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when Designing Web Support for Smoking Cessation ... people are more responsive to preference consistent information – a finding ... email and word of mouth.
Assessing Patient Experience and Patient Preference when Designing Web Support for Smoking Cessation Elizabeth Sillence

PaCTLab Northumbria University Newcastle upon Tyne, UK +441912437246

[email protected]

Peter R Harris

School of Psychology University of Sussex Brighton, UK +440123876638

[email protected]


Patients will often resist campaigns to promote healthier behavior but the digital health revolution allows the creation of a much more nuanced set of health messages that can be tailored to the patient or end user. In this study we explore the effects of patient preference on message acceptance and also explore what happens when messages are framed in terms of patient experience. Smokers (n=113) viewed a quitting website in which material was expressed either as a factsheet or as patient experience (PEx) and where the material was either matched or unmatched to their own preferred quitting methods. Across a range of measures, we found evidence that preference matching was effective in motivating smokers to engage with the material and we found modest support for the role of PEx in reducing message resistance.

Categories and Subject Descriptors

H.3.5 Online Information Services: web based services; K.4.1 Public Policy Issues: Computer-related health issues


Smoking cessation; eHealth; patient experience; homophily


Campaigns to promote healthier behavior face many obstacles. One significant issue is message resistance: those to whom the message is directed – such as the overweight targeted by a campaign to promote dietary improvement or smokers targeted by a quit campaign – may be less likely to accept the message or see it as personally relevant than are those for whom the message is less relevant. Intriguingly, there is evidence that presenting information in the form of reported patient experience (PEx) may reduce resistance and facilitate message uptake [1, 2]. However, to date relatively few studies have examined this potentially significant consequence of PEx. In this study we tested whether PEx would reduce the tendency of a targeted audience (smokers) to resist a quit message. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]. DH’15, May 18–20, 2015, Florence, Italy. Copyright © 2015 ACM 978-1-4503-34921/15/05…$15.00.

Pam Briggs

PaCTLab Northumbria University Newcastle upon Tyne, UK +441912273885

[email protected]

We created a message that would support patients to quit smoking using aids (current evidence suggests that smokers are more likely to quit when using aids). We then created a PEx version of the message – framing the original facts as a personal story. On the basis of previous findings, we predicted that the PEx version would promote greater message acceptance. In a further manipulation, we examined the influence of preference match. Preference match addresses whether the health information offered online supports pre-existing beliefs and needs (i.e., is preference consistent or preference inconsistent). In general, people are more responsive to preference consistent information – a finding related to homophily in health social networks [3]. We therefore anticipated that our advice would be more readily accepted when it was preference matched to the reader, but in keeping with our argument that PEx reduces message resistance, we felt that this effect may be attenuated in the PEx as opposed to the factsheet condition. We randomised smokers to view the four versions of online material in a 2 (factsheet vs PEx) x 2 (preference consistent vs preference inconsistent) design. We had previously established participants’ preferences for mode of quitting (supported versus unsupported) and their previous quit experiences and practices in order to allocate to preference matched or unmatched conditions. The dependent outcome – message acceptance – was measured in several ways. Initial responses were assessed using immediate measures of mood, ratings of message acceptance and personal relevance. Other measures assessed changes in motivation and readiness to change (e.g., intentions to quit).


Current smokers were recruited to the study via poster advert, email and word of mouth. A total of 113 participants completed the online study. Most (n = 74, 65.5%) were students.

2.1 Measures

Along with basic demographics (age, sex, occupation), we measured baseline smoking behavior, Internet use, motivation to quit [4] attitude to method of quitting, and previous quit attempts (to assess preference consistency). Participants were asked whether they had smoked any cigarettes or used other tobacco, even a puff, in the last 14 days, whether they had made a serious attempt to stop smoking within the last 2 weeks and how many cigarettes they had smoked in the previous 24 hours. Post-

exposure materials comprised measures of mood, motivation to quit [4], message acceptance, negative affect and personal relevance. Website responses were assessed using 34 items from a new measure e-health impact questionnaire (EHIQ) [5].

2.2 Materials

The health message was presented as a single web page and contained evidence about quitting smoking taken from an authoritative source [4]. Two different but similarly sized versions of the web page were created, both containing exactly the same design features and layout but varying in terms of the way in which the information was presented. In the factsheet condition the quitting smoking facts were presented as a bullet point list of statements. In the PEx conditions the same facts were presented as a personal story of quitting.


The data were analyzed using a 2 (information type: information only, PEx) x 2 (preference consistency: preference consistent, preference inconsistent) between subjects ANOVA. Missing data on dependent variables resulted in the following cell sizes for most analyses: information only, n = 21 (preference consistent), n = 16 (preference inconsistent); PEx, n = 50 (preference consistent), n = 20 (preference inconsistent). Alpha was set at p ≤ .05. There were significant main effects of preference consistency on several of the dependent measures: when the message was consistent with their preferences, participants spent more time viewing the material (Consistent M = 95.2 seconds, Inconsistent M = 67.8 seconds), F(1, 101) = 6.09, p = .015, were more motivated to quit smoking (Consistent M = 4.7, Inconsistent M = 4.0), F(1, 103) = 4.00, p = .048, reported thinking more deeply about the information (Consistent M = 3.7, Inconsistent M = 2.7), F(1, 103) = 8.29, p = .005, reported being more worried by it (Consistent M = 4.2, Inconsistent M = 3.4), F(1, 103) = 4.13, p = .045, and worrying more about the health risks of their smoking (Consistent M = 4.0, Inconsistent M = 2.9), F(1, 103) = 10.74, p = .001. In terms of responses to the site, they had higher scores EHIC confidence (Consistent M = 30.4, Inconsistent M = 26.7), F(1, 102) = 6.29, p = .014, and EHIC understanding (Consistent M = 31.3, Inconsistent M = 27.6), F(1, 102) = 6.61, p = .012, but not EHIC information (Consistent M = 26.9, Inconsistent M = 25.9), F(1, 102) = 1.02, p = .319. There was only one significant main effect of condition: the PEx promoted more positive mood (M = 4.6) than did the information only (M = 4.2), F(1, 103) = 4.68, p = .033. The key condition x preference interaction was only significant for one dependent measure. As hypothesized, preference consistency affected intentions to cut down in the information only condition (Consistent M = 5.5, Inconsistent M = 4.2) but not in the PEx condition (Consistent M = 5.0, Inconsistent M = 5.2), F(1, 102) = 4.97, p = .028.


There is good evidence here that health information expressed in a way that is preference consistent will lead to higher levels of engagement with online content. This supports findings in the general health literature around preference consistency and reflects the role of homophily or preference for health information from ‘people like me’ as a component of effective health behavior change [3, 6].

There is more limited evidence that this response is moderated by the presentation of material in a patient narrative (PEx). We argued that PEx can reduce message resistance by facilitating the acceptance of information that is inconsistent with the person’s preferences, but there is only one significant interaction (on intentions) that supports this hypothesis and only two of the tested interactions are significant. It should be noted, of course, that the tests of the interaction effect are likely to be somewhat underpowered owing to the impact of participant attrition on cell sizes. We began this study with several questions about the potential role of patient preference and patient experience in reducing message resistance. We have found good evidence for patient preference as a key issue in interacting with web material, but more limited evidence that PEx can reduce unpalatable message resistance and promote more active engagement with online health advice.


This publication presents independent research funded by the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research programme (RP-PG0608-10147). The views expressed in this publication are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. We would also like to thank colleagues from the iPEx study group for their helpful comments in some of the design stages of this work.


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