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Mobile Health Interventions for Improving Health Outcomes in Youth: A Meta-analysis
Open accessAbstract
Importance: Mobile health interventions are increasingly popular in pediatrics; however, it is unclear how effective these interventions are in changing health outcomes. Objective: To determine the effectiveness of mobile health interventions for improving health outcomes in youth 18 years or younger. Data Sources: Studies published through November 30, 2016, were collected through PubMed, Cumulative Index to Nursing and Allied Health Literature, Educational Resources Information Center, and PsychINFO. Backward and forward literature searches were conducted on articles meeting study inclusion criteria. Search terms included telemedicine, eHealth, mobile health, mHealth, app, and mobile application. Study Selection: Search results were limited to infants, children, adolescents, or young adults when possible. Studies were included if quantitative methods were used to evaluate an application of mobile intervention technology in a primary or secondary capacity to promote or modify health behavior in youth 18 years or younger. Studies were excluded if the article was an unpublished dissertation or thesis, the mean age of participants was older than 18 years, the study did not assess a health behavior and disease outcome, or the article did not include sufficient statistics. Inclusion and exclusion criteria were applied by 2 independent coders with 20% overlap. Of 9773 unique articles, 36 articles (containing 37 unique studies with a total of 29 822 participants) met the inclusion criteria. Data Extraction and Synthesis: Of 9773 unique articles, 36 articles (containing 37 unique studies) with a total of 29 822 participants met the inclusion criteria. Effect sizes were calculated from statistical tests that could be converted to standardized mean differences. All aggregate effect sizes and moderator variables were tested using random-effects models. Main Outcomes and Measures: Change in health behavior or disease control. Results: A total of 29 822 participants were included in the studies. In studies that reported sex, the total number of females was 11 226 (53.2%). Of those reporting age, the average was 11.35 years. The random effects aggregate effect size of mobile health interventions was significant (n = 37; Cohen d = 0.22; 95% CI, 0.14-0.29). The random effects model indicated that providing mobile health intervention to a caregiver increased the strength of the intervention effect. Studies that involved caregivers in the intervention produced effect sizes (n = 16; Cohen d = 0.28; 95% CI, 0.18-0.39) larger than those that did not include caregivers (n = 21; Cohen d = 0.13; 95% CI, 0.02-0.25). Other coded variables did not moderate study effect size. Conclusions and Relevance: Mobile health interventions appear to be a viable health behavior change intervention modality for youth. Given the ubiquity of mobile phones, mobile health interventions offer promise in improving public health.
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“However, which theoretical paradigm works best in mHealth interventions remains unclear, especially when previous meta-analyses documented that the use of theory to guide intervention development does not significantly moderate ESs [1].”
From The Comparative Effectiveness of Mobile Phone Interventions in Improving Health Outcomes: Meta-Analytic Review (2019) · cites this paper as [1]
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Citations
Cites
Statistical power analysis for the behavioral sciences
Cohen, J. (1990) · Computers Environment and Urban Systems · doi:10.1016/0198-9715(90)90050-4 · Cited by 65,415
Cochrane Handbook for Systematic Reviews of Interventions: Cochrane Book Series
(2008) · doi:10.1002/9780470712184 · Cited by 25,048
(2000) · Cited by 9,198
The file drawer problem and tolerance for null results.
Rosenthal, R. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.3.638 · Cited by 9,068 · cited 1×
“omnibus test, 634 null findings would be necessary to overturn the findings presented herein.(51)”
BackgroundUpdate on Key Emerging Challenges in Cystic Fibrosis
Jennings, M. T., Riekert, K. A., & Boyle, M. (2014) · Medical Principles and Practice · doi:10.1159/000357646 · Cited by 3,671
The Handbook of Research Synthesis.
