Cultural pressure and biased responding in free will attitudes

Whether you believe free will exists has profound effects on your behaviour, across different levels of processing, from simple motor action to social cognition. It is therefore important to understand which specific lay theories are held in the general public and why. Past research largely focused on investigating free will beliefs (FWB, ‘Do you think free will exists?’), but largely ignored a second key aspect: free will attitudes (FWA, ‘Do you like/value will?’). Attitudes are often independently predictive of behaviour, relative to beliefs, yet we currently know very little about FWAs in the general public. One key issue is whether such attitudes are subject to biased, socially desirable responding. The vast majority of the general public strongly believes in the existence of free will, which might create cultural pressure to value free will positively as well. In this registered report, we used a very large ( N = 1100), open available dataset measuring implicit and explicit attitudes towards free will and determinism to address this issue. Our results indicate that both explicit and implicit attitudes towards free will are more positive than attitudes towards determinism. We also show that people experience cultural pressure to value free will, and to devalue determinism. Yet, we found no strong evidence that this cultural pressure affected either implicit or explicit attitudes in this dataset.

Methods of Detecting Insufficient Effort Responding: Comparisons and Practical Recommendations

Insufficient effort responding (IER) affects many forms of assessment in both educational and psychological contexts. Much research has examined different types of IER, IER’s impact on the psychometric properties of test scores, and preprocessing procedures used to detect IER. However, there is a gap in the literature in terms of practical advice for applied researchers and psychometricians when evaluating multiple sources of IER evidence, including the best strategy or combination of strategies when preprocessing data. In this study, we demonstrate how the use of different IER detection methods may affect psychometric properties such as predictive validity and reliability. Moreover, we evaluate how different data cleansing procedures can detect different types of IER. We provide evidence via simulation studies and applied analysis using the ACT’s Engage assessment as a motivating example. Based on the findings of the study, we provide recommendations and future research directions for those who suspect their data may contain responses reflecting careless, random, or biased responding.

A computer-based avatar task designed to assess behavioral inhibition extends to behavioral avoidance but not cognitive avoidance

Avoidance is a common feature of post-traumatic stress disorder (PTSD) as well as anxiety and depressive disorders. Avoidance can be expressed behaviorally as well as cognitively. Most personality assessments for avoidance involve self-report inventories which are susceptible to biased responding. The avatar task (Myers et al., 2016a) was developed as an objective measure of behavioral inhibition (BI) which is defined as a tendency for avoidance of unfamiliar people and situations. The avatar task has been demonstrated to screen avoidant behaviors related to BI, PTSD, as well as harm avoidance (HA) as measured by the Tridimensional Personality Questionnaire (TPQ). In the current work, the avatar task was tested with cognitive as well as behavioral avoidance as measured by the cognitive-behavioral avoidance scale (CBAS; Ottenbreit & Dobson, 2004). The CBAS includes four subscales which measure behavioral social (BS) avoidance, behavioral non-social (BN) avoidance, cognitive social (CS) avoidance, and cognitive non-social (CN) avoidance. It was hypothesized that avatar scores would be significantly positively related to behavioral, but not cognitive, avoidance. In addition, it was also hypothesized that performance on the avatar task would be more related to social than non-social behavioral avoidance. Participants completed the avatar task, the HA scale of the TPQ and the CBAS. Pearson’s product moment correlations revealed that avatar scores were significantly related to CBAS total scores as well as BS and BN scores, but not CS and CN scores. In addition, BS has a stronger relationship with avatar scores than BN avoidance which fits with the social aspects of the scenarios in the avatar task. A median split of the avatar scores produced a significant difference in scores on the behavioral but not the cognitive subscales. Overall, the current results supported the idea that the avatar task is measuring behavioral avoidance, specifically in social situations, rather than cognitive avoidance. Future work could adapt the avatar task to include scenarios similar to the cognitive items on the CBAS to create an objective measure of cognitive avoidance which may be relevant in measuring avoidance in depression and behavioral avoidance associated with PTSD as well as anxiety disorders.