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. 2013 Aug 19;15(8):e170.
doi: 10.2196/jmir.2566.

Usage of a generic web-based self-management intervention for breast cancer survivors: substudy analysis of the BREATH trial

Sanne W van den Berg  1 , Esmee J Peters, J Frank Kraaijeveld, Marieke F M Gielissen, Judith B Prins
Affiliations

Usage of a generic web-based self-management intervention for breast cancer survivors: substudy analysis of the BREATH trial

Sanne W van den Berg et al. J Med Internet Res. .

Abstract

Background: Generic fully automated Web-based self-management interventions are upcoming, for example, for the growing number of breast cancer survivors. It is hypothesized that the use of these interventions is more individualized and that users apply a large amount of self-tailoring. However, technical usage evaluations of these types of interventions are scarce and practical guidelines are lacking.

Objective: To gain insight into meaningful usage parameters to evaluate the use of generic fully automated Web-based interventions by assessing how breast cancer survivors use a generic self-management website. Final aim is to propose practical recommendations for researchers and information and communication technology (ICT) professionals who aim to design and evaluate the use of similar Web-based interventions.

Methods: The BREAst cancer ehealTH (BREATH) intervention is a generic unguided fully automated website with stepwise weekly access and a fixed 4-month structure containing 104 intervention ingredients (ie, texts, tasks, tests, videos). By monitoring https-server requests, technical usage statistics were recorded for the intervention group of the randomized controlled trial. Observed usage was analyzed by measures of frequency, duration, and activity. Intervention adherence was defined as continuous usage, or the proportion of participants who started using the intervention and continued to log in during all four phases. By comparing observed to minimal intended usage (frequency and activity), different user groups were defined.

Results: Usage statistics for 4 months were collected from 70 breast cancer survivors (mean age 50.9 years). Frequency of logins/person ranged from 0 to 45, total duration/person from 0 to 2324 minutes (38.7 hours), and activity from opening none to all intervention ingredients. 31 participants continued logging in to all four phases resulting in an intervention adherence rate of 44.3% (95% CI 33.2-55.9). Nine nonusers (13%), 30 low users (43%), and 31 high users (44%) were defined. Low and high users differed significantly on frequency (P<.001), total duration (P<.001), session duration (P=.009), and activity (P<.001). High users logged in an average of 21 times, had a mean session duration of 33 minutes, and opened on average 91% of all ingredients. Signing the self-help contract (P<.001), reporting usefulness of ingredients (P=.003), overall satisfaction (P=.028), and user friendliness evaluation (P=.003) were higher in high users. User groups did not differ on age, education, and baseline distress.

Conclusions: By reporting the usage of a self-management website for breast cancer survivors, the present study gained first insight into the design of usage evaluations of generic fully automated Web-based interventions. It is recommended to (1) incorporate usage statistics that reflect the amount of self-tailoring applied by users, (2) combine technical usage statistics with self-reported usefulness, and (3) use qualitative measures. Also, (4) a pilot usage evaluation should be a fixed step in the development process of novel Web-based interventions, and (5) it is essential for researchers to gain insight into the rationale of recorded and nonrecorded usage statistics.

Trial registration: Netherlands Trial Register (NTR): 2935; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=2935 (Archived by WebCite at http://www.webcitation.org/6IkX1ADEV).

Keywords: Internet; Web-based intervention; breast cancer; exposure; intervention adherence; log file analysis; usage evaluation; usage statistics; user groups; website use.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Continuous usage and intermittent usage based on logins during 4 intervention phases (n=70).
Figure 2
Figure 2
Distribution of total opened intervention ingredients per participants (n=70).
See this image and copyright information in PMC

References

    1. Jemal A, Bray F, Center MM, Ferlay J, Ward E, Forman D. Global cancer statistics. CA Cancer J Clin. 2011;61(2):69–90. doi: 10.3322/caac.20107. http://dx.doi.org/10.3322/caac.20107 - DOI - DOI - PubMed
    1. Cappiello M, Cunningham RS, Knobf MT, Erdos D. Breast cancer survivors: information and support after treatment. Clin Nurs Res. 2007 Nov;16(4):278–93; discussion 294. doi: 10.1177/1054773807306553. - DOI - PubMed
    1. Afshari M, Ghani MFA, Radzi NM. Use of the internet by breast cancer patients. Sci Res Essays. 2011;6(17):1992–2248.
    1. Eysenbach G. The impact of the Internet on cancer outcomes. CA Cancer J Clin. 2003;53(6):356–71. - PubMed
    1. Fogel J, Albert SM, Schnabel F, Ditkoff BA, Neugut AI. Use of the Internet by women with breast cancer. J Med Internet Res. 2002;4(2):E9. doi: 10.2196/jmir.4.2.e9. http://www.jmir.org/2002/2/e9/ - DOI - PMC - PubMed

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