Using mobile apps to promote a healthy lifestyle among adolescents and students: a review of the theoretical basis and lessons learned.
Open accessAbstract
BACKGROUND: European adolescents and students tend to have low levels of physical activity and eat unhealthy foods, and the prevalence of overweight and obesity has increased, which poses a public health challenge. Mobile apps play an important role in their daily lives, suggesting their potential to be used in health-promoting strategies. OBJECTIVE: This review aimed to explore how mobile apps can contribute to the promotion of healthy nutrition, physical activity, and prevention of overweight in adolescents and students. For the apps identified, the review describes the content, the theoretical mechanisms applied, and lessons learned. METHODS: The databases Scopus, MEDLINE, Embase, and PsycINFO were searched for English-language publications from January 2009 to November 2013. Studies were included if (1) the primary component of the intervention involves an app; (2) the intervention targets healthy nutrition, or physical activity, or overweight prevention; and (3) the target group included adolescents or students (aged 12-25 years). RESULTS: A total of 15 studies were included, which describe 12 unique apps. Ten of these apps functioned as monitoring tools for assessing dietary intake or physical activity levels. The other apps used a Web-based platform to challenge users to exercise and to allow users to list and photograph their problem foods. For 5 apps, the behavioral theory underpinning their development was clearly specified. Frequently applied behavior change techniques are prompting self-monitoring of behavior and providing feedback on performance. Apps can function self-contained, but most of them are used as part of therapy or to strengthen school programs. From the age of 10 years users may be capable of using apps. Only 4 apps were developed specifically for adolescents. All apps were tested on a small scale and for a short period. CONCLUSIONS: Despite large potential and abundant usage by young people, limited research is available on apps and health promotion for adolescents. Apps seem to be a promising health promotion strategy as a monitoring tool. Apps can enable users to set targets, enhance self-monitoring, and increase awareness. Three apps incorporated social features, making them "social media," but hardly any evidence appeared available about their potential.
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Several mobile apps have been developed to help students keep track of how they spend their time in the study situation.
“In recent years, several mobile apps have been developed to help students keep track of how they spend their time in the study situation (e.g., Dute et al., 2016)”
From How Study Environments Foster Academic Procrastination: Overview and Recommendations (2020) · cites this paper as Dute et al., 2016
The Results (Mobile App Characteristics; page unavailable) describe several apps used by adolescents and students to monitor diet or physical activity. They do not describe apps that track how students spend their time studying, so the claimed purpose is unsupported. (LLM, conf=0.80)
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Cites
Users of the world, unite! The challenges and opportunities of Social Media
Kaplan, A. M., & Haenlein, M. (2010) · Business Horizons · doi:10.1016/j.bushor.2009.09.003 · Cited by 17,875 · cited 1× · see citing works
“Kaplan and Haenlein [35] describe that research into social media should acknowledge features like social presence and media richness, and social processes, which includes self-presentation and self-disclosure.”
The Transtheoretical Model of Health Behavior Change.
