Eyewitness Identification Performance Research Articles

Does Cross‐Age Contact Reduce the Cross‐Age Deficit in Younger and Older Adult's Eyewitness Identification Performance?

ABSTRACTAge‐related differences in identification performance between younger (18–35 years) and older adults (62–68 years), alongside the cross‐age effect (CAE), where people recognise own‐age faces better than other‐age faces, were investigated. Self‐reported levels of other‐age contact and attitudes, participants' memory for the unbiased lineup instructions, and the confidence‐accuracy (C‐A) relationship were also examined. Participants (N = 154) viewed two filmed events: one with a young adult target and one with an older adult target. Older adults were less likely than younger adults to identify the perpetrator. Interestingly, the CAE, contact, attitudes, and choosing behaviours did not impact identification performance. Older adults experienced more difficulty remembering the pre‐lineup instructions than younger adults, but only after the first lineup. Confidence was predictive of accuracy for both age groups, but this relationship was differently influenced by the CAE. The findings provide further insights into the factors that may impact younger and older adults' identification performance.

The effects of filler similarity and lineup size on eyewitness identification.

A photo lineup, which is a cross between an old/new and a forced-choice recognition memory test, consists of one suspect, whose face was either seen before or not, and several physically similar fillers. First, the participant/witness must decide whether the person who was previously seen is present (old/new) and then, if present, choose the previously seen target (forced choice). Competing signal-detection models of eyewitness identification performance make different predictions about how certain variables will affect a witness's ability to discriminate previously seen (guilty) suspects from new (innocent) suspects. One key variable is the similarity of the fillers to the suspect in the lineup, and another key variable is the size of the lineup (i.e., the number of fillers). Previous research investigating the role of filler similarity has supported one model, known as the Ensemble model, whereas previous research investigating the role of lineup size has supported a competing model, known as the Independent Observations model. We simultaneously manipulated these two variables (filler similarity and lineup size) and found a pattern that is not predicted by either model. When the fillers were highly similar to the suspect, increasing lineup size reduced discriminability, but when the fillers were dissimilar to the suspect, increasing lineup size enhanced discriminability. The results suggest that each additional filler adds noise to the decision-making process and that this noise factor is minimized by maximizing filler dissimilarity. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Using objective measures to examine the effect of suspect-filler similarity on eyewitness identification performance - Final Registered Report

When selecting fillers to include in a police lineup, one must consider the level of similarity between the suspect and potential fillers. In order to reduce misidentifications, an innocent suspect should not stand out. Therefore, it is important that the fillers share some degree of similarity. Importantly, increasing suspect–filler similarity too much will render the task too difficult reducing correct identifications of a guilty suspect. Determining how much similarity yields optimal identification performance is the focus of the proposed study. Extant research on lineup construction has provided somewhat mixed results. In part, this is likely due to the subjective nature of similarity, which forces researchers to define similarity in relative terms. In the current study, we manipulate suspect–filler similarity via a multidimensional scaling model constructed using objective facial measurements. In doing so, we test the “propitious heterogeneity” and the diagnostic-feature-detection hypotheses which predict an advantage of lineups with low-similarity fillers in terms of discriminability. We found that filler similarity did not affect discriminability. We discuss limitations and future directions.

Modeling face similarity in police lineups.

Police investigators worldwide use lineups to test an eyewitness's memory of a perpetrator. A typical lineup consists of one suspect (who is innocent or guilty) plus five or more fillers who resemble the suspect and who are known to be innocent. Although eyewitness identification decisions were once biased by police pressure and poorly constructed lineups, decades of social science research led to the development of reformed lineup procedures that provide a more objective test memory. Under these improved testing conditions, cognitive models of memory can be used to better understand and ideally enhance eyewitness identification performance. In this regard, one question that has bedeviled the field for decades is how similar the lineup fillers should be to the suspect to optimize performance. Here, we model the effects of manipulating filler similarity to better understand why such manipulations have the intriguing effects they do. Our findings suggest that witnesses rely on a decision variable consisting of the degree to which the memory signal for a particular face in the lineup stands out relative to the crowd of memory signals generated by the set of faces in the lineup. The use of that decision variable helps to explain why discriminability is maximized by choosing fillers that match the suspect on basic facial features typically described by the eyewitness (e.g., age, race, gender) but who otherwise are maximally dissimilar to the suspect. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Experimental validation of a multinomial processing tree model for analyzing eyewitness identification decisions

