The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Diabetes Buddies: Peer Support Through a Mobile Phone Buddy System
Open accessAbstract
Purpose The purpose of this study is to test the feasibility and acceptability of a mobile phone–based peer support intervention among women in resource-poor settings to self-manage their diabetes. Secondary goals were to evaluate the intervention’s effectiveness to motivate diabetes-related health choices. Methods Women with diabetes (n = 22) in Cape Town, South Africa, participated in a 12-week program focused on providing and applying knowledge of health routines to manage diabetes. Women were linked with a buddy via a mobile phone for support and were questioned daily about a health behavior via text message. Women were assessed at recruitment and then 3 and 6 months later by a trained interviewer using a mobile phone for data collection. The women were evaluated on technology uptake, reduction of body mass index, blood glucose levels, and increases in positive coping and general health-seeking behaviors. Results Women exchanged 16 739 text messages to buddies and received 3144 texts from the project. Women responded to 29% of texted questions (n = 1321/14 582). Women attended at least 9 of 12 possible intervention sessions; a third attended all 12 sessions (n = 8/22). Between baseline and 3 months, women increased their sleep and reported a higher level of positive action and social support coping, yet blood glucose increased by 3.3 points. From 3 to 6 months, spiritual hope decreased and diastolic blood pressure increased. One year later, the 22 women continue to attend meetings. Conclusions Mobile phones are an easy and reliable way to provide peer support and disseminate health messages. Both positive and negative changes were observed in this pilot study.
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In the citing paper
“For patients, unsurprisingly, the two most important enabling resources necessary for a mHealth intervention to be (perceived to be) useful were access to mobile phones [37, 45, 46, 50, 53–55] (also possible through borrowing [46, 50]) and the availability of a functioning stable telecommunications network [20, 36, 39, 42, 45, 47, 48, 52, 55].”
From A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa (2017) · cites this paper as [55]
Experimental — accuracy not yet measuredIn the citing paper
“In 8 studies, mHealth interventions connected a patient to a provider, thus directly facilitating patient access to (professional) care [20, 37, 46, 50, 51, 53–55].”
From A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa (2017) · cites this paper as [55]
In the citing paper
“Participating patients or providers usually required only a few days of training on how to use the mobile technology (such as the mobile phone and its application software) and the consultation procedures [41, 43, 46–48, 50, 55].”
From A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa (2017) · cites this paper as [55]
In the citing paper
“For patients, the most important predisposing characteristic associated with the perception that a mHealth intervention was more useful than an alternative was the patients’ cultural and social acceptance of the mobile technology, which involved familiarity with the technology in the community and absence of negative myths [38, 40, 41, 46, 53, 55].”
From A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa (2017) · cites this paper as [55]
In the citing paper
“In addition, studies reported that mHealth interventions have to be specifically designed to be easy to use for particular groups of patients, such as older age groups [55], or people with low educational levels [50, 55] or poor socio-economic backgrounds [50].”
From A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa (2017) · cites this paper as [55]
In the citing paper
“If patients faced access barriers such as long travel times, waiting times, and high travel costs, mHealth interventions were perceived to be useful [20, 42, 45, 46, 48–50, 52, 53, 55].”
From A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa (2017) · cites this paper as [55]
In the citing paper
“Furthermore, three studies found that sicker patients were more likely to use the interventions, possibly because they found it easier to use the mHealth interventions rather than, for instance, walk to a provider [20, 51, 55].”
From A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa (2017) · cites this paper as [55]
In the citing paper
“Enabling resources for first-contact providers were access to basic infrastructure, such as electric power and functioning medical technologies [49, 52], ambulance services and good roads [46, 47], as well as the affordability of telecommunication services and other operating costs [50, 54, 55] (see Table 2).”
From A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa (2017) · cites this paper as [55]
In the citing paper
“Furthermore, (first-contact) providers reported that they needed support in order to follow guidelines [50, 54, 55] and that mHealth could contribute to overcoming barriers to accessing supervision [37, 40–42, 47, 51].”
