mundane vs experimental realism

Exploring Mundane Realism in Psychology: Implications and Considerations

Have you ever wondered how realistic psychological research studies are in the context of everyday life? Mundane realism in psychology refers to the extent to which research findings accurately reflect the complexities of real-world experiences. This article delves into the importance of mundane realism in psychological research, the methods used to assess it, its implications on the generalizability of findings, and strategies for enhancing it in studies. Join us as we explore the intricacies of mundane realism and its impact on psychological research.

• 1 What is Mundane Realism in Psychology?
• 2.1 What is the Difference between Mundane Realism and Experimental Realism?
• 3.1 What are the Common Methods of Assessing Mundane Realism?
• 3.2 What are the Limitations of Assessing Mundane Realism?
• 4.1 How Does Mundane Realism Affect the Generalizability of Research Findings?
• 4.2 What are the Ethical Considerations of Using Mundane Realism in Research?
• 5.1 What are Some Strategies for Enhancing Mundane Realism?
• 5.2 How Can Researchers Address the Limitations of Mundane Realism?
• 6 Conclusion: The Importance of Considering Mundane Realism in Psychological Research
• 7.1 What is mundane realism in psychology?
• 7.2 Why is mundane realism important in psychological research?
• 7.3 How can mundane realism be evaluated in psychological studies?
• 7.4 What are the implications of low mundane realism in psychological research?
• 7.5 How can researchers increase mundane realism in their studies?
• 7.6 What are some considerations to keep in mind when exploring mundane realism in psychological research?

What is Mundane Realism in Psychology?

Mundane realism in psychology refers to the extent to which an experiment mirrors real-life situations and experiences, aiming to replicate the everyday environment in a controlled setting.

This concept plays a crucial role in experimental settings as it enhances the ecological validity of the research, making the findings more applicable to real-world scenarios. By incorporating elements of everyday life, researchers can observe how individuals react and behave in situations that closely resemble their usual experiences.

When participants are exposed to scenarios that are relatable and reflect their daily routines, it can lead to more authentic responses and behaviors, providing researchers with valuable insights into human behavior.

One example of a study that utilized mundane realism is the Workplace Simulation Study conducted by Smith et al., where participants were placed in a realistic office setting to observe their decision-making processes and interactions with colleagues, demonstrating the importance of creating environments that mirror real-life situations in psychological research.

Why is Mundane Realism Important in Psychological Research?

Mundane realism holds crucial importance in psychological research as it enhances the external validity of a study, allowing researchers to draw meaningful conclusions that can be generalized to real-life situations.

This concept essentially ensures that the settings and scenarios used in experiments closely resemble everyday situations, increasing the reliability of the study’s findings. By immersing research participants in scenarios that mimic real-world experiences, researchers can observe natural behaviors and responses, offering deeper insights into human behavior. Mundane realism plays a significant role in studying variables in authentic contexts, providing a more accurate reflection of how individuals would react in similar situations outside a controlled lab setting.

What is the Difference between Mundane Realism and Experimental Realism?

Mundane realism and experimental realism are two key concepts in psychology that differentiate in their emphasis on simulating real-world environments versus creating controlled but authentic experimental conditions to ensure construct validity.

Experimental realism places a paramount importance on designing experiments that closely mirror real-life situations while offering the ability to control and manipulate specific variables. This approach often involves creating scenarios that participants can fully immerse themselves in, allowing researchers to observe genuine reactions and behaviors.

On the contrary, mundane realism puts the focus on how closely the experimental setting resembles the everyday experiences and contexts that individuals encounter outside of a research setting. This can involve using familiar settings, tasks, and stimuli that participants are likely to encounter in their daily lives, aiming to capture natural responses and behaviors in a controlled environment.

How is Mundane Realism Assessed in Psychological Studies?

Assessing mundane realism in psychological studies involves utilizing statistical analysis and validity measures to gauge the degree to which the study accurately reflects real-world contexts and situations.

Researchers employ various methods to ensure the authenticity of experimental settings. One common approach is through the manipulation of stimuli and environmental cues to mirror real-life scenarios. Conducting pilot tests and pre-testing instruments helps in refining the experimental setup to enhance the study’s resemblance to everyday situations. Statistical tools like ANOVA and regression analyses aid in interpreting data and determining the significance of results. Regular validity checks are imperative to maintain the study’s credibility by verifying the alignment of the experimental conditions with real-world contexts.

What are the Common Methods of Assessing Mundane Realism?

Common methods of assessing mundane realism in psychological research include conducting field studies to observe behaviors in natural settings, and employing power analysis techniques to determine the study’s ability to detect meaningful effects.

Field studies provide researchers with an opportunity to witness how individuals behave in their everyday environments, offering a glimpse into real-life interactions and responses.

These studies often involve naturalistic observations without participants being aware they are being studied, ensuring a more authentic representation of human behavior.

Power analysis is crucial as it helps researchers determine the sample size required to detect a significant effect with a given level of confidence, ensuring the study’s validity in practical scenarios.

What are the Limitations of Assessing Mundane Realism?

Despite its benefits, assessing mundane realism in psychological studies can pose limitations related to ensuring construct validity and maintaining statistical validity when replicating real-life situations in controlled experimental settings.

One of the key challenges in evaluating mundane realism lies in replicating real-world scenarios in a controlled experimental environment without compromising the authenticity of the experience.

Researchers often face difficulties in recreating the full complexity and nuances of everyday situations, leading to a potential gap between the experimental setup and real life.

Maintaining construct validity becomes problematic when attempting to generalize findings from artificial experimental conditions to the broader population.

What are the Implications of Mundane Realism in Psychological Research?

Mundane realism in psychological research significantly influences the generalizability of findings, providing insights into how behaviors observed in controlled experiments may relate to real-world phenomena such as anxiety and depression.

One of the key implications of mundane realism is that it ensures that research findings can be applied to various real-life situations, making the results more applicable and meaningful to society. By examining how individuals interact in simulated environments that closely mirror everyday scenarios, researchers can better understand human behavior in naturalistic settings.

This understanding gained from controlled experiments can offer valuable perspectives on issues like anxiety and depression, offering practical solutions that can be translated into interventions for individuals struggling with mental health challenges.

How Does Mundane Realism Affect the Generalizability of Research Findings?

Mundane realism plays a vital role in enhancing the generalizability of research findings by capturing nuances of social interaction and conformity behaviors within realistic settings, enabling a deeper understanding of these phenomena.

Realistic experimental settings are essential in creating an environment that mirrors everyday life, allowing researchers to observe natural responses and behaviors. This authenticity leads to findings that can be more applicable to real-world situations, rather than artificial laboratory conditions. By immersing participants in scenarios that closely resemble their daily experiences, studies become more relatable and reflective of how individuals would react in practical scenarios. This focus on realism ensures that the data collected is not only relevant but also highly credible, increasing the validity and applicability of research outcomes.

What are the Ethical Considerations of Using Mundane Realism in Research?

When employing mundane realism in research, ethical considerations such as respecting participants’ autonomy in studies related to social cognition and mental health are paramount to ensure the well-being and rights of individuals involved.

Researchers must navigate a delicate balance between creating authentic research scenarios and safeguarding the rights and well-being of participants. In studies exploring social cognition and mental health, ensuring confidentiality, informed consent, and debriefing procedures becomes even more crucial. Upholding ethical standards involves transparency in the study design, ensuring that participants understand the purpose and potential impact of their involvement.

Respecting autonomy means that participants have the right to choose their level of involvement and withdrawal without any form of coercion, protecting their dignity and privacy in the research process.

How Can Researchers Improve Mundane Realism in Their Studies?

Researchers can enhance mundane realism in their studies by employing effective manipulation of variables, ensuring proper control of experimental conditions, and incorporating elements that closely mimic real-life situations.

One approach is to carefully select and manipulate the independent variables within the study to reflect real-world complexities. By incorporating diverse and nuanced elements into the experiments, researchers can create a more authentic environment for their investigations. Establishing stringent control over extraneous variables is crucial in ensuring that the true effects of the manipulated variables are accurately captured. Researchers may also consider implementing scenarios or tasks that closely resemble everyday situations, allowing participants to engage with the study material in a context that feels familiar and relevant.

What are Some Strategies for Enhancing Mundane Realism?

Strategies for enhancing mundane realism in studies include utilizing real-world scenarios like towel usage behaviors in hotel guests to improve the validity of findings and create more relatable experimental conditions.

By incorporating such context-specific elements into research designs, researchers can bridge the gap between controlled laboratory settings and everyday life situations, thereby increasing the applicability and generalizability of their results. Observing and analyzing how hotel guests interact with towels can provide valuable insights into consumer behavior patterns and decision-making processes, shedding light on practical implications for the hospitality industry and beyond. This method not only strengthens the credibility of the study but also ensures that the outcomes accurately reflect real-world scenarios, enabling more actionable conclusions and recommendations.

How Can Researchers Address the Limitations of Mundane Realism?

Researchers can address the limitations of mundane realism by considering alternative approaches such as integrating elements of experimental realism as proposed by Fredrickson to enhance the authenticity of study settings and overcome potential constraints.

One of the key strategies to implement experimental realism is to create scenarios that closely resemble real-world situations, allowing participants to engage in behaviors as they would naturally. By incorporating interactive elements or live simulations, researchers can capture more genuine responses and behaviors from participants, thus increasing the ecological validity of their studies. Utilizing advanced technologies like virtual reality or immersive environments can further enhance the experiential aspect of the research, creating a more life-like setting for participants to interact within.

Conclusion: The Importance of Considering Mundane Realism in Psychological Research

The careful consideration of mundane realism in psychological research is paramount for ensuring the validity and generalizability of study findings, highlighting the need for researchers to balance authenticity with control in experimental settings.

Mundane realism refers to the extent to which the environment and tasks in a study resemble the real world. By incorporating everyday scenarios and settings in research, researchers can better understand how individuals behave and react in natural contexts, thus increasing the external validity of their findings.

The inclusion of mundane elements in research helps in minimizing demand characteristics, where participants may alter their behavior due to the artificiality of the experimental setup. This authenticity promotes more genuine responses, leading to more accurate conclusions.

Frequently Asked Questions

What is mundane realism in psychology.

Mundane realism in psychology refers to the degree to which an experimental setting or scenario accurately reflects real-life, everyday situations and experiences.

Why is mundane realism important in psychological research?

Mundane realism is important in psychological research because it helps to ensure that the results and findings of a study can be applied to real-world situations and contexts, increasing the external validity of the research.

How can mundane realism be evaluated in psychological studies?

Mundane realism can be evaluated by examining the level of similarity between the experimental setting and the real-life situation it is attempting to represent, as well as by considering the participants’ perceptions of the study’s realism.

What are the implications of low mundane realism in psychological research?

Low mundane realism can limit the generalizability of research findings, as well as potentially bias participants’ responses and behaviors due to the artificial nature of the experimental setting. It can also lead to a lack of ecological validity, or the extent to which the study reflects real-life conditions.

How can researchers increase mundane realism in their studies?

Researchers can increase mundane realism in their studies by using more naturalistic settings and scenarios, incorporating real-world stimuli and measures, and providing participants with meaningful tasks and goals that mimic real-life situations.

What are some considerations to keep in mind when exploring mundane realism in psychological research?

Some considerations to keep in mind include the balance between mundane realism and experimental control, potential ethical concerns arising from using more realistic scenarios, and the trade-off between mundane realism and internal validity, or the ability to determine causality within the study.

Dr. Naomi Kessler is a forensic psychologist with extensive experience in criminal behavior analysis and legal consultancy. Her professional journey includes working with law enforcement agencies, providing expert testimony in court cases, and conducting research on the psychological profiles of offenders. Dr. Kessler’s writings delve into the intersection of psychology and law, aiming to shed light on the complexities of human behavior within the legal system and the role of psychology in justice and rehabilitation.

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Mundane Realism: Definition: Mundane realism refers to the extent to which an experiment or research study accurately captures and represents real-world situations and everyday experiences. It aims to replicate the ordinary circumstances and conditions under which people typically behave.

Importance of Mundane Realism: Mundane realism is crucial in psychological and social research as it enhances the ecological validity of findings. By closely resembling real-life situations, researchers can provide results that are applicable and generalizable to everyday life scenarios.

Key Characteristics: Mundane realism emphasizes the use of familiar materials, settings, and procedures that resemble naturalistic contexts. It focuses on avoiding artificiality and contrived experimental environments, allowing participants to engage in activities that reflect their usual behaviors and responses.

Methods of Achieving Mundane Realism: Researchers strive to achieve mundane realism by employing field experiments, naturalistic observations, or employing manipulations and scenarios that closely resemble real-life encounters. This can involve conducting research in natural settings or replicating real-world situations in laboratory settings.

Benefits and Limitations: The benefits of mundane realism include a higher degree of external validity, as findings are more likely to apply to real-world situations. This can enhance the applicability and practicality of research outcomes. However, mundane realism may be challenging to achieve in certain areas of study, and researchers must carefully balance ecological validity with experimental control.

Example: An example of a study with mundane realism would be studying driver behavior by observing participants driving in a realistic simulator that replicates real road conditions rather than using artificial stimuli in a laboratory setting. This approach provides a more accurate representation of how individuals respond and behave while driving in their daily lives.

