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Demographic Diversity and Effective Message Design: How Behavioral Theory Can Help
Unformatted Document Text:  Diversity effects 19 of how the construct should be measured. As an illustration of this contention, Borzekowski and Poussant (1999) assessed perceived ad effectiveness by asking agreement with the statement that ‘This video will have an effect on people who see it’. It seems unlikely that studies that employ such different measures of perceived ad effectiveness lead to the same conclusions. A different question is whether the gender effect allows us to make a case that we can expect differential change because of exposure to anti-drug ads as a function of the receiver’s gender. Assuming for a moment that perceived ad effectiveness is in fact a good predictor of actual ad effectiveness, the effect of gender on perceived ad effectiveness suggests that after ad exposure women should become more negative toward regular marijuana use than men. Our findings do not support this expectation. Perhaps we should interpret the less than compelling correlations between perceived effectiveness and the determinants of regular marijuana use as evidence that perceptions of effectiveness do not predict actual effectiveness. This would have serious consequences for the validity of pre-tests that rely heavily on perceptions of a message’s effectiveness to decide whether or not to implement the message. On the other hand, recall that because of sample size considerations all nine treatment conditions were pooled together to contrast no exposure to any exposure. Therefore, results of effective ads may have been averaged out by ineffective ads. Unfortunately, our data do not allow evaluations of individual ads. Until we can, we should be careful in disclaiming the validity of perceived effectiveness as a proxy of actual effectiveness. In conclusion, this research used the Integrative Model as a theoretical framework to examine the usefulness of demographic variables for segmentation purposes. In our example of adolescents’ regular marijuana use we found that age is a relevant segmentation dimension. In general, the health educator may expect gender differences in how adolescents perceive anti-drug

Authors: Fishbein, Martin., Cappella, Joseph. and Yzer, Marcus.
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Diversity effects 19
of how the construct should be measured. As an illustration of this contention, Borzekowski and
Poussant (1999) assessed perceived ad effectiveness by asking agreement with the statement that
‘This video will have an effect on people who see it’. It seems unlikely that studies that employ
such different measures of perceived ad effectiveness lead to the same conclusions.
A different question is whether the gender effect allows us to make a case that we can
expect differential change because of exposure to anti-drug ads as a function of the receiver’s
gender. Assuming for a moment that perceived ad effectiveness is in fact a good predictor of
actual ad effectiveness, the effect of gender on perceived ad effectiveness suggests that after ad
exposure women should become more negative toward regular marijuana use than men. Our
findings do not support this expectation. Perhaps we should interpret the less than compelling
correlations between perceived effectiveness and the determinants of regular marijuana use as
evidence that perceptions of effectiveness do not predict actual effectiveness. This would have
serious consequences for the validity of pre-tests that rely heavily on perceptions of a message’s
effectiveness to decide whether or not to implement the message. On the other hand, recall that
because of sample size considerations all nine treatment conditions were pooled together to
contrast no exposure to any exposure. Therefore, results of effective ads may have been averaged
out by ineffective ads. Unfortunately, our data do not allow evaluations of individual ads. Until
we can, we should be careful in disclaiming the validity of perceived effectiveness as a proxy of
actual effectiveness.
In conclusion, this research used the Integrative Model as a theoretical framework to
examine the usefulness of demographic variables for segmentation purposes. In our example of
adolescents’ regular marijuana use we found that age is a relevant segmentation dimension. In
general, the health educator may expect gender differences in how adolescents perceive anti-drug


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