Table 3.

Table 3 List of Exemplary Research that Fits Each Generation

Reference	Generation	Health care	Persuasion Goal	Supporting Technologies	Study Outcomes
		sub-Domains
Piette J, Kraemer F, Weinberger M, and McPhee S. Impact of automated calls with nurse follow-up on diabetes treatment outcomes in a department of Veterans Arrairs Health Care System. Diab Care 2001;24:202–8. 9	G1	Diabetes treatment	Behaviour change	Automated telephone messages Personal and live follow-up communications	Intervention patients reported more frequent glucose self-monitoring and foot inspections, completion of a cholesterol test, fewer symptoms of poor glycemic control, and greater satisfaction with their health care than the control patients
Friedman R, Stollerman J, Mahoney D, and Rozenblyum L. The virtual visit: using telecommunications technology to take care of patients. Journal of the American Medical Informatics Association 1997;(4)413–425. 10	G1	Chronic disease monitoring Patient counselling Home caregiver support of patients with disabling conditions Diet/nutrition Physical activity	Improved health management and outcomes Behaviour change	Automated telephone system	Program participants showed higher medicine adherence, lower diastolic blood pressure readings, greater health awareness, lower total cholesterol readings, and greater physical activity than control group
Irvine AB, Ary DV, Grove DA, Gilfillan-Morton L. The effectiveness of an interactive multimedia program to influence eating habits. Health Educ Res 2004;19:290–305. 11	G1, G2	Weight loss Diet/nutrition	Behaviour change	Custom-created educational multimedia (IMM programming) and PC driven on healthy eating strategies Non-Internet based	Interactive multimedia programming (IMM) has a positive impact on behavior change (e.g., reduction in fats and increase in fruits and vegetables)
Kroeze W, Werkman A, and Brug J. A systematic review of randomized trials on the effectiveness of computer-tailored education on physical activity and dietary behaviors. Ann Behav Med 2006;31:205–33. 12	G1, G2	Diet/nutrition Physical activity	Behaviour change Attitude change	Computer-based systems/interactive multimedia programs	Strong evidence that computer-tailored nutritional education impacts behavior but weakness exist with short-time frame of studies
Lenert L, Munoz R, Perez J, Bansod A. Automated e-mail messaging as a tool for improving quit rates in an Internet smoking cessation intervention. Journal of the American Medical Informatics Association 2004;11:235–240. 13	G1, G2	Smoking cessation	Behaviour change Motivation Attitude change	e-mail Education-only Web sites	Individually timed educational messages (ITEM) group showed higher quit date establishment, intent-to-treat quit rates, and increase in odds-to-quit ratio than non-item group
Tate DF, Wing RR, Winett RA. Using Internet technology to deliver a behavioral weight loss program. JAMA 2007;285:1172–1177. 14	G2	Weight loss	Behaviour change	Computer/Internet Web-based diaries Web-based information on diet, exercise, other resources Weekly e-mails (personalized) to IBT group	IBT group lost more body weight and reduced their waist circumference over control group
Atkinson N, and Gold R. The promise and challenge of eHealth interventions. Am J Health Behav 2002;26:494–503.	G2	Various	Behaviour change	Message tailoring/Intervention tailoring	eHealth intervention shows promise in changing behavior
Baranowski T, Baranowski J, Cullen K, Marsh T, Islam N, Zakeri I, Hones-Morreale L, and Demoor C. Squire's Quest! Dietary outcome evaluation of a multimedia game. American J Prev Med 2003;24:52–61. 15	G2	Diet/nutrition	Behaviour change Attitude change	Psychoeducational, multimedia game	Program participants increased their fruit, juice, and vegetable consumption over nonparticipation group
Obermayer J, Riley W, Asif O, and Jean-Mary J. College smoking-cessation using cell phone text messaging. J Am Coll Health 2004;53–71–78. 16	G2	Smoking cessation	Behaviour change Motivation Attitude change	Web and cell phone technologies (text messages)	Support shown for using text messages in the aid to reduce smoking rates
Hurling R, Catt M, de boni M, Fairly B, Hurst T, Murray P, Richardson A, and Sodhi J. Using Internet and Mobile phone technology to deliver an Automated Physical Activity Program. J Med Internet Res 2007;9(2):e7. 17	G2	Diet/nutrition Physical activity	Behaviour change Motivation	Sensor and Internet technologies	Test group reported a significant greater increase over the control group
Chen D, Yang J, Malkin R, and Wactlar H. Detecting social interactions of the elderly in a nursing home environment. ACM transactions on multimedia computing, Communications and Applications 2007;3(1). 18	G3	Physical activity Aging Habitat monitoring	Behaviour change Surveillance Attitude change	Multimedia processing Simulation and modeling Wireless sensor networks	Detection of social interaction patterns is possible and can be used to predict changes in physical and behavioral states
Eriksson H, and Timpka T. The potential of smart homes for injury prevention among the elderly. Inj Control Saf Promot 2007;9(2). 19	G3	Physical activity Habitat monitoring	Various	Wireless sensors IP-based networks	Literature review on the use of wireless sensor networks and smart homes and the four components needed—sensors, communication network, computational components, and actuators—for injury detection and activity monitoring
Jovanov E, Milenkovic A, Otto C, and De Groen P. A wireless body network of intelligent motion sensors for computer assisted physical rehabilitation. J J Neuroengineering Rehab 2005;2(6). 20	G3	Physical activity	Behaviour change Motivation	Wireless body area network (WBAN) Physiological sensors	WBAN's can support unobtrusive and unsupervised ambulatory monitoring of physical activity and health states and provide feedback messages to promote change persuasion