937 resultados para Ingroup Bias


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PURPOSE The objective of this study was to assess the risk of bias of randomized controlled trials (RCTs) published in prosthodontic and implant dentistry journals. MATERIALS AND METHODS The last 30 issues of 9 journals in the field of prosthodontic and implant dentistry (Clinical Implant Dentistry and Related Research, Clinical Oral Implants Research, Implant Dentistry, International Journal of Oral & Maxillofacial Implants, International Journal of Periodontics and Restorative Dentistry, International Journal of Prosthodontics, Journal of Dentistry, Journal of Oral Rehabilitation, and Journal of Prosthetic Dentistry) were hand-searched for RCTs. Risk of bias was assessed using the Cochrane Collaboration's risk of bias tool and analyzed descriptively. RESULTS From the 3,667 articles screened, a total of 147 RCTs were identified and included. The number of published RCTs increased with time. The overall distribution of a high risk of bias assessment varied across the domains of the Cochrane risk of bias tool: 8% for random sequence generation, 18% for allocation concealment, 41% for masking, 47% for blinding of outcome assessment, 7% for incomplete outcome data, 12% for selective reporting, and 41% for other biases. CONCLUSION The distribution of high risk of bias for RCTs published in the selected prosthodontic and implant dentistry journals varied among journals and ranged from 8% to 47%, which can be considered as substantial.

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Why do people take longer to associate the word “love” with outgroup words (incongruent condition) than with ingroup words (congruent condition)? Despite the widespread use of the implicit association test (IAT), it has remained unclear whether this IAT effect is due to additional mental processes in the incongruent condition, or due to longer duration of the same processes. Here, we addressed this previously insoluble issue by assessing the spatiotemporal evolution of brain electrical activity in 83 participants. From stimulus presentation until response production, we identified seven processes. Crucially, all seven processes occurred in the same temporal sequence in both conditions, but participants needed more time to perform one early occurring process (perceptual processing) and one late occurring process (implementing cognitive control to select the motor response) in the incongruent compared with the congruent condition. We also found that the latter process contributed to individual differences in implicit bias. These results advance understanding of the neural mechanics of response time differences in the IAT: They speak against theories that explain the IAT effect as due to additional processes in the incongruent condition and speak in favor of theories that assume a longer duration of specific processes in the incongruent condition. More broadly, our data analysis approach illustrates the potential of electrical neuroimaging to illuminate the temporal organization of mental processes involved in social cognition.

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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.

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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.

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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.

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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.

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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.

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Signatur des Originals: S 36/G10472

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Signatur des Originals: S 36/G10473

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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. ^