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1 This article was downloaded by: [University of Wyoming Libraries] On: 31 October 2012, At: 07:48 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: Registered office: Mortimer House, Mortimer Street, London W1T 3JH, UK Psychiatry, Psychology and Law Publication details, including instructions for authors and subscription information: Determining True and False Witnessed Events: Can an Eyewitness-Implicit Association Test Distinguish Between the Seen and Unseen Scott Freng a & Andre Kehn b a University of Wyoming, Laramie, WY, USA b University of North Dakota, Grand Forks, ND, USA Version of record first published: 31 Oct To cite this article: Scott Freng & Andre Kehn (2012): Determining True and False Witnessed Events: Can an Eyewitness-Implicit Association Test Distinguish Between the Seen and Unseen, Psychiatry, Psychology and Law, DOI: / To link to this article: PLEASE SCROLL DOWN FOR ARTICLE Full terms and conditions of use: This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material.

2 Psychiatry, Psychology and Law ifirst article, 2012, 1 20 Determining True and False Witnessed Events: Can an Eyewitness-Implicit Association Test Distinguish Between the Seen and Unseen? 1 Scott Freng a and Andre Kehn b a University of Wyoming, Laramie, WY, USA; b University of North Dakota, Grand Forks, ND, USA Despite the current popularity of indirect cognitive measures in psychology, there is a paucity of research using indirect measures in the psychology and law literature. We bridge this gap in two studies in which we tested whether a modified version of the Implicit Association Test (IAT) could distinguish between seen and unseen events from a previously witnessed incident. College students (total N ¼ 69) viewed a short crime video and completed an eyewitness-implicit Association Test (eiat) and recognition task. In Study 1, the eiat and recognition task presented true and false central and peripheral details from the video. In Study 2, we used a misinformation paradigm to test the utility of the eiat. In both studies, the eiat successfully distinguished between witnessed and non-witnessed details. However, in Study 2, the eiat did not improve upon the recognition task s ability to correctly classify participants (i.e., control vs. misinformed group). Implications are discussed. Key words: eyewitness memory; indirect measure; misinformation. Rarely has methodology had more of an impact on psychology than the recent advent of implicit or indirect 2 measures in social cognition (Wittenbrink & Schwarz, 2007). Indirect measures are popular in part because they purport to overcome some limitations (e.g., social desirable responding) associated with self-report (Olson & Fazio, 2009). One of the most popular indirect measures is the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998). Since the creation of the IAT over 15 years ago, more than 600 published articles have used the methodology to examine a variety of topics including acculturation (Kim, Sarason, & Sarason, 2006), attitudes (Greenwald et al., 1998), cigarette smoking (Sherman, Rose, Koch, Presson, & Chassin, 2003), discriminatory behavior (McConnell & Leibold, 2001), fear (Ellwart, Rinck, & Becker, 2006), motives (Slabbinck, De Houwer, & Van Kenhove, 2011), product preference (Maison, Greenwald, & Bruin, 2004), self-esteem (Greenwald & Farnham, 2000), and suicidal behavior (Nock et al., 2010). The rationale of the IAT is that response latency in a sorting task provides a measure of association between categories and evaluations (Greenwald et al., 1998). For example, in the first block of a typical IAT, participants are asked to sort items (e.g., words like daisy or cockroach) Correspondence: Scott Freng, Department of Psychology, University of Wyoming, Dept 3415, 1000 E. University Ave, Laramie, WY 82071, USA. Tel: ; Fax: ; sfreng@uwyo.edu ISSN print/issn online Ó 2012 The Australian and New Zealand Association of Psychiatry, Psychology and Law

3 2 S. Freng and A. Kehn into categories by pressing a designated key on the keyboard for one category (e.g., flowers) and a different key for another category (e.g., insects). In the second block, participants complete the same sorting procedure for items with obvious evaluations (e.g., words like happy or poison), where one key is pressed for a certain evaluation (e.g., good) and another key is pressed for the opposite evaluation (i.e., bad). The third block of the IAT combines the sorting task for categories and evaluations. 3 In other words, when presented with items belonging to a specific category or evaluation (i.e., flowers þ good), one presses the left key. If presented with items in the other category or evaluation (i.e., insects þ bad), the key on the right is used. The fourth block reverses the initial sorting of evaluations. So, if good words were originally assigned to the left key (and bad to the right), good words are now assigned to the right key (and bad to the left). The fifth and final block of the IAT reverses the initial combined sorting of items into categories and evaluations, such that words in the category flowers now share the same response key as bad (with flowers þ bad to left key) and insects or good share a response key (with insects þ good to right key). The difference between the two combined sorting tasks (i.e., flowers þ good /insects þ bad vs. flowers þ bad/insects þ good) represents the strength of association. In the present example, one can imagine that it would be easier to associate flowers with good (or insects and bad) than flowers with bad (or insects with good). In the logic of the IAT, this would indicate that one has a relative preference for flowers over insects. The easier combined sorting task (e.g., flowers þ good/insects þ bad) is often said to be compatible with one s beliefs, while the sorting task that is more effortful and therefore takes longer is incompatible (e.g., flowers