To improve police protocols for lineup procedures, it is helpful to understand the processes underlying eyewitness identification performance. The two-high threshold (2-HT) eyewitness identification model is a multinomial processing tree model that measures four latent cognitive processes on which eyewitness identification decisions are based: two detection-based processes (the detection of culprit presence and absence) and two non-detection-based processes (biased and guessing-based selection). The model takes into account the full 2 × 3 data structure of lineup procedures, that is, suspect identifications, filler identifications and rejections in both culprit-present and culprit-absent lineups. Here the model is introduced and the results of four large validation experiments are reported, one for each of the processes specified by the model. The validation experiments served to test whether the model’s parameters sensitively reflect manipulations of the processes they were designed to measure. The results show that manipulations of exposure duration of the culprit’s face at encoding, lineup fairness, pre-lineup instructions and ease of rejection of culprit-absent lineups were sensitively reflected in the parameters representing culprit-presence detection, biased suspect selection, guessing-based selection and culprit-absence detection, respectively. The results of the experiments thus validate the interpretations of the parameters of the 2-HT eyewitness identification model.

A validation of the two-high threshold eyewitness identification model by reanalyzing published data

The two-high threshold (2-HT) eyewitness identification model serves as a new measurement tool to measure the latent cognitive processes underlying eyewitness identification performance. By simultaneously taking into account correct culprit identifications, false innocent-suspect identifications, false filler identifications in culprit-present and culprit-absent lineups as well as correct and false lineup rejections, the model capitalizes on the full range of data categories that are observed when measuring eyewitness identification performance. Thereby, the model is able to shed light on detection-based and non-detection-based processes underlying eyewitness identification performance. Specifically, the model incorporates parameters for the detection of culprit presence and absence, biased selection of the suspect and guessing-based selection among the lineup members. Here, we provide evidence of the validity of each of the four model parameters by applying the model to eight published data sets. The data sets come from studies with experimental manipulations that target one of the underlying processes specified by the model. Manipulations of encoding difficulty, lineup fairness and pre-lineup instructions were sensitively reflected in the parameters reflecting culprit-presence detection, biased selection and guessing-based selection, respectively. Manipulations designed to facilitate the rejection of culprit-absent lineups affected the parameter for culprit-absence detection. The reanalyses of published results thus suggest that the parameters sensitively reflect the manipulations of the processes they were designed to measure, providing support of the validity of the 2-HT eyewitness identification model.

Could precise and replicable manipulations of suspect-filler similarity optimize eyewitness identification performance?

Could precise and replicable manipulations of suspect-filler similarity optimize eyewitness identification performance?

Supplemental Material for Could Precise and Replicable Manipulations of Suspect-Filler Similarity Optimize Eyewitness Identification Performance?

Supplemental Material for Could Precise and Replicable Manipulations of Suspect-Filler Similarity Optimize Eyewitness Identification Performance?

Eyewitness identification performance is not affected by time-of-day optimality

The circadian rhythm regulates arousal levels throughout the day and determines optimal periods for engaging in mental activities. Individuals differ in the time of day at which they reach their peak: Morning-type individuals are at their best in the morning and evening types perform better in the evening. Performance in recall and recognition of non-facial stimuli is generally superior at an individual’s circadian peak. In two studies (Ns = 103 and 324), we tested the effect of time-of-testing optimality on eyewitness identification performance. Morning- and evening-type participants viewed stimulus films depicting staged crimes and made identification decisions from target-present and target-absent lineups either at their optimal or non-optimal time-of-day. We expected that participants would make more accurate identification decisions and that the confidence-accuracy and decision time-accuracy relationships would be stronger at optimal compared to non-optimal time of day. In Experiment 1, identification accuracy was unexpectedly superior at non-optimal compared to optimal time of day in target-present lineups. In Experiment 2, identification accuracy did not differ between the optimal and non-optimal time of day. Contrary to our expectations, confidence-accuracy relationship was generally stronger at non-optimal compared to optimal time of day. In line with our predictions, non-optimal testing eliminated decision-time-accuracy relationship in Experiment 1.

Live Presentation for Eyewitness Identification is Not Superior to Photo or Video Presentation

Eyewitnesses are widely believed to have a better chance of identifying a perpetrator from a live identification procedure than from photo or video alternatives. To test this live superiority hypothesis, prospective students and their parents (N = 1048) became unsuspecting witnesses to staged events and were randomly assigned to live, photo, or video identification procedures. In Experiment 1, participants viewed a single person at the identification procedure. In Experiment 2, participants viewed a lineup of six people. Across experiments, live identification procedures did not improve eyewitness identification performance. The results show that even under experimental settings designed to eliminate the disadvantages of conducting live lineups in practice, live presentation confers no benefit to eyewitnesses.