Howel, D., Cooper, H., & Hedges, L. V. (1995) · Biometrics · doi:10.2307/2533295 · Cited by 3,657
Webb, T. L., Joseph, J., Yardley, L., & Michie, S. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1376 · Cited by 2,517
Free, C., Phillips, G., Watson, L., Galli, L., Felix, L., Edwards, P., Patel, V., & Haines, A. (2013) · PLoS Medicine · doi:10.1371/journal.pmed.1001363 · Cited by 1,187
Hamine, S., Gerth-Guyette, E., Faulx, D., Green, B. B., & Ginsburg, A. S. (2015) · Journal of Medical Internet Research · doi:10.2196/jmir.3951 · Cited by 1,149 · cited 1×
“Theubiquitousnatureofmobilephoneusecoupledwith continual technological advances have given rise to a proliferation inmobilehealth (mHealth) interventions inwhichmobile devices target a range of health promotion and disease management foci.(5,6)”
BackgroundDesign of an mHealth app for the self-management of adolescent type 1 diabetes: a pilot study
Cafazzo, J. A., Casselman, M., Hamming, N., Katzman, D. K., & Palmert, M. R. (2012) · Journal of Medical Internet Research · doi:10.2196/jmir.2058 · Cited by 676
Flagged first, then by citations
Research works printed but not linked: 4
- [2]Smith A. Chapter one: a portrait of smartphone ownership. PewResearchCenter. http://www.pewinternet.org/2015/04/01/chapter-one-a-portrait-of-smartphone-ownership/. Published April 1, 2015. Accessed September 10, 2016.
- [14]Lu F, Turner KMB. Reducing adolescent obesity with a mobile fitness application: study results of youth age 15 to 17. Paper presented at: 2013 Institute of Electrical and Electronics Engineers 15th International Conference on e-Health Networking, Applications and Services (Healthcom 2013); Lisbon, Portugal. [Google Scholar]
- [15]Higgins J, Green S. Cochrane Handbook for Systematic Reviews of Interventions. Chichester, England: Wiley-Blackwel; 2011. [Google Scholar]
- [32]Hashemian TS, Kritz-Silverstein D, Baker R. Text2Floss: the feasibility and acceptability of a text messaging intervention to improve oral health behavior and knowledge. J Public Health Dent. 2015;75(1):34-41. [DOI] [PubMed] [Google Scholar]
Cited by
Sorted by citations
An overview of and recommendations for more accessible digital mental health services
Lattie, E. G., Stiles-Shields, C., & Graham, A. K. (2022) · Nature Reviews Psychology · doi:10.1038/s44159-021-00003-1 · Cited by 446
Villinger, K., Wahl, D. R., Boeing, H., Schupp, H. T., & Renner, B. (2019) · Obesity Reviews · doi:10.1111/obr.12903 · Cited by 310
Goldberg, S. B., Lam, S. U., Simonsson, O., Torous, J., & Sun, S. (2022) · PLOS Digital Health · doi:10.1371/journal.pdig.0000002 · Cited by 237
“Future primary studies with youth and adolescent samples may be warranted, particularly given evidence of clinical need, acceptability, and potential efficacy of mobile health interventions for this group [66].”
BackgroundBadawy, S. M., & Radovic, A. (2020) · JMIR Pediatrics and Parenting · doi:10.2196/20049 · Cited by 242
Telemedicine in Pediatrics: Systematic Review of Randomized Controlled Trials
Shah, A., & Badawy, S. M. (2021) · JMIR Pediatrics and Parenting · doi:10.2196/22696 · Cited by 199
Treatment of adolescent obesity
Steinbeck, K. S., Lister, N. B., Gow, M. L., & Baur, L. A. (2018) · Nature Reviews Endocrinology · doi:10.1038/s41574-018-0002-8 · Cited by 182
Ramsey, W. A., Heidelberg, R. E., Gilbert, A. M., Heneghan, M. B., Badawy, S. M., & Alberts, N. M. (2019) · Psycho-Oncology · doi:10.1002/pon.5280 · Cited by 173
A Review of the Quality and Impact of Mobile Health Apps
