Abstract
This article investigates two kinds of information search strategies in the context of selecting romantic partners. Confirmatory searching occurs when people ask for more information about a romantic partner in order to validate or confirm their assessment. Balanced searches are characterized by a search for risk information for partners rated as attractive and for attractiveness information about partners rated as risky in order to attain a more complete evaluation. A factorial survey computer program randomly constructed five types of partner descriptions and college-age respondents evaluated nine descriptions in terms of both health risk and romantic attractiveness outcomes. The results show little evidence of balanced search strategies: for all vignette types the respondents searched for attractiveness information. Regression analysis of the search outcomes showed no difference between males and females in the desire for attractiveness or risk information, the amount of additional information desired, or the proportion of descriptions for which more information was desired. However, an attractive physical appearance did increase the amount of additional information desired and the proportion of vignettes for which more information was desired. The results were generally inconsistent with a balanced search hypothesis; a better characterization of the respondents' strategy might be “confirmatory bias.”
Acknowledgements
This research was supported by NIMH grant MH 62983. We thank Aram Aghazarian and Herbert Simons of the Department of Speech Communication, Temple University, for providing space and resources for data collection on their campus. We also thank Suzanne Martin and Nicole Trentacoste for comments of earlier drafts.
Notes
1. There were 162 males matched with opposite-sex partner descriptions, nine bisexual males matched with opposite-sex ones, and three males matched with same-sex ones. There were 202 females matched with opposite-sex partners, nine bisexual females matched with opposite-sex ones, and three females matched with same-sex ones.
2. The adjustment produces consistent estimates of the standard errors (i.e., bias decreases as the sample size gets larger) and as long as it is used in situations where the clustering variable has more than 20 values, it gives acceptable Type I error rates (Donner & Klar, Citation2000, p. 94; Murray, Citation1998, p. 99). Thus, this is not a concern here, for our clustering variable—the respondent ID—has 393 values.