1. The efficiency of E-FIT with mild learning disabled witnesses Julie Gawrylowicz j.gawrylowicz@abertay.ac.uk Supervisory team: Dr Derek Carson, Dr Fiona Gabbert, University of Abertay Dundee, Professor William Lindsay, University of Abertay Dundee and NHS Tayside and Professor Peter Hancock, University of Stirling Presented at Postgraduate Awayday, 2009 UNIVERSITY OF ABERTAY

2. E-FIT  E-FIT = Electronic Facial Identification Technique

3. E-FIT

4. Relevance  High prevalence rate (Emerson, 2001)  People with LD are more susceptible to victimization (Kebbel & Hatton, 1999 )  LD might have serious impacts on reliability and accuracy of an eyewitness account, since it influences several cognitive skills

5. Research Question  Does the ability of people with mLD to use E-FIT differ from the ability of people without a learning disability (controls) and if so in what way?

6. Phase I: E-FIT construction phase  Participants  30 with mLD (19-68; mean = 43 yrs)  WASI: FSIQ-4 score: mean = 57.97, SD = 3.63, range = 52-69)  30 controls (19-48; mean = 29 yrs)  Design  2 (group: mLD vs. controls) x 2 (description mode: from photo vs. from memory) between-subjects design  DV:  Quality of the resulting E-FITs (assessed during evaluation phase)  Differences between mLD group and controls:  Amount of facial information obtained during the Cognitive Interview (CI)  Duration of E-FIT construction phase

7. Phase II: Evaluation phase  Identification task  46 participants  2 (group: mLD vs. controls) x 2 (description mode: from photo vs. from memory) mixed design  DV: amount of correct identifications based on mLD E-FITs & control E-FITs  Example: E-FIT Line-up X

8. Results: Evaluation phase  Main effect for group (p <.001)  Main effects for description mode (p <.001) Chance performance

9. Amount of facial information  Main effect for group (p <.001)  No other sig. effects observed

10. Duration of E-FIT construction phase  Main effect for group (p <.001)  No other sig. effects observed

11. Conclusions  E-FITs constructed by participants with mLD were poorer than those constructed by controls  This difference in the quality of E-FITs might be due to:  Less detailed description of the target face  More easily satisfied with resulting E-FIT

12. Possible future directions  Ways to improve the performance of mLD witnesses with facial composite systems:  EvoFit (evolutionary facial identification technique)  Does not require the generation of a verbal description of the face  Relies on face recognition rather than on verbal facial description

13. The efficiency of E-FIT with mild learning disabled witnesses Julie Gawrylowicz j.gawrylowicz@abertay.ac.uk Supervisory team: Dr Derek Carson, Dr Fiona Gabbert, University of Abertay Dundee, Professor William Lindsay, University of Abertay Dundee and NHS Tayside and Professor Peter Hancock, University of Stirling Presented at Postgraduate Awayday, 2009 UNIVERSITY OF ABERTAY