Grundy, Q. (2021) · Annual Review of Public Health · doi:10.1146/annurev-publhealth-052020-103738 · Cited by 167
Sanders, T., Noetel, M., Parker, P., Del Pozo Cruz, B., Biddle, S., Ronto, R., Hulteen, R., Parker, R., Thomas, G., De Cocker, K., et al. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01712-8 · Cited by 148
Early, J., Gonzalez, C., Gordon-Dseagu, V., & Robles-Calderon, L. (2019) · Health Promotion Practice · doi:10.1177/1524839919855391 · Cited by 122
Gerotechnology for Older Adults With Cardiovascular Diseases
Krishnaswami, A., Beavers, C. J., Dorsch, M. P., Dodson, J. A., Creber, R. M., Kitsiou, S., Goyal, P., Maurer, M. S., Wenger, N. K., Croy, D. S., et al. (2020) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2020.09.606 · Cited by 120
Yang, Q., & Van Stee, S. K. (2019) · JMIR mHealth and uHealth · doi:10.2196/11244 · Cited by 113
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Montagni, I., Cariou, T., Feuillet, T., Langlois, E., & Tzourio, C. (2018) · JMIR mhealth and uhealth · doi:10.2196/mhealth.9131 · Cited by 110
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Leech, T., Dorstyn, D., Taylor, A., & Li, W. (2021) · Children and Youth Services Review · doi:10.1016/j.childyouth.2021.106073 · Cited by 100
Virella-Perez, Y. I., Medlow, S., Ho, J., & Steinbeck, K. (2019) · Journal of Medical Internet Research · doi:10.2196/13579 · Cited by 73
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Kilfoy, A., Hsu, T. C., Stockton-Powdrell, C., Whelan, P., Chu, C. H., & Jibb, L. (2024) · npj Digital Medicine · doi:10.1038/s41746-024-01385-1 · Cited by 115
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Fuchs, J. D., Stojanovski, K., Vittinghoff, E., McMahan, V., Hosek, S., Amico, K. R., Kouyate, A., Gilmore, H. J., Buchbinder, S., Lester, R. T., et al. (2018) · AIDS Patient Care and STDs · doi:10.1089/apc.2017.0255 · Cited by 86
Batsis, J. A., Petersen, C. L., Clark, M. M., Cook, S. B., Kotz, D. F., Gooding, T., Roderka, M. N., Al-Nimr, R. I., Pidgeon, D., Haedrich, A., et al. (2021) · BMC Geriatrics · doi:10.1186/s12877-020-01978-x · Cited by 85
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Himes, B. E., Leszinsky, L., Walsh, R. N., Hepner, H., & Wu, A. C. (2019) · The Journal of Allergy and Clinical Immunology In Practice · doi:10.1016/j.jaip.2019.08.034 · Cited by 80
Kim, H., & Seo, K. (2019) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph17010015 · Cited by 76
Hides, L. M., Dingle, G. A., Quinn, C. A., Stoyanov, S. R., Zelenko, O., Tjondronegoro, D., Johnson, D. M., Cockshaw, W. D., & Kavanagh, D. J. (2018) · JMIR mhealth and uhealth · doi:10.2196/11482 · Cited by 71
Danaher, J., Nyholm, S., & Earp, B. D. (2018) · The American Journal of Bioethics · doi:10.1080/15265161.2017.1409823 · Cited by 70
Stoilova, M., Livingstone, S., & Khazbak, R. (2021) · RePEc: Research Papers in Economics · Cited by 66
Shin, Y., Kim, S. K., & Lee, M. (2019) · Public Health Nursing · doi:10.1111/phn.12655 · Cited by 64
Fowler, L. A., Grammer, A. C., Staiano, A. E., Fitzsimmons‐Craft, E. E., Chen, L., Yaeger, L., & Wilfley, D. E. (2021) · International Journal of Obesity · doi:10.1038/s41366-021-00765-x · Cited by 63
Wang, X., Markert, C., & Sasangohar, F. (2021) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720821998110 · Cited by 65
Examining the Correlates of Adolescent Food and Nutrition Knowledge
Brown, R. C., Seabrook, J. A., Stranges, S., Clark, A. F., Haines, J., O’Connor, C. P., Doherty, S. T., & Gilliland, J. (2021) · Nutrients · doi:10.3390/nu13062044 · Cited by 62