Prochaska, J. O., & Velicer, W. F. (1997) · American Journal of Health Promotion · doi:10.4278/0890-1171-12.1.38 · Cited by 7,782 · see citing works
The theory of planned behaviour: Reactions and reflections
Ajzen, I. (2011) · Psychology and Health · doi:10.1080/08870446.2011.613995 · Cited by 4,846 · see citing works
A taxonomy of behavior change techniques used in interventions
Abraham, C., & Michie, S. (2008) · Health Psychology · doi:10.1037/0278-6133.27.3.379 · Cited by 2,525 · see citing works
Webb, T. L., Joseph, J., Yardley, L., & Michie, S. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1376 · Cited by 2,517 · see citing works
Currie, C. E., Zanotti, C., Morgan, A. M., Currie, D. B., de Looze, M. E., Roberts, C., Samdal, O., Smith, O. R. F., & Barnekow, V. (2012) · Cited by 1,591 · see citing works
Moderate-to-Vigorous Physical Activity From Ages 9 to 15 Years
Nader, P. R. (2008) · JAMA · doi:10.1001/jama.300.3.295 · Cited by 1,213 · see citing works
Carter, M. C., Burley, V. J., Nykjaer, C., & Cade, J. E. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2283 · Cited by 666 · see citing works
Patrick, H., & Williams, G. C. (2012) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/1479-5868-9-18 · Cited by 481 · see citing works
Behavior Change Techniques in Top-Ranked Mobile Apps for Physical Activity
Conroy, D. E., Yang, C., & Maher, J. P. (2014) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2014.01.010 · Cited by 466 · see citing works
Use of Social Media in Health Promotion
Neiger, B. L., Thackeray, R., Wagenen, S. A. V., Hanson, C. L., West, J. H., Barnes, M., & Fagen, M. C. (2012) · Health Promotion Practice · doi:10.1177/1524839911433467 · Cited by 417 · see citing works
Online Prevention Aimed at Lifestyle Behaviors: A Systematic Review of Reviews
Kohl, L. F., Crutzen, R., & de Vries, N. K. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2665 · Cited by 388 · see citing works
The Use of Mobile Devices in Aiding Dietary Assessment and Evaluation
Zhu, F., Bosch, M., Woo, I., Kim, S., Boushey, C. J., Ebert, D. S., & Delp, E. J. (2010) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2010.2051471 · Cited by 355 · see citing works
Weight loss—there is an app for that! But does it adhere to evidence-informed practices?
Breton, E. R., Fuemmeler, B. F., & Abroms, L. C. (2011) · Translational Behavioral Medicine · doi:10.1007/s13142-011-0076-5 · Cited by 276 · see citing works
Evidence-Based Development of a Mobile Telephone Food Record
Six, B. L., Schap, T. E., Zhu, F. M., Mariappan, A., Bosch, M., Delp, E. J., Ebert, D. S., Kerr, D. A., & Boushey, C. J. (2009) · Journal of the American Dietetic Association · doi:10.1016/j.jada.2009.10.010 · Cited by 200 · see citing works
Development of Smartphone Applications for Nutrition and Physical Activity Behavior Change
Hebden, L., Cook, A., van der Ploeg, H. P., & Allman-Farinelli, M. (2012) · JMIR Research Protocols · doi:10.2196/resprot.2205 · Cited by 160 · cited 6× · see citing works
“Another example of using the model by Hebden et al [17] is that users receive motivational tips as a source of positive encouragement to enhance self-efficacy.”
InfluentialDunton, G. F., Liao, Y., Intille, S. S., Spruijt‐Metz, D., & Pentz, M. (2010) · Obesity · doi:10.1038/oby.2010.302 · Cited by 149 · see citing works
Carter, M. C., Burley, V. J., Nykjaer, C., & Cade, J. E. (2013) · British Journal of Nutrition · doi:10.1017/s0007114512001353 · Cited by 144 · see citing works
Kerr, D. A., Pollard, C. M., Howat, P. A., Delp, E. J., Pickering, M. R., Kerr, K. R., Dhaliwal, S. S., Pratt, I., Wright, J., & Boushey, C. J. (2012) · BMC Public Health · doi:10.1186/1471-2458-12-477 · Cited by 69 · see citing works
Hebden, L., Balestracci, K., McGeechan, K., Denney‐Wilson, E., Harris, M., Bauman, A. E., & Allman-Farinelli, M. A. (2013) · Trials · doi:10.1186/1745-6215-14-75 · Cited by 69 · see citing works
