title: Investigating predictors of visiting, using, and revisiting an online health-communication program: a longitudinal study.
abstract: BACKGROUND
  Online health communication has the potential to reach large audiences, with the additional advantages that it can be operational at all times and that the costs per visitor are low. Furthermore, research shows that Internet-delivered interventions can be effective in changing health behaviors. However, exposure to Internet-delivered health-communication programs is generally low. Research investigating predictors of exposure is needed to be able to effectively disseminate online interventions.
  
  
  OBJECTIVE
  In the present study, the authors used a longitudinal design with the aim of identifying demographic, psychological, and behavioral predictors of visiting, using, and revisiting an online program promoting physical activity in the general population.
  
  
  METHODS
  A webpage was created providing the public with information about health and healthy behavior. The website included a "physical activity check," which consisted of a physical activity computer-tailoring expert system where visitors could check whether their physical activity levels were in line with recommendations. Visitors who consented to participate in the present study (n = 489) filled in a questionnaire that assessed demographics, mode of recruitment, current physical activity levels, and health motivation. Immediately after, participants received tailored feedback concerning their current physical activity levels and completed a questionnaire assessing affective and cognitive user experience, attitude toward being sufficiently physically active, and intention to be sufficiently physically active. Three months later, participants received an email inviting them once more to check whether their physical activity level had changed.
  
  
  RESULTS
  Analyses of visiting showed that more women (67.5%) than men (32.5%) visited the program. With regard to continued use, native Dutch participants (odds ratio [OR] = 2.81, 95% confidence interval [CI] = 1.16-6.81, P = .02) and participants with a strong motivation to be healthy (OR = 1.46, CI = 1.03-2.07, P = .03) were most likely to continue usage of the program. With regard to revisiting, older participants (OR = 1.04, CI = 1.01-1.06, P = .01) and highly educated participants (OR = 4.69, CI = 1.44-15.22, P = .01) were more likely to revisit the program after three months. In addition, positive affective user experience predicted revisiting (OR = 1.64, CI = 1.12-2.39, P = .01).
  
  
  CONCLUSIONS
  The results suggest that online interventions could specifically target men, young people, immigrant groups, people with a low education, and people with a weak health motivation to increase exposure to these interventions. Furthermore, eliciting positive feelings in visitors may contribute to higher usage rates.
authors.affiliation: Wageningen University and Research Centre, Agricultural Economics Research Institute, The Hague, Netherlands. jonathan.vantriet@wur.nl
authors.forename: Jonathan
authors.initials: J
authors.lastname: Van 't Riet
authors.forename: Rik
authors.initials: R
authors.lastname: Crutzen
authors.forename: Hein
authors.initials: H
authors.lastname: De Vries
mesh_terms: D003142:Communication; D015444:Exercise; D005260:Female; D015438:Health Behavior; D006293:Health Promotion / Q000379:methods / Q000639:trends; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D009042:Motivation; D009862:Online Systems; D011237:Predictive Value of Tests
references.citation: J Med Internet Res. 2010 Feb 10;12(1):e3
references.pmid: 20147006
references.citation: Psychol Bull. 1992 May;111(3):455-74
references.pmid: 1594721
references.citation: Health Psychol. 2007 Jul;26(4):496-506
references.pmid: 17605570
references.citation: Ann Behav Med. 2003 Spring;25(2):92-9
references.pmid: 12704010
references.citation: Am J Public Health. 2004 May;94(5):744-6
references.pmid: 15117693
references.citation: J Med Internet Res. 2005 Jul 01;7(3):e27
references.pmid: 15998618
references.citation: J Clin Psychol. 2004 Feb;60(2):209-20
references.pmid: 14724928
references.citation: J Med Internet Res. 2005 Mar 31;7(1):e11
references.pmid: 15829473
references.citation: Eur J Clin Nutr. 2005 Aug;59 Suppl 1:S130-7; discussion S138-9
references.pmid: 16052181
references.citation: Health Psychol. 2001 Jul;20(4):256-66
references.pmid: 11515737
references.citation: Soc Sci Med. 2005 Apr;60(7):1467-78
references.pmid: 15652680
references.citation: J Health Psychol. 2008 Oct;13(7):906-11
references.pmid: 18809641
references.citation: J Med Internet Res. 2007 Jan 22;9(1):e1
references.pmid: 17478410
references.citation: BMJ. 2006 May 20;332(7551):1210-2
references.pmid: 16710004
references.citation: World Health Organ Tech Rep Ser. 2003;916:i-viii, 1-149, backcover
references.pmid: 12768890
references.citation: J Med Internet Res. 2006 Jun 23;8(2):e10
references.pmid: 16867965
references.citation: Health Educ Res. 2008 Jun;23(3):427-39
references.pmid: 18209115
references.citation: Am J Prev Med. 2007 Jul;33(1):54-64
references.pmid: 17572313
references.citation: Health Educ Res. 2010 Aug;25(4):585-95
references.pmid: 19897515
references.citation: J Nutr Educ Behav. 2004 Jan-Feb;36(1):20-4
references.pmid: 14756978
references.citation: Am J Health Promot. 1996 Nov-Dec;11(2):87-98
references.pmid: 10163601
references.citation: Med Sci Sports Exerc. 2003 Aug;35(8):1381-95
references.pmid: 12900694
references.citation: J Med Internet Res. 2007 Sep 30;9(3):e26
references.pmid: 17942388
references.citation: J Med Internet Res. 2009 Aug 26;11(3):e38
references.pmid: 19709990
references.citation: Health Psychol. 2008 Sep;27(5):638-44
references.pmid: 18823190
references.citation: Am J Public Health. 1999 Sep;89(9):1322-7
references.pmid: 10474547
references.citation: Cyberpsychol Behav. 2005 Oct;8(5):465-72
references.pmid: 16232039
references.citation: Am J Prev Med. 2007 May;32(5 Suppl):S119-26
references.pmid: 17466816