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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 (
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.
Noncommunicable diseases have now overtaken communicable diseases in causing the greatest disease burden worldwide, with coronary heart disease (CHD) being the number one cause of disability-adjusted life years globally [
With the expanse and scope of the Internet, 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, and are potentially appealing to the public because they are convenient and easily accessible [
A number of quantitative studies have described the characteristics of individuals who engage more in Web-based behavior change interventions. The findings have been mixed, with one study finding no association between website use and clinical and sociodemographic variables [
A number of behavior change theories additionally suggest that lifestyle interventions will only be successful if individuals perceive themselves to be at risk of developing the target disease [
The Information and Risk Modification (INFORM) Trial [
This study is a secondary analysis of data collected as part of the INFORM trial. Details of that trial are reported elsewhere [
The Web-based lifestyle advice was based on an intervention originally developed for the Heart to Health study, which was shown to be effective in a randomized controlled trial [
Face-to-face interviews with a purposive sample of 41 participants were conducted as part of the INFORM trial by an experienced qualitative researcher (GS). Full details of the recruitment and methods are reported in detail elsewhere [
Quantitative data on usage of the Web-based intervention was collected by tracking which pages participants had accessed during the trial. Participants were considered high engagers with the website if they completed all three sessions for either diet, physical activity, or smoking, and low engagers if they did not. Student’s t-tests or Chi-squared tests were used to assess differences between the high and low engagers with significance set at
We first used thematic analysis [
Once coding was complete, we combined the qualitative data with the quantitative data in a mixed-methods matrix with one row for each of the 37 participants. Data on the level of website engagement was used to divide participants based on whether they were low or high engagers and Chi-square tests were used to test associations. After identifying themes associated with engagement with the website from this matrix, we then returned to the qualitative data to explore those themes in greater depth. Data on the views of the intervention itself were also analyzed separately across all participants using thematic analysis.
The characteristics of the 37 participants are described in
Using the quantitative data from the website, 13 participants were characterized as low engagers and 24 as high engagers. There was no difference in age (
Low engagement with the website was more often associated with: (1) reporting a negative emotional reaction to the risk score (
Characteristics of participants.
Participant characteristic | n=37 | |
Male | 23 | |
Female | 14 | |
40-49 | 5 | |
50-59 | 14 | |
60-69 | 13 | |
70-80 | 5 | |
Phenotypic risk + genetic risk + lifestyle advice | 22 | |
Phenotypic risk + lifestyle advice | 15 | |
Married | 26 | |
Separated or divorced | 3 | |
Widowed | 3 | |
Single | 5 | |
No formal education | 1 | |
Secondary education (to age 18) | 17 | |
University education | 19 | |
Less than £8000 | 1 | |
Between £8001-40,000 | 13 | |
More than £40,000 | 19 | |
Did not know or did not answer | 4 | |
<5% | 11 | |
5-10% | 14 | |
10-20% | 9 | |
>20% | 3 |
Mixed-methods matrix ordered according to the level of website engagement, where dots indicate the presence of that theme within the qualitative interview data.
Level of |
Participant |
Response to risk information | Previous behavior change attempts | Views of the |
|||||
ID | Age | Sex | Negative emotional reaction | Unsuccessful | Successful | No new information | Felt obliged to |
||
Low engagers | 9 | 73 | F | ● | |||||
12 | 69 | M | ● | ● | ● | ||||
13 | 64 | M | ● | ||||||
15 | 56 | M | ● | ● | ● | ||||
19 | 75 | F | ● | ||||||
22 | 59 | M | ● | ● | |||||
24 | 55 | M | ● | ● | ● | ||||
25 | 67 | M | ● | ● | |||||
26 | 44 | F | ● | ● | ● | ||||
27 | 54 | F | ● | ● | ● | ||||
30 | 56 | M | ● | ● | |||||
31 | 44 | F | ● | ● | |||||
33 | 59 | M | ● | ● | |||||
High engagers | 1 | 64 | M | ● | |||||
2 | 70 | M | |||||||
3 | 57 | M | ● | ||||||
4 | 59 | F | ● | ||||||
5 | 72 | M | ● | ● | ● | ||||
6 | 63 | F | ● | ||||||
7 | 57 | M | ● | ● | ● | ||||
8 | 67 | M | ● | ● | |||||
10 | 68 | M | ● | ● | |||||
14 | 68 | F | |||||||
16 | 63 | M | ● | ||||||
17 | 64 | F | ● | ● | |||||
18 | 61 | M | ● | ● | |||||
20 | 49 | M | ● | ● | ● | ||||
21 | 55 | M | ● | ||||||
23 | 76 | M | ● | ● | ● | ||||
28 | 58 | M | |||||||
29 | 64 | M | ● | ● | |||||
32 | 66 | M | ● | ● | |||||
34 | 51 | F | ● | ● | ● | ● | |||
35 | 55 | F | ● | ● | ● | ||||
36 | 56 | F | ● | ● | ● | ||||
37 | 46 | F | ● | ||||||
40 | 45 | F | ● | ● | ● |
A greater proportion of low engagers described a negative emotional reaction to the risk, which was understood as expressing fear, anxiety, worry, shock, concern, or irritation when being asked during the interview to recall their feelings at the time they received the risk information. In many cases this reaction was surprise, disappointment, or worry because the risk did not match how they perceived themselves in relation to their health behavior and comparison with others:
It was a bit of a shock to be honest, because as I say, I thought that when I would get the results of that my, say, I’m 59, I know, but I thought my heart would be, or my rating would be say down much lower at 54, 55 or something like that...’cos of the amount of exercise I do and, you know, my weight I think is about right and I’m, I don’t get ill at all and fortunately I haven’t got any, you know, any long-term health problems.
