The effect of individual characteristics on susceptibility to aggressive and/or intimidating approaches: quantifying probability pathways by creating a victimization model.

Background: A significant body of literature has identified multiple factors that contribute to established victimization by aggressive and/or intimidating behaviours. These studies primarily originate from the fields of intimate partner violence (IPV), bullying, sexual abuse, and/or commercial sexual exploitation (CSE), and generally focus on female victims. It appears, however, complicated to quantify the cumulative contribution of these factors on susceptibility to intimidating and/or hostile engagements on an individual level.Objective: To develop a comprehensive risk model to quantify, on an individual level, the cumulative effects of previously reported characteristics on susceptibility to aggressive/intimidating approaches, leading to victimization (e.g. in the context of IPV/sexual abuse).Methods: A Bayesian belief network was developed using data from previous studies, capturing the multivariate contribution of previously reported characteristics on the likelihood of becoming victimized by aggressive and/or intimidating approaches (e.g. in the IPV/CSE context) in female victims aged 12-24 years.Results: The model showed that specific combinations of characteristics may contribute to an increased likelihood of victimization (e.g. in the context of IPV/bullying/sexual abuse or CSE). This likelihood could be quantified and categorized into specific clusters of factors differentiating between victimization by physically violent, non-physical, and/or sexual aggressive/intimidating approaches.Conclusion: The present model appears to be the first to successfully quantify the cumulative contribution of individual characteristics on the likelihood of becoming victimized by aggressive and/or intimidating approaches, typically leading to victimization. Moreover, the present scientific effort and resulting model suggest that there may be a latent variable mediating between the implemented factors and overall outcome, i.e. the susceptibility to aggressive and/or intimidating approaches. From that perspective, the model may also be considered as an initial outline to effectively indicate susceptibility to such approaches.

This study constructed a Bayesian belief network of published statistics to quantify the cumulative effects of individual characteristics on victimization (e.g. in the context of IPV/sexual abuse/bullying/CSE).The model showed that the likelihood of victimization following aggressive and/or intimidating approaches could be quantified and categorized into three different features: the likelihood of becoming victimized by physically violent, non-physical, and/or sexual aggressive/intimidating approaches. The likelihood of becoming victimized by physically violent and non-physical aggressive/intimidating approaches seems to be predominantly characterized by risk factors such as depressive symptoms and elevated neuroticism. The likelihood of victimization by sexual intimidating approaches seems to be primarily associated with externalizing risk factors (e.g. impulsivity), strengthened by factors related to previous (negative) sexual experiences and early-onset puberty.This model could be considered as an initial outline to effectively indicate susceptibility to aggressive/intimidating approaches. The model may therefore be considered an applicable framework for future research to further unravel the complicated aggressive and/or intimidating victim­perpetrator interactions related to victimization.

Warm ears, a red flag for sleepiness?

Core body and skin temperatures are intimately linked to sleep and alertness. The distal-to-proximal skin temperature gradient has been described as a good physiological predictor for sleep onset. Increased ear skin temperature is often caused by increased blood flow reflected in redness, which is commonly noticed in people who are sleepy, especially anecdotally in children. Nonetheless, no prior study investigated the possible relation between sleepiness and ear skin temperature as a separate measurement. We assessed the relation between ear skin temperature and sleepiness in patients undergoing regular electroencephalographic examinations, because of suspicion of epilepsy, both without and after sleep deprivation. Subjective sleepiness was measured using the Stanford Sleepiness Scale, and objective sleepiness by determining sleep onset with electroencephalography. Distal, proximal and ear skin temperature were measured repeatedly using wireless measurement devices (iButtons). Forty-four adult patients were included. Ear skin temperature correlates weakly with distal skin temperature (r = 0.174, p < 0.001) and distal-to-proximal gradient (r = 0.160, p < 0.001), but not with proximal skin temperature (r = -0.001, p = 0.975). Ear skin temperature increased significantly in a subgroup of 13 patients, between 5 and 1 min before sleep onset (p = 0.002; η2  = 0.059), even though this increase was also associated with supine posture. iButtons is a valid method to measure ear skin temperature, which appears to function partly like a distal and partly like a proximal skin temperature measurement. Change in ear skin temperature is associated with sleep onset and supine posture.