Technology-based health promotion: Current state and perspectives in emerging gig economy

• Autorzy: Morales Jafet , Inupakutika Devasena , Kaghyan Sahak , Akopian David , Yin Zenong , Evans Martin , Parra-Medina Deborah

Identyfikatory

DOI

10.1016/j.bbe.2019.07.006

• Języki publikacji: EN

Abstrakty

EN

It has been a decade since smartphone application stores started allowing developers to post their own applications. This paper presents a narrative review on the state-of-the-art and the future of technology used by researchers in the field of mobile health promotion. Researchers build high cost, complex systems with the purpose of promoting health and collecting data. These systems promote health by using a feedback component that ''educates'' the subject. Other researchers instead use platforms which provide them with data collected by others, which allows for no communication with subjects, but may be cheaper than building a system to collect the data. This second type of systems cannot be used directly for health promotion. However, both types of systems are relevant to the field of health promotion, because they are precursors to a third type of systems that are emerging, the gig economy systems for mobile health data collection, which are low cost, globally available, and provide limited communication with subjects. If such systems evolve to include more channels for communication with the data-generating subjects, and also bring developers into the economy, they may eventually revolutionize the field of mobile health promotion and data collection by giving researchers new capabilities, such as the ability to replicate existing health promotion campaigns with the click of a button and the appropriate licenses. In this paper we present a review of state-of-the-art systems for mobile health promotion and data collection and a model for what these systems may look like in the future.

Słowa kluczowe

EN

health promotion; gig economy; mobile health

PL

promocja zdrowia; rynek umów krótkoterminowych; medycyna mobilna

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2019
• Tom: Vol. 39, no. 3
• Strony: 825--842
• Opis fizyczny: Bibliogr. 89 poz., rys., tab.

Twórcy

autor

Morales Jafet

• University of Texas at San Antonio, San Antonio, TX, United States; BSE 1.500, One UTSA Circle, San Antonio, TX 78249, United States

