Empirically Defining Treatment Response and Remission in Body Dysmorphic Disorder Using a Short Self-Report Instrument

Determining response or remission status in body dysmorphic disorder (BDD) usually requires a lengthy interview with a trained clinician. This study sought to establish empirically derived cutoffs to define treatment response and remission in BDD using a brief self-report instrument, the Appearance Anxiety Inventory (AAI). Results from three clinical trials of BDD were pooled to create a sample of 123 individuals who had received cognitive-behavioral therapy for BDD, delivered via the Internet. The AAI was compared to gold-standard criteria for response and remission in BDD, based on the clinician-administered Yale–Brown Obsessive Compulsive Scale, modified for BDD (BDD-YBOCS), and evaluated using signal detection analysis. The results showed that a ≥ 40% reduction on the AAI best corresponded to treatment response, with a sensitivity of 0.71 and a specificity of 0.84. A score ≤ 13 at posttreatment was the optimal cutoff in determining full or partial remission from BDD, with a sensitivity of 0.75 and a specificity of 0.88. These findings provide benchmarks for using the AAI in BDD treatment evaluation when resource-intensive measures administered by clinicians are not feasible.     

The verifiability approach to deception detection: A preregistered direct replication of the information protocol condition of Nahari,Vrij, and Fisher (2014b)

Nahari, Vrij, and Fischer [(2014b), Applied Cognitive Psychology, 28, 122–128] found that, when participants were forewarned that their statements would be checked for verifiable details, truth tellers gave much more verifiable details than liars. In this direct replication (n = 72), participants wrote a statement claiming they had carried out their regular campus activities, whereas liars had actually stolen an exam. Statements were coded for verifiable details. Our primary prediction was confirmed: Truth tellers provided significantly more verifiable details than liars. Of note, the replication effect size (d = 0.49) was less than half that of the original (d = 1.14), and – like in the original study – was smaller than the lie‐truth effect size for total details (verifiable and unverifiable details combined; d = 0.80). We hope this will stimulate other independent investigations of VA to tell whether or not coding for verifiability will pass Ockham's razor test.     

Can bottom-up processes of attention be a source of ‘interference’ in situations where top-down control of attention is crucial?

In this study, we investigate whether emotionally engaged bottom-up processes of attention can be a source of ‘interference’ in situations where top-down control of attention is necessary. Participants were asked to monitor and report on a video of a war scenario showing a developing battle in two conditions: emotionally positive and emotionally negative. Half of the participants (n = 15) were exposed to task-irrelevant pictures of positive emotional valence embedded within the scenario; the other half were exposed to task-irrelevant pictures of negative emotional valence. Sensitivity and Bias scores were calculated using signal detection theory. Overall, task accuracy scores were dependent upon the valence; negative pictures had an adverse effect on performance, whereas positive pictures improved performance. We concluded that negative emotional pictures interfered with top-down control of attention by attracting competing bottom-up processes of attention. We found the opposite effect for positive emotional stimuli.     

Developing ways to encourage early detection and presentation of oral cancer: What do high-risk individuals think?

The aim of this pilot research was to improve understanding of individuals at risk of oral cancer, to determine their attitudes towards and responses to early detection interventions. In-depth interviews with the target group (n?=?25) were used to determine their views, attitudes and requirements for an intervention to encourage early detection of oral cancer. This data was used in combination with theory-based constructs to develop written material that aimed to increase awareness of oral cancer, encourage mouth self-examination (MSE) and early presentation. A second pilot study used a think-aloud protocol to assess the target groups’ (n?=?14) reactions to the written information. In both studies the tape-recorded responses were analysed using framework analysis. The target group had limited knowledge about oral cancer, particularly the signs and symptoms. Participants saw benefits in performing MSE but noted the main barriers were not knowing what signs to look for or where to look. The written information was generally well-received but required some modifications. In particular, the target group required further persuasion that their lifestyle contributed to an increased risk of oral cancer. The results of these pilot studies have informed the development of a theory-based intervention for the early detection of oral cancer.     