Overall, mundane realism plays a vital role in ensuring research accurately reflects and represents the complexities of the real world, allowing for meaningful and applicable conclusions to be drawn.

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Keeping It Real in Experimental Research—Understanding When, Where, and How to Enhance Realism and Measure Consumer Behavior

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Andrea C Morales, On Amir, Leonard Lee, Keeping It Real in Experimental Research—Understanding When, Where, and How to Enhance Realism and Measure Consumer Behavior, Journal of Consumer Research , Volume 44, Issue 2, August 2017, Pages 465–476, https://doi.org/10.1093/jcr/ucx048

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In this article, we consider why employing realistic experimental designs and measuring actual behavior is important and beneficial for consumer research. More specifically, we discuss when, where, and how researchers might go about doing this in order to increase the veracity and believability of their work. We analyze the choice of independent variables (IVs) along the experimental-realism dimension, ranging from artificial to realistic, and the choice of dependent variables (DVs) along the behavioral-measures dimension ranging from hypothetical intention to actual behavior. Importantly, we also map various goals of consumer research along these two dimensions to highlight when it is most appropriate to enhance the realism and behavioral measures of an experiment. Using a number of illustrative examples from research in the extant literature, we specifically highlight how consumer researchers can increase experimental realism and utilize actual-behavior measures in their experiments in order to improve both the fidelity of the research and the likelihood that the research provides insight into real consumer behavior.

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The Treachery of Images: How Realism Influences Brain and Behavior

Jacqueline c. snow.

1 Department of Psychology, University of Nevada Reno, Reno, Nevada, USA

Jody C. Culham

2 Department of Psychology, University of Western Ontario, London, Ontario, Canada

3 Brain and Mind Institute, Western Interdisciplinary Research Building, University of Western Ontario, London, Ontario, N6A 3K7, Canada

Although the cognitive sciences aim to ultimately understand behavior and brain function in the real world, for historical and practical reasons, the field has relied heavily on artificial stimuli, typically pictures. We review a growing body of evidence that both behavior and brain function differ between image proxies and real, tangible objects. We also propose a new framework for “immersive neuroscience” to combine two approaches: (1) the traditional “build-up” approach of gradually combining simplified stimuli, tasks, and processes; and (2) a newer “tear-down” approach that begins with reality and compelling simulations such as virtual reality to determine which elements critically affect behavior and brain processing.

The Dependence on Proxies for Realism in Cognitive Sciences

In a famous painting, The Treachery of Images , artist René Magritte painted a pipe above the words “Ceci n’est pas une pipe” (“This is not a pipe”). When asked about the painting, he replied, “Could you stuff my pipe? No, iťs just a representation, is it not? So if I had written on my picture ‘This is a pipe’, I'd have been lying!” [ 1 ]. Magritte had an insight that applies even to psychology and neuroimaging: a picture of an object is only a limited representation of the real thing.

Despite such intuitions regarding the importance of realism, researchers in the cognitive sciences often employ experimental proxies (see Glossary) for reality. One ubiquitous proxy is the use of artificial two-dimensional (2-D) images of stimuli that are not actually present, evoking indirect perceptions of depicted objects or scenes [ 2 ]. Images predominate over real objects in research because they are easy to create, easy to present rapidly with accurate timing on computer displays, and easy to control (e.g., for low-level attributes like brightness). Researchers will often employ the phrase “real-world” to imply that some feature of the image matches some aspect of reality (such as category, image statistics, familiar properties like size, or implied depth), even though the stimuli are not real objects, which we define as physical, tangible 3-D solids (see Box 1 ).

Box 1: Terminology for Visual Stimuli

One of the challenges in understanding differences between stimuli is the conflicting nomenclature used by different researchers. Some of the confusion could be remedied by adopting of a consistent set of terms:

2-D Images are planar displays that lack consistent cues to depth. Most commonly, 2-D images are presented via a computer to a monitor or projection screen; however, they can also be printed. They may differ in iconicity, the degree to which the picture resembles the real object [ 126 ], ranging from line drawings to photographs. Typically, 2-D images provide only monocular cues to depth (e.g., shading, occlusion) but no stereoscopic or motion-parallax cues to the depth of components within the image. 2-D images often misrepresent the size of the depicted object, with unrealistic relationships between physical size, distance and familiar size.

3-D Images are generated by presenting two 2-D images, one to each eye, that provide stereoscopic cues to depth. They assume a fixed head position and do not provide motion parallax if the observer moves.

Real Objects

Real Objects are tangible solids that can be interacted with. We prefer not to use the term “3-D Objects,” which implies that the key difference from 2-D images is the third dimension (vs. other potential differences such as tangibility or actability). Although many researchers use the terms “real” or “real-world” for images that depict real objects, confusion could be avoided by limiting the use of “real” to physical objects and using other descriptors like “realistic” for representations that capture reality incompletely.

Simulated Realities

Simulated Realities (SR) includes approaches that aim to induce a sense of immersion, presence and agency . In Virtual Reality (VR), a computer-generated simulated environment is rendered in a head-mounted display (HMD). The display provides stereoscopic 3-D depth cues and changes as the observer moves, giving the observer the illusions of presence and agency. VR may also enable interactions with objects, typically through hand-held controllers. In Augmented Reality (AR) computer-generated stimuli are superimposed on an observer’s view of the real environment (through a transparent head-mounted display (HMD) or passed-through live video from cameras attached to the HMD). Some use the term Mixed Reality (XR) to encompass VR and AR; however, the term is used inconsistently (sometimes being treated as synonymous with AR) so we propose the term Simulated Realities. SR could include other approaches that are technically not VR or AR, such as game engines that present stimuli on monitors or 3-D projectors rather than HMDs.

Here we address whether behavior and brain responses to real objects may differ from images. Though the potential theoretical importance of realism has been recognized for decades [ 2 ], there is an emerging body of empirical evidence for such differences. With the advent of human neuroimaging, our understanding has expanded from the earliest stages of visual processing (e.g., V1) to higher-level brain regions involved in recognition and actions in the real world. Correspondingly, our understanding of vision and cognition may need to progress beyond light patterns and images to encompass the tangible objects and scenes that determine everyday behavior.

Why Might Proxies Differ from the Real World?

Before reviewing empirical evidence for differences between proxies and the real world, we note that philosophically, there are reasons to posit such differences.

Realism vs. symbolism

As Magritte highlighted best, while tangible objects satisfy needs, images are representational and often symbolic (e.g., cartoons). Images have a unique ‘duality’ because they are both physical objects comprised of markings on a surface, and at the same time, they are representations of something else [ 2 – 5 ]. Humans can easily recognize images such as line drawings; however, such representational images are a relatively new invention of humankind, with cave drawings appearing only within the last 45,000 years [ 6 ] of the 4–5 million years of hominin evolution. Moreover, pictures were highly schematic (such as outlines with no portrayal of depth) until artists learned how to render cues like perspective during the Renaissance and to use photography and film in the 19 th century [ 7 ]. With increasingly compelling simulations, there is increased awareness of the potential importance of presence , the sense of realism and immersion [ 8 , 9 ].

Animals evolved to survive in the natural world using brain mechanisms that perform actions guided by sophisticated perceptual and cognitive systems. Modern cognitive neuroscience relies heavily on reductionism, using impoverished stimuli and tasks that neglect the importance of actions as the outcomes upon which survival has depended for millions of years [ 10 ]. Despite the importance of action outcomes for evolutionary selection, historically, psychology has neglected motor control [ 11 ], even though all cognitive processes, even those that are not explicitly motor (e.g., attention and memory), evolved in ultimate service of affecting motor behavior [ 12 ]. Increasingly, researchers are realizing that theories developed in motor control, such as the importance of forward models and feedback loops [ 13 ], may explain many other cognitive functions from perception through social interactions [ 14 ]. As such, one must question why so many cognitive studies use stimuli – particularly static images -- that do not afford motor behavior or use tasks no more sophisticated than pressing a button or uttering a verbal response. Images do not afford actual actions. Images may evoke notions of affordances [ 15 ] and action associations [ 16 ] but they lack actability , the potential to interact with the represented object meaningfully. Put simply, one cannot pound a nail with a photo of a hammer.

In addition, images are purely visual and thus lack genuine cross-modal processing. For example, when determining the ripeness of a peach, color provides some cues to ripeness but ideally this is confirmed by assessing how well it yields to a squeeze, smells fragrant, and tastes sweet and juicy. Multisensory processing not only allows more accurate interpretation of objects in the world, it enables hypotheses generated from one sense to be tested using another. Yet pictures are rarely touched (by adults) and haptic exploration would merely confirm the flatness conveyed by vision.

Motion and depth

Even in terms of vision alone, images are impoverished. Most notably, images never change, although videos can be used to convey animation. In addition, images lack a veridical combination of depth cues. Whereas pictures can accurately convey relative depth relationships (e.g., the ball is in front of the block), they have limited utility in computing absolute distances (e.g., the ball is 40 cm away, within reach, and the block is 90 cm away, beyond reach) and thus inferring real-world size and actability. With images, depth cues may be in conflict: monocular cues (e.g., shading, occlusion) convey three-dimensionality while stereopsis and oculomotor cues convey flatness and implausible size-distance relationships. For example, in typical fMRI studies, stimuli may include large landmarks (e.g., the Eiffel tower) and small objects (e.g., coins) that subtend the same retinal angle at the same viewing distance even though their typical sizes differ by orders of magnitude in the real world. Compared to static images, dynamic movies can evoke stronger activation in lateral (but not ventral) occipitotemporal cortex [ 17 – 19 ]. The addition of 3-D cues from stereopsis evokes stronger brain responses and stronger inter-regional connectivity, compared to flat 2D movies [ 8 , 20 ]. 3-D effects are stronger for stimuli that appear near (vs. far) and the effects increase through the visual hierarchy [ 21 ]. Motion and depth are also likely to be important for the perception of real objects, although none of these studies actually employed real objects, where depth may be especially important for both action and perception.

Development

Not only are these factors important for object processing in adults, they are fundamental during early development. Infants learn to make sense of their environment largely through the interactions and multisensory integration provided in the tangible world. Young infants fail to understand that images are symbolic and may try to engage with them [ 22 ]. Bodily movement and interaction with objects are crucial to child development, as shown by the quantum leaps in cognitive abilities that occur once infants become mobile [ 23 – 25 ]. Indeed, as classic research showed, humans [ 26 ] and other animals [ 27 ] require self-initiated active exploration of the visual environment for normal development and coordination. Evidence is mixed as to whether other species comprehend images as representations of reality [ 28 ], even though images are common stimuli for neurophysiological research. Realism can also have striking effects on object processing in human infants and young children, as well as in animals (see Box 2 ).

Box 2: Realness influences behavior in human infants and animals

Similar to adults, children’s object recognition is influenced by the realness of the stimuli and tasks. Object recognition in infants has traditionally been investigated using habituation tasks, which are based on infants’ general preference for new stimuli over previously seen items, as reflected in looking and grasping behaviors [ 119 ]. Capitalizing on this novelty preference in habituation tasks, infants are initially exposed (or ‘habituated’) to a stimulus, such as a picture of a shape or toy, and are subsequently presented with a different stimulus, such as a real object, to see whether or not habituation transfers to the new item. Habituation studies have shown that human infants can perceive the information carried in pictures even with remarkably little pictorial experience. For example, newborn babies can discriminate between basic geometric figures that differ in shape alone [ 120 ] and between 2-D versus 3-D stimuli [ 121 , 122 ]. By 6–9 months of age, infants can distinguish pictures from real objects. Moreover, infants show generalization of habituation from real objects to the corresponding 2-D pictures [ 122 – 124 ], and from 2-D pictures to their real objects [ 124 , 125 ]. Although picture-to-real object transfer in recognition performance improves with age and iconicity [ 126 ], this does not mean that infants understand what pictures are. Elegant work by Judy DeLoache and colleagues, for example, has shown that when given colored photos of toys, young infants initially attempted to grasp the pictures off the page, as do children raised in environments without pictures (such as Beng infants from West Africa) [ 22 ]. As in habituation studies showing picture-to-object transfer, manual investigation of pictures of toys is influenced by how realistic the pictures look, with more realistic pictures triggering greater manual investigation [ 127 ]. In a comprehensive review of the literature on picture perception, Bovet & Vauclair [ 28 ] concluded that a diverse range of animals (from invertebrates through great apes) can show appropriate responses to depicted stimuli, particularly ecologically relevant stimuli such as predators or conspecifics. Similar to human infants, such effects in animals appear strongest when animation or three-dimensionality are present and with increased exposure to pictorial stimuli. Nevertheless, their review highlights many cases where animals, infants and individuals from cultures without pictures fail to recognize depicted objects.

In sum, because humans have evolved and developed in the real world, our behaviors and brain processes are likely to reflect the important features of tangible objects and environments – tangibility, actability, multisensory processing, and motion and depth.

Empirical Evidence for The Importance of Real Objects

Despite theoretical arguments for the importance of real objects for understanding behavior and brain function, surprisingly few empirical studies have used real-world stimuli or directly compared responses to stimuli in different formats. However, with the development of novel methods for presenting real objects under controlled conditions (see Figure 1 ), there is growing evidence that real objects elicit different responses compared to images.

