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XRIndex: a brief screening tool for individual differences in security threat detection in x-ray images.

Rusconi E, Ferri F, Viding E, Mitchener-Nissen T - Front Hum Neurosci (2015)

Bottom Line: The results show that the Attention to Detail score from the autism-spectrum quotient (AQ) questionnaire (Baron-Cohen et al., 2001) is a linear predictor of threat detection accuracy.The XRIndex is not redundant with any of the Big Five personality traits.Further studies are needed to determine whether this can also apply to trained professionals.

View Article: PubMed Central - PubMed

Affiliation: Department of Security and Crime Science, University College London London, UK ; Department of Neurosciences, University of Parma Parma, Italy ; Division of Psychology, Abertay University Dundee, UK.

ABSTRACT
X-ray imaging is a cost-effective technique at security checkpoints that typically require the presence of human operators. We have previously shown that self-reported attention to detail can predict threat detection performance with small-vehicle x-ray images (Rusconi et al., 2012). Here, we provide evidence for the generality of such a link by having a large sample of naïve participants screen more typical dual-energy x-ray images of hand luggage. The results show that the Attention to Detail score from the autism-spectrum quotient (AQ) questionnaire (Baron-Cohen et al., 2001) is a linear predictor of threat detection accuracy. We then develop and fine-tune a novel self-report scale for security screening: the XRIndex, which improves on the Attention to Detail scale for predictive power and opacity to interpretation. The XRIndex is not redundant with any of the Big Five personality traits. We validate the XRIndex against security x-ray images with an independent sample of untrained participants and suggest that the XRIndex may be a useful aid for the identification of suitable candidates for professional security training with a focus on x-ray threat detection. Further studies are needed to determine whether this can also apply to trained professionals.

No MeSH data available.


Related in: MedlinePlus

Scatterplots with linear regression models for the XRIndex on: (A) overall accuracy; (B) Hits minus False Alarms (HFA); and (C) sensitivity (d’) in Study 1. Each point may represent one or more participants.
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Figure 4: Scatterplots with linear regression models for the XRIndex on: (A) overall accuracy; (B) Hits minus False Alarms (HFA); and (C) sensitivity (d’) in Study 1. Each point may represent one or more participants.

Mentions: We then conducted a preliminary criterion validity check and tested the prediction that the XRIndex would perform better than the Attention to Detail scale at predicting threat detection performance, thanks to the relation of its items with the original “Regularities minus Memory” index. To do that we used the data from 215 participants for whom both threat detection performance and XRIndex scores were available. Linear regression models having the XRIndex as predictor revealed significant trends in overall detection accuracy (R2 = 0.07, constant = 77, b = 0.44, p < 0.001), in detection accuracy for threat present items (R2 = 0.03, constant = 78, b = 0.33, p = 0.009), in rejection accuracy for threat absent items (R2 = 0.05, constant = 74, b = 0.54, p = 0.001), in HFA (R2 = 0.07, constant = 54, b = 0.87, p < 0.001), and in d’ (R2 = 0.08, constant = 1.56, b = 0.03, p < 0.001; see also Table 2; Figure 4) but not in c or RTs (p = 0.118 and p = 0.922 respectively).


XRIndex: a brief screening tool for individual differences in security threat detection in x-ray images.

Rusconi E, Ferri F, Viding E, Mitchener-Nissen T - Front Hum Neurosci (2015)

Scatterplots with linear regression models for the XRIndex on: (A) overall accuracy; (B) Hits minus False Alarms (HFA); and (C) sensitivity (d’) in Study 1. Each point may represent one or more participants.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4530599&req=5

Figure 4: Scatterplots with linear regression models for the XRIndex on: (A) overall accuracy; (B) Hits minus False Alarms (HFA); and (C) sensitivity (d’) in Study 1. Each point may represent one or more participants.
Mentions: We then conducted a preliminary criterion validity check and tested the prediction that the XRIndex would perform better than the Attention to Detail scale at predicting threat detection performance, thanks to the relation of its items with the original “Regularities minus Memory” index. To do that we used the data from 215 participants for whom both threat detection performance and XRIndex scores were available. Linear regression models having the XRIndex as predictor revealed significant trends in overall detection accuracy (R2 = 0.07, constant = 77, b = 0.44, p < 0.001), in detection accuracy for threat present items (R2 = 0.03, constant = 78, b = 0.33, p = 0.009), in rejection accuracy for threat absent items (R2 = 0.05, constant = 74, b = 0.54, p = 0.001), in HFA (R2 = 0.07, constant = 54, b = 0.87, p < 0.001), and in d’ (R2 = 0.08, constant = 1.56, b = 0.03, p < 0.001; see also Table 2; Figure 4) but not in c or RTs (p = 0.118 and p = 0.922 respectively).

Bottom Line: The results show that the Attention to Detail score from the autism-spectrum quotient (AQ) questionnaire (Baron-Cohen et al., 2001) is a linear predictor of threat detection accuracy.The XRIndex is not redundant with any of the Big Five personality traits.Further studies are needed to determine whether this can also apply to trained professionals.

View Article: PubMed Central - PubMed

Affiliation: Department of Security and Crime Science, University College London London, UK ; Department of Neurosciences, University of Parma Parma, Italy ; Division of Psychology, Abertay University Dundee, UK.

ABSTRACT
X-ray imaging is a cost-effective technique at security checkpoints that typically require the presence of human operators. We have previously shown that self-reported attention to detail can predict threat detection performance with small-vehicle x-ray images (Rusconi et al., 2012). Here, we provide evidence for the generality of such a link by having a large sample of naïve participants screen more typical dual-energy x-ray images of hand luggage. The results show that the Attention to Detail score from the autism-spectrum quotient (AQ) questionnaire (Baron-Cohen et al., 2001) is a linear predictor of threat detection accuracy. We then develop and fine-tune a novel self-report scale for security screening: the XRIndex, which improves on the Attention to Detail scale for predictive power and opacity to interpretation. The XRIndex is not redundant with any of the Big Five personality traits. We validate the XRIndex against security x-ray images with an independent sample of untrained participants and suggest that the XRIndex may be a useful aid for the identification of suitable candidates for professional security training with a focus on x-ray threat detection. Further studies are needed to determine whether this can also apply to trained professionals.

No MeSH data available.


Related in: MedlinePlus