Writing Health Communication: An Evidence-Based Guide
Abraham, C., & Kools, M. (2012) · SAGE Publications Ltd eBooks · doi:10.4135/9781446288054 · Cited by 61 · see citing works
Overweight Prevention Implemented by Primary School Teachers: A Randomised Controlled Trial
Brandstetter, S., Klenk, J., Berg, S., Galm, C., Fritz, M., Peter, R., Prokopchuk, D., Steiner, R. P., Wartha, O., Steinacker, J. M., et al. (2012) · Obesity Facts · doi:10.1159/000336255 · Cited by 58 · see citing works
Schiel, R., Kaps, A., & Bieber, G. (2011) · Appetite · doi:10.1016/j.appet.2011.11.021 · Cited by 45 · see citing works
Six, B. L., Schap, T. E., Kerr, D. A., & Boushey, C. J. (2011) · Journal of Food Composition and Analysis · doi:10.1016/j.jfca.2011.06.006 · Cited by 31 · see citing works
Identification of determinants for weight reduction in overweight and obese children and adolescents
Schiel, R., Kaps, A., Bieber, G., Kramer, G., Seebach, H., & Hoffmeyer, A. (2010) · Journal of Telemedicine and Telecare · doi:10.1258/jtt.2010.091005 · Cited by 22 · see citing works
Suzuki, A., Pope, B. T., Roe, D. J., et al. (2012) · The FASEB Journal · doi:10.1096/fasebj.26.1_supplement.131.4 · Cited by 3 · see citing works
Usability of mobile phone food records to assess dietary intake in adolescents
Casperson, S. L., Reineke, J., Sieling, J., Moon, J., & Roemmich, J. N. (2013) · The FASEB Journal · doi:10.1096/fasebj.27.1_supplement.230.2 · Cited by 2 · see citing works
Using smartphones to maintain engagement of youth participation in 8‐week walking program
Hongu, N. K., Pope, B. T., Martinez, C. L., et al. (2013) · The FASEB Journal · doi:10.1096/fasebj.27.1_supplement.36.4 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [3]Barnekow V Currie C Letsch C de Looze M Morgan A A snapshot of the health of young people in Europe. A Report Prepared for the European Commission Conference on Youth Health, Brussels, Belgium, 9–10 July 2009 2009 Denmark World Health Organization Europe http://www.euro.who.int/__data/assets/pdf_file/0013/70114/E93036.pdf
Cited by
Sorted by citations
Young people’s use of digital health technologies in the global north: Narrative review
Lupton, D. (2021) · Journal of Medical Internet Research · doi:10.2196/18286 · Cited by 211 · see citing works
How Study Environments Foster Academic Procrastination: Overview and Recommendations
Svartdal, F., Dahl, T. I., Gamst-Klaussen, T., Koppenborg, M., & Klingsieck, K. B. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.540910 · Cited by 159 · see citing works
Technologies and Health Inequities
Timmermans, S., & Kaufman, R. (2020) · Annual Review of Sociology · doi:10.1146/annurev-soc-121919-054802 · Cited by 83 · see citing works
- Authors
- Dute, D. J., Bemelmans, W. J. E., & Breda, J.
- Affiliations
- National Institute for Public Health and the Environment (NL)
- World Health Organization Regional Office for Europe (DK)
- Corresponding author
- Bemelmans, Wanda Jose Erika
- Venue
- JMIR mhealth and uhealth
- Publisher
- JMIR Publications Inc.
- Published
- 2016-05-05
- Volume
- 4
- Issue
- 2
- Pages
- e39
- ISSN
- 2291-5222 (ISSN-L)
- PMC
- PMC4873621
- OpenAlex
- W2345718830
- Cited by
- 142
- References
- 28
- Citations by year
- 2026: 4 · 2025: 13 · 2024: 15 · 2023: 18 · 2022: 16 · 2021: 15 · 2020: 19 · 2019: 14 · 2018: 14 · 2017: 12 · 2016: 2
- FWCI
- 26.08
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JMIR mhealth and uhealth (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Rivm (National Institute for Public Health and the Environment) (submittedVersion)
- Funders
- World Health Organization
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- mobile health apps, health promotion, adolescents, students, physical activity, healthy eating, overweight prevention, obesity, self-monitoring, behaviour change techniques, feedback, dietary monitoring, social media, theoretical mechanisms
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