From A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa (2017) · cites this paper as [55]
In the citing paper
“Other enabling resources were assurance of privacy [43, 48], support from partners/relatives [51, 55], reduced costs of travel, and reduced time away from home or work [24, 50–53].”
From A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa (2017) · cites this paper as [55]
In the citing paper
“For patients, unsurprisingly, the two most important enabling resources necessary for a mHealth intervention to be (perceived to be) useful were access to mobile phones [37, 45, 46, 50, 53–55] (also possible through borrowing [46, 50]) and the availability of a functioning stable telecommunications network [20, 36, 39, 42, 45, 47, 48, 52, 55].”
From A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa (2017) · cites this paper as [55]
In the citing paper
“For (specialized) healthcare providers, the most important enabling resources were a tolerable additional workload [40, 46, 47], the use of financial incentives [47, 55], and the availability of policy guidelines regarding data protection, phone usage, etc. [40, 43, 45, 52].”
From A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa (2017) · cites this paper as [55]
In the citing paper
“Enabling resources influencing patients’ perceived ease of use of mHealth interventions included the durability and portability of mobile phones [37, 55] and the low complexity of the technology, for example, short message service (SMS) and icons [53, 55].”
From A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa (2017) · cites this paper as [55]
In the citing paper
“Enabling resources influencing patients’ perceived ease of use of mHealth interventions included the durability and portability of mobile phones [37, 55] and the low complexity of the technology, for example, short message service (SMS) and icons [53, 55].”
From A realist review of mobile phone-based health interventions for non-communicable disease management in sub-Saharan Africa (2017) · cites this paper as [55]
In the citing paper
“Results showed no evidence of significant change in health over a 6-month period, although the sample size was very small (n=22) (32).”
From Assessing the impact of mHealth interventions in low- and middle-income countries – what has been shown to work? (2014) · cites this paper as [32]
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Citations
Cites
Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin
(2002) · New England Journal of Medicine · doi:10.1056/nejmoa012512 · Cited by 19,011
Wild, S., Roglic, G., Green, A., Sicree, R., & King, H. (2004) · Diabetes Care · doi:10.2337/diacare.27.5.1047 · Cited by 15,297
Global estimates of the prevalence of diabetes for 2010 and 2030
Shaw, J. E., Sicree, R. A., & Zimmet, P. Z. (2010) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2009.10.007 · Cited by 7,216
The International Telecommunication Union
Jones, R. W. (2002) · Digest - IEEE Antennas and Propagation Society. International Symposium · doi:10.1109/aps.1997.631791 · Cited by 1,903
Beneficial health effects of modest weight loss.
Goldstein, D. J. (1992) · PubMed · Cited by 915
Diabetes and obesity: the twin epidemics
Smyth, S., & Heron, A. (2006) · Nature Medicine · doi:10.1038/nm0106-75 · Cited by 643 · cited 1×
“It is unlikely that the resources will be present within the health care system to manage the rising epidemic of diabetes and obesity-linked diseases.(24,25) Community health workers and personal self-management of family's daily routines will be critical in the next decades.”
BackgroundObesity in South Africa: The South African Demographic and Health Survey
Puoane, T. R., Steyn, K., Bradshaw, D., Laubscher, R., Fourie, J. M., Lambert, V., & Mbananga, N. (2002) · Obesity Research · doi:10.1038/oby.2002.141 · Cited by 572 · cited 1×
“5%).(6) Black women have higher rates of obesity (31%-34%) than white (18%-24%), Indian (20%-22%), or colored (26%-28%) women.”
