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Research paper
Assessing the effectiveness of antismoking television advertisements: do audience ratings of perceived effectiveness predict changes in quitting intentions and smoking behaviours? Emily Brennan,1 Sarah J Durkin,2 Melanie A Wakefield,2 Yoshihisa Kashima3 1
Center of Excellence in Cancer Communication Research, Annenberg School for Communication, University of Pennsylvania, Philadelphia, Pennsylvania, USA 2 Centre for Behavioural Research in Cancer, Cancer Council Victoria, Melbourne, Victoria, Australia 3 Department of Psychological Sciences, University of Melbourne, Melbourne, Victoria, Australia Correspondence to Dr Emily Brennan, Center of Excellence in Cancer Communication Research, Annenberg School for Communication, University of Pennsylvania, 3620 Walnut Street, Philadelphia, PA 19104, USA;
[email protected] Received 21 December 2012 Accepted 21 March 2013 Published Online First 20 April 2013
ABSTRACT Background Decisions about which antismoking advertisements should be aired are often guided by audience ratings of perceived effectiveness (PE). Given that the usefulness of PE measures depends on their ability to predict the likelihood that a message will have a positive impact on outcomes such as behaviour change, in the current study we used pre-exposure, postexposure and follow-up measures to test the association between PE and subsequent changes in quitting intentions and smoking behaviours. Methods Daily smokers (N=231; 18 years and older) completed baseline measures of quitting intentions before watching an antismoking advertisement. Immediately following exposure, intentions were measured again and PE was measured using six items that factored into two scales: ad-directed PE (ADPE) and personalised PE (PPE). A follow-up telephone survey conducted within 3 weeks of exposure measured behaviour change (reduced cigarette consumption or quit attempts). Results From pre-exposure to postexposure, 18% of smokers showed a positive change in their intentions. Controlling for baseline intentions, PPE independently predicted intention change (OR=2.57, p=0.004). At follow-up, 26% of smokers reported that they had changed their behaviour. PPE scores also predicted the likelihood of behaviour change (OR=1.93, p=0.009). Conclusions Audience ratings of PPE, but not ADPE, were found to predict subsequent intention and behaviour change. These findings increase confidence in the use of PE measures to pretest and evaluate antismoking television advertisements, particularly when these measures tap the extent to which a smoker has been personally affected by the message.
INTRODUCTION
To cite: Brennan E, Durkin SJ, Wakefield MA, et al. Tob Control 2014;23:412–418.
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Variations in the effectiveness of antismoking mass media campaigns are due in large part to differences in the reach, intensity and duration of campaign exposure.1 However, campaign success may also be related to the content and executional characteristics of the messages used.1 2 For this reason, there is a need for methods that can efficiently and effectively determine which messages are most likely to have the desired effects.3 Audience ratings of perceived effectiveness (PE)—which typically tap the extent to which a message has been favourably received and evaluated—may provide one such method.
Confidence in the utility of PE measures has increased recently, as the body of evidence linking PE with measures of actual effectiveness such as attitude4 5 and intention change3 4 6 has grown. In one recent study, the PE ratings given to the four antismoking advertisements to which an individual was exposed (from a range of 100 messages total) were found to predict quitting-related intentions.3 In another recent study, Davis et al6 found that PE ratings predicted several campaign outcomes measured 2 weeks after initial exposure to the message, including greater intentions to quit. However, Davis et al6 did not find PE ratings to be associated with the likelihood that smokers had actually attempted to stop smoking. While evidence of a predictive relationship between PE and changes in behavioural intentions is undoubtedly an important finding, and the link between intentions and behaviours is well established,7 it remains the case that demonstrating an association between PE ratings and subsequent behaviour change would greatly enhance confidence in the use of these measures. As such, in the current study we aimed to provide a further test of the association between the PE ratings given to antismoking television advertisements and the likelihood of subsequent changes in quitting intentions and smoking behaviours. In explaining why they did not find a significant association between PE and behaviour change, Davis et al6 emphasised that participants received only a low dose of media exposure, and that for many smokers, a 2-week follow-up may not have allowed sufficient time for implementation of their decision to quit. In addition, baseline rates of quitting over a 2-week period are typically low (eg, 5%8), so the Davis et al study may have lacked power to detect differences in the rates of quitting activity. Therefore, given that many smokers relapse within the first week of quitting,9 and some smokers try to reduce their cigarette consumption before making an actual attempt to quit,10 in the current study we more broadly defined behaviour change to include both successful and unsuccessful quit attempts, as well as reductions in cigarette consumption, thereby capturing the activity most likely to occur soon after exposure to an effective antismoking message. Some studies have found that smokers who are intending to quit tend to give higher PE ratings to antismoking advertisements than those who are uninterested in quitting,11 12 a finding which could be taken to indicate that antismoking messages will be most effective for this group.11 On the other
