Impact of interaction with a partner or friend on the exposure effects of pornography and erotica

Past studies on the effects of sexually explicit materials on women have tended to study them alone, in pairs, or in groups of strangers. By contrast, our study randomly assigned women to bring either a same-sex friend or a male partner to reflect more natural viewing conditions. Discussion between the participant and her companion followed exposure to the sexual images. Women who viewed pornography maintained their (quite high) level of negative mood, whereas women who viewed erotica experienced a substantial improvement in mood. The sex of the companion did not have a direct influence on participants' mood, with discussion improving mood across the board. However, participants' ratings of their satisfaction with the discussion were significantly influenced by the sex of their companion. We suggest that future research should focus more on the interpersonal aspects of male-female relationships when exploring the effects of sexually explicit materials on heterosexual women.     

Heuristic methods for the analysis of managerial problems

Problem analysis is a critical element of managerial problem solving that has not been included in or explicated by traditional stage models of the process. This paper argues that an analysis stage is needed to develop the implications of a problem's definition and to direct the selection and pursuit of solution strategies. Problem analysis is a beuristic activity. The paper explains and applies seven heuristic methods of analysis to a classic management case, generating a richer understanding and broader set of solution alternatives. Strategies for future research on problem analysis are discussed.     

Sharp tongues and bitter pills

How bad is big pharma? An American medical journal has taken draconian measures to vet analyses of clinical trials sponsored by the pharmaceutical industry. Are their statistics so bad? Stephen Senn has a look at the controversy.     

Power and sample size when multiple endpoints are considered

A common approach to analysing clinical trials with multiple outcomes is to control the probability for the trial as a whole of making at least one incorrect positive finding under any configuration of true and false null hypotheses. Popular approaches are to use Bonferroni corrections or structured approaches such as, for example, closed-test procedures. As is well known, such strategies, which control the family-wise error rate, typically reduce the type I error for some or all the tests of the various null hypotheses to below the nominal level. In consequence, there is generally a loss of power for individual tests. What is less well appreciated, perhaps, is that depending on approach and circumstances, the test-wise loss of power does not necessarily lead to a family wise loss of power. In fact, it may be possible to increase the overall power of a trial by carrying out tests on multiple outcomes without increasing the probability of making at least one type I error when all null hypotheses are true. We examine two types of problems to illustrate this. Unstructured testing problems arise typically (but not exclusively) when many outcomes are being measured. We consider the case of more than two hypotheses when a Bonferroni approach is being applied while for illustration we assume compound symmetry to hold for the correlation of all variables. Using the device of a latent variable it is easy to show that power is not reduced as the number of variables tested increases, provided that the common correlation coefficient is not too high (say less than 0.75). Afterwards, we will consider structured testing problems. Here, multiplicity problems arising from the comparison of more than two treatments, as opposed to more than one measurement, are typical. We conduct a numerical study and conclude again that power is not reduced as the number of tested variables increases.     

Maximum likelihood estimation of treatment effects for samples subject to cregression to the mean

A general maximum likelihood approach for estimating the effects of treatments applied to samples subject to regression to the mean is outlined. Models may be specified in terms of three factors: whether the treatment effect is multiplicative or additive, whether the treatment group is above or below some truncation point and the type of sample involved. The way in which solutions may be obtained for all 16 models so defined is described.     

R&D productivity rides again?

A recent analysis of R&D productivity suggests that there are grounds for ‘cautious optimism’ that the industry ‘turned the corner’ in 2008 and is ‘on the comeback trail’. We believe that this analysis is flawed and most probably wrong. We present an alternative analysis of these same data to suggest that the industry is not yet ‘out of the woods’ and suggest that many of the systemic issues affecting pharmaceutical R&D productivity are still being resolved. Copyright © 2014 John Wiley & Sons, Ltd.     

What’s the Confusion About Fusion?—Differentiating Positive and Negative Closeness in Lesbian Relationships

This study differentiated between closeness and fusion in lesbian relationships, and examined whether age, adult attachment style, social support, outness, and relationship satisfaction were associated with these variables. Participants consisted of 77 women in long-term, lesbian relationships. Overall, women who reported showing greater closeness toward their partners were more satisfied in their relationships. Age and attachment style were better predictors of closeness and fusion than were social support and outness. The theoretical implications of these findings are discussed. Findings highlight the need for therapists to distinguish between positive and negative types of closeness in lesbian relationships, and avoid pathologizing high levels of closeness in lesbian relationships simply because they may deviate from a heterosexual norm.