autor

Inupakutika Devasena

• University of Texas at San Antonio, San Antonio, TX, United States

autor

Kaghyan Sahak

• University of Texas at San Antonio, San Antonio, TX, United States

autor

Akopian David

• University of Texas at San Antonio, San Antonio, TX, United States

autor

Yin Zenong

• University of Texas at San Antonio, San Antonio, TX, United States

autor

Evans Martin

• University of Texas at Austin, Austin, TX, United States

autor

Parra-Medina Deborah

• University of Texas at Austin, Austin, TX, United States

Bibliografia

• [1] Fineberg H. A successful and sustainable health system— how to get there from here. N Engl J Med 2012;366(11):1020–7.
• [2] Lehoux P, Roncarolo F, Silva HP, Boivin A, Denis JL, Hébert R. What health system challenges should responsible innovation in health address? Insights from an international scoping review. Int J Health Policy Manage 2018;8(2):63–75.
• [3] CTIA, The Wireless Industry. Industry Data, 2019. [Online]. Available: https://www.ctia.org/the-wireless-industry/ infographics-library. [Accessed 21 6 2019].
• [4] Hesseldahl A. Blackberry gets chatty. Forbes 2002;4(March) [Online]. Available: https://www.forbes.com/2002/03/04/0304tentech. html#adfb5f669f97. [Accessed 21 6 2019].
• [5] Ventola CL. Mobile devices and apps for health care professionals: uses and benefits. P T 2014;39(5):356–64.
• [6] Boulos MN, Brewer AC, Karimkhani C, Buller DB, Dellavalle RP. Mobile medical and health apps: state of the art, concerns, regulatory control and certification. Online J Public Health Inform 2014;5(3).
• [17] Arsand E, Tatara N, Østengen G, Hartvigsen G. Mobile phone-based self-management tools for type 2 diabetes: the few touch application. J Diabetes Sci Technol 2010;4 (Mar (2)):328–36.
• [19] Glynn LG, Hayes PS, Casey M, Glynn F, Alvarez-Iglesias A, Newell J, et al. Effectiveness of a smartphone application to promote physical activity in primary care: the SMART MOVE randomised controlled trial. Br J Gen 2014;64(624). e384-91.
• [20] Brewer LC, Jenkins S, Lackore K, Johnson J, Jones C, Cooper LA, et al. mHealth intervention promoting cardiovascular health among African-Americans: recruitment and baseline characteristics of a pilot study. JMIR Res Protoc 2018;7(1).
• [21] Overdijkink SB, Velu AV, Rosman AN, van Beukering MD, Kok M, Steegers-Theunissen RP. The Usability and effectiveness of mobile health technology-based lifestyle and medical intervention apps supporting health care during pregnancy: systematic review. JMIR mHealth and uHealth 2018;6(4).
• [22] Armoiry X, Sturt J, Phelps EE, Walker CL, Court R, Taggart F, et al. Digital clinical communication for families and caregivers of children or young people with short- or long-term conditions: rapid review. J Med Internet Res 2018;20(1).
• [23] Zan S, Agboola S, Moore SA, Parks KA, Kvedar JC, Jethwani K. Patient engagement with a mobile web-based telemonitoring system for heart failure self-management: a pilot study. JMIR mHealth and uHealth 2015;3(2).
• [24] Wolf JA, Moreau JF, Akilov O, Patton T, English JC, Ho J, et al. Diagnostic inaccuracy of smartphone applications for melanoma detection. JAMA Dermatol 2013;149(4):422–6.
• [25] Hurt K, Walker RJ, Campbell JA, Egede LE. mHealth interventions in low and middle-income countries: a systematic review. Global J Health Sci 2015;8(9).
• [26] Ossebaard H, Gemert-Pijnen J. EHealth and quality in health care: implementation time. Int J Qual Health Care 2016;28 (3):415–9.
• [27] Tamura T, Maeno S, Hattori T, Kimura Y, Yoshida M, Minato K. Assessment of participant compliance with a web-based home healthcare system for promoting specific health checkups. Biocybernet Biomed Eng 2014;34(1):63–9.
• [28] Glowacz A, Glowacz Z. Recognition of images of finger skin with application of histogram, image filtration and K-NN classifier. Biocybernet Biomed Eng 2016;36(1):95–101.
• [29] Morales J, Akopian D. Physical activity recognition by smartphones, a survey. Biocybernet Biomed Eng 2017;37(no. 3):388–400.
• [30] Istepanian RSH, Laxminarayn S, Pattichis CS. M-Health: emerging mobile health systems. Topics in biomedical engineering. Int. Book Series. London, UK: Springer-Verlag; 2006.
• [31] Research2guidance. mHealth App Developer Economics 2014 Report. http://www.research2guidance.com/r2g/research2guidance- mHealth-App-Developer-Economics-2014.pdf.
• [32] Naslund JA, Aschbrenner KA. Digital technology for health promotion: opportunities to address excess mortality in persons living with severe mental disorders. Evid Based Mental Health 2019;22(1):17–22.
• [33] Pickard KT. Exploring markets of data for personal health information. IEEE International Conference on Data Mining Workshop (ICDMW) 2014.