Brennan E, et al. Tob Control 2014;23:412–418. doi:10.1136/tobaccocontrol-2012-050949
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Research paper hand, it is also possible that PE may not be all that important in determining whether those who are intending to quit are influenced by an advertisement, given that the arguments made in the message are likely to be consistent with their current attitudes. In contrast, those who are not yet planning to quit are likely to require convincing of the merits of the antismoking argument and may therefore only be affected by the advertisements that they perceive to be credible, relevant and motivating. To our knowledge, no previous studies have examined whether the association between PE and campaign outcomes is the same for smokers who are and are not intending to quit (note however that the two recent studies did control for baseline interest in quitting when testing the association between PE and postexposure intentions3 6). Therefore, given the practical implications of any such differences for the use of PE measures to pretest antismoking advertisements, in the current study we also examined whether the association between PE ratings and subsequent intention and behaviour change was moderated by baseline intentions to quit.
METHODS Sample and procedure Data were collected as part of a larger study in which current smokers and non-smokers participated in friendship pairs. In this study, a two (advertisement: Pam Laffin or Rick Stoddard— 46 Years Old) by two (conversation: no conversation or conversation) experimental design assessed the influence of interpersonal conversations on campaign effectiveness. For the purposes of the current study, however, participants from the four experimental conditions were combined, and the sample was restricted to the 231 current smokers. Additional information about the design, sample and procedures of the experimental study can be obtained from the authors. One member of each friendship pair was recruited through a market research company’s existing database of research participants, and the second participant was a friend of this recruit. All participants were at least 18 years old and resided in the state of Victoria in Australia. One experimental session was conducted per friendship pair; however, each participant was exposed to the advertisement and completed all measures in isolation from, but at the same time as, their partner. Participants were exposed to one of two antismoking advertisements, both of which had not aired in Victoria before (the Pam Laffin and Rick Stoddard—46 Years Old advertisements can both be found online at http://apps. nccd.cdc.gov/MCRC). Prior to exposure, participants completed measures of quitting intentions and individual characteristics (Time 1 measures); after watching the advertisement, they completed a postexposure questionnaire (Time 2 measures). All participants were then independently followed up within 3 weeks by telephone (Time 3 measures). Participants were reimbursed $60, and this study was approved by the University of Melbourne’s Human Research Ethics Committee.
Measures Predictor variables Potential covariates At Time 1, participants reported their sex, age, highest level of education completed and daily cigarette consumption. Socioeconomic status (SES) was measured using the Australian Bureau of Statistics’ Index of Socio-Economic Disadvantage, using 2006 census data of the postcode area in which respondents resided.13 Sample characteristics are presented in table 1. Preliminary logistic regression analyses determined whether each of these individual characteristic variables was included as
a covariate in the models predicting intention and behaviour change.
Perceived effectiveness At Time 2, six items drawn from previous studies11 14–16 measured PE, and factor analysis was used to determine if these items represented one or more underlying factors. On a 5-point scale (1—strongly disagree to 5—strongly agree), participants indicated whether the advertisement: (a) made me stop and think; (b) made a strong argument for quitting; (c) taught me something new; (d) was relevant to me; (e) made me feel concerned about my smoking and (f ) made me feel motivated to try to quit smoking. Inspection of the polychoric correlation matrix17 and the Kaiser-Meyer-Olkin value (0.82) indicated that the data were suitable for factor analysis,18 and a principal factors extraction with promax rotation revealed a two-factor structure. Three items loaded on the first factor: stop and think (0.58), strong argument for quitting (0.76) and taught me something new (0.61). This factor was labelled ad-directed PE (ADPE), and the three items were averaged together (α=0.74). Three items loaded on a second factor: relevant to me (0.49), concerned about my smoking (0.86) and motivated to try to quit (0.67). This factor was defined as personalised PE (PPE) (α=0.75). The ADPE and PPE scales were moderately correlated (r=0.66).
