knight, R., Robertson, S., Whittaker, R., Edwards, P., Zhou, W., Rodgers, A., Cairns, J., Kenward, M. G., & Roberts, I. (2011) · The Lancet · doi:10.1016/s0140-6736(11)60701-0 · Cited by 728
A Smartphone Application to Support Recovery From Alcoholism: A Randomized Clinical Trial
Gustafson, D. H., McTavish, F. M., Chih, M.-Y., Atwood, A. K., Johnson, R. A., Boyle, M. G., Levy, M. S., Driscoll, H., Chisholm, S. M., Dillenburg, L., et al. (2014) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2013.4642 · Cited by 692

Show all 52 references

Research works printed but not linked: 5

Borenstein M., 2011, Introduction to m eta-analysis
10.2196/jmr.1005 · DOI
Lipsey M. W., 2001, Applied social research methods series; Vol. 49. Practical meta-analysis
*Miner, A., Kuhn, E., Hoffman, J. E., Owen, J. E., Ruzek, J. I., & Taylor, C. B., 2016, Psychological Trauma: Theory, Research, Practice, and Policy, 8
10.1111/acer.2012.36.issue-3 · DOI

Sorted by citations

Items 201–264 of 264

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Monitoring alcohol craving in daily life: theories and methods for intensive longitudinal psycho-physiological studies
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(2025) · Emerald Group Publishing Limited eBooks · doi:10.1108/978-1-83797-428-320251009
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State of the Science: Reducing the disease burden of depression at the population level with psychological interventions
Cuijpers, P. J. (2026) · Behavior Therapy · doi:10.1016/j.beth.2026.10.003
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Luijsmans, M., Claes, L., Tatnell, R., Houben, M., Vaessen, T., Smeets, T. J. M., Myin‐Germeys, I., & Kiekens, G. (2026) · Internet Interventions · doi:10.1016/j.invent.2026.101014
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Authors: Wang, L., & Miller, L. C.
Affiliations: University of Southern California (US)
Corresponding author: Wang, Liyuan
ORCID: Wang, Liyuan
Miller, Lynn Carol
Venue: Health Communication
Publisher: Informa UK Limited
Published: 2019-09-05
Volume: 35
Issue: 12
Pages: 1531-1544
ISSN: 1041-0236 (ISSN-L)
1532-7027
DOI: 10.1080/10410236.2019.1652388
OpenAlex: W2971759879
Cited by: 264
References: 52
Citations by year: 2026: 53 · 2025: 58 · 2024: 47 · 2023: 43 · 2022: 35 · 2021: 21 · 2020: 6 · 2019: 1
FWCI: 17.84
Type: journal article
Language: en
Open access: closed
Locations: Health Communication (publishedVersion)
PubMed (publishedVersion)
Topics: Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
Keywords: just-in-time adaptive interventions, personalized feedback, tailored support, mobile health, wearable sensors, treatment efficacy, effect size, need states, glycemic control, alcohol recovery, waitlist control
MeSH terms: Behavior Therapy, Humans, Cell Phone

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Just-in-the-Moment Adaptive Interventions (JITAI): A Meta-Analytical Review

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