N = 2904) were tested with a static photo lineup; the viewing angle of the lineup members was the same or different from the perpetrator at encoding. In Experiment 2, participants (N = 1430) were tested with a novel interactive lineup in which they could rotate the lineup faces into any angle. In both experiments, discrimination accuracy was greater when the viewing angle at encoding and test matched. Participants reinstated the angle of the interactive faces to match their encoding angle. Our results highlight the importance of encoding specificity for eyewitness identification, and show that people actively seek out information in the testing environment that matches the study environment to aid memory retrieval.We examined how encoding view influences the information that is stored in and retrieved from memory during an eyewitness identification task. Participants watched a mock crime and we varied the angle from which they viewed the perpetrator. In Experiment 1, participants ( Lineup members are shown from the shoulders up, facing forward, even if a witness viewed the perpetrator from a different angle at the time of the crime . The National Academy of Sciences recently called for the development of new technology to improve lineup identification accuracy3. In this paper, we heed this call and examine whether discrimination accuracy can be improved by enabling witnesses to see the lineup faces from the same angle that the perpetrator’s face was seen during the crime. We also introduce a novel interactive lineup procedure to test whether during the lineup people spontaneously reinstate the angle at which they saw the perpetrator, and if so, whether pose-reinstatement is associated with increased discrimination accuracy.Worldwide, witnesses are given lineups to help the police identify criminal perpetrators. A lineup contains the police suspect—who may or may not be the perpetrator—embedded among ‘fillers’, who are individuals who look similar to the police suspect and are known by the police to be innocent. The goal of the eyewitness is to identify the perpetrator if the perpetrator is present in the lineup (known as a correct identification) or to identify no one if the perpetrator is absent from the lineup (known as a correct rejection). The ability of the eyewitness to distinguish the presence or absence of the perpetrator is known as discrimination accuracy. In many countries , lineups consist of static photographsencoding specificity—holds that the correspondence in the context in which memories are acquired and retrieved is a powerful determinant of memory accuracy4. One example is that divers, who learnt words either on dry land or in water, were better able to recall words if they were tested in the same environment as they had studied the words compared to the alternative environment5. The notion that the match between encoding and retrieval is important is also central to other key concepts in memory theory, such as the transfer-appropriate processing framework6, and the proceduralist approach, which assumes that encoding operations are re-enacted during remembering7. These principles predict that greater overlap of cues present at encoding and test, such as a high correspondence between viewing angle at encoding and test, lead to better memory performance.There are good reasons to predict that discrimination accuracy will be higher if witnesses can view the lineup faces from the same angle that they studied the perpetrator. One of the most influential principles of human memory—10. At a 30-degree study-test difference, the performance cost plateaus, and at 45 degrees, recognition performance is impaired significantly11. Neurophysiological studies also indicate pose-sensitivity in cortical regions12. In the context of police lineups, overlapping cues at learning and test, such as the quantity of facial information available at encoding versus test 13, clothing14, and disguises15 boost discrimination accuracy. Context reinstatement16 and alcohol state-dependent learning17 effects have also been reported in the eyewitness literature. Together, this research supports the encoding specificity principle, whereby overlapping cues at learning and test facilitate accurate memory retrieval.In accordance with these memory principles, a wealth of face recognition research shows that similarity across study-test viewing angle improves recognition accuracy18. Indeed, some research suggests that in more naturalistic contexts, the correspondence between study and test pose does not always enhance recognition accuracy, and faces at certain angles  are difficult to learn and recognize19. Null findings regarding the overlap of pose at learning and test have also been reported in the eyewitness literature. A study that varied whether a perpetrator was studied at eye level versus from overhead found that recognition accuracy was not increased by having matching information at the lineup test. However, this study was likely underpowered20. Therefore, it is important to test if people benefit from consistent viewpoint information at study and at test, and under conditions that are akin to real life, such as an eyewitness identification task.What is not yet clear, however, is whether the encoding specificity principle generalises to conditions in which people encode viewpoint information and use it during a lineup identification test. Face recognition paradigms employ numerous study-test trials. Each study trial presents an individual face, with pose typically varying across faces. In these studies, pose is therefore a key distinguishing feature, so participants may attend to and encode pose information more than they otherwise would in a more naturalistic contextactively seek out information at test that matches the study environment as an aide-mémoire. Most memory paradigms experimentally manipulate the degree of overlap between the cues present at encoding and at test, with some participants allocated to experience overlap and others not5. But would, for example, divers who studied underwater be more inclined to jump back into the pool at test to reinstate study context to aid their memory retrieval compared to those who studied on land? Here, we test if participants naturally seek out cues at test that correspond with information learned at study, using an eyewitness identification task.Moreover, research has not yet determined if, during memory retrieval, humans https://tinyurl.com/t4nc9gp). If participants reinstate pose at test—by naturally rotating the lineup faces into the same angle from which they saw the perpetrator commit the crime, then this suggests people encode viewpoint information, and seek (consciously or unconsciously) to make use of overlapping cues gleaned through pose reinstatement. Further, if accurate participants reinstate perpetrator pose to a greater degree than inaccurate participants, this suggests pose information is a valuable retrieval cue for eyewitnesses.To do so, we developed an interactive lineup procedure, wherein each lineup face can be rotated along the vertical axis. This enables the witness to dynamically view the lineup faces from − 90° to 90° and hold the faces in any pose desired  whether consistent viewpoint information at study and at test is associated with higher discrimination accuracy; and (2) whether people naturally reinstate at test the pose in which they had viewed a perpetrator if given the opportunity to do so with an interactive lineup.and the highest when they had the same pose information plus an additional unstudied pose. Specifically, a geometric representation of the face can be constructed from the frontal and profile views of the face21. Indeed, the first police system to catalogue faces for criminal identification was developed by Alphonse Bertillon, and it photographically described arrestees using the profile and frontal view. Seeing a face from more than one angle is thought to be useful for building a representation of the face’s three-dimensional structure, and knowing the three-dimensional structure of a face can provide additional cues that boost discrimination accuracy22. In Experiment 1, we tested whether seeing the lineup faces from the angle in which the perpetrator was studied improved discrimination (pose reinstatement hypothesis) compared to when such information was not available, and (b) whether having the same pose information plus additional unstudied information about the face at test boosted discrimination accuracy the most. We pre-registered our hypotheses and analysis plan before we collected data (https://osf.io/vs48c).In Experiment 1, we tested whether consistent viewpoint information at study and at test improved accuracy on a lineup identification task. Based on the encoding specificity principle and the existing face recognition literature, we predicted that discrimination accuracy would be higher when participants had available at test the same pose information that they encoded compared to when they had different pose information (pose-reinstatement hypothesis). We were also interested whether discrimination accuracy would be higher when participants had available at test the same pose information that they encoded as opposed to different pose information, All methods were carried out in accordance with relevant guidelines and regulations.We used a 2  × 3  × 2  between-subjects design.N = 3021) were recruited using Amazon Mechanical Turk; they were remunerated 0.40 cents to take part in the experiment, which took 5 min to complete. Participants who incorrectly answered the validation question or experienced a technical issue (n = 117) were excluded, leaving a total of 2,904 participants . Our data-collection stopping rule was to recruit 3,000 participants—250 in each of the between-subjects conditions. Using the mean difference and SDs observed in Mickes, Flowe, and Wixted, 201223 as a guide, a power analysis indicated that, with 250 subjects per between-subjects condition, power would exceed 80%. The research was reviewed according to the University of Birmingham Science, Technology, Engineering and Mathematics Ethical Review Committee. Informed consent was obtained from all subjects.Participants  of the perpetrator from the videosee Fig. . Target-N = 80) with the description of the perpetrator followed by a frontal target-present lineup or target-absent lineup. The mock-witnesses did not view a crime or a to-be-remembered face; they simply had to select the lineup member who best fit the modal description that we provided for them25. The perpetrator was identified 7% of the time in the target-present lineup, a rate that did not exceed chance  and the most frequently chosen lineup member was identified 20% of the time in the target-absent lineup, a rate that did not significantly exceed chance expectation. We also calculated E’26, a measure of effective size, which assesses the number of lineup members that are effective at drawing mock-witness choices27. Effective size was 6.50  in the target-present lineup and 6.76  in the target-absent lineup. These values are appreciably larger than the effective size of lineups reported in field research on UK police lineups  for photo lineups, and 4.46 (SE = 0.32) for video lineups)28. Together, the mock-witness test illustrated that our lineups were perceptually fair, based on the description of the perpetrator.To check that our lineup fillers were plausible alternatives to the suspect, we conducted a mock-witness test. First, we asked 10 independent observers to describe the appearance of the perpetrator while looking at the perpetrator’s photograph to create a modal description. We presented a