Nudging intensive care unit personnel towards sustainable behaviour.

BACKGROUND: The health care sector is among the most carbon-intensive sectors, contributing to societal problems like climate change. Previous research demonstrated that especially the use of personal protective equipment (e.g., aprons) in critical care contributes to this problem. To reduce personal protective equipment waste, new sustainable policies are needed. AIMS: Policies are only effective if people comply. Our aim is to examine whether compliance with sustainable policies in critical care can be increased through behavioural influencing. Specifically, we examined the effectiveness of two sets of nudges (i.e., a Prime + Visual prompt nudge and a Social norm nudge) on decreasing apron usage in an intensive care unit (ICU). STUDY DESIGN: We conducted a field experiment with a pre- and post-intervention measurement. Upon the introduction of the new sustainable policy, apron usage data were collected for 9 days before (132 observations) and 9 days after (114 observations) the nudge interventions were implemented. RESULTS: Neither the Prime + Visual prompt nudge, nor the Social norm nudge decreased apron usage. CONCLUSIONS: While previous studies have found that primes, visual nudges and social norm nudges can increase sustainable behaviour, we did not find evidence for this in our ICU field experiment. Future research is needed to determine whether this null finding reflects reality, or whether it was due to methodological decisions and limitations of the presented experiment. RELEVANCE TO CLINICAL PRACTICE: The presented study highlights the importance of studying behavioural interventions that were previously proven successful in the lab and in other field contexts, in the complex setting of critical care. Results previously found in other contexts may not generalize directly to a critical care context. The unique characteristics of the critical care context also pose methodological challenges that may have affected the outcomes of this experiment.

Mining Bodily Cues to Deception.

A significant body of research has investigated potential correlates of deception and bodily behavior. The vast majority of these studies consider discrete, subjectively coded bodily movements such as specific hand or head gestures. Such studies fail to consider quantitative aspects of body movement such as the precise movement direction, magnitude and timing. In this paper, we employ an innovative data mining approach to systematically study bodily correlates of deception. We re-analyze motion capture data from a previously published deception study, and experiment with different data coding options. We report how deception detection rates are affected by variables such as body part, the coding of the pose and movement, the length of the observation, and the amount of measurement noise. Our results demonstrate the feasibility of a data mining approach, with detection rates above 65%, significantly outperforming human judgement (52.80%). Owing to the systematic analysis, our analyses allow for an understanding of the importance of various coding factor. Moreover, we can reconcile seemingly discrepant findings in previous research. Our approach highlights the merits of data-driven research to support the validation and development of deception theory.

Pain, Culture and Pedagogy: A Preliminary Investigation of Attitudes Towards "Reasonable" Pain Tolerance in the Grassroots Reproduction of a Culture of Risk.

In recent years a considerable body of psychological research has explored the relationship between membership of socio-cultural groups and personal pain perception. Rather less systematic attention has, however, been accorded to how such group membership(s) might influence individual attitudes towards the pain of others. In this paper, immersion in the culture of competitive sport, widely regarded as being exaggeratedly tolerant of risky behaviours around pain, is taken as a case-in-point with students of Physical Education (PE) in tertiary education as the key focus. PE students are highly-immersed in competitive sporting culture both academically and (typically) practically, and also represent a key nexus of cross-generational transmission regarding the norms of sport itself. Their attitudes towards the pain that others should reasonably tolerate during a range of activities, sporting and otherwise, were evaluated through a direct comparison with those of peers much less immersed in competitive sporting culture. In total, N=301 (144 PE, 157 non-PE) undergraduate students in the UK responded to a vignette-based survey. Therein, all participants were required to rate the pain (on a standard 0-10 scale) at which a standardised "other" should desist engagement with a set of five defined sporting and non-sporting tasks, each with weak and strong task severities. Results indicated that PE students were significantly more likely to expect others to persevere through higher levels of pain than their non-PE peers, but only during the sport-related tasks - an effect further magnified when task severity was high. In other tasks, there was no significant difference between groups, or valence of the effect was actually reversed. It is argued that the findings underscore some extant knowledge about the relationship between acculturated attitudes to pain, while also having practical implications for understanding sport-based pedagogy, and its potentially problematic role in the ongoing reproduction of a "culture of risk."

A Personal Model of Trumpery: Linguistic Deception Detection in a Real-World High-Stakes Setting.

