Disinformation in the medical field is a growing problem that carries a significant risk. Therefore, it is crucial to detect and combat it effectively. In this article, we provide three elements to aid in this fight: 1) a new framework that collects health-related articles from verification entities and facilitates their check-worthiness and fact-checking annotation at the sentence level; 2) a corpus generated using this framework, composed of 10335 sentences annotated in these two concepts and grouped into 327 articles, which we call KEANE (faKe nEws At seNtence lEvel); and 3) a new model for verifying fake news that combines specific identifiers of the medical domain with triplets subject-predicate-object, using Transformers and feedforward neural networks at the sentence level. This model predicts the fact-checking of sentences and evaluates the veracity of the entire article. After training this model on our corpus, we achieved remarkable results in the binary classification of sentences (check-worthiness F1: 0.749, fact-checking F1: 0.698) and in the final classification of complete articles (F1: 0.703). We also tested its performance against another public dataset and found that it performed better than most systems evaluated on that dataset. Moreover, the corpus we provide differs from other existing corpora in its duality of sentence-article annotation, which can provide an additional level of justification of the prediction of truth or untruth made by the model.

Researchers have identified kinematic differences between deceptive and non-deceptive rugby reorientation actions. However, the honest and deceptive signals corresponded to \'deception detection\' (accuracy increasing) rather than signals that caused deception (accuracy decreasing). In this study, statistical parametric mapping and multilevel modelling were applied to examine the kinematic differences between sidestep and non-deceptive actions during the time window of deception. The analysis compared three-dimensional motion capture data from 144 deceptive actions and 144 genuine actions performed by six high-skilled rugby players. Results indicated that the kinematics of deceptive actions were characterized by a combination of exaggerated head roll, outside foot and centre-of-mass displacement, and attenuated thorax roll and yaw relative to genuine actions. These are candidate sources for the cause of deception, either individually or in combination with other sources. Furthermore, the results indicate that previously identified \'honest\' signals may not be reliable sources of information earlier in the action sequence.

We all lie. Some more than others, and others still have made it a way of life in relationships. There is a fine line between the normal and the pathological. It is certainly more psychologically comfortable to side with the truth than with lies. So what is it that drives the liar to stick to his guns?

Three preregistered studies examined whether 5-year-old children cheat consistently or remain honest across multiple math tests. We observed high consistency in both honesty and cheating. All children who cheated on the first test continued cheating on subsequent tests, with shorter cheating latencies over time. In contrast, 77% of initially honest children maintained honesty despite repeated failure to complete the tests successfully. A brief integrity intervention helped initially honest children remain honest but failed to dissuade initially cheating children from cheating. These findings demonstrate that cheating emerges early and persists strongly in young children, underscoring the importance of early prevention efforts. They also suggest that bolstering honesty from the start may be more effective than attempting to remedy cheating after it has occurred. RESEARCH HIGHLIGHTS: Our research examines whether 5-year-old children, once they have started cheating, will continue to do so consistently. We also investigate whether 5-year-old children who are initially honest will continue to be honest subsequently. We discovered high consistency in both honesty and cheating among 5-year-old children. Almost all the children who initially cheated continued this behavior, while those who were honest stayed honest. A brief integrity-boosting intervention successfully helped 5-year-old children maintain their honesty. However, the same intervention failed to deter cheaters from cheating again. These findings underscore the importance of implementing integrity intervention as early as possible, potentially before children have had their first experience of cheating.

Event-related potentials (ERPs) have been used with the concealed information test (CIT) to detect concealed recognition of specific stimuli (i.e., \"probes\"). While most research has focused on the P300 component, which is larger for infrequent probes than for frequent control stimuli (i.e., \"irrelevants\"), some studies have investigated an earlier ERP component, the anterior N2, with mixed results. Although some studies have reported a larger anterior N2 for probes than irrelevants (N2 enhancement), other studies, including our own, have not found such an effect. The present study aimed to replicate and extend our previous findings using the same CIT paradigm and measurement parameters. Results of Bayesian analyses show strong evidence against the hypothesis of anterior N2 enhancement by probes, replicating our previous work. Bayesian analyses also show strong evidence against the hypothesis of N2 enhancement for the three components revealed by a temporal principal component analysis (PCA) conducted to disentangle potentially overlapping ERP effects. In conclusion, whereas the CIT has shown promise in detecting recognition of specific information, anterior N2 enhancement cannot be used as an electrophysiological measure of concealed information across CIT paradigms.

