Source confusion influences the effectiveness of the autobiographical IAT

Autobiographical Implicit Association Test and eye movements: fixations topography enables detection of autobiographical memories

Introduction

Autobiographical memory is the capacity to recollect memories of personally experienced events. The detection of such memories plays a key role in criminal trials. Among behavioral memory-detection methods, the autobiographical Implicit Association Test (aIAT) has gained popularity for its flexibility and suitability for forensic applications. The aIAT is a reaction time-based methodology aiming to assess whether information about an event is encoded in the respondent's mind. Here, we introduced the eye-D index, a measure based on the topography of fixations while performing the aIAT, as an additional measure to detect autobiographical memories covertly.

Methods

In this study, participants were involved in a mock-crime experiment in which they could act as Guilty or Innocent. One week later all participants underwent the aIAT combined with eye-tracking to investigate the presence of the crime-related memory.

Results

Guilty participants showed a higher number of fixations towards the category labels in the block in which true sentences shared the same response key with crime-related sentences, as compared to the block in which true sentences were paired with sentences describing an alternative version. Innocent participants showed the opposite pattern. This unbalanced allocation of attention to the category labels was quantified by the eye-D index and was found to be highly correlated to the standard aIAT-D index.

Discussion

This suggests that more fixations to the category labels could indicate increased cognitive load and monitoring of response conflicts. These preliminary results highlight eye-tracking as a tool to detect autobiographical memories covertly while performing the aIAT.

Two Cases of Malingered Crime-Related Amnesia

Amnesia is a frequent claim in major crimes, and it is estimated that the complete or partial absence of memory following a crime ranges from 25% to 50% of total cases. Although some cases may constitute a genuine form of amnesia, due to organic-neurological defects or psychological causes, and possibly combined with a dissociative or repressive coping style after an extreme experience, malingering is still fairly common in offenders. Therefore, one of the main goals in medico-legal proceedings is to find methods to determine the credibility of crime-related amnesia. At present, a number of lie and memory detection techniques can assist the forensic assessment of the reliability of declarative proof, and have been devised and improved over the past century: for example, modern polygraphs, event-related potentials, thermal imaging, functional magnetic resonance imaging, kinematic, and facial analysis. Other ad hoc psychological tests, such as the so-called Symptom Validity Test (SVT) and Performance Validity Test (PVT), as well as the autobiographical Implicit Association Test (aIAT), can also be used. To date, however, there is little evidence or case reports that document their real usefulness in forensic practice. Here, we report two cases of crime-related amnesia, whereby both defendants, who were found guilty of homicide, appeared to exhibit dissociative amnesia but where the application of SVTs, PVTs, and aIAT detected a malingered amnesia.

Can implicit measures detect source information in crime-related amnesia?

Participants who are asked to simulate amnesia for a mock crime have a weaker memory for this event when they have to give up their role as a feigner, than those who are not asked to feign memory loss. According to the source monitoring framework (SMF), this memory-undermining effect of simulating amnesia for a crime would be due to misattribution of the right source of information. However, we know that the content of self-generated information (e.g., feigned version of the crime) might be preserved and recognised over time as a result of elaborative cognitive processing. In the present study, we aimed to contrast these two explanations. We showed participants a mock crime video and we instructed them to either feign amnesia (simulators) or confess the mock crime (confessors). Next, a free recall memory test was administered. After one week, participants were asked to perform a personalised source monitoring task using the autobiographical Implicit Association Test (aIAT). As predicted, we found that simulators were able to discriminate the content of their self-generated feigned story of the crime from the original version. Moreover, simulators were quicker than confessors at the aIAT task. Practical and theoretical implications of our results are discussed.

Assessing autobiographical memory: the web-based autobiographical Implicit Association Test

By assessing the association strength with TRUE and FALSE, the autobiographical Implicit Association Test (aIAT) [Sartori, G., Agosta, S., Zogmaister, C., Ferrara, S. D., & Castiello, U. (2008). How to accurately detect autobiographical events. Psychological Science, 19, 772-780. doi: 10.1111/j.1467-9280.2008.02156.x ] aims to determine which of two contrasting statements is true. To efficiently run well-powered aIAT experiments, we propose a web-based aIAT (web-aIAT). Experiment 1 (n = 522) is a web-based replication study of the first published aIAT study [Sartori, G., Agosta, S., Zogmaister, C., Ferrara, S. D., & Castiello, U. (2008). How to accurately detect autobiographical events. Psychological Science, 19, 772-780. doi: 10.1111/j.1467-9280.2008.02156.x ; Experiment 1]. We conclude that the replication was successful as the web-based aIAT could accurately detect which of two playing cards participants chose (AUC = .88; Hit rate = 81%). In Experiment 2 (n = 424), we investigated whether the use of affirmative versus negative sentences may partly explain the variability in aIAT accuracy findings. The aIAT could detect the chosen card when using affirmative (AUC = .90; Hit rate = 81%), but not when using negative sentences (AUC = .60; Hit rate = 53%). The web-based aIAT seems to be a valuable tool to facilitate aIAT research and may help to further identify moderators of the test's accuracy.

