THE ASSESSMENT OF USER ENGAGEMENT WITH EHEALTH CONTENT: THE EHEALTH ENGAGEMENT SCALE1

R. Craig Lefebvre, PhD, Yuri Tada, PhD, Sandra W. Hilfiker, MA & Cynthia Baur, PhDHealth Communication, Marketing and Media Conference12 August 2009

1 Accepted for publication in the Journal of Computer-Mediated Communication

eHealth Tools

Enable consumers, patients, and informal caregivers to gather information, make healthcare decisions, communicate with healthcare providers, manage chronic disease, and engage in other health-related activities.

The 5 As: Behavior Change Benchmarks

Ask, Advise, Assess, provide Anticipatory Guidance and Arrange Follow-Up 1.

An assessment of 273 health websites that targeted seven health behaviors 2.

Results: 25% used three or more of the 5 As; very low (<20%) participation rates among the general population

Implications: Need more research to improve (1) participation rates and use of eHealth internet sites, and (2) the quality of the eHealth interventions to promote changes in health behaviors.1. Cummins et al. (2003). Development of Review Criteria to Evaluate Health Behavior Change Websites. Journal of Health Psychology; 8: 55-62.  2. Evers et al (2005). Online Health Behavior and Disease Management Programs: Are We Ready for Them? Are They Ready for Us? J Med Internet Res; 7(3):e27 [doi:10.2196/jmir.7.3.e27].

Engagement is turning on a prospect to a brand idea enhanced by the surrounding context (Advertising Research Foundation).

“…engagement starts from the vantage point of the customer - either current or potential. By starting there and thinking about whether they are engaged, how can we engage them, and how can we help them achieve their desires, goals or needs, then the risk of not being invited in goes away because you become more relevant. “

Engagement in eHealth

The process of involving users in health content in ways that motivate and lead to health behavior change.

Engagement and Advertising Effectiveness

Can Advertising Measures of Engagement be Used for eHealth?

The variability of results achieved across numerous stimulus conditions (i.e., whether it is sensitive to variations in user perceptions of different materials).

The internal consistency of the scale. Its underlying factor structure. Its association with immediate outcomes

(intentions and self-efficacy to change health behaviors after viewing content).

Method

Healthfinder.gov prototype development.

Nine health topics: overweight/obesity, physical activity, preventing falls in the elderly, high blood pressure screening, influenza immunization, nutrition, tobacco cessation, colorectal cancer screening, and talking to children about drugs.

Engagement Items

•Absorbing•Attention-Grabbing•Stimulating•Surprising•Suspenseful•Thought-Provoking

•Clever•Convincing•Balanced•Believable•(Not) Dull•Hip/Cool

Method

Online and telephone recruitment of stratified sample (N=403)

Assigned to condition: Seeking information about a health

problem for themselves or someone they know.

Wanting to find out if they or someone they know has a health problem or reason to be concerned about a health problem.

Seeking information to prevent the onset of a health problem.

Protocol

Participant Characteristics 260/403 (65% completion rate) 30 removed – response bias (15), +3 SD

completion time (14), double exposure (1) Final sample = 230 (88%). Χ2 for demographic

differences was n.s. 60:40 split of women (n = 138) to men (n = 92) 55% of the sample was between the ages of

30-49 years old skewed towards the upper levels of household

income (HHI) with 19% (44) reporting HHI > $100,000 and 9% (21) reporting HHI < $20,000 (Median = $40,001-$70,000).

Involving

Involving

Credible

Factor Structure

Three solutions: confirmatory, modified 4-factor, and a 2-factor.

Tested against predictive validity criteria: The information made me feel more

confident that I can do something. The information made me feel more

prepared to do something. The information made me feel more

prepared to do something in the next month.

Path Model of Modified 4-Factor Solution to Explain Immediate Outcome Variables

Implications

A measure of engagement developed for commercial television advertising viewing to predict advertising effectiveness can be used to assess user engagement with eHealth content.

A modified 9-item version of the original scale accounted for 56% of the variance in self-reported confidence and intentions to act across nine different health topics.

Implications

This modified 4-factor model was subsequently used to analyze the engagement data for each of the nine health content areas separately. Our results (not shown here) found that the factor structure of the modified 4-factor solution was stable across all nine topic areas.

User engagement may prove to be an important mediator of user retention of information, intentions to change, and ultimately efforts to undertake and achieve behavior change.