Texting From the Bush: Data Collection Using SMS Text Messaging in Areas of Low Network Coverage From Low-Literacy Providers
Abstract
Mobile health technology, specifically Short Message Service (SMS), provides a low-cost medium to transmit data in real time. SMS has been used for data collection by highly literate and educated health care workers in low-resource countries; however, no previous studies have evaluated implementation of an SMS intervention by low-literacy providers. The Liberian Ministry of Health and Social Welfare identified a lack of accurate data on the number of pregnancies from rural areas. To capture these data from 11 rural communities in Liberia, 66 low-literate traditional midwives and 15 high-literate certified midwives were trained to report data via SMS. Data were reported via a 9-digit code sent from Java-based mobile phones. Study aims included determining the following components of SMS transmission: success rate, accuracy, predictors of successful transmission, and acceptance. Success rate of SMS transmission was significantly higher for certified midwives than for traditional midwives. The error rate was significantly higher for traditional midwives than for certified midwives. Years of education was the only predictor of successful SMS transmission. Traditional midwives and certified midwives accepted the intervention, although certified midwives found it easier to use. Certified midwives performed significantly better than did traditional midwives. SMS texting interventions should be targeted to health care workers with higher rates of literacy.
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An adequate level of literacy or competent agents with previous experience of use increases acceptance of the technology.
“Thus, an adequate level of literacy (29) or competent agents (26) who have previous experience of use (29) would increase acceptance of the technology.”
From A mixed methods systematic review of success factors of mhealth and telehealth for maternal health in Sub-Saharan Africa (2017) · cites this paper as [29]
The Results > Acceptability section (page unavailable) reports that both groups accepted SMS data collection, while the more educated certified midwives found it easier to use; years of education predicted reported ease of sending messages. The Discussion (page unavailable) links prior phone and SMS experience to better transmission success and accuracy, but does not show that prior experience increased acceptance. The separate claim about competent agents is cited to another source in the sentence. (LLM, conf=0.84)
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Cites
Pop-Eleches, C., Thirumurthy, H., Habyarimana, J. P., Zivin, J. G., Goldstein, M. P., de Walque, D., MacKeen, L., Haberer, J., Kimaiyo, S., Sidle, J., et al. (2011) · AIDS · doi:10.1097/qad.0b013e32834380c1 · Cited by 982 · see citing works
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 · see citing works
Chib, A., Wilkin, H., Ling, L. X., Hoefman, B., & Van Biejma, H. (2012) · Journal of Health Communication · doi:10.1080/10810730.2011.649104 · Cited by 118 · see citing works
Reaching Remote Health Workers in Malawi: Baseline Assessment of a Pilot mHealth Intervention
Lemay, N. V., Sullivan, T., Jumbe, B., & Perry, C. P. (2012) · Journal of Health Communication · doi:10.1080/10810730.2011.649106 · Cited by 96 · see citing works
Cocosila, M., Archer, N., Brian Haynes, R., & Yuan, Y. (2009) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2008.07.011 · Cited by 90 · see citing works
Using cell phones to collect postpartum hemorrhage outcome data in rural Ghana
Andreatta, P., Debpuur, D., Danquah, A., & Perosky, J. (2011) · International Journal of Gynecology & Obstetrics · doi:10.1016/j.ijgo.2010.11.020 · Cited by 88 · see citing works
Self-citationOptimizing Network Connectivity for Mobile Health Technologies in sub-Saharan Africa
Siedner, M. J., Lankowski, A., Musinga, D., Jackson, J., Muzoora, C., Hunt, P. W., Martin, J. N., Bangsberg, D. R., & Haberer, J. E. (2012) · PLoS ONE · doi:10.1371/journal.pone.0045643 · Cited by 36 · see citing works
Flagged first, then by citations
Research works printed but not linked: 29
- Alipour S Jannat F Hosseini L Teaching breast cancer screening via text messages as part of continuing education for working nurses: a case-control study Asian Pacific Journal of Cancer Prevention 2014 15 5607 9 doi:10.7314/APJCP.2014.15.14.5607 25081673 · DOI
