Cited by 193Smoking Behavior and CessationBehavioral Health and InterventionsMedia Influence and Health

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Working mechanisms of computer-tailored health education: evidence from smoking cessation

Dijkstra, Arie·2005·Health Education Research

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Abstract

To further develop tailored interventions, their working mechanisms must be identified. In the present study, three tailored messages that each contained one potential working mechanism--personalization, adaptation or feedback--were compared with a standard information condition. Two hundred and two students who smoked tobacco daily were randomly divided over four conditions. After the computer pre-test questionnaire, they read the information in their condition and filled in the immediate post-test. After 4 months, they were sent a follow-up questionnaire assessing their quitting activity. The data show that personalization (44.5%) and feedback (48.7%), but not adaptation (28.6%), led to significantly more quitting activity after 4 months than did the standard information (22.9%). Moreover, the effect of condition on quitting activity was completely mediated by individuals' evaluations of the tailoring.

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Research works printed but not linked: 1

Dijkstra, A. (1999) Are computer-tailored interventions more effective than standardized interventions? A critical test. Presentation at the 13th Conference of the European Society of Health Psychology, Florence, Italy.

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Background
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Background
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Self-citation
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Background
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“making behavior change more likely [8–10].”
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“This has a positive impact on their behavior change, such as quitting smoking, as some studies have already shown [56, 57].”
Result
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de Jong, S. D. J., Candel, M. J. J. M., Segaar, D., Cremers, H., & de Vries, H. (2014) · Journal of Medical Internet Research · doi:10.2196/jmir.2469 · Cited by 38
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E-Rehabilitation – an Internet and mobile phone based tailored intervention to enhance self-management of Cardiovascular Disease: study protocol for a randomized controlled trial
Antypas, K., & Wangberg, S. C. (2012) · BMC Cardiovascular Disorders · doi:10.1186/1471-2261-12-50 · Cited by 37
“Perceived tailoring will be assessed via four items from Dijkstra [42]. eHealth literacy is assessed by the eHealth Literacy Scale [43].”
Method
A Tailored Approach to Identifying and Addressing College Students’ Online Health Information Literacy
Banas, J. R. (2008) · American Journal of Health Education · doi:10.1080/19325037.2008.10599043 · Cited by 37
The PAS study: A randomized controlled trial evaluating the effectiveness of a web-based multiple tailored smoking cessation programme and tailored counselling by practice nurses
Smit, E. S., de Vries, H., & Hoving, C. (2010) · Contemporary Clinical Trials · doi:10.1016/j.cct.2010.03.001 · Cited by 36
“Feedback letters are personalized and based upon the answers provided by respondents in the questionnaires, as personalization and feedback are both shown to be working mechanisms of tailoring [26, 27].”
Background
Can tailoring increase elaboration of health messages delivered via an adaptive educational site on adolescent sexual health and decision making?
Cortese, J., & Lustria, M. L. A. (2012) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.22700 · Cited by 36
Internet based Computer Tailored Feedback on Sunscreen Use
de Vries, H., Logister, M., Krekels, G. A. M., Klaasse, F., Servranckx, V., & van Osch, L. (2012) · Journal of Medical Internet Research · doi:10.2196/jmir.1902 · Cited by 38
“Internet based, computer tailoring has shown to be effective [5,6] because of working mechanisms such as increasing personal relevance, interest, and frequency of message reading [5,7,8].”
Background
Assessing the cross-cultural applicability of tailored advertising
Masłowska, E., Smit, E. G., & van den Putte, B. (2013) · International Journal of Advertising · doi:10.2501/ija-32-4-487-511 · Cited by 35
“As Dijkstra (2005) suggested, tailoring may be effective only when it is combined with personalisation.”
Background
Health Behavior Change Support Systems as a research discipline; A viewpoint
Kelders, S. M., Oinas-Kukkonen, H., Oörni, A., & van Gemert-Pijnen, J. E. W. C. (2016) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2016.06.022 · Cited by 32
Opening the Black Box: Explaining the Process of Basing a Health Recommender System on the I-Change Behavioral Change Model
Hors-Fraile, S., Malwade, S., Luna-Perejón, F., Amaya, C., Civit, A., Schneider, F., Bamidis, P. D., Syed-Abdul, S., Li, Y., & de Vries, H. (2019) · IEEE Access · doi:10.1109/access.2019.2957696 · Cited by 32
“characteristics has been demonstrated to result in smokers’ increased attention, increased information processing abilities, increased motivation to quit, and successful quitting that can be maintained after 24 months [41], [42].”
Background
The Effectiveness of Personalized E-mail Newsletters and the Role of Personal Characteristics
Masłowska, E., van den Putte, B., & Smit, E. G. (2011) · Cyberpsychology Behavior and Social Networking · doi:10.1089/cyber.2011.0050 · Cited by 33