BACKGROUND: Deceptive movements occur when an actor seeks to fake, hide or delay kinematic information about their true movement outcomes. The purpose of deceptive movements is to impair the perception of opponents (the \'observer\') to gain an advantage over them. We argue though that a lack of conceptual clarity has led to confusion about what deception is and in understanding the different approaches by which an actor can deceive their opponent. The aim of this article is to outline a conceptual framework for understanding deceptive movements in sport.
METHODS: Adopting Interpersonal Deception Theory from the field of communication, we define deception as when an actor deliberately alters their actions in an attempt to impair the ability of an observer to anticipate their true action outcomes. Further, deception can be achieved either by what we define as deceit, the act of providing false information, or disguise, the act of concealing the action outcome. Skilled athletes often have actions that are difficult to anticipate, but an action is only classified as containing deception if the actor has explicit intent to deceive an observer. Having outlined the conceptual framework, we then review existing empirical findings on the skilled perception of deceptive movements considering the framework. This approach includes a critical evaluation of the mechanisms known to facilitate the perceptual ability to prevent being deceived, including a consideration of visual search strategies, confidence, the contribution of visual and motor experiences, and the influence of response biases and action capabilities on perceptual performance.
CONCLUSIONS: The distinction between deceit and disguise particularly helps to show that most research has examined deceit, with little known about how an actor can more effectively disguise their action, or about how an observer can improve their ability to anticipate the outcome of disguised actions. The insights help to identify fruitful areas for future research and outline implications for skill acquisition and performance enhancement.

Cross-situational inconsistency is common in the expression of honesty traits; yet, there is insufficient emphasis on behavioral dishonesty across multiple contexts. The current study aimed to investigate behavioral dishonesty in various contexts and reveal the associations between trait honesty, behavioral dishonesty, and neural patterns of observing others behave honestly or dishonestly in videos (abbr.: (dis)honesty video-watching). First, the results revealed limitations in using trait honesty to reflect variations in dishonest behaviors and predict behavioral dishonesty. The finding highlights the importance of considering neural patterns in understanding and predicting dishonest behaviors. Second, by comparing the predictive performance of seven types of data across three neural networks, the results showed that functional connectivity in the hypothesis-driven network during (dis)honesty video-watching provided the highest predictive power in predicting multitask behavioral dishonesty. Last, by applying the feature elimination method, the midline self-referential regions (medial prefrontal cortex, posterior cingulate cortex, and anterior cingulate cortex), anterior insula, and striatum were identified as the most informative brain regions in predicting behavioral dishonesty. In summary, the study offered insights into individual differences in deception and the intricate connections among trait honesty, behavioral dishonesty, and neural patterns during (dis)honesty video-watching.

Cheating behavior is spreading among nursing students worldwide, necessitating the development of a validated questionnaire evaluating the reasons for such behavior. Nursing students (N = 482) from 2 universities in Saudi Arabia participated in this observational study. A survey containing items on socio-demographics and the 33-item Reasons for Cheating Scale (RCS) was completed by the respondents. The RCS had a 1-factor structure; the model fit indices were similar between the 1-, 2-, and 3-factor models, but the inter-factor correlations were too high for the 2- and 3-factor models. The measures of the quality of the factor score estimates were as follows: factor determinacy index, 0.987; expected a posteriori marginal reliability, 0.974; sensitivity ratio, 6.178; and expected percentage of true differences, 97.3%. The measures of the closeness to unidimensionality for the overall RCS were as follows: unidimensional congruence, 0.957; explained common variance, 0.875; and mean item residual absolute loading, 0.223. The intraclass correlation coefficient and McDonald\'s omega were 0.96 (CI: 0.93-0.98) and 0.962 (95% CI: 0.958-0.967), respectively. The severity score, infit, and outfit ranged from -0.847 to -2.015, 0.813 to 1.742, and 0.837 to 1.661, respectively. For all RCS items, the thresholds ranked τi1 < τi2 < τi3 < τi4 and showed invariance between the sexes. The RCS showed robust psychometric validity for both classical and item response theory parameters. It also had excellent test-retest reliability, internal consistency, item discrimination, factorial validity, measurement invariance, and ordered threshold level for the responses. Therefore, the RCS is a valid and reliable tool for assessing cheating behavior among nursing students.

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