In some cases, particularly amongst those participants who did not fully understand the risk information, this led to confusion, irritation, or annoyance.
Yeah, it was [confusing] actually, because it just came, it didn’t explain why it would be that way so I mean I did, I haven’t angst, I haven’t sort of lost sleep over it but I did kind of think why basically, why should it be that way? The percentages were pretty much the same which seemed bizarre given the differential on the age thing.
By comparison, several high engagers had also felt irritated, surprised, or concerned by receiving risk scores higher than they had expected but, unlike the low engagers, described acceptance of the score as a reasonable assessment.
Useful and concerned ’cos I think 60, a heart age of 69 is significantly greater than I would like it to be, so that’s why I read on all the material about diet and exercise because I wanted to see if I could do something about it.
Notably all of the low engagers reported that the intervention did not provide any new lifestyle information.
Whilst many of the high engagers also felt there was little new lifestyle information, some of those nevertheless considered that the intervention was still helpful as it presented the lifestyle information differently or reinforced their prior knowledge.
No [I did not learn anything new], I think I was aware of it, but it’s when, you know, you see it linked up, because you, so much information comes out about diet, food, and it does change quite regularly, sometimes it’s difficult, it is difficult to try and keep up with everything.
A further theme associated with level of engagement was the finding that many of the high engagers had completed all three sessions partly for the purpose of the study. For these participants, any reactions they had to the risk information or views about the intervention were superseded by a desire to “do what they had been told” or committed to.
I thought having been asked to do it you know, I’d religiously go through it and make sure you know, I’d covered all the elements.
Although not statistically significant, the final theme found amongst low engagers related to prior experiences of behavior change. Compared to high engagers, low engagers tended to have had more unsuccessful prior behavior change attempts and less successful experiences.
...the, the eating habit I’ve got, that’s going to be my biggest problem, I bring a banana into work and then I, five o’clock, oh, it’s still there, and I’ve walked down to the shop and got myself a roll [laughs]. So, changing that is my bigger problem, the eating part, although I have been on a diet in the past and lost nearly four stone, but then it all came back again.
Almost all participants, regardless of their level of engagement with the website, described aspects of the Web-based intervention that acted as either barriers or facilitators to use (
The most commonly cited barriers related to issues with access to the intervention itself, either due to difficulties remembering the link to the site or passwords, or a perceived lack of flexibility within the website. Several participants also felt that the lifestyle advice provided was too limited and did not include sufficient options for those already achieving the goals, or with particular likes/dislikes or medical problems. Conversely, most participants commented favorably about the content of the lifestyle information provided. For many participants, the nonpreaching and nonjudgmental presentation of the lifestyle information was an important facilitator, along with the use of simple language and inclusion of up-to-date lifestyle information from a respected source. Several individuals also described how the personalized nature of the risk and lifestyle information made them feel more engaged.
A number of participants also suggested possible additions to the intervention to improve it; these included incorporating a progress chart or tracker that would allow participants to log in and update the website with their progress whilst also providing a reason to return to the website regularly to remind them of the information, and linking it with calendar applications to allow participants to add reminders to their calendars to prompt them between the scheduled sessions.
Barriers to engagement.
Barrier | Representative quotations |
Difficulty remembering passwords | |
Difficulty getting back into the website after clicking on additional information | |
Difficulty getting back into the website for the later modules | |
Difficulty remembering all the information | |
Lack of flexibility/too prescriptive | |
Limited options for those with particular likes/dislikes, medical problems or already achieving the goals |
Facilitators to engagement.
Facilitator | Representative quotations |
Nonpreaching nature of lifestyle information | |
Nonjudgmental | |
Links to further information | |
Simple language | |
Easy to navigate | |
Up to date information from |
|
Personalized | |
Reminder emails |
Using a mixed-methods approach, this study demonstrates that lower engagement with a Web-based lifestyle intervention following provision of an estimate of 10-year CHD risk was associated with reporting a negative emotional reaction to the risk score, perceiving that the intervention did not provide any helpful lifestyle information, being less likely to have reported feeling an obligation to complete the intervention as part of the study and less success with prior experiences of behavior change attempts. No associations were seen between engagement with the website and the level of CHD risk or reported barriers or facilitators to health behavior change. The most commonly cited barriers to engagement were difficulty accessing the website, a perceived lack of flexibility within the website, and lack of time. Facilitators included the nonjudgmental presentation of lifestyle information, the use of simple language, and the personalized nature of the intervention.
