TextTB: A Mixed Method Pilot Study Evaluating Acceptance, Feasibility, and Exploring Initial Efficacy of a Text Messaging Intervention to Support TB Treatment Adherence
Objective. To assess a text messaging intervention to promote tuberculosis (TB) treatment adherence. Methods. A mixed-methods pilot study was conducted within a public pulmonary-specialized hospital in Argentina. Patients newly diagnosed with TB who were 18 or older, and had mobile phone access were recruited and randomized to usual care plus either medication calendar ( ) or text messaging intervention ( ) for the first two months of treatment. Primary outcomes were feasibility and acceptability; secondary outcomes explored initial efficacy. Results. Feasibility was evidenced by high access to mobile phones, familiarity with texting, most phones limited to basic features, a low rate of participant refusal, and many describing suboptimal TB understanding. Acceptability was evidenced by participants indicating feeling cared for, supported, responsible for their treatment, and many self-reporting adherence without a reminder. Participants in the texting group self-reported adherence on average 77% of the days whereas only 53% in calendar group returned diaries. Exploring initial efficacy, microscopy testing was low and treatment outcomes were similar in both groups. Conclusion. The texting intervention was well accepted and feasible with greater reporting of adherence using text messaging than the diary. Further evaluation of the texting intervention is warranted. 1. Introduction The mobile phone is cited as the most rapidly adopted technology on the planet [1]. The figure of 6.8 billion mobile phones subscribers in 2013 is nearing the number of people on earth [2]. In an attempt to combat the continued challenges of tuberculosis (TB) as a major global health problem researchers have proposed using short message service (SMS) or text messaging to improve TB treatment adherence [3]. TB treatment adherence remains a challenge in TB control efforts and nonadherence can lead to poor outcomes, such as prolonged infectivity, increase in the risk of relapse after treatment, generation and propagation of drug resistance, treatment failure, and increased mortality [4, 5]. Heightening TB patients’ involvement in their own care and improving communication between patients and their healthcare team have been recommended to improve adherence [3, 6]. Argentina has high access to mobile phones and a need to improve TB treatment outcomes. With an estimated population of 40.8 million, there was a reported 59.6 million mobile phones in service and 11.3 billion SMS messages sent in January 2013 [7]. Argentina’s National TB Program acknowledges that the overall TB treatment
References
[1]
The World in 2009: ICT Facts and Figures, http://www.itu.int/net/pressoffice/backgrounders/general/pdf/3.pdf.
[2]
The World in 2013: ICT Facts and Figures, http://www.itu.int/en/ITU-D/Statistics/Documents/facts/.
[3]
E. Barclay, “Text messages could hasten tuberculosis drug compliance,” The Lancet, vol. 373, no. 9657, pp. 15–16, 2009.
[4]
G. Maartens and R. J. Wilkinson, “Tuberculosis,” The Lancet, vol. 370, no. 9604, pp. 2030–2043, 2007.
[5]
D. A. Mitchison, “How drug resistance emerges as a result of poor compliance during short course chemotherapy for tuberculosis,” International Journal of Tuberculosis and Lung Disease, vol. 2, no. 1, pp. 10–15, 1998.
[6]
W. A. Kaplan, “Can the ubiquitous power of mobile phones be used to improve health outcomes in developing countries?” Globalization and Health, vol. 2, article 9, 2006.
[7]
Servicios Publicos, Buenos Aires, Argentina, http://www.indec.mecon.gov.ar/nuevaweb/cuadros/14/esp_02_10.pdf.
[8]
Instituto Nacional de Enfermedades Respiratorias E. Coni, Resultado del Tratamiento de los Casos de Tuberculosis, Situación Nacional y por Jurisdicción, Buenos Aires, Argentina, 2010.
[9]
“TB country profile Argentina,” 2010, http://www.who.int/tb/country/data/profiles/en/.
[10]
Instituto Nacional de Enfermidades Respiratorias E. Coni, Notificación de Casos de Tuberculosis. Período 1990–2010, 2011.
[11]
H. Cole-Lewis and T. Kershaw, “Text messaging as a tool for behavior change in disease prevention and management,” Epidemiologic Reviews, vol. 32, no. 1, pp. 56–69, 2010.
[12]
B. S. Fjeldsoe, A. L. Marshall, and Y. D. Miller, “Behavior change interventions delivered by mobile telephone short-message service,” American Journal of Preventive Medicine, vol. 36, no. 2, pp. 165–173, 2009.
[13]
S. Mohammed, O. Siddiqi, O. Ali et al., “User engagement with and attitudes towards an interactive SMS reminder system for patients with tuberculosis,” Journal of Telemedicine and Telecare, vol. 18, pp. 404–408, 2012.
[14]
J. DeMaio, L. Schwartz, P. Cooley, and A. Tice, “The application of telemedicine technology to a directly observed therapy program for tuberculosis: a pilot project,” Clinical Infectious Diseases, vol. 33, no. 12, pp. 2082–2084, 2001.
[15]
J. A. Hoffman, J. R. Cunningham, A. J. Suleh et al., “Mobile direct observation treatment for tuberculosis patients: a technical feasibility pilot using mobile phones in Nairobi, Kenya,” American Journal of Preventive Medicine, vol. 39, no. 1, pp. 78–80, 2010.
[16]
V. A. Wade, J. Karnon, J. A. Eliott, and J. E. Hiller, “Home videophones improve direct observation in tuberculosis treatment: a mixed methods evaluation,” PLoS One, vol. 7, Article ID e50155, 2012.
[17]
P. Kunawararak, S. Pongpanich, S. Chantawong et al., “Tuberculosis treatment with mobile-phone medication reminders in northern Thailand,” The Southeast Asian Journal of Tropical Medicine and Public Health, vol. 42, no. 6, pp. 1444–1451, 2011.
