A pilot study of mobile phone-based therapy for obese patients
Abstract
Summary We conducted a pilot study to assess the feasibility of a web-based therapy management system with mobile phone access to support obese patients. A total of 25 patients participated in the study. The mean age of the patients was 48 years. The mean body mass index of the patients at recruitment was 35.6 kg/m 2. The mean observation period was 70 days. A total of 361 successful data transmissions was performed — the mean number of transmissions per patient was 14. The total number of outgoing reminder messages was 123, corresponding to 4.9 reminder messages per patient. At the end of the study, there were significant reductions of 2.4 cm in abdominal girth ( P < 0.001), 2.4 kg in bodyweight ( P < 0.001) and 0.78 kg/m 2 in body mass index ( P < 0.001). In a questionnaire at the end of the study, the majority of the participants gave answers that indicated a positive attitude towards the system. The pilot study showed that mobile phones can be utilized as patient terminals for therapy in patients suffering from obesity.
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Mobile devices have been used successfully to provide dietary guidance and to self-monitor weight and other health-related variables and dietary intake.
“Mobile devices have been used successfully to provide dietary guidance [12] and self-monitor weight and other health-related variables [13,14] and dietary intake [15].”
From Tweets, Apps, and Pods: Results of the 6-Month Mobile Pounds Off Digitally (Mobile POD) Randomized Weight-Loss Intervention Among Adults (2011) · cites this paper as [14]
Cites
Obesity : Preventing and managing the global epidemic
Akram, D. S., Astrup, A. V., Atinmo, T., Boissin, J.-L., Bray, G. A., Carroll, K. N., Chitson, P., Chen, C., Dietz, W. H., Hill, J. O., et al. (2000) · Research at the University of Copenhagen (University of Copenhagen) · Cited by 12,945 · see citing works
Dansinger, M. L., Gleason, J. A., Griffith, J. L., Selker, H. P., & Schaefer, E. J. (2005) · JAMA · doi:10.1001/jama.293.1.43 · Cited by 1,726 · see citing works
The efficacy of tailored interventions
Ryan, P., & Lauver, D. R. (2002) · Journal of Nursing Scholarship · doi:10.1111/j.1547-5069.2002.00331.x · Cited by 230 · see citing works
Assessing dietary intake in the management of obesity
O'Neil, P. M. (2001) · Obesity Research · doi:10.1002/oby.2001.9.s5.361 · Cited by 48 · see citing works
Morak, J., Kollmann, A., & Schreier, G. (2007) · PubMed · Cited by 15 · see citing works
Self-citationUtilizing Mobile Phones as Patient Terminal in Managing Chronic Diseases
Kollmann, A., Kästner, P., & Schreier, G. (2011) · IGI Global eBooks · doi:10.4018/978-1-59140-658-7.ch010 · Cited by 11 · see citing works
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Mapping mHealth research: a decade of evolution
Fiordelli, M., Diviani, N., & Schulz, P. J. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2430 · Cited by 570 · see citing works
Turner-McGrievy, G., & Tate, D. (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1841 · Cited by 263 · see citing works
Shaw, R., & Bosworth, H. (2012) · Health Informatics Journal · doi:10.1177/1460458212442422 · Cited by 131 · see citing works
Evaluation of a mobile phone-based diet game for weight control
Lee, W., Chae, Y. M., Kim, S., Ho, S. H., & Choi, I. (2010) · Journal of Telemedicine and Telecare · doi:10.1258/jtt.2010.090913 · Cited by 92 · see citing works
Sze, Y. Y., Daniel, T. O., Kilanowski, C. K., Collins, R. L., & Epstein, L. H. (2015) · JMIR mHealth and uHealth · doi:10.2196/mhealth.4603 · Cited by 94 · see citing works
Rao, G., Burke, L. E., Spring, B. J., Ewing, L. J., Turk, M., Lichtenstein, A. H., Cornier, M.-A., Spence, J. D., Coons, M., & on behalf of the American Heart Association Obesity Committee of the Council on Nutrition, P. A. A. M. (2011) · Circulation · doi:10.1161/cir.0b013e31822b9543 · Cited by 90 · see citing works
Sociotechnical Challenges and Progress in Using Social Media for Health
Munson, S. A., Cavusoglu, H., Frisch, L., & Fels, S. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2792 · Cited by 57 · see citing works
Castelnuovo, G., & Simpson, S. (2011) · Clinical Practice & Epidemiology in Mental Health · doi:10.2174/1745017901107010005 · Cited by 34 · see citing works
Wireless and Mobile Technologies Improving Diabetes Self-Management
Årsand, E., Tatara, N., & Hartvigsen, G. (2011) · Handbook of Research on Mobility and Computing · doi:10.4018/978-1-60960-042-6.ch009 · Cited by 17 · see citing works
- Authors
- Morak, J., Schindler, K., Goerzer, E., Kastner, P., Toplak, H., Ludvik, B., & Schreier, G.
- Affiliations
- AIT Austrian Institute of Technology GmbH (AT)
- Medical University of Vienna (AT)
- Medical University of Graz (AT)
- Department of Biomedical Engineering, Division of E-health Systems, Austrian Research Centers GmbH –ARC, Graz
- Venue
- Journal of Telemedicine and Telecare
- Publisher
- SAGE Publications
- Published
- 2008-03-01
- Volume
- 14
- Issue
- 3
- Pages
- 147-149
- ISSN
- 1357-633X (ISSN-L)
- 1758-1109
- OpenAlex
- W2009567402
- Cited by
- 40
- References
- 6
- Citations by year
- 2023: 1 · 2021: 2 · 2019: 2 · 2018: 2 · 2017: 3 · 2015: 2 · 2014: 7 · 2013: 5 · 2012: 3
- FWCI
- 8.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Telemedicine and Telecare (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Physical Sciences › Computer Science › Information Systems › Mobile Learning in Education
- Keywords
- obesity, remote patient monitoring, weight loss, body mass index, abdominal girth, reminders, feasibility, patient attitudes
- MeSH terms
- Diabetes Mellitus, Type 2, Feasibility Studies, Female, Humans, Male, Middle Aged, Obesity, Patient Compliance, Pilot Projects, Self Care, Body Mass Index, Telemedicine, Cell Phone
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