Innovative methods used to compare responses to real objects and representations. (A) Example from behavior. (i) In a recent study of decision-making, Romero et al. [ 57 ] used a custom-built turntable device to display a large set of real objects and closely-matched 2-D computerized images of everyday snack foods. Schematic shows the experimental setup from above. On real object trials the stimuli were visible on one sector of the turntable; on image trials the stimuli were displayed on a retractable monitor mounted on a sliding platform. Stimulus viewing on all trials was controlled using liquid-crystal glasses that alternated from transparent (‘closed’) to opaque (‘open’) states. (ii) Real object trial (left); image trial (right). Though stimuli are shown from above here, from the participants’ viewpoint, displays appeared similar except for differences in stereopsis. (B) Presenting observers with real objects is especially challenging within fMRI environments. (i) Snow et al. [ 53 ] used fMRI to compare brain responses to everyday real-world objects versus photos. Using a repetition-suppression design, pairs of real/picture stimuli were presented from trial-to-trial on a turntable mounted over the participant’s waist. Following from Culham et al., [ 130 ], the head coil was tilted forwards to enable participants to view the stimuli directly, without the use of mirrors. (ii) On each trial, two objects (lower left), each mounted on opposite sides of a central partition, were presented in rapid succession. Stimulus viewing on each trial was controlled using time-locked LED illumination; gaze was controlled using a red fixation light (lower right).

Object Recognition

Recognition performance may be better for real objects compared to pictures, an effect known as a real-object advantage , in both neuropsychological patients and typical individuals. Although patients with visual agnosia are typically unable to recognize 2-D pictures of everyday objects, they can often recognize objects presented as real-world solids [ 29 – 36 ]. Interestingly, the real-object advantage in agnosia patients appears to be related to expectations about the typical real-world size of tangible objects – information that is not available in 2-D images. Specifically, patients with visual agnosia performed better at object recognition for tangible objects than pictures but only when the physical size of the real objects was consistent with the typical real-world size [ 37 ].

A driving factor in the real-object advantage seems to be actability. An electroencephalography (EEG) study that found that, compared to matched images, real tools invoked a stronger and more sustained neural signature of motor preparation contralateral to the dominant hand of participants [ 38 ]. Moreover a neuroimaging study found different neural representations for real, tangible objects vs. similar images during hand actions, particularly when 3-D cues conveyed important information for grasping [ 39 ]. Notably, not all phenomena show a real-object advantage, and this can provide clues as to the nature of processing. For example, realism does not influence tool priming, suggesting that this particular phenomenon relies on a semantic process unaffected by actability [ 40 , 41 ].

Though we have focussed on visual objects, realism may also be important for sensory processing and recognition in domains other than vision. For example, audition researchers are coming to realize that a large body of research using simple tones may not generalize to natural sounds [ 42 – 45 ].

Real objects are more memorable than 2-D photographs of the same objects. When asked to remember everyday objects, free recall and recognition were both superior for participants who viewed real objects compared to those who viewed colored photographs or line drawings [ 46 ]. Realism may be particularly important for the study of episodic memory, which is heavily framed by the context [ 47 ].

In an electroencephalography study, a neural correlate of familiarity for previously seen stimuli (the ‘old-new’ effect) was stronger when objects were first seen in real format then picture format compared to the converse [ 38 ]. These results suggest that stimuli that were first encountered as real-world objects were more memorable than their pictures [ 46 ].

Attention and gaze preferences

Real objects also capture attention more so than 2-D or 3-D images. When participants were asked to discriminate the orientation of tools (spoons), their reaction times were more affected by the orientation of irrelevant distractor objects when the stimuli were real objects compared to pictures or stereoscopic 3-D images [ 48 ]. Critically, the stronger attentional capture for real stimuli depended on actability. When the stimuli were positioned out of reach of the observer, or behind a transparent barrier that prevented in-the-moment interaction with the stimuli, the real objects elicited comparable interference effects as did the 2-D images. The use of a transparent barrier is a particularly elegant manipulation because it removes immediate actability while keeping the visual stimulus (including 3-D visual cues) nearly identical. Studies of eye gaze also suggest that real objects capture attention more effectively than pictures, an effect we term the real-object preference . For example, when infants as young as 7 months see a real object beside a matched photo, they spend more time gazing at the real object, even if they had already habituated to it [ 49 ]. Moreover, the preference for real objects is correlated with the frequency with which individual infants use touch to explore objects, suggesting that actability and multisensory interactions are key factors [ 50 ]. Macaque monkeys also spontaneously look at real objects longer than pictorial stimuli [ 51 ].

Neural evidence suggests that real objects are processed differently than matched pictures, consistent with behavioral preferences and mnemonic advantages for real objects. While repeated presentations of object images leads to reduced fMRI activation levels, a phenomenon called repetition suppression [ 52 ], surprisingly, such repetition effects were weak, if not absent, when real objects were repeated [ 53 ].

Neural evidence from humans and n0n-human primates suggests that brain responses in action-selective regions are driven by actability, with stronger responses in action-selective brain regions to real objects that are within reach [ 54 ], especially of the dominant hand [ 55 ]. Indeed the responses in some neurons is reduced or eliminated when a real object is placed beyond reach or blocked by a transparent barrier [ 56 ]. Similarly, in studies of human decision-making, real food is considered more valuable [ 57 , 58 ] and more irresistible [ 59 ] than images of food [ 60 ], particularly when it is seen within reach [ 58 , 61 ].

Attention also appears to be modulated by the cognitive knowledge that an object is real, including the recognition that real interactions would have real consequences. That is, actability may include not just the ability to grasp and manipulate stimuli but for those stimuli to have real ecological consequences. As one example, participants who believed a real tarantula [ 62 ] or snake [ 63 ] was approaching showed robust activation in emotion-related regions, apparently stronger than for images [ 64 ].

Quantitative vs. Qualitative Differences Between Real Objects and Images

Accumulating evidence certainly suggests that, compared to artificial stimuli, realistic stimuli lead to quantitative changes in responses, including improvements in memory [ 46 , 47 ] object recognition [ 37 ], attention and gaze capture [ 48 , 49 , 51 ], or valuation [ 57 , 58 ]. These findings signal that realistic stimuli can amplify or strengthen behavioral and brain responses that might otherwise be difficult to observe when relying on proxies.

Though it may be tempting to dismiss quantitative changes as trivial, large changes can nevertheless be meaningful. When research statistics have limited power, especially in neuroimaging studies where costs limit sample sizes, boosts to effect sizes can affect the detectability of meaningful effects. However, given that artificial stimuli are easier to generate and present in the laboratory than real ones, an alternative approach to tackling quantitative differences would be to rely on proxies but compensate for attenuated effects, for example by designing experiments to maximize power (for example, with larger sample sizes).

Although quantitative differences are of theoretical and practical interest, a vital question for ongoing and future research is whether stimulus realism leads to qualitative differences. Qualitative differences would be reflected, for example, by different patterns of behavior, or by activation in different brain areas or networks, for real objects versus artificial stimuli. This question is vital because qualitative differences would suggest that the conclusions about behavior and brain processing generated from studies using images may not generalize to real stimuli. Finding qualitative differences associated with realism could enrich our understanding of naturalistic behavior and brain function, and critically inform theoretical frameworks of vision and action. While quantitative differences in responses to real objects and pictures that stem from lower-level attributes (such as an absence of binocular disparity cues) may seem uninteresting, these cues provide a gateway to higher-level stimulus characteristics, such as egocentric distance and real-world size, which are important for actability.

New methodological approaches that address the similarity of behavioral [ 65 ] or neural [ 66 ] “representations” (based on the similarity of ratings, or patterns of fMRI activation within a brain region, respectively) can assess qualitative differences in the way real versus artificial stimuli are processed, over and above differences in response magnitude. Using these approaches, recent studies have begun to reveal qualitative differences arising from realism.

Real and simulated objects appear to be “represented” differently in typical adult participants. When observers were tasked with manually arranging a set of graspable objects by their similarities, their groupings differed between pictures, real objects, and virtual 3-D objects presented using augmented reality (AR) [ 67 ]. Using a computer mouse, observers grouped pictures of objects by a conceptual factor, the objects’ typical location. In contrast, using the hands to move virtual 3-D projections of objects using AR, observers arranged the items not by their typical location but rather according to their physical characteristics of real-world size, elongation, and weight (rather surprisingly as virtual objects have no actual mass). Observers who lifted and moved real objects incorporated both conceptual and physical object properties into their arrangements. Thus, changes in the format of an object can lead to striking shifts in responses. Objects that can be manipulated using the hands, either directly in reality, or indirectly via AR, evoke richer processing of physical properties, such as real-world size and weight. Such results suggest that experimental approaches that rely solely on images may overestimate the role of cognitive factors and underestimate physical ones.

We propose a testable hypothesis: the factors that contribute to behavioral and neural differences (both qualitative and quantitative) will depend upon the processes being studied and the brain regions and networks that subserve them. For example, images may be a perfectly good, arguably preferable [ 68 ] stimulus for studying low-level visual processes at the earliest stages of the visual system (e.g., primary visual cortex). Even at higher levels of visual processing concerned with perception and semantics (the ventral visual stream), images may effectively evoke concepts to a comparable degree as real objects [ 41 , 69 ]. However, higher levels of visual processing for representing space and actions (the dorsal visual stream) [ 70 , 71 ] are likely to be strongly affected by depth [ 72 – 75 ], and actability [ 54 ].

From Stimulus Realism to Task Realism

In addition to enhancing the realness of stimuli, cognitive neuroscience will also benefit from approaches that allow more natural unfolding of cognitive processes . Growing evidence suggests that real actions affect behavior and brain processes differently than simulations. For example, real actions differ from pantomimed or delayed actions, both behaviorally and neurally [ 76 – 79 ].

Cognitive neuroscience uses a reductionist taxonomy of siloed cognitive functions – perception, action, attention, memory, emotion – studied largely in isolation [ 80 ] and by structured experimental paradigms with experimenter-defined trials and blocks [ 81 ]. Yet in everyday life, a multitude of cognitive functions and the brain networks that subserve them are seamlessly and dynamically integrated. New naturalistic approaches examine correlated brain activation across participants watching the same naturalistic movie segments [ 82 , 83 ]; the results corroborate findings from conventional approaches [ 84 , 85 ], providing a balance between rigour and realism [ 86 ]. Nevertheless, movie viewing is a passive act and may neglect active, top-down cognitive or motor processes.

Many experimental approaches in cognitive neuroscience map stimuli to responses without “closing the feedback loop” such that the consequences of one response become the stimulus for the next response [ 13 ]. This issue has long been recognized [ 87 ] but has had limited impact on mainstream experimental approaches. Alternative approaches advocate for the study of the “freely behaving brain” [ 88 ]. For example, studies of taxi drivers’ neuroanatomy [ 89 ] and spontaneous cognitions during virtual driving tasks [ 90 , 91 ] have unveiled the neural basis of dynamic real-world navigation. Emerging technologies may enable recording of human neural activity in real-world scenarios [ 92 – 96 ]. Emerging data-driven analysis strategies enable the study of brain processes during broad-ranging stimuli or behaviors [ 95 , 97 , 98 ], even under natural situations. Rather than trying to isolate stimulus or task features, users of these approaches realize that features that co-occur in the real world are likely jointly represented in brain organizational principles [ 99 , 100 ].

Immersive Neuroscience

Based on the theoretical and empirical differences between reality and proxies, we propose a potential new direction in the cognitive sciences, an approach we call immersive neuroscience . The goal of immersive neuroscience is to push the field of experimental cognitive sciences closer to the real world using a combination of realism and, where realism is challenging or impossible, compelling simulations such as VR/AR. The approach resonates with historical advocacy for an ecological approach ([ 15 , 101 ] and reviewed in depth elsewhere [ 47 , 102 ]). However, the development of new technologies for studying brain and behavior in realistic contexts has dramatically improved in recent decades (see Box 3 ).

Box 3: The Potential of Simulated Realities in Research

Thus far we have presented empirical evidence that the realness of stimuli and tasks affects behavior and brain activation; one key question for moving forward is to determine which aspects of realness matter. Studies that use fully real stimuli are providing important new insights into perception, cognition and action. Nevertheless, studies that use real stimuli and tasks also present practical challenges that are not typically encountered when using images, such as the need to control or factor out potential confounds. Yet there are powerful arguments for moving away from approaches in which cognitive and neural processes are studied as if they are discrete de-contextualized events, but rather, as a continuous stream of sensory-cognitive-motor loops, reminiscent of how they unfold in naturalistic environments [ 81 ].

One emerging tool for both enhancing realism and testing the importance of components of realism is virtual reality (VR) and augmented reality (AR). There is growing enthusiasm for simulated realities (SR) in cognitive sciences because the technology enables a much more compelling experience for a user or research participant than conventional (typically computer-screen based) stimuli. VR/AR has the potential to optimize the trade-off between realism and control, though how well they evoke natural behavior and brain responses remains an open question and one that must be actively addressed (see Figure I ). That is, researchers should not take for granted that VR/AR is a perfect proxy for reality, particularly in light of current technical limitations. Some contend that, because VR and AR can compellingly place the observer egocentrically and actively in a scene, especially through self-generated motion parallax , they evoke a sense of presence and recruit the dorsal visual stream more than much more reduced simulations like 2-D images [ 128 ]. Others contend that present-day technology is limited in verisimilitude because it may not fully engage action systems without genuine interactions directly with the body (vs. handheld controllers without haptic feedback) and displays are limited (e.g., low spatiotemporal resolution, small field of view) [ 129 ]. Many of these limitations are under active development by technology firms and will likely improve dramatically in the near future. However, some features are hard to improve, particularly the vergence-accommodation conflict and the need for compelling, affordable haptics that do not require cumbersome cybergloves. Moreover, issues such as motion sickness may limit the utility of simulation and no matter how good the technology becomes, people may remain aware that even compelling environments are not real and thus lack complete presence.

