due in 24 hours for PHILLIS YOUNG

Journal of Applied Research in Memory and Cognition 5 (2016) 270–276

Contents lists available at ScienceDirect

Journal of Applied Research in Memory and Cognition

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / j a r m a c

The Effects of Verbal Descriptions on Eyewitness Memory: Implications for the Real-World�

Laura Mickes ∗

University of London, United Kingdom

The criminal justice system depends on verbal accounts of crimes. Can the act of reporting a crime harm eyewitness memory for the perpetrator of that crime? The answer is yes according the verbal overshadowing effect. The verbal overshadowing effect describes the finding that memory is adversely affected after verbally describing a previously presented item (e.g., face). Often in studies of the verbal overshadowing effect, participants watch a video of a mock crime, describe the perpetrator (verbal condition) or engage in another task (control condition). In many of these studies, including the original (Schooler & Engstler-Schooler, 1990) and replication studies (Alogna et al., 2014), memory for a perpetrator is tested on target-present lineups, and, if described, the perpetrator is less often identified. However, it is unknown whether or not the lower identification rate is due to reduced discriminability or due to more conservative responding after providing a description. The verbal overshadowing effect ought to be defined as a reduction in discriminability, which is measured by taking both the correct ID rates (from target-present lineups) and false ID rates (from target-absent lineups) into consideration. Another important and independent measure is the reliability of identifications (i.e., the positive predictive value of a suspect identification made with a given level of confidence). As matters stand, the take-home message is this: too little information currently exists to allow for an assessment of the effects of verbal descriptions on discriminability and reliability; thus, the field is not yet in a position to offer clear guidance for practice in the criminal justice system.

R

c e s ( p c i t d c q

[ d C

Disc

i ( a o e e g e i m

Keywords: Eyewitness memory, Verbal overshadowing, relationship, Policy recommendations

eporting Crimes and Making Identifications

From a criminal offence to completion of the ensuing court ase, the criminal justice system follows a linear process. The ntire process usually takes at least several months, and as hown in Figure 1 may include the crime, report, investigation if deemed worthy by the police), eyewitness identification (ID) rocedure administration, formal charge against the suspect, and ourt case. The timescale in Figure 1 represents averages of ndicted cases in the UK (UK Ministry of Justice, 2011). Repor- ing a crime to the authorities inevitably involves describing

etails of the crime and the perpetrator(s). Emergency services, all dispatchers, and investigating officers are trained to ask uestions about the crime in such a way that as much accurate

Author Note This work was supported by the Economic and Social Research Council

ES/L012642/1]. The content is solely the responsibility of the author and oes not necessarily reflect the views of the Economic and Social Research ouncil.

J

D T

b r

riminability, Reliability, Confidence–accuracy

nformation as possible is gathered in a non-suggestive way Technical Working Group for Eyewitness Evidence, 1999), nd online self-report forms follow a similar structure (College f Policing, 2013). To answer questions about the perpetrator, yewitnesses are asked to describe the individual. If needed, yewitnesses are prompted to consider the perpetrator’s age, ender, ethnicity, height, build, distinguishing characteristics, tc. (Association of Chief Police Officers, 2016). If police later dentify a suspect, as part of the investigation, a lineup procedure

ay be administered to eyewitnesses.

� Please note that this paper was handled by the current editorial team of ARMAC. ∗ Correspondence concerning this article should be addressed to Laura Mickes, epartment of Psychology, Royal Holloway, University of London, Egham W20 0EX, United Kingdom. Contact: [email protected]

A lineup consists of the police suspect (who may or may not e the perpetrator) and several other individuals who physically esemble the perpetrator, called “fillers.” The lineup members

WHAT ARE THE EFFECTS OF VERBAL DESCRIPTIONS ON EYEWITNESS MEMORY? 271

a t v m

T

y e d b M s t g p o m 2 2 & b o o e

t c m 8 w t C p d o E a e s v t b E

w i o

A

B

F E

( d i d c i f

b h c a r i 2 c w t R

i c i &

Figure 1. Criminal justice system case progression in the UK.

re all presented via photos or videos, and the witness attempts o identify the perpetrator (ID in Figure 1). What if the task of erbally describing the perpetrator has a detrimental effect on emory for that very perpetrator?