þ bad/insects þ good). Because indirect measures like the IAT do not rely on self-report, they may provide unique information regarding attitudes and behavior. In fact, indirect and direct measures (i.e., those based on self-report) are not always highly correlated (for a discussion see Gawronski, LeBel, & Peters, 2007). In addition, indirect measures can predict different behaviors than direct measures (Olson & Fazio, 2009; Van Bockstaele et al., 2011) and explain unique variance in behavior even after accounting for information acquired through self-report (Egloff & Schmukle, 2002; Ellwart et al., 2006; Greenwald, Poehlman, Uhlmann, & Banaji, 2009; Maison et al., 2004; Nock et al., 2010). Psychology and Law Research with the IAT Despite recent work and the current popularity of indirect measures in many areas of psychology, the utility of such measures remains largely unexplored in the psycho-legal literature (but see Dodson & Reisberg, 1991; Gray, Brown, MacCulloch, Smith, & Snowden, 2005; Gray, Mac- Culloch, Smith, Morris, & Snowden, 2003; Gregg, 2007). Some of the earliest work in adapting the IAT for a psychology and law context was conducted by Gray and colleagues (2003, 2005). In one study, Gray et al. (2005) found that pedophiles implicitly associated children and sex, whereas non-pedophiles associated adults with sex. In another study, Gray et al. (2003) used the IAT to examine the association between violence and unpleasantness in murderers. They found that psychopaths relative to non-psychopathic murderers had a diminished negative reaction to violence. Most relevant for our purposes, however, is a recent study by Sartori, Agosta, Zogmaister, Ferrara, and Castiello (2008). Sartori et al. demonstrated that a modified version of the IAT could accurately distinguish true from false autobiographical events. In six experiments, Sartori et al. (2008) illustrated that individuals who had specific autobiographical knowledge of a previous

4 True and False Witnessed Events 3 event responded faster to statements probing this knowledge when those statements shared a response key with sentences reporting true events. For example, in study five, two groups of individuals were compared on an autobiographical IAT (aiat). The first group consisted of individuals whose driver s license had been suspended due to drunk driving (i.e., guilty group), whereas the second group included individuals without license suspension due to drunk driving (i.e., innocent group). The first block of the aiat required participants to sort autobiographical statements that were either currently true (e.g., I m in front of the computer ) or false (e.g., I m climbing a mountain ). In the second block, participants sorted statements indicating autobiographical knowledge of guilt (e.g., I drove after I drank, so my driving license was suspended ) or innocence (e.g., My driving license was not suspended because I was drunk ) in regards to drunk driving. The third block combined the tasks, so either true and guilty statements (as well as false and innocent statements) shared a response key or true and innocent statements (as well as false and guilty statements) shared a response key. The fourth block reversed the keys assigned to innocent and guilty statements. Finally, the fifth block reversed the combined categorization used in the third block. By comparing the response latency for the third and fifth blocks, Sartori et al. found that guilty individuals had shorter response latencies to true autobiographical statements when they shared a response key with guilty statements (e.g., I m in front of a computer þ I drove after I drank, so my driving license was suspended ) than when true autobiographical statements and innocent statements were combined (e.g., I m in front of a computer þ My driving license was not suspended because I was drunk ). Innocent individuals showed the opposite pattern; they were faster to associate true and innocent statements. We wondered if the methodology of Sartori et al. could be extended beyond autobiographical events (i.e., knowledge about the self) to examine witnessed events (i.e., knowledge about a witnessed event). Eyewitness Memory for Peripheral and Central Details A crucial aspect of studying recollections about past events involves the importance of specific information to the witnessed event. Peripheral details are items from an event that do not impact the overall plot of an event, whereas central details involve the main activity of an event (Dalton & Daneman, 2006). For example, in a scenario where a thief tries to pry open a desk drawer with a pocket knife, the brand name of the soda can on the desk is a peripheral detail, whereas breaking into a desk drawer rather than a file cabinet is a central detail, and is critical to understanding the specific theft (Heath & Erickson, 1998). Because peripheral information is less relevant to the primary activity, details of this sort may not be encoded during the event or more easily forgotten afterward. Therefore, peripheral details should be more prone to misinformation or distortion (Heath & Erickson, 1998). Indeed, research consistently shows that peripheral details are more susceptible to misinformation than central details and conversely, individuals typically have better recollection for central items (Dalton & Daneman, 2006; Heath & Erickson, 1998). In fact, Heath and Erickson (1998) found a memory advantage for central details across four different measures of memory. However, to the authors knowledge no research has examined the memory advantage for central details using a reaction time measure like the IAT. Overview of Research Because previous research has shown the IAT to be a highly flexible method with