[18]
J. M. Cramm, H. J. Finkenflügel, V. M？ller, and A. P. Nieboer, “TB treatment initiation and adherence in a South African community influenced more by perceptions than by knowledge of tuberculosis,” BMC Public Health, vol. 10, article 72, 2010.
[19]
S. A. Munro, S. A. Lewin, H. J. Smith, M. E. Engel, A. Fretheim, and J. Volmink, “Patient adherence to tuberculosis treatment: a systematic review of qualitative research,” PLoS Medicine, vol. 4, no. 7, article e238, pp. 1230–1245, 2007.
[20]
S. Iribarren, S. Beck, P. F. Pearce et al., “Collaborative development of a text-messaging intervention to improve tuberculosis treatment adherence,” . In progress.
[21]
S. Iribarren, K. Sward, S. Beck, P. F. Pearce, D. Thurston, and C. Chirico, “Socio-technical evaluation of a piloted text messaging-based intervention to improve TB medication adherence: considerations for conducting a larger trial,” Methods of Information in Medicine. Under review.
[22]
C. Chirico, A. Kuriger, M. Etchevarria, L. Casamajor, and N. Morcillo, “Anti-tuberculosis treatment evaluation in Northern districts of Buenos Aires suburbs,” Medicina, vol. 67, no. 2, pp. 131–135, 2007.
[23]
J. D. Fisher and W. A. Fisher, “Changing AIDS-risk behavior,” Psychological Bulletin, vol. 111, no. 3, pp. 455–474, 1992.
[24]
J. D. Fisher, W. A. Fisher, K. R. Amico, and J. J. Harman, “An information-motivation-behavioral skills model of adherence to antiretroviral therapy,” Health Psychology, vol. 25, no. 4, pp. 462–473, 2006.
G. J. Wagner and J. G. Rabkin, “Measuring medication adherence: are missed doses reported more accurately then perfect adherence?” AIDS Care, vol. 12, no. 4, pp. 405–408, 2000.
[27]
D. Schoenfeld, “Statistical considerations for pilot studies,” International Journal of Radiation Oncology, Biology, Physics, vol. 6, no. 3, pp. 371–374, 1980.
[28]
B. G. Tabachnick and L. S. Fidell, Using Multivariate Statistics, Harper Collins, New York, NY, USA, 5th edition, 2006.
[29]
Y. Lincoln and E. Guba, Naturalistic Inquiry, Sage Publications, Newbury Park, Calif, USA, 1985.
[30]
P. A. Harris, R. Taylor, R. Thielke, J. Payne, N. Gonzalez, and J. G. Conde, “Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support,” Journal of Biomedical Informatics, vol. 42, no. 2, pp. 377–381, 2009.
[31]
World Health Organization, Treatment for Tuberculosis: Guidelines, World Health Organization, Geneva, Switzerland, 3rd edition, 2009.
[32]
P. C. Hill, W. Stevens, S. Hill et al., “Risk factors for defaulting from tuberculosis treatment: a prospective cohort study of 301 cases in the Gambia,” International Journal of Tuberculosis and Lung Disease, vol. 9, no. 12, pp. 1349–1354, 2005.
[33]
M. A. Khan, J. D. Walley, S. N. Witter, S. K. Shah, and S. Javeed, “Tuberculosis patient adherence to direct observation: results of a social study in Pakistan,” Health Policy and Planning, vol. 20, no. 6, pp. 354–365, 2005.
[34]
World Health Organization, The Global Plan to Stop TB, 2006-2015: Actions for Life: Towards a World Free of Tuberculosis, The World Health Organization, Geneva, Switzerland, 2006.
[35]
R. T. Lester, P. Ritvo, E. J. Mills et al., “Effects of a mobile phone short message service on antiretroviral treatment adherence in Kenya (WelTel Kenya1): a randomised trial,” The Lancet, vol. 376, no. 9755, pp. 1838–1845, 2010.
[36]
A. K. Person, M. L. M. Blain, H. Jiang, P. W. Rasmussen, and J. E. Stout, “Text messaging for enhancement of testing and treatment for tuberculosis, human immunodeficiency virus, and syphilis: a survey of attitudes toward cellular phones and healthcare,” Telemedicine Journal and e-Health, vol. 17, no. 3, pp. 189–195, 2011.
[37]
L. Mbuagbaw, R. C. Bonono-Momnougui, and L. Thabane, “Considerations in using text messages to improve adherence to highly active antiretroviral therapy: a qualitative study among clients in Yaoundé, Cameroon,” HIV/AIDS, vol. 4, pp. 45–50, 2012.
[38]
D. C. Wamalwa, C. Farquhar, E. M. Obimbo et al., “Medication diaries do not improve outcomes with highly active antiretroviral therapy in Kenyan children: a randomized clinical trial,” Journal of the International AIDS Society, vol. 12, article 8, 2009.
[39]
World Health Organization, International Standards for Tuberculosis Care: Diagnosis, Treatment and Public Health, Assistance TCfT, 2006.
[40]
T. Lopez, M. Moreno, F. Salvador, A. Zacarias, R. Carvalho, and E. Tomas, “Tuberculosis diagnosed in a rural setting in Angola. Accuracy of follow-up sputum smears to predict outcome,” Pathogens and Global Health, vol. 107, pp. 5–10, 2013.
[41]
M. C. Garber, D. P. Nau, S. R. Erickson, J. E. Aikens, and J. B. Lawrence, “The concordance of self-report with other measures of medication adherence: a summary of the literature,” Medical Care, vol. 42, no. 7, pp. 649–652, 2004.
