Return to search

Eyewitness identification performance on lineups for distinctive suspects

When constructing lineups for suspects with distinctive facial features (e.g., scars, tattoos, piercings), current police guidelines in several countries state that the distinctive suspect must not stand out. To this end, police officers sometimes artificially replicate a suspect’s distinctive feature across the other lineup members (replication); other times, they conceal the feature on the suspect and conceal a similar area on the other members by pixelating the area (pixelation), or covering the area with a solid rectangle (block). Although these three techniques are used frequently, little research has examined their efficacy. This thesis investigates how the lineup techniques for distinctive suspects influence eyewitness identification performance and, in doing so, tests the predictions of a new model of eyewitness decision-making—the diagnostic-feature-detection model (Wixted & Mickes, 2014). The research uses a standard eyewitness identification paradigm and signal detection statistics to examine how replication, pixelation, and block techniques influence identification performance: [1] compared to doing nothing to stop the distinctive suspect from standing out; [2] in young, middle-aged and older adults; and [3] when the culprit does not have the feature during the crime. It also examines [4] how variation in the way the suspect’s feature is replicated influences identification performance. The results converge to suggest that all three lineup techniques currently used by the police to accommodate distinctive suspects are equally effective and, when the culprit has the feature at the time of the crime, all enhance people’s ability to discriminate between innocent and guilty suspects more than doing nothing to prevent a distinctive suspect from standing out. All three lineup techniques enable people of all ages to make highly confident decisions when they are likely to be accurate. These findings align with the predictions of the diagnostic-feature-detection model, which suggests that the model remains a viable theory of eyewitness decision-making.

Identiferoai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:720457
Date January 2016
CreatorsColloff, Melissa F.
PublisherUniversity of Warwick
Source SetsEthos UK
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
Sourcehttp://wrap.warwick.ac.uk/90153/

Page generated in 0.0021 seconds