5 4 S. Freng and A. Kehn utility in multiple contexts (Gray et al., 2003, 2005; Kim et al., 2006; Maison et al., 2004; Nock et al., 2010), our goal was to create a modified version of the IAT (i.e., eyewitness IAT or eiat) that could distinguish between information witnessed during a previous event and information that was not witnessed. Our research expands upon Sartori et al. (2008) by exploring witnessed events rather than purely autobiographical events. In Study 1, we examined if the eiat could distinguish between seen and unseen details for both central and peripheral items from a witnessed event. Because few studies in psychology and law utilize both direct and indirect measures (but see Dodson & Reisberg, 1991; Heath & Erickson, 1998; Robinson, Johnson, & Herndon, 1997), Study 1 extended previous research on peripheral and central details by using a direct (recognition task), and an indirect (eiat) measure of memory. In Study 2, we investigated the utility of the eiat in a misinformation paradigm and tested whether the eiat could assist classification (i.e., did the participant receive accurate information or misinformation) after accounting for performance on a direct measure of memory. Study 1 To examine the utility of the eiat, participants viewed a simulated crime video and later completed an eiat and a recognition task. For the eiat and recognition tasks, we exposed participants to statements that were either true (e.g., robber had a gun ) or false (e.g., robber had a knife ) regarding the witnessed event. We also manipulated the centrality of the details. For example, main robber had a gun was a central detail, whereas robbers entered the store after the customer was a peripheral detail. Regarding performance on the eiat, we hypothesized that participants would respond faster to items seen in a simulated crime video when paired with true statements (Hypothesis 1). Based on previous research with peripheral and central cues (Dalton & Daneman, 2006; Heath & Erickson, 1998), we anticipated that participants would make fewer sorting errors on eiat trials presenting central items than on trials displaying peripheral items (Hypothesis 2). Mirroring the eiat results, and replicating previous work (Dalton & Daneman, 2006; Heath & Erickson, 1998), we also expected participants would correctly answer more statements pertaining to central details than peripheral details on the recognition task (Hypothesis 3). Method Participants Participants were 20 undergraduate students from a large Rocky Mountain university in the USA who received course credit for their participation. Two participants were dropped prior to analyses; one because they committed excessive errors on the eiat (i.e., more than 2.5 standard deviations from the mean), and one because 38% of their responses on the eiat were faster than 300 milliseconds (only one other participant had even a single response faster than 300 milliseconds). Therefore, we were left with a final sample of 18 participants (9 women, 9 men, M age ¼ 21.5 years, 94.4% White/European American). Materials and Procedure Participants read and signed an informed consent form and then watched a short video clip with up to one additional participant. The brief clip, taken from Gabbert, Memon, Allan, and Wright (2004), is approximately 90 seconds long and depicts a video store robbery perpetrated by two men. After participants viewed the video clip, we had them complete several filler

6 True and False Witnessed Events 5 questionnaires so that their memory for the events in the video could fade. Next, participants completed a recognition task followed by the eiat (both measures are described below). After the eiat, participants provided demographic information and filled out a second recognition task. The purpose of the second recognition task was to determine if the act of completing the eiat altered participants memory for the video clip. Finally, participants completed a manipulation check (detailed below) and were debriefed. Recognition task. Participants completed a 30-item recognition task in which they were asked to indicate which of two words or phrases accurately reflected what happened in the video clip (see Appendix A for a complete listing of the recognition task items and response choices). For example, the statement The main robber threatened the employee with a: could be answered correctly with gun or incorrectly with knife. Correct answers appeared as the first option approximately half the time. If participants were unsure which of the words or phrases were accurate, they could respond don t know. Items on the test were broken down as follows: (1) five statements pertained directly to the central details assessed by the eiat, (2) five statements corresponded to the peripheral details in the eiat, and (3) the remaining 20 statements were not assessed by the eiat. The order of statements was randomized across participants. Participants completed the recognition task prior to, and after, taking the eiat so we could determine if the act of completing the eiat altered participants memory or responses on the recognition task. 4 Eyewitness-Implicit Association Test. The eiat consisted of five blocks of trials (see Table 1). Statements were sorted using the A and L keys on standard keyboards. To avoid inadvertently correcting participants Table 1. Description of blocks in eyewitness implicit association test. Block 1 Block 2 Block 3 Block 4 Block 5 Response Logical Initial witnessed Initial double Reversed witnessed Reversed double Key Discrimination Discrimination Categorization Discrimination Categorization A key False sentences Not In Video sentences False þ Not In In Video sentences False þ In Video sentences Video sentences Not In Video sentences True þ Not In Video sentences L key True sentences In Video sentences True þ In Video sentences Note: In Study 1, blocks 2 and 4 presented both central and peripheral details. In addition, blocks 3 and 5 were split into sub-blocks. Specifically, one sub-block consisted of central items (i.e., block 3-central, block 5-central) and the other sub-block contained peripheral items (i.e., block 3-peripheral, block 5-peripheral).