different group of participants acting as mock-witnesses . Then participants watched either the front or right-profile mock-crime video. We told participants to pay attention because they would be asked questions about the video later. Next, participants watched a distractor cartoon for 1 min 11 s and attempted to solve anagrams for a further 2 min. We asked participants if they had experienced any technical problems when viewing the video. Following this, participants were told that they would view a lineup and their task was to try and recognize the perpetrator from the mock-crime video. In line with recommended police practice, participants were told that the perpetrator may or may not be present in the lineupNext, the lineup was displayed. The lineup was administered sequentially . We experimentally manipulated the angle from which the lineup members were shown see Fig. : In the Sections of these data were presented by Heather D. Flowe at the Society for Applied Research in Memory and Cognition , Cape Cod, Massachusetts, The United States.https://osf.io/jm2k9/). Recall that participants were randomly assigned to encode the perpetrator from the front (n = 1449) or the right-profile (n = 1455). After watching the mock crime video, participants were randomly assigned to a lineup condition, with 969 viewing the front lineup (480 viewed a target-present lineup and 489 viewed a target-absent lineup), 975 the right-profile lineup (487 viewed a target-present lineup and 488 viewed a target-absent lineup), and 960 the front + right-profile lineup (493 viewed a target-present lineup and 467 viewed a target-absent lineup). For analysis, we combined over perpetrator encoding pose and lineup member pose conditions to create same-pose, different-pose, and same + additional pose conditions, as per our OSF pre-registration. This allowed us to test the pose-reinstatement hypothesis, and whether having the same pose information plus additional unstudied information about the face boosted discrimination accuracy the most. The numbers of participants in each pose condition by experimental group are given in Table Our data are available . That estimated value was then divided by the number of target-absent lineups to estimate the false ID rate in each condition. The overall correct ID rates were 0.66, 0.49, and 0.65 for the same-pose, different-pose, and same + additional pose conditions, respectively. The corresponding overall false ID rates were 0.04, 0.05, and 0.04 for the same-pose, different-pose, and same + additional pose conditions, respectively. Thus, even without performing any additional analyses, it is clear that those in the same and same + additional pose conditions performed better than those in the different pose condition, as predicted by the pose-reinstatement hypothesis.Response frequencies for perpetrator, filler and reject  decisions at every level of confidence for the same-pose, different-pose, and same + additional pose conditions are displayed in Table 23. It is apparent that those in the same-pose and same + additional pose conditions discriminated perpetrators from innocent suspects better than those in the different-pose condition. Partial area under the curve (pAUC) values were computed using a target-absent filler ID cut-off  of 0.618 with the statistical package pROC30. We used a Bonferroni-corrected alpha level of 0.017. As predicted by the pose-reinstatement hypothesis, the pAUC for the same-pose condition (0.186) was significantly greater than the pAUC for the different-pose condition (0.117), D = 5.43, p < 0.001. The pAUC for the same + additional pose condition (0.194) was also greater than the pAUC for the different-pose condition (0.117), D = 6.29, p < 0.001. Although the same + additional pose condition yielded a slightly higher pAUC (0.194) than the same-pose condition (0.186), that difference was not statistically significant, D = 0.639, p = 0.523.We conducted ROC analysis to measure participants’ collective ability to discriminate between perpetrators and innocent suspects. Figure We conducted additional ROC analyses to study pose reinstatement effects in each perpetrator encoding pose condition (see Supplementary Appendix pAUC results reported here. Compared to when participants had different pose information at test (d′ = 1.67), discrimination accuracy was better when they had the same pose information that they encoded  = 35.37, p < 0.001) and when they had the same pose information plus additional unstudied information  = 39.51, p < 0.001). Discrimination accuracy was not boosted further when participants had available at test additional unstudied information about the face  = 0.10, p = 0.752). The same was true when the model was fit to each perpetrator encoding pose condition separately, and the effect appears larger in the frontal compared to the profile encoding condition . Relatedly, an interactive virtual reality eyewitness memory study with avatars reported that having multiple face viewpoints available at test increased accuracy, but only when the perpetrator was present in the lineup32. However, this study was likely underpowered, and did not vary encoding pose or measure discrimination accuracy. We developed an interactive lineup procedure that enabled participants to rotate the lineup faces into any pose desired. The procedure recorded the length of time participants spend viewing the faces at different angles. We predicted that participants would naturally reinstate the lineup faces, particularly the perpetrator’s face, into the same pose as they had encoded the perpetrator, and that greater pose reinstatement would be associated with better discrimination accuracy. We pre-registered our hypotheses and analysis plan before we collected data (https://osf.io/ezsxg).In Experiment 2, we extended Experiment 1 by examining whether participants would We used a 2  × 2  between-subjects design.N = 1727) were recruited from Amazon Mechanical Turk; they were remunerated 0.45 cents. Participants who incorrectly answered the attention check question (n = 40) and those who did not interact with any of the faces in the lineup (n = 257) were excluded, leaving a total of 1430 participants . None of the participants who took part in Experiment 1 took part in Experiment 2.Participants  and 705 viewed the left-profile crime video (355 were assigned a target-present lineup and 350 were assigned a target-absent lineup). Participants were randomly allocated into conditions, with the constraint that the number of participants in each condition was relatively equal. Our data-collection stopping rule was to recruit 1400 participants—350 in each of the between-subject conditions. Using the medium effect sizes determined in a pilot study, a power analysis indicated that, with 350 subjects per between-subjects condition, power would exceed 80% in all of our planned analyses.Eyewitness Interactive program. The lineup members were the same as those used in Experiment 1, but this time we used 6 lineup members, instead of 9, for use in our Eyewitness Interactive software. Target-present lineups contained the perpetrator and 5 fillers, target-absent lineups contained 6 fillers. To assess perceptual fairness in the 6-person interactive lineups, we conducted a mock-witness test and presented a new group of participants (N = 50) with the description of the perpetrator followed by the target-present lineup or target-absent lineup. The perpetrator was identified 12% of the time in the target-present lineup and the most frequently chosen lineup member was identified 25% of the time in the target-absent lineup; these rates did not significantly exceed chance expectation (17%), p > 0.05. Effective size was 5.63  in the target-present lineup and 5.05  in the target-absent lineup. This means that there were approximately 5 members who were viable alternatives from which the witness might choose. Together, the mock-witness test illustrated that our lineups were perceptually fair, based on the description of the perpetrator.We used the same mock crime as Experiment 1, but this time we used only the right-profile and left-profile crime videos. Unlike Experiment 1, participants could interact with the lineup members and view them from any angle desired. To this end, we took images of the lineup members and rendered them into rotatable objects using our We want to see how people interact with these faces. We are recording what you are doing with your mouse.” Participants had to view each lineup member for at least 5 s, after which time, they could press the “next” button to proceed to the next face or, if they had already seen all 6 faces, make a lineup decision. As such, the stopping rule was that participants had to see every lineup face before making a decision. Under each lineup member, we reminded participants: “Remember to click on and rotate the face. Please examine the face for as long as you need. You must wait 5 s before you can continue”.We used the same procedures as in Experiment 1 with three exceptions. First, participants either saw the left-profile or right-profile mock-crime video. Second, to reduce the overall length of the experiment, we removed the anagrams, so participants just watched the distractor cartoon for 1 min and 11 s during the filler task. Finally, at test, we used an interactive lineup. During the interactive lineup, each lineup member was initially shown in frontal pose and participants were instructed that they could use their mouse or touchpad to rotate the face so that they could view it from other angles. If participants did not interact, the face was shown facing forward the entire time. The program used to present the interactive lineup recorded whether, and for how long, participants examined five regions of the face . It is important to note that we were interested in how participants behaved naturally. As such, we did not constrain the length of time participants spent on each of the members to be equal, and we did not force participants to interact with the faces in any particular manner. We did, however, encourage participants to interact. Before the lineup, we told participants: “https://osf.io/vtmdb/). Response frequencies for perpetrator, filler, and reject decisions at every level of confidence for the right-profile and left-profile encoding conditions are displayed in Table Our data are available (pAUC (computed using a target-absent filler ID cut-off of 0.59) for the right-profile condition (0.228) was significantly greater than the pAUC for the left-profile condition (0.191), D = 2.35, p = 0.019. The results of a signal-detection model fit to the data partially agreed with the pAUC results reported here: d′ was estimated to be higher in the right-profile (2.14) than the left-profile (1.95) encoding condition, but that difference did not quite reach statistical significance, χ2 (1) = 3.55, p = 0.060. We had not expected to see any differences in accuracy between the left- and right- profile encoding conditions, but previous research has found that the right compared to the left side of a face is perceptually more salient to an observer33, which may explain why participants were more accurate when they encoded the perpetrator in right-profile pose. Given the unexpected difference in accuracy between the right-profile and left-profile, in our subsequent analyses, we ran additional tests to check that the results were consistent across both the left- and right- encoding conditions.Given the observed differences in the correct ID rates, we conducted ROC analysis to see whether discrimination accuracy was significantly different between left- and right-profile encoding conditions. Note