he Verbal Overshadowing Effect

That is the implication of a finding first reported nearly 30 ears ago (Schooler & Engstler-Schooler, 1990). In a set of xperiments, participants viewed a video of a mock robbery uring the study phase, and either described the perpetrator (ver- al condition) or engaged in a control task (control condition). emory for the perpetrator, or target, was tested on an 8-person

imultaneous target-present lineup. Surprisingly, participants in he verbal condition were less able to correctly identify the tar- et than those who were not asked to verbally describe the erpetrator. This counterintuitive finding, termed the verbal vershadowing effect, inspired much followup research with ixed results (e.g., Dodson, Johnson, & Schooler, 1997; Finger,

002; Finger & Pezdek, 1999; Kitagami, Sato, & Yoshikawa, 002; Nakabayashi, Lloyd-Jones, Butcher, & Liu, 2012; Smith

Flowe, 2014; Wickham & Swift, 2006). Because of this, and ecause a meta-analysis revealed a much smaller effect than the riginal experiments (Meissner & Brigham, 2001), two of the riginal experiments were the object of a large direct replication ffort (Alogna et al., 2014).

Figure 2 shows a schematic of the experimental design of he two replication experiments. In both experiments, the pro- edure was delineated by the study phase (presentation of the ock crime video) and the test phase (memory tested on an

-person lineup). The only difference between the experiments as the timing of the experimental manipulation (where par-

icipants either verbally described the perpetrator or did not). learly, the experimental analog is a much shorter version of the rotracted criminal justice system in Figure 1, which is a point iscussed later. In Experiment 1, the experimental manipulation ccurred immediately after the study phase (Figure 2A) and in xperiment 2, the experimental manipulation occurred 20 min fter the study phase (Figure 2B). The effect replicated. In both xperiments, the correct ID rate (i.e., the proportion of guilty uspects identified from target-present lineups) was lower in the erbal condition, but markedly lower when the verbal descrip- ion was given 20 min after the study phase and immediately efore the test (and the effect sizes were small, especially in xperiment 1).

However, by comparing only correct ID rates, it is unclear

hether the difference is due to a difference in discriminabil-

ty (the ability to distinguish innocent from guilty suspects) r response bias (the likelihood of choosing a lineup member)

t r a

igure 2. Procedural order of the replication studies for Experiment 1 (A) and xperiment 2 (B) in Alogna et al. (2014).

Clare & Lewandowsky, 2004; Meissner & Brigham, 2001). To isentangle the two possible explanations for the difference, it s necessary to include target-absent lineups in the experimental esign. By doing so, false ID rates (i.e., the proportion of inno- ent suspects identified from target-absent lineups) can be taken nto account and discriminability can be measured separately rom response bias (Mickes & Wixted, 2015).

Discriminability in Verbal Overshadowing: A Matter of Concern for Policymakers

A veridical verbal overshadowing effect ought to be defined y a reduction in discriminability (i.e., lower correct ID rates and igher false ID rates) in the verbal condition compared to the ontrol condition. Discriminability cannot be measured by only

reduction in correct ID rates. It follows that the results of the eplication studies cannot inform whether or not discriminability s affected after providing a verbal account (Mickes & Wixted, 015; Rotello, Heit, & Dube, 2015). To be informed about dis- riminability, receiver operating characteristic (ROC) analysis, hich measures objective discriminability of lineup data, needs

o be conducted (Gronlund, Wixted, & Mickes, 2014; National esearch Council, 2014; Wixted & Mickes, 2012).

ROC analysis was recently introduced to measure discrim- nability in lineup data (Wixted & Mickes, 2012), and there is urrently some resistance to its use in the field of eyewitness dentification research (Wells, Smalarz, & Smith, 2015; Wixted

Mickes, 2015a, 2015b). Some researchers continue to support

he use of the diagnosticity ratio (DR; correct ID rate/false ID ate) to measure discriminability in preference to ROC analysis, rguing that ROC analysis is not appropriate for lineups (Wells

WHAT ARE THE EFFECTS OF VERBAL DESCRIPTIONS ON EYEWITNESS MEMORY? 272

Table 1 Correct ID Rates from Alogna et al. (2014), Hypothetical False ID Rates, and Corresponding d′ Scores and Diagnosticity Ratios (DR). The Hypothetical Val- ues are in Bold Font