7 6 S. Freng and A. Kehn memories, and to remain consistent with previous research (Sartori et al., 2008), we did not provide participants with feedback regarding the correctness or incorrectness of their responses. Block 1 (20 trials) of the eiat involved sorting statements that accurately (i.e., true) or inaccurately (i.e., false) described the participants (see Appendix B for a complete list of statements used). For example, for the statement I am sitting at a desk, participants would press the key indicating this was true of them currently, whereas the statement I am sitting on a couch would be sorted as a false claim. Block 2 (40 trials) required participants to sort statements about events in the video clip. For example, I saw the main robber threaten the clerk with a gun would be assigned to the in video key since it reflected what occurred in the video clip, whereas I saw the main robber threaten the clerk with a knife would be delegated to the not in video key. In block 2, participants were exposed to statements deemed in pretesting to be of central (i.e., central details; robber had a gun vs. a knife) and lesser importance (i.e., peripheral details; advertising display in store was for Coke vs. Dr. Pepper) to the event. Block 3 (80 trials) presented a combined compatible (true þ in video/false þ not in video) sorting task. Within block 3, we exposed participants to central and peripheral details (i.e., block 3-central and block 3-peripheral with 40 trials each) in separate sub-blocks and counterbalanced the order of details across participants. Block 4 (40 trials) reversed the sorting of block 2. In video statements were now assigned to the A key instead of the L key (and not in video sentences were now assigned the L key instead of the A key). Block 5 (80 trials) presented an incompatible sorting task (true þ not in video/false þ in video), but the order of central and peripheral details mirrored the presentation in block 3 (i.e., if central details were presented first in block 3, they were presented first in block 5). Manipulation check. Although we conducted pilot testing to determine the centrality of certain details from the video clip, we also assessed participants views of the importance of each item at the conclusion of the study. Specifically, for each detail (central and peripheral) tested in the study, we asked whether the fact made a difference in the robbery scenario. Participants responded on a 1 (definitely not important) to 7 (definitely important) scale. In making their determination, we asked participants to consider whether it was possible to leave out, or replace this detail without changing the main content of the plot (Talarico, Berntsen, & Rubin, 2009, p. 386). Results Manipulation Check and Timing of Recognition Task Analysis of the manipulation check questions confirmed that central items (M ¼ 5.22, SD ¼.97) were rated as more important than peripheral items (M ¼ 3.53, SD ¼ 1.02), t(17) ¼ 6.01, p 5.001, d ¼ To determine whether the eiat influenced performance on the recognition task, we compared pre post scores on: (1) the number of correctly answered peripheral statements (of five possible) and (2) the number of correctly answered central items (of five). We found a trend toward better recognition after the eiat for peripheral details, t(17) ¼ 1.84, p ¼.08, d ¼.37; preeiat recognition M ¼ 2.5, SD ¼.86 and post-eiat recognition M ¼ 2.83, SD ¼.92, but not central details. In addition to examining correct responses, we also analyzed the number of errors on the recognition task. Recall that participants could choose to answer each statement with don t know. Therefore, correct responses and errors may provide unique

8 True and False Witnessed Events 7 information. When tallying the number of incorrect responses for each individual, we ignored don t know responses. In other words, don t know responses did not influence the calculation of the total number of correct or incorrect items. As with the number of correctly answered questions, the number of incorrectly answer questions could range from 0 to 5 for central details, as well as for peripheral details. Similar to the trend on correct items, participants made fewer errors on peripheral details after the eiat, t(17) ¼ 2.41, p 5.05, d ¼.62; pre-eiat errors M ¼.39, SD ¼.61 and post-eiat errors M ¼.83, SD ¼.79. Performance on the IAT We hypothesized (Hypothesis 1) that response latencies would be faster when true statements were paired with witnessed events (and false statements were paired with non-witnessed events) than when true statements were paired with non-witnessed events (and false statements were paired with witnessed events). In order to test this hypothesis, we used the improved IAT scoring algorithm discussed in Greenwald, Nosek, and Banaji (2003). Specifically, we eliminated participants with more than 10% of responses faster than 300 milliseconds (previously mentioned in Participants section), deleted trials with latencies over 10,000 milliseconds, replaced error trials with the mean block latency for correct responses plus a 600- millisecond error penalty, and analyzed all combined sorting blocks rather than ignoring practice trials. The recommended IAT measure is D, which is the difference between compatible and incompatible block means divided by the pooled standard deviation for those blocks. Therefore, D (Greenwald et al., 2003) is similar to the effect-size measure d (Cohen, 1988). In our data, positive D scores indicated faster latencies to associate true statements with witnessed events (and false statements with non-witnessed events), whereas negative D scores represented quicker responses to pairing true statements with non-witnessed events (and false statements with witnessed events). One-sample t-tests were used to determine if the D scores for peripheral and central details were significantly different from zero. Consistent with Hypothesis 1, the eiat was able to discriminate events for both central (D ¼.50) and peripheral (D ¼.42) details, t(17) ¼ 3.54, p 5.01 and t(17) ¼ 2.70, p 5.05, respectively. Specifically, participants were faster to associate true statements with witnessed events (and false statements with nonwitnessed events) than true statements with non-witnessed events (and false statements with witnessed events). D values did not differ between central and peripheral details (p ¼.47). To investigate whether participants would make a higher percentage of errors on peripheral than central trials on the eiat, we conducted a 2 (block compatibility; compatible vs. incompatible) 6 2 (detail; central vs. peripheral) withingroups analyis of variance (ANOVA). Based on previous research with peripheral and central details (Dalton & Daneman, 2006; Heath & Erickson, 1998), we expected that participants would make fewer errors in sorting central than peripheral details on the eiat (Hypothesis 2). As predicted, participants had a lower percentage of errors in the combined sorting tasks of the eiat when dealing with central (M ¼ 13.92%, SD ¼ 12.84) than peripheral details (M ¼ 20%, SD ¼ 10.45), F(1,17) ¼ 4.99, p 5.05, Z 2 partial ¼.23. Results of the within-groups ANOVA also revealed an unsurprising main effect for block compatibility. Specifically, participants committed a higher percentage of sorting errors on incompatible trials (M ¼ 23.92%, SD ¼ 16.47) than on compatible trials (M ¼ 10.01%, SD ¼ 6.81), F(1, 17) ¼ 17.69, p.001, Z 2 partial ¼.51.

