Evaluating the impact of first-yes-counts instructions on eyewitness performance using the two-high threshold eyewitness identification model

Abstract

In eyewitness research, multiple identification decisions in sequential lineups are typically prevented by telling participants that only their first identification decision counts. These first-yes-counts instructions are incompatible with standard police protocols prescribing that witnesses shall see the entire lineup. Horry et al. were the first to experimentally test how this discrepancy between eyewitness research and standard police protocols affects eyewitness identification decisions. Here, the two-high threshold eyewitness identification model was used to disentangle the effect of the first-yes-counts instructions on the detection and guessing processes underlying eyewitness identification decisions. We report both a reanalysis of Horry et al.’s data and a conceptual replication. Both the reanalysis and the results of the conceptual replication confirm that first-yes-counts instructions do not affect the detection of the culprit but decrease the probability of guessing-based selections. To improve the ecological validity, research on sequential lineups should avoid first-yes-counts instructions.

The effects of lineup size on the processes underlying eyewitness decisions

“…Our aim was to use a base model that was as simple as possible. Therefore, we imposed parameter restrictions onto the 2-HT eyewitness identification model that were the same as those used in prior applications of this model 11 , 12 , 17 . First, given that the same sets of suspects and fillers were used in all conditions, lineup fairness must necessarily be the same across the four conditions.…”

“…The more ecologically valid sequential lineup protocol applied here gives participants the opportunity to change their mind by allowing them to select a lineup member later in the sequence even though another lineup member has already been selected earlier. In fact, there is direct evidence that the probability of guessing-based selection is significantly less likely when first-yes-counts instructions are used than when the standard police protocol is used 17 .…”

“…Materials and procedure were essentially as described by Winter et al 12 , 17 and Menne et al 18 with the exception of the lineup size manipulation described below. The experiment was conducted online.…”

“…In validation studies, it has been empirically shown that the parameters of the 2-HT eyewitness identification model sensitively reflect manipulations of the processes they were intended to measure in both simultaneous and sequential lineups 11 , 12 . The model has already been successfully applied to examine the effects of first-yes-counts instructions on guessing-based selection 17 and to measure the effects of lineup fairness 18 .

Figure 1 Illustration of the 2-HT eyewitness identification model.

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On the advantages of using AI-generated images of filler faces for creating fair lineups

“…We used the same mock-crime videos, the same facial photographs of the suspects and the same database-derived facial filler photographs as in our previous experiments 13 , 14 , 28 , 29 . The facial images of the AI-generated fillers were newly created for the purpose of the present experiment.…”