“2 Despite the increased focus of marketing activities on e-mail personalization 3 and growing commercial e-mail expenditures, 4 we are lacking knowledge about personalized e-mail communication.”
Mechanisms of change associated with technology-based interventions for substance use
Dallery, J., Jarvis, B. P., Marsch, L. A., & Xie, H. (2015) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2015.02.036 · Cited by 33
“Tailoring refers to three general procedures: personalization based on characteristics such as age, gender, first name; adaptation based on theory-derived constructs such as self-efficacy; and feedback based on responses to questionnaires and other interactive content (Dijkstra, 2005).”
Combining Users’ Needs With Health Behavior Models in Designing an Internet- and Mobile-Based Intervention for Physical Activity in Cardiac Rehabilitation
Antypas, K., & Wangberg, S. C. (2014) · JMIR Research Protocols · doi:10.2196/resprot.2725 · Cited by 31
“Tailoring relies on three main methods: (1) personalization, (2) adaptation, and (3) feedback [18].”
Enhancing Web-Based Kidney Disease Prevention Messages for Hispanics Using Targeting and Tailoring
Roberto, A. J., Krieger, J. L. R., & Beam, M. A. (2009) · Journal of Health Communication · doi:10.1080/10810730903089606 · Cited by 32
“More recently, studies have shown that even minimally tailored messages can be effective (Dijkstra, 2005).”
Background
Influence of Delivery Strategy on Message-Processing Mechanisms and Future Adherence to a Dutch Computer-Tailored Smoking Cessation Intervention
Stanczyk, N. E., Crutzen, R., Bolman, C. A. W., Muris, J. W. M., & de Vries, H. (2013) · Journal of Medical Internet Research · doi:10.2196/jmir.2153 · Cited by 31
“Current research has shown the superiority of tailored materials over existing standard materials [8,9].”
Background
Methodologic and Design Issues in Patient-Centered e-Health Research
Resnicow, K., Strecher, V., Couper, M., Chua, H., Little, R., Nair, V., Polk, T. A., & Atienza, A. A. (2010) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2009.09.034 · Cited by 30
Health Education and Health Promotion: Key Concepts and Exemplary Evidence to Support Them
de Vries, H., Kremers, S., & Lippke, S. (2018) · Springer eBooks · doi:10.1007/978-0-387-93826-4_17 · Cited by 39
Optimizing Text Messages to Promote Engagement With Internet Smoking Cessation Treatment: Results From a Factorial Screening Experiment
Graham, A. L., Papandonatos, G. D., Jacobs, M. A., Amato, M. S., Cha, S., Cohn, A. M., Abroms, L. C., & Whittaker, R. (2020) · Journal of Medical Internet Research · doi:10.2196/17734 · Cited by 29
“Personalization can increase smokers’ attention to written information and the perceived quality of that information [23,24] and is a desired and expected feature of text messaging [25].”
Background
The persuasive effects of personalization through: name mentioning in a smoking cessation message
Dijkstra, A. (2014) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-014-9147-x · Cited by 32
“For example, Dijkstra (2005) tested information in which the recipient’s name was mentioned, but also the number cigarettes smoked, the number of years smoked, and the type of cigarettes.”
MethodSelf-citation
Tribal Recommendations for Designing Culturally Appropriate Technology-based Sexual Health Interventions Targeting Native Youth in the Pacific Northwest
Rushing, S. C. (2012) · American Indian and Alaska Native Mental Health Research · doi:10.5820/aian.1901.2012.76 · Cited by 29
Self-endorsing in digital advertisements: Using virtual selves to persuade physical selves
Ahn, S. J., Phua, J., & Shan, Y. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.01.045 · Cited by 29
Identifying the Most Autonomy-Supportive Message Frame in Digital Health Communication: A 2x2 Between-Subjects Experiment
Smit, E. S., Zeidler, C., Resnicow, K., & de Vries, H. (2019) · Journal of Medical Internet Research · doi:10.2196/14074 · Cited by 28
“As such, tailored health communication interventions have been found to be more successful in attracting and keeping the receiver’s attention [16,17] and in achieving effortful processing of information [18] when compared with nontailored interventions.”
The association between sociodemographic and clinical characteristics and poor glycaemic control: a longitudinal cohort study
McBrien, K., Manns, B., Hemmelgarn, B. R., Weaver, R. G., Edwards, A. L., Ivers, N. M., Rabi, D. M., Lewanczuk, R. Z., Braun, T., Naugler, C. T., et al. (2015) · Diabetic Medicine · doi:10.1111/dme.13023 · Cited by 26
Optimising text messaging to improve adherence to web-based smoking cessation treatment: a randomised control trial protocol
Graham, A. L., Jacobs, M. A., Cohn, A. M., Cha, S., Abroms, L. C., Papandonatos, G. D., & Whittaker, R. (2016) · BMJ Open · doi:10.1136/bmjopen-2015-010687 · Cited by 26
THRIVE study protocol: a randomized controlled trial evaluating a web-based app and tailored messages to improve adherence to adjuvant endocrine therapy among women with breast cancer
Paladino, A. J., Anderson, J. N., Krukowski, R. A., Waters, T. M., Koçak, M., Graff, J. C., Blue, R., Jones, T. N., Buzaglo, J. S., Vidal, G. A., et al. (2019) · BMC Health Services Research · doi:10.1186/s12913-019-4588-x · Cited by 28
Behavioral economics and diabetic eye exams
Williams, A. M., Liu, P. J., Muir, K. W., & Waxman, E. L. (2018) · Preventive Medicine · doi:10.1016/j.ypmed.2018.04.006 · Cited by 25
Web-based interventions to decrease alcohol use in adolescents: a Delphi study about increasing effectiveness and reducing drop-out