We conceptualize the move toward realism as a continuum, with highly reduced stimuli (and tasks) on one end, fully real stimuli (and tasks) on the other, and gradations in between (see Figure 2 ). A typical assumption is that reduced stimuli provide high experimental control and convenience while sacrificing ecological validity; whereas, real-world stimuli provide the converse (but note that concepts like “ecological validity” and “real world” have been criticized as ill-defined and context dependent [ 103 ]). However, there are ways of optimizing both control/convenience and ecological validity through well-designed apparatus and protocols [ 104 ]. Although we have depicted ecological validity (and control/convenience) as a continuum, effects of stimulus richness may be monotonic but not necessarily gradual. That is, although gradual increases in stimulus realism could lead to gradual changes in behavior and brain responses, it is also plausible that there could be abrupt qualitative changes, for example between tangible solids and all simulations. Thus, although we are advocating for increasing realism, including better simulations like AR/VR, we view full reality as the empirical gold standard against which simulations should be assessed. Moreover, although we have depicted a continuum of realness according to visual richness, the relevant stimulus dimensions may turn out to be highly multidimensional and the dimensions may not be straightforward to define [ 100 ].

Different stimuli can be conceptualized as falling along a continuum of realness, from reduced or artificial (low in ecological validity, as shown in the lower left ), to fully real (high in ecological validity, as shown in the upper right ). Although ecological validity and control/convenience are thought to trade off, immersive neuroscience approaches can optimize both through well-designed apparatus and protocols. Answering questions about the importance of realness requires a fundamental shift away from the traditional “build-up” approach, in which cognition is studied by making reduced stimuli gradually more complex, to a “tear-down” approach, in which we start by studying responses to fully real stimuli and then gradually remove components. Although “tear-down” and “build-up” approaches may not always yield the same results, combining the two methods will permit a fuller understanding of the cognitive and brain mechanisms that support naturalistic vision and action. For example, the importance of stereopsis as a depth cue may differ between a build-up approach using random-dot stereograms [ 133 ] and a tear-down approach in which other depth cues (especially motion parallax) are available. A tear-down approach can reveal whether solids are processed qualitatively differently than artificial stimuli (represented by the distance between vertical dashed gray lines), in which case responses to real-world solids cannot be predicted by those to pictures or virtual stimuli. We postulate that the gap between artificial stimuli vs. real objects may be more quantitative or qualitative depending on the participants’ task and the brain area under study.

The immersive neuroscience approach is not intended to suggest that centuries of research using reductionist approaches are invalid, nor that all research necessitates realism. Reductionism is one essential approach in science and “starting simple” is especially important in the early years of new fields (such as neuroscience, little over a century old, and cognitive neuroscience, mere decades old). Moreover, research in the full-blown real world involves many technical challenges that can limit rapid progress [ 105 ]. That said, we promote an alternative to the reductionist or “build-up” approach of only using minimalist stimuli that become gradually combined to add complexity. The alternative is a “tear-down” approach in which we start with reality and remove components to see which matter ( Figure 2 ). Importantly, the “tear-down” approach is a complement, not a replacement, to the “build-up” approach. A third alternative is to relinquish the notion of experimentally dissecting behavior and brain processing at all, instead embracing the complexity of the natural environment in its own right [ 101 , 102 ]. The challenge remains that many current neuroscience techniques are not entirely “reality compatible”. For example, “bringing the real world into the MRI scanner” [ 53 ] introduces elaborate technical challenges. In such cases, the tear-down approach can determine whether heroic efforts to enhance realism are worthwhile or whether easier proxies (e.g., VR/AR) may suffice.

A comprehensive understanding of the cognitive sciences will likely benefit from the combination of approaches: building up, tearing down, and studying fully natural situations and environments. While controlled experiments are useful for testing hypotheses about the contributions of components (e.g., whether a component is necessary or sufficient), ecological experiments are useful for testing whether those hypotheses generalize to natural settings, and for generating new hypotheses that consider the complexities of the organism in its environment.

The use of reality and validated proxies also informs cutting-edge computational techniques, such as artificial neural networks [ 106 ] which can handle the messy complexities of the natural world, as does the brain itself [ 107 ]. As some have recently argued [ 102 ], a key factor in the success of modern neural networks is the utilization of large data sets sampled from “the real world”, including its inherent nonlinearities and interactions. This approach has proven far more successful than earlier approaches in artificial intelligence that sought sterilized and comprehendible algorithms based on limited input data. Nevertheless, artificial neural networks are often trained on data sets that lack potentially crucial aspects of realism. In vision science, for example, giant databases of static images [ 108 ] are used to train artificial neural networks and compare the “representations” to those in the brain [ 109 – 111 ]. While this approach has been enlightening, especially for ventral-stream perceptual processes, next-generation endeavors could benefit from incorporating 3-D depth structure [ 112 ], self-generated motion [ 113 ], embodiment [ 107 ], and active manipulation [ 114 , 115 ]. Such approaches could lead to artificial intelligence that learns in a manner akin to how human infants learn to comprehend and act within the real world through a series of transitions in their active experiences [ 25 , 116 ].

Concluding Remarks

We reviewed a growing body of literature that emphasizes (1) the theoretical arguments for why stimulus realism might matter for perception, cognition and action; (2) the feasibility of developing approaches, both real and virtual, for enhancing naturalism in research paradigms; (3) the evidence that realism affects multiple domains of cognition; (4) the factors that influence the real-object advantage, with actability seeming the most prevalent; and (5) a proposal for how an immersive neuroscience approach could operate and could benefit the field (see Outstanding Questions ). In experimental psychology and neuroscience, restricting the stimuli, the tasks and the processes that we investigate may limit our understanding of the integrated workings of sensory-cognitive-motor loops and our theoretical framework of human and animal cognition. Such limitations may hamper the development of real-world applications such as robotics [ 117 ] and brain-computer interfaces [ 118 ]. We argue that the importance of various components of realism is an empirical question, not merely a philosophical one. Reductionist and virtual proxies may prove appropriate for investigating cognition, but greater validation of these approaches in natural contexts would serve the community well.

Outstanding Questions

• How well do common stimuli (e.g., pictures) and tasks developed for cognitive neuroscience research evoke the same behaviors and neural processes as real-world situations? Are differences qualitative or merely quantitative?
• When differences between proxies and reality are found, what drives those differences (e.g., three-dimensionality, multisensory attributes/tangibility, actability, ability to fulfill goals, presence)?
• Given the long-history of the “build-up” approach (reductionism) in cognitive neuroscience, how can the “tear-down” approach be used to ask interesting new questions?
• How can simulated realities (VR/AR/game engines) be used to bring cognitive neuroscience closer to realism? How do these technologies need to improve to better simulate reality? How can we optimize the balance between experimental control and convenience vs. ecological validity in research? How can simulated realities be optimized for commercial, practical and clinical applications (e.g., image-guided surgery, VR training, rehabilitation)?
• How can cognitive neuroscience study not just natural stimuli and tasks but also the natural cognitive processes of the “freely behaving brain”?
• As the “real-world” comes to include more technology with simulated stimuli and interactions (e.g., smartphones, computers, VR), how does this affect behavior and brain processing?
• As artificial neural network approaches improve, how can they take advantage of the complexities of the natural world and the means by which organisms learn in the natural world?
• How can emerging technologies measure brain activation in humans with fewer constraints (e.g., functional near-infrared spectroscopy) and enable real-world neuroscience?

The flowchart illustrates a sequence to determine and optimize the validity of a proxy for reality.

Although commonly utilized in cognitive neuroscience, images evoke different behavior and brain processing compared to the real, tangible objects they aim to approximate. Differences have been found in perception, memory, and attention. One key factor in differences appears to be that only real objects can be acted upon.

Evolution and development are shaped by the real world. Shortfalls between proxies and reality are evident in other species and in young children, who have not learned to comprehend representations as human adults can.

New technologies and new experimental approaches provide the means to study cognitive neuroscience with a balance between experimental control and ecological validity.

In addition to the standard approach of “building up” ecologically valid stimuli from simpler components, a complementary approach is to use reality as the gold standard and “tear down” various components to infer their contributions to behavior and brain processes.

Acknowledgments

Support was received from National Eye Institute of the National Institutes of Health (NIH) (R01EY026701), the National Science Foundation (1632849), and the Clinical Translational Research Infrastructure Network (17-746Q-UNR-PG53-00) (to JCS), the Natural Sciences and Engineering Research Council of Canada, the Canadian Institutes of Health Research, and the New Frontiers in Research Fund (to JCC) and a Canada First Research Excellence Fund “BrainsCAN” grant (to Western University).

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• 00:00 Overview
• 00:52 Experimental Design
• 01:53 Running the Experiment
• 03:03 Representative Results
• 03:36 Applications
• 04:24 Summary

Realism in Experimentation

Source: Laboratories of Gary Lewandowski , Dave Strohmetz, and Natalie Ciarocco—Monmouth University

In an ideal world researchers would conduct their studies in real world settings where behaviors naturally happen. For example, if you want to see what influences individuals’ voting behavior, it would be best to watch them vote. However, research in these settings is not always ethical or even practical. Further, a researcher may want more control over the setting to better pinpoint the exact variables that are influencing an outcome. 

When researchers need to conduct studies in a lab, they try to optimize mundane realism, which means that they do everything they can to make the lab feel like a real-life experience. This video demonstrates a two-group design that examines how researchers use mundane realism in a lab to determine whether positive restaurant reviews are connected to diners’ level of tipping.

Psychological studies often use higher sample sizes than studies in other sciences. A large number of participants helps to ensure that the population under study is better represented and the margin of error accompanied by studying human behavior is sufficiently accounted for.

In this video, we demonstrate this experiment using just two participants, one for each condition. However, as represented in the results, we used a total of 200 (100 for each condition) participants to reach the experiment’s conclusions.

1. Define key variables.

• A positive review is one that gives a general rating of 4 stars (out of 5) or higher and also compliments the service.
• A negative review is one that gives a general rating of 2 stars (out of 5) or lower and also criticizes the service.
• For purposes of this experiment, tip amount is defined as the amount of money the participant allocates to the server in paying the bill.

2. Conduct the study.

• Dress and act like a restaurant server ( e.g. , wear white shirt and black apron, folded at waist).
•  Sit participant down at a table.
• Provide participant with informed consent, a brief description of the research (influences on spending behavior), a sense of the procedure, an indication of potential risks/benefits, the right of withdrawal at any time, and a manner to get help if they experience discomfort.
• Give participant a wallet containing $136.10 (3-$20, 4-$10, 5-$5, 10-$1, and $1.10 in coins).
• Say to participant: “Before you dine, to give you a bit more context, I thought you’d like to see the most recent online review of our restaurant.”
• Provide participant with the positive review ( Figure 1 ).

• Instruct the participant to imagine themselves as one of the diners in the video and to imagine that the researcher is the server in the video.

• Participant responds, “No thanks. Keep the change.”
• “Thank you for participating. In this study I was trying to determine if reading an online restaurant review influences how much a person tips. There were two conditions, both of which watched the same video of subpar service. However, one group read a positive online review, while the other read a negative online review. We hypothesized that the group who read the positive online review would be more forgiving of the subpar service and give a higher tip.”
• “We want to tell you why we ran this study this way. First, we couldn’t explicitly tell you that we were studying online reviews because it may have affected how you tipped. We also had to run this study in a laboratory setting because, as you can easily imagine, a real restaurant would not want to be part of a study involving subpar service where the key variable was their online reviews (particularly the negative ones).”

4. Conduct sections 2 and 3 with a new participant.

• Everything else should be the same.

5. Data Analysis

• Count the money the participant placed in the billfold.
• $55.00 in the positive condition = $10.33 tip
• $45.00 in the negative condition = $0.33 tip
• Positive = 23%
• Negative = 0.7%

Conducting research in a realistic setting is optimal, but unfortunately, is not always ethical or even practical.

For example, researchers cannot simply march into a voting booth and observe what factors influence individuals’ voting behaviors.

Instead, they can create realism in the laboratory by designing an authentic voting experience, which includes questioning and observing the exact variables that might influence the study’s outcome.

Using a realistic setting, this video will demonstrate how to design, conduct, analyze, and interpret an experiment that investigates whether restaurant reviews are related to a diner’s level of tipping.

In this experiment, a realistic restaurant setting is designed to allow the researcher to manipulate how restaurant reviews—positive and negative— influence participants’ dining behavior.

For the positive review group, participants are asked to read a critique that compliments the service. In contrast, the negative review group is asked to read a critique that condemns the service.

After reading one of the reviews, participants are then shown a video that depicts a dining scenario with subpar service and must imagine themselves as one of the diners and the researcher as the server.

Once the video is over, participants are given a bill for the imagined meal. The dependent variable is the amount of money left as a tip.

Thus, participants who read the positive review are hypothesized to be more forgiving of the subpar service and offer a higher tip than diners who read the negative review.

