ABSTRACT
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.
ABSTRACT
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.