Development and Implementation of Culturally Tailored Offline Mobile Health Surveys

Background In low and middle income countries (LMICs), and other areas with low resources and unreliable access to the Internet, understanding the emerging best practices for the implementation of new mobile health (mHealth) technologies is needed for efficient and secure data management and for informing public health researchers. Innovations in mHealth technology can improve on previous methods, and dissemination of project development details and lessons learned during implementation are needed to provide lessons learned to stakeholders in both the United States and LMIC settings. Objective The aims of this paper are to share implementation strategies and lessons learned from the development and implementation stages of two survey research projects using offline mobile technology, and to inform and prepare public health researchers and practitioners to implement new mobile technologies in survey research projects in LMICs. Methods In 2015, two survey research projects were developed and piloted in Puerto Rico and pre-tested in Costa Rica to collect face-to-face data, get formative evaluation feedback, and to test the feasibility of an offline mobile data collection process. Fieldwork in each setting involved survey development, back translation with cultural tailoring, ethical review and approvals, data collector training, and piloting survey implementation on mobile tablets. Results Critical processes and workflows for survey research projects in low resource settings were identified and implemented. This included developing a secure mobile data platform tailored to each survey, establishing user accessibility, and training and eliciting feedback from data collectors and on-site LMIC project partners. Conclusions Formative and process evaluation strategies are necessary and useful for the development and implementation of survey research projects using emerging mHealth technologies in LMICs and other low resource settings. Lessons learned include: (1) plan institutional review board (IRB) approvals in multiple countries carefully to allow for development, implementation, and feedback, (2) in addition to testing the content of survey instruments, allow time and consideration for testing the use of novel mHealth technology (hardware and software), (3) incorporate training for and feedback from project staff, LMIC partner staff, and research participants, and (4) change methods accordingly, including content, as mHealth technology usage influences and is influenced by the content and structure of the survey instrument. Lessons learned from early phases of LMIC research projects using emerging mHealth technologies are critical for informing subsequent research methods and study designs.

[1]  Jesse Chandler,et al.  Using Mechanical Turk to Study Clinical Populations , 2013 .

[2]  C. Díaz,et al.  Formative evaluation of a proposed mHealth program for childhood illness management in a resource-limited setting in Peru. , 2015, Revista panamericana de salud publica = Pan American journal of public health.

[3]  N. Ford,et al.  Is operational research delivering the goods? The journey to success in low-income countries. , 2012, The Lancet. Infectious diseases.

[4]  N. Chin,et al.  Tobacco use in the Dominican Republic: understanding the culture first , 2006, Tobacco Control.

[5]  Ada Hamosh,et al.  Problematic variation in local institutional review of a multicenter genetic epidemiology study. , 2003, JAMA.

[6]  J. Winickoff,et al.  Tobacco Control and Children: An International Perspective. , 2010, Pediatric Allergy, Immunology, and Pulmonology.

[7]  N. Chin,et al.  Tobacco Cessation in Economically Disadvantaged Dominican Republic Communities: Who are the Ex-Users? , 2016, Journal of smoking cessation.

[8]  N. Chin,et al.  A qualitative study of tobacco use in eight economically disadvantaged Dominican Republic communities , 2017, Global health promotion.

[9]  Joy Buolamwini,et al.  A Novel Electronic Data Collection System for Large-Scale Surveys of Neglected Tropical Diseases , 2013, PloS one.

[10]  Gunther Eysenbach,et al.  Web-Assisted Tobacco Interventions: Empowering Change in the Global Fight for the Public’s (e)Health , 2008, Journal of medical Internet research.

[11]  Ann Dozier,et al.  Ethical Review Issues in Collaborative Research between US and Low Middle Income Country Partners: A Case Example , 2008, Bioethics.

[12]  D. Ossip-Klein,et al.  Tobacco use in six economically disadvantaged communities in the Dominican Republic. , 2008, Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco.

[13]  Vinu Ilakkuvan,et al.  Implementation of a Multimodal Mobile System for Point-of-Sale Surveillance: Lessons Learned From Case Studies in Washington, DC, and New York City , 2015, JMIR public health and surveillance.

[14]  Kara L. Hall,et al.  Research Dissemination and Diffusion , 2009 .

[15]  Malia Villegas,et al.  Community-Based Participatory Research: Its Role in Future Cancer Research and Public Health Practice , 2013, Preventing chronic disease.

[16]  K. Thevenet‐Morrison,et al.  Health Care Workers’ Knowledge, Attitudes and Practices on Tobacco Use in Economically Disadvantaged Dominican Republic Communities , 2015, International journal of environmental research and public health.

[17]  T. Richards,et al.  Poor countries make the best teachers: discuss , 2004, BMJ : British Medical Journal.

[18]  Ralph Maddison,et al.  A Development and Evaluation Process for mHealth Interventions: Examples From New Zealand , 2012, Journal of health communication.

