Biased interpretation in perfectionism and its modification

Perfectionism is a transdiagnostic construct associated with a range of diagnoses, including depression, eating disorders and obsessive compulsive disorder. Treatments that directly target perfectionist cognitions have been shown to successfully reduce associated pathologies. However, the way in which they do this is not clear. We set out to assess the role of one candidate mechanism of action, namely the cognitive process of interpretation of ambiguity. In one experiment we looked for associations between biased interpretation and perfectionism. In a second, we manipulated interpretations, thereby providing a strong test of their aetiological significance. Results from the first experiment confirmed the presence of biased interpretation in perfectionism and demonstrated that these are highly specific to perfection relevant information, rather than reflecting general negativity. The second experiment succeeded in manipulating these perfection relevant interpretations and demonstrated that one consequence of doing so is a change in perfectionist behaviour. Together, these data experimentally demonstrate that biased interpretation of perfection relevant ambiguity contributes to the maintenance of perfectionism, but that it is also possible to reverse this. Clinical implications include the identification of one likely mechanism of therapeutic change within existing treatments, as well as identification of an appropriate evidence-based focus for future treatment development. Targeting underlying functional mechanisms, such as biased interpretation, has the potential to offer transdiagnostic benefits.     

Developing a measure of interpretation bias for depressed mood: An ambiguous scenarios test

The tendency to interpret ambiguous everyday situations in a relatively negative manner (negative interpretation bias) is central to cognitive models of depression. Limited tools are available to measure this bias, either experimentally or in the clinic. This study aimed to develop a pragmatic interpretation bias measure using an ambiguous scenarios test relevant to depressed mood (the AST-D).¹ In Study 1, after a pilot phase (N = 53), the AST-D was presented via a web-based survey (N = 208). Participants imagined and rated each AST-D ambiguous scenario. As predicted, higher dysphoric mood was associated with lower pleasantness ratings (more negative bias), independent of mental imagery measures. In Study 2, self-report ratings were compared with objective ratings of participants’ imagined outcomes of the ambiguous scenarios (N = 41). Data were collected in the experimental context of a functional Magnetic Resonance Imaging scanner. Consistent with subjective bias scores, independent judges rated more sentences as negatively valenced for the high versus low dysphoric group. Overall, results suggest the potential utility of the AST-D in assessing interpretation bias associated with depressed mood.     

On the power of the test for cluster bias

Cluster bias refers to measurement bias with respect to the clustering variable in multilevel data. The absence of cluster bias implies absence of bias with respect to any cluster‐level (level 2) variable. The variables that possibly cause the bias do not have to be measured to test for cluster bias. Therefore, the test for cluster bias serves as a global test of measurement bias with respect to any level 2 variable. However, the validity of the global test depends on the Type I and Type II error rates of the test. We compare the performance of the test for cluster bias with the restricted factor analysis (RFA) test, which can be used if the variable that leads to measurement bias is measured. It appeared that the RFA test has considerably more power than the test for cluster bias. However, the false positive rates of the test for cluster bias were generally around the expected values, while the RFA test showed unacceptably high false positive rates in some conditions. We conclude that if no significant cluster bias is found, still significant bias with respect to a level 2 violator can be detected with an RFA model. Although the test for cluster bias is less powerful, an advantage of the test is that the cause of the bias does not need to be measured, or even known.     

Cascading effects: the influence of attention bias to threat on the interpretation of ambiguous information

Both attention bias to threat and negative interpretive bias have been implicated in the emergence and maintenance of anxiety disorders. However, relations between attention and interpretive biases remain poorly understood. The current study experimentally manipulated attention bias to threat and examined the effects of attention training on the way ambiguous information was interpreted. Results suggest that the preferential allocation of attention towards threat affects the manner in which ambiguous information is interpreted. Individuals trained to attend to threat were more likely than individuals in a placebo training group to interpret ambiguous information in a threat-related manner. These data suggest that perturbations in the initial stages of information processing associated with anxiety may lead to a cascade of subsequent processing biases.     