A key strength of this study is the use of a mixed-methods approach to explore associations between participants’ views expressed during the qualitative interviews and their engagement with a Web-based intervention. Unlike previous studies which have focused on differences in the clinical and sociodemographic characteristics of individuals [
However, the findings must be interpreted with consideration of the limitations of the study. The main limitation is that the participants were a small purposive sample selected from blood donors already taking part in another trial, so they may have had better knowledge or a more positive attitude towards healthy lifestyles than the general population. Participants were also highly educated and earning more money than the national average; their views may, therefore, not be representative of the general population and our findings may not reflect the reasons for participation among less educated or lower socioeconomic groups. By using an inductive approach guided by the data, the analysis is also limited to the topics raised during the interviews. While we identified no new themes when coding the later interviews and believe we reached data saturation, it is possible that new themes would have been present in a larger, more diverse sample. A second limitation is our measure of website engagement. We measured engagement by tracking which pages participants had accessed during the trial and considered participants high engagers if they completed all three sessions, and low engagers if they did not. While this method is better than self-report [
Although not reported previously, the findings that engagement was lower in those who expressed negative emotions such as fear, anxiety, or worry when being asked during the interview to recall their feelings at the time they received the risk information, and in those who reported less success with prior experiences of behavior change attempts, are consistent with behavioral theory. Two widely used theories of behavior change (Protection Motivation Theory [
The findings that perception that there was little or no helpful lifestyle information provided by the intervention was associated with not completing the intervention, and a third of those who were high engagers with the Web-based intervention reported feeling an obligation to complete the intervention as part of the study, are also consistent with reports on participation in research. Two of the key motivators for taking part in clinical trials are a willingness to help others and contribute towards furthering medical knowledge, and perceiving some benefit (and/or no significant disadvantage) for themselves [
In addition to these individual-level factors associated with engagement with the intervention, this study also highlights a number of features of Web-based interventions that can act as either barriers or facilitators. The most common barriers that were reported related to difficulties with access to the intervention itself, such as forgetting the link to the website or passwords [
In the context of a growth of interest in scalable interventions, where small effect sizes across large numbers of individuals have the potential to impact health at the population level, this study has a number of implications for clinicians involved in communicating risk of disease and providing lifestyle advice, and those developing Web-based interventions. Our findings suggest that tailoring Web-based health behavior change interventions to take account of participants’ prior perceptions of their risk, any earlier attempts at behavior change, and their current knowledge of health behaviors may improve engagement. These approaches could be achieved by presenting risk in different visual or verbal formats, using behavior change techniques targeted at improving self-efficacy for those with previous failed attempts at behavior change, and providing information in a stepwise manner with more complex information available for those with greater baseline knowledge. Seeking to prevent or address negative emotions at the time of delivery of risk information by providing endorsement of the risk information and Web-based intervention at the time of referral or provision of risk, may also reduce subsequent maladaptive coping strategies. Developing or recommending interventions that take account of difficulties with access and perceived lack of flexibility by having simple password reminder systems and clear navigation, whilst continuing to present lifestyle information in a nonjudgmental way using simple language, may also increase engagement and reduce attrition.
coronary heart disease
cardiovascular disease
Information and Risk Modification
National Health Service
The INFORM study was funded by European Commission Framework 7 EPIC-CVD Grant agreement (No. 279233). NHS Blood and Transplant funded the INTERVAL trial. Deoxyribonucleic acid extraction and genotyping in INTERVAL/INFORM was funded by the United Kingdom National Institute of Health Research. The coordinating team for INTERVAL/INFORM at the Cardiovascular Epidemiology Unit of the University of Cambridge was supported by core funding from: United Kingdom Medical Research Council (G0800270), British Heart Foundation (SP/09/002), British Heart Foundation Cambridge Cardiovascular Centre of Excellence, and United Kingdom National Institute for Health Research Cambridge Biomedical Research Centre. JUS was funded by a National Institute for Health Clinical Lectureship and BS was supported by the Medical Research Council (MC_UU_12015/4).
A complete list of investigators and contributors to the INTERVAL trial is provided elsewhere [
JUS contributed to the design of the INFORM study, analyzed the qualitative and quantitative data, and wrote the first draft of the manuscript. LW analyzed the qualitative data and critically revised the manuscript. GS designed the qualitative elements of the INFORM study, contributed to the development of the Web-based intervention, conducted the interviews, analyzed the qualitative data, and critically revised the manuscript. BS designed the INFORM study, developed the content for the Web-based intervention, and critically revised the manuscript. RP developed the Web-based intervention, contributed to the design of the INFORM study, and critically revised the manuscript. SG designed the INFORM study and critically revised the manuscript. All authors were involved in interpretation of the data.
None declared.