Technology-Supported Behavior Change-Applying Design Thinking to MHealth Application Development

Overview

Journal Eur J Investig Health Psychol Educ

Specialty Medical Education

Date 2024 Mar 27

PMID 38534900

Authors

Ramona Schweitzer

Stephan Schlogl

Marco Schweitzer

Affiliations

Soon will be listed here.

Abstract

Non-communicable diseases are the leading cause of global deaths. The risk of their development and progression is increased by modifiable behavioral risk factors. Yet, despite the known benefits of primary and secondary prevention, people often do not follow recommendations for a healthier lifestyle. To this end, mobile health (mHealth) applications offer features for behavioral interventions. Yet, reported user engagement is often low. The objective of the work presented in this article is thus to evaluate the suitability of Design Thinking (DT) as a means to inform the development of an mHealth application that helps increase long-term engagement, and consequently supports individuals in sustainably changing their lifestyle. Applying the DT approach, key user needs and challenges were investigated and used to design a first low-fidelity mHealth application prototype. Think-Aloud analysis, task completion, and post-test interviews were then used to evaluate the prototype and generate early-stage insights. Subsequently, a structured, retrospective analysis of this process, evaluating the insight-generation potential of each step in the DT process cycle, was used to reflect on its suitability to inform mHealth application development. The respective results highlight (1) the distinct value of the DT method, particularly in the early stages of a development project; (2) the strong need for interdisciplinary collaboration in such projects, so as to capture realistic end-user requirements and improve the overall effectiveness of the application design; and (3) the significance of integrating behavioral change theories into the design of mHealth applications, in order to promote long-term engagement.

References

Odendaal W, Anstey Watkins J, Leon N, Goudge J, Griffiths F, Tomlinson M . Health workers' perceptions and experiences of using mHealth technologies to deliver primary healthcare services: a qualitative evidence synthesis. Cochrane Database Syst Rev. 2020; 3:CD011942. PMC: 7098082. DOI: 10.1002/14651858.CD011942.pub2. View

Witteman H, Chipenda Dansokho S, Colquhoun H, Coulter A, Dugas M, Fagerlin A . User-centered design and the development of patient decision aids: protocol for a systematic review. Syst Rev. 2015; 4:11. PMC: 4328638. DOI: 10.1186/2046-4053-4-11. View

Lee J, Lee D, Kim K, Shim J, Sung E, Kang J . Development of tailored nutrition information messages based on the transtheoretical model for smartphone application of an obesity prevention and management program for elementary-school students. Nutr Res Pract. 2017; 11(3):247-256. PMC: 5449382. DOI: 10.4162/nrp.2017.11.3.247. View

Searl M, Borgi L, Chemali Z . It is time to talk about people: a human-centered healthcare system. Health Res Policy Syst. 2010; 8:35. PMC: 3009465. DOI: 10.1186/1478-4505-8-35. View

Schoeppe S, Alley S, Van Lippevelde W, Bray N, Williams S, Duncan M . Efficacy of interventions that use apps to improve diet, physical activity and sedentary behaviour: a systematic review. Int J Behav Nutr Phys Act. 2016; 13(1):127. PMC: 5142356. DOI: 10.1186/s12966-016-0454-y. View

Miller G . The Smartphone Psychology Manifesto. Perspect Psychol Sci. 2015; 7(3):221-37. DOI: 10.1177/1745691612441215. View

Direito A, Carraca E, Rawstorn J, Whittaker R, Maddison R . mHealth Technologies to Influence Physical Activity and Sedentary Behaviors: Behavior Change Techniques, Systematic Review and Meta-Analysis of Randomized Controlled Trials. Ann Behav Med. 2016; 51(2):226-239. DOI: 10.1007/s12160-016-9846-0. View

Lear S, Hu W, Rangarajan S, Gasevic D, Leong D, Iqbal R . The effect of physical activity on mortality and cardiovascular disease in 130 000 people from 17 high-income, middle-income, and low-income countries: the PURE study. Lancet. 2017; 390(10113):2643-2654. DOI: 10.1016/S0140-6736(17)31634-3. View

Painter J, Borba C, Hynes M, Mays D, Glanz K . The use of theory in health behavior research from 2000 to 2005: a systematic review. Ann Behav Med. 2008; 35(3):358-62. DOI: 10.1007/s12160-008-9042-y. View

10.

