Judgements of a 2 × 2 contingency table: Sequential processing and the learning curve

Shanks (1985) has used a video game to investigate how subjects estimate the effect of their behaviour in a task defined by a 2×2 contingency table. The subjects were able to distinguish positive and negative contingencies from zero contingencies. In addition, they showed a learning curve and a bias to rate zero contingencies with a high outcome density higher than low-density zero contingencies. He interpreted these data as being consistent with associative models derived from animal learning. In Experiment 1 we replicated these results using a task and instructions similar to his. In a second experiment we showed that the subjects' tendency to overestimate high-density zero contingencies did not arise because the “game” was so difficult that it interfered with processing the events. In this experiment subjects were given tables of the outcome frequencies that had been determined by the earlier subjects. These subjects were, if anything, less accurate in rating the zero contingencies. We point out several logical problems with Shanks's initial task. The task did not represent a true 2×2 contingency, and aspects of it were physically impossible. In Experiment 3 we modified the task to represent a true 2×2 contingency. Using this task, we found a similar pattern of results, except that there was no evidence of the learning curve predicted by the associative models. We conclude that there is little in our data to rule out a “rule-based” analysis of contingency judgements.     

Policies for life Contributions to family therapy—social policy

We live our lives like chips in a kaleidoscope, always part of patterns that are larger than ourselves and somehow more than the sum of their parts (Minuchin, 1983; p. 3).     

Mathematics—a Critical Filter for STEM-Related Career Choices? A Longitudinal Examination among Australian and U.S. Adolescents

Although women have made progress in entering scientific careers in biology, they remain underrepresented in mathematically intensive fields such as physics. We investigated whether gender differences in mathematics motivation and socialisers’ perceptions impacted choices for diverse STEM careers of varying mathematical intensity. Drawing on expectancy-value theory, we tested structural equation models in which adolescents’ preferred careers related to each of physics, biology, chemistry, and mathematics were predicted by prior mathematical performance, motivations, and mothers’ perceptions. We explored potential differences in gendered processes of influence using multigroup models. Samples were 331 Australian adolescents followed from 9th to 11th grade in 1998 and 277 U.S. adolescents from 9th to 12th grade in 2009–10. In both samples female adolescents preferred biological careers more than males did; male adolescents preferred physics-related careers and also mathematical careers in the Australian sample. Mothers’ perceptions were important to female and male adolescents’ mathematics motivations; gendered motivations were more evident in the Australian sample. Mathematics interest played the strongest role in male adolescents’ preferred careers, whereas actual or perceived mathematical achievements were most important for females, demonstrating the impacts of mathematical motivations on preferences for diverse STEM careers.     

Informed Decision-Making in the Context of Prenatal Chromosomal Microarray

The introduction of chromosomal microarray (CMA) into the prenatal setting has involved considerable deliberation due to the wide range of possible outcomes (e.g., copy number variants of uncertain clinical significance). Such issues are typically discussed in pre-test counseling for pregnant women to support informed decision-making regarding prenatal testing options. This research study aimed to assess the level of informed decision-making with respect to prenatal CMA and the factor(s) influencing decision-making to accept CMA for the selected prenatal testing procedure (i.e., chorionic villus sampling or amniocentesis). We employed a questionnaire that was adapted from a three-dimensional measure previously used to assess informed decision-making with respect to prenatal screening for Down syndrome and neural tube defects. This measure classifies an informed decision as one that is knowledgeable, value-consistent, and deliberated. Our questionnaire also included an optional open-ended question, soliciting factors that may have influenced the participants’ decision to accept prenatal CMA; these responses were analyzed qualitatively. Data analysis on 106 participants indicated that 49% made an informed decision (i.e., meeting all three criteria of knowledgeable, deliberated, and value-consistent). Analysis of 59 responses to the open-ended question showed that “the more information the better” emerged as the dominant factor influencing both informed and uninformed participants’ decisions to accept prenatal CMA. Despite learning about the key issues in pre-test genetic counseling, our study classified a significant portion of women as making uninformed decisions due to insufficient knowledge, lack of deliberation, value-inconsistency, or a combination of these three measures. Future efforts should focus on developing educational approaches and counseling strategies to effectively increase the rate of informed decision-making among women offered prenatal CMA.