Using Google Analytics as a process evaluation method for Internet-delivered interventions: an example on sexual health
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The study aimed to demonstrate the potential of Google Analytics as a process evaluation method for Internet-delivered interventions, using a website about sexual health as an example. This study reports visitors' behavior until 21 months after the release of the website (March 2009-December 2010). In total, there were 850 895 visitors with an average total visiting time (i.e. dose) of 5:07 min. Google Analytics provided data to answer three key questions in terms of process evaluation of an Internet-delivered intervention: (i) How do visitors behave?; (ii) Where do visitors come from? and (iii) What content are visitors exposed to? This real-life example demonstrated the potential of Google Analytics as a method to be used in a process evaluation of Internet-delivered interventions. This is highly relevant given the current expansion of these interventions within the field of health promotion.
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The bounce rate of 19.37% was substantially lower than that observed in other interventions (e.g., 32.9% in a sexual health intervention, 56.3% in a heart-healthy behaviors intervention).
“The bounce rate of 19.37% was also substantially lower than that observed in other interventions (eg, 32.9% in an intervention promoting sexual health, and 56.3% in an intervention promoting heart-healthy behaviors) [21,22], indicating that the home page was effective at engaging users.”
From Breaking open the black box: isolating the most potent features of a web and mobile phone-based intervention for depression, anxiety, and stress (2015) · cites this paper as [21]
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Cites
DeLamater, J., & Ward, A. (2013) · Handbooks of sociology and social research · doi:10.1007/978-94-007-6772-0 · Cited by 7,565 · see citing works
Petty, R. E., Wegener, D. T., & Fabrigar, L. R. (1997) · Annual Review of Psychology · doi:10.1146/annurev.psych.48.1.609 · Cited by 2,290 · see citing works
Attention web designers: You have 50 milliseconds to make a good first impression!
Lindgaard, G., Fernandes, G., Dudek, C., & Brown, J. M. (2006) · Behaviour and Information Technology · doi:10.1080/01449290500330448 · Cited by 1,025 · see citing works
Process evaluation for public health interventions and research
Steckler, A., Linnan, L. A., & Israel, B. A. (2002) · Cited by 864 · see citing works
Website-Delivered Physical Activity Interventions
Vandelanotte, C., Spathonis, K. M., Eakin, E. G., & Owen, N. (2007) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2007.02.041 · Cited by 475 · see citing works
Brouwer, W., Kroeze, W., Crutzen, R., de Nooijer, J., de Vries, N. K., Brug, J., & Oenema, A. (2011) · Journal of Medical Internet Research · doi:10.2196/jmir.1639 · Cited by 455 · see citing works
Self-citationPortnoy, D. B., Scott-Sheldon, L. A. J., Johnson, B. T., & Carey, M. P. (2008) · Preventive Medicine · doi:10.1016/j.ypmed.2008.02.014 · Cited by 451 · see citing works
Advanced Web Metrics with Google Analytics
Clifton, B. (2008) · Cited by 249 · see citing works
Engagement and retention: measuring breadth and depth of participant use of an online intervention
Couper, M. P., Alexander, G. L., Zhang, N., Little, R. J., Maddy, N., Nowak, M. A., McClure, J. B., Calvi, J. J., Rolnick, S. J., Stopponi, M. A., et al. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1430 · Cited by 244 · see citing works
Effects of Web- and Computer-Based Smoking Cessation Programs
Myung, S., McDonnell, D. D., Kazinets, G., Seo, H. G., & Moskowitz, J. M. (2009) · Archives of Internal Medicine · doi:10.1001/archinternmed.2009.109 · Cited by 237 · see citing works
Google Analytics for measuring website performance
Plaza, B. (2010) · Tourism Management · doi:10.1016/j.tourman.2010.03.015 · Cited by 206 · see citing works
Crutzen, R., Peters, G.-J. Y., Portugal, S. D., Fisser, E. M., & Grolleman, J. J. (2011) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2010.09.002 · Cited by 205 · see citing works
Self-citationCan the Internet Be Used Effectively to Provide Sex Education to Young People in China?
