Coming out of the Therapy Closet: Women’s Disclosure of Same-sex Attraction in Counselling

“Coming out” is a process that same-sex attracted people undergo if they choose to acknowledge it to others. Minimal research exists examining the coming-out experience for same-sex attracted women in counselling settings. This qualitative study addressed the gaps in existing research by exploring counsellors’ perceptions of factors influencing same-sex attracted female clients to disclose their sexual orientation to a counsellor. Semi-structured interviews were conducted with 10 counsellors from diverse clinical backgrounds. In their view, the main factors influencing disclosure were the perceived lesbian, gay, bisexual, and queer (LGBQ) friendliness of a service or counsellor; the presence of LGBQ symbols within services; using gender-neutral language; and the level of a client’s self-acceptance of their sexual orientation. These findings suggest that the utilisation of culturally affirming models by counsellors working with same-sex attracted female clients can create a safe environment for disclosure of sexual orientation.     

Face Preferences for Infant‐ and Adult‐Directed Speakers in Infants of Depressed and Nondepressed Mothers: Association with Infant Cognitive Development

Face preferences for speakers of infant‐directed and adult‐directed speech (IDS and ADS) were investigated in 4‐ to 13.5‐month‐old infants of depressed and nondepressed mothers. Following 1 min of exposure to an ID or AD speaker (order counterbalanced), infants had an immediate paired‐comparison test with a still, silent image of the familiarized versus a novel face. In the test phase, ID face preference ratios were significantly lower in infants of depressed than nondepressed mothers. Infants' ID face preference ratios, but not AD face preference ratios, correlated with their percentile scores on the cognitive (Cog) scale of the Bayley Scales of Infant & Toddler Development (3rd Edition; BSID‐III), assessed concurrently. Regression analyses revealed that infant ID face preferences significantly predicted infant Cog percentiles even after demographic risk factors and maternal depression had been controlled. Infants may use IDS to select social partners who are likely to support and facilitate cognitive development.     

ALL IN THE FAMILY: Red States,Blue States,and Postmodern Family Patterns, 2000 and 2004

In this article, we propose a new way of understanding presidential election outcomes in red and blue states in 2000 and 2004, one that takes into account state‐level variation in postmodern family patterns. Using data from the Statistical Abstract, Census, the American Community Survey, and National Vital Statistics Reports, we construct two measures of state patterns of postmodern family formation (a father‐absent family scale, and a small/delayed family scale). We find that these patterns of postmodern family formation are powerful predictors of states' percentage of votes cast for the Democratic candidate in 2000 and 2004, even after controlling for differences in the composition of states' populations and for differences in states' economic characteristics (rates of economic growth, unemployment, and poverty). We suggest ways that this approach could contribute to the literature on how individual‐level factors, such as demographic characteristics and moral values, shape voting behavior and electoral outcomes.     

'But she didn't say no': an exploration of sibling sexual abuse

Sibling sexual abuse often causes polarities of view in professional and client groups alike. These views range from seeing it as benign to damaging. For professionals new to the field this paper gives an overview of the discussion that sibling sexual abuse is as traumatic as parental sexual abuse, and has lasting impact on its victims. Recognising the particular dynamics of sibling sexual abuse and effect on victims raises the challenge of case management in families where it occurs. This paper will explore this challenge within the New South Wales context.     

Inferential procedures based on the integrated empirical characteristic function

AStA Advances in Statistical Analysis - We introduce the novel notion of the integrated characteristic function and its empirical counterpart. Some basic properties of these new objects are...     

A New Model for Multivariate Markov Chains

We propose a new model for multivariate Markov chains of order one or higher on the basis of the mixture transition distribution (MTD) model. We call it the MTD‐Probit. The proposed model presents two attractive features: it is completely free of constraints, thereby facilitating the estimation procedure, and it is more precise at estimating the transition probabilities of a multivariate or higher‐order Markov chain than the standard MTD model.     

Efficient designs for Bayesian networks with sub-tree bounds

We present upper and lower bounds for information measures, and use these to find the optimal design of experiments for Bayesian networks. The bounds are inspired by properties of the junction tree algorithm, which is commonly used for calculating conditional probabilities in graphical models like Bayesian networks. We demonstrate methods for iteratively improving the upper and lower bounds until they are sufficiently tight. We illustrate properties of the algorithm by tutorial examples in the case where we want to ensure optimality and for the case where the goal is an approximate solution with a guarantee. We further use the bounds to accelerate established algorithms for constructing useful designs. An example with petroleum fields in the North Sea is studied, where the design problem is related to exploration drilling campaigns. All of our examples consider binary random variables, but the theory can also be applied to other discrete or continuous distributions.     

Nonparametric Bayesian analysis for multi-site hidden Markov model

The hidden Markov model (HMM) provides an attractive framework for modeling long-term persistence in a variety of applications including pattern recognition. Unlike typical mixture models, hidden Markov states can represent the heterogeneity in data and it can be extended to a multivariate case using a hierarchical Bayesian approach. This article provides a nonparametric Bayesian modeling approach to the multi-site HMM by considering stick-breaking priors for each row of an infinite state transition matrix. This extension has many advantages over a parametric HMM. For example, it can provide more flexible information for identifying the structure of the HMM than parametric HMM analysis, such as the number of states in HMM. We exploit a simulation example and a real dataset to evaluate the proposed approach.     

A Bayesian Analysis of Synchronous Distance Learning versus Matched Traditional Control in Graduate Biostatistics Courses

Distance learning can be useful for bridging geographical barriers to education in rural settings. However, empirical evidence on the equivalence of distance education and traditional face-to-face (F2F) instruction in statistics and biostatistics is mixed. Despite the difficulty in randomization, we minimized intra-instructor variation between F2F and online sections in seven graduate-level biostatistics service courses in a synchronous (live, real time) fashion; that is, for each course taught in a traditional F2F setting, a separate set of students were taught simultaneously via online learning technology, allowing for two-way interaction between instructor and students. Our primary objective was to compare student performance in the two courses that use these two teaching modes. We used a Bayesian hierarchical model to test equivalence of modes. The frequentist mixed model approach was also conducted for reference. The results of Bayesian and frequentist methods agree and suggest a difference of less than 1% in average final grades. Finally, we discuss barriers to instruction and learning using the applied online teaching technology.     

Envisioning emerging nanotechnologies: a three-year panel study of South Carolina citizens

This article reports results from a three-year panel study of a nonrandom sample of 76 South Carolina citizens, recruited from a variety of walks of life, and their impressions of emerging nanotechnology. This discussion focuses on material from depth interviews conducted alongside a baseline opinion and awareness inventory at the beginning of the study, the most intensive data-gathering phase. These results are placed in the context of data from three additional surveys conducted at about equal intervals over the three years, plus exit interviews from 21 of the 34 individuals who completed the entire study. The results give insight into popular thinking about technology but little indication of strong emerging concerns, a trajectory of amplification of those concerns, or opinion polarization over time, despite some awareness of risks and potential ethical dimensions. Nanotechnology may stand out more as an example of risk attenuation than of risk amplification, consistent with most results from national surveys.