How do different delivery schedules of tailored web-based physical activity advice for breast cancer survivors influence intervention use and efficacy?
- 531 Downloads
The purpose of the study is to investigate the impact of differing delivery schedules of computer-tailored physical activity modules on engagement and physical activity behaviour change in a web-based intervention targeting breast cancer survivors.
Insufficiently active breast cancer survivors (n = 492) were randomly assigned to receive one of the following intervention schedules over 12 weeks: a three-module intervention delivered monthly, a three-module intervention delivered weekly or a single module intervention. Engagement with the website (number of logins, time on site, modules viewed, action plans completed) was measured using tracking software. Other outcomes (website acceptability, physical activity behaviour) were assessed using online surveys. Physical activity outcomes were analysed using regression models for both study completers and when applying intention-to-treat (using multiple imputation).
Completers allocated to the monthly module group rated the intervention higher (b = 2.2 95 % CI = 0.02–4.53) on acceptability and had higher levels of resistance-training (IRR = 1.88, 95 % CI = 1.16–3.04) than those in the single module group. When accounting for missing data, these differences were no longer significant. The completion of at least two action plans was higher among those allocated to the monthly module group compared to those in the weekly module group (53 vs 40 %, p = 0.02); though the completion of at least two modules was higher in the weekly module group compared to the monthly module group (60 vs 46 %; p = 0.01). There were no other significant between group differences observed.
This study provides preliminary evidence that web-based computer-tailored interventions can be used to increase physical activity among breast cancer survivors. Further, there were some outcome differences based on how the tailored modules were delivered, with the most favourable outcomes observed in the monthly delivery group.
Implications for Cancer Survivors
This study will be useful for informing the design of future web-based interventions targeting breast cancer survivors.
KeywordsPhysical activity eHealth Cancer Behaviour change
The authors thank Catherine Coysh for her assistance with the project and feedback on the manuscript. CES is supported by an Early Career Fellowship (ID 1090517) from the National Health and Medical Research Council. ALR is supported by an Early Career Fellowship (ID1105926) from the National Health Medical Research Council. KSC is supported by the Canada Research Chairs Program. RCP is supported by a Research Fellowship from the National Health and Medical Research Council. CV is supported by a Future Leader Fellowship from the National Heart Foundation of Australia (ID 100427). MJD is supported by a Future Leader Fellowship (ID 100029) from the National Heart Foundation of Australia.
Compliance with ethical standards
CES is supported by an Early Career Fellowship (ID 1090517) from the National Health and Medical Research Council. ALR is supported by an Early Career Fellowship (ID1105926) from the National Health Medical Research Council. KSC is supported by the Canada Research Chairs Program. RCP is supported by a Research Fellowship from the National Health and Medical Research Council CV is supported by a Future Leader Fellowship from the National Heart Foundation of Australia (ID 100427). MJD is supported by a Future Leader Fellowship (ID 100029) from the National Heart Foundation of Australia.
Conflict of interest
All authors declare that they have no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
- 5.Rock, C.L., et al., Nutrition and physical activity guidelines for cancer survivors. CA: a Cancer Journal for Clinicians, 2012: p. n/a-n/a.Google Scholar
- 12.Australian Institute of Health and Welfare, Breast cancer in Australia: an overview 2012, AIHW: Canberra.Google Scholar
- 15.Short CE et al. Designing engaging online behaviour change interventions: a proposed model of user engagement. The European Health Psychologist. 2015;17(1):32–8.Google Scholar
- 17.Wolfenden, L., N. Nathan, and C.M. Williams, Computer-tailored interventions to facilitate health behavioural change. British Journal of Sports Medicine, 2014.Google Scholar
- 21.Oinas-Kukkonen, H. and M. Harjumaa, Persuasive Systems Design: Key Issues, Process Model, and System Features. Communications of the Association for Information Systems. 2009. 24(28):485–500.Google Scholar
- 24.Australian Government- Department of Health. Australia's Physical Activity and Sedentary Behaviour Guidelines 2014 [cited 2014 18/08/14]; Available from: http://www.health.gov.au/internet/main/publishing.nsf/content/health-pubhlth-strateg-phys-act-guidelines.
- 26.Short CE, James E, Plotnikoff RC. Theory-and evidence-based development and process evaluation of the move more for life program: a tailored-print intervention designed to promote physical activity among post-treatment breast cancer survivors. International Journal of Behavioural Nutrition and Physical Activity. 2013;10:124.CrossRefGoogle Scholar
- 27.Short, C.E., James, E.L, Girgis, A., D’Souza, M.I, Main outcomes of the Move More for Life Trial: a randomised controlled trial examining the effects of tailored-print and targeted-print materials for promoting physical activity among post-treatment breast cancer survivors, 2015, 24(7):p 771–778.Google Scholar
- 31.Crutzen, R. and G.-J.Y. Peters, Scale quality: alpha is an inadequate estimate and factor-analytic evidence is needed first of all. Health Psychology Review. 2015. doi: 10.1080/17437199.2015.1124240.
- 33.Brooke, J., SUS: A “quick and dirty” usability scale. Usability Evaluation in Industry (1996), London: Taylore & Francis.Google Scholar
- 35.Kirakowski J, Corbett M. Measuring user satisfaction. People and computers. Cambridge: Cambridge University Press; 1998.Google Scholar
- 38.Godin G, Shepard R. Godin leisure-time exercise questionnaire. Med Sci Sports Exerc. 1997;29(6):36–8.Google Scholar
- 39.Australian Bureau of Statistics, Household income and income distribution, Australia, 2011–2012. 2013.Google Scholar
- 42.White IR et al. Strategy for intention to treat analysis in randomised trials with missing outcome data. Br Med J. 2011;7:342.Google Scholar
- 44.R Core Team, R: A language and environment for statistical computing. R Foundation for Statistical Computing. 2015: Vienna, Austria. URL http://www.R-project.org/.
- 45.StataCorp., Stata Statistical Software: Release 11. 2009: College Station, TX: StataCorp LP.Google Scholar