The Internet has become an important source of health information and advice, with between 40% and 80% of those with Internet access in the United States and Europe using it for health care purposes [1,2]. However, the quality of the available information is highly variable. For example, in a 2002 meta-analysis, Eysenbach and colleagues noted that 70% of website reviews expressed concern about the quality of the health-related information provided on the Internet [3]. In the face of such variable quality, how do health consumers decide whether or not to trust the information and advice they find online?

Briggs and colleagues addressed this issue in a series of studies of trust in eHealth that led to the development of a staged model of trust and a set of guidelines [4-6]. They found that users rapidly rejected health sites on the basis of superficial cues capable of influencing consumer trust. These included advertising, complex layout, inconsistent design, or the presence or absence of reputable brand markers.

Sillence et al [5,6] noted that a great deal of high-quality health information was lost to the consumer through this process and that drug company sites in particular—often highly rated by health experts in terms of health content [7]—were frequently rejected because of the presence of commercial cues.

Health consumers, then, do not always choose the best-quality health sites or follow the best advice. Indeed, they can show a marked reluctance to trust advice they perceive to be inconsistent with their important prior beliefs, even displaying a “defensive” response to such information [8-11] that can take the form of close critical scrutiny and subsequent rejection of good-quality information [12,13]. As a result, those most at risk can be the most averse to change and may be the most difficult to persuade. Clearly, given this propensity to respond defensively, it is counter-productive to present consumers with cues that might inadvertently trigger a negative response to good health advice.

This is particularly problematic in the eHealth context, where consumers can often find conflicting advice and are able to navigate to websites that tell them what they would prefer to hear. In one study, for example, a population struggling to modify their drinking behavior sought pro-drinking rather than anti-drinking material when left free to choose via the Internet [14]. In our own study, we are interested in the fact that Internet material often contains visual design elements, or cues, that are unrelated to the quality of the health information presented but that could be used to influence credibility judgments about the site and that may also subsequently influence acceptance and adherence to health advice. What happens to an individual who spends time reading important high-quality health advice on a website that coincidentally displays negative credibility cues (such as a drug company site containing high-quality health information alongside advertising)? Can these content-irrelevant cues affect acceptance or rejection of important health advice?

We present an experimental study in which women with different levels of weekly alcohol consumption were exposed to high-quality, uncongenial, Internet-based information concerning a related health risk (breast cancer). This unpalatable information was presented alongside positive or negative trust cues unrelated to the information content. We explored four research questions: First, do the cues influence direct engagement with the material on the site? We examined how long the women spent on the site, their pattern of eye movements when examining the site’s pages, and their ability to recall site content. Second, do the cues influence how they respond cognitively and affectively to the site? We examined their subsequent message acceptance, emotional and risk perceptions, and their intentions to adopt the recommended behavior. Third, do the cues influence the extent to which they subsequently act on the advice given? We examined reports of behavior at follow-up 1 week after exposure to the site. Finally, does the impact of the cues vary with how much alcohol the women typically drink? We tested whether baseline alcohol consumption moderated the effects of condition on any of the above outcome measures. That is, we tested whether any cue effects were most pronounced among those who drank most (i.e., those who might display the biggest defense motivation) [10,15].

To test these research questions we developed a two-page website containing information about the link between alcohol consumption and the risk of breast cancer. All material was based on a recent definitive study showing such a link [16]. At the time of testing this was (and in the UK largely remains) a relatively unknown association, so for most women the information on the site was novel. The text contained strong arguments that were not easily denigrated and was identical in both content and layout in both experimental conditions. Participants—women aged 18 to 46 who varied in their level of alcohol consumption—were randomly exposed to this information on a website containing either positive credibility cues (i.e., cues that had been positively associated with credibility in previous research [6]) or negative credibility cues (also based on previous findings [17]). The cues were selected to be unrelated to the content of the site. In summary, the aim of this study was to assess whether design-based credibility cues promote acceptance or rejection of important health advice.

Did the cues influence engagement with the material on the site? We examined how long the women spent on the site, their pattern of eye movements when examining it, and their recall of site content and found that, whereas the cues did not affect the overall time the women spent on the site or how long they spent reading the text, they did influence where the women directed their gaze and how much they subsequently recalled. Participants paid more attention to certain negative cues, such as the donation button, than to positive cues in the equivalent location, and those in the negative cues condition were subsequently more accurate in their recall of information, suggesting that they paid closer attention to the site content.

Did the cues influence how the participants responded cognitively and affectively? No. We found no effects of the cues on any of the explicit ratings of cognition, affect, vulnerability, or intentions—at least not initially (see below). However, those who drank more reported more negative affect and vulnerability and expressed stronger intentions to cut down on their drinking, effects that persisted at follow-up. This suggests that the material had been persuasive, even among the heavier drinkers. Interestingly, these effects occurred even though drinking level had not influenced how the women examined the site visually or their recall of its contents.

Did the cues influence the extent to which the women subsequently acted on the advice given? Yes, the important influence of credibility cues was seen most clearly at follow-up, where the positive cues promoted greater alcohol reduction than did the negative cues among those who had previously reported heavier drinking. Thus, the answer to our final question— Does the impact of the cues vary with how much alcohol the women typically drank?—is also yes. Indeed, the cues now interacted with baseline drinking level to change the women’s belief in the evidence: specifically, women who had reported drinking the most expressed less belief in the evidence at follow-up, especially the women in the positive cues condition.

Consequently, the results of this study indicate that seemingly superficial design elements of a website can influence responses to health-risk information. As predicted, cues known to be positively or negatively associated with credibility affected engagement with the site and influenced subsequent health behavior and cognition.

We interpret these data as being consistent with findings in the broader literature on defensive responding to threatening information [8-11]. In essence, we expected the presence of positive (but non-content-related) credibility cues to bolster the message but negative cues to undermine it. We were unsure how immediate or delayed such effects might be, and it is clear that, in the short term, message content predominated. However, with time, the negative cues exerted detrimental effects by reducing the extent to which the heavier-drinking women acted on the advice. Moreover, 1 week later, the heavier drinkers also reported perceiving the evidence linking breast cancer and alcohol to be weaker, thus showing the first signs of message rejection on any of our explicit measures. Perhaps this is because, after a week of reduced consumption, they appreciated more fully the difficulties involved in trying to reduce alcohol consumption. If so, we may have captured them in the early stages of defensively re-evaluating the original website material. This might be the focus for further investigation. Indeed, at this stage there was even the suggestion that the protective effects of the positive cues may have been wearing off, as belief in the link was lower among heavier drinkers in the positive cues condition.

The findings thus present an intriguing picture of a group of participants developing their response to a website containing credible, but unwelcome, health-related information. The eye-tracking data also contribute to our understanding of how people allocate their attention to features of websites. For instance, those in the positive cues condition spent relatively little time looking at the HON code or the TRUSTe seal relative to other elements of the site, such as the logo (see Table 2). Indeed, the presence of such codes and awards has been shown elsewhere to have little effect on the credibility or retention of health information on a Web page [28], and Eysenbach and Köhler [29] noted that consumers failed to click on the HON logo when it was present on websites, despite having suggested that some form of controlling authority or an endorsement by a third party would be a helpful quality marker. There have been claims that consumer expectations of such health seals are often inconsistent with how they respond to them in practice [30]. Certainly, here participants were more inclined either to look at negative cues more than their positive equivalents or to spend relatively little time looking directly at either.