Αναγνώριση σημαίνει ενοχή; Mια ανασκόπηση των παραγόντων επιρροής της επίδοσης των αυτοπτών μαρτύρων

Eyewitness identification stands as one of the core aspects of the judicial system. However, when it comes to identifying faces, people often make mistakes. Thus, it should not come as a surprise that eyewitness identification has been shown to be the number one factor of wrongful convictions (www.innoccenceproject.org). Therefore it is importantto understand the reasons that make eyewitnesses so error prone and investigate how we could enhance their performance. In the present article we examine the factors that have an impact on eyewitnessidentification performance. More specifically, we will refer to those variables over which the research community has reached consensus. These include estimator and system variables as well as postdictors,which are variables capable to diagnose the identification accuracy once it has taken place. In doing so we aim to reveal those parameters that are based on a sturdy research base, but have notwithstanding beenneglected by the Greek judicial system. We suggest a number of alterations and improvements, based on this research basis that can improve identification performance.

“All I remember is the black eye”: A distinctive facial feature harms eyewitness identification

SummaryMany crimes occur in which a perpetrator has a distinctive facial feature, such as a tattoo or black eye, but few eyewitness identification (ID) studies have involved such a feature. We conducted an experiment to determine how eyewitness ID performance is impacted by a distinctive facial feature, and how police could deal with this issue. Participants (N = 4,218) studied a target face with or without a black eye, and later viewed a simultaneous photo lineup either containing the target or not. For those who saw a target with a black eye, this feature was either replicated among all lineup members or was removed. The black eye harmed empirical discriminability regardless of replication or removal, which did not differ. However, participants responded more conservatively when the black eye was removed, compared to replication. Lastly, immediate confidence was consistently indicative of accuracy.

Identification Performance from Multiple Lineups: Should Eyewitnesses Who Pick Fillers Be Burned?

Over the course of a criminal investigation, eyewitnesses are sometimes shown multiple lineups in an attempt to identify the culprit, yet little research has examined eyewitness identification performance from multiple lineups. In two experiments, we examined eyewitness identification accuracy among witnesses who made an inaccurate identification from an initial lineup, correctly rejected an initial lineup, or saw no initial lineup. Consistent with the legal practice of “burning” eyewitnesses who pick fillers, witnesses who made an inaccurate identification from an initial lineup provided subsequent identification evidence that had little diagnostic value and reflected poor memory performance. Critically, these eyewitnesses’ initial-identification confidence did not predict their subsequent identification accuracy, thus precluding the identification of witnesses who could provide diagnostic evidence in a subsequent lineup. Eyewitnesses who correctly rejected the initial lineup performed similarly to eyewitnesses who saw only one lineup, and initial-rejection confidence was associated with subsequent identification accuracy under some conditions.

Eyewitness identification performance on showups improves with an additional-opportunities instruction: Evidence for present-absent criteria discrepancy.

We tested the proposition that when eyewitnesses find it difficult to recognize a suspect (as in a culprit-absent showup), eyewitnesses accept a weaker match to memory for making an identification. We tie this proposition to the basic recognition memory literature, which shows people use lower decision criteria when recognition is made difficult so as to not miss their chance of getting a hit on the target. We randomly assigned participant-witnesses (N = 610) to a condition in which they were told that if they did not believe the suspect was the culprit, they would have additional opportunities to make an identification later (additional-opportunities instruction). We fully crossed this instruction with the standard admonition (i.e., the culprit may or may not be present) and with the presence or absence of the culprit in a showup identification procedure. The standard admonition had no impact on eyewitness decision-making; however, the additional-opportunities instruction reduced innocent-suspect identifications (from 33% to 15%) to a greater extent than culprit identifications (57% to 51%). The additional-opportunities instruction yielded a better tradeoff between culprit and innocent-suspect identifications as indicated by binary logistic regression and receiver operator characteristic (ROC) analyses. (PsycINFO Database Record

Supplemental Material for Eyewitness Identification Performance on Showups Improves With an Additional-Opportunities Instruction: Evidence for Present–Absent Criteria Discrepancy

Supplemental Material for Eyewitness Identification Performance on Showups Improves With an Additional-Opportunities Instruction: Evidence for Present–Absent Criteria Discrepancy

How sure are you that this is the man you saw? Child witnesses can use confidence judgments to identify a target.