that this analysis was not part of our pre-registered plan because we did not expect to see any differences between the left- and right-profile encoding conditions. Those assigned to the right-profile condition were slightly better at discriminating innocent from guilty suspects than those assigned to the left-profile condition. The We hypothesized that participants would turn the lineup faces to reinstate the same pose as they had viewed the perpetrator in the mock-crime video, and also hypothesised that this pose-restatement effect would be larger for the perpetrator’s face compared to filler faces in the target-present lineup. To measure pose reinstatement, we calculated for every participant and lineup face the proportion of time that the participant spent examining the same profile side of the lineup face as the perpetrator had been shown, as well as the proportion of time that participants spent examining the opposite profile of the lineup face relative to the profile view in which the perpetrator had been shown. The proportion of time spent on the same profile of the face was measured by determining the total amount of time a lineup face was rotated and paused within the same profile region divided by the total length of time that the lineup face was on screen. Proportion of time spent on the opposite profile of the face was similarly determined, summing the total length of time the lineup face was rotated and paused within the opposite profile region and dividing by the total length of time that the lineup face was on screen. To examine how the subject interacted with the target compared to the filler faces, we averaged across the filler faces the same side proportion data and the opposite side proportion data.M = 0.23, SEM = 0.005 versus M = 0.11, SEM = 0.003, respectively), a large sized significant main effect for pose reinstatement, F = 425.39, p < 0.001, ηp2 = 0.39. Participants also spent a larger proportion of time examining the perpetrator’s face compared to the filler faces in profile view , a moderately sized significant main effect for face type, F = 84.92, p < 0.001, ηp2 = 0.11. As we had hypothesized, there was also a pose reinstatement × face type interaction effect, F = 58.32, p < 0.0001, ηp2 = 0.08. Participants apportioned more time viewing the perpetrator’s face in the same profile as the perpetrator had been shown compared to the fillers’ faces , t(670) = 9.76, p < 0.001. The proportion of time spent viewing the profile of the faces that was opposite to that in which the perpetrator had been shown did not differ by face type , t(680) = − 0.256, p > 0.05.To examine pose reinstatement in target-present lineups, we conducted a 2  × 2  repeated measures ANOVA using the proportion of time data from the target-present condition. The top panel of Fig. M = 0.19, SEM = 0.004 versus M = 0.11, SEM = 0.003, respectively), a large sized significant main effect for pose reinstatement, F = 298.5, p < 0.001, ηp2 = 0.29.To examine pose reinstatement in target-absent lineups, we conducted a 2  repeated measures ANOVA using the proportion of time data from the target-absent condition. Descriptive data are shown in the bottom panel of Fig. https://osf.io/ezsxg). First, as per the preregistration, we did not include encoding condition as a variable in the ANOVAs. However, since we unexpectedly found higher discrimination accuracy in the right- compared to the left-profile condition in our preliminary examination of the data, we ran an additional test and checked whether encoding condition had an effect on the ANOVA results reported here. When encoding condition is included in the model, the pattern and statistical significance of the results we report here do not change. Second, as stated in our OSF preregistration, we had planned to include accuracy (correct versus incorrect ID decision) in the ANOVA. However, given that this treatment of accuracy would confound discrimination accuracy with response bias23, we instead examined the association between pose reinstatement and discrimination accuracy using ROC analysis. We present these analyses next.There are two things to note about the ANOVA results reported above in relation to our data analysis plan reported in the OSF preregistration . We created two pose-reinstatement groups: high and low pose reinstatement, using a median split. The overall correct and false ID rates for the high pose-reinstatement group were 0.73 and 0.10, respectively. Whereas the overall correct and false ID rates for the low pose-reinstatement group were 0.67 and 0.10, respectively.pAUC (0.217) than the low pose-reinstatement group (0.184), D = 2.148, p = 0.03. Note that a similar pattern of results was found across the encoding conditions. In the right-profile encoding condition, there was a non-significant trend for the pAUC to be greater in the high (0.233) compared to low (0.196) pose-reinstatement group, D = 1.78, p = 0.08. In the left-profile condition, there was also a non-significant trend for the pAUC to be greater in the high (0.199) compared to the low (0.176) pose-reinstatement group, D = 1.01, p = 0.31. Again, when we fit a signal-detection model to the data (Supplementary Appendix pAUC results reported here: d′ was estimated to be greater for the high pose-reinstatement group (2.14) than the low pose-reinstatement group (1.97), though that difference did not reach statistical significance, χ2 (1) = 3.04, p = 0.08.To see whether discrimination accuracy is significantly greater for those in the high pose-reinstatement group, we conducted ROC analysis; Fig. Analyses of the confidence-accuracy relationship for the low and high pose reinstatement groups are presented in Supplementary Appendix We investigated whether pose-reinstatement effects, which have been demonstrated only with standard face recognition paradigms, generalize to the eyewitness identification context. As predicted by the encoding specificity principle, in two experiments, we found that accuracy varied in relation to whether the participant had the same or different pose information in the lineup task as was encoded during the mock crime. Notably, our novel interactive lineup test, which allowed participants to rotate and view the lineup members in any angle, enabled us to test whether participant witnesses naturally seek to reinstate perpetrator pose at test, and if pose reinstatement was associated with discrimination accuracy. We found that participants reinstated perpetrator pose during the interactive lineup task and high pose reinstatement was associated with accuracy.10, our results show that people store viewpoint information in memory, even when face learning occurs under more naturalistic conditions. Remarkably, without instruction, participants spontaneously rotated the lineup faces to match the pose in which they had encoded the perpetrator. This suggests that people—consciously or unconsciously—value the information that can be gleaned from reinstating pose when making an identification decision from a lineup. More broadly, it evidences that humans actively seek out information in the testing environment that matches the study environment to help them to retrieve information from memory, a result that is in line with other eyewitness research varying the overlap between cues at learning and at test17.Consistent with the basic face recognition literature39. Seale-Carlisle et al.31 also compared photo and video lineups and found no significant difference (though photo lineups yielded a higher ROC). However, perpetrator encoding angle, and the overlap between the angle of the faces at encoding and test was not considered in any of these studies. Our data suggest that showing the lineup members in the same pose that the perpetrator was viewed, or conducting interactive lineups—that allow witnesses to actively seek the pose information they require—could significantly increase eyewitness discrimination accuracy compared to existing lineup procedures. A recent meta-analysis of the literature31 indicated that the weighted average pAUC for sequentially presented static frontal pose photographic lineups is 0.100% CI , which, descriptively speaking, is lower than the pAUCs (left encoding pAUC = 0.198 and right encoding pAUC = 0.221) we obtained for interactive lineups in the present study. Further, we found in two experiments, one conducted in lab and the other online, that interactive lineups boost discrimination accuracy over static frontal pose photographic lineups, increasing the correct identification of guilty suspects by 18%40.Our study provides evidence that identification procedures allowing participants to reinstate perpetrator pose could boost discrimination accuracy. Research comparing the efficacy of static frontal pose photo lineups and video lineup procedures has found mixed results42. Third, another key direction for further research is to use interactive lineups as a tool to study memory retrieval processes, such as whether people search for diagnostic versus non-diagnostic features43. The interactive procedure allows for exploring face viewing behaviour in online studies with large samples of participants, and therefore, is a useful adjunct to other methods being used to study decision processes, such as eye tracking44 and response time46. Fourth, like every lineup procedure, the interactive lineup comprises different components . One component or a combination of components may be responsible for improvements in eyewitness accuracy. We have demonstrated that interactive lineups can facilitate pose reinstatement and improve accuracy and additional research should determine which components of the procedure have the largest effect on accuracy. Finally, future work is needed to ascertain whether eyewitnesses are able to accurately report the pose in which they encoded the perpetrator, and whether doing so is necessary for obtaining pose reinstatement effects. In the case of the infamous serial killer Ted Bundy, for example, a lineup identification was called into question by the defense owing to differences between encoding and test pose47.Considering our main findings, and the limitations of this study, we suggest five key areas for further research. First, future research could systematically control the rotation of the lineup faces and assess the effect on accuracy, particularly using a wider variety of encoding poses and significantly longer retention intervals. The benefit of pose reinstatement may vary depending on the difficulty of encoding. Discrimination accuracy was higher when the perpetrator was studied in frontal as opposed to profile view. When participants encoded the perpetrator from front-on, discrimination accuracy was higher when the frontal pose was available at test compared to when it was not available. While there was also a pose reinstatement effect when the perpetrator was encoded in profile view, the size of the effect was smaller. Second, it would be interesting to examine the role of movement as a recognition cue in the context of lineups. According to the representation enhancement hypothesis, facial motion  aids perception 3D structure50 and answers the National Academy of Sciences’3 call for the use of psychological theory and innovative technology to improve the accuracy of eyewitness identification.In sum, our findings provide evidence that allowing witnesses to reinstate pose at test increases discrimination accuracy. Our results deepen our theoretical understanding of how faces are processed during learning and remembering, particularly in more naturalistic contexts. Our work follows the example of others in innovating lineup proceduresSupplementary Information.