9 8 S. Freng and A. Kehn The block compatibility and detail interaction was not significant, p ¼.31. The lack of a significant interaction is important since it could be argued that the reason for no difference between the D scores for peripheral and central items was due to a higher percentage of errors on incompatible blocks for peripheral than central items. Because of the built-in penalty for error trials (mean of block plus a 600-millisecond penalty), a higher percentage of errors on incompatible trials for peripheral than central details could artificially inflate the overall incompatible compatible block difference for peripheral details. Such a differential effect of errors might make it appear that peripheral and central details are sorted equally well on the eiat when in fact it is easier to distinguish the seen from the unseen for central details (i.e., in reality central details should have a larger D score). However, the lack of an interaction negates this possibility. Performance on the Recognition Task Finally, we predicted that participants would provide more correct answers on central compared with peripheral details on the recognition task (Hypothesis 3). Because there was a trend toward performance on the recognition task to improve after exposure to the eiat, we analyzed responses on the pre-eiat recognition task (see Table 2 for descriptive statistics). 5 Consistent with Hypothesis 3, participants had higher accurate recall for central items (M ¼ 4.28, SD ¼.67) than peripheral items (M ¼ 2.5, SD ¼.86), t(17) ¼ 6.21, p 5.001, d ¼ There was no difference on the number of errors for central and peripheral details on the recognition task. Discussion In Study 1, we found that a modified version of the IAT could distinguish between the seen and unseen. Specifically, participants responded faster to true statements paired with witnessed events (and false statements with non-witnessed events) than when false statements were paired with witnessed events (and true statements with non-witnessed events). Our results extend Sartori et al. s (2008) research beyond autobiographical events to witnessed events. Therefore, the eiat represents another tool in the investigation of eyewitness memory, complimenting existing indirect measures of memory (Dodson & Reisberg, 1991; Heath & Erickson, 1998; Robinson et al., 1997). Our results also replicate previous work on peripheral and central details by demonstrating a memory advantage for central details on a recognition task (Heath & Erickson, 1998). Participants also committed fewer errors sorting central than peripheral details on the eiat. This is unsurprising since sorting statements as either witnessed or not witnessed is likely similar to the processes involved in the recognition task (Mandler & Boeck, 1974; Ratcliff, Sheu, & Gronlund, 1992). Table 2. Means, standard deviations, and zero-order correlations for study 1. Variable M (SD) Items Correct for Central Details.28 (.67) 2. Items Incorrect for Central Details.17 (.38) Items Correct for Peripheral Details 2.50 (.86) Items Incorrect for Peripheral Details.39 (.61) D score for Central Details 50 (.60) D score for Peripheral Details.42 (.66) * Note: *p

10 True and False Witnessed Events 9 However, we found that eiat performance, as indexed by D, was similar for central and peripheral details. The different results for the recognition task and eiat (i.e., D score) are consistent with the possibility that the tasks tap into different memory systems and therefore each may provide unique information (Dodson & Reisberg, 1991). Because previous research has shown that direct and indirect measures can assess distinct constructs (Nosek & Smyth, 2007) and predict different outcomes (Olson & Fazio, 2009; Robinson et al., 1997; Van Bockstaele et al., 2011), we wondered if the eiat could assist a recognition task (i.e., direct measure of memory) in classifying participants previous experience. For instance, could the eiat predict whether people were exposed to accurate information or misinformation after accounting for performance on a recognition task? This question was the focus of Study 2. Before introducing Study 2, it is important to note a methodological flaw in Study 1; we did not counterbalance the order of block compatibility. All participants completed the compatible block (i.e., true þ in video/false þ not in video; block 3) first and the incompatible block (i.e., true þ not in video/false þ in video; block 5) second. This is potentially problematic since previous research has shown that when compatible blocks occur first, the resulting difference in response latency (i.e., incompatible compatible) is larger than when participants complete the incompatible blocks first (Nosek, Greenwald, & Banaji, 2005). Therefore, the results of Study 1 may overestimate the size of D. In Study 2, we rectify this limitation by counterbalancing the order of block compatibility across participants. Study 2 In Study 2, we used a misinformation paradigm to determine if the eiat would significantly predict the classification of participants (misinformed vs. control) after controlling for performance on a direct measure. We presented participants with the same simulated crime video (Gabbert et al., 2004) used in Study 1. Employing a confederate, we manipulated exposure to either true information or misinformation regarding the crime and asked participants to complete a recognition task and the eiat. We used a co-witness (Allan & Gabbert, 2008; Dalton & Daneman, 2006; Gabbert et al., 2004; Meade & Roediger, 2002; Shaw, Garven, & Wood, 1997) rather than a written narrative (Zaragoza, McCloskey, & Jamis, 1987) or leading questions (Loftus, Levidow, & Duensing, 1992; Loftus & Palmer, 1974) to provide misinformation. We did this for two reasons. First, we felt providing misinformation through a co-witness was more ecologically valid than providing misinformation through a written narrative. Second, socially provided misinformation produces a stronger misinformation effect than does a written narrative (Akehurst, Burden, & Buckle, 2009; Gabbert et al., 2004). In addition, misinformation supposedly obtained from a co-witness is just as influential as using misleading questions (Shaw et al., 1997) and is relatively resistant to explicit warnings (Meade & Roediger, 2002). In Study 2, we expected to replicate the classic misinformation effect on the recognition task. Specifically, we predicted that participants in the misinformed group would make more errors (and provide fewer correct answers) on relevant items compared with participants in the control group (Hypothesis 1). Consistent with Study 1, we hypothesized that the eiat would distinguish the seen from the unseen (Hypothesis 2). We also expected that sorting errors on the eiat would mirror those found on the recognition task. In other words, participants in the misinformed group would make more sorting