We tested whether an alternative lineup procedure designed to minimize problematic influences (e.g., metacognitive development) on decision criteria could be effectively used by children and improve child eyewitness identification performance relative to a standard identification task. Five hundred sixteen children (6- to 13-year-olds) watched a video of a target reading word lists and, the next day, made confidence ratings for each lineup member or standard categorical decisions for 8 lineup members presented sequentially. Two algorithms were applied to classify confidence ratings into categorical decisions and facilitate comparisons across conditions. The classification algorithms produced accuracy rates for the confidence rating procedure that were comparable to the categorical procedure. These findings demonstrate that children can use a ratings-based procedure to discriminate between previously seen and unseen faces. In turn, this invites more nuanced and empirical consideration of ratings-based identification evidence as a probabilistic index of guilt that may attenuate problematic social influences on child witnesses' decision criteria. (PsycINFO Database Record

Stress, stress-induced cortisol responses, and eyewitness identification performance.

In the eyewitness identification literature, stress and arousal at the time of encoding are considered to adversely influence identification performance. This assumption is in contrast with findings from the neurobiology field of learning and memory, showing that stress and stress hormones are critically involved in forming enduring memories. This discrepancy may be related to methodological differences between the two fields of research, such as the tendency for immediate testing or the use of very short (1–2 hours) retention intervals in eyewitness research, while neurobiology studies insert at least 24 hours. Other differences refer to the extent to which stress‐responsive systems (i.e., the hypothalamic–pituitary–adrenal axis) are stimulated effectively under laboratory conditions. The aim of the current study was to conduct an experiment that accounts for the contemporary state of knowledge in both fields. In all, 123 participants witnessed a live staged theft while being exposed to a laboratory stressor that reliably elicits autonomic and glucocorticoid stress responses or while performing a control task. Salivary cortisol levels were measured to control for the effectiveness of the stress induction. One week later, participants attempted to identify the thief from target‐present and target‐absent line‐ups. According to regression and receiver operating characteristic analyses, stress did not have robust detrimental effects on identification performance. Copyright © 2016 John Wiley & Sons, Ltd. © 2016 The Authors Behavioral Sciences & the Law Published by John Wiley & Sons Ltd

Lineup identification accuracy: The effects of alcohol, target presence, confidence ratings, and response time

Despite the intoxication of many eyewitnesses at crime scenes, only four published studies to date have investigated the effects of alcohol intoxication on eyewitness identification performance. While one found intoxication significantly increased false identification rates from target absent showups, three found no such effect using the more traditional lineup procedure. The present study sought to further explore the effects of alcohol intoxication on identification performance and examine whether accurate decisions from intoxicated witnesses could be postdicted by confidence and response times. One hundred and twenty participants engaged in a study examining the effects of intoxication (control, placebo, and mild intoxication) and target presence on identification performance. Participants viewed a simultaneous lineup one week after watching a mock crime video of a man attempting to steal cars. Ethanol intoxication (0.6 ml/kg) was found to make no significant difference to identification accuracy and such identifications from intoxicated individuals were made no less confidently or slowly than those from sober witnesses. These results are discussed with respect to the previous research examining intoxicated witness identification accuracy and the misconceptions the criminal justice system holds about the accuracy of such witnesses.

Eyewitness Identification when “The Perpetrator Reminds Me of Someone I Know”

We investigated the effect on eyewitness identification performance of witnesses making an association between the perpetrator of a crime and someone well known to them. Participants were either cued or not cued to associate the perpetrator of a mock-crime with somebody famous before attempting to identify the culprit from a target-present photoarray a week later. It was hypothesized that those who made an association would: (1) think about the associated face during their rehearsal of the target memory throughout the week, and (2) exhibit worse identification test performance (i.e., by making fewer correct identifications and rejecting the line-up more often) relative to those who made no association. Although we demonstrated that concurrent rehearsal of the target and associated face had occurred, similar patterns of identification choices emerged regardless of whether an association was made or not. The implications of this finding in the absence of an effect on identification test performance are discussed in relation to memory strength, identification response criterion setting and future directions in identification research.

Missing the information needed to perform ROC analysis? Then compute d′, not the diagnosticity ratio

In a typical recognition memory experiment, the participant’s ask is to discriminate between “old” items that were previously ncountered and “new” items that were not. Common examples nclude discriminating between words that were presented on a list nd words that were not, or discriminating between guilty suspects ho appeared in a mock-crime video and innocent suspects who id not. For eyewitness identification experiments, performance or guilty suspects (old items) and innocent suspects (new items) s characterized by the correct ID rate (the proportion of guilty uspects who are correctly identified), and the false ID rate (the proortion of innocent suspects who are incorrectly identified). What s the best way to combine these two measures to gauge overall ecognition performance? Although the possibilities are limitless, his question usually boils down to a choice between some kind f ratio measure (e.g., correct ID rate/false ID rate) vs. some kind f difference score (e.g., correct ID rate minus false ID rate). The hoice depends on one’s goal, so the first issue to consider is what hat goal should be.