To begin the study, meet the participant at the lab door and welcome them into the Hawk Villa restaurant. Guide all participants through the consent process and discuss the overall plan for the session.

After the participant consents to the experiment, give them a wallet containing $136.10, divided into specific bill and coin amounts.

Randomly divide participants to one of two experimental groups by handing them either a positive or negative review.

When the participants finish reading the reviews, have them watch a video depicting a dining scene. Instruct the participants to imagine themselves as the diner and the researcher as the server.

After showing the video, return to the table with the bill.

Once the participant places money in the billfold, return to the table and ask if they need any change.

To conclude the experiment, debrief the participant and explain why simulating a restaurant in the lab was necessary for the experiment.

To analyze the data, first count the money each participant placed in the billfold. Subtract the bill total of $44.67 from the amount the participant left to calculate the tip amount. Then, calculate the tip percentage.

To visualize the data, graph the mean tip percentages by group. Notice that participants in the positive review condition tipped higher than those in the negative review condition.

Now that you are familiar with how to optimize realism within a laboratory environment, let’s take a look at how you can apply this approach to other forms of research.

Driving simulators are often used in the laboratory to safely investigate driving ability in individuals with visual deficits or those under the influence of a substance, such as alcohol.

In addition, researchers can study navigational skills in individuals by examining task performance in a simulated real-world environment.

Finally, researchers have adapted dance movements to engage patients who express poor mobility and balance, such as those with Parkinson’s disease, and subsequently monitored changes in motor performance.

You’ve just watched JoVE’s introduction to using realism in laboratory experiments. Now you should have a good understanding of how to design and conduct this type of study, and how to calculate results and apply the phenomenon conducting research using realistic settings.

Thanks for watching! 

Data were collected from 200 participants overall during a different instance of this study. This large number of participants helps to ensure that the results are reliable.  If this research were conducted using just two participants, it’s likely that the results would have been much different, and not reflective of the greater population. A t-test was performed for independent means comparing the positive review condition to the negative review condition to see how they influenced tip amount ( Figure 4 ).

Applications and Summary

Some tipping experiments can occur in actual restaurants. For example, Guéguen and Jacob studied how the color of a waitresses’ tee shirt influenced tipping. 1 To do this, servers at five restaurants wore red, blue, black, yellow, green, or white shirts. The results indicated that servers who wore red tee shirts received higher tips, but only when the customer was a male. In another study, Stohmetz et al. showed that customers who received candy with their bill tipped more than those who did not. 2

The use of mundane realism in research is particularly common when researchers want to study variables that cannot be easily manipulated for ethical or practical reasons.

Because it is often impractical to conduct experimental studies in casinos, gambling researchers commonly have participants come to a laboratory to gamble in a simulated setting. For example, researchers wanted to determine if gamblers’ beliefs in their own skill level or rituals influenced gambling behavior on a slot machine. 3 Their results indicated that perceived skills ( e.g. , a false sense of control) led participants to want to continue gambling following a near-miss; however, ritual beliefs ( e.g. , superstitions) did not influence desire to continue playing. 

• Guéguen, N., & Jacob, C. Clothing color and tipping: Gentlemen patrons give more tips to waitresses with red clothes. Journal of Hospitality & Tourism Research. 38 (2), 275-280. doi:10.1177/1096348012442546 (2014).
• Strohmetz, D. B., Rind, B., Fisher, R., & Lynn, M. Sweetening the till: The use of candy to increase restaurant tipping. Journal of Applied Social Psychology. , 32 (2), 300-309. doi:10.1111/j.1559-1816.2002.tb00216.x (2002).
• Billieux, J., Van der Linden, M., Khazaal, Y., Zullino, D., & Clark, L. Trait gambling cognitions predict near‐miss experiences and persistence in laboratory slot machine gambling. British Journal of Psychology. 103 (3), 412-427. doi:10.1111/j.2044-8295.2011.02083.x (2012).

For example, researchers cannot simply march into a voting booth and observe what factors influence individuals’ voting behaviors.

Instead, they can create realism in the laboratory by designing an authentic voting experience, which includes questioning and observing the exact variables that might influence the study’s outcome.

Using a realistic setting, this video will demonstrate how to design, conduct, analyze, and interpret an experiment that investigates whether restaurant reviews are related to a diner’s level of tipping.

In this experiment, a realistic restaurant setting is designed to allow the researcher to manipulate how restaurant reviews—positive and negative— influence participants’ dining behavior.

Now that you are familiar with how to optimize realism within a laboratory environment, let’s take a look at how you can apply this approach to other forms of research.

Finally, researchers have adapted dance movements to engage patients who express poor mobility and balance, such as those with Parkinson’s disease, and subsequently monitored changes in motor performance.

You’ve just watched JoVE’s introduction to using realism in laboratory experiments. Now you should have a good understanding of how to design and conduct this type of study, and how to calculate results and apply the phenomenon conducting research using realistic settings.

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• What Is Ecological Validity? | Definition & Examples

What Is Ecological Validity? | Definition & Examples

Published on September 9, 2022 by Kassiani Nikolopoulou . Revised on June 22, 2023.

Ecological validity measures how generalizable experimental findings are to the real world, such as situations or settings typical of everyday life. It is a subtype of external validity .

If a test has high ecological validity, it can be generalized to other real-life situations, while tests with low ecological validity cannot.

Using this approach, your findings would have low ecological validity. The experience of watching the video at home is vastly different from watching it on a plane.

Ecological validity is often applied in experimental studies of human behavior and cognition, such as in psychology and related fields.

Table of contents

What is ecological validity, assessing ecological validity, ecological validity vs. external validity, examples of ecological validity, limitations of ecological validity, other interesting articles, frequently asked questions.

Ecological validity assesses the validity of a study’s findings based on the environment or setting in which the study took place. If you have reason to suspect that the study’s environment may have influenced the generalizability of its results or led to research bias , the study’s ecological validity may be questioned.

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To assess the ecological validity of a study, you must critically examine the setting where it took place. It’s not as cut-and-dried as “the experiment took place in a lab, therefore it lacks ecological validity.” Rather, it’s more about pointing out what can prevent results from one environment or setting from being successfully applied to another.

The following questions can help you assess ecological validity:

• What environment is the study taking place in?
• To what other environment(s) are you trying to apply these conclusions?
• How are these two different, or similar?

It’s important to keep in mind that research studies conducted in a lab setting don’t necessarily lack ecological validity. And generalizability does not depend on ecological validity alone—you need to consider other factors, too, such as population validity .

External validity examines whether study findings can be generalized beyond the sample. In other words, it analyzes whether you can apply what you’ve found in your study to other populations , situations, or variables .

On the other hand, ecological validity examines, specifically, whether the study findings can be generalized to real-life settings. Ecological validity is a subtype of external validity.

To assess external validity, you need to ask whether the findings can be generalized to patients with characteristics that are different from those in the study in some way. This could mean patients who are treated in a different way, or patients who have longer-term follow-ups.

Measuring ecological validity shows you to what degree results obtained from research or experiments are representative of conditions in the real world. Here are a few examples.

• Walk in the rain to get to their destination, an auditorium in an adjacent building
• Walk inside, but for a much greater distance, to get to the same auditorium

Your findings show that 83% of the participants would choose to walk a shorter distance in the rain.

You can argue that your study findings can be generalized to the real world for two reasons:

• The setting in which your test took place is an everyday setting, a campus.
• The dilemma you presented participants with can easily occur in everyday life.

Now, you can feel confident in generalizing what most people in a similar situation would do. In this case, they would likely prefer to walk through the rain in order to reach their destination faster, rather than taking a longer route and staying dry.

When results obtained from research or (controlled) experiments are not representative of conditions in the real world, the study findings are characterized by low ecological validity.

After a few weeks, you observe the same players in a natural setting. Your results show that the players have more or less the same number of verbal outbursts in both settings. However, they are more willing to take monetary risks in the lab. Given that the players were aware that they were participating in an experiment, and there was no real money involved, this is not a surprising outcome.

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Ecological validity has a few limitations to be aware of.

Laboratory environments

Often, research studies in fields like psychology are conducted in laboratories, with the goal of better understanding human behavior. Ideally, an experiment like this will produce generalizable results—meaning that it predicts behavior outside the laboratory. If so, the study shows evidence of ecological validity.

However, laboratories are controlled environments. Distractions are minimized so that study participants can focus on the task at hand, clear instructions are provided, and researchers ensure that equipment works. Additionally, lab experiments risk having demand characteristics , or cues that point to the study’s objectives . These cues may lead participants to alter their behavior.

As these are all conditions that are usually not present in real life, they may compromise the study’s ecological validity.

Lack of standard measurements

There is no consensus about a standard definition of ecological validity; in fact, multiple definitions exist. As a result, there are no agreed-upon standards for measuring ecological validity. This leads some researchers to question the usefulness of ecological validity, arguing that being specific about what behavior or context you are testing is sufficient to mitigate research bias .

Before addressing ecological validity in your dissertation or research paper , it is important to find out how your teacher, department, or field of study defines it.

Tradeoff with internal validity

As mentioned above, controlled laboratory environments are not always a good fit for high ecological validity. However, controlled environments are better for establishing the cause-and-effect relationships needed for high internal validity , where it’s ideal for circumstances to be as identical as possible.

This can lead to a bit of a tradeoff between the almost-unnatural setting needed to assess internal validity and the approximation of real life needed to assess ecological validity. While a natural environment yields high ecological validity, it comes with the risk of more external factors influencing the relationship between different types of variables , leading to low internal validity.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

The purpose of theory-testing mode is to find evidence in order to disprove, refine, or support a theory. As such, generalizability is not the aim of theory-testing mode.

Due to this, the priority of researchers in theory-testing mode is to eliminate alternative causes for relationships between variables . In other words, they prioritize internal validity over external validity , including ecological validity .

Reliability and validity are both about how well a method measures something:

• Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
• Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

I nternal validity is the degree of confidence that the causal relationship you are testing is not influenced by other factors or variables .

External validity is the extent to which your results can be generalized to other contexts.

The validity of your experiment depends on your experimental design .

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It is not real until it feels real: Testing a new method for simulation of eyewitness experience with virtual reality technology and equipment

• Open access
• Published: 28 July 2023
• Volume 56 , pages 4336–4350, ( 2024 )

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• Kaja Glomb   ORCID: orcid.org/0000-0001-5083-0385 1 ,
• Przemysław Piotrowski   ORCID: orcid.org/0000-0002-3163-3228 1 &
• Izabela Anna Romanowska   ORCID: orcid.org/0000-0002-9487-2111 2  

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Laboratory research in the psychology of witness testimony is often criticized for its lack of ecological validity, including the use of unrealistic artificial stimuli to test memory performance. The purpose of our study is to present a method that can provide an intermediary between laboratory research and field studies or naturalistic experiments that are difficult to control and administer. It uses Video-360° technology and virtual reality (VR) equipment, which cuts subjects off from external stimuli and gives them control over the visual field. This can potentially increase the realism of the eyewitness's experience. To test the method, we conducted an experiment comparing the immersion effect, emotional response, and memory performance between subjects who watched a video presenting a mock crime on a head-mounted display (VR goggles; n  = 57) and a screen ( n  = 50). The results suggest that, compared to those who watched the video on a screen, the VR group had a deeper sense of immersion, that is, of being part of the scene presented. At the same time, they were not distracted or cognitively overloaded by the more complex virtual environment, and remembered just as much detail about the crime as those viewing it on the screen. Additionally, we noted significant differences between subjects in ratings of emotions felt during the video. This may suggest that the two formats evoke different types of discrete emotions. Overall, the results confirm the usefulness of the proposed method in witness research.

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Introduction

For many decades, forensic experts have drawn attention to the limited possibility of reaching inferences about the real experiences of eyewitnesses based on the results obtained in laboratory studies. One of the most fundamental issues is the lack of ecological validity of such experiments (Chae, 2010 ; McKenna et al., 1992 ; Wagstaff et al., 2003 ; Yuille & Wells, 1991 ). During laboratory experiments, stimulus manipulation does not evoke states that mimic the experiences of real eyewitnesses. Participants who stay in a safe space are rarely surprised by stimuli, and do not confront unexpected events. Therefore, it is possible that their reactions to short films, slides, narratives, or recordings presenting a crime are the product of rational thought rather than instinctive responses. Thus, there is no shortage of voices in the literature encouraging more field research and analysis based on real crime cases (e.g., Yuille, 2013 ). This type of study, however, has its own challenges related to the limited ability to control for confounding variables and the need to rigorously repeat the procedure in situ, which is more complex and unpredictable (Grzyb & Doliński, 2021 ). Moreover, this type of research is demanding to organize and administer, which, with the heavy emphasis on increasing the sample size in psychological studies, can make it time-consuming and cumbersome (Doliński, 2018 ). As a result, the contribution of field or naturalistic experiments is very limited. In preparing this paper, we analyzed 1400 publications indexed in Google Scholar (search term: eyewitness testimony 'field study'), examining the abstracts of empirical articles and the method sections. We found that the vast majority of them are in one area of interest: the effects of alcohol and other psychoactive substances on witness memory. This may suggest that, for most psychologists, field experiments are a last resort, used essentially only when a safer, better-controlled laboratory alternative is not available.