Jander, A., Crutzen, R., Mercken, L. A. G., & de Vries, H. (2015) · BMC Public Health · doi:10.1186/s12889-015-1639-z · Cited by 24
“Personalization and feedback have been shown to be effective working mechanisms of CT interventions [26].”
Background
Effect of a Counseling Session Bolstered by Text Messaging on Self-Selected Health Behaviors in College Students: A Preliminary Randomized Controlled Trial
Sandrick, J., Tracy, D., Eliasson, A. H., Roth, A., Bartel, J. S., Simko, M., Bowman, T., Harouse-Bell, K., Kashani, M., & Vernalis, M. (2017) · JMIR mhealth and uhealth · doi:10.2196/mhealth.6638 · Cited by 24
Evaluation of QuitNow Men: An Online, Men-Centered Smoking Cessation Intervention
Bottorff, J. L., Oliffe, J. L., Sarbit, G., Sharp, P., Caperchione, C. M., Currie, L. M., Schmid, J., Mackay, M., & Stolp, S. (2016) · Journal of Medical Internet Research · doi:10.2196/jmir.5076 · Cited by 23
“Furthermore, given the tailored nature of the QuitNow Men smoking cessation website and that it caters to the specific values of a particular population (ie, men) [37-39], it has the potential to attract, engage, and retain men interested in quitting smoking.”
Background
Health information, behavior change, and decision support for patients with type 2 diabetes: development of a tailored, preference-sensitive health communication application
Weymann, N., Härter, M. C., Petrak, & Dirmaier, J. (2013) · Patient Preference and Adherence · doi:10.2147/ppa.s46924 · Cited by 22
“Further studies support the effectiveness of these three strategies.(43,44)”
Result
A case series of an off-the-shelf online health resource with integrated nurse coaching to support self-management in COPD
Early, F. H., Young, J., Robinshaw, E., Mi, E., Mi, E., & Fuld, J. P. (2017) · International Journal of COPD · doi:10.2147/copd.s139532 · Cited by 29
Personalization in Digital Psychological Interventions for Young Adults
Jahedi, F., Henman, P. W. F., & Ryan, J. C. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2158261 · Cited by 24
“Personalization has been shown to reduce users ’ cognitive load, increase persuasion (Dijkstra, 2005; Hawkins et al., 2008) and enhance user satisfaction, which can improve the effectiveness of tailored versus non-tailored health behavior interventions (Lustria et al., 2013; Thakkar et al., 2016).”
Background
A Microsoft Kinect-Based Virtual Rehabilitation System to Train Balance Ability for Stroke Patients
Lai, C.-L., Huang, Y., Liao, T.-K., Tseng, C.-M., Chen, Y.-F., & Erdenetsogt, D. (2015) · International Conference on Cyberworlds (CW) · doi:10.1109/cw.2015.44 · Cited by 21
“Furthermore, a computer-tailor intervention with feedback and personalization was reported to be promising in increasing intervention effectiveness [20].”
Background
Examining the minimal required elements of a computer-tailored intervention aimed at dietary fat reduction: results of a randomized controlled dismantling study
Kroeze, W., Oenema, A., Dagnelie, P. C., & Brug, J. (2007) · Health Education Research · doi:10.1093/her/cym075 · Cited by 20
Tailored Communications for Health-Related Decision-Making and Behavior Change
Noar, S. M., & Harrington, N. G. (2016) · Springer eBooks · doi:10.1007/978-1-4939-3486-7_18 · Cited by 20
Living is Easy With Eyes Closed: Avoidance of Targeted Political Advertising in Response to Privacy Concerns, Perceived Personalization, and Overload
Stubenvoll, M., Binder, A., Noetzel, S., Hirsch, M., & Matthes, J. (2022) · Communication Research · doi:10.1177/00936502221130840 · Cited by 20
“We measured perceived personalization with 2 items that were based on Dijkstra (2005) and adapted to the context of targeting.”
Method
Evaluation of a real-time virtual intervention to empower persons living with HIV to use therapy self-management: study protocol for an online randomized controlled trial
Côté, J., Godin, G., Guéhéneuc, Y., Rouleau, G., Ramirez-Garcìa, P., Otis, J., Tremblay, C. L., & Fadel, G. (2012) · Trials · doi:10.1186/1745-6215-13-187 · Cited by 20
“This makes it possible to achieve more significant results as the person feels more engaged by the messages and in turn engages more readily in the proposed strategies [38-40].”
Background
Effects of Program Exposure and Engagement With Tailored Prevention Communication on Sun Protection by Young Adolescents
Reynolds, K. D., Buller, D. B., Yaroch, A. L., Maloy, J. A., Geno, C. R., & Cutter, G. (2008) · Journal of Health Communication · doi:10.1080/10810730802412149 · Cited by 19
“Tailored messages have improved diet, tobacco prevention, physical activity, mammography use, and headache prevention with adults when compared with both untailored communication and no communication (Brinberg, Axelson, & Price, 2000; Dijkstra, 2005; Jacobs et al., 2004; Lauver, Settersten, Kane, & Henriques, 2003; Ni…”
Background
Results of the PAS Study: A Randomized Controlled Trial Evaluating the Effectiveness of a Web-Based Multiple Tailored Smoking Cessation Program Combined With Tailored Counseling by Practice Nurses
Smit, E. S., Candel, M. J. J. M., Hoving, C., & de Vries, H. (2016) · Health Communication · doi:10.1080/10410236.2015.1049727 · Cited by 19
‘It’s my virtual space’: the effect of personalized advertising within social media
Kim, J., & Jeong, H. J. (2023) · International Journal of Advertising · doi:10.1080/02650487.2023.2274243 · Cited by 22
“For a manipulation check, the level of personalization was measured using the same six items employed in Study 1 (McMillan and Hwang 2002; Dijkstra 2005) (α = .937).”
Method