Lou, C., Zhao, Q., Gao, E., & Shah, I. (2006) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2006.04.003 · Cited by 188 · see citing works
Computer-tailored dietary behaviour change interventions: a systematic review
Neville, L. M., O'Hara, B., & Milat, A. J. (2009) · Health Education Research · doi:10.1093/her/cyp006 · Cited by 166 · see citing works
Crutzen, R., de Nooijer, J., Brouwer, W., Oenema, A., Brug, J., & de Vries, N. K. (2011) · Health Education & Behavior · doi:10.1177/1090198110372878 · Cited by 158 · see citing works
Self-citationExamining Information Processing on the World Wide Web Using Think Aloud Protocols
Eveland, W. P., & Dunwoody, S. (2000) · Media Psychology · doi:10.1207/s1532785xmep0203_2 · Cited by 149 · see citing works
Brouwer, W., Oenema, A., Raat, H., Crutzen, R., de Nooijer, J., de Vries, N. K., & Brug, J. (2010) · Health Education Research · doi:10.1093/her/cyp063 · Cited by 147 · cited 2× · see citing works
“…bounce rate is quite low in comparison with other Internet-delivered interventions [e.g. 56.3% in an intervention promoting heart-healthy behaviors (Brouwer et al., 2010)], it demonstrates the importance of the first impression which has a long-lasting effect on website use (Lindgaard et al.,…”
BackgroundInfluentialSelf-citationUsing Google Analytics to Evaluate the Usability of E-Commerce Sites
Hasan, L., Morris, A., & Probets, S. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-02806-9_81 · Cited by 132 · see citing works
Crutzen, R., & Göritz, A. S. (2010) · BMC Public Health · doi:10.1186/1471-2458-10-720 · Cited by 129 · see citing works
Self-citationA Computer-based Approach to Preventing Pregnancy, STD, and HIV in Rural Adolescents
Roberto, A. J., Zimmerman, R. S., Carlyle, K. E., & Abner, E. L. (2007) · Journal of Health Communication · doi:10.1080/10810730601096622 · Cited by 128 · see citing works
Riet, J. V. ‘., Crutzen, R., & de Vries, H. (2010) · Journal of Medical Internet Research · doi:10.2196/jmir.1345 · Cited by 93 · see citing works
Self-citationKaushik, A. (2007) · International Linear Collider · Cited by 81 · see citing works
Murry, J. P., Stam, A., & Lastovicka, J. L. (1993) · Journal of the American Statistical Association · doi:10.1080/01621459.1993.10594288 · Cited by 61 · see citing works
Crutzen, R., de Nooijer, J., Brouwer, W., Oenema, A., Brug, J., & de Vries, N. K. (2009) · Health Promotion International · doi:10.1093/heapro/dap018 · Cited by 60 · see citing works
Self-citationA web analytics tool selection method: an analytical hierarchy process approach
Nakatani, K., & Chuang, T. (2011) · Internet Research · doi:10.1108/10662241111123757 · Cited by 52 · see citing works
Health education and the Internet: the beginning of a revolution
Bernhardt, J. M. (2001) · Health Education Research · doi:10.1093/her/16.6.643 · Cited by 52 · see citing works
Steele, R. M., Mummery, W. K., & Dwyer, T. (2009) · Health Education & Behavior · doi:10.1177/1090198109335802 · Cited by 48 · see citing works
Portnoy, D. B., Scott‐Sheldon, L. A. J., Johnson, B. T., & Carey, M. P. (2007) · OpenCommons - UConn (University of Connecticut) · Cited by 46 · see citing works
Does social desirability compromise self-reports of physical activity in web-based research?