Different discriminability

Equal discriminability

Verbal Control Verbal Control

Experiment 1 Correct ID rate 0.51 0.55 0.51 0.55 False ID rate 0.11 0.02 0.02 0.02 d′ 1.27 2.18 2.18 2.18 DR 4.81 27.49 32.48 27.50

Experiment 2 Correct ID rate 0.38 0.54 0.38 0.54 False ID rate 0.06 0.02 0.01 0.02

e a r t c b m c 2 a

o e i c e e G b a a c o t

f l i b i s w c

R ( f d i

Table 2 Concerns, Relevant Analyses, and Goals for Different Decision-Makers

Policymakers Courts

Concern Discriminability Reliability Analysis Receiver operating

characteristic Confidence-accuracy characteristic

Goal High discriminability IDs made with high

h m w s o a d i w t

c s t v r b a b p 2

v r c a n ( o e a

i c t i i r u

d′ 1.26 2.16 2.15 2.15 DR 6.37 27.18 54.29 27.00

t al., 2015). However, it is not clear how one can successfully rgue that it is acceptable to measure overall correct and false ID ates from lineups, which are needed to compute the DR, while at he same time arguing that it is unacceptable to compute all other orrect and false ID rates, which are needed to plot the ROC (e.g., y setting a more conservative standard and not counting any ID ade with very low confidence). Moreover, because the DR

onfounds response bias and discriminability (Gronlund et al., 014), it is not the pure measure of discriminability that ROC nalysis is.

ROC analysis is widely accepted as the preferred measure f discriminability in other fields (e.g., diagnostic medicine, xperimental psychology, machine learning, physics, etc.), and t was recently deemed superior to the DR by a prestigious ommittee of the National Academy of Sciences charged with valuating research methodologies and empirical findings in yewitness identification (National Research Council, 2014). iven its widespread use in other fields and its recent backing y the National Research Council, my own view is that it is only

matter of time before eyewitness identification researchers as whole accept ROC analysis as the proper way to measure dis- riminability. Nevertheless, for now, it also seems fair to say that thers disagree with my position on this issue. Only time will ell how this debate will ultimately be resolved.

To conduct ROC analysis, correct ID rates are plotted against alse ID rates, resulting in ROC curves for each condition. The arger the area under the ROC curve, the better the discriminabil- ty. In other words, the larger the area under the ROC curve, the etter the identification procedure is at distinguishing between nnocent and guilty suspects. Thus, for there to be a verbal over- hadowing effect, the area under the verbal condition ROC curve ould need to be smaller than that of the control condition ROC

urve. Though false ID rates, essential for the construction of

OC curves, are not available from the replication studies

because target-absent lineups were not included), hypothetical alse ID rates can be used to demonstrate the point about iscriminability. Table 1 shows the correct ID rates reported n Alogna et al. (2014) and hypothetical false ID rates. The

P u w r

confidence are highly accurate

ypothetical false ID rates are in bold font. A parametric easure of discriminability, d′, and diagnosticity ratio, DR, hich are computed using the correct and false ID rates are also

hown in bold font. Figure 3 shows four possible ROC outcomes f the replication Experiment 1 (A and B) and Experiment 2 (C nd D). In both experiments, it is possible, given the available ata, that the verbal condition falls on a lower ROC, as shown n Figure 3A and C. If the data yielded this pattern, then that ould be a clear difference in discriminability, and one could

hen conclude that there is a verbal overshadowing effect. It is also possible, given the available data, that the verbal

ondition falls on the same ROC as the control condition, as hown in Figure 3B and D. If the data yielded this pattern, then here would not be a difference in discriminability, and thus no erbal overshadowing effect, but there would be a difference in esponse bias between the two conditions. Though this point can e demonstrated by using overall correct and false ID rates, ide- lly confidence ratings associated with the identifications would e used in the analysis so that the entire locus of ROC operating oints per condition can be plotted (Mickes, Flowe, & Wixted, 012).

When and if differences in discriminability arise after a erbal description is one fact worth knowing, and the ROC esults should be used to aid decision-makers (e.g., police chiefs) harged with making procedural endorsements. Although ROC nalysis provides essential information to policymakers, it does ot provide particularly useful information to triers of fact judges and juries). Triers of fact are interested in the reliability f an ID, and that information is provided by an altogether differ- nt analysis. The different concerns of different decision-makers nd the relevant analyses are shown in Table 2.

