Internet-based interpretation bias modification for social anxiety: A pilot study

BACKGROUND AND OBJECTIVES: The biased interpretation of ambiguous social situations is considered a maintaining factor of Social Anxiety Disorder (SAD). Studies on the modification of interpretation bias have shown promising results in laboratory settings. The present study aims at pilot-testing an Internet-based training that targets interpretation and judgmental bias. METHOD: Thirty-nine individuals meeting diagnostic criteria for SAD participated in an 8-week, unguided program. Participants were presented with ambiguous social situations, were asked to choose between neutral, positive, and negative interpretations, and were required to evaluate costs of potential negative outcomes. Participants received elaborate automated feedback on their interpretations and judgments. RESULTS: There was a pre-to-post-reduction of the targeted cognitive processing biases (d = 0.57-0.77) and of social anxiety symptoms (d = 0.87). Furthermore, results showed changes in depression and general psychopathology (d = 0.47-0.75). Decreases in cognitive biases and symptom changes did not correlate. The results held stable accounting for drop-outs (26%) and over a 6-week follow-up period. Forty-five percent of the completer sample showed clinical significant change and almost half of the participants (48%) no longer met diagnostic criteria for SAD. LIMITATIONS: As the study lacks a control group, results lend only preliminary support to the efficacy of the intervention. Furthermore, the mechanism of change remained unclear. CONCLUSION: First results promise a beneficial effect of the program for SAD patients. The treatment proved to be feasible and acceptable. Future research should evaluate the intervention in a randomized-controlled setting.

A Validation Study on Voter Turnout Bias in Switzerland

Surveys on voting behavior typically overestimate turnout rates substantially. To disentangle different sources of bias - coverage error, nonresponse bias, and overreporting - we conducted a validation study in which respondents' self-reported voting behavior was compared to administrative voting records (N = 2000). Our results show that all three sources of error inflate the survey estimate of the turnout rate and also bias estimates from political participation models, although coverage error is only moderate compared to the more pronounced biases due to nonresponse and overreporting. Furthermore, results from a wording experiment do not provide evidence that revised wording reduces measurement bias.

Effects of stereotypic behaviour and chronic mild stress on judgement bias in laboratory mice

Cognitive processes are influenced by underlying affective states, and tests of cognitive bias have recently been developed to assess the valence of affective states in animals. These tests are based on the fact that individuals in a negative affective state interpret ambiguous stimuli more pessimistically than individuals in a more positive state. Using two strains of mice we explored whether unpredictable chronic mild stress (UCMS) can induce a negative judgement bias and whether variation in the expression of stereotypic behaviour is associated with variation in judgement bias. Sixteen female CD-1 and 16 female C57BL/6 mice were trained on a tactile conditional discrimination test with grade of sandpaper as a cue for differential food rewards. Once they had learned the discrimination, half of the mice were subjected to UCMS for three weeks to induce a negative affective state. Although UCMS induced a reduced preference for the higher value reward in the judgement bias test, it did not affect saccharine preference or hypothalamic–pituitary–adrenal (HPA) activity. However, UCMS affected responses to ambiguous (intermediate) cues in the judgement bias test. While control mice showed a graded response to ambiguous cues, UCMS mice of both strains did not discriminate between ambiguous cues and tended to show shorter latencies to the ambiguous cues and the negative reference cue. UCMS also increased bar-mouthing in CD-1, but not in C57BL/6 mice. Furthermore, mice with higher levels of stereotypic behaviour made more optimistic choices in the judgement bias test. However, no such relationship was found for stereotypic bar-mouthing, highlighting the importance of investigating different types of stereotypic behaviour separately.

An Exploration Based Cognitive Bias Test for Mice: Effects of Handling Method and Stereotypic Behaviour

Behavioural tests to assess affective states are widely used in human research and have recently been extended to animals. These tests assume that affective state influences cognitive processing, and that animals in a negative affective state interpret ambiguous information as expecting a negative outcome (displaying a negative cognitive bias). Most of these tests however, require long discrimination training. The aim of the study was to validate an exploration based cognitive bias test, using two different handling methods, as previous studies have shown that standard tail handling of mice increases physiological and behavioural measures of anxiety compared to cupped handling. Therefore, we hypothesised that tail handled mice would display a negative cognitive bias. We handled 28 female CD-1 mice for 16 weeks using either tail handling or cupped handling. The mice were then trained in an eight arm radial maze, where two adjacent arms predicted a positive outcome (darkness and food), while the two opposite arms predicted a negative outcome (no food, white noise and light). After six days of training, the mice were also given access to the four previously unavailable intermediate ambiguous arms of the radial maze and tested for cognitive bias. We were unable to validate this test, as mice from both handling groups displayed a similar pattern of exploration. Furthermore, we examined whether maze exploration is affected by the expression of stereotypic behaviour in the home cage. Mice with higher levels of stereotypic behaviour spent more time in positive arms and avoided ambiguous arms, displaying a negative cognitive bias. While this test needs further validation, our results indicate that it may allow the assessment of affective state in mice with minimal training— a major confound in current cognitive bias paradigms.