In this study, we implemented a model with which a robot expressed such complex emotions as heartwarming  or horror (fear and surprise) by its touches and experimentally investigated the effectiveness of the modeled touch behaviors. Robots that can express emotions through touching behaviors increase their interaction capabilities with humans. Although past studies achieved ways to express emotions through a robot’s touch, such studies focused on expressing such basic emotions as happiness and sadness and downplayed these complex emotions. Such studies only proposed a model that expresses these emotions by touch behaviors without evaluations. Therefore, we conducted the experiment to evaluate the model with participants. In the experiment, they evaluated the perceived emotions and empathies from a robot’s touch while they watched a video stimulus with the robot. Our results showed that the touch timing before the climax received higher evaluations than touch timing after for both the scary and heartwarming videos. For social robots that interact with people, emotional expression is becoming necessary to be accepted by people. For this purpose, robotics researchers developed various kinds of robots that can express emotions using facial expressions , full-boHowever, the above studies mainly focused on expressing relatively simple emotions, such as happiness and sadness, which are defined as basic emotions . Touch cBased on our previous study , this neThis study used similar materials and methods from our past study  that modWe focused on heartwarming and horror emotions as target emotions that our past study also targeted  the timing at which the robot should start its grip as a reaction (or anticipation) to the climax, ttouch; 3) the grip’s duration ∆t; and 4) ∆tstart , which is the difference between the touch and climax to extract the timing features (via a grip behavior (The implementation process requires four kinds of parameters: 1) the most appropriate climax timing of that video, tfeatures . The reabehavior .start and ∆t compared to other functions . Therefore, we used the NIG function in this study, and it showed the best fitting results for implementation. Our past study concluded that using a normal-inversed Gaussian (NIG) function is a better approach to model tstart ranges of the heartwarming and horror NIG models. Directly sampling from these ranges might fail to reproduce typical touch timings based on gathered data, i.e., reacting before the horror climax or after the heartwarming climax. We mitigated this problem by limiting the sampling range within one standard deviation . However, using a sampling method might fail to reproduce typical touch parameters. The majority of touches started before the climax timing and ended after it. But due to the likelihood of exceedingly small touch durations, for example, a sampled minus −3 s ∆tstart and a sampled 1-s ∆t mean the touch will end 2 s before the climax. In fact, even though we limited the sampling ranges, ∆t’s sampling ranges are still relatively wide to reliably reproduce the typical touch parameters. To reproduce them, we simply used the mean values instead of the sampling approach, i.e., ∆t is 8.525 s for the heartwarming videos and 12.857 s for the horror videos. Based on this calculation, the system calculates the end timing of robot’s grip (ttouch + ∆t).For selecting touch duration ∆t, we re-analyzed the touch data within one standard deviation sampling range due to the above implication policies. First, 11 of 11 touches in the heartwarming videos and 49 of 59 touches in the horror videos started before the climax timing and ended after it, i.e., a similar touch characteristic from the original data. We again conducted a binominal test and found significant differences between them  whose ages ranged from 21 to 48 and averaged 34. They had diverse backgrounds, and none joined our previous data collection .category factor: heartwarming video and horror video and model factor: heartwarming NIG and horror NIG). The category factor is related to video stimuli, and the model factor is related to the robot’s behaviors. For example, in the combination of heartwarming video (the category factor) and heartwarming NIG (the model factor), the participant will watch heartwarming videos, and the robot will grip the participant based on the heartwarming NIG function.Our experiment had a within-participant design. Each participant experienced the four conditions under two factors described below , whose ages ranged from 24 to 35 and averaged 26, provided their perceived climax timing of each video. We used the average of the largest clusters of the histograms of the climax timing as tclimax for each video. We edited the videos to only have one typical climax timing  and at least another 30 s after the climax to the end of the video to leave enough time to finish the robot’s touch.Since the robot needs to know the tTo compare and investigate the perceived naturalness of ERICA’s touch behaviors, the participants compared two aspects in the first questionnaire: Q1) naturalness of touch  and Q2) naturalness of touch timing . Participants answered this questionnaire for each video.We also asked the participants about their perceived empathy with ERICA from two aspects in the second questionnaire: Q3) perceived empathy to ERICA (degree of perceived empathy to ERICA) and Q4) perceived empathy from ERICA (degree of perceived empathy of ERICA to you). Participants answered this questionnaire after each condition . We used a response format on a seven-point scale for these questionnaires, i.e., describing the options ranging from most negative to most positive.In the second questionnaire as a manipulation check, we asked the participants about their perceived emotions from the robot’s touch. The only emotional signal from the robot is her grip behavior; she said nothing throughout the entire experiment and maintained a neutral facial expression. Although we expected the perceived emotions to reflect the category factor, confirming them is important. We asked the participants to select the top two perceived emotions (Q5/Q6) from Ekman’s basic six emotions . The parBefore the experiment, the participants were given a brief description of its purpose and procedure. Our institution’s ethics committee approved this research for studies involving human participants (20-501-4). Written, informed consent was obtained from them.First, we explained that they would be watching a series of heartwarming/horror videos with ERICA, who would continue to touch their hand during the process. Sometimes she would grip it to convey emotion. The participants sat on ERICA’s left. To reproduce identical touch behaviors for all the participants, they put their right hands on specific table markers to guarantee that they all experienced identical interactions during the identical touch behaviors, and we asked the participants to use the mouse with their left hand to start the video stimuli. To avoid discomfort feeling due to constraining their hand position, we adjusted the height of the chair.touch and ∆t based on the tclimax of each video by using the NIG function. The used parameters are different due to the condition; the robot uses the parameters for the heartwarming model under the heartwarming NIG condition or the horror model under the horror NIG condition. Because we used a probabilistic distribution approach, the grip timing and duration are different between the participants even though they watched the same video. When a video started, ERICA put her hand on a participant’s hand and gripped at a selected moment that lasted a certain duration using the mechanism described in After the experiment started, the participants used a user interface to play the videos. Each video played independently. Before starting each video, the robot calculates tWe adopted a counterbalanced design for each factor. The order of the category factor is randomized, and all the horror or heartwarming videos were played randomly, during which ERICA drew samples from either the horror or the heartwarming NIG. Then the videos were played again as ERICA drew samples from the second NIG. These steps were repeated for the remaining videos.heartwarming and horror categories are happy/sad and fear/surprise, regardless of the NIG functions. For the former category, similar to a past study that investigated expressions of deeply heartwarming emotion in Japan  = 16.736, p < 0.001, partial η2 = 0.527]. We did not identify a significant main effect in the category factor  or in the interaction effect .category and model. The sphericity of the analysis was not violated in this setting. We identified a significant main effect in the model factor  = 47.481, p < 0.001, partial η2 = 0.760). We did not identify a significant main effect in the category factor  or in the interaction effect .These results show that the participants evaluated the touches higher with the horror NIG regardless of the video categories. Thus, category and model. The sphericity of the analysis was not violated in this setting. We identified a significant main effect in the category factor . We did not identify a significant main effect in the model factor  or in the interaction effect .category and model. The sphericity of the analysis was not violated in this setting. We identified a significant main effect in the category factor  or in the interaction effect .These results show that participants felt empathy with the robot when they watched horror videos, regardless of the NIG models. Thus, We applied two video stimuli in each video category and used them in the data collection experiment in our verification experiment. We did not think combining the old and new video stimuli were problematic because the participants who trained the models in the first experiment and evaluated them in the second experiment differed. Evaluating the models with only new video stimuli would provide additional evidence of effectiveness.category and model. The sphericity of the analysis was not violated in this setting. We identified significant main effects in the model factor  and in the category factor . We did not identify a significant main effect in the interaction effect .category and model. The sphericity of the analysis was not violated in this setting. We identified a significant main effect in the model factor . We did not identify a significant main effect in the category factor  or in the interaction effect . These results show the models are effective for the video stimuli that were not used in the data collection. We note that the statistical analysis for only the videos in the data