Factors influencing prescribing decisions in the treatment of depression: a social judgement theory approach

The under‐diagnosis and inappropriate treatment of depression in primary care has become a serious public health problem despite the development of many clinical guidelines to guide recognition and treatment of the disorder. This study aims to investigate decision‐making processes and to identify factors which influence general practitioners' (GPs) prescribing decisions and how these factors differ from those the guidelines recommend. Brunswik's lens model, from Social Judgement Theory (SJT), was employed to explore individual treatment decision policies of 40 GPs in the Grampian region of Scotland for 20 case vignettes. These individual policies were then aggregated and compared with those derived from guideline recommendations; important differences emerged between the two in the utilization of cues and there was considerable variation between GPs' policies. Guidelines placed more importance on the duration of symptoms whereas GPs gave weight also to particular symptoms, such as ‘thoughts of suicide’ and ‘sleep disturbance’ and patient treatment preference. GPs prescribed antidepressants at a greater rate than was recommended by the guidelines. The findings have important implications for implementation strategies, which maybe developed to accompany clinical guidelines. Copyright © 2002 John Wiley & Sons, Ltd.     

A Unification of Two Approaches to Vagueness: The Boolean Many-Valued Approach and the Modal-Precisificational Approach

The Boolean many-valued approach to vagueness is similar to the infinite-valued approach embraced by fuzzy logic in the respect in which both approaches seek to solve the problems of vagueness by assigning to the relevant sentences many values between falsity (or 0) and truth (or 1), but while the fuzzy-logic approach postulates linearly-ordered values (or ‘degrees’) between 0 and 1, the Boolean approach assigns to sentences values in a many-element (including infinite-element) complete Boolean algebra. On the modal-precisificational approach represented by Kit Fine, if a (vague) sentence is indeterminate in truth value in some world (possibly the actual world), it is taken to be true in one precisified world accessible from that world and false in another. This paper points to a way to unify these two approaches to vagueness by showing that Fine’s version of the modal-precisificational approach can be combined with the Boolean many-valued approach instead of supervaluationism, one of the most popular approaches to vagueness.     

Physical Attractiveness,Altruism and Cooperation in an Ultimatum Game

Explaining cooperative tendencies through an evolutionary lens has been problematic for theorists. Traditional explanations derive from theories of reciprocity, biological markets, and more recently via partner choice and sexual selection. The sexual selection hypothesis has been tested within game-theoretic frameworks gaining empirical support in explaining the evolution of altruism. Males have been found to be more altruistic towards attractive females. However, previous research has predominantly adopted a design where participants are not engaging with ‘real people’. Instead, participants make decisions when viewing images or hypothetical scenarios without visual cues. The present study aimed to investigate the sexual selection hypothesis using a face-to-face game theoretic framework. One hundred and thirty-eight participants played a 2-round ultimatum game with chocolate coins as the monetary incentive. We find, that physical attractiveness had no influence on generosity and cooperation when participants play a face-to-face ultimatum game. Instead, proposers were fair when allocating stakes, offering an average of half the endowment to responders. This study refutes the link between the sexual selection hypothesis and generosity when playing economic games with real people. Fairness appeared to drive generosity and cooperation.     

Virtual reality cue reactivity assessment in cigarette smokers.

Drug craving has purportedly been linked to relapse and to substance use. For over two decades, cue reactivity has been a viable method to assess craving and physiological reactions to drug stimuli. However, traditional cue reactivity has faced the following limitations: austere situations or stimuli, lack of complex cues, lack of standardization, and limited generalization outside of the lab setting. In order to improve cue methodologies, a virtual reality (VR) nicotine cue reactivity assessment system (VR-NCRAS) was developed and tested in a controlled experimental trial. Ten nicotine dependent smokers were exposed to VR smoking cues and VR neutral cues in a standardized, timed, computer controlled experiment. Subjective craving and physiological responses were recorded and compared across VR-NCRAS stimuli. Subjective cigarette craving increased significantly and corresponding physiological reactivity was observed in response to VR smoking cues. VR neutral cues did not result in subjective or physiological changes consistent with craving. Implications of these findings on substance abuse research and treatment are discussed.     

Accuracy in parameter estimation for targeted effects in structural equation modeling: sample size planning for narrow confidence intervals

In addition to evaluating a structural equation model (SEM) as a whole, often the model parameters are of interest and confidence intervals for those parameters are formed. Given a model with a good overall fit, it is entirely possible for the targeted effects of interest to have very wide confidence intervals, thus giving little information about the magnitude of the population targeted effects. With the goal of obtaining sufficiently narrow confidence intervals for the model parameters of interest, sample size planning methods for SEM are developed from the accuracy in parameter estimation approach. One method plans for the sample size so that the expected confidence interval width is sufficiently narrow. An extended procedure ensures that the obtained confidence interval will be no wider than desired, with some specified degree of assurance. A Monte Carlo simulation study was conducted that verified the effectiveness of the procedures in realistic situations. The methods developed have been implemented in the MBESS package in R so that they can be easily applied by researchers.     

Control of a virtual vehicle influences postural activity and motion sickness

Everyday experience suggests that drivers are less susceptible to motion sickness than passengers. In the context of inertial motion (i.e., physical displacement), this effect has been confirmed in laboratory research using whole body motion devices. We asked whether a similar effect would occur in the context of simulated vehicles in a visual virtual environment. We used a yoked control design in which one member of each pair of participants played a driving video game (i.e., drove a virtual automobile). A recording of that performance was viewed (in a separate session) by the other member of the pair. Thus, the two members of each pair were exposed to identical visual motion stimuli, but the risk of behavioral contagion was minimized. Participants who drove the virtual vehicle (drivers) were less likely to report motion sickness than participants who viewed game recordings (passengers). Data on head and torso movement revealed that drivers tended to move more than passengers, and that the movements of drivers were more predictable than the movements of passengers. Before the onset of subjective symptoms of motion sickness movement differed between participants who (later) reported motion sickness and those who did not, consistent with a prediction of the postural instability theory of motion sickness. The results confirm that control is an important factor in the etiology of motion sickness and extend this finding to the control of noninertial virtual vehicles.     

Visual discrimination,sequential learning and memory retrieval in the Australian desert ant <Emphasis Type="Italic">Melophorus bagoti</Emphasis>

Bees, wasps and ants—so-called central-place foragers—need potent homing strategies to return to their nest. Path integration and view-based landmark guidance are the key strategies for the ants’ navigation. For instance, they memorise different views in a sequence (sequential memory) but also have a step counter that informs them about the covered distance during each foraging trip (odometer). The sequential memory and the odometer information can act as contextual cues during travel for retrieving the appropriate stored view. When and which cue is used at different stages and lengths of the foraging trips is still unknown. In this study, we examined how the Australian desert ant Melophorus bagoti uses sequential memory and odometric information to retrieve visual memories. Using a set-up made out of channels and two-choice boxes (Y-mazes), we demonstrate first that M. bagoti foragers are able to learn and discriminate a variety of visual stimuli in a sequence of views along the inbound trip back to the nest. We then forced the homing ants to encounter a fixed sequence of two visual patterns during their inbound trips. By manipulating the position and distance of the visual stimuli and decision boxes, we could set the two contextual cues (sequential memory and odometer) into conflict. After the short 4-m outbound distance, a preference for odometric information as a contextual cue was found, but after the long 8-m outbound distance, ants relied primarily on their sequential memory retrieval. Odometer precision deteriorates with increasing travel distance, and accordingly, our findings imply that desert ants may be relying on the most reliable contextual cue for retrieving visual memories.