The use of mobile phones for the prevention and control of arboviral diseases: a scoping review
Carrillo, M. A., Kroeger, A., Cardenas Sanchez, R., Diaz Monsalve, S., & Runge-Ranzinger, S. (2021) · BMC Public Health · doi:10.1186/s12889-020-10126-4 · Cited by 64
Li, Z., Lu, F., Wu, J., Bao, R., Rao, Y., Yang, Y. J., & Wang, H. (2024) · Journal of Medical Internet Research · doi:10.2196/56556 · Cited by 52
Contemporary approaches to the prevention and management of paediatric obesity: an Australian focus
Mihrshahi, S., Gow, M. L., & Baur, L. A. (2018) · The Medical Journal of Australia · doi:10.5694/mja18.00140 · Cited by 57
Adolescents Are Still Waiting on a Digital Health Revolution
Psihogios, A. M., Lane-Fall, M. B., & Graham, A. K. (2022) · Archives of Pediatrics and Adolescent Medicine · doi:10.1001/jamapediatrics.2022.0500 · Cited by 51
Oh, C., Carducci, B., Vaivada, T., & Bhutta, Z. A. (2022) · PEDIATRICS · doi:10.1542/peds.2021-053852h · Cited by 60
Son, Y., Oh, S., & Kim, E. Y. (2020) · Journal of Advanced Nursing · doi:10.1111/jan.14455 · Cited by 56
Heida, A., Dijkstra, A., Kobold, A. C. M., Rossen, J. W. A., Kindermann, A., Kokke, F. T. M., de Meij, T. G. J., Norbruis, O. F., Weersma, R. K., Wessels, M. M. S., et al. (2017) · Journal of Crohn s and Colitis · doi:10.1093/ecco-jcc/jjx169 · Cited by 50
Tark, R., Metelitsa, M., Akkermann, K., Saks, K., Mikkel, S., & Haljas, K. (2019) · JMIR Serious Games · doi:10.2196/13776 · Cited by 57
Tomines, A. (2019) · Advances in Pediatrics · doi:10.1016/j.yapd.2019.04.005 · Cited by 46
Efficacy of digital health interventions in youth with chronic medical conditions: A meta-analysis
Domhardt, M., Schröder, A., Geirhos, A., Steubl, L., & Baumeister, H. (2021) · Internet Interventions · doi:10.1016/j.invent.2021.100373 · Cited by 45
Effectiveness of an mHealth Intervention for Infant Sleep Disturbances
Leichman, E. S., Gould, R. A., Williamson, A. A., Walters, R. M., & Mindell, J. A. A. (2020) · Behavior Therapy · doi:10.1016/j.beth.2019.12.011 · Cited by 46
Psihogios, A. M., Stiles‐Shields, C., & Neary, M. (2020) · Journal of Pediatric Psychology · doi:10.1093/jpepsy/jsaa094 · Cited by 44
Wang, Y., Mitchell, J. W., Zhang, C., & Liu, Y. (2022) · AIDS Research and Therapy · doi:10.1186/s12981-022-00456-1 · Cited by 44
Badawy, S. M., Barrera, L., Cai, S. W., & Thompson, A. A. (2018) · BioMed Research International · doi:10.1155/2018/8296139 · Cited by 45
Cueto, V., Wang, C.-H. J., & Sanders, L. (2019) · JMIR mhealth and uhealth · doi:10.2196/14458 · Cited by 49
Atujuna, M., Simpson, N., Ngobeni, M., Monese, T., Giovenco, D., Pike, C., Figerova, Z., Visser, M. J., Biriotti, M., Kydd, A., et al. (2021) · Frontiers in Reproductive Health · doi:10.3389/frph.2021.687677 · Cited by 45
Fedele, D. A., McConville, A., Thomas, J. G., McQuaid, E. L., Janicke, D. M., Turner, E. M., Moon, J., & Abu‐Hasan, M. (2017) · Contemporary Clinical Trials · doi:10.1016/j.cct.2017.09.007 · Cited by 43
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Donovan, E., Martin, S. R., Seidman, L. C., Zeltzer, L. K., Cousineau, T. M., Payne, L. A., Trant, M., Weiman, M., Knoll, M., & Federman, N. C. (2019) · JMIR mhealth and uhealth · doi:10.2196/10921 · Cited by 40
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Muhamat, N. A., Hasan, R., Saddki, N., Arshad, M., & Ahmad, M. (2021) · PLoS ONE · doi:10.1371/journal.pone.0257035 · Cited by 44
Nahum-Shani, I., Rabbi, M., Yap, J., Philyaw-Kotov, M. L., Klasnja, P., Bonar, E. E., Cunningham, R. M., Murphy, S. A., & Walton, M. A. (2021) · Health Psychology · doi:10.1037/hea0001101 · Cited by 41