collection showed similar trends.Unlike our hypotheses, the experiment results showed a better impression invoked by the horror NIG model where the robot and the participants watched both heartwarming and horror videos together. This result provides design implications for a robot’s touch behavior.First, as a touch behavior implementation for a social robot, touch timing before a climax provides better impressions than touch timing after it, at least in a touch-interaction scenario where videos were the only external emotional stimuli that people intended to watch with the robot. One technical consideration is how to estimate the climax timing. Several past studies proposed methods to identify highlighted movie scenes by information processing . Such anSecond, our result suggests that directly using the parameters observed from human behaviors might overlook better parameters for the behavior designs of robots in emotional interaction contexts. From our study, even with an abundant number of participants for data collection, the observed touch models, i.e., heartwarming NIG, failed to reflect the people’s actual expectations in the evaluations.Why did the observed heartwarming NIG model show disadvantages? Perhaps the setting was different between the data collection and the experiment. During the data collection, our participants watched the videos repeatedly to identify the robot’s touch-timing characteristics. They already knew the climax timing of the video. On the other hand, they had no prior knowledge about the video stimuli or their climax timing in the experiment. In such situations, perhaps the touch timing before the possible climax was interpreted more favorably because such touch timing might demonstrate a sense of empathy to people who were touched in this way. Another possibility is that the climax timing was different between the system and participants because the variance of heartwarming videos is relatively larger than the horror videos. For example, if the climax timing of the participants were earlier than the system’s timing, perceived naturalness becomes lower.In addition, even though the estimated emotions by participants matched the video categories, we identified no significant effects for perceived empathy. The expressions of emotions only by touching might be implicit. To perceive empathy, feeling, and sharing another’s emotions are important. Therefore, such implicit expressions might be insufficient to increase the perceived empathy. As we previously discussed , using dheartwarming and horror video stimuli, regardless of the NIG functions, which might indicate that the types of visual stimuli have relatively stronger effects than the touch stimuli toward perceived empathy and emotions. Whether this phenomenon is common regardless of the co-viewer types  remains unknown. Investigating the relationships among perceived empathy, co-viewer’s characteristics, and the categories of co-viewing content are interesting future work.Another point of view is the category of the contents for the shared experiences. Our results did not show any significant effect of our touch behavior design toward perceived empathy, although the participants perceived higher empathy when they watched the horror video stimuli than the heartwarming video stimuli. Moreover, participants felt happy/sad and fear/surprise for the Since we only used a specific android robot with a female appearance, we must test different types of robots before generalizing our experimental results. In addition, our android’s hands resemble human hands and can perform gripping behaviors. For robots without such hand structure, other touch characteristics must be considered. The robot’s appearance and the participant’s ages influence the perceived emotions . MoreoveWe only used heartwarming and horror videos as emotional stimuli because they are typically used in human-robot interaction studies and human science literature. Investigating appropriate touch timing for different emotions is needed to convey such emotions by touching.Affective touch is an essential part of expressing emotions for social robots. However, past studies investigated the effectiveness of using touch behaviors to express robot emotions and generally focused on expressing relatively simple emotions. Although our past study  focused To evaluate the developed models, we experimented with 16 participants to investigate the effectiveness of both models using heartwarming/horror videos as emotional stimuli. The horror NIG model has advantages compared to the heartwarming NIG model, regardless of the video types, i.e., people preferred a touch timing before climax for both videos. This knowledge will contribute to the emotional touch-interaction design of social robots.


Hippocampus erectus, with unformed, newly formed, and pregnant brood pouches identified a total of 141 and 2,533 differentially expressed genes together with 73 and 121 significantly differential metabolites related to brood pouch formation and pregnancy, respectively. Specifically, integrative omics analysis revealed that retinoic acid (RA) synthesis and signaling pathway played essential roles in the formation of the brood pouch and pregnancy. RA might function upstream of testosterone and progesterone, thereby directly influencing brood pouch formation by regulating the expression of fshr and cyp7a1. Our results also revealed that RA regulates antioxidant defenses, particularly during male pregnancy. Alternatively, pregnancy caused a consistent decrease in RA, canthaxanthin, astaxanthin, and glutathione synthetase, and an increase in susceptibility to oxidative stress, which may balance brood pouch development and reproduction in seahorses and pave the way to successful gestation.Seahorses epitomize the exuberance of evolution. They have the unique characteristic of male pregnancy, which includes the carrying of many embryos in a brood pouch that incubates and nourishes the embryos, similar to the mammalian placenta. However, the regulatory networks underlying brood pouch formation and pregnancy remain largely unknown. In this study, comparative transcriptomic and metabolomic profiling on the lined seahorse  •Male seahorses epitomize the unique characteristic of male pregnancy•Retinoic acid (RA) plays key regulatory roles in brood pouch formation and pregnancy•RA could influence the brood pouch formation by regulating steroid hormone metabolism•RA may contribute to the successful gestation by regulating antioxidant defense  Two pacyp7a1]) and PG  brood pouches  were differentially expressed during pregnancy in both H. erectus and H. abdominalis  also significantly decreased in pregnant seahorses  (rarres3), and astaxanthin showed a positive correlation with UDP glucuronosyltransferase 2 family, polypeptide A2 (ugt2a2) and beta,beta-carotene 15,15′-dioxygenase (bco1) during pregnancy  . Meanwhiregnancy C. Rarresignaling  and S11.In this study, we quantified transcripts and metabolites over different seahorse brood pouch developmental stages and suggested multiple roles of RA in pouch formation and pregnancy by regulating steroid hormone metabolism and antioxidant defense. In seahorses, interruption of PRL synthesis leads to disruption of brooding tissues and spontaneous abortions during pregnancy as PRL production is essential for PR and TE secretion.,,,In addition to the roles of steroid hormones, our results may indicate that RA regulates 54 downstream target genes with diverse functions, indicating its potential roles in seahorse brood pouch development . In factaldh1a2), the enzyme that metabolizes the vitamin A-intermediate retinaldehyde into RA, results in embryonic pituitary dysmorphology and alters hormone expression.,Contradictory results have been reported regarding the relationship between the RA signaling pathway and steroid hormone metabolism. On the one hand, conditional deletion of aldehyde dehydrogenase 1 family member A2  in August 2017. These seahorses were categorized into three developmental stages according to brood pouch morphology: (1) unformed (UF) stage comprising 50 seahorses (5.0–5.7 cm in length and 0.39–0.54 g in weight) with unformed brood pouches; (2) newly formed (NF) stage, which included 25 male seahorses (6.2–7.4 cm in length and 0.78–1.43 g in weight) with newly formed brood pouches; and (3) pregnant (PG) stage, including 25 male seahorses (9.0–9.3 cm in length and 2.42–3.55 g in weight) during pregnancy.,The seahorse dissection and sampling processes were performed on ice. After dissection, UF-stage seahorse gonads were observed under a microscope, and only male seahorses with testes were retained. Embryos were gently removed from pregnant seahorses before sampling. A total of 18 individual seahorses in each of the three stages were used. Muscles from six seahorses from each stage were used to detect RA, PRL, PR, and TE; another 12 seahorses in each stage were used for transcriptome and metabolome analyses. From each animal, half of the pituitary gland, testis, and brood pouch tissue were dissected, pooled, and quickly frozen in liquid nitrogen until transcriptome analysis. For the UF stage, skin tissue was collected from the primordial brood pouch area and designated as the pouch sample. After transcriptome sampling, all remaining tissues from each animal were then frozen separately in liquid nitrogen for metabolome analysis. Finally, 12 samples from each stage were used for metabolome analysis and 3 out of the 12 samples were randomly selected and used for transcriptome analysishttp://www.r-project.org/) for sample relationship analysis. DEGs were detected with the edgeR package using the following criteria: >2-fold change >2 and false discovery rate <0.05.,https://david.ncifcrf.gov/) and KOBAS software,RNA (three replicates per stage) was extracted using TRIzol  and RNA quality was assessed using an Agilent 2100 Bioanalyzer . Each replicate was used to generate an independent library. The RNA sequencing paired-end (PE) libraries were prepared using a NEBNext Ultra RNA Library Prep Kit for Illumina , following the manufacturer's protocols. Each library was sequenced on an Illumina HiSeq platform  with 150 bp PE reads. A total of approximately 489 million clean PE reads were generated. After reads filtering and removal of rRNA-mapped reads,H. erectus. To better illustrate the role of RA in Hippocampus, we also searched RA-related genes from among the DEGs identified in the pregnancy process of the pot-bellied seahorse Hippocampus abdominalis.We first recorded RA-related genes identified in previous studies, including genes participating in the RA synthesis and signaling pathway,http://www.genome.jp/kegg/) and MetaboAnalyst  were utilized to search for metabolite pathways. Pathways with a calculated p value < 0.05 were considered significantly enriched.All remaining tissues from the 36 seahorses (12 replicates per stage) were freeze-dried separately  and made into powder using a tissue crushing apparatus . After mixing evenly, approximately 20 mg of tissue per sample was collected for UHPLC-QE Orbitrap/MS analysis according to the standard protocol . The resulting data matrix, including the peak number, sample name, and normalized peak area was imported to the SIMCA 14.1 software package  for PCA. Metabolites with variable importance for the projection values > 1 and p value < 0.05 were identified as SDMs. Commercial databases, including KEGG  we detected levels of PRL, PR, and TE due to their reported roles in seahorse brood pouch development.,For each of the two processes (pouch formation and pregnancy), two separate KEGG analyses were conducted for identified DEGs and SDMs. We then compared the enriched KEGG pathways of the DEGs and SDMs identified for the same process to identify the co-enriched pathways of transcriptome and metabolome analysis. Pearson correlation coefficients between DEGs and SDMs identified for comparison of the same pouch process were further calculated. DEGs and SDMs with a correlation coefficient >0.9 and p value < 0.01 were imported to Cytoscape (v.3.3.0),