Reliability in Verbal Overshadowing: A Matter of Concern for the Courts

Whether or not discriminability is affected by verbal reports s not a matter for judges and jurors. In the court of law, the oncern is about reliability. Reliability is measured by the posi- ive predictive value (PPV) of suspect identifications. The PPV s the probability that a suspect who was identified by a witness s the perpetrator. For the discussion that follows, equal base ates (i.e., half target-present lineups and half target-absent line- ps) are assumed for the sake of simplicity. Generally speaking,

PV varies directly with the base rate of target present line- ps. The PPV can be measured in several different ways. One ay is to compute a DR. Using the data in Table 1 and the cor-

esponding ROC curves in Figure 3B to compute DR values,

WHAT ARE THE EFFECTS OF VERBAL DESCRIPTIONS ON EYEWITNESS MEMORY? 273

False ID Rate

0 .0 0 0 .0 5 0 .1 0 0 .1 5 0 .2 0 0 .2 5 0 .3 0

C o rr

e c t

ID R

a te

0 .0

0 .2

0 .4

0 .6

0 .8

Control Condition

Ve rba l Cond ition

False ID Rate

0 .0 0 0 .0 5 0 .1 0 0 .1 5 0 .2 0 0 .2 5 0 .3 0 0 .0

0 .2

0 .4

0 .6

0 .8

False ID Rate

0 .0 0 0 .0 5 0 .1 0 0 .1 5 0 .2 0 0 .2 5 0 .3 0

C o rr

e c t

ID R

a te

0 .0

0 .2

0 .4

0 .6

0 .8

False ID Rate

0 .0 0 0 .0 5 0 .1 0 0 .1 5 0 .2 0 0 .2 5 0 .3 0 0 .0

0 .2

0 .4

0 .6

0 .8 A B

C D

Figure 3. ROC curves constructed with correct ID rates and hypothetical false ID rates for Experiment 1 (A and B) and Experiment 2 (C and D) of Alogna et al. (2014). The ROC curves in A and C show a clear discriminability advantage for the control condition. The ROC curves in B and D show no discriminability difference, b ata, it u

f D m t m i u d

w s n u a

R fi F a

t v c a i a w s d ( (

a a B u r

ut more conservative responding for the verbal condition. With the existing d nknown.

or the verbal condition DR = 32.5 and for the control condition R = 27.5. The higher DR scores in the verbal condition would ean that reliability is better in that condition (despite having

he same discriminability). A related but more complete way to easure reliability is to conduct confidence-accuracy character-

stic (CAC) analysis (Mickes, 2015). Like the DR, CAC analysis ses only correct and incorrect suspect identifications. Thus, the ependent measure, PPV, is defined by

PPV = Sg Sg + Si

, (1)

here Sg is the number of correct IDs (i.e., the number of guilty uspects identified from target-present lineups). Si refers to the umber of innocent suspects identified from target-absent line- ps. When the base rates are equal, Sg and Si can be thought of s the correct and false ID rates, respectively.

Using the indicative ROC curves from Figure 3A, three

OC points can be computed for low, medium, and high con- dence levels for both control and verbal conditions, shown in igure 4A. The PPV is computed for every level of confidence nd shown in Figure 4B. In Figure 4A, the ROC is lower for

a m r C

is possible to have different or equal discriminability, and which it is remains

he verbal condition; in Figure 4B, the PPV is also lower for the erbal condition and by the same amount. In this case the verbal ondition has simultaneously lower discriminability (Figure 4A) nd lower reliability (Figure 4B). Generally higher discrim- nability is associated with higher reliability, but this is not lways the case. This can be seen clearly from Figure 4C and D, here the same ROC curves are used but the ROC points are

hifted towards more liberal responding for the control con- ition. Discriminability is still lower for the verbal condition Figure 4C), but the PPV is actually higher in the verbal condition Figure 4D).

