Diagnosing eyewitness identifications with reaction timebased Concealed Information Test: the effect of viewpoint congruency between test and encoding.
Psychol Res
; 88(2): 639-651, 2024 Mar.
Article
en En
| MEDLINE
| ID: mdl-37477730
Mistaken eyewitness identifications continue to be a major contributor to miscarriages of justice. Previous experiments have suggested that implicit identification procedures such as the Concealed Information Test (CIT) might be a promising alternative to classic lineups when encoding conditions during the crime were favorable. We tested this idea by manipulating view congruency (frontal vs. profile view) between encoding and test. Participants witnessed a videotaped mock theft that showed the thief and victim almost exclusively from frontal or profile view. At test, viewing angle was either congruent or incongruent with the view during encoding. We tested eyewitness identification with the RT-CIT (N = 74), and with a traditional simultaneous photo lineup (N = 97). The CIT showed strong capacity to diagnose face recognition (d = 0.91 [0.64; 1.18]), but unexpectedly, view congruency did not moderate this effect. View congruency moderated lineup performance for one of the two lineups. Following these unexpected findings, we conducted a replication with a stronger congruency manipulation and larger sample size. CIT (N = 156) showed moderate capacity to diagnose face recognition (d = 0.63 [0.46; 0.80]) and now view congruency did moderate the CIT effect. For lineups (N = 156), view congruency again moderated performance for one of the two lineups. Capacity for diagnosing face recognition was similar for lineups and RT-CIT in our first comparison, but much stronger for lineups in our second comparison. Future experiments might investigate more conditions that affect performance in lineups vs. the RT-CIT differentially.
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1
Banco de datos:
MEDLINE
Asunto principal:
Reconocimiento en Psicología
/
Reconocimiento Facial
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Año:
2024
Tipo del documento:
Article