Significance: Immigrant day laborers suffer from disproportionate occupational health risks from hazardous reconstruction jobs after natural disasters.Methods: We conducted a randomized controlled trial of a short-video educational intervention to improve safety knowledge and intent to engage in safety preventive behaviors among 98 Hispanic day laborers (49 randomized to video and 49 control). The short video featured a male promotor and a female promotora who narrated 3 stories of day laborers who were injured while doing construction work in post-Katrina New Orleans. The main outcome measures were changes in scores for day laborer-reported safety knowledge and safety behaviors derived from interviewer-delivered baseline and post-intervention surveys.Results: Video participants reported improvement in overall average safety knowledge score , as compared to the control group (mean score of 8.6 or 72%) who were not offered the video (p < 0.00001). The intervention was highly successful in workers stating that they learned and were willing to change their safety preventive behaviors to reduce their occupational risk. The average safety behavior score was higher among those watching the video  as compared to control (14.5 or 65.9%) (p = 0.0024).Conclusion: A short video intervention can improve knowledge and intent to engage in preventive behaviors among Hispanic workers for which there is a dearth of construction safety preventive research. The United States (US) National Institute of Occupational Safety and Health (NIOSH) has designated immigrant Hispanic construction workers as a high-risk and high-need population. After agriculture, the construction industry has the second largest proportion of Hispanic workers with a higher rate of fatal , 2 and nUS immigrant Hispanic day laborers are often targeted by contractors who do not comply with the US Occupational Safety and Health Administration (OSHA)'s occupational injury prevention policies, picking them up from street corners for dangerous jobs with no written guarantee of pay . AlthougImmigrant day laborers conduct a disproportionate amount of reconstruction involving demolition, cleanup of debris, and other potentially hazardous jobs after natural disasters. For example, after Hurricane Katrina devastated much of the New Orleans, Louisiana, a large numbers of predominantly young, uneducated and undocumented Latino migrants arrived in the city to help –13. The promotores or female promotoras) knowledgeable about the community have been effective at translating evidence-based preventive health care and interventions for underserved populations -led short-video format, instead of an in-person promotor(a) intervention, because formative work showed that a video format was more feasible, and could allow for the intervention to be replicated in other settings and to be disseminated to a larger number of lower literacy populations.Other work highlights the potential benefit of a combined peer-video approach, reporting that  success , 27. For success  and othe success  supportepromotor(a)-based short-video intervention to reduce occupational health risks faced by Hispanic workers in the US. Specifically, the research aimed to find out whether a brief educational video featuring a male promotor and female promotora can increase safety knowledge and intended use of safety preventive behaviors regarding occupational risks among Hispanic day laborers.The goal of this study was to develop and pilot a promotor(a) intervention for the Hispanic worker population to improve safety knowledge and use of safety preventive behaviors regarding construction occupational risks. We used a randomized and controlled approach to provide preliminary data on the efficacy of the video intervention. Interviewer-delivered baseline and immediately post-intervention surveys were conducted to estimate short-term changes in safety knowledge and intended safety behaviors.We used community-based participatory research (CBPR) methods to develop and pilot a brief video promotor(a). The recruitment criteria were being a day laborer who was currently working in that capacity, had direct knowledge of the community, was fluent in Spanish, and very interested in working with fellow day laborers and the research team. Once recruited, the investigators trained the day laborers about the project following a standardized protocol.The content of the intervention was informed by a formative assessment process that documented the occupational exposures and experiences of day laborers, as well as their perceptions on existing educational materials available in Spanish through OSHA's website . The vidpromotor(a) demonstrated the appropriate equipment, a potentially risky situation, and modeled safety behavior. The video closed with a summary of three actions day laborers can take to avoid risky situations, and resources to report unsafe working conditions. The editing process involved final selection of the video clips and messages to balance camera time of both the male promotor and the female promotora, visual and cultural appeal of the images, and content to cover the key safety occupational knowledge and preventive actions. Final cuts kept the video under 12 min.The resulting intervention was a short educational video that highlighted best practices regarding occupational hazards and preventive behaviors identified as most relevant during the formative assessment stage. The video included three vignettes about roofing, ladder falls, as well as demolition and clean up, correspondingly. In each vignette, the The target population was Spanish-speaking day laborers in the US who work in the construction industry, for whom there is a dearth of appropriately language- and culturally appropriate occupational information. The community partner  led the recruitment process from their main clinic site, and their mobile preventive health clinic that meets migrant workers at major job search areas. Approached day laborers received a brief description of the study and were eligible if (i) 18 or older, (ii) preferred Spanish, (iii) had worked as a day laborer in the past 12 months, and (iv) planned to work as a day laborer in the next 3 months.Eligible individuals who were interested in participating completed written informed consent in Spanish before proceeding to answer the baseline survey. Once the baseline survey was completed, the data collector opened the sealed envelope that determined if the subject would be assigned to the video or control group. Participants randomized for the treatment group (video) watched the video in a separate location with no distractions. Once it was completed, participants responded to the follow up survey. Participants randomized to the control group took a 15–30 refreshment minute break before answering the follow up survey and then given the option to observe the video. The Human Subjects Protection Committee at the RAND Corporation approved this study. A Certificate of Confidentiality to protect information about the subject's identity and immigration status was granted by the US Department of Health and Human Services.We implemented a blocked randomization strategy where blocks were recruitment sites . A random sequence of study condition assignments was drawn before the beginning of the recruitment in each block. The sequences ensured that the sample sizes in each condition would be approximately balanced. Recruiters were blind to the randomization sequences.n = 50 per arm) can yield a 95% confidence interval with a half-length of 0.28 times standard deviation, or equivalently, have a power of 80% to detect a standard effect size of 0.57 times standard deviation with a two-sided p-value < 0.05.A total of 100 participants were approached and recruited for the study's two arms. Two participants left the study before completing the baseline survey. Our final sample, therefore, included 98 individuals, 49 randomized to the treatment group (video) and 49 randomized to the control group. All participants remained in the study for the post-intervention survey. As a pilot study the planned sample size was not meant to detect a small treatment effect but to provide a crude estimate of the possible effect size. The planned sample size , literacy level , type ann = 8 individuals to assess understandability, literacy appropriateness, and time required. The design and modifications to the survey items or instructions made as a result of pilot testing were conducted in Spanish and then back-translated into English following a language and cultural equivalence consensus approach.The surveys' language and cultural appropriateness were evaluated by a committee of bilingual and bicultural Spanish native speakers. The survey(s) were piloted in t-test of difference in proportions of independent groups. The evaluation of treatment effectiveness used the same statistical technique but comparing pre and post-treatment differences in mean scores between the groups.The success of the randomization was assessed comparing treatment and control groups at baseline for demographic characteristics, type of jobs, knowledge and safety behaviors using a Regarding occupational characteristics, participants performed, on average, three different types of jobs at the construction