• [34] Uber Technologies Inc., "Uber," 2019. [Online]. Available: https://www.uber.com/. [Accessed 20 6 2019].
• [35] Airbnb, " Airbnb," 2019. [Online]. Available: https://www.airbnb.com/. [Accessed 20 6 2019].
• [36] TaskRabbit, "The convenient & affordable way to get things done around the home.," 2019. [Online]. Available: https://www.taskrabbit.com. [Accessed 20 6 2019].
• [37] N. Koziol A. Arthur, An Introduction to Secondary Data Analysis, CYFS Statistics and Measurement.
• [38] Romano, Using secondary data, Department of Medicine and Pediatrics. University of California.
• [39] Kirwan M, Duncan M, Vandelanotte C, Mummery W. Using smartphone technology to monitor physical activity in the 10,000 steps program: a matched case-control trial. JMIR 2012;14(2). p. e55.
• [40] Slootmaker S, Chinapaw M, Seidell J, van Mechelen W, Schuit A. Accelerometers and Internet for physical activity promotion in youth? Feasibility and effectiveness of a minimal intervention. Prev Med 2010;51(1):31–6.
• [41] Fukuoka Y, Vittinghoff E, Jong S, Haskell W. Innovation to motivation: pilot study of a mobile phone intervention to increase physical activity among sedentary women. Prev Med 2010;51(3–4):287–9.
• [42] Seto E, Hua J, Wu L, Shia V, Eom S, Wang M, et al. Models of individual dietary behavior based on smartphone data: the influence of routine, physical activity, emotion, and food environment. PLoS ONE 2016;11(4).
• [43] Harries T, Eslambolchilar P, Rettie R, Stride C, Walton S, van Woerden H. Effectiveness of a smartphone app in increasing physical activity amongst male adults: a randomised controlled trial. BMC Public Health 2016;16. p. 925.
• [44] Garde A, Umedaly A, Abulnaga S, Robertson L, Junker A, Chanoine J. Assessment of a mobile game ('MobileKids Monster Manor') to promote physical activity among children. Games Health 2015;4(2):149–58.
• [45] Furrer M, Bichsel L, Niederer M, Baur H, Schmid S. Validation of a smartphone-based measurement tool for the quantification of level walking. Gait Posture 2015;42:289–94.
• [46] Cowdery J, Majeske P, Frank R, Brown D. Exergame apps and physical activity: the results of the ZOMBIE trial. Am J Health Educ 2015;46:216–22.
• [47] Schaefer S, Van Loan M, German J. A feasibility study of wearable activity monitors for pre-adolescent school-age children. Prev Chronic Dis 2014;11.
• [48] Klein M, Mogles N, van Wissen A. Intelligent mobile support for therapy adherence and behavior change. J Biomed Inform 2014;51:137–51.
• [49] Direito A, Jiang Y, Whittaker R, Maddison R. Apps for IMproving FITness and increasing physical activity among young people: the AIMFIT pragmatic randomized controlled trial. JMIR 2015.
• [50] Hooke M, Gilchrist L, Tanner L, Hart N, Withycombe J. Use of a fitness tracker to promote physical activity in children with acute lymphoblastic leukemia. Pediatr Blood Cancer 2016;63(4):684–9.
• [51] Vosa S, Janssena M, Goudsmita J, Lauwerijssenc C, Brombacherb A. From problem to solution: developing a personalized smartphone application for recreational runners following a three-step design approach. Procedia Eng 2016;147:799–805.
• [52] Nes A, van Dulmen S, Eide E. The development and feasibility of a web-based intervention with diaries and situational feedback via smartphone to support self-management in patients with diabetes type 2. Diabetes Res Clin Pract 2012;97(3):385–93.
• [53] Morrison L, Hargood C, Lin S, Dennison L, Joseph J, Hughes S, et al. Understanding usage of a hybrid website and smartphone app for weight management: a mixed- methods study. J Med Internet Res 2014;16(10).
• [54] Schaefer S, Ching C, Breen H, German J. Wearing, thinking, and moving: testing the feasibility of fitness tracking with urban youth. Am J Health Educ 2016;47(1):8–16.
• [55] Nolan M, Mitchell J, Doyle-Baker P. Validity of the Apple iPhone® /iPod Touch® as an accelerometer-based physical activity monitor: a proof-of-concept study. J Phys Act Health 2014;11:759–69.
• [56] Choi J, Lee J, Vittinghoff E, Fukuoka Y. mHealth physical activity intervention: a randomized pilot study in physically inactive pregnant women. Matern Child Health 2016;20:1091–101.
• [57] Hayes L, Van Camp C. Increasing physical activity of children during school recess. J Appl Behav Anal 2015;48 (3):690–5.
• [58] Nguyen N, Hadgraft N, Moore M, Rosenberg D, Lynch C, Reeves M, et al. A qualitative evaluation of breast cancer survivors' acceptance of and preferences for consumer wearable technology activity trackers. Support Care Cancer 2017;25(11):3375–84.
• [59] Årsand E, Tatara N, Hartvigsen G. Mobile phone-based self-management tools for type 2 diabetes: the Few Touch Application. J Diabetes Sci Technol 2010;4(2):328–36.