With this in mind, the purpose of this study is to test a method that employs elements of virtual reality (VR) and its equipment for experimental manipulation. We believe that this procedure could provide an intermediate point between laboratory research and naturalistic or field experiments, as it allows exposure to more realistic stimuli. Empirical research in eyewitness testimony research already makes use of VR and Video-360° display equipment—for example, Kloft et al. ( 2020 ) in their study on false memory used virtual reality equipment and digital imagery. They simulated two criminal events in which the subjects played the role of an uninvolved witness of a physical attack on a policeman, or a perpetrator of theft in a bar. The scene was created with digitally generated graphics; thus the perpetrator, victims, and bystanders resembled game avatars. As we are not aware whether fully digital characters have the capacity to imitate humans in a way to produce effects similar to the experience of watching a real person being harmed, this type of manipulation will not necessarily be adequate for the study of emotions and phenomena typical of social situations. After all, as we know from the game research, one of the leading factors in determining how believable a so-called NPC (non-playable character) is depends on perceptual cues (e.g., Warpefelt, 2016 )—thus, characters that look, move, express emotions, and behave unnaturally may not evoke similar psychological reactions as humans.

At this stage of the use of VR in eyewitness testimony research, however, the main obstacle is not so much the potential inadequacy of the stimuli, but rather a lack of methodological analysis of its effectiveness in inducing desired psychological states. Controlling for realism with few questions about the "realness" of the environment (e.g., Romeo et al., 2019 ), while important, does not allow us to fully determine the extent of immersion in the stimulus, and therefore subjects' engagement with the virtual world. Nor does it provide a way to identify these aspects of the method that can compete with more traditional research methods used in the psychology of witness testimony. We, therefore, decided to conduct a systematic study focused on VR, which appears to be essential to understanding the psychological states evoked by this medium. Our aim was to investigate the capability offered by virtual reality technology with respect not only to the realism of the experience but also to its potential consequences in terms of emotions and cognition.

To the best of our knowledge, this paper presents the results of the first methodological analysis of the potential of VR in eyewitness testimony research. Our study is set firmly in this field. While we do not ignore the body of work which demonstrates the capability of virtual reality to evoke emotions and arousal (e.g., Hofmann et al., 2021 , who studied the subjective emotions and cortical α activity evoked by riding a rollercoaster in VR) or a sense of presence (e.g., Barreda-Ángeles et al., 2021 , who used a design similar to ours while investigating journalistic pieces in terms of immersion and cognitive processing ), we believe that, with such a specific medium and research subject, it is essential to ensure that the particular context is addressed. For, as Yuille and Wells ( 1991 ) argue, in order for psychological lab research to be generalizable to real-life situations and to serve, for example, expert witnesses, it is essential to consider the contextual equivalence of the real eyewitness experience and the study. In our view, press materials and rollercoaster rides do not reflect this context; thus, our ability to infer the utility of VR in the paradigm of witness testimony is limited.

Crucial limitations of laboratory experiments in eyewitness testimony

The discussion regarding the generalizability of laboratory research on memory has been ongoing for many decades, and any attempt to summarize it deserves a separate article. No less intense is the debate over the validity of laboratory research on eyewitness testimony—for some experts the overreliance primarily on laboratory studies is the reason for the deficient recognition of many psychological phenomena in the forensic field. An extreme position has been presented by Yuille ( 2013 ), who argues that the context of the laboratory is so different from the context of many crimes, particularly violent crimes, that using the lab to study memory in the forensic context is pointless (p. 9).

One key criticism of laboratory research on eyewitness testimony is that it often uses highly controlled and artificial stimuli, such as photographs or videos of staged events, rather than live events. These stimuli hardly apply to real situations, where witnesses often encounter more complex and dynamic stimuli for which they are not prepared. Processing of stimuli that are simplified or highly focused on a specific aspect of reality appears to be less prone to the distortions present with the high demands that crime observation places on the witness's real-life experience, even when their level of involvement is minimal. As a result, one can expect findings from lab-based research that suggest better witness memory performance than may be the case with higher distraction (Lane, 2006 ).

Other important aspects relate to the inability to simulate a sense of threat and fear in the lab, and the consequences (or lack thereof) that lab eyewitnesses suffer for making mistakes. However, from the point of view of this paper, the critique concerning the conditions for processing and encoding information is crucial—it is this lack of the naturalness of the stimulus that we are addressing with this research. With this in mind, the goal of our research was to verify an experimental method using VR elements to simulate the experience of an eyewitness. We believe that this method may overcome the limitations of typical witness testimony research, and has the potential to create a stimulus-rich, close-to-real experience, while maintaining high control and replicability of the procedure.

How can virtual reality help experimental psychologists?

The definition of virtual reality is a subject of debate among experts, who do not always agree on the criteria that constitute VR. Since covering the discussion of this topic is beyond the scope of this paper, we focus solely on the criteria that justify the choice of this medium for psychological research. They relate primarily to the capacity users have in this environment and the degree of influence they have on it. Many experts would agree to use the term virtual reality only if the user has the ability to move, interfere, and change certain elements of that environment (Kardong-Edgren et al., 2019 ). For the purposes of this study, however, we adopted a less rigorous criterion: virtual reality is a digital space in which the user's movements are tracked, and their environment is continuously rendered and displayed according to those movements. Its purpose is to replace the signals coming from the real environment with digital ones (Fox et al., 2009 ). Therefore, a medium that adapts to the user's point of view and cuts off their access to real existing stimuli can be considered to be virtual reality.

These criteria are met by Video-360° (also called spherical video). Although the ability to influence the environment is limited to changing the field of view, the realism of this medium gives it an undeniable advantage over the strictly digital environment for psychological research. Video-360° uses recordings of real people in a real space. Therefore, researchers need not fear the effects that are present when it comes to realistic computer-generated characters (e.g., uncanny valley; Tinwell et al., 2011 ).

Some definitions of VR also focus not so much on the technology itself but place the user and their experience at the center. For example, as highlighted by Jerald ( 2015 , p. 45): VR is about psychologically being in a place different from where one is physically located, where that place may be a replica of the real world or may be an imaginary world that does not exist and could never exist . This definition refers, not explicitly, to psychological phenomena reflecting a sense of presence, transportation, or immersion in a particular medium. They define the state of being absorbed by the environment, a sense of being part of it, and experiencing it (Rigby et al., 2019 ). These are related terms, but their meanings vary among those in the broad field of human-computer or human-media interactions. In this paper, we have chosen to use the term immersion primarily to ensure consistency between theoretical terms and research methods. It is crucial to underline that the immersion effect is, in our view, an index of the simulation's realism, and this is the focal point of this study, as by realism we consider not so much the accuracy of the reflection of some fragment of reality, but realism of the user's subjective experience. Similarly to Steuer et al. ( 1995 ), we believe that a sense of immersion can enhance the overall viewing experience, making it feel more real and lifelike. As a result, we can expect psychological states and behaviors similar to real life, as the medium is capable of invoking the illusions of place (a sensation of being in a real place) and plausibility (the illusion that the scenario being depicted is actually occurring) (Slater, 2009 ).

These main criteria—the ability for the users to change their point of view, isolation from external stimuli, and the capacity for immersion effect—are components of the simulation which better imitate the real-life experience of an eyewitness. However, these are not the only benefits of using VR in experimental procedures. It also automates the procedure so that it is consistent and not affected by external unexpected events (compared to staged crime). More complex systems also offer performance recording, which provides insight into what the subject is doing in this environment, e.g., via eye tracking. Thus, increased realism does not come at the expense of the rigor of the procedure or control of the experiment.

Current study: Variables and hypotheses

Taking into account the nature of witness testimony research and, above all, the need to increase the ecological validity of the research while maintaining the rigor of the experimental procedure, we formulated the following hypotheses.

Our main dependent variable is immersion—an effect that can be described as being absorbed by a given medium (a game, a movie, or even a book). Thus, in this research, immersion is considered an operationalized realism of the experience. We expect that [H1] video watched on head-mounted displays (HMDs) creates a stronger immersion effect into the scene than a video watched on screen. The verification of this hypothesis is crucial for this study. If the participants have a higher sense of being present in the created scene and have the impression that they are in the space in which a crime is taking place, we would consider that the simulation has fulfilled its primary role, which is to increase the realism of simulation of the experience typical of an eyewitness. In addition to the main effect, we also expect differences in one of the subscale—Transportation. This subscale reflects a psychological state in which the distance between the observer and the scene is shortened, resulting in an observer feeling as if they are part of the events being presented. Achieving such a state seems to fulfill the previously mentioned definition of VR proposed by Jerald ( 2015 ), outlining a psychological "transfer" to a created reality.

A secondary issue with increased immersion relates to the consequences of this effect. As our objective was to develop a stimulus manipulation suitable for eyewitness testimony research, we assumed [H2] that subjects who watched the scene on HMD would feel stronger emotions than those who watched the same video on a screen. In particular, we expected higher negative emotions ratings accompanied by higher arousal. Therefore, we expected that our experiment would be in line with other studies suggesting an increased emotional response and arousal in VR (see, e.g., Estupiñán et al., 2013 ; Tian et al., 2021 ).

Due to the stimulus-rich environment, playing videos on head-mounted displays can also have negative consequences in terms of distraction and difficulty focusing on the scene presented. One of the challenges of creating any narrative in Video-360° format is to attract and direct attention to the focal actions, as the VR viewer has a much larger field of vision to explore (Dooley, 2017 ). As a result, participants in the experiment may ignore the events that are presented and focus on something completely different. Another problem related to immersive media such as VR is visual fatigue and cognitive overload, which can lead to impairment of certain cognitive functions (Frederiksen et al., 2020 ; Souchet et al., 2022a ; for a review, see: Souchet et al., 2022b ). In fact, there are some empirical studies suggesting the existence of this effect, although the material presented was much different from the one we prepared for this research (Barreda-Ángeles et al., 2021 ).

It is therefore necessary to examine whether attention processes—and the resulting memory processes—are in any way impaired in this stimuli-reach environment. As the purpose of the study was to test an experimental method suitable for research in eyewitness testimony, we chose long-term (episodic) memory as a measure of cognitive functioning. This type of memory is the main focus of research in this area. The theoretical and empirical rationale behind investigating the relationship between attentional processes and long-term memory is substantial. Prominent concepts in information processing recognize attention, working memory, and long-term memory as interconnected systems (for example, the embedded-process model proposed by Cowan, 1995 , 1999 ). Additionally, neuroscientific research provides evidence supporting the interaction between attention and long-term memory (for a review, see Chun & Turk-Browne, 2007 ). Hence, we set out to explore potential differences in event recollection. If the proposed simulation proved itself to be a valid research method, [H3] we would expect similar memory functioning in both groups.

Materials and method

Participants.

A total of 115 subjects participated in the study (female = 76). Ultimately, due to incomplete questionnaires and device or recording malfunctions, 107 subjects (M age  = 22.18; SD age  = 2.74) were eligible for the final analysis. The experimental group (VR equipment) included 57 subjects (female = 38), while the control group (flat screen) included 50 subjects (female = 35). The groups did not differ in terms of age ( t (104 Footnote 1 ) = .422; p  = .674). As compensation for participation in the study, subjects were offered a 15-minute VR gaming session and an individual personality profile.

Materials and apparatus

Experimental manipulation.

The video presenting a staged criminal incident prepared for the experiment was shot using Video-360° technology, which allows the full perceptual field to be observed. It lasts about three minutes and presents a scene in a pub with an outdoor garden. The criminal incident involves two perpetrators, male and female. They rob a girl who is sitting next to them. To carry out the theft, the male perpetrator turns to the victim and asks her for directions; at the same time, the female perpetrator approaches the table, takes a tablet and a wallet, and walks away from the scene. When the girl realizes that her belongings have been stolen and tries to run after the female perpetrator, the male stops her by pushing her onto a chair and knocking the rest of the items off the table.

Video display equipment

We used an HP Omen laptop computer with a 15″ diagonal screen and HP Reverbs G1 goggles (head-mounted device). We used the HMD in the experimental conditions, and a computer screen in the control group. In the experimental condition, subjects were able to view the full perceptual field, covering 360 degrees, while the subjects watching the movie on the screen viewed a slice of that scene, covering the central visual field, which was adapted to the flat screen. A comparison of the image observed by subjects in both groups is presented in Fig. 1 .

Comparison of perceptual fields accessible to subjects under two conditions. At the top is a 360-degree view as seen in HMD; the bottom screen shows the scene on a 2D screen.

Post-event emotional ratings

The Geneva Emotion Wheel (GEW; Sacharin et al., 2012 ) was used to determine the valence and intensity of emotions experienced by participants while watching the film. This is a self-report measure consisting of discrete emotion labels corresponding to emotion domains that are arranged in a circle. The alignment of emotion terms is fundamental to the two-dimensional (2D) values (negative to positive) and control (low to high). The response options correspond to different levels of intensity for each emotion family, from low intensity (1) to high intensity (5). Subjects can also indicate that they did not feel a particular emotion (0), and they can independently label the name of the emotion they experienced.

Psychophysiological measurements

To assess arousal, we measured electrodermal activity (EDA). A wireless Shimmer3 GSR+ unit (worn as a wristband on the nondominant hand) and two EDA diodes were used. The unit was calibrated with a sampling rate frequency of 512 Hz. Subjects were asked to take a comfortable position, place their forearms on the desk, and attempt to minimize hand movement while watching the video. Preprocessing and further data analysis were performed in Python using a pyEDA (Hossein Aqajari et al., 2021 ).

