Strategies to evaluate the impact of pictorial health warnings

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Strategies to evaluate the impact of pictorial
health warnings
James F. Thrasher
INSTITUTO NACIONAL DE SALUD PÚBLICA MÉXICO
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Overview of methods

• Ranking tasks
• Experimental auctions
• Surveys

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Ranking

• Convenience sample of 60 adult smokers
• Intercept interviews in Cuernavaca, Morelos
• Pile sorting/ranking
• 5 categories of pictograms from Brazil, Canada
  EU
• lung cancer
• other mortal diseases
• short-term and chronic health effects
• impact on fetus and children
• toxic tobacco components
• Rank pictures within categories, from the most to
  least powerful in terms of making you think
  about quitting

Thrasher et al. (2006), Salud Pública de México.
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Example theme images Other mortal diseases
Thrasher et al. (2006), Salud Pública de México.
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Results Other mortal diseases
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Conclusions

• One or two images stuck out within each category,
  independent of sociodemographic group
• Images rated as most likely were the most
  dramatic and evocative
• Sorting/Ranking method is a quick, easy and
  feasible approach for evaluating many images

Thrasher et al. (2006), Salud Pública de México.
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Experimental economics ? Estimate differences in
demand associated with packaging characteristics
Thrasher et al (2007), Addictive Behaviors
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17 difference in perceived value estimated
17 decline in demand
Graphic image
Text only
Thrasher et al (2007), Addictive Behaviors
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Current auction study among US smokers to inform
FDA regulation of cigarette packaging
3.71
3.43
3.26
3.02
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Which kind of pictorial warnings have the
greatest impact?
Risk/Fear?
Rational/abstract?
Uruguay
Australia
Thailand
Thrasher et al (under review)
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International Tobacco Control Policy Evaluation
Surveys of adult smokers

• Australia (n1574)
• Population-based sample
• Random digit dial
• Telephone administration
• Uruguay (n924) Thailand (n1012)
• Population-based sample (5 provinces of Thailand
  Montevideo, capital of Uruguay)
• Multi-stage cluster sample
• In-person administration

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Noticed warning labels often or very often in
last month
Prevalence across countries
Adjusted ORs of intending to quit in the next 6
months
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adjusted for sex, age, education, income, daily
vs. non-daily smoker, attempt to quit in previous
year
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HWLs made you think about smoking risks often
or very often in last month
Prevalence across countries
Adjusted ORs of intending to quit in the next 6
months
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adjusted for sex, age, education, income, daily
vs. non-daily smoker, attempt to quit in previous
year
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HWLs made you think about quitting often or
very often in last month
Prevalence across countries
Adjusted ORs of intending to quit in the next 6
months
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adjusted for sex, age, education, income, daily
vs. non-daily smoker, attempt to quit in previous
year
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Conclusions

• Thai smokers higher than Australian Uruguayan
  smokers on all indicators of HWL impact
• HWL indicators of deeper level cognitive
  processing had an independent association with
  quit intentions
• Australian smokers higher than Uruguayan smokers
  on indicators of HWL cognitive impact
• All HWL indicators independently associated with
  quit intentions
• Among Uruguayan smokers, no HWL indicator had a
  statistically significant association with quit
  intentions

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New round of Uruguayan warning labels, 2008
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No changes in HWL impact on Uruguayan smokers,
2006 vs 2008
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