The value of RCT evidence depends on the quality of statistical analysis

The authors examined statistical practices in 193 randomized controlled trials (RCTs) of psychological therapies published in prominent psychology and psychiatry journals during 1999-2003. Statistical significance tests were used in 99% of RCTs, 84% discussed clinical significance, but only 46% considered-even minimally-statistical power, 31% interpreted effect size and only 2% interpreted confidence intervals. In a second study, 42 respondents to an email survey of the authors of RCTs analyzed in the first study indicated they consider it very important to know the magnitude and clinical importance of the effect, in addition to whether a treatment effect exists. The present authors conclude that published RCTs focus on statistical significance tests ("Is there an effect or difference?"), and neglect other important questions: "How large is the effect?" and "Is the effect clinically important?" They advocate improved statistical reporting of RCTs especially by reporting and interpreting clinical significance, effect sizes and confidence intervals.     

Automatic optimism: Biased use of base rate information for positive and negative events

People generally judge that positive events will occur in their lives and negative events will not, even when both events have the same objective likelihood to occur. In four studies, we examined the possibility that this optimistic bias is the result of people’s automatic affective reactions to future events. Studies 1 and 2 demonstrate, in two different contexts, that people are consistently optimistic in their predictions, despite identical base rates for positive and negative events. In Study 2, optimistic bias was not influenced by incentives for motivated reasoning or rewards for accuracy, suggesting that bias was the result of automatic processes. Studies 3 and 4 showed that optimistic bias was more pronounced when predictions were speeded and when participants made predictions after exposure to affectively valenced words. Together, these findings suggest that people optimistically interpret base rates and that this optimism is due to an effortless affective process.     

Mad enough to see the other side: Anger and the search for disconfirming information

The current research explored the effect of anger on hypothesis confirmation—the propensity to seek information that confirms rather than disconfirms one's opinion. We argued that the moving against action tendency associated with anger leads angry individuals to seek out more disconfirming information than sad individuals, attenuating the confirmation bias. We tested this hypothesis in two studies of experimentally primed anger and sadness on the selective exposure to hypothesis confirming and disconfirming information. In Study 1, participants in the angry condition were more likely to choose disconfirming information than those in the sad or neutral condition when given the opportunity to read more about a social debate, and reading the disconfirming information affected their subsequent attitude. Study 2 measured participants' opinions and information selection about the 2008 US Presidential Election and their desire to “move against” a person or object. Participants in the angry condition reported a greater tendency to oppose a person or object, which resulted in the attenuation of the confirmation bias.     

Negative interpretation bias as a mechanism of the relationship between rejection sensitivity and depressive symptoms

Rejection sensitivity and negative cognitive biases have been identified as important risk factors for depression. Rejection sensitivity is defined as the tendency to anxiously anticipate, easily perceive, and overreact to rejection. Although prior studies have found an association between one component of rejection sensitivity, the tendency to anxiously anticipate rejection, and depression, little is known about the mechanisms through which anxious anticipation of rejection might confer depression risk. One possibility is that rejection anticipation leads to negatively biased interpretations, a cognitive risk factor for depression. Results from two studies (one cross-sectional, one longitudinal) indicate that negative interpretation biases mediate the association between the anxious anticipation of rejection and depressive symptoms. These findings indicate that interpretation biases represent a mechanism through which anxious anticipation of rejection confers risk for depression, and suggest that interventions designed to challenge negative interpretations may help to decrease depression risk among individuals who anticipate rejection.     

Threat is in the eye of the beholder: social anxiety and the interpretation of ambiguous facial expressions

The current study investigated the tendency of individuals with high levels of social anxiety to interpret ambiguous facial expressions in a threatening manner. Results obtained from self-report measures were consistent with previous studies in which highly socially anxious individuals endorsed threatening interpretations for ambiguous social information. More importantly, highly socially anxious participants showed relative facilitation of processing of threatening faces following neutral faces when a priming technique was used to eliminate artifact due to response selection bias. These findings support the hypothesized social anxiety-linked interpretive bias.     

