Eyewitness identifications from lineups are prone to error. More indirect identification procedures, such as the reaction-time based Concealed Information Test (RT-CIT) could be a viable alternative to lineups. The RT-CIT uses response times to assess facial familiarity. Theory and initial evidence with autobiographical stimuli suggests that the accuracy of RT-CIT can be augmented when participants' reliance on familiarity-based responding increases. We tested this assumption in two pre-registered experiments with 173 participants. Participants witnessed a mock crime. In the subsequent RT-CIT protocol, participants reacted to probe faces from the mock crime video, to irrelevant faces, and to target faces that required a unique response. Targets were either unknown people or were well-known celebrities (e.g., Taylor Swift). As expected, reaction times were longer to probes than to irrelevants in all conditions, indicating a CIT effect. Contrasting our pre-registered predictions, the CIT effect was not larger in the familiar condition (Experiment 1: unfamiliar targets: d = 0.77 vs. celebrity targets: d = 0.24; Experiment 2: unfamiliar targets: d = 1.09 vs. celebrity targets: d = 0.79). This suggests that familiar targets did not increase the validity of the RT-CIT in diagnosing concealed face recognition. A potential lack of saliency of the familiar targets might explain these unexpected findings. Of note, we did find medium to large effect sizes overall, speaking to the potential of diagnosing face recognition with the RT-CIT.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11522165 | PMC |
http://dx.doi.org/10.1007/s00426-024-02003-1 | DOI Listing |
Mil Med
January 2025
Veterans Affairs Quality Scholars Fellowship, Ralph H. Johnson VA Medical Center, Charleston, SC 29412, USA.
Introduction: Cardiovascular disease (CVD) is the leading cause of death for women in the United States, and U.S. female Veterans have higher rates of CVD compared to civilian women.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Department of Computer Science, Tunghai University, Taichung 407224, Taiwan.
Background And Objective: Cardiovascular disease (CVD), one of the chronic non-communicable diseases (NCDs), is defined as a cardiac and vascular disorder that includes coronary heart disease, heart failure, peripheral arterial disease, cerebrovascular disease (stroke), congenital heart disease, rheumatic heart disease, and elevated blood pressure (hypertension). Having CVD increases the mortality rate. Emotional stress, an indirect indicator associated with CVD, can often manifest through facial expressions.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Genetics Department, Hospital Sant Joan de Déu, Member of ERN-ITHACA, 08950 Esplugues de Llobregat, Spain.
: duplication syndrome (MDS) (MIM#300260) is a rare X-linked neurodevelopmental disorder. This study aims to (1) develop a specific clinical severity scale, (2) explore its correlation with clinical and molecular variables, and (3) automate diagnosis using the Face2gene platform. : A retrospective study was conducted on genetically confirmed MDS patients who were evaluated at a pediatric hospital between 2012 and 2024.
View Article and Find Full Text PDFOtol Neurotol
January 2025
Department of Otolaryngology-Head and Neck Surgery, University of California, San Diego, La Jolla, California.
Objective: To evaluate hearing preservation (HP) outcomes for patients with small sporadic vestibular schwannomas (VS) who elect to undergo microsurgical resection.
Study Design: Retrospective study.
Setting: Tertiary single-academic institution.
Food Chem
January 2025
School of Automation Engineering, Northeast Electric Power University, Jilin 132012, China; Institute of advanced sensor technology, Northeast Electric Power University, Jilin 132012, China. Electronic address:
Pork freshness is crucial for flavour, nutrition and consumer health. The current colorimetric sensor array (CSA) detection systems face challenges related to high sensor development costs, low recognition accuracy and limitations in the platform use. Herein, we developed a CSA and ColorNet framework to detect pork freshness.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!