• [61] The University of Texas at Austin, "Healthy Frio," 2018. [Online]. Available: https://liberalarts.utexas.edu/lri/ResearchPrograms/index. php. [Accessed 4 7 2018].
• [62] Fitbit, Inc, "Fitbit Flex 2," 2018. [Online]. Available: https://www.fitbit.com/my/flex2. [Accessed 19 12 2018].
• [63] Withings, "Scales," 2018. [Online]. Available: https://www.withings.com/us/en/scales. [Accessed 19 12 2018].
• [64] Moodle Community, "moodle," [Online]. Available: https://moodle.org/. [Accessed 19 12 2018].
• [65] nPhase, Inc, "REDCAP CLOUD," 2018. [Online]. Available: https://www.redcapcloud.com/. [Accessed 19 12 2018].
• [66] Small Steps Labs LLC, "fitabase," 2018. [Online]. Available: https://www.fitabase.com/. [Accessed 19 12 2018].
• [67] US Federal Government, "HealthData.gov," U.S. Department of Health & Human Services, 30 11 2018. [Online]. Available: https://healthdata.gov. [Accessed 30 11 2018].
• [68] US Government, "DATA.GOV," US Government, [Online]. Available: https://www.data.gov/. [Accessed 30 11 2018].
• [69] Kaggle Inc, "kaggle," Kaggle Inc, 2018. [Online]. Available: https://www.kaggle.com/. [Accessed 30 11 2018].
• [70] University of California, Irvine and Rexa.info, "UCI Machine Learning Repository," University of California, Irvine and Rexa.info, [Online]. Available: https://archive.ics.uci.edu/ml/datasets.html. [Accessed 30 11 2018].
• [71] HealthVerity, Inc., " Healthverity Marketplace," Healthverity, 2018. [Online]. Available: http://healthverity.com/. [Accessed 21 May 2018].
• [72] The Health Exchange Market, "The Health Exchange Market," Website Design by Bigfoot Media, 2018. [Online]. Available: https://thehealthexchangemarket.com/. [Accessed 21 May 2018].
• [73] Health Wizz, "Health Wizz," Health Wizz, 2018. [Online]. Available: https://www.healthwizz.net/. [Accessed 21 May 2018].
• [74] Health Wizz Inc., " MY HEALTHCARE IN MY HANDS, A user-centric approach to mak ing medical records accessible on blockcha in," [Onl ine]. Available: https://daks2k3a4ib2z.cloudfront.net/ 586ebe41ba9f9499729002dc/ 5a4b017c7b791a00019e6fb1_Healthwizz_WhitePaper.pdf. [Accessed 21 May 2018].
• [75] CoverUS, " CoverUs," 2018. [Online]. Available: https://www.coverus.io/ [Accessed 21 May 2018].
• [76] Longenesis, " Longenesis," Longenesis Ltd, 2018. [Online]. Available: http://longenesis.com/. [Accessed 21 May 2018].
• [77] Mamoshina P, Ojomoko L, Yanovich Y, Ostrovski A, Botezatu A, Prikhodko P, et al. Converging blockchain and next-generation artificial intelligence technologies to decentralize and accelerate biomedical research and healthcare. Oncotarget 2018;9(5):5665–90.
• [78] Desta Y. 9 simple tips for making your website disability-friendly. Mashable 2014;22(April) [Online]. Available: https://mashable.com/2014/04/22/website-disability- friendly/#g2mztd2RasqO. [Accessed 25 October 2018].
• [79] de Arriba-Pérez F, Caeiro-Rodríguez M, Santos-Gago J. Collection and processing of data from wrist wearable devices in heterogeneous and multiple-user scenarios. Sensors (Basel) 2016;16(9). p. PMC5038811.
• [80] R. 6749, "The Oauth2.0 Authorization Framework," 1 October 2012. [Online]. Available: https://tools.ietf.org/html/rfc6749. [Accessed 7 July 2018].
• [81] Apple, Inc, "Apple Health," Apple, Inc, 2018. [Online]. Available: https://www.apple.com/ios/health/. [Accessed 21 May 2018].
• [82] Google, "The Google Fit SDK," [Online]. Available: https://developers.google.com/fit/. [Accessed 21 May 2018].
• [83] SAMSUNG, " Samsung Health: The Beginning of Smart Health Care," 2018. [Online]. Available: https://health.apps.samsung.com/. [Accessed 21 May 2018].
• [84] Fitbit, Inc., " Fitbit," 2018. [Online]. Available: https://www.fitbit.com/home. [Accessed 21 May 2018].
• [85] MyFitnessPal, Inc., "Lose Weight with MyFitnessPal," 2018. [Online]. Available: https://www.myfitnesspal.com/. [Accessed 21 May 2018].
• [86] Nokia, " Nokia Body, Weight & BMI Wi-Fi Scale," 2018. [Online]. Available: https://health.nokia.com/uk/en/body. [Accessed 21 May 2018].
• [87] Morales J, Escobar R, Kaghyan S, Natarajan G, Akopian D, Chalela P, et al. Two-tier state-machine programming for messaging applications. Electronic imaging 2017; 2017. Burlingame, CA, USA.
• [88] Morales J, Akopian D, Agaian S. Human activity recognition by smartphones regardless of device orientation. Proc. SPIE 9030, mobile devices and multimedia: enabling technologies, algorithms, and applications 2014; 2014. San Francisco, CA, USA.
• [89] Morales J, Akopian D. Human activity tracking by mobile phones through hebbian learning. Int J Artif Intell Appl 2016;7(6).

Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).

PL

W opisie bibliogr. brak poz. nr 7-16, 18, 60.