The point is that the two analyses answer different questions nd, while they likely agree most of the time in practice, they re potentially dissociable (as they are in Figure 4C and D). ecause of this possibility, it is necessary to analyze the data sing both ROC and CAC analyses. Furthermore, the fact that the esults of CAC analysis are easier to understand give it a distinct

dvantage over the DR. For example, 98% versus 92% accurate akes more sense than DR values of 40 versus 11. Therefore,

esearch shedding light on the reliability of identifications using AC analysis is needed. Moreover, when and if differences in

WHAT ARE THE EFFECTS OF VERBAL DESCRIPTIONS ON EYEWITNESS MEMORY? 274

Confidence

Low Mediu m High

Low Mediu m High

0.5

0.6

0.7

0.8

0.9

1.0

Confidence

P P

V

0.5

0.6

0.7

0.8

0.9

1.0

Control Condition Verbal Condition

A

False ID Rate

0.00 0.05 0.10 0.15 0.20 0.25 0.30

C o

rr e c t

ID R

a te

0.0

0.2

0.4

0.6

0.8

False ID Rate

0.00 0.05 0.10 0.15 0.20 0.25 0.30

C o

rr e c t

ID R

a te

0.0

0.2

0.4

0.6

0.8

B

C D

P P

V

F d C) d bal c c

r t a (

i s c j F t t c a

i r l b r

i t r m i r t i a R d e t a

I v t e

igure 4. Hypothetical ROC curves and CAC curves. Both ROC curves (A an iffer with higher PPV in the control condition (B), and higher PPV in the ver onducted to measure discriminability and reliability, respectively.

eliability arise after a verbal description is worth knowing, and he results should be used to aid decision-makers (e.g., judges nd jurors) charged with making judgments about culpability see Table 2).

Conclusions

Collecting verbal reports from eyewitnesses of crimes is an nescapable necessity. As the research currently stands, we lack ufficient information about discriminability (a matter of con- ern for policymakers) and reliability (a matter of concern for udges and jurors) to make recommendations to guide practice. urthermore, different patterns may arise that are contingent on

he intervals between exposure and description and identifica- ion. After all, different retention intervals differentially affect orrect ID rates (Alogna et al., 2014). Does that finding reflect

difference in discriminability or a difference in response bias? There was a glimpse in the replication studies that discrim-

nability is lower after time lapses between the crime and the

eport. In Experiment 1, in which the experimental manipu- ation occurred immediately after the study phase and 20 min efore the identification test (see Figure 2A), the correct ID ates and the filler ID rates (i.e., identifications made to fillers

c a t T

show lower discriminability for the verbal condition, but the associated PPVs ondition (D). This illustrates why ROC analysis and CAC analysis need to be

n the target-present lineup) were lower in the verbal condition han in the control condition. This pattern suggests a shift in esponse bias. However, in Experiment 2, in which the experi- ental manipulation occurred 20 min after the study phase and

mmediately before the lineup test (see Figure 2B), the filler ID ates were no different for the verbal condition versus the con- rol condition despite the fact that correct ID rates were lower n the former condition. This pattern suggests that there was not

shift in response bias, but lower discriminability. However, OC analysis is required to definitively answer the question of iscriminability and importantly, if the ROC curves are repeat- dly lower with longer delays between crime and description, hen the police should encourage eyewitnesses to report crimes s soon as possible.

What about reliability? That is what CAC analysis will reveal. f the CAC curves are higher, but the ROC curve is lower in the erbal condition (a possibility demonstrated in Figure 4C and D), hen the conclusion would be that the verbal overshadowing ffect is real, but, compared to the control condition, identifi-

ations made with high confidence from the verbal condition re more reliable anyway. This scenario may arise because the ask of verbally describing the perpetrator is a challenging one. hat fact may be appreciated by the participants in that condition

ESC

w h i q l w c

w t d t i 2 a n m r fi W W W h t t

A

A

B

C

C

D

F

F

G

H

K

M

M

M

M

N

N

P

R

S

S

S

T

U

WHAT ARE THE EFFECTS OF VERBAL D

ho in turn may be more cautious to make an identification with igh confidence (Clare & Lewandowsky, 2004). Both hypothet- cal CAC scenarios in Figure 4 are possible. Another important uestion is whether the timing of the verbal description and ater identification differentially affect reliability (as it might ith discriminability). The research has yet to, but needs to, be