Authors: Dijkstra, A.
Affiliations: University of Groningen (NL)
Corresponding author: Dijkstra, Arie
ORCID: Dijkstra, Arie
Venue: Health Education Research
Publisher: Oxford University Press (OUP)
Published: 2004-02-08
Volume: 20
Issue: 5
Pages: 527-539
ISSN: 0268-1153 (ISSN-L)
1465-3648
DOI: 10.1093/her/cyh014
OpenAlex: W2100836598
Cited by: 193
References: 23
Citations by year: 2026: 2 · 2025: 5 · 2024: 5 · 2023: 7 · 2022: 10 · 2021: 6 · 2020: 7 · 2019: 8 · 2018: 7 · 2017: 10 · 2016: 16 · 2015: 13 · 2014: 17 · 2013: 15 · 2012: 15
FWCI: 1.85
Type: journal article
Language: en
Open access: closed
Locations: Health Education Research (publishedVersion)
PubMed (publishedVersion)
University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion)
University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion)
Topics: Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Smoking Behavior and Cessation
Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
Social Sciences › Communication › Media Influence and Health
Keywords: smoking cessation, operating mechanism, personalization, adaptation, feedback, students, tobacco use, quitting behavior
MeSH terms: Adult, Communication, Computer-Assisted Instruction, Female, Health Education, Humans, Male, Netherlands, Surveys and Questionnaires, Smoking Cessation

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Working mechanisms of computer-tailored health education: evidence from smoking cessation

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