E-screening: Challenges and opportunities for health
AbstractDear Sir,1 There is growing interest in applying e-health approaches to prevent and control of the diseases and their risk factors (1). Using electronic information and communication technologies for health provide immediate and tailored feedback, cost-effective outcome and have the potential for widespread reach for high risk and hard reach populations (2). The internet, on the one hand, provides a powerful tool in unique opportunity to identify, management and prevention of the diseases, and on the other hand it as an interactive tool increases knowledge about the diseases, risk factors, and offer approaches to deal with health problem (3). Internet-based health technologies are becoming increasingly available for the rapid identification of the risk factors and also for the more accurate monitoring of non-communicable disease activity. Web-based surveillance tools and e-screening intelligence methods, used by all major public health institutions, are intended to facilitate risk assessment and timely detection (1, 4). E-screening provides real-time scoring of screen for professionals and patients. E-screening was used for non-communicable risk factors and lifestyle (5-7). E-screening has the potential to * Corresponding Author: Leila Jahangiry, Postal Address: Department of Health Education and Health Promotion, School of Public Health, Tabriz University of Medical Sciences, Tabriz, Iran. Email: Jahangiry@razi.tums.ac.ir increase the efficiency of mental health care by reallocating limited human resources where they are most needed in-depth follow-up assessment, referral, and treatment (8). The web-based healthy lifestyle education, focused on healthy nutrition and exercise, can lead to improvements in general health (9). There is substantial evidence showing that use of web-based interventions improves behavioral change outcomes. These outcomes included increased exercise time, increased knowledge of nutritional status, increased knowledge of asthma treatment, increased participation in health care, slower health decline, improved body shape perception, and 18-month weight loss maintenance (10). According to Rose (11) general population and at-risk population is accessed to screening and intervention tools. According to Rose (11) general population and at-risk population screening is used to detect certain individuals who were well but they must know that they are in high-risk conditions. It seems that the web can act as a relatively simple approach for diagnosing the risk factors of high prevalence diseases such as cardiovascular diseases. Metabolic syndrome that defines as clustering of risk factors might be provided in the prevention through web due to easily measurable risk factors. In addition, it seems that selfmeasurement of waist circumference is easy to perform and it is known in related to cardiovascular diseases (12). Thus, from a public health point of view, early identification of high risk and difficult to reach individuals Journalthrough the internet is an important issue, especially in primary care.
Barak A, Klein B, Proudfoot JG. Defining internet-supported therapeutic interventions. Ann Behav Med 2009; 38(1): 4-17.
Avis JL, Bridger T, Buchholz A, Chanoine JP, Hadjiyannakis S, Hamilton J, et al. It's like rocket science…only more complex: Challenges and experiences related to managing pediatric obesity in Canada. Expert Rev Endocrinol Metab 2014; 9(3): 223-9.
Piette JD. Enhancing support via interactive technologies. Curr Diab Rep 2002; 2(2): 160-5.
Murray E, Burns J, See TS, Lai R, Nazareth I. Interactive health communication applications for people with chronic disease. Cochrane Database Syst Rev 2005; (4): CD004274.
Jahangiry L, Shojaeizadeh D, Abbasalizad FM, Yaseri M, Mohammad K, Najafi M, et al. Interactive web-based lifestyle intervention and metabolic syndrome: Findings from the Red Ruby (a randomized controlled trial). Trials 2015; 16: 418.
Jahangiry L, Shojaeizadeh D, Montazeri A, Najafi M, Mohammad K, Abbasalizad FM.
Modifiable lifestyle risk factors and metabolic syndrome: Opportunities for a web-based preventive program. J Res Health Sci 2014; 14(4): 303-7.
Norman GJ, Zabinski MF, Adams MA, Rosenberg DE, Yaroch AL, Atienza AA. A review of eHealth interventions for physical activity and dietary behavior change. Am J Prev Med 2007; 33(4): 336-45.
Choo EK, Ranney ML, Aggarwal N, Boudreaux ED. A systematic review of emergency department technology-based behavioral health interventions. Acad Emerg Med 2012; 19(3): 318-28.
Bastani F, Hashemi S. Effects of a web based lifestyle education on general health and severity of the symptoms of premenstrual syndrome (PMS) among female students: A Randomized Controlled Trial. Procedia Soc Behav Sci 2012; 46: 3356-62.
Wantland DJ, Portillo CJ, Holzemer WL, Slaughter R, McGhee EM. The effectiveness of Web-based vs. non-Web-based interventions: A meta-analysis of behavioral change outcomes. J Med Internet Res 2004; 6(4): e40.
Rose G. Sick individuals and sick populations. Int J Epidemiol 2001; 30(3): 427-32.
Jahangiry L, Shojaeezadeh D, Montazeri A, Najafi M, Mohammad K. Health-related quality of life among people participating in a metabolic syndrome e-screening program: A web-based study. Int J Prev Med 2016; 7: 27.