Immersion assessment

To measure immersion in videos, we used the Immersive Experience Questionnaire for Film and TV (Film IEQ) developed by Rigby et al. ( 2019 ). The questionnaire was translated into Polish. It consists of 24 items and four factors: Captivation, real-world Dissociation, Comprehension, Transportation. The overall result of the questionnaire determines the strength of the immersion effect. Participants were asked to indicate on a seven-point scale how much they agreed with the statement.

Post-event memory performance

In this study, we analyzed episodic memory in delay condition and free recall procedure. For the purpose of the study, we created an index including the number of correctly remembered details about the event. The list of data that were considered includes information on the course of the event and the look and behavior of the perpetrators. It was developed by two competent judges who were unrelated to the project and not involved in the psychology of witness testimony. They were asked to watch a video (in the 2D variant) and then, immediately after watching it, to record all the information about the scene and the appearance and behavior of the people they watched. Based on the two lists we received, we created one covering all the noticeable details. We treated every detail as bits of information, which we then scored (if the information was given) in the subjects' responses. The maximum the subjects could report was 83 bits of information.

Due to differences between the videos in the size of the perceptual field, we only included information common to both conditions in the analysis.

The experiment was conducted in a between-subjects design. Subjects were randomly assigned to the experimental or control condition at the time of enrollment. The conditions differed in the type of equipment used to display the video. In the experimental conditions, subjects watched a 360-degree video played on head-mounted displays; in the control conditions, we used the traditional method of playing the video, i.e., on a flat screen.

Due to the health concerns of the subjects and the resulting sanitary rigor, the experiment was conducted in individual sessions. The whole procedure took about 1 h (+ c. 15–20 min for the game session offered as compensation). It included the following steps:

Preparation and baseline measurement (relaxing video) of electrodermal activity.

Exposure to stimulus (HMD versus flat screen) and electrodermal activity measurement.

Emotion self-report. Immediately after watching the video, subjects were asked to rate the intensity of emotions they felt while watching the video. We wanted to measure them soon after the film ended, so that the emotions would still be vivid and could be evaluated easily.

Immersion measurement (self-report).

Filler task designed to delay the memory testing, allowing us to study long-term memory rather than working memory. The participants completed questionnaires, the results of which will not be reported here.

Free recall memory task. Respondents were asked three questions: (1) Tell all you remember about the scene in a pub that you just watched, both about how the scene unfolded and about the people who participated in it . (2) Do you remember anything about the appearance of the main characters ? (3) Is that all you remember about the film? The task format, i.e., including three questions, was developed after the pilot study which showed that subjects, when asked to describe "everything they remember," were limited to a very schematic and brief description of the events. As very short description do not allow for a reliable comparative analysis, we decided to expand the task and ask three questions. As our study is concerned with eyewitness testimony, the question about the perpetrators' look was crucial (this type of information is often collected by investigators to identify the perpetrators.). We also added a third question in case that a subject remembered something about the perpetrators' behavior after recalling their appearance. Subject responses were recorded using a voice recorder. The recordings were then transcribed and coded to be analyzed in terms of the amount of information provided. The time interval between the encoding memory and recollection was set at 25 min.

The procedure was positively reviewed and approved by the Research Ethics Committee at the Institute of Applied Psychology at the Jagiellonian University before its application (decision number 56/2019 dated 25 November 2019).

For statistical analysis, we used PS Imago (IBM SPSS Statistics 28), JASP 0.16.4.0, and Python 3.10. The default software was SPSS; thus, we only specify when the analyses were performed with different tools.

Hypothesis 1. Videos watched on HMD are more immersive than those watched on screen

Our main objective was to verify the hypothesis of deeper immersion of a video viewed on HMD. To examine this, we used Film IEQ to measure the overall immersion effect and its components. We were most interested in the main effect, but we also expected to see a difference in terms of Transportation. The results of the subjects’ ratings and between-subjects comparison are presented in Table 1 .

A comparison made using a one-tailed (given the directional hypothesis) t -test for independent samples showed that participants who watched the video on HMD rated immersion ( t (105) = 2.756; p  = .003; d  = .534) and its two components, Captivation ( t (105) = 2.963; p  = .002; d  = .574) and Transportation, higher ( t (105) = 1.963; p  = .026; d  = .380). Ratings for the two other factors, namely Comprehension ( t (105) = –.553; p  = .291) and Dissociation ( t (105) = .132; p  = .189), did not differ between conditions. Given that we primarily expected a significant difference in the main effect, we consider Hypothesis 1 to be confirmed.

Hypothesis 2. Video watched on HMD evokes stronger emotions and higher arousal

Our second hypothesis relates to the potential consequences of the immersion effect, i.e., stronger emotional responses. In this experiment, we examined subjects’ rates of emotions in terms of their intensity and valence, as well as psychophysiological arousal. The first two aspects were examined using self-reports (GEW), while arousal was operationalized as electrodermal activity (EDA).

Post-event emotional self-ratings

To answer the question of whether video played on HMD evokes stronger emotions than video played on a screen, we analyzed the answers that subjects gave in the GEW. We first analyzed all discrete emotion labels and compared them between conditions (Table 2 ). The analysis indicates that the only emotion that the subjects in the experimental group (VR) rated higher was guilt ( t (79.53*) = 2.753; p  = .004; d  = .520; one-tailed significance). Moreover, contrary to our directional hypothesis, participants who watched the video on the screen rated hate ( t (89.69*) = –2.368; p  = .010; d  = .455) and anger t (104.97*) = –2.928; p  = .002; d  = .562) higher. These emotions, rather than fear, are expected after watching a criminal incident (theft and assault), as the subjects were not at risk of any harm.

In the second step, we created general indices of domains of emotions, in line with the theoretical background of the method (Scherer, 2005 ). Each indicator is an averaged rating of an emotion belonging to one of the quarters of the GEW (negative valence, low control; negative valence, high control; positive valence, low control; positive valence, high control). As can be seen in Table 3 , there is a significant (one-tailed) difference ( t (105)  =  –1.762; p  = .040; d  = .349) between conditions with respect to the ratings of emotions with negative valence and high control. This is a consequence of higher ratings for anger and hate that comprise this domain. However, significantly, the result is opposite to the one we assumed.

We began the EDA analysis by checking the data for any recording errors or artifacts that might strongly distort the measurement. As we did not identify such records, we performed the analysis using the calculation method proposed by Hossein Aqajari et al. ( 2021 ). First, we examined the mean level of electrodermal activity recorded when subjects watched the video. This allowed us to determine the overall arousal induced by the medium. Figure 2 presents the filtered electrodermal activity. To eliminate individual differences in perspiration, we compared the measurements recorded during the crime video with baseline measurements recorded during the preparation for the experiment. We compared two segments lasting 165 seconds, omitting the first seconds of the video because of the potential novelty effect that may cause arousal.

Filtered electrodermal response recorded while watching the video. Between-subjects comparison

Table 4 presents the results of our analysis (“mean activity”). Although we were unable to obtain a significant difference ( t (105) = 1.553; p  = .062) between the conditions in the one-tailed test (owing to the directional hypothesis assuming higher arousal in the experimental condition), we can describe these results as on the verge of significance.

The second step of our analysis was to compare only the end of the video—that is, the several seconds (18 s) during which the crime occurred. This is because we wanted to isolate the arousal caused by the crime stimulus itself, not the entire video. The results are presented in Table 4 (“max. peak”). To verify the hypothesis of stronger arousal experienced when the crime itself was observed on the HMD rather than on the screen, we compared the maximum amplitude peak between conditions. Once again, we observed close to significance in a one-tailed t -test ( t (91.98) = 1.529; p  = .065). To summarize the analyses performed to verify Hypothesis 2, we can cautiously conclude that subjects under the experimental conditions were more aroused than those in the control group. At the same time, they generally rated negative emotions with high control lower than those who watched the film on the screen. However, they felt stronger guilt than the subjects in the control condition. Thus, we consider these results to be inconclusive.

Hypothesis 3. Video displayed in VR HMD is not more distracting than video played on screen

We considered post-event memory performance as a measure of distraction. We assumed that distraction would be indicated by a lower number of correctly reported pieces of information about the crime scene. Thus, to compare recollection between conditions, we used an index covering the number of details accurately remembered by the subjects. Table 5 presents the results. The t -test revealed that the conditions do not differ in the number of correctly remembered details ( t (105) = .073; p  = .942). However, as our hypothesis stated that there are no differences in recollection, we also decided to use Bayesian statistics and to apply the Bayes factor (BF) in the interpretation. BF is interpreted as the ratio of the probability of obtaining given observations in two comparable models (null hypothesis and alternative hypothesis; Masson, 2011 ). We performed the analysis in JASP and adopted the interpretation of the factor according to Andraszewicz et al. ( 2015 ): BF1–3 = anecdotal evidence for the null hypothesis; BF3–10 = moderate evidence for the null hypothesis; BF10–30 = strong evidence for the null hypothesis. The Bayesian independent t -test shows that there is moderate evidence for H0 (that is, there is no difference in terms of the number of correctly recalled bits of information about the event, BF 01  = 4.866).

In addition, to investigate more subtle aspects of recollection, we also analyzed misreports. We took into account both types of errors: (1) distortions , which are all bits of information that involve details that were present in the video but were incorrectly reported (e.g., incorrect color of pants, misremembered behavior), and (2) additions , which are all the bits of information that were absent in the video but were reported by subjects. As can be seen in Table 6 , the mean number of both types of errors, but also their overall value (Σ distortions + additions), is similar in VR and Screen conditions. Between-subjects comparison also showed no statistical difference in the number of errors; however, in the case of distortions there is only anecdotal evidence for the null hypothesis (BF 01  = 2.46). Finally, we decided to investigate the overall accuracy of recollection and compare the rates between conditions. We define recollection rate after Evans and Fisher ( 2011 ) as the number of accurately provided details (see Table 5 ) of the event / Σ accurate + errors (see Table 6 ). The rates, as shown in Table 7 , are almost identical for both conditions, and between-subject comparison indicates that there are no differences in terms of the accuracy of the recall ( t (105) = .127; p  = .899). The Bayesian t -test provides moderate evidence for the null hypothesis (BF = 4.84). Considering all the above analyses performed for Hypothesis 3, we conclude that it has been confirmed.

In the experiment ( N  = 107) in which we compared two types of video display devices (head-mounted device and flat screen), and thus two formats of video recording (Video-360° and 2D video), we obtained results suggesting that our proposed method may be a more realistic alternative to traditional stimulus manipulations using videos. We infer the higher realism of the subjects' experiences primarily based on the difference in terms of immersion effect evoked during stimuli manipulation. We observed higher rates of immersion and its two factors (Captivation and Transportation) among people who watched the video on HMD; thus, we believe that this medium offers researchers the potential to elicit in subjects a sense of being highly engrossed in a mediated experience. Our results suggest that the VR group felt more involved in the video and were more motivated to watch it (Captivation). Furthermore, there are some arguments in favor of the notion that, while watching a criminal incident on HMD, subjects felt like they were experiencing events for themselves and were located in the world portrayed in the video (Transportation). These differences between conditions indicate that the proposed method increases the realism of the experience and shortens the distance between the observer and the scene.

The results of our study can be related to the concept of two different types of realism in laboratory research introduced by Aronson and Carlsmith ( 1968 ) and developed by Wilson et al. ( 2010 ). The researchers proposed to assess lab research in terms of experimental and mundane realism. The first one implies subjects’ involvement in the situation created in the laboratory and the authentic experiences evoked during the task, while the latter is defined as the similarity of the experimental situation to events that might happen in real life. The results of our study support the argument that VR may enhance both types of realism. On the one hand, subjects in the VR group were more engaged in the experiment, as evidenced by higher scores in Captivation; on the other hand, they felt as if they were part of the crime event (Transportation), which appears to satisfy the definition of mundane realism. Therefore, we believe that studies that use VR for stimulus presentation seem to be less burdened by the accusation that is made against traditional laboratory research in eyewitness testimony, which points to the “artificiality” of experimental manipulation.

In contrast to immersion, we obtained inconclusive results when comparing subjects' emotional responses between conditions. On the one hand, we can argue (with some caution) that subjects in the experimental conditions were slightly more aroused than those in the control conditions, although the results are only on the cusp of significance in one-sided tests. To evaluate the level of uncertainty associated with the results, we conducted additional analyses in which we used bootstrapping simulation. Their results (see Appendix—Supplementary Analysis B ) provide additional support for the notion that the subjects' arousal was higher while watching the crime scene in VR than on the screen. First, parametric bootstrapping (resampling 10,000 times) demonstrated a significant difference between the conditions in terms of the change in arousal between the baseline measurement and the arousal experienced during the viewing offense. Secondly, the permutation test showed that although the maximum arousal registered during the last scene (the actual crime) was comparable, this finding is only true for low and medium amplitudes. For the most responsive subjects, the crime scene viewed in VR was significantly more arousing than the scene presented on the screen. These results suggest that experimental manipulation in VR may be recommended in particular for a strong emotional stimulus and/or a population with a low arousal threshold. Our study thus indirectly supports the finding of Slater et al. ( 2006 ), who showed a significant increase in arousal in an anxiety situation experienced in VR in phobic-sensitive subjects.

