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Factors Associated With Engagement With a Web-Based Lifestyle Intervention Following Provision of Coronary Heart Disease Risk: Mixed Methods Study

Overview of attention for article published in Journal of Medical Internet Research, October 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Average Attention Score compared to outputs of the same age and source

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1 policy source
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10 X users
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Citations

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8 Dimensions

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78 Mendeley
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Title
Factors Associated With Engagement With a Web-Based Lifestyle Intervention Following Provision of Coronary Heart Disease Risk: Mixed Methods Study
Published in
Journal of Medical Internet Research, October 2017
DOI 10.2196/jmir.7697
Pubmed ID
Authors

Juliet A Usher-Smith, Laura R Winther, Guy S Shefer, Barbora Silarova, Rupert A Payne, Simon J Griffin

Abstract

Web-based interventions provide the opportunity to combine the tailored approach of face-to-face interventions with the scalability and cost-effectiveness of public health interventions. This potential is often limited by low engagement. A number of studies have described the characteristics of individuals who engage more in Web-based interventions but few have explored the reasons for these variations. We aimed to explore individual-level factors associated with different degrees of engagement with a Web-based behavior change intervention following provision of coronary heart disease (CHD) risk information, and the barriers and facilitators to engagement. This study involved the secondary analysis of data from the Information and Risk Modification Trial, a randomized controlled trial of a Web-based lifestyle intervention alone, or alongside information on estimated CHD risk. The intervention consisted of three interactive sessions, each lasting up to 60 minutes, delivered at monthly intervals. Participants were characterized as high engagers if they completed all three sessions. Thematic analysis of qualitative data from interviews with 37 participants was combined with quantitative data on usage of the Web-based intervention using a mixed-methods matrix, and data on the views of the intervention itself were analyzed across all participants. Thirteen participants were characterized as low engagers and 24 as high engagers. There was no difference in age (P=.75), gender (P=.95), or level of risk (P=.65) between the groups. Low engagement was more often associated with: (1) reporting a negative emotional reaction in response to the risk score (P=.029), (2) perceiving that the intervention did not provide any new lifestyle information (P=.011), and (3) being less likely to have reported feeling an obligation to complete the intervention as part of the study (P=.019). The mixed-methods matrix suggested that there was also an association between low engagement and less success with previous behavior change attempts, but the statistical evidence for this association was weak (P=.16). No associations were seen between engagement and barriers or facilitators to health behavior change, or comments about the design of the intervention itself. The most commonly cited barriers related to issues with access to the intervention itself: either difficulties remembering the link to the site or passwords, a perceived lack of flexibility within the website, or lack of time. Facilitators included the nonjudgmental presentation of lifestyle information, the use of simple language, and the personalized nature of the intervention. This study shows that the level of engagement with a Web-based intervention following provision of CHD risk information is not influenced by the level of risk but by the individual's response to the risk information, their past experiences of behavior change, the extent to which they consider the lifestyle information helpful, and whether they felt obliged to complete the intervention as part of a research study. A number of facilitators and barriers to Web-based interventions were also identified, which should inform future interventions.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 78 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 18%
Student > Ph. D. Student 11 14%
Student > Master 9 12%
Student > Doctoral Student 7 9%
Student > Bachelor 7 9%
Other 6 8%
Unknown 24 31%
Readers by discipline Count As %
Psychology 14 18%
Medicine and Dentistry 12 15%
Nursing and Health Professions 8 10%
Business, Management and Accounting 5 6%
Agricultural and Biological Sciences 3 4%
Other 7 9%
Unknown 29 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 June 2022.
All research outputs
#4,209,172
of 25,382,440 outputs
Outputs from Journal of Medical Internet Research
#3,104
of 7,867 outputs
Outputs of similar age
#70,529
of 335,261 outputs
Outputs of similar age from Journal of Medical Internet Research
#54
of 90 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,867 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.8. This one has gotten more attention than average, scoring higher than 60% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 335,261 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 90 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.