A call for policy guidance on psychometric testing in doping control in sport

One of the fundamental challenges in anti-doping is identifying athletes who use, or are at risk of using, prohibited performance enhancing substances. The growing trend to employ a forensic approach to doping control aims to integrate information from social sciences (e.g., psychology of doping) into organised intelligence to protect clean sport. Beyond the foreseeable consequences of a positive identification as a doping user, this task is further complicated by the discrepancy between what constitutes a doping offence in the World Anti-Doping Code and operationalized in doping research. Whilst psychology plays an important role in developing our understanding of doping behaviour in order to inform intervention and prevention, its contribution to the array of doping diagnostic tools is still in its infancy. In both research and forensic settings, we must acknowledge that (1) socially desirable responding confounds self-reported psychometric test results and (2) that the cognitive complexity surrounding test performance means that the response-time based measures and the lie detector tests for revealing concealed life-events (e.g., doping use) are prone to produce false or non-interpretable outcomes in field settings. Differences in social-cognitive characteristics of doping behaviour that are tested at group level (doping users vs. non-users) cannot be extrapolated to individuals; nor these psychometric measures used for individual diagnostics. In this paper, we present a position statement calling for policy guidance on appropriate use of psychometric assessments in the pursuit of clean sport. We argue that, to date, both self-reported and response-time based psychometric tests for doping have been designed, tested and validated to explore how athletes feel and think about doping in order to develop a better understanding of doping behaviour, not to establish evidence for doping. A false 'positive' psychological profile for doping affects not only the individual 'clean' athlete but also their entourage, their organisation and sport itself. The proposed policy guidance aims to protect the global athletic community against social, ethical and legal consequences from potential misuse of psychological tests, including erroneous or incompetent applications as forensic diagnostic tools in both practice and research.

It is not just memory: propositional thinking influences performance on the autobiographical IAT

INTRODUCTION

The autobiographical Implicit Association Test (aIAT) is a variant of the Implicit Association Test reportedly capable of detecting an individual's concealed autobiographical event with very high accuracy. A previous attempt to utilize this measurement technique for the identification of cocaine users rendered an alarming rate of false positives. In this study, we aimed to explore the potential reasons behind the measurement's inaccuracy.

METHODS

Two versions of the cocaine aIAT were devised with different category labels (descriptive 'guilty/innocent' and self-referenced 'as if you were/were not'). Forty-one cocaine abstinent participants (43.9% male; mean age = 28.17 ± 7.36) were randomly assigned to one of the two conditions. Self-declared cocaine abstinence was confirmed for the 12-month period preceding data collection through hair analysis. Participants were also administered bespoke implicit and explicit cocaine user attitude measures, the self-esteem IAT and the Rosenberg self-esteem scale.

RESULTS

The category labels which elicited self-referenced knowledge showed low accuracy (19%) compared to the 65% of the 'guilty/innocent' labels proposed by original authors. The self-referenced aIAT version significantly correlated with the self-concept measures. The aIAT outcomes were independent from attitudes toward cocaine users.

CONCLUSIONS

Category labels play an influential role in determining the test's accuracy, demonstrating that participants' propositional knowledge and self-concept are involved during test performance. The aIAT does not appear to tap directly into an individual's implicit memory when relevant memory is not available. Although the test cannot be recommended for detecting drug use, further research should investigate underlying mechanisms and other potentials of the technique.

The autobiographical IAT: a review

The autobiographical Implicit Association Test (aIAT; Sartori et al., 2008) is a variant of the Implicit Association Test (IAT; Greenwald et al., 1998) that is used to establish whether an autobiographical memory is encoded in the respondent's mind/brain. More specifically, with the aIAT, it is possible to evaluate which one of two autobiographical events is true. The method consists of a computerized categorization task. The aIAT includes stimuli belonging to four categories, two of them are logical categories and are represented by sentences that are always true (e.g., I am in front of a computer) or always false (e.g., I am climbing a mountain) for the respondent; two other categories are represented by alternative versions of an autobiographical event (e.g., I went to Paris for Christmas, or I went to New York for Christmas), only one of which is true. The true autobiographical event is identified because, in a combined block, it gives rise to faster reaction times when it shares the same motor response with true sentences. Here, we reviewed all the validation experiments and found more than 90% accuracy in detecting the true memory. We show that agreement in identifying the true autobiographical memory of the same aIAT repeated twice is, on average, more than 90%, and we report a technique for estimating accuracy associated with a single classification based on the D-IAT value, which may be used in single subject's investigations. We show that the aIAT might be used to identify also true intentions and reasons and conclude with a series of guidelines for building an effective aIAT.