A Hierarchical Modeling Approach to Data Analysis and Study Design in a Multi-site Experimental fMRI Study

We propose a hierarchical Bayesian model for analyzing multi-site experimental fMRI studies. Our method takes the hierarchical structure of the data (subjects are nested within sites, and there are multiple observations per subject) into account and allows for modeling between-site variation. Using posterior predictive model checking and model selection based on the deviance information criterion (DIC), we show that our model provides a good fit to the observed data by sharing information across the sites. We also propose a simple approach for evaluating the efficacy of the multi-site experiment by comparing the results to those that would be expected in hypothetical single-site experiments with the same sample size.     

Sun protection behaviour of children and their parents at the beach

Abstract

The present study observed the sun protection behaviour of 8–12 year old children and their parents on the beach. Interviews with children and parents were then conducted to examine possible influences on sun protection and the relationship between observed and self reported behaviour.

The sample consisted of 50 children and 68 parents. All 50 children were observed and interviewed. All the parents were observed and 33 were interviewed. Indices of sun protection cover were computed as a sum of clothing and sunscreen cover. Most parents and children were inadequately covered against the sun. Factors related to children's sun protection included parent's cover and the child's tan level. The relationship between attitude to sun protection and observed behaviour could not be examined as all children and parents indicated they thought it was important to protect their skin against the sun.

Inconsistencies between observed and self-reported sun protection were found for children who were not protecting themselves. The possibility that self-report may overestimate actual protective behaviour is discussed.     

A gendered approach to workforce participation patterns over the life course for an Australian baby boom cohort

Population ageing and its future implications for governments and individuals have been central to much policy debate and research targeted to retain older people in the workforce. This study identified workforce participation patterns across the adult life course for women and men entering later life, and explored the influences of various early and adult life socio-demographic circumstances. Data were collected from 1261 men and women aged 60 to 64 years in the Life History and Health (LHH) Survey (a sub-study of the Sax Institute's 45 and Up Study, Australia) in 2010–11. LHH provides detailed information on personal histories of paid work, socio-economic resources from childhood (number of books and father's occupation) and adult life factors such as educational attainment, marital histories, childcare and informal caring. Latent class analysis (LCA) was undertaken to identify patterns of workforce participation for participants across their adult life. Significant gender differences were confirmed. Further analysis (LCA with covariates) showed that women who reported having books during childhood, and those who had post-school qualification, were more likely to have mostly been in paid work and less likely to have not been in paid work; while ever partnered women had significantly higher odds of increasing part time work over time. Men who had reported ever having had informal caring activities were likely to have had decreasing participation in paid work over time, and were highly likely to be not in paid work after 55 years. Ever partnered status was protective for being in paid work for men. These findings indicate the need for gender-specific policies and strategies to enable continued workforce participation throughout adult life and into later working years, particularly for people who had fewer social or economic opportunities earlier in life.     

When Is Difficult Planning Good Planning? The Effects of Scenario‐Based Planning on Optimistic Prediction Bias

As a general rule, individuals tend to be optimistic in predicting when they will complete an upcoming activity. Building upon the ease of generation theory, we examined how dividing the planning process into multiple steps would impact the magnitude of optimism in “real world” planning. In Experiment 1 we found a decrease in optimistic prediction bias when individuals described their plans by generating a relatively difficult five‐step, rather than a relatively easy two‐step, optimistic scenario. In Experiment 2 the bias diminished when individuals generated the easy, rather than difficult, pessimistic scenario. In Experiment 3 the bias decreased even among individuals who generated the easy, rather than difficult, optimistic scenario when they were led to negatively interpret the feeling of ease.     

Psychological research and the prostate-cancer screening controversy

In October of 2011, the U.S. Preventive Services Task Force released a draft report in which they recommended against using the prostate-specific antigen (PSA) test to screen for prostate cancer. We attempt to show that four factors documented by psychological research can help explain the furor that followed the release of the task force's report. These factors are the persuasive power of anecdotal (as opposed to statistical) evidence, the influence of personal experience, the improper evaluation of data, and the influence of low base rates on the efficacy of screening tests. We suggest that augmenting statistics with facts boxes or pictographs might help such committees communicate more effectively with the public and with the U.S. Congress.