- Best ML Jones K Kondo I Thakur D Wornyo E Yu C Post-conflict communications: The case of Liberia Communications of the ACM 2007 50 10 33 39 doi:10.1145/1290958.1290987 · DOI
- Brown ON O’Connor LE Savaiano D Mobile MyPlate: A Pilot Study Using Text Messaging to Provide Nutrition Education and Promote Better Dietary Choices in College Students Journal of American College Health 2014 62 5 320 327 doi: 10.1080/07448481.2014.899233 24654921 · DOI
- Coomes CM Lewis MA Uhrig JD Furberg RD Harris JL Bann CM Beyond reminders: a conceptual framework for using short message service to promote prevention and improve healthcare quality and clinical outcomes for people living with HIV AIDS care 2012 24 3 348 357 doi:10.1080/09540121.2011.608421 21933036 · DOI
- Curioso WH Karras BT Campos PE Buendía C Holmes KK Kimball AM Design and implementation of Cell-PREVEN: a real-time surveillance system for adverse events using cell phones in Peru American Medical Informatics Association Annual Symposium Proceedings 2005 2005 176 180 (Vol. 2005, p. 176-180) PMC1560594 16779025
- Evans WD Abroms LC Poropatich R Nielsen PE Wallace JL Mobile health evaluation methods: the Text4baby case study Journal of Health Communication 2012 17 sup1 22 29 doi:10.1080/10810730.2011.649157 22548595 · DOI
- Frank B Adams MH Edelstein J Speakman E Shelton M Community-based nursing education of prelicensure students: Settings and supervision Nursing Education Perspectives 2005 26 5 283 286 16295307
- Gartland MG Taryor VD Norman AM Vermund SH Access to facility delivery and caesarean section in north-central Liberia: a cross-sectional community-based study BMJ open 2012 2 6 doi:10.1136/bmjopen-2012-001602 PMC3532996 23117566 · DOI
- Koshy E Car J Majeed A Effectiveness of mobile-phone short message service (SMS) reminders for ophthalmology outpatient appointments: observational study BMC Ophthalmology 2008 8 1 9 doi:10.1186/1471-2415-8-9 18513438 PMC2438329 · DOI
- Le Bodic G Mobile messaging technologies and services: SMS, EMS and MMS 2005 John Wiley & Sons, Inc. West Sussex, U.K.
- Lori JR Boyle JS Cultural childbirth practices, beliefs and traditions in postconflict Liberia Health Care for Women International 2011 32 6 454 473 doi:10.1080/07399332.2011.555831 21547801 · DOI
- Lori JR Munro ML Boyd CJ Andreatta PB Cell phones to collect pregnancy data from remote areas in Liberia Journal of Nursing Scholarship 2012 44 3 294-3-1. doi:10.1111/j.1547-5069.2012.01451.x PMC3432659 22672157 · DOI
- Lori JR Munro ML Moore JE Fladger J Lessons learned in Liberia: Preliminary examination of the psychometric properties of trust and teamwork among maternal healthcare workers BMC health services research 2013a 13 1 134 doi:10.1186/1472-6963-13-134 23578288 PMC3635917 · DOI
- Lori JR Munro ML Rominski S Williams G Dahn BT Boyd CJ Moore JE Gwenegale W Maternity waiting homes and traditional midwives in rural Liberia International Journal of Gynecology & Obstetrics 2013b 123 2 114 118 doi:10.1016/j.ijgo.2013.05.024 23992657 PMC3795996 · DOI
- Lori JR Starke AE A critical analysis of maternal morbidity and mortality in Liberia, West Africa Midwifery 2012 28 1 67 72 doi:10.1016/j.midw.2010.12.001 21232836 · DOI
- Leong KC Chen WS Leong KW Mastura I Mimi O Sheikh MA Zailinawati AH Ng CJ Phua KL Teng CL The use of text messaging to improve attendance in primary care: a randomized controlled trial Family practice 2006 23 6 699 705 doi:10.1093/fampra/cml044 16916871 · DOI · Paper page
- Lund S Hemed M Nielsen BB Said A Said K Makungu MH Rasch V Mobile phones as a health communication tool to improve skilled attendance at delivery in Zanzibar: a cluster-randomised controlled trial BJOG: An International Journal of Obstetrics & Gynaecology 2012 119 10 1256 1264 doi:10.1111/j.1471-0528.2012.03413.x 22805598 · DOI · Paper page
- Mason M Benotsch EG Way T Kim H Snipes D Text messaging to increase readiness to change alcohol use in college students The Journal of Primary Prevention 2014 35 1 47 52 doi:10.1007/s10935-013-0329-9 24114551 · DOI
- Mohammed S Siddiqi O Ali O Habib A Haqqi F Kausar M Khan AJ User engagement with and attitudes towards an interactive SMS reminder system for patients with tuberculosis Journal of Telemedicine and Telecare 2012 18 7 404 408 doi:10.1258/jtt.2012.120311 23034935 · DOI