On the other hand, we obtained rather surprising results in ratings of the intensity of discrete emotions. They indicate stronger anger and hate felt by the subjects in the control conditions and more intense guilt felt by those in the experimental group.

First, it is necessary to address the discrepancy between the two measurements of the components of emotion (subjective feeling and psychophysiological measurement). This inconsistency is explainable theoretically, and parallels in other empirical studies can be pointed out (e.g., Mauss et al., 2004 ; Chivers et al., 2010 ; Ciuk et al., 2015 ). People struggle to identify and evaluate the intensity of emotions for various reasons. Labeling a specific emotion may be difficult, as during the emotional process they may quickly change (Scherer, 1987 ). Moreover, some stimuli may elicit emotions that are more complex and multifaceted than those captured by simple measurement methods associated with discrete emotions.

However, this discrepancy does not explain why subjects watching the crime in VR felt stronger guilt, while those watching the video on screen rated anger and hate higher. As our research is the first attempt at methodological analysis of stimulus manipulation using Video-360° and VR equipment to compare discrete emotions, in discussing the results, we decided to include two alternative explanations—we consider them as a starting point for future research on the proposed technique in witness testimony studies.

First of all, it should be considered that such emotion ratings adequately represent the subject's emotional experience, and therefore, in fact, these two media elicit different kinds of emotion. Based on the theory of emotions, it is possible to formulate possible explanations of which aspects of the experimental manipulation may be considered as their antecedents.

Although we commonly think of shame and guilt as feelings we experience as a result of our own actions, feelings of self-condemnation can sometimes result from acts committed by others. In such a situation, we can refer to so-called vicarious guilt , as Lickel et al. ( 2005 ) defined it. It assumes that personal causality is not always a prerequisite for the experience of guilt, but that there are certain conditions that may induce it. Thus, referring to Lickel's research, it seems possible that subjects who experienced increased transportation to the crime event and immersion in the scene could have felt stronger vicarious guilt due to virtual reality-induced control of the situation. Perhaps they felt while watching the crime that they could have done something—helped the victim catch the perpetrators, or even stopped them before the crime occurred. Importantly, the intensity of this guilt is not high. This may be because the emotion was triggered by the behaviors and actions of someone else, not themselves. This explanation, however, needs further verification with methods capable of discriminating between different types of guilt.

Anger and hate

These two emotions are substantively content related and are sometimes considered together (e.g., Bernier & Dozier, 2002 ; Frijda, 1986 ; Power & Dalgleish, 2015 ). Anger is often defined as a modal/basic emotion. By signaling significance at the individual–environment interface, it organizes a response to the stimulus, which often takes the form of aggression. However, anger is not necessarily a response to a stimulus directly related to the individual's self, but can also be triggered by aversive environmental stimuli, such as unpleasant sights, smells, and extreme thermal sensations (Berkowitz, 1990 ). In this sense, then, it appears more similar to hate than to a modal emotion that prepares for a fight. After all, one way to understand hate—on an individual, not a group level—is to define it as a strong feeling of intense or passionate dislike for someone or something. When considering hate, we most commonly refer to an emotion aroused by frustration of needs or an unpleasant sensory experience (Brogaard, 2020 ), but this emotion also has links to the moral evaluation of certain behaviors (Pretus Gomez et al., 2022 ). In this sense, hate and anger are emotions that could be evoked by the video that presents two individuals committing a crime and behaving in an irritating manner. Juxtaposing self-report rates with psychophysiological measurements (lower arousal in control condition), we can conclude that the video probably did not evoke violent, highly arousing emotions or trigger a fight/flight response. It results rather in a moral emotion based on evaluation of the culprits’ behavior. This line of reasoning, however, requires additional research that would provide a more in-depth understanding of the subjects' emotional states. Methods based on a free response format (e.g., Geneva Affect Label Coder; K. R. Scherer, 2005 ) or focused interview may be most useful.

However, why these emotions were felt more intensively when the crime was seen on the screen is more challenging to explain. Perhaps this format allowed the subjects to focus more on the course of the events they were watching. They had no influence on the visual field, so they could only follow what the perpetrators did. As a result, their attitude, conversation, and actions may evoke stronger emotions. Such an explanation would be consistent with research results indicating that shifting attention from an emetogenic stimulus to its background significantly reduces emotional experience (e.g., Dolcos et al., 2020 ). Moreover, the ability to change attention is one of the theoretical factors mediating emotional experience: it is necessary for regulating emotions and, therefore, maintaining desirable emotional states (Wadlinger & Isaacowitz, 2011 ).

This format-driven focus exclusively on a key part of the scene, reducing the ecological validity of the "witnessing" experience, may have also made the scene less ambivalent and simpler to interpret. Meanwhile, the scene viewed on HMD gave the subjects some control over the experience—although they remained static (they couldn't change their seats), they could look away, and see how others were reacting. Perhaps, too, the incident was more surprising or startling, which was not covered by the self-report method we used. As a result of being present in the space with other eyewitnesses, the subjects' responses may have been influenced by how other people present in the pub behaved (the characters expressed surprise and incomprehension of what had happened—both with their reactions and verbally). After all, as Erber and Erber ( 2000 ) stated, people are often compelled to regulate affective states according to the demands of the situation, and social appropriateness (especially when interacting with strangers) is one of the most prominent motives for self-regulation. Thus, in the experimental conditions, perhaps emotions more appropriate to the situation were evoked, not so much anger and hatred toward the perpetrators, but surprise that the robbery happened at all. However, this interpretation requires verification to determine the intensity of the surprise felt in a VR environment.

An alternative explanation for the results obtained in the study can be offered. It refers not so much to the results of the control group, as to the experimental one. Researchers investigating the immersion effect, in particular the presence in a virtual environment, draw attention to the essential hedonic nature of this experience. As Murray ( 2017 , p. 98) states, “ The experience of being transported to an elaborately simulated place is pleasurable in itself, regardless of the fantasy content .” Accepting this explanation, it can be argued that this pleasurable nature of being in a simulated space among other people on a warm, summer day may have resulted in the suppression of negative emotions in the experimental group. This explanation is all the more plausible when one considers that the study took place during a period of a sanitary regime (related to the COVID-19 pandemic), which limited opportunities for social participation Footnote 3 . On the other hand, the results of the comparison of conscious positive emotions do not differ between the groups. However, subjects who watched the video on HMD rated it slightly higher than those who watched it on a screen (M VR  = .91, SD = 1.57; M screen  = .54, SD =1.28; t (104.45) = 1.348; p  = .090 (one-tailed).

Our study also demonstrated that the proposed simulation method does not affect memory processes. This indicates that a full Video-360° stimulus environment is not more distracting, nor does it lead to cognitive exhaustion. Thus, our research does not confirm the results obtained by Barreda-Ángeles et al., 2021 , who observed that a virtual reality environment can harm focused attention, recognition, and cued recall of information. This discrepancy is likely due to a significant difference in the content presented. While our study tried to present a realistic crime scene, and therefore a video that can be used in the psychology of eyewitness testimony, the study by Barreda-Ángeles et al. used journalistic excerpts, with specific narration and editing. While virtual reality can cause cognitive fatigue in situations where the task is also performed in this environment, it is multimodal in nature, and the quality of the simulation causes negative phenomena such as simulator sickness or visual sense interference (Nash et al., 2000 ; Souchet, et al., 2022b ), we believe that our Video-360° was easy to process. The scene presented in this research appears to be realistic, coherent, and thus processed fluently—it is not so much a content carrier, but more of a presence in the environment itself. However, the scene in VR directs attention and forces concentration on the elements chosen by the developer, so in this respect it is still a proxy of the witness experience, in which case greater memory disruption is expected (Ihlebæk et al., 2003 ).

Limitations and future research

Although our study identified that the potential application of virtual reality in memory research is an important contribution to the research methodology in the psychology of eyewitness testimony, it is not free from limitations. As the study compared a video presented on-screen with one mediated by virtual reality equipment, the ability to infer the ecological validity of this method is still limited. For a method to be considered more ecologically accurate, a comparison with a natural experiment is necessary. Nevertheless, based on the results, we can infer a higher realism of the witnesses' experience—a deeper sense of being a real observer of the crime, rather than a viewer of a crime film.

Another limitation is the relatively modest sample size, which probably resulted in some of the analyses not yielding significant results and being only on the verge of significance. However, the research was conducted during a period of sanitary regime, which not only made it harder to access potential participants, but also slowed the research process. Research using virtual reality equipment required subjects to be present in the laboratory and could not be carried out over the Internet. Therefore, we decided to conduct the experiment within the scheduled project period, even at the cost of a smaller sample size.

We believe that the research should be repeated not only due to the small sample size but also to the surprising results of the emotional response analysis that are contrary to the hypotheses. Given that the tool we chose to measure the intensity of emotions did not allow us to capture surprise, we are not certain that the idea of the coherence between the reactions of the subjects and other “eyewitnesses” presented in the film is adequate. Future research should therefore compare the reaction of being startled. This would provide a stronger argument that the behavior and reactions elicited by the simulation using VR are realistic. Optimally, though, similar comparisons should be made between the VR experiment and the naturalistic one. Moreover, a more in-depth analysis of the subjects' emotional states and experiences of observing the crime is also necessary—ideally, one that allows the subjects to describe their states without the researcher's suggestion of how to label them. The account of more complex phenomenological experiences can potentially be compared to actual witnesses' emotional states, and this may provide a key argument for recognizing the proposed method as a valid simulation of witnesses' experiences.

Furthermore, the potentially pleasant nature of VR-mediated experiences should also be verified. As mentioned above, one possible explanation for the lower ratings of negative emotions in VR may be their suppression by the pleasurable nature of virtual reality. To determine whether an experimental manipulation mediated by VR in fact evokes different emotions than one performed using a traditional method, it is necessary to repeat the experiment during the period of ordinary access to social life. Another way to test it is to prepare a different stimulus that is not as easily associated with pleasure and leisure.

Given the above, however, we believe that our study represents an important step in the development of an ecologically valid experimental method. It can potentially change not only the psychology of witness testimony, but also more general studies of other mental function or behavior, so that they are set in a more realistic context without losing control of the procedure.

One person in the experimental group did not report age.

The video has been deposited in a repository and is available for noncommercial use by researchers under a CC BY-NC-ND 4.0 license.

DOI: 10.26106/r0av-bn42

https://ruj.uj.edu.pl/xmlui/handle/item/308227?locale-attribute=en

We consider this explanation plausible also in light of the qualitative assessment of the subjects' reports, which they spontaneously produced after watching the film. A portion of the participants, when asked to describe the scene, also highlighted their own emotions and described their experience. Some statements included accounts of the pleasure they felt during the simulation. Since description of emotional states in free response format was not part of the procedure, we did not systematically analyze them, but we consider this explanation plausible and in need of verification by more sensitive methods.

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Acknowledgments

The study was partially funded by a mini-grant for Ph.D. students financed by the Faculty of Management and Social Communication, Jagiellonian University in Kraków.

The authors thank HP Poland Inc. for providing free of charge the VR equipment for testing and research purposes.

We want to thank Maciej Bernaś, without whom the Video-360 produced for the study would not have been created—and certainly not in such a professional form.

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The Video-360° (DOI: 10.26106/r0av-bn42), which is the basis of the experimental procedure, is deposited in an open repository and is available for noncommercial use by researchers under a CC BY-NC-ND 4.0 license.

Link to the video: https://uj.rodbuk.pl/dataset.xhtml?persistentId=doi:10.26106/r0av-bn42

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Glomb, K., Piotrowski, P. & Romanowska, I.A. It is not real until it feels real: Testing a new method for simulation of eyewitness experience with virtual reality technology and equipment. Behav Res 56 , 4336–4350 (2024). https://doi.org/10.3758/s13428-023-02186-2

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Home » Society & Community » Conformity & Obedience » Milgram’s Obedience Experiments » Milgram’s Obedience Experiments #2

Milgram’s Obedience Experiments #2

PART 2 Criticisms of the classic study Martin Orne & Charles Holland (1968) claimed that the research lacked experimental realism , meaning that the experimental set-up was simply not believable. They thought the participants realised that the electric shocks were not real because powerful electric shocks were not a believable punishment for making a mistake on a word-pair test. Thus, the research lacked internal validity , as the obedience was not a genuine effect. Orne & Holland claimed the participants were just playing along to please the experimenter – demand characteristics . They based this on Holland’s (1967) replication of Milgram’s experiment, in which he found afterwards that 75% of the participants did not believe the deception.

However, Milgram argued the participants’ stress reactions contradict this, indicating they were so caught up in the situation it seemed real to them, meaning the study did have experimental realism. Additionally, in the post-experimental interview the participants were asked to rate how painful they thought the last few shocks they administered were to the learner on a scale of 1 (‘not at all painful’) to 14 (‘extremely painful’). The mode of the results was 14, with a mean of 13.42. Assuming the participants were answering honestly, they clearly believed they were seriously harming the learner. In a post-experiment questionnaire completed a year later, 56.1% of the participants stated that they “fully believed” , 24% “had some doubts” but believed, 11.4% had doubts but thought it unlikely they were being deceived, 6..1% “just weren’t sure” and only 2.4% were “certain” the shocks were not real. However, Gina Perry (2012) has produced evidence which, on the face of it, seