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Demographic Diversity and Effective Message Design: How Behavioral Theory Can Help

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Abstract:

This paper illustrates the usefulness of the Integrative Model of Behavioral Prediction for determining the validity of demographic variables as segmentation dimensions. Using the example of adolescents’ regular marijuana use two types of demographic diversity effects are identified. First, diversity risk effects refer to relationships between demographic variables and determinants of regular marijuana use. Analyses of these effects showed that older adolescents are at higher risk than younger adolescents, suggesting stratification by age. Second, diversity message effects refer to the influence of demographic variables on both the perception of anti-drug messages and the potency of those messages in changing determinants of regular marijuana use. In this sample, female adolescents perceived a set of anti-drug ads as more effective than male adolescents. In general, the analyses illustrate a systematic and theory-based examination of the implications of demographic diversity for effective health message design.

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effect (174), use (127), marijuana (89), ad (87), messag (75), divers (54), perceiv (54), drug (53), differ (47), adolesc (45), demograph (44), variabl (43), condit (43), segment (43), regular (43), gender (36), anti (36), behavior (36), age (36), studi (34), belief (33),

Author's Keywords:

audience segmentation, behavioral theory, anti-drug interventions
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Name: International Communication Association
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MLA Citation:

Fishbein, Martin., Cappella, Joseph. and Yzer, Marcus. "Demographic Diversity and Effective Message Design: How Behavioral Theory Can Help" Paper presented at the annual meeting of the International Communication Association, Marriott Hotel, San Diego, CA, May 27, 2003 <Not Available>. 2009-05-26 <http://www.allacademic.com/meta/p111869_index.html>

APA Citation:

Fishbein, M. , Cappella, J. and Yzer, M. C. , 2003-05-27 "Demographic Diversity and Effective Message Design: How Behavioral Theory Can Help" Paper presented at the annual meeting of the International Communication Association, Marriott Hotel, San Diego, CA Online <.PDF>. 2009-05-26 from http://www.allacademic.com/meta/p111869_index.html

Publication Type: Conference Paper/Unpublished Manuscript
Review Method: Peer Reviewed
Abstract: This paper illustrates the usefulness of the Integrative Model of Behavioral Prediction for determining the validity of demographic variables as segmentation dimensions. Using the example of adolescents’ regular marijuana use two types of demographic diversity effects are identified. First, diversity risk effects refer to relationships between demographic variables and determinants of regular marijuana use. Analyses of these effects showed that older adolescents are at higher risk than younger adolescents, suggesting stratification by age. Second, diversity message effects refer to the influence of demographic variables on both the perception of anti-drug messages and the potency of those messages in changing determinants of regular marijuana use. In this sample, female adolescents perceived a set of anti-drug ads as more effective than male adolescents. In general, the analyses illustrate a systematic and theory-based examination of the implications of demographic diversity for effective health message design.

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Document Type: .PDF
Page count: 27
Word count: 7188
Text sample:
Diversity effects 1 Demographic Diversity and Effective Message Design: How Behavioral Theory Can Help Abstract This paper illustrates the usefulness of the Integrative Model of Behavioral Prediction for determining the validity of demographic variables as segmentation dimensions. Using the example of adolescents’ regular marijuana use two types of demographic diversity effects are identified. First diversity risk effects refer to relationships between demographic variables and determinants of regular marijuana use. Analyses of these effects showed that older adolescents are at
Bathroom 3.54 1.12 40 3.65 .92 42b Roaches 3.81 .95 43 Teeth 3.86 .99 40 Lab rats 3.51 1.26 41 Kentucky Michael 3.68 1.11 130 3.54 .92 130d Dealer 3.40 1.09 130 Non-reactive Long way home 3.91 1.03 45 3.86 .75 45d Everclear 3.80 .81 45 Note. An overall perceived effectiveness score was computed when valid individual ad effectiveness scores for at least a 2 out of 3 b 2 out of 4 c 3 out of 5 or


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