Gilliland J, Sadler R, Clark A, OConnor C, Milczarek M, Doherty S . Using a Smartphone Application to Promote Healthy Dietary Behaviours and Local Food Consumption. Biomed Res Int. 2015; 2015:841368. PMC: 4561980. DOI: 10.1155/2015/841368. View

11.

Or C, Karsh B . A systematic review of patient acceptance of consumer health information technology. J Am Med Inform Assoc. 2009; 16(4):550-60. PMC: 2705259. DOI: 10.1197/jamia.M2888. View

12.

Ding D, Lawson K, Kolbe-Alexander T, Finkelstein E, Katzmarzyk P, van Mechelen W . The economic burden of physical inactivity: a global analysis of major non-communicable diseases. Lancet. 2016; 388(10051):1311-24. DOI: 10.1016/S0140-6736(16)30383-X. View

13.

Choi J, Kim J, Lee S, Lee S, Shin S, Park S . A Smartphone App (AnSim) With Various Types and Forms of Messages Using the Transtheoretical Model for Cardiac Rehabilitation in Patients With Coronary Artery Disease: Development and Usability Study. JMIR Med Inform. 2021; 9(12):e23285. PMC: 8693185. DOI: 10.2196/23285. View

14.

Laranjo L, Ding D, Heleno B, Kocaballi B, Quiroz J, Tong H . Do smartphone applications and activity trackers increase physical activity in adults? Systematic review, meta-analysis and metaregression. Br J Sports Med. 2020; 55(8):422-432. DOI: 10.1136/bjsports-2020-102892. View

15.

Milne-Ives M, Lam C, de Cock C, Van Velthoven M, Meinert E . Mobile Apps for Health Behavior Change in Physical Activity, Diet, Drug and Alcohol Use, and Mental Health: Systematic Review. JMIR Mhealth Uhealth. 2020; 8(3):e17046. PMC: 7113799. DOI: 10.2196/17046. View

16.

Spencer L, Adams T, Malone S, Roy L, Yost E . Applying the transtheoretical model to exercise: a systematic and comprehensive review of the literature. Health Promot Pract. 2006; 7(4):428-43. DOI: 10.1177/1524839905278900. View

17.

Kushniruk A . Evaluation in the design of health information systems: application of approaches emerging from usability engineering. Comput Biol Med. 2002; 32(3):141-9. DOI: 10.1016/s0010-4825(02)00011-2. View

18.

Gordon C, Rezzadeh K, Li A, Vardanian A, Zelken J, Shores J . Digital mobile technology facilitates HIPAA-sensitive perioperative messaging, improves physician-patient communication, and streamlines patient care. Patient Saf Surg. 2015; 9:21. PMC: 4487585. DOI: 10.1186/s13037-015-0070-9. View

19.

Yerrakalva D, Yerrakalva D, Hajna S, Griffin S . Effects of Mobile Health App Interventions on Sedentary Time, Physical Activity, and Fitness in Older Adults: Systematic Review and Meta-Analysis. J Med Internet Res. 2019; 21(11):e14343. PMC: 6908977. DOI: 10.2196/14343. View

20.

McEwan D, Beauchamp M, Kouvousis C, Ray C, Wyrough A, Rhodes R . Examining the active ingredients of physical activity interventions underpinned by theory versus no stated theory: a meta-analysis. Health Psychol Rev. 2018; 13(1):1-17. DOI: 10.1080/17437199.2018.1547120. View