BackgroundEffect of Degree of Weight Loss on Health Benefits
Blackburn, G. L. (1995) · Obesity Research · doi:10.1002/j.1550-8528.1995.tb00466.x · Cited by 500
Long-term Effects of Modest Weight Loss in Type II Diabetic Patients
Wing, R. R. (1987) · Archives of Internal Medicine · doi:10.1001/archinte.1987.00370100063012 · Cited by 484
Obesity, weight loss and prognosis in type 2 diabetes
Lean, M. E. J., Powrie, J. K., Anderson, A. S., & Garthwaite, P. H. (1990) · Diabetic Medicine · doi:10.1111/j.1464-5491.1990.tb01375.x · Cited by 318
Clinical Outcomes and Cost-Effectiveness of Strategies for Managing People at High Risk for Diabetes
Eddy, D. M., Schlessinger, L., & Kahn, R. (2005) · Annals of Internal Medicine · doi:10.7326/0003-4819-143-4-200508160-00006 · Cited by 318 · cited 1×
“Adopting and maintaining a healthy lifestyle is key to lifelong diabetes management and achieving positive, long-term outcomes.(11,12) In treating type 2 diabetes mellitus (T2DM) in adults in the United States, reducing body weight via a lifestyle program that focuses on increasing exercise and developing healthier di…”
BackgroundThe Prevention and Treatment of Obesity: Application to type 2 diabetes
Maggio, C. A., & Pi-Sunyer, X. (1997) · Diabetes Care · doi:10.2337/diacare.20.11.1744 · Cited by 261
Obesity in South Africa: challenges for government and health professionals
Kruger, H. S., Puoane, T. R., Senekal, M., & van der Merwe, M.-T. (2005) · Public Health Nutrition · doi:10.1079/phn2005785 · Cited by 235 · cited 1×
“Simultaneously, many South Africans consider being overweight desirable.(4,5) Obesity is especially prevalent among South African women (30%) compared with men (7.”
BackgroundLevitt, N. S., Katzenellenbogen, J. M., Bradshaw, D., Hoffman, M. N., & Bonńici, F. (1993) · Diabetes Care · doi:10.2337/diacare.16.4.601 · Cited by 182 · cited 1×
“8% to 8%.(2,3) In 2005, diabetes was the sixth leading cause of death in South Africa, whereas HIV was the tenth.”
BackgroundAn Intervention for Parents With AIDS and Their Adolescent Children
Rotheram‐Borus, M. J., Lee, M. B., Gwadz, M. V., & Draimin, B. (2001) · American Journal of Public Health · doi:10.2105/ajph.91.8.1294 · Cited by 170
Self-citationMerwe, M. ‐. V. D., & Pepper, M. S. (2006) · Obesity Reviews · doi:10.1111/j.1467-789x.2006.00237.x · Cited by 145 · cited 2×
“Black women have higher rates of obesity (31%-34%) than white (18%-24%), Indian (20%-22%), or colored (26%-28%) women.(7)* In addition, 1 in 5 black South African children are stunted in childhood,(8) which has been associated with later obesity, diabetes, and hypertension as adults.”
BackgroundThe National Diabetes Education Program
Funnell, M. M. (2011) · AJN American Journal of Nursing · doi:10.1097/01.naj.0000408193.98005.2b · Cited by 138
Chaturvedi, N., & Fuller, J. (1995) · Diabetes Care · doi:10.2337/diacare.18.6.766 · Cited by 105
Cross-cultural and international adaptation of peer support for diabetes management
Fisher, E. B., Earp, J. A., Maman, S., & Zolotor, A. (2010) · Family Practice · doi:10.1093/fampra/cmp013 · Cited by 101 · cited 1×
“This approach is also consistent with the principle, endorsed by South Africa’s Department of Health, of using paraprofessionals to extend care for chronic lifestyle diseases beyond public health sector professionals.(10)”
ResultFaber, M., & Kruger, H. S. (2005) · PubMed · Cited by 71
Mbeh, G. N., Edwards, R., Ngufor, G., Assah, F. K., Fezeu, L., & Mbanya, J. C. (2010) · Global Health Promotion · doi:10.1177/1757975910363925 · Cited by 42 · cited 1×
“Beliefs in retribution for sins and in witchcraft were common.(21,22) Women reported being very religious.”
