Ante-natal HIV testing: An observational study of HIV test discussion in maternity care

There has been a vociferous call for ante-natal HIV testing but low uptake persists in the UK despite DOH guidelines. The reasons for this are complex, with many studies examining intention, offer and uptake of HIV test but few observing the process to understand the nature of HIV discussion with pregnant women. A field observational study was undertaken where researchers attended 154 ante-natal consultations. These were selected in rotation during ante-natal visits by women at four London hospital based ante-natal clinics. A standardized checklist was utilized to monitor information on HIV. A mean of 1.73 minutes was spent discussing HIV infection and testing during ante-natal consultations which lasted for a mean of 33.1 minutes. Risk factors for HIV were mentioned infrequently. When mentioned they concentrated on sexual behaviour which was raised in 11.7% of the consultations. Potential interventions to reduce vertical transmission were discussed with no more than one in five women and possible adverse implications of HIV testing with fewer than one in ten, the only exception being the implications of a positive diagnosis for the baby. Discussion of interventions was associated with HIV test uptake, but risk discussion was not. The short time spent on discussing HIV testing, combined with paucity of mention of information relevant to pregnancy are issues for concern and probably help to explain the level of uptake in the UK.     

Bayesian model selection of informative hypotheses for repeated measurements

When analyzing repeated measurements data, researchers often have expectations about the relations between the measurement means. The expectations can often be formalized using equality and inequality constraints between (i) the measurement means over time, (ii) the measurement means between groups, (iii) the means adjusted for time-invariant covariates, and (iv) the means adjusted for time-varying covariates. The result is a set of informative hypotheses. In this paper, the Bayes factor is used to determine which hypothesis receives most support from the data. A pivotal element in the Bayesian framework is the specification of the prior. To avoid subjective prior specification, training data in combination with restrictions on the measurement means are used to obtain so-called constrained posterior priors. A simulation study and an empirical example from developmental psychology show that this prior results in Bayes factors with desirable properties.     

Faint-hearted Anti-realism and Knowability

It is often claimed that anti-realists are compelled to reject the inference of the knowability paradox, that there are no unknown truths. I call those anti-realists who feel so compelled ‘faint-hearted’, and argue in turn that anti-realists should affirm this inference, if it is to be consistent. A major part of my strategy in defending anti-realism is to formulate an anti-realist definition of truth according to which a statement is true only if it is verified by someone, at some time. I also liberalize what is meant by a verification to allow for indirect forms of verification. From this vantage point, I examine a key objection to anti-realism, that it is committed to the necessary existence of minds, and reject a response to this problem set forth by Michael Hand. In turn I provide a more successful anti-realist response to the necessary minds problem that incorporates what I call an ‘agential’ view of verification. I conclude by considering what intellectual cost there is to being an anti-realist in the sense I am advocating.     

The Feminizing Effect of Sexual Violence in Third-Party Perceptions of Male and Female Victims

Sex Roles - Various scholars have noted that the label “victim” frequently elicits connotations of stereotypical, passive femininity—especially when the crime entails rape or...     

Approximated adjusted fractional Bayes factors: A general method for testing informative hypotheses

Informative hypotheses are increasingly being used in psychological sciences because they adequately capture researchers’ theories and expectations. In the Bayesian framework, the evaluation of informative hypotheses often makes use of default Bayes factors such as the fractional Bayes factor. This paper approximates and adjusts the fractional Bayes factor such that it can be used to evaluate informative hypotheses in general statistical models. In the fractional Bayes factor a fraction parameter must be specified which controls the amount of information in the data used for specifying an implicit prior. The remaining fraction is used for testing the informative hypotheses. We discuss different choices of this parameter and present a scheme for setting it. Furthermore, a software package is described which computes the approximated adjusted fractional Bayes factor. Using this software package, psychological researchers can evaluate informative hypotheses by means of Bayes factors in an easy manner. Two empirical examples are used to illustrate the procedure.     

Veracity is in the eye of the beholder: A lens model examination of consistency and deception

Research has attempted to explain perceived cues to deception based upon self-report of what participants believe are ‘good’ cues to deception, or self-report of what cues participants say they base their veracity judgements on. However, it is not clear to what extent participants can accurately self-report what influences their decision-making. Using a within-subjects design, 285 participants completed a questionnaire regarding their beliefs about deception before rating a selection of truthful and deceptive statements on a variety of cues. Expert coders also rated the statements for the same cues. Laypeople and expert coders do not conceptualise between-subject consistency in the same way. A lens model showed that whilst perceptions of cues, such as consistency and amount of detail, influence veracity judgements, these perceptions (and overall veracity judgements) are mostly inaccurate. Fundamentally, there seems to be inconsistencies between how deception research examines consistency and how it is understood and used by laypeople.     

The Metacognitive Model of Generalized Anxiety Disorder in Children and Adolescents

Worry is a common phenomenon in children and adolescents, with some experiencing excessive worries that cause significant distress and interference. The metacognitive model of generalized anxiety disorder (Wells 1995, 2009) was developed to explain cognitive processes associated with pathological worry in adults, particularly the role of positive and negative beliefs about worry. This review evaluates the application of the model in understanding child and adolescent worry. Other key issues reviewed include the link between cognitive and metacognitive development and worry, and the measurement of worry and metacognitive worry in young people. Implications of these findings and directions for future research are discussed.