onducted. The effects of verbal descriptions on eyewitness memory is

orth investigating using procedures that are more protracted o mimic the experience of real eyewitnesses (i.e., eyewitnesses o not provide a verbal description immediately after seeing he perpetrator, nor would a lineup procedure be administered mmediately after describing the perpetrator; Mickes & Wixted, 015). In addition to extending the procedural timeline, target- bsent lineups need to be included, and the appropriate analyses eed to be conducted. Confidence should be collected (1) to easure discriminability (with ROC analysis) and to measure

eliability (with CAC analysis), and (2) because confidence at rst identification is diagnostic of accuracy (e.g., Brewer & ells, 2006; Horry, Palmer, & Brewer, 2012; Palmer, Brewer, eber, & Nagesh, 2013; Sauer, Brewer, Zweck, & Weber, 2009; ixted, Mickes, Clark, Gronlund, & Roediger, 2015). Once we

ave a body of work that replicates and researchers have come o a general consensus about the interpretations of the results, hen we can guide practice. But we are not quite there yet.

References

logna, V. K., Attaya, M. K., Aucoin, P., Bahnik, S., Birch, S., & Birt, A. R. (2014). Registered replication report: Schooler & Engstler-Schooler (1990). Perspectives on Psychological Science, 9, 556–579. http://dx.doi.org/10.1177/1745691614545653

ssociation of Chief Police Officers. (2016). True vision association of chief police officers. http://report-it.org.uk/home

rewer, N., & Wells, G. L. (2006). The confidence–accuracy relation- ship in eyewitness identification: Effects of lineup instructions, foil similarity, and target-absent base rates. Journal of Experimental Psychology: Applied, 12, 11–30.

lare, J., & Lewandowsky, S. (2004). Verbalizing facial memory: Criterion effects in verbal overshadowing. Journal of Experimen- tal Psychology: Learning, Memory, and Cognition, 30, 739–755. http://dx.doi.org/10.1037/0278-7393.30.4.739

ollege of Policing. (2013). Investigation: Investigative interview- ing. https://www.app.college.police.uk/app-content/investigations/ investigative-interviewing/#structuring-a-witness-interview

odson, C. S., Johnson, M. K., & Schooler, J. W. (1997). The verbal overshadowing effect: Why descriptions impair face recogni- tion. Memory & Cognition, 25, 129–139. http://dx.doi.org/10.3758/ BF03201107

inger, K. (2002). Mazes and music: Using perceptual processing to release verbal overshadowing. Applied Cognitive Psychology, 16, 887–896. http://dx.doi.org/10.1002/acp.922

inger, K., & Pezdek, K. (1999). The effect of the cognitive interview on face identification accuracy: Release from verbal overshadowing. Journal of Applied Psychology, 84, 340–348.

ronlund, S. D., Wixted, J. T., & Mickes, L. (2014). Evaluating eyewitness identification procedures using receiver operating char- acteristic analysis. Current Directions in Psychological Science, 23, 3–10. http://dx.doi.org/10.1177/0963721413498891

W

RIPTIONS ON EYEWITNESS MEMORY? 275

orry, R., Palmer, M. A., & Brewer, N. (2012). Backloading in the sequential lineup prevents within-lineup criterion shifts that undermine eyewitness identification performance. Journal of Exper- imental Psychology: Applied, 18, 346–360.

itagami, S., Sato, W., & Yoshikawa, S. (2002). The influence of test-set similarity in verbal overshadowing. Applied Cognitive Psychology, 16, 963–972. http://dx.doi.org/10.1002/acp.917

eissner, C. A., & Brigham, J. C. (2001). A meta-analysis of the ver- bal overshadowing effect in face identification. Applied Cognitive Psychology, 15, 603–616. http://dx.doi.org/10.1002/acp.728

ickes, L. (2015). Receiver operating characteristic analysis and con- fidence accuracy characteristic analysis in investigations of system variables and estimator variables that affect eyewitness memory. Journal of Applied Research in Memory and Cognition, 4, 93–102. http://dx.doi.org/10.1016/j.jarmac.2015.01.003

ickes, L., Flowe, H. D., & Wixted, J. T. (2012). Receiver operating characteristic analysis of eyewitness memory: Comparing the diag- nostic accuracy of simultaneous versus sequential lineups. Journal of Experimental Psychology: Applied, 18, 361–376.