11 10 S. Freng and A. Kehn errors on the eiat than participants in the control group (Hypothesis 3). Finally, consistent with previous research showing that indirect measures predict unique variance in behavior (Egloff & Schmukle, 2002; Ellwart et al., 2006; Greenwald et al., 2009; Maison et al., 2004; Nock et al., 2010), we hypothesized that the eiat would significantly contribute to a classification model (i.e., misinformed vs. control group) after controlling for performance on a recognition task (Hypothesis 4). Method Participants Participants were 60 undergraduate students from a large Rocky Mountain university in the USA who received course credit for their participation. Nine participants were dropped from the study; one because the participant did not follow instructions, four because of errors by the confederate, and four because participants guessed the role of the confederate. We were left with a sample of 51 participants (31 women, 20 men, M age ¼ years, 94.1% White/European American). Materials and Procedure For Study 2, each session was comprised of one participant, a confederate, and the researcher. Upon arrival, participants provided informed consent and learned they would take part in a recall task after watching a brief video clip of a store robbery (Gabbert et al., 2004). After watching the video alongside a female confederate, participants completed several filler questionnaires on a computer. Next, during a free recall task, participants were asked to briefly describe... what you can remember from the video clip. We used a rigged drawing so that the confederate would go first in the free recall task. After the rigged drawing, the researcher asked the confederate to: Briefly recall as much information from the clip as you can remember. You can mention anything that comes to mind, even if you do not think it is that important. It also does not have to be in the order that it occurred in the video clip. The confederate then discussed either 17 factual details from the video (i.e., control condition) or 17 true details from the video plus four pieces of misinformation (i.e., misinformation condition). In the misinformation condition, participants were mislead by the confederate regarding: (1) the main robber holding the gun in his left hand, (2) the lookout also having a gun, (3) the advertising display by the door being for Dr. Pepper, and (4) the customer asking the employee for the location of the Action section. Participants were randomly assigned to either the control or misinformation conditions. Following the confederate, participants reported their memory of the video clip. The confederate and participant then worked individually on several filler tasks before completing the recognition task and eiat. After participants completed the eiat, they filled out a demographic form, and finally, were debriefed. 6 Recognition task. The recognition task was identical to the measure used in Study 1 except it was shortened to 20 items. Twelve statements related to material from the video clip that were not mentioned by the confederate during the rigged free recall and four statements reflected true details from the video clip that were mentioned by the confederate. Finally, four statements covered details that were either factually correct (i.e., control group) or misinformation provided by the confederate for participants in the misinformed condition. These same four statements appeared in the eiat. As in Study 1, participants were given three options: (1) the correct event, (2) a false event, or (3) a don t know option. For participants in the

12 True and False Witnessed Events 11 misinformation condition, each piece of misleading information was presented as the false event option. Eyewitness-Implicit Association Test. The eiat was the same as the measure used in Study 1 except for four changes. First, we used a smaller subset of statements (see Appendix B) and therefore, the eiat used in Study 2 was shorter; 200 total trials compared with the 260 trials in Study 1. Second, we did not manipulate the centrality of the details. Instead, based on pretest data, we selected four details (one central and three peripheral) that were vulnerable to misinformation. Third, we manipulated exposure to misinformation in Study 2. The misleading information provided by the confederate was represented by the four statements from the not in video category. Therefore, participants in the misinformation condition contrasted witnessed in video statements with misleading not in video statements, while participants in the control condition performed a task similar to Study 1, only without manipulating the centrality of details. Finally, to overcome a flaw in the first study, we counterbalanced the order of compatible (true þ in video/false þ not in video) and incompatible (true þ not in video/false þ in video) blocks across participants. Results Performance on Recognition Task Consistent with Hypothesis 1, we were able to replicate the standard misinformation effect on the recognition task. Participants in the control group answered more of the misinformed items correctly (M ¼ 2.03, SD ¼.98) than individuals in the misinformed condition (M ¼ 1.50, SD ¼.74), t(49) ¼ 2.13, p 5.05, d ¼.62, and there was no difference between the control group and misinformed group in correctly identifying details accurately described, or not mentioned, by the confederate. We found similar results when we examined errors on the misinformed items. Specifically, participants in the misinformed condition made more errors in recognition on relevant items (M ¼ 2.14, SD ¼.83) than participants in the control group (M ¼.41, SD ¼.63), t(49) ¼ 8.43, p 5.001, d ¼ There was no difference in errors on items not mentioned by the confederate, but curiously there were more errors in the misinformed group (M ¼.82, SD ¼.73) than the control group (M ¼.38, SD ¼.62) on details that were accurately mentioned by the confederate, t(49) ¼ 2.31, p 5.05, d ¼.65. Overall, the evidence supported the successful manipulation of misinformation by the confederate. Performance on the IAT We used the same scoring criteria as Study 1 in calculating D. Unlike Study 1, we counterbalanced block compatibility to eliminate the possibility that Ds in Study 1 were artificially inflated due to the fixed block order (i.e., compatible before incompatible). However, in Study 2, order had no influence on either the magnitude of D or the percentage of errors made during the eiat (p ¼.17 and p ¼.50, respectively). Therefore, for the remaining analyses we collapse across the order of block compatibility. Consistent with Study 1 and Hypothesis 2, we found that participants in the control condition were faster to respond to true sentences combined with witnessed events (and false sentences with non-witnessed events) than true sentences with nonwitnessed events (and false sentences with witnessed events), D ¼.67, t(28) ¼ 5.75, p These results also held for participants in the misinformed condition, D ¼.95, t(21) ¼ 19.27, p In fact, D was significantly larger for the misinformed group, t(37.29) ¼ 2.20, p 5.05, equal variances not assumed.