site with painting (61%), roofing (34%), demolition (34%), and framing (29%), among the most prevalent. Among all participants, the 3 more common job-related reported symptoms were back pain, skin rash or itchiness, and ear, nose or throat irritation. The most commonly reported respiratory hazards listed were dust from cement, concrete, tile, etc. (76.5%), mold (39%) and lead (37.3%). In terms of risky occupational activities, participants reported working on surfaces 6 feet or more above the ground (81.6%), cutting wood or other materials (78.6%), and half reported working on their knees for long periods of time or in working without protection in places where something could fall on their head.About half of participants reported having received training about how to use a mask or respirator, use a harness, safety googles, and portable ladders. Two thirds said they had not received training about hazardous substances or chemicals, what to do about inappropriate ventilation for a job, and to protect themselves from asbestos or mold. Among those reporting training, about one third said they received training from co-workers, family or friends, health professionals, or other community organizations, and not employers, although employers are required by law to do so.At baseline the treatment and control groups were comparable in terms of the Summary Knowledge Score (max = 12) as well as the item-specific knowledge items shown in promotor(a) intervention was associated with statistically significant improvement in occupational preventive knowledge both overall and by specific content areas (p < 0.01), and (iv) effectiveness of different types of protective equipment .The video nt areas . The trep < 0.05): (i) “Self-advocacy” behaviors , and (ii) “Other Protective Actions” .The video intervention was highly successful in workers stating that they learned and were willing to change their behaviors to reduce their occupational risk. The average behavior score was statistically significantly higher among those watching the video (17.2 out of a max of 22) compared to control (14.5 points) . Resultspromotor and a female promotora was highly successful in improving reports of safety knowledge gained and workers stating that they would change safety behaviors to reduce their occupational risks. The promotor(a) played the role of day laborers as they narrated 3 stories of workers who got injured while doing day construction work. Once they saw the video participants reported improvement in overall average safety knowledge score as compared to the control group who were not offered the video. The video intervention was highly successful in workers stating that they learned and were willing to change their behaviors to reduce their occupational risk, with the average safety behavior score being statistically significantly higher among those watching the video as compared to control.We piloted a short-video educational intervention to improve construction-related risk knowledge and intent to engage in preventive safety behaviors among Spanish-speaking day laborers who experience occupational-related disparities. The video presentation featuring a male promotores(as) in both the development of the script and as actors in the video was paramount in the efficacy of the video with the intended audience. Likewise, working with a Hispanic videographer promoted the use of culturally-congruent messaging in the execution of the video scenes. Although it took time to find a Hispanic videographer and promotor(a) who had the necessary technical skills, the success of the product depended on them being part of the research team.Our findings are consistent with previous work that supports the benefits of a participatory approach in designing educational videos for both occupational , 31, 32 promotor(a) in preventive medicine interventions to reduce occupational exposures (promotores(as) to reach workers in high-risk jobs eases access and acceptance, particularly when workers are not protected by standard work arrangements (such as unions and benefits), or move worksites regularly to maintain employability (promotores(as) as cultural and community gatekeepers and mediators greatly enhanced recruitment for and implementation of our pilot study.We also replicated the beneficial role of peer-support approaches in difficult-to-reach populations , 34, andxposures , 35. In promotores(as) through our community partners is well-established in the literature  in the video role modeled how day laborers can stand up to their employers when protective equipment is not provided. Although empowerment-like approaches have been used in longer in-person training (more than 4 h)  , 25, to Although the randomized and controlled design for this pilot strengthens our findings, there are several limitations that are important to consider in the interpretation of our results. The sample size was slightly lower than planned. Although in the end we had enough power to detect moderate effect sizes, the small sample size limited the number of outcomes we could evaluate. It was also not feasible to assess retention of gained knowledge beyond the immediate intervention period, nor associated changes in actual self-protective behaviors, instead of intended behaviors. Finally, although the results of this pilot study provide a good case study for an effective prevention intervention in a group of post-Katrina day laborers, the findings may not be generalizable to construction worker populations whose work is non-transient, though it provides relevant insights for day laborers in other industries. Acknowledging these limitations, we speculate, however, that implementation of the video intervention in a community setting could contribute to favorable end outcomes—increased actual safety preventive actions and associated reductions in work-related exposures, morbidity, and mortality—among other Hispanic day laborers.(promotor) and female (promotora) can increase safety knowledge and intended use of safety preventive behaviors regarding occupational risks among Hispanic day laborers. In doing so, it contributed new knowledge about the effectiveness of promotor(a) interventions, in general, and video interventions, specifically, to present culturally, linguistically, and educationally-appropriate methods of communication to inform difficult to reach and vulnerable populations. Lessons learned about the effectiveness of the pilot intervention in post-Katrina New Orleans can inform other interventions to reduce occupational risk in Hispanic and other vulnerable workers responding to natural disasters in other locations.This study showed that a brief educational video featuring a male The results of this pilot study also increased our understanding of working conditions experienced by US Hispanic day laborers after a natural disaster, for which there is a dearth of construction safety preventive research. From a research perspective, the next step would be scaling up the intervention and conducting a larger-scale effectiveness trial to replicate the findings and follow up workers to assess, not only changes in knowledge and behavior intentions, but also the long-term impact on work safety behavior.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Human Subjects Protection Committee at the RAND Corporation . The patients/participants provided their written informed consent to participate in this study.ML was the PI of the project and oversaw the design, implementation, analysis and write up of results presented here. CD co-developed the survey, analyzed and drafter results. JC recruited, interviewed and assisted in data analysis. SG co-developed the intervention, script for the video, contributed to the review of literature and survey design. MT, then director of Common Ground Health Clinic, coordinated the entire field work for data collection and intervention implementation. She was instrumental in the design of the intervention protocol and survey. BH developed the sampling strategy and co-developed the analytical strategy for the results presented here. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


We found that contact via VR reduced stigmatization only for participants who liked the person encountered. Our data suggest that it is crucial how participants evaluate the person that they encounter and that stronger perception of spatial presence during reception plays an important role, too. Therefore, we discussvarious boundary conditions that need to be considered in VR interventions and future research on destigmatization towards mental disorders, especially schizophrenia.People with mental disorders such as schizophrenia do not only suffer from the symptoms of their disorders but also from the stigma attached to it. Although direct intergroup contact is an effective tool to reduce stigmatization, it is rare in real life and costly to be established in interventions, and the success of traditional media campaigns is debatable. We propose Virtual Reality (VR) as a low-threshold alternative for establishing contact since it involves less barriers for affected and unaffected persons. In a 2 + 1 experiment ( In 2017, approximately 792 million people suffered from mental disorders worldwide ,4. The cOne approach to reducing stigmatization is to establish meaningful encounters between those who are affected by a mental disorder and those who are not . AlthougWe set out to test the potential of a digital technology that has not yet been in focus regarding stigmatization towards people with mental disorders: Virtual Reality (VR). The high sensual richness and involvement make VR a promising tool for intergroup contact ,14. In tAccording to Goffman, a stigma is a deeply discrediting attribute attached to a person or group . IndividThe stigma around mental disorders such as schizophrenia has real consequences for affected persons. The unaffected majority feels more anxious, less empathic, more socially distant towards affected persons, and is less supportive of policies that benefit people with mental disorders ,28. As aFor a long time, scholars have studied ways to reduce stigmatization towards people with mental disorders . Among oIn response to the lack of direct contact, researchers investigated indirect forms of contact, among others via media . ContactOne technology that has received little attention as a means for intergroup contact and destigmatization, is VR. VR allows recipients to freely adjust their view in a 360° video or a computer-animated space using a headset. Moreover, it enables rendering the perceived scene in 3D as both eyes are provided separate screens. As such, VR allows for high