Crutzen, R., & Göritz, A. S. (2011) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/1479-5868-8-31 · Cited by 46 · see citing works
Self-citationActionable Web Analytics: Using Data to Make Smart Business Decisions
Burby, J., & Atchison, S. (2007) · Cited by 38 · see citing works
Crutzen, R., de Nooijer, J., Candel, M. J. J. M., & de Vries, N. K. (2008) · Journal of Health Psychology · doi:10.1177/1359105308095064 · Cited by 37 · see citing works
Self-citationEffectiveness of online word of mouth on exposure to an Internet-delivered intervention
Crutzen, R., de Nooijer, J., Brouwer, W., Oenema, A., Brug, J., & de Vries, N. K. (2008) · Psychology and Health · doi:10.1080/08870440802521094 · Cited by 35 · see citing works
Self-citationBarak, A., & Fisher, W. A. (2003) · Sexual & Relationship Therapy · doi:10.1080/1468199031000153928 · Cited by 33 · see citing works
Frequency and Type of Use of a Home-Based, Internet Intervention for Adolescent Smoking Cessation
Patten, C. A., Rock, E., Meis, T. M., Decker, P. A., Colligan, R. C., Pingree, S., Dornelas, E. A., Offord, K. P., Boberg, E. W., & Gustafson, D. H. (2007) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2007.05.016 · Cited by 32 · see citing works
Cult of Analytics: Driving online marketing strategies using web analytics
Jackson, S. (2009) · Routledge eBooks · doi:10.4324/9780080885179 · Cited by 31 · see citing works
Impact of a mass media campaign upon calls to the New South Wales Hep C Helpline
Chen, J., Smith, B. J., Loveday, S., et al. (2005) · Health Promotion Journal of Australia · doi:10.1071/he05011 · Cited by 11 · see citing works
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O’Connor, S., Hanlon, P., O’Donnell, C. A., Garcia, S., Glanville, J., & Mair, F. S. (2016) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-016-0359-3 · Cited by 636 · see citing works
Short, C. E., DeSmet, A., Woods, C., Williams, S. L., Maher, C., Middelweerd, A., Müller, A. M., Wark, P. A., Vandelanotte, C., Poppe, L., et al. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9397 · Cited by 400 · see citing works
Self-citationTitov, N., Dear, B. F., Staples, L. G., Bennett-Levy, J., Klein, B., Rapee, R. M., Andersson, G., Purtell, C., Bezuidenhout, G., & Nielssen, O. B. (2017) · Australian & New Zealand Journal of Psychiatry · doi:10.1177/0004867416671598 · Cited by 183 · see citing works
Kelders, S. M., Bohlmeijer, E. T., & Van Gemert-Pijnen, J. E. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2258 · Cited by 88 · see citing works
Whitton, A. E., Proudfoot, J., Clarke, J., Birch, M.-R., Parker, G., Manicavasagar, V., & Hadzi-Pavlovic, D. (2015) · JMIR Mental Health · doi:10.2196/mental.3573 · Cited by 69 · see citing works
Simons, D., De Bourdeaudhuij, I., Clarys, P., De Cocker, K., Vandelanotte, C., & Deforche, B. (2018) · JMIR mHealth and uHealth · doi:10.2196/10003 · Cited by 56 · see citing works
Understanding adherence to web-based interventions
Kelders, S. M. (2012) · doi:10.3990/1.9789036534178 · Cited by 29 · see citing works
- Authors
- Crutzen, R., Roosjen, J. L., & Poelman, J.
- Affiliations
- Maastricht University (NL)
- Corresponding author
- Crutzen, R.
- ORCID
- Crutzen, R.
- Venue
- Health Promotion International
- Publisher
- Oxford University Press (OUP)
- Published
- 2012-02-29
- Volume
- 28
- Issue
- 1
- Pages
- 36-42
- ISSN
- 0957-4824 (ISSN-L)
- 1460-2245
- OpenAlex
- W2116194564
- Cited by
- 113
- References
- 36
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 5 · 2023: 4 · 2022: 8 · 2021: 12 · 2020: 10 · 2019: 9 · 2018: 15 · 2017: 12 · 2016: 8 · 2015: 9 · 2014: 9 · 2013: 5 · 2012: 3
- FWCI
- 9.47
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Health Promotion International (publishedVersion)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek
- Topics
- Social Sciences › Health › Social Media in Health Education
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- Google Analytics, process evaluation, online intervention, sexual health, website visitors, visitor behavior, website traffic, health promotion, online health interventions
- MeSH terms
- Health Education, Health Promotion, Humans, Software, Internet, Informatics, Data Mining, Reproductive Health
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