Case-control study of association of maternal recall of diarrhea or use of antimicrobials in the periconceptional period and neural tube defects

In June 1995 a case-control study was initiated by the Texas Department of Health among Mexican American women residing in the fourteen counties of the Texas-Mexico border. Case-women had carried infants with neural tube defect. Control-women had given birth to infants without neural tube defects. The case-control protocol included a general questionnaire which elicited information regarding illnesses experienced and antibiotics taken from three months prior to conception to three months after conception. An assessment of the associations between periconceptional diarrhea and the risk of neural tube defects indicated that the unadjusted association of diarrhea and risk of neural tube defect was significant (OR = 3.3, CI = 1.4–7.6). The unadjusted association of use of oral antimicrobials and risk of neural tube defect was also significant (OR = 3.4, CI = 1.6–7.3). These associations persisted among women who had no fever during the periconceptional period and were present irrespective of folate intake. Diarrhea was associated with an increased risk of NTD independent of use of antimicrobials. The converse was also true; antimicrobials were associated with an increased risk of NTD independent of diarrhea. Further research regarding these potentially modifiable risk factors is warranted. Replication of these findings could result in interventions in addition to folate supplementation. ^

Racial Bias in Motor Vehicle Searches: Additional Theory and Evidence

Knowles, Persico, and Todd (2001) develop a model of police search and offender behavior. Their model implies that if police are unprejudiced the rate of guilt should not vary across groups. Using data from Interstate 95 in Maryland, they find equal guilt rates for African-Americans and whites and conclude that the data is not consistent with racial prejudice against African-Americans. This paper generalizes the model of Knowles, Persico, and Todd by accounting for the fact that potential offenders are frequently not observed by the police and by including two different levels of offense severity. The paper shows that for African-American males the data is consistent with prejudice against African-American males, no prejudice, and reverse discrimination depending on the form of equilibria that exists in the economy. Additional analyses based on stratification by type of vehicle and time of day were conducted, but did not shed any light on the form of equilibria that best represents the situation in Maryland during the sample period.

Fanny Bias als Elise, Rollenbild, in: Jean Aumer: Les Pages du Duc de Vendôme

Signatur des Originals: S 36/G10472

Fanny Bias als Elise, Rollenbild, in: Jean Aumer: Les Pages du Duc de Vendôme, 1. Akt

Signatur des Originals: S 36/G10473

Prior history of atopy or autoimmunity increases risk for alopecia areata

Background. The association between a prior history of atopy or other autoimmune diseases and risk of alopecia areata is not well established. ^ Objective. Purpose of this study was to use the National Alopecia Areata Registry database to further investigate the association between history of atopy or other autoimmune diseases and risk of alopecia areata. ^ Methods. A total of 2,613 self-registered sporadic cases (n = 2,055) and controls (n = 558) were included in the present analysis. ^ Results. Possessing a history of any atopy (OR = 2.00; 95% CI 1.50-2.54) or autoimmune disease (OR = 1.73; 95% CI 1.10-2.72) was associated with an increased risk of alopecia areata. There was no trend for possessing a history of more than one atopy or autoimmune disease and increasing risk of alopecia areata. ^ Limitations. Recall, reporting, and recruiting bias are potential sources of limitations in this analysis. ^ Conclusion. This analysis revealed that a prior history of atopy and autoimmune disease was associated with an increased risk of alopecia areata and that the results were consistent for both the severe subtype of alopecia areata (i.e., alopecia totalis and alopecia universalis) and the localized subtype (i.e., alopecia areata persistent).^

Selection bias and the cross-validation of regression models for prediction

Strategies are compared for the development of a linear regression model with stochastic (multivariate normal) regressor variables and the subsequent assessment of its predictive ability. Bias and mean squared error of four estimators of predictive performance are evaluated in simulated samples of 32 population correlation matrices. Models including all of the available predictors are compared with those obtained using selected subsets. The subset selection procedures investigated include two stopping rules, C$\sb{\rm p}$ and S$\sb{\rm p}$, each combined with an 'all possible subsets' or 'forward selection' of variables. The estimators of performance utilized include parametric (MSEP$\sb{\rm m}$) and non-parametric (PRESS) assessments in the entire sample, and two data splitting estimates restricted to a random or balanced (Snee's DUPLEX) 'validation' half sample. The simulations were performed as a designed experiment, with population correlation matrices representing a broad range of data structures.^ The techniques examined for subset selection do not generally result in improved predictions relative to the full model. Approaches using 'forward selection' result in slightly smaller prediction errors and less biased estimators of predictive accuracy than 'all possible subsets' approaches but no differences are detected between the performances of C$\sb{\rm p}$ and S$\sb{\rm p}$. In every case, prediction errors of models obtained by subset selection in either of the half splits exceed those obtained using all predictors and the entire sample.^ Only the random split estimator is conditionally (on $\\beta$) unbiased, however MSEP$\sb{\rm m}$ is unbiased on average and PRESS is nearly so in unselected (fixed form) models. When subset selection techniques are used, MSEP$\sb{\rm m}$ and PRESS always underestimate prediction errors, by as much as 27 percent (on average) in small samples. Despite their bias, the mean squared errors (MSE) of these estimators are at least 30 percent less than that of the unbiased random split estimator. The DUPLEX split estimator suffers from large MSE as well as bias, and seems of little value within the context of stochastic regressor variables.^ To maximize predictive accuracy while retaining a reliable estimate of that accuracy, it is recommended that the entire sample be used for model development, and a leave-one-out statistic (e.g. PRESS) be used for assessment. ^