Developing a theory-driven contextually relevant mHealth intervention

References

• Hall CS, Fottrell E, Wilkinson S, et al. Assessing the impact of mHealth interventions in low- and middle-income countries – what has been shown to work? Glob Health Action. 2014;7:25606.
   Web of Science ®Google Scholar
• Bergström A, Fottrell E, Hopkins H, et al. mHealth: can mobile technology improve health in low- and middle- income countries? UCL public policy briefing. 2015. [cited 2018 Nov 6] Available from: https://www.ucl.ac.uk/public-policy/sites/public-policy/files/migrated-files/mhealth_briefing.pdf
   Google Scholar
• Fottrell E. Commentary: the emperor’s new phone. BMJ. 2015;350:h2051.
   Web of Science ®Google Scholar
• Gurman TA, Rubin ER, Ross AA. Effectiveness of mHealth behaviour change communication in developing countries: a systematic review of literature. J Health Commun. 2012;17:82–22.
   PubMed Web of Science ®Google Scholar
• Ramachandran A, Snehalatha C, Ram J, et al. Effectiveness of mobile phone messaging in prevention of type 2 diabetes by lifestyle modification in men in India: a prospective, parallel-group, randomised controlled trial. Lancet Diabetes Endocrinol. 2013;1:191–198.
   PubMed Web of Science ®Google Scholar
• Cotterez AP, Durant N, Agne AA, et al. Internet interventions to support lifestyle modification for diabetes management: a systematic review of the evidence. J Diabetes Complications. 2014;28:243–251.
   Web of Science ®Google Scholar
• Nationl Institute of Population Research and Training (NIPORT). Bangladesh demographic and health survey 2014: key indicators. 2015 [cited 2018 Nov 6]. Available from: https://www.k4health.org/sites/default/files/bdhs_2014.pdf
   Google Scholar
• Ahmed T, Lucas H, Khan AS, et al. eHealth and mHealth initiatives in Bangladesh: a scoping study. BMC Health Serv Res. 2014;14:260–268.
   PubMed Web of Science ®Google Scholar
• World Health Organisation. Global report on diabetes. Geneva, Switzerland: World Health Organisation; 2016.
   Google Scholar
• International Diabetes Federation. Diabetes atlas. 8th ed. Brussels, Belgium: International Diabetes Federation; 2017.
   Google Scholar
• Bleich SN, Koehlmoos TLP, Rashid M, et al. Noncommunicable chronic disease in Bangladesh: overview of existing programs and priorities going forward. Health Policy. 2011;100:282–289.
   Web of Science ®Google Scholar
• Fottrell E, Jennings H, Kuddus A, et al. The effect of community groups and mobile phone messages on the prevention and control of diabetes in rural Bangladesh: study protocol for a three-arm cluster randomised controlled trial. Trials. 2016;17:600.
   Web of Science ®Google Scholar
• Michie S, van Stralen M, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. 2011;6:42.
   PubMed Web of Science ®Google Scholar
• Bangladesh Bureau of Statistics. Bangladesh population and housing census 2011. Dhaka: Bangladesh Bureau of Statistics; 2013.
   Google Scholar
• Fottrell E, Ahmed N, Shaha SK, et al. Age, sex, and wealth distribution of diabetes, hypertension and non-communicable disease risk factors among adults in rural Bangladesh: a cross-sectional epidemiological survey. BMJ Global Health. 2018. in press.
   Web of Science ®Google Scholar
• Green JT, Thorogood N. Qualitative methods for health research. London: SAGE; 2005.
   Google Scholar
• Bernard HR. Research methods in anthropology: qualitative and quantitative approaches. Oxford: AltaMira Press; 2006.
   Google Scholar
• Ogden J. Celebrating variability and a call to limit systematisation: the example of the behaviour change technique taxonomy and the behaviour change wheel. Health Psychol Rev. 2016;10:245–250.
   PubMed Web of Science ®Google Scholar
• Ogden J. Theories, timing and choice of audience: some key tensions in health psychology and a response to commentaries on Ogden (2016). Health Psychol Rev. 2016;10:274–276.
   PubMed Web of Science ®Google Scholar
• Cane J, O’Connor D, Michie S. Validation of the theoretical domains framework for use in behaviour change and implementation research. Implement Sci. 2012;7:37–53.
   PubMed Web of Science ®Google Scholar
• Michie S, Johnston M, Abraham C, et al. on behalf of the ‘Psychological Theory’ Group. Making psychological theory useful for implementing evidence based practice: a consensus approach. Qual Saf Health Care. 2005;14:26–33.
   PubMed Web of Science ®Google Scholar
• Michie S, Richardson M, Johnston M, et al. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an International consensus for the reporting of behavior change interventions. Ann Behav Med. 2013;46:81–95.
   PubMed Web of Science ®Google Scholar
• Atkins S, Michie S. Conference on ‘Changing dietary behaviour: physiology through to practice’ Symposium 4: changing diet and behaviour – putting theory into practice. Designing interventions to change eating behaviours. Proc Nutr Soc. 2015;74:164–170.
   Web of Science ®Google Scholar
• French SD, Green SE, O’Connor DA, et al. Developing theory-informed behaviour change interventions to implement evidence into practice: a systematic approach using the theoretical domains framework. Implement Sci. 2012;7:38.
   PubMed Web of Science ®Google Scholar
• Fishbain M, Yzer MC. Using theory to design effective health behavior interventions. Commun Theory. 2003;13:164–183.
   Web of Science ®Google Scholar