Social anxiety and interpretation biases for facial displays of emotion: emotion detection and ratings of social cost

The current study assessed the processing of facial displays of emotion (Happy, Disgust, and Neutral) of varying emotional intensities in participants with high vs. low social anxiety. Use of facial expressions of varying intensities allowed for strong external validity and a fine-grained analysis of interpretation biases. Sensitivity to perceiving negative evaluation in faces (i.e., emotion detection) was assessed at both long (unlimited) and brief (60 ms) stimulus durations. In addition, ratings of perceived social cost were made indicating what participants judged it would be like to have a social interaction with a person exhibiting the stimulus emotion. Results suggest that high social anxiety participants did not demonstrate biases in their sensitivity to perceiving negative evaluation (i.e. disgust) in facial expressions. However, high social anxiety participants did estimate the perceived cost of interacting with someone showing disgust to be significantly greater than low social anxiety participants, regardless of the intensity of the disgust expression. These results are consistent with a specific type of interpretation bias in which participants with social anxiety have elevated ratings of the social cost of interacting with individuals displaying negative evaluation.     

Remarks on the test of significance for the method of paired comparisons

A three-component model for comparative judgment which allows for individual differences in preference is proposed. An implication of the model is that errors in the observed proportions due to sampling individuals in paired comparisons experiments are correlated. By neglecting this correlation, Mosteller's test for the method of paired comparisons tends to accept falsely the goodness of fit of the Case V solution. It is shown that bounds may be set for the correlation effect which make a valid test possible in some cases and provide useful standard errors for the estimated affective values.Preparation of this paper has been supported in part by the Quartermaster Food and Container Institute for the Armed Forces. Views and conclusions expressed herein are those of the author and do not necessarily reflect the views or endorsement of the Department of Defense. Comments of one of the reviewers, which substantially improved an earlier version of this paper, are gratefully acknowledged.     

A Single-Session Online Cognitive Bias Modification of Interpretations Modified for Adults With Anxiety and Depressive Symptoms

Anxiety and depression are common, co-occurring, and costly mental health disorders. Cognitive bias modification aims to modify biases to reduce associated symptoms. Few studies have targeted multiple biases associated with both anxiety and depression, and those that have lacked a control condition. This study piloted a single-session online cognitive bias modification (known as CBM-IA) designed to target two biases associated with anxiety and depression—interpretation bias and attribution style—in adults with varying levels of anxiety and depressive symptoms. Participants (18–26 years) with at least mild levels of anxiety/stress and depressive symptoms on the DASS-21 were randomly allocated to an intervention (n = 23) or a control (n = 22) condition. The training consisted of a single-session online CBM-IA to encourage positive interpretations and a positive attribution style.Interpretation bias, attribution style, anxious and depressive mood states, and anxiety, stress and depressive symptoms improved at posttraining and at follow-up, irrespective of condition. Changes in interpretation bias from pre- to posttraining were significantly associated with changes in anxious mood state. CBM-IA, as implemented in this single-session pilot study, did not significantly reduce targeted biases and symptoms compared to a control condition. This adds to the mixed evidence on the efficacy of single-session CBM-I for altering biases and symptoms.     

Threat interpretation in anxious children and their mothers: comparison with nonclinical children and the effects of treatment

Interpretation biases towards threat play a prominent role in cognitive theories of anxiety, and have been identified amongst highly anxious adults and children. Little is known, however, about the development of these cognitive biases although family processes have been implicated. The current study investigated the nature of threat interpretation of anxious children and their mothers through (i) comparison of a clinic and non-clinic population, (ii) analysis of individual differences; and (iii) pre- and post-treatment comparisons. Participants were 27 children with a primary anxiety disorder and 33 children from a non-clinic population and their mothers. Children and mothers completed self-report measures of anxiety and indicated their most likely interpretation of ambiguous scenarios. Clinic and non-clinical groups differed significantly on measures of threat interpretation. Furthermore, mothers' and children's threat interpretation correlated significantly. Following treatment for child anxiety, both children and their mothers reported a reduction in threat interpretation.     

