1. Cancer Institute Tobacco Tracking Survey
Topline Evaluation Report #12
Version 1.0 | 14 Jan 2016
Report prepared for:
Donna Perez
Caroline Anderson
Sally Dunlop
Report prepared by:
Paul Myers
Natasha Vickers

2. Campaign overview 570 TARPS 15 Nov – 19 Dec Many Diseases (30 sec)
Category: Graphic

3. Research methodology Method Respondents Sample size and design
Telephone survey
Respondents
Smokers or recent quitters aged 18 years and over in NSW
Sydney, and Northern and Southern regional (including Canberra) TV markets only
Sample size and design
40 interviews per week in 2015
Dual frame sample design: 50/50 Landline RDD / Mobile RDD
Landline sample stratified in proportion to population
Interview length
Average 16.3 mins

4. Research methodology Total 2015 sample (Week 26-50): n=1,041 Weighting
Pre-campaign tracking – What’s Worse: W40-41; Campaign: W42-47; Post- campaign tracking: W48-50
Pre-campaign tracking – Many Diseases: W44-45; Campaign: W46-50; No post- campaign tracking period due to Christmas break
Weighting
Two-stage process to adjust for an individual’s chance of selection (in-scope sample members in a household, the number of landlines in the household used for private calls; and/or having a mobile phone), as well as age, gender, location and telephony status.

5. Sample profile Selected characteristics n= % W26 – W50 sample 1,041
100.0
CALD
Yes
190
18.3 No
851
81.7
Age
18-39
374
35.9
40+
667
64.1
Gender
Male
580
55.7
Female
461
44.3
Smoking Status
Smoker
904
86.8
Recent quitter
137
13.2
SEIFA Quintiles
One
214
20.6
Two
218
20.9
Three
245
23.5
Four
197
18.9
Five
167
16.0
Data is unweighted

6. Recognition of TVC
Recognition of Many Diseases TVC rose steadily over the campaign period, reaching a peak of 43% in the fourth week of the campaign. Recognition of the TVC averaged 31% over the campaign period for the total sample and 37% for the target audience.
Further, the levels of recognition achieved was below the level of recognition predicted using the Dunlop model for a graphic ad (≈55%). The level of recognition achieved in the final two weeks of the campaign for year olds was higher than the level of recognition predicted.
Base: 2015 sample, Week 44 to Week 50. Total (n=320), year olds (n=108).
Respondents were read a description of each TVC and asked - Have you seen this ad recently?
No post-campaign data is shown, as recognition questions were only asked 2 weeks pre due to Christmas break.

7. Relevance and Believability* *
Respondents who recognised Many Diseases were asked to rate the ad in terms of its relevance and believability. These items form part of the personalised effectiveness and ad-directed effectiveness composite measures, respectively.
Over two-thirds (70%) of those who saw Many Diseases in the 2015 campaign period thought it was relevant to them, this was lower than targets set for the campaign (75%). This result was also lower, albeit not significantly than previous bursts of the campaign. Further, approximately three-quarters (79%) of those who saw Many Diseases thought the ad was believable, this exceeded expectations set for the campaign (75%). However, this result was significantly lower than all previous bursts of the campaign.
Base: All respondents who saw ad in campaign period. 2008, n=117; 2009, n=211; 2010, n=179; 2015, n=109; years, n=41.
Thinking about this ad, how relevant / believable would you say it is? Chart shows % very/somewhat.
* Indicates response is significantly different from the 2008 burst.

8. Population Impact * *
Smokers who recognised Many Diseases were asked the extent to which the ad make you think again about quitting. The figure above shows the proportion of all smokers who said it had ‘a lot’ or ‘somewhat’ made them think about quitting again. This provides a measure of ‘population impact’ of the advertisement.
Approximately one-quarter (28%) of all smokers stated that Many Diseases had made them think again about quitting, this is comparable to the average for other ads adopting a ‘graphic’ style and the two most recent bursts of the campaign. Further, this exceeded targets set for the campaign (25%).
Base: All smokers in campaign period. 2008, n=81 ; 2009, n=124 ; 2010, n=96; 2015, n=60; years, n=75.
Respondents who recognised the campaign and said it made them ‘think again about quitting’. Chart shows % a lot/somewhat.
* Indicates response is significantly different from the category average.

9. Campaign-related beliefs
Total
Recognised ad
Did not recognise ad
You could get any one of a number of diseases caused by your smoking 86 81 88
The majority (86%) of smokers who recognised Many Diseases agreed that you could get any one of a number of diseases caused by your smoking.
No significant differences were noted between smokers who recognised Many Diseases and those who hadn’t.
Message take out underperformed expectations set for the campaign (94%).
Base: All smokers in relevant campaign period only (n=211).
Respondents were read a number of statements about smoking relevant to each ad. Chart shows % Strongly Agree and Agree.
* Indicates response is significantly different from recognised ad.