Language use differs between truthful and deceptive statements, but not all differences are consistent across people and contexts, complicating the identification of deceit in individuals. By relying on fact-checked tweets, we showed in three studies (Study 1: 469 tweets; Study 2: 484 tweets; Study 3: 24 models) how well personalized linguistic deception detection performs by developing the first deception model tailored to an individual: the 45th U.S. president. First, we found substantial linguistic differences between factually correct and factually incorrect tweets. We developed a quantitative model and achieved 73% overall accuracy. Second, we tested out-of-sample prediction and achieved 74% overall accuracy. Third, we compared our personalized model with linguistic models previously reported in the literature. Our model outperformed existing models by 5 percentage points, demonstrating the added value of personalized linguistic analysis in real-world settings. Our results indicate that factually incorrect tweets by the U.S. president are not random mistakes of the sender.

A liar and a copycat: nonverbal coordination increases with lie difficulty.

Studies of the nonverbal correlates of deception tend to examine liars' behaviours as independent from the behaviour of the interviewer, ignoring joint action. To address this gap, experiment 1 examined the effect of telling a truth and easy, difficult and very difficult lies on nonverbal coordination. Nonverbal coordination was measured automatically by applying a dynamic time warping algorithm to motion-capture data. In experiment 2, interviewees also received instructions that influenced the attention they paid to either the nonverbal or verbal behaviour of the interviewer. Results from both experiments found that interviewer-interviewee nonverbal coordination increased with lie difficulty. This increase was not influenced by the degree to which interviewees paid attention to their nonverbal behaviour, nor by the degree of interviewer's suspicion. Our findings are consistent with the broader proposition that people rely on automated processes such as mimicry when under cognitive load.

To freeze or not to freeze: A culture-sensitive motion capture approach to detecting deceit.

We present a new signal for detecting deception: full body motion. Previous work on detecting deception from body movement has relied either on human judges or on specific gestures (such as fidgeting or gaze aversion) that are coded by humans. While this research has helped to build the foundation of the field, results are often characterized by inconsistent and contradictory findings, with small-stakes lies under lab conditions detected at rates little better than guessing. We examine whether a full body motion capture suit, which records the position, velocity, and orientation of 23 points in the subject's body, could yield a better signal of deception. Interviewees of South Asian (n = 60) or White British culture (n = 30) were required to either tell the truth or lie about two experienced tasks while being interviewed by somebody from their own (n = 60) or different culture (n = 30). We discovered that full body motion-the sum of joint displacements-was indicative of lying 74.4% of the time. Further analyses indicated that including individual limb data in our full body motion measurements can increase its discriminatory power to 82.2%. Furthermore, movement was guilt- and penitential-related, and occurred independently of anxiety, cognitive load, and cultural background. It appears that full body motion can be an objective nonverbal indicator of deceit, showing that lying does not cause people to freeze.

When Lying Feels the Right Thing to Do.

Fraud is a pervasive and challenging problem that costs society large amounts of money. By no means all fraud is committed by 'professional criminals': much is done by ordinary people who indulge in small-scale opportunistic deception. In this paper, we set out to investigate when people behave dishonestly, for example by committing fraud, in an online context. We conducted three studies to investigate how the rejection of one's efforts, operationalized in different ways, affected the amount of cheating and information falsification. Study 1 demonstrated that people behave more dishonestly when rejected. Studies 2 and 3 were conducted in order to disentangle the confounding factors of the nature of the rejection and the financial rewards that are usually associated with dishonest behavior. It was demonstrated that rejection in general, rather than the nature of a rejection, caused people to behave more dishonestly. When a rejection was based on subjective grounds, dishonest behavior increased with approximately 10%, but this difference was not statistically significant. We subsequently measured whether dishonesty was driven by the financial loss associated with rejection, or emotional factors such as a desire for revenge. We found that rejected participants were just as dishonest when their cheating did not led to financial gain. However, they felt stronger emotions when there was no money involved. This seems to suggest that upon rejection, emotional involvement, especially a reduction in happiness, drives dishonest behavior more strongly than a rational cost-benefit analysis. These results indicate that rejection causes people to behave more dishonestly, specifically in online settings. Firms wishing to deter customers and employees from committing fraud may therefore benefit from transparency and clear policy guidelines, discouraging people to submit claims that are likely to be rejected.

AMAB: automated measurement and analysis of body motion.

Technologies that measure human nonverbal behavior have existed for some time, and their use in the analysis of social behavior has become more popular following the development of sensor technologies that record full-body movement. However, a standardized methodology to efficiently represent and analyze full-body motion is absent. In this article, we present automated measurement and analysis of body motion (AMAB), a methodology for examining individual and interpersonal nonverbal behavior from the output of full-body motion tracking systems. We address the recording, screening, and normalization of the data, providing methods for standardizing the data across recording condition and across subject body sizes. We then propose a series of dependent measures to operationalize common research questions in psychological research. We present practical examples from several application areas to demonstrate the efficacy of our proposed method for full-body measurements and comparisons across time, space, body parts, and subjects.