This study evaluated the effectiveness of Active-Online, a web-based physical activity intervention, compared to a non-tailored website. Over 1500 participants were randomized into a control, intervention, or spontaneous user group. The intervention and spontaneous user groups had access to Active-Online and received tailored advice and feedback. While all groups self-reported increased activity levels over time, there were no significant differences between the randomized groups. Spontaneous users showed more pronounced increases in activity levels. However, frequency and duration of Active-Online use did not clearly impact behavior changes. The study had methodological limitations including high attrition rates, unequal groups, and contamination of the control group.

1. Presentation by
CATCH-IT Health Informatics Journal
Club
Presentation by
Lamia Chowdhury
November 16, 2009

2. Effectiveness of Active-Online: An
Individually Tailored Physical Activity
Intervention, in a Real-Life Setting:
RCT
Wanner M., Martin-Diener E., Braun-Fahrländer C., Bauer
G., Martin B.W. (2009)
Journal of Medical Internet Research, 11 (3): e23.
2

3. Outline
Why this paper
About the Authors
Summary of Study and Findings
Methodological Issues
Validity & Usefulness of ResultsValidity & Usefulness of Results
Further Research
Questions for theAuthors
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4. Why I chose this paper
Randomized ControlledTrial
Attrition
Chronic disease and Inactive lifestyles
Internet surfing and health?
Public Health
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Public Health
Physicians, trainers
Vendors

5. About the Authors
MiriamWanner
Institute of Social and Preventive Medicine, University of Basel,
Switzerland
Swiss Federal Institute of Sport, Magglingen, Switzerland
Publications
5
Publications
Citations

6. Publications & CitationsPublications & CitationsPublications & CitationsPublications & Citations
-JMIR
6
• JMIR
• Swiss Journal for Sports Medicine and Sports Medicine

7. Study Objectives
To evaluate the effectiveness of Active-Online
Web –based, tailored physical activity intervention
Freely accessible on the Internet
Tested for acceptability and feasibility before going live in 2003
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Aim is to increase physical activity levels in users by
offering individually tailored counselling and
motivational feedback

8. 1. How effective is Active-Online, compared
to a non-tailored website,in increasing self-
reported and objectively measured physical
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reported and objectively measured physical
activity levels when delivered in a real-life
setting?

9. 2. Do respondents recruited for the
randomized study differ from spontaneous
users of Active-Online, and does
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users of Active-Online, and does
effectiveness differ between these groups?

10. 3. What is the impact of frequency and
duration of use of Active-Online on changes
in physical activity behaviour?
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in physical activity behaviour?

11. Originality of the Study
Study claims only one other similar study exists
Spittaels H, et al. (2007) Effectiveness of an online computer-tailored
physical activity intervention in a real-life setting. Health Educ Res,22(3):385-
396
Spittaels H, et al. (2007) Evaluation of a website-delivered computer-
tailored intervention for increasing physical activity in the general
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tailored intervention for increasing physical activity in the general
population. Prev Med 44(3):209-217.
Most other studies investigating the effectiveness of web-
based tailored physical activity interventions have
been carried out in small populations in controlled settings
looked at short term effects

12. Originality of Study
Sternfeld et al. (2009) Improving Diet and PhysicalActivity
withALIVE.AWorksite RandomizedTrial. American
Journal of Preventive Medicine 36 (6), pp. 475-483
Slootmaker, S. et al. (2009) Feasibility and effectiveness of
online physical activity advice based on a personal
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online physical activity advice based on a personal
activity monitor: randomized controlled trial. Journal
of Medical Internet research 11 (3), pp. e27

13. Methods
Participants recruited through ads in
newspapers, magazines, Internet
Active-Online website
Three study groups
Control (CG), Intervention (IG), Spontaneous Users (SU)
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Control (CG), Intervention (IG), Spontaneous Users (SU)
IG and SU Active-Online
CG Static website
Follow-up (FU) at 6 weeks, 6 months, 13 months

14. Results
n CG IG SU
Total 688 681 162
Responded to all FU 399 (58%) 289 (42.4%) 59 (36.4%)
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15. 1. How effective is Active-Online, compared
to a non-tailored website,in increasing self-
reported and objectively measured physical
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reported and objectively measured physical
activity levels when delivered in a real-life
setting?

16. Significant increase in self-reported physical
activity levels between baseline and last FU
for all groups, but no significant differences
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for all groups, but no significant differences
between randomized groups.

17. 2. Do respondents recruited for the
randomized study differ from spontaneous
users of Active-Online, and does
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users of Active-Online, and does
effectiveness differ between these groups?

18. Yes.
SU have a more pronounced increase in
activity levels.
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activity levels.
However, these users are not randomized—they are self-selected and
account for only 7.4% of total visits to Active-Online.

19. 3. What is the impact of frequency and
duration of use of Active-Online on changes
in physical activity behaviour?
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in physical activity behaviour?

20. Not clear.
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Not clear.

21. Methodological Issues—The Good
Sufficient scientific background for study
Computer-randomized groups
Detailed description of data collection
Specific objectives and questions
Clearly defined outcome measures, statistical analyses,
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Clearly defined outcome measures, statistical analyses,
recruitment and follow-up dates, baseline demographics,
Power calculation to determine sample size, allowing for
attrition
Participant flow diagram included, all participants accounted
for
Acknowledges limited effectiveness of the system

22. Methodological Issues—The Bad
Participant eligibility criteria not explicit
Settings and locations of data collection unclear
Study not blinded—study personnel could identify participants
groups through email addresses
Survey and questionnaire sample not provided
Trial not registered
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Trial not registered
Justification of spontaneous user-group not clear
All groups not equal
Admits to contamination of control group
Attrition rate >50%
Out-dated website design and theoretical framework
(transtheoretical model of behaviour change)
Validity of time-stamp calculating frequency of use
Participants already had high levels of physical activity

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24. Validity and Usefulness of Results
Participants were highly selective—only those with Internet
access and competence
Real-life setting—too many uncontrolled factors
Conclusion is nothing new
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Usefulness to stakeholders
Family physicians
Trainers
Public health officials
Vendors

25. Further Research
Integrate web-based interventions in a wider health
promotion context
Primary care setting
Workplace setting
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26. Summary of Issues
Pitfalls of a real-life setting
Contamination of control group
Attrition
Unequal participant groups
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Unequal participant groups

27. Questions for the Authors
Were the three groups following similar exercise routines?
How do you account for contamination of CG in Internet-based
studies? Could CG have accessedActive-Online as SU (using a
different email address perhaps)?
What were the technical difficulties causing 38 participants to be
omitted from the study?
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Could study results be affected by incentives?
What was the point of having SU?
How to validate uniqueness of participants?
What was the reason for not measuring usage of non-tailored
website?
Why did the total reported activity of those meeting HEPA at
baseline decrease at FU3?

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