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Anxious individuals predict the onset of aggression earlier in a CCTV surveillance task
Benjamin M Aitken1, James C Champion1, Matthew J Stainer1
1School of Applied Psychology, Griffith University.
Abstract:
Attentional biases in anxious individuals can facilitate the detection of threatening stimuli. A particular field of research that may benefit from enhanced threat detection is in closed-circuit television (CCTV) surveillance, in which operators search through multiple camera feeds to attempt to identify threatening situations before they occur. The present study examined whether the enhanced threat detection of anxious individuals extends to the ability to detect threat in a multiple-scene CCTV task. Anxiety was measured in a nonclinical sample using the State-Trait Inventory for Cognitive and Somatic Anxiety. Participants were asked to try to find aggressive incidents that were simulated using the game Grand Theft Auto V in displays showing 1, 4, or 9 simultaneous videos. The results revealed that higher levels of trait cognitive, state cognitive, and trait somatic anxiety were related to earlier responses, with no change in confidence or accuracy. Increasing the number of screens to be monitored was associated with detecting the events later and a reduced confidence in responses. These results suggest that, in nonclinical populations, a moderate degree of anxiety may be beneficial in predicting acts of aggression during CCTV monitoring tasks. Trait (i.e., stable) levels of anxiety may inform recruitment of operators for surveillance tasks. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