ickes, L., & Wixted, J. T. (2015). On the applied implications of the “verbal overshadowing effect”. Perspectives on Psychological Sci- ence, 10, 400–403. http://dx.doi.org/10.1177/1745691615576762

akabayashi, K., Lloyd-Jones, T. J., Butcher, N., & Liu, C. H. (2012). Independent influences of verbalization and race on the configural and featural processing of faces: A behavioral and eye movement study. Journal of Experimental Psychology: Learning, Memory, and Cognition, 38, 61–77. http://dx.doi.org/10.1037/a0024853

ational Research Council. (2014). Identifying the culprit: Assessing eyewitness identification. Washington, DC: The National Academies Press. http://dx.doi.org/10.17226/18891

almer, M. A., Brewer, N., Weber, N., & Nagesh, A. (2013). The confidence–accuracy relationship for eyewitness identification deci- sions: Effects of exposure duration, retention interval, and divided attention. Journal of Experimental Psychology: Applied, 19, 55–71.

otello, C. M., Heit, E., & Dube, C. (2015). When more data steer us wrong: replications with the wrong dependent measure perpet- uate erroneous conclusions. Psychonomic Bulletin and Review, 22, 944–954. http://dx.doi.org/10.3758/s13423-014-0759-2

auer, J., Brewer, N., Zweck, T., & Weber, N. (2009). The effect of retention interval on the confidence–accuracy relationship for eye- witness identification. Law and Human Behavior? 34, 337–347. http://dx.doi.org/10.1007/s10979-009-9192-x

chooler, J. W., & Engstler-Schooler, T. Y. (1990). Verbal overshad- owing of visual memories: Some things are better left unsaid. Cognitive Psychology, 22, 36–71. http://dx.doi.org/10.1016/0010- 0285(90)90003-M

mith, H. M. J., & Flowe, H. D. (2014). Roc analysis of the ver- bal overshadowing effect: Testing the effect of verbalisation on memory sensitivity. Applied Cognitive Psychology, 29, 159–168. http://dx.doi.org/10.1002/acp.3096

echnical Working Group for Eyewitness Evidence. (1999). Eyewitness evidence: A guide for law enforcement. Washington, DC: United States Department of Justice, Office of Justice Programs, National Institute of Justice. https://www.ncjrs.gov/pdffiles1/nij/178240.pdf

K Ministry of Justice. (2011, June). Time intervals survey of criminal proceedings in magistrates’ courts. https://www.gov.uk/ government/uploads/system/uploads/attachment data/file/217768/ tis-bulletin-0611.pdf

ells, G. L., Smalarz, L., & Smith, A. M. (2015). Roc analysis of line- ups does not measure underlying discriminability and has limited value. Journal of Applied Research in Memory and Cognition, 4, 313–317. http://dx.doi.org/10.1016/j.jarmac.2015.08.008

ESC

W

W

W

W

W

WHAT ARE THE EFFECTS OF VERBAL D

ickham, L. H. V., & Swift, H. (2006). Articulatory suppression atten- uates the verbal overshadowing effect: A role for verbal encoding in face identification. Applied Cognitive Psychology, 20, 157–169. http://dx.doi.org/10.1002/acp.1176

ixted, J. T., & Mickes, L. (2012). The field of eyewitness memory should abandon probative value and embrace receiver operating characteristic analysis. Perspectives on Psychological Science, 7, 275–278. http://dx.doi.org/10.1177/1745691612442906 http://pps.sagepub.com/content/7/3/275.abstract

ixted, J. T., & Mickes, L. (2015a]). Evaluating eyewitness identifi- cation procedures: Roc analysis and its misconceptions. Journal of Applied Research in Memory and Cognition, 4, 318–323. http://dx.doi.org/10.1016/j.jarmac.2015.08.009

RIPTIONS ON EYEWITNESS MEMORY? 276

ixted, J. T., & Mickes, L. (2015b]). Roc analysis measures objec- tive discriminability for any eyewitness identification procedure. Journal of Applied Research in Memory and Cognition, 4, 329–334. http://dx.doi.org/10.1016/j.jarmac.2015.08.007

ixted, J. T., Mickes, L., Clark, S. E., Gronlund, S. D., & Roediger, H. L., III. (2015). Initial eyewitness confidence reliably predicts eyewit- ness identification accuracy. American Psychologist, 70, 515–526.

Received 1 May 2016; received in revised form 3 July 2016;

accepted 3 July 2016