BackgroundFamily‐centred HIV interventions: lessons from the field of parental depression
Tomlinson, M. (2010) · Journal of the International AIDS Society · doi:10.1186/1758-2652-13-s2-s9 · Cited by 11 · cited 1×
“Community health workers and personal self-management of family's daily routines will be critical in the next decades.(26) This pilot reflects a model that could be a prototype of peer support and intervention that could be sustained at a community or neighborhood level.”
BackgroundSelf-citation
Research works printed but not linked: 5
- Faber M, 2005, Ethn Dis, 15, 238
- Steyn K, 2006, Health Services Research in South Africa
- Goldstein DJ, 1992, Int J Obes Relat Metab Disord, 16, 397
- Derogatis LR, 1993, Brief Symptom Inventory: Administration, Scoring, and Procedures Manual
- Golooba-Mutebi F, 2007, Afr Soc Rev, 11, 64
Cited by
Sorted by citations
Interactive telemedicine: effects on professional practice and health care outcomes
Flodgren, G., Rachas, A., Farmer, A. J., Inzitari, M., & Shepperd, S. (2015) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd002098.pub2 · Cited by 806
Aranda-Jan, C. B., Mohutsiwa-Dibe, N., & Loukanova, S. (2014) · BMC Public Health · doi:10.1186/1471-2458-14-188 · Cited by 644
“existing networks, reducing phone costs) [18,22,26,49,50,56,58,59,62,63], and is easy to use [43] -Limited text capacity of mobile phones and text messages (e.”
InfluentialVandelanotte, C., Müller, A. M., Short, C. E., Hingle, M., Nathan, N., Williams, S. L., Lopez, M. L., Parekh, S., & Maher, C. A. (2016) · Journal of Nutrition Education and Behavior · doi:10.1016/j.jneb.2015.12.006 · Cited by 396
Hall, C. S., Fottrell, E., Wilkinson, S., & Byass, P. (2014) · Global Health Action · doi:10.3402/gha.v7.25606 · Cited by 384
“Results showed no evidence of significant change in health over a 6-month period, although the sample size was very small (n"22) (32).”
Müller, A. M., Alley, S., Schoeppe, S., & Vandelanotte, C. (2016) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-016-0434-2 · Cited by 213
“positive effects on either physical activity or diet outcomes following an e-& mHealth intervention [35, 42, 47, 50].”
Influential
Metadata
- Authors
- Rotheram-Borus, M. J., Tomlinson, M., Gwegwe, M., Comulada, W. S., Kaufman, N., & Keim, M.
- Affiliations
- Center for Community Health, University of California at Los Angeles, Los Angeles, California (Dr Rotheram-Borus, Dr Comulada)
- University of California, Los Angeles (US)
- Venue
- The Diabetes Educator
- Publisher
- SAGE Publications
- Published
- 2012-04-30
- Volume
- 38
- Issue
- 3
- Pages
- 357-365
- ISSN
- 0145-7217 (ISSN-L)
- 1554-6063
- PMC
- PMC4059372
- OpenAlex
- W2146644753
- Cited by
- 108
- References
- 22
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 3 · 2023: 1 · 2022: 6 · 2021: 7 · 2020: 6 · 2019: 7 · 2018: 14 · 2017: 9 · 2016: 15 · 2015: 11 · 2014: 15 · 2013: 8 · 2012: 1
- FWCI
- 19.89
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- The Science of Diabetes Self-Management and Care (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- SUNScholar (Stellenbosch University) (submittedVersion)
- Funders
- National Institute of Mental Health (P30MH058107)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- diabetes self-management, peer support, mobile phone intervention, text messaging, women with diabetes, resource-limited settings, feasibility and acceptability, glycemic control, body mass index, sleep, coping, health-seeking behavior, diastolic blood pressure, Cape Town
- MeSH terms
- Adult, Aged, Blood Glucose, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Feasibility Studies, Health Services Accessibility, Humans, Middle Aged, Monitoring, Physiologic, Motivation, Pilot Projects, Surveys and Questionnaires, Self Care, Social Support, South Africa, Health Behavior, Young Adult, Text Messaging
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