Reinstating effortful encoding operations at test enhances episodic remembering

Two experiments investigated the effects of reinstating encoding operations on remember and know responses in recognition memory. Experiment 1 showed that reinstating an effortful encoding task (generating words from fragments) increased remember responses at test but reinstating an automatic encoding task (reading intact words) did not. This pattern was confirmed in Experiment 2 in which words were either read intact or generated from anagrams. These findings show that repeating effortful (but not automatic) encoding operations at test cues not only the recognition of the information that was acquired via those operations but also the conscious recollection of the encoding episode.     

Category length produces an inverted-U discriminability function in episodic recognition memory

Four experiments used signal detection analyses to assess recognition memory for lists of words consisting of differing numbers of exemplars from different semantic categories. The results showed that recognition memory performance, measured by d _a , (a) increased as category length (CL, the number of study-list items selected from the same semantic category) increased from 1 to 8 but then decreased as CL further increased from 8 to 14, (b) was greater when 2 studied items from the same category occurred back to back, rather than being separated by 5–11 items from other categories, and (c) was greater for the first studied 2 exemplars than for the last studied 2 exemplars from blocked categories with CLs of 8 or 14. For all CLs, all z-coordinate receiver operating characteristic (z-ROC) functions were linear with slopes significantly less than 1.0, and none had a significant quadratic component. These results pose a challenge for three major classes of recognition memory models: item-noise, context-noise, and dual-process models.     

An Intelligence Survey of a Typical Town School

In this study, the authors investigated the relation between early social contingency experiences and infants' competencies to detect nonsocial contingencies. In this study of 87 three-month-old infants, the authors operationalized early social contingencies as prompt, contingent maternal responses and coded microanalytically on the basis of video-recorded mother-infant interactions. The authors assessed competence to detect nonsocial contingencies by 2 methods: (a) the mobile conjugate reinforcement paradigm, which focuses on detecting contingencies between the infants' actions (kicking) and nonsocial consequences (mobile moving) and (b) the visual expectation paradigm, which focuses on detecting contingencies between 1 event (a smiley face projected on a screen) that was followed by a 2nd event (a complex picture projected on the other side of the screen). The results showed that early social contingencies are related to the competency to detect nonsocial action-consequence contingencies in the mobile conjugate reinforcement paradigm.     

A novel method for assessing rival models of recognition memory

A general comparison is made between the multinomial processing tree (MPT) approach and a strength-based approach for modeling recognition memory measurement. Strength models include the signal-detection model and the dual-process model. Existing MPT models for recognition memory and a new generic MPT model, called the Multistate (MS) model, are contrasted with the strength models. Although the ROC curves for the MS model and strength model are similar, there is a critical difference between existing strength models and MPT models that goes beyond the assessment of the ROC. This difference concerns the question of stochastic mixtures for foil test trials. The hazard function and the reverse hazard function are powerful methods for detecting the presence of a probabilistic mixture. Several new theorems establish a novel method for obtaining information about the hazard function and reverse hazard function for the latent continuous distributions that are assumed in the strength approach to recognition memory. Evidence is provided that foil test trials involve a stochastic mixture. This finding occurred for both short-term memory procedures, such as the Brown–Peterson task, and long-term list-learning procedures, such as the paired-associate task. The effect of mixtures on foil trials is problematic for existing strength models but can be readily handled by MPT models such as the MS model. Other phenomena, such as the mirror effect and the effect of target-foil similarity, are also predicted accurately by the MPT modeling framework.     

Signal detection models for the same–different task

Signal detection models for the same–different task are presented. In contrast to the standard approach that only considers the proportion correct, the models apply to the full four by two same–different table. The approach allows one to consider models that recognize bias and other effects. Two basic signal detection models, associated with different decision rules, are presented. A version of the covert decisions rule is introduced that directly allows for same–different bias, in contrast to earlier versions. It is shown how to fit the models with standard software for nonlinear mixed models. The models are applied to data from a recent same–different study.