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Cheng, C. F., Werner, N. E., Doutcheva, N., Warner, G., Barton, H. J., Kelly, M. M., Ehlenbach, M. L., Wagner, T., Finesilver, S., Katz, B. J., et al. (2020) · Hospital Pediatrics · doi:10.1542/hpeds.2020-0076 · Cited by 33
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Hind, J. M. (2022) · In clinical practice · doi:10.1007/978-3-030-98808-1_21 · Cited by 38
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Nguyen, N., Léveillé, E., Guadagno, E., Kalisya, L. M., & Poenaru, D. (2020) · Journal of Telemedicine and Telecare · doi:10.1177/1357633x20934682 · Cited by 35
Analysis of real-world data on growth hormone therapy adherence using a connected injection device
Koledova, E. B., Tornincasa, V., & van Dommelen, P. (2020) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-020-01183-1 · Cited by 36
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Self-citationPatel, J., Hung, C., & Katapally, T. R. (2024) · Psychiatry Research · doi:10.1016/j.psychres.2024.116277 · Cited by 29
Schwartz, L. A., Psihogios, A. M., Henry‐Moss, D., Daniel, L. C., Hoeve, E. S. V., Velázquez‐Martin, B., Butler, E. S., Hobbie, W. L., Lunsford, N. B., Sabatino, S. A., et al. (2019) · Clinical Practice in Pediatric Psychology · doi:10.1037/cpp0000272 · Cited by 29
Ramsey, R. R., Holbein, C. E., Powers, S. W., Hershey, A. D., Kabbouche, M. A., O’Brien, H. L., Kacperski, J. E., Shepard, J., & Hommel, K. A. (2018) · Cephalalgia · doi:10.1177/0333102418756864 · Cited by 29
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Carmody, J. K., Denson, L. A., & Hommel, K. A. (2018) · Journal of Pediatric Psychology · doi:10.1093/jpepsy/jsy086 · Cited by 28
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McGill, D. E., Volkening, L. K., Butler, D. A., Wasserman, R. M., Anderson, B. J., & Laffel, L. M. (2019) · Diabetic Medicine · doi:10.1111/dme.13929 · Cited by 27
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Choi, J., Chung, C., & Woo, H. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18073496 · Cited by 25
Kitsao-Wekulo, P., Langat, N., Nampijja, M., Mwaniki, E., Okelo, K., & Kimani-Murage, E. W. (2021) · PLoS ONE · doi:10.1371/journal.pone.0254621 · Cited by 28
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Metadata
- Authors
- Fedele, D. A., Cushing, C. C., Fritz, A., Amaro, C. M., & Ortega, A.
- Affiliations
- University of Florida Health (US)
- University of Kansas (US)
- Corresponding author
- Fedele, David A.
- Venue
- JAMA Pediatrics
- Publisher
- American Medical Association (AMA)
- Published
- 2017-05-01
- Volume
- 171
- Issue
- 5
- Pages
- 461
- ISSN
- 1072-4710 (ISSN-L)
- 2168-6203
- PMC
- PMC6037338
- OpenAlex
- W2601896593
- Cited by
- 316
- References
- 56
- Citations by year
- 2026: 19 · 2025: 28 · 2024: 24 · 2023: 29 · 2022: 48 · 2021: 58 · 2020: 38 · 2019: 31 · 2018: 34 · 2017: 6
- FWCI
- 48.32
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Archives of Pediatrics and Adolescent Medicine (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
- Keywords
- mobile health intervention, mobile health, youth health, health behavior change, disease control, adolescents, children, caregivers, telemedicine, eHealth apps, intervention effectiveness, effect size, child health promotion, disease prevention, health disparities, healthcare workers
- MeSH terms
- Adolescent, Child, Female, Health Promotion, Humans, Infant, Male, Health Behavior, Telemedicine, Young Adult
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