levels of perceived realism and immersion during media reception ,41.In the context of mental disorders, VR has been primarily studied in the context of cognitive behavioral therapy for inducing attitudinal and behavioral change in patients with mental disorders, for example, by exposing them to virtual situations that elicited their fears, such as public speaking or spiders . With reEmpirical studies that assess the effects of contact with an out-group member in VR are scarce —and withTo what extent can contact with a person with schizophrenia through VR reduce stigma associated with the mental disorder in comparison to no contact at all and a regular video?We employed a 2 + 1 experimental design with two experimental groups that watched either a VR video or a regular video and a control group.Insta360 Pro). As we expected our participants to be fairly young, we chose a young actor to increase the likelihood that recipients relate and identify with him due to their age. In line with this, we chose a male actor since males are usually diagnosed with schizophrenia at a younger age compared to females [We recorded a video of an actor portraying a young man with schizophrenia using a 360°-3D camera with multiple lenses  via advertisements at a German public university in June 2019. The mean age was M = 24 years (SD = 6.6 years), 58% of participants were female and 63% had a high-school diploma. These demographics suggest that our pool of participants consisted of majority, but not solely, students.Assuming a small effect size, η = 0.15  and alloAfter arriving at the laboratory, participants were seated in front of a laptop and randomly assigned to one of the three groups. They were informed about the study procedure and their right to stop participation anytime. All participants were informed that they were about to answer questions regarding their perceptions of persons with schizophrenia. Participants in the VR group and in the regular video group were additionally informed that they were about to watch a video of a person who suffered from schizophrenia talking about their experiences, and—in the case of the VR video—that this may cause slight dizziness.Zeiss VR One with a Samsung Galaxy S8) that was hidden in a drawer and helped the respondent mount it. Participants were then given about 90 seconds to become acquainted with the virtual surroundings. The assistant then started the video on the phone. In the regular video group, the assistant started the video on the laptop. In the control group, no video was shown. All participants then filled out a questionnaire on the laptop. At the end, participants were comprehensibly debriefed and handed over a fact sheet about schizophrenia. For the debriefing document, see the online supplementary material (OSM).In the VR group, the assistant then revealed the VR headset  to 7 . Where applicable, we applied Confirmatory Factor Analysis (CFA) and Exploratory Factor Analysis (EFA) for uncovering underlying dimensions within the scales. For all items and the analysis code, see the OSM.We assessed all measures but contact frequency with a Likert-type scale ranging from 1  and created a mean index .We measured empathy toward persons with schizophrenia using an indicator developed by Kinnebrock et al.  and usedr = 0.48) and created a mean index .We measured benevolence toward persons with schizophrenia with the benevolence dimension of the Community-Attitudes-Toward-the-Mentally-Ill Inventory (CAMI), translated to German by Angermeyer et al. . We replnot at all) to 5 (a lot).We asked how much contact participants have had with persons with schizophrenia within their “family, circle of friends or acquaintances within the past five years” on a scale ranging from 0  and then 0.6.8; ), and tin 1.3.1; ). Additip < 0.05.We ran various Structural Equation Models (SEM) to cover comparisons between our experimental groups. We always used anxiety, social proximity, empathy, and benevolence as outcome variables and controlled for the quantity of prior out-group contact, gender, and age. For the comparison between the VR and regular video groups, we additionally controlled for evaluation of the encountered group member and spatial presence during reception. We focus on both statistical significance and effect sizes/directions and report significance at See RMSEA = 0.070, CFI = 0.921). None of the effects were significant, and in terms of mere effect sizes, the VR video group showed more social proximity than the control group, but also marginally more anxiety and marginally less empathy and benevolence.In Model 1, we compared the VR group with the control group and found that contact in VR did not decrease stigmatization in comparison to not having any exposure at all . In this comparison, VR contact actually increased stigmatization. The VR group showed significantly more anxiety, significantly less social proximity and empathy, and less benevolence judging by the effect only. Contrasting VR with regular video contact allowed us to account for context variables surrounding the reception experience. The evaluation of the group member emerged as a crucial predictor: A more positive evaluation of the encountered person significantly decreased anxiety and significantly increased social proximity and benevolence, as well as empathy, judging by the effect only. Moreover, we found that spatial presence during reception marginally decreased anxiety and increased social proximity, empathy and benevolence—although only the effect on benevolence was significant.In Model 2, we compared the VR group with the regular video group . In comparison to no exposure, the regular video decreased anxiety, increased empathy, social proximity, and marginally benevolence—although only the effect for social proximity reached statistical significance.In Model 3, we compared the regular video group with the control group . As a result, the effect of the VR video changed directions. VR exposure significantly increased social proximity and—although not significantly—also increased benevolence and decreased anxiety.To corroborate the impression from Model 2, we re-ran the comparison between the VR group and the control group just for participants who evaluated the group member in the video in a positive way, i.e., who scored higher than the median value, in Model 4 (Finally, it is notable that more prior direct contact decreased stigmatization constantly and mostly significantly in all models. Although gender had no significant effect, older participants usually showed higher levels of stigmatization.This study aimed for contributing to the growing literature on destigmatization of mental disorders via contact interventions by testing the potential of VR technology. Specifically, we investigated whether intergroup contact with a person with schizophrenia through VR technology can decrease stigmatization towards people with schizophrenia.Our study revealed that contact through VR is not a magic bullet for reducing stigmatization in the context of mental disorders. Encountering a person talking about their life with schizophrenia in VR did not significantly decrease stigmatization. Judging by effect direction only, contact via VR may even have negative effects and perpetuate existing stigma. In comparison to watching the regular video, VR contact was associated with significantly more stigmatization in three out of four outcomes. At the same time, participants who watched the regular video showed slightly less stigma than the control group. At first glance, the negative effects of the VR video intervention are counter-intuitive, since the sensual richness and personal involvement of VR promised to make it an effective form of intergroup contact . HoweverIn our study, evaluation of the encountered group member emerged as the most important factor for a successful destigmatization via VR. A positive evaluation was negatively associated with all indicators of stigmatization, regardless of the type of video. Moreover, contact in VR did decrease stigmatization among respondents who evaluated our actor in a positive way. It is therefore essential to establish in advance that the encountered person appears likeable to the target audience. This may be particularly important for mental disorders such as schizophrenia that are stereotypically associated with threat ,20.The evaluation of the encountered person was important in VR, but not in the regular video which decreased stigmatization independently of it. Subjects were likely overwhelmed by the VR experience and therefore processed the video in a peripheral, heuristic manner . Among pBased on our findings, future researchers do not only need to choose a likeable person for VR contact, but simultaneously ensure high levels of immersion without making the experience overwhelming, which is in line with previous research . SeveralAltogether, we only expect positive effects from VR encounters if the contact situation is carefully calibrated. The assumed advantages of VR over other forms of mediated contact may turn out to be disadvantages otherwise. Future research should investigate the suggestions introduced above. While it was not in the focus of this article, our results indicate the importance of direct intergroup contact as a means for reducing stigmatization, as the mere quantity of prior contact was constantly associated with less stigmatization.Our study is a first exploration of the potential of VR contact for reducing stigmatization against persons with schizophrenia. As an explorative study, it is limited regarding four ways. First, using a sample that predominantly consists of students can have advantages for exploratory studies with limited sample size, since age and education are rather homogeneous. However, a more heterogeneous sample would yield more generalizable effects . Second, contact . Since p contact , future In contrast to our expectations, contact through VR did not reduce stigmatization as compared to no contact and led to more negative attitudes as compared to contact through a regular video in our study. This effect shifted once we only considered individuals who evaluated the encountered group member positively. Our findings offer first insights into the conditions of successful destigmatization through contact in VR—namely how it could be optimized to maximize positive effects and minimize undesirable outcomes. We hope this study instills a greater engagement with the potential of new technologies for generating pro-social attitudes towards people with mental disorders in general and people with schizophrenia in particular and thus contributes to a better quality of life for those affected.