13 12 S. Freng and A. Kehn To investigate whether the standard misinformation effect would be found for errors on the eiat, we conducted a 2 (condition; control vs. misinformed) 6 2 (block compatibility; compatible vs. incompatible) mixed ANOVA, with condition as a between groups factor and block compatibility as the within-groups factor. There was a main effect for condition, F(1, 49) ¼ 16.14, p 5.001, Z 2 partial ¼.25. Not surprisingly, participants committed a higher percentage of errors on the eiat when they were in the misinformed group (M ¼ 32.01%, SD ¼ 11.11) than in the control group (M ¼ 20.92%, SD ¼ 10.88) thus supporting Hypothesis 3. There was also a main effect of block compatibility, F(1, 49) ¼ 18.22, p 5.001, Z 2 partial ¼.27, with a higher percentage of errors made on incompatible (M ¼ 29.66%, SD ¼ 12.71) than compatible blocks (M ¼ 23.27%, SD ¼ 9.29). There was no interaction between condition and block compatibility. Finally, we used binary logistic regression to determine if answers on the selfreport recognition task and the D score on the eiat would differentiate participants exposed to misinformation from those in the control condition (see Table 3 for descriptive statistics). Specifically, we examined the four statements on the recognition task where participants were given either accurate information or misinformation. Although the number of correct answers to the four statements on the recognition task was negatively correlated to the number of incorrect responses (r ¼ 7.42), the size of the correlation was not substantial enough to suggest that the number of correct and incorrect answers were completely redundant indices of responding. Therefore, we entered the number of correct and incorrect responses to the four statements, as well as the D score from the eiat, simultaneously as predictors. The criterion was whether the participant received misinformation or not (misinformation ¼ 0, control ¼ 1). The model was able to distinguish participants in the control group from those in the misinformed group, w 2 (3, N ¼ 51) ¼ 38.84, p 5.001, Nagelkerke R 2 ¼.72. The model correctly classified 86.3% of participants. However, contrary to Hypothesis 4, the only variable that significantly contributed to this model was the number of errors made on the recognition task, with more errors making it more likely the participant was in the misinformed condition (Wald ¼ 12.97, p 5.001, Exp(B) ¼.08). 7 Discussion In Study 2, we replicated the standard misinformation effect. Participants made more errors on both the direct and indirect measures, as well as answered fewer questions correctly on the recognition task when in the misinformed group. As in Study 1, we demonstrated that the eiat could distinguish between witnessed and non-witness events. Participants were once again faster to associate true statements with witnessed events than true statements with non-witnessed events. These results held for participants who received accurate Table 3. Means, standard deviations, and zero-order correlations for study 2. Overall (N ¼ 51) Control (n ¼ 29) Misinformed (n ¼ 22) Variable M (SD) 1 2 M (SD) 1 2 M (SD) 1 2 Items Correct 1.80 (.92) 2.03 (.98) 1.50 (.74) Items Incorrect 1.16 (1.12) 7.42**.41 (.63) 7.37* 2.14 (.83) 7.27 D score.79 (.51) *.67 (.63) (.23) Note: *p 5.05, **p 5.01.

14 True and False Witnessed Events 13 information and those exposed to misinformation. However, the eiat did not explain unique variance in a classification model that included information obtained from the recognition task. Despite the current popularity of indirect measures in psychology, Study 2 found there are instances where direct measures may be difficult to improve upon. However, further research needs to specifically investigate scenarios where the eiat might be superior to direct measures in predicting the authenticity of eyewitness s reports. For example, reluctant eyewitnesses might more easily hide information during interviews (i.e., a direct measure), whereas performance on the eiat might be more difficult to modify. Several reasons could explain why the eiat did not improve classification. First, it may be that the eiat is less sensitive to memory than a recognition task. Second, the direct measure accounted for a substantial amount of variance in classification leaving little variance for the eiat to explain. In fact, the number of errors on the recognition task alone resulted in 88% correct classification. Somewhat related, the eiat may involve the process of recognition when sorting statements (Mandler & Boeck, 1974; Ratcliff et al., 1992). Therefore, an aspect of the eiat could be redundant with what is measured by a recognition task. Finally, unlike standard IATs, which have relatively low error rates (5 13% in Greenwald et al., 2003), we obtained large error rates, especially in Study 2 (overall 25.5% errors). 8 On the one hand, this is not surprising since we did provide half our sample with misinformation, but on the other hand, it is difficult to know what elevated error rates mean for the validity of the eiat. The D score on other IATs, especially those that provide error feedback and allow for answer correction is driven more by speed of responding, whereas D on the eiat results from a combination of speed of responding and errors in responding. However, Greenwald et al. (2003) argued that when conditions produce higher response latencies also produce higher error rates, analyses of latencies and error rates will support the same conclusions (p. 205). In our data, response latencies and error rates are in agreement. Therefore, errors may actually enhance the eiat s ability to distinguish between the seen and unseen. But, having elevated error rates could be problematic for two reasons. One, with more errors, there are fewer trials to calculate block means, and therefore, block mean estimates may be less reliable and valid. Second, it is difficult to determine the source of errors on the eiat. Errors on standard IATs or the aiat likely represent mistakes in sorting. But, errors on the eiat represent some combination of mistakes in responding, as well as genuine problems with remembering. Both of these issues should be examined in future research. Despite these questions, the eiat was able to distinguish witnessed and nonwitnessed events across two studies which varied importance of details and the presence of misinformation. Therefore, the eiat represents a new measure for the investigation of memory. General Discussion Our research provides preliminary evidence on the utility of a new indirect measure of eyewitness memory. Across two studies, we demonstrated that the eiat could distinguish the seen from the unseen. Specifically, we found that participants were faster to associate true statements with witnessed events than true statements with non-witnessed events. These results held for both peripheral and central details (Study 1) and were found among the accurately informed and misinformed (Study 2). Additionally, we replicated the commonly found memory advantage for central over peripheral details (Study 1) and the classic misinformation effect

15 14 S. Freng and A. Kehn (Study 2) using a recognition task. Although previous research has shown that direct and indirect measures can predict different outcomes (Olson & Fazio, 2009; Van Bockstaele et al., 2011) and explain unique variance in behavior (Egloff & Schmukle, 2002; Ellwart et al., 2006; Greenwald, Poehlman et al., 2009; Maison et al., 2004; Nock et al., 2010), we failed to find evidence that the eiat could improve upon a recognition task s ability to classify the experience of participants (i.e., exposure to accurate information vs. misinformation) in a misinformation paradigm. Indirect Measures, Research, and Theory Our results offer several methodological contributions to the literature on eyewitness memory. First, we demonstrated that the logic of the IAT could be modified and employed to differentiate witnessed and non-witnessed events. Therefore, our work provides another tool for the study of eyewitness memory, as well as expands the findings of Sartori et al. (2008). Sartori et al. s aiat was designed to differentiate true from false autobiographical memories, whereas the eiat discriminates between seen and unseen events. Because the aiat focuses on autobiographical information, it likely taps self-referent memory (Conway & Dewhurst, 1995) more than the eiat. Despite evidence of a memory advantage for self-referent material (Rogers, Kuiper, & Kirker, 1977), which may result in larger effect sizes for the aiat relative to the eiat (Agosta, Ghirardi, Zogmaister, Casitello, & Sartori, 2011), we still found that the eiat was sensitive enough to distinguish witnessed from non-witnessed events. The present research also contributes to the understanding of the complex picture of eyewitness memory. Although we were able to replicate the memory advantage of central over peripheral details on a recognition task, and by examining the sorting errors on the eiat, we found no such advantage on the D index from the eiat. Therefore, conclusions regarding a memory advantage might depend upon the method used to measure it. Research on misinformation has also found that method matters. For example, Dodson and Reisberg (1991) reported that although misinformation impaired performance on a direct measure of memory (i.e., recognition test), it did not influence an indirect measure. Additionally, Heath and Erickson (1998) found that an indirect measure (i.e., sentence completion task disguised as a test of free association) was more resilient to misinformation than other measures. Given the complex effects of misinformation on direct and indirect measures, the dearth of research using indirect measures in psychology and law contexts, and the fact that researchers continue to debate the mechanism underlying the acceptance of misinformation (Davis & Loftus, 2007), future investigations into eyewitness memory may benefit from including both direct and indirect measures to examine the nuanced effects of manipulations in memory research. Indirect Measures and Implications for Application Because the logic of the eiat necessitates the generation of statements reflecting what was witnessed and not witnessed, the measure is limited to situations where an investigator knows, or can infer what was seen and unseen. In some cases, an investigator may be able to deduce the details of a scenario from other sources (e.g., additional witnesses, surveillance footage, and physical trace evidence). For situations that fail to meet this requirement, it is possible that adapting other indirect techniques such as the Go/No Go Association Task (GNAT, Nosek & Banaji, 2001) or the single category IAT (SC- IAT, Karpinski & Steinman, 2006) may provide useful alternatives. The GNAT