Intentions to quit At Time 1 and Time 2, participants were grouped into one of six perspectives on change based on the transtheoretical model’s stages-of-change.8 19 Precontemplators (not considering quitting within the next 6 months) were divided based on whether they (1) were happy to continue smoking forever or (2) planned to quit sometime. Contemplators (considering quitting within the next 6 months) were divided according to whether (3) quitting was just a possibility or (4) they were actually thinking about it, and preparers (planning to quit within the next month) were further divided based on whether they (5) had not set a date to quit within the next 2 weeks or (6) had set a date to quit within the next 2 weeks.8 In analyses examining interactions between baseline intentions and PE ratings, those who had plans to quit (PTQ) at Time 1 were captured using a binary variable (no PTQ—perspectives 1, 2, 3 and 4; PTQ—perspectives 5 and 6).
Outcome variables Participants were categorised as having changed their intentions to quit if they showed any forward movement on the perspectives on change measures between Time 1 and Time 2 (eg, from perspective 1, to perspectives 2, 3, 4, 5 or 6; from perspective 5 to 6, etc), or if they remained in perspective number 6. At the beginning of the follow-up survey (Time 3), participants were asked whether they had changed, or had thought about changing, their smoking behaviour in the past week. Participants were dichotomised into those who had not changed their behaviour (no change; thought about quitting, but did not make an attempt; or decided to quit, but did not make an attempt) and those who had made an actual change (tried to cut down the number of cigarettes smoked; attempted to quit but relapsed to smoking; or attempted to quit and are still quit).
Statistical analyses Models predicting intention change used the full analytic sample (N=231; note that 1 current smoker (from an original sample of 232) was excluded from the analytic sample due to outlier values on several variables). Models predicting behaviour
Brennan E, et al. Tob Control 2014;23:412–418. doi:10.1136/tobaccocontrol-2012-050949
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Research paper Table 1 Distribution of participant characteristics in the initial sample, the followed-up sample and the not followed-up sample Participant characteristic Age Daily cigarette consumption Sex Male Female Highest level of education Not finished secondary Finished secondary At least some tertiary SES Low SES area Moderate SES area High SES area Advertisement condition Pam Laffin Rick Stoddard—46 Years Old Conversation condition No conversation Conversation
Initial sample (N=231) M (SD)
Followed-up (n=208) M (SD)
Not followed-up (n=23) M (SD)
31.4 (10.1) 12.9 (7.8) %
31.3 (10.0) 13.1 (7.9) %
32.5 (11.3) 11.0 (6.6) %
45.5 54.6
43.3 56.7
65.2 34.8
21.7 36.8 41.6
22.6 37.5 39.9
13.0 30.4 56.5
22.5 38.5 39.0
23.1 38.0 38.9
17.4 43.5 39.1
53.7 46.3
55.8 44.2
34.8 65.2
52.8 47.2
51.9 48.1
60.9 39.1
t
p Value
0.57 −1.28 χ2 4.02
0.571 0.203 p 0.045
2.53
0.282
0.46
0.795
3.67
0.055
0.67
0.415
t Tests (degrees of freedom=229) and χ2 (with degrees of freedom of 1 or 2) tested differences in the distribution of characteristics among those participants who were and were not followed-up. Due to rounding, percentages may not total to 100. SES, socioeconomic status.
change were restricted to the 208 current smokers (90%) who completed the follow-up survey (days to follow-up: M=8.5; SD=3.5; range=5–21). t Tests and χ2 compared the characteristics of those who were and were not followed up, and these analyses indicated that the two samples differed significantly in the distribution of men and women (χ2 (1, N=231)=4.02, p=0.045), and that the difference in the proportion of participants who had watched the Pam Laffin and Rick Stoddard—46 Years Old advertisements was approaching statistical significance (χ2 (1, N=231)=3.67, p=0.055). However, because 90% of the initial sample was retained at follow-up, these different distributions did not produce noticeable differences in the characteristics of the initial and followed-up samples (table 1). Across all Time 1 measures, only two missing values for the education variable and one missing value for SES were identified, and these were replaced using the sample median. There were no missing data for any Time 2 or Time 3 variables. A preliminary set of logistic regression models tested the association between each potential covariate and the two outcome variables (for categorical covariates, a χ2 test assessed the overall effect of the variable), and only those that were associated with the outcome at p