- Moore SC Crompton K van Goozen S van den Bree M Bunney J Lydall E A feasibility study of short message service text messaging as a surveillance tool for alcohol consumption and vehicle for interventions in university students BMC Public Health 2013 13 1 1011 doi:10.1186/1471-2458-13-1011 24160674 PMC4137472 · DOI
- Munro ML Lori JR Boyd CJ Andreatta PB Knowledge and skill retention of a mobile phone data collection protocol in rural Liberia Journal of Midwifery & Women’s Health 2014 59 2 176 183 doi:10.1111/jmwh.12155 PMC3976765 24655593 · DOI · Paper page
- Patnaik S Brunskill E Thies W Evaluating the accuracy of data collection on mobile phones: A study of forms, SMS, and voice Proceedings of the 3rd international conference on Information and communication technologies and development 2009 74 84 IEEE Press. doi: 10.1109/ICTD.2009.5426700 · DOI
- Speciale AM Freytsis M MHealth for Midwives: A Call to Action Journal of Midwifery and Women’s Health 58 1 76 82 doi: 10.1111/j.1542-2011.2012.00243.x 23317302 · DOI
- Thaddeus S Maine D Too Far to Walk: Maternal Mortality in Context Social Science & Medicine 1994 38 8 1091 1110 doi 10.1016/0277-9536(94)90226-7 8042057 · DOI · Paper page
- Tomlinson M Solomon W Singh Y Doherty T Chopra M Ijumba P Tsai AC Jackson D The use of mobile phones as a data collection tool: a report from a household survey in South Africa BMC Medical Informatics and Decision Making 2009 9 1 51 doi:10.1186/1472-6947-9-51 20030813 PMC2811102 · DOI · Paper page
- Walton G Childs S Blenkinsopp E Using mobile technologies to give health students access to learning resources in the UK community setting Health Information and Libraries Journal 2005 22 2 Suppl. 51 65 doi:10.1111/j.1470-3327.2005.00615.x 16279976 · DOI
- Whitford MH Donnan PT Symon AG Kellett G Monteith-Hodge E Rauchhaus P Wyatt JC Evaluating the reliability, success rate of transmission, acceptability, and practicality of SMS text messaging as a tool to collect research data: results from the Feeding Your Baby project Journal of American Medical Informatics Association 2012 19 5 744 9 doi:10.1136/amiajnl-2011-000785 PMC3422836 22539081 · DOI
- Ybarra ML Holtrop JS Bağci Bosi AT Bi̧lir N Korchmaros JD Salih Emri AK Feasibility and acceptability of a text messaging–based smoking cessation program in Ankara, Turkey Journal of health communication 2013 18 8 960 973 doi:10.1080/10810730.2012.757399 23627304 · DOI
- Zurovac D Otieno G Kigen S Mbithi AM Muturi A Snow RW Nyandigisi A Ownership and use of mobile phones among health workers, caregivers of sick children and adult patients in Kenya: cross-sectional national survey Globalization and health 2013 9 1 20 doi:10.1186/1744-8603-9-20 23672301 PMC3695884 · DOI
Cited by
Sorted by citations
Ag Ahmed, M. A., Gagnon, M.-P., Hamelin-Brabant, L., Mbemba, G. I. C., & Alami, H. (2017) · mHealth · doi:10.21037/mhealth.2017.05.04 · Cited by 66 · see citing works
“Among these, three articles (26-28) reported on a same study, and two other publications (29,30) were also related to a single study.”
Background
- Authors
- Perosky, J. E., Munro, M. L., Kay, J. L., Nyanplu, A., Williams, G., Andreatta, P. B., & Lori, J. R.
- Affiliations
- University of Michigan (US)
- University of Minnesota (US)
- Corresponding author
- Perosky, Joseph E.
- Venue
- Journal of Health Communication
- Publisher
- Informa UK Limited
- Published
- 2015-07-06
- Volume
- 20
- Issue
- 9
- Pages
- 1052-1059
- ISSN
- 1081-0730 (ISSN-L)
- 1087-0415
- PMC
- PMC4699450
- OpenAlex
- W1856411498
- Cited by
- 12
- References
- 7
- Citations by year
- 2025: 2 · 2023: 2 · 2022: 2 · 2019: 1 · 2018: 2 · 2017: 3
- FWCI
- 3.05
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Health Communication (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Fogarty International Center (1 K01 TW008763-01A1)
- United States Agency for International Development (USAID-M-OOA-GH-HSR-10-40)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Physical Sciences › Computer Science › Information Systems › ICT in Developing Communities
- Social Sciences › Health › Social Media in Health Education
- Keywords
- safety management systems, mobile health, health data collection, traditional midwives, certified midwives, intervention acceptance, Liberia
- MeSH terms
- Adult, Aged, Data Collection, Female, Humans, Liberia, Middle Aged, Midwifery, Pregnancy, Rural Population, Reproducibility of Results, Young Adult, Health Literacy, Text Messaging
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