A comparison of normative data for the Trail Making Test from several countries: equivalence of norms and considerations for interpretation

The Trail Making Test may not be equivalent across cultures, i.e., differences in the scores across different cultures may not reveal real differences in the ability of the subjects on the construct being measured. In order to assess this hypothesis, normative samples from ten different countries were compared. Age decade subgroups across samples were ranked based on mean time taken to complete each part of the task. Large Z scores differences were found between these samples when comparing the first with the second, and the last in the rank. These differences were significant even when age and education were comparable across samples. Following Van de Vijver & Tanzer (1997), several possible sources of bias were identified. Incomparability of samples and administration differences were the most likely factors accounting for differences. Because of the lack of validity studies in the countries considered, no firm conclusions could be obtained regarding construct bias. Although the TMT may be measuring visual scanning, psychomotor speed and mental flexibility, normative data from different countries and cultures are not equivalent which might lead to serious diagnostic errors.     

Evaluating correlations in studies of personality and behavior: Beyond the number of significant findings to be expected by chance

When large numbers of statistical tests are computed, such as in broad investigations of personality and behavior, the number of significant findings required before the total can be confidently considered beyond chance is typically unknown. Employing modern software, specially written code, and new procedures, the present article uses three sets of personality data to demonstrate how approximate randomization tests can evaluate (a) the number of significant correlations between a single variable and a large number of other variables, (b) the number of significant correlations between two large sets of variables, and (c) the average size of a large number of effects. Randomization tests can free researchers to fully explore large data sets and potentially have even wider applicability.     

A method of optimal scaling for multivariate ordinal data and its extensions

This paper develops a method of optimal scaling for multivariate ordinal data, in the framework of a generalized principal component analysis. This method yields a multidimensional configuration of items, a unidimensional scale of category weights for each item and, optionally, a multidimensional configuration of subjects. The computation is performed by alternately solving an eigenvalue problem and executing a quasi-Newton projection method. The algorithm is extended for analysis of data with mixed measurement levels or for analysis with a combined weighting of items. Numerical examples and simulations are provided. The algorithm is discussed and compared with some related methods.Earlier results of this research appeared in Saito and Otsu (1983). The authors would like to acknowledge the helpful comments and encouragement of the editor.     

The computerized scoring algorithm for the autobiographical memory test: updates and extensions for analyzing memories of English-speaking adults

ABSTRACT

The Autobiographical Memory Test (AMT) has been central in psychopathological studies of memory dysfunctions, as reduced memory specificity or overgeneralised autobiographical memory has been recognised as a hallmark vulnerability for depression. In the AMT, participants are asked to generate specific memories in response to emotional cue words, and their responses are scored by human experts. Because the manual coding takes some time, particularly when analysing a large dataset, recent studies have proposed computerised scoring algorithms. These algorithms have been shown to reliably discriminate between specific and non-specific memories of English-speaking children and Dutch- and Japanese-speaking adults. The key limitation is that the algorithm is not developed for English-speaking adult memories, which may cover a wider range of vocabulary that the existing algorithm for English-speaking child memories cannot process correctly. In the present study, we trained a new support vector machine to score memories of English-speaking adults. In a performance test (predicting memory specificity against human expert coding), the adult-memory algorithm outperformed the child-memory variant. In another independent performance test, the adult-memory algorithm showed robust performances to score memories that were generated in response to a different set of cues. These results suggest that the adult-memory algorithm reliably scores memory specificity.