Target Specificity of Subjective Relationship Measures: Understanding the Determination of Item Variance

The present study was conducted to test the ability of two subscales from the Friendship Quality Questionnaire (FQQ; Parker & Asher, 1993 ) to discriminate between different target friendships. This was done by testing for mean differences between targets, and by using both exploratory and confirmatory factor analyses to examine the factor structures for these measures when the responses for different targets were considered together. Participants were 293 Italian middle‐school students. Both subscales (Validation and Caring, and Conflict and Betrayal) showed mean differences between the best friend and the second and third best friends, but only the validation and caring subscale demonstrated differences between the second and third best friends. Factor analyses showed that for both subscales some items were able to discriminate between friends whereas others were not. Confirmatory factor analyses demonstrated the existence of target‐specific factors, as well as a common ‘individual differences’ factor. Practical and theoretical issues regarding the different sources of item variance are discussed.     

Expert and Public Perception of Risk from Biotechnology

Risk perceptions of a series of biotechnology applications were examined in a public (nonexpert) sample and an expert sample. Compared with the experts, the public perceived all biotechnology applications as more risky. Both groups perceived food-related applications to be riskier than medical applications. Compared with the public, experts perceived both food and medical applications as less harmful and more useful. Experts also judged the risks posed from medical biotechnology applications as more familiar and acknowledged by people and science. Lay estimates of the risk of food applications were predicted by potential harm, potential benefits, science knowledge, and familiarity; experts' estimates were predicted only by harm and benefits. Lay estimates of the risk of medical applications were predicted by potential harm; experts' estimates were predicted by potential benefits, number and type of people exposed, and science knowledge. We discuss the implications of the results for risk communication about and management of different types of biotechnologies.