[19]  Jay R. Levinsohn,et al.  Electronic Data Collection and Management System for Global Adult Tobacco Survey , 2012, Online journal of public health informatics.

[20]  Trisha Greenhalgh,et al.  Is it time to drop the ‘knowledge translation’ metaphor? A critical literature review , 2011, Journal of the Royal Society of Medicine.

[21]  R. Brislin Back-Translation for Cross-Cultural Research , 1970 .

[22]  Dana Chandler,et al.  Breaking Monotony with Meaning: Motivation in Crowdsourcing Markets , 2012, ArXiv.

[23]  A. Alshawabkeh,et al.  Distribution, variability, and predictors of urinary concentrations of phenols and parabens among pregnant women in Puerto Rico. , 2013, Environmental science & technology.

[24]  J. Samet,et al.  Secondhand smoke exposure among women and children: evidence from 31 countries. , 2008, American journal of public health.

[25]  D. Mozaffarian,et al.  The Preventable Causes of Death in the United States: Comparative Risk Assessment of Dietary, Lifestyle, and Metabolic Risk Factors , 2009, PLoS medicine.

[26]  M. Mckee,et al.  The unequal health of Europeans: successes and failures of policies , 2013, The Lancet.

[27]  Siddharth Suri,et al.  Conducting behavioral research on Amazon’s Mechanical Turk , 2010, Behavior research methods.

[28]  D. Berwick Lessons from developing nations on improving health care , 2004, BMJ : British Medical Journal.

[29]  L. French,et al.  Tobacco use and exposure to secondhand smoke among pregnant women in the Dominican Republic: an exploratory look into attitudes, beliefs, perceptions, and practices. , 2011, Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco.

[30]  D. Ossip,et al.  Cohort study of smoke-free homes in economically disadvantaged communities in the Dominican Republic. , 2014, Revista panamericana de salud publica = Pan American journal of public health.

[31]  D. Ossip,et al.  Understanding Sociodemographic and Sociocultural Factors that Characterize Tobacco Use and Cessation During Pregnancy Among Women in the Dominican Republic , 2014, Maternal and Child Health Journal.

[32]  H. Jefee-Bahloul,et al.  Using a Store-and-Forward System to Provide Global Telemental Health Supervision and Training: A Case from Syria , 2016, Academic Psychiatry.

[33]  R. Gilman,et al.  Ethics review procedures for research in developing countries: a basic presumption of guilt , 2004, Canadian Medical Association Journal.

[34]  I. Padilla,et al.  Urinary phthalate metabolite concentrations among pregnant women in Northern Puerto Rico: distribution, temporal variability, and predictors. , 2014, Environment international.

[35]  N. Chin,et al.  Health Care Workers in the Dominican Republic: Self-Perceived Role in Smoking Cessation , 2009, Evaluation & the health professions.

[36]  Donna Berryman,et al.  NLM Informationist Grant – Web Assisted Tobacco Intervention for Community College Students , 2013 .

[37]  Peter Tugwell,et al.  Knowledge translation in global health. , 2005, Bulletin of the World Health Organization.

[38]  Siddhartha Nambiar,et al.  Towards evaluating and enhancing the reach of online health forums for smoking cessation , 2014, Network Modeling Analysis in Health Informatics and Bioinformatics.

[39]  Tara S. Behrend,et al.  The viability of crowdsourcing for survey research , 2011, Behavior research methods.

[40]  Adam J. Berinsky,et al.  Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk , 2012, Political Analysis.

[41]  Geoffrey O. Arunga,et al.  A comparison of smartphones to paper-based questionnaires for routine influenza sentinel surveillance, Kenya, 2011–2012 , 2014, BMC Medical Informatics and Decision Making.

[42]  Michael D. Buhrmester,et al.  Amazon's Mechanical Turk , 2011, Perspectives on psychological science : a journal of the Association for Psychological Science.

[43]  H. Nawaz,et al.  Developing the Evidence Base to Inform Best Practice: A Scoping Study of Breast and Cervical Cancer Reviews in Low- and Middle-Income Countries , 2015, PloS one.

[44]  S. Kwankam What e-Health can offer. , 2004, Bulletin of the World Health Organization.

[45]  Ping Yu,et al.  The development and evaluation of a PDA-based method for public health surveillance data collection in developing countries , 2009, Int. J. Medical Informatics.

[46]  Peter Yellowlees,et al.  Cost analysis of store-and-forward telepsychiatry as a consultation model for primary care. , 2012, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[47]  C. Adebamowo,et al.  Knowledge and attitudes to personal genomics testing for complex diseases among Nigerians , 2014, BMC medical ethics.

[48]  N. Pakenham-Walsh Learning from one another to bridge the “know-do gap” , 2004, British medical journal.

[49]  V. Thamlikitkul Bridging the gap between knowledge and action for health: Case studies. , 2006, Bulletin of the World Health Organization.

[50]  C. Nelson,et al.  Primary care providers' perceptions of mobile store-and-forward teledermatology. , 2015, Dermatology online journal.