Warning! Proceed With Caution: a Meta-Analysis of the Effectiveness of Warning Labels

Jennifer J. Argo, University of Manitoba
Kelly J. Main, University of Manitoba
EXTENDED ABSTRACT - Current warning label designs may not effectively warn consumers about the harms of various products (Otsubo 1988; Wogalter, Godfrey, Fontenelle, Desaulniers, Rothstein, & Laughery 1987). Therefore, we propose to use meta-analysis to synthesize across the various independent and dependent measures utilized in the research. Meta-analysis is an appropriate empirical method because it allows us to identify overall trends in the effectiveness of warning labels (Hunter & Schmidt 1990). In our discussion, we identify five dimensions in information processing and five warning label characteristics relevant to the effectiveness of warning labels and test the relationships between these factors. We conclude with a discussion of the results, implications for public policy, and directions for future research.
[ to cite ]:
Jennifer J. Argo and Kelly J. Main (2002) ,"Warning! Proceed With Caution: a Meta-Analysis of the Effectiveness of Warning Labels", in NA - Advances in Consumer Research Volume 29, eds. Susan M. Broniarczyk and Kent Nakamoto, Valdosta, GA : Association for Consumer Research, Pages: 235-236.

Advances in Consumer Research Volume 29, 2002     Pages 235-236

WARNING! PROCEED WITH CAUTION: A META-ANALYSIS OF THE EFFECTIVENESS OF WARNING LABELS

Jennifer J. Argo, University of Manitoba

Kelly J. Main, University of Manitoba

EXTENDED ABSTRACT -

Current warning label designs may not effectively warn consumers about the harms of various products (Otsubo 1988; Wogalter, Godfrey, Fontenelle, Desaulniers, Rothstein, & Laughery 1987). Therefore, we propose to use meta-analysis to synthesize across the various independent and dependent measures utilized in the research. Meta-analysis is an appropriate empirical method because it allows us to identify overall trends in the effectiveness of warning labels (Hunter & Schmidt 1990). In our discussion, we identify five dimensions in information processing and five warning label characteristics relevant to the effectiveness of warning labels and test the relationships between these factors. We conclude with a discussion of the results, implications for public policy, and directions for future research.

Research on warning label effectiveness has attempted to identify factors that create the most effective label. The ultimate test of effectiveness is behavioral compliance (Wogalter, Kalsher, Frederick, Magurno, & Brewster 1998). However, investigating the effectiveness of warning labels using behavioral compliance as a dependent measure is difficult to do because of situational and ethical restraints (Wogalter et al. 1998). Consequently, researchers have employed a variety of other intermediate measures of effectiveness such as perceived hazard (Wogalter et al. 1998; Friedmann 1988; Otsubo 1988), recall (Lehto & Miller 1988), noticeability (Frantz & Rhoades 1993), conspicuousness (Malouff, Schutte, Wiener, Brancazio, & Fish 1993), and likelihood of injury (Friedmann 1988; Otsubo 1988). Research on warning labels has also explored a wide range of characteristics that are purported to influence effectiveness. The most common characteristics studied are symbols, color, signal words, levels of specificity of information, and word characteristics.

There is often wide variation in the magnitude of the correlations reported in the literature on warning label effectiveness. One objective of meta-analysis is to identify potential moderators and we identified type of participant and product type.

In terms of a meta-analytic procedure, we relied on Hunter and Schmidt’s (1990) technique which represents each study with one effect size which is corrected for unreliability or other statistical artifacts. In addition, it allows researchers to test for moderating variables and other potential sources of variation. In terms of technique, each study in the analysis is represented by one effect size. To measure the overall variability of the effect sizes, the sum of the squared differences between each effect size and the estimated population effect is weighted by the sample size. Further, the amount of variation due to sampling error is computed and if one accounts for at least 75% of the overall variation, the effect sizes are assumed to be homogeneous and represent a single underlying population. If the variation does not account for 75% of the variance, researchers should endeavor to search for potential moderator variables that could be accounting for the unexplained variance. Hunter and Schmidt (1990) also maintain that researchers should code for study design artifacts that can affect the correlation coefficient such as sampling error, measurement error, range variation, attrition artifacts and reporting errors.

The data collection was initiated through a search of the relevant databases using warning label, product label, and warning as key words from 1975 to present. The data bases searched were Psychlit, Proquest Direct, Social Sciences Index, General Science Index, Medline, and the Health Index. Our meta-analysis is restricted to including only published papers. This first phase of the data collection resulted in 23 articles. In reviewing the reference lists of the collected articles, we uncovered those papers that were not identified through the database search. This search for relevant articles resulted in an additional 13 articles. The final sample consisted of 27 articles with 34 studies upon the removal of articles that did not report adequate data.

Overall, one of the basic findings that result from this research is the fact that the majority of the relationships are weak to moderately correlated. Few of the results are strong, and these are all based on a single study. While these findings replicate the majority of the research in this area, the relationships are not as strong as previously believed. This raises questions as to how much we as researchers actually know about what comprises an effective warning label.

Moderator analyses illustrated that the type of participant moderated the effectiveness of warning labels in influencing beliefs and attitudes. Thus, undergraduate participants were more likely to be influenced by the warning labels than participants from the general population. The reliance on subject populations, a common practice in most research areas, limits the generalizability of the results.

There are a number of implications of this meta-analysis for policymakers. First, one of the major reasons that warning labels appear on such a variety of products is due to the fact that manufacturers are attempting to avoid or reduce their liability. Second, consumers’ attitudes and beliefs were not influenced by the more specific information contained in the warning label contrary to expectations stemming from changes made by the US government in cigarette warning label requirements. Finally, consumers do not always appear to understand what information the symbols convey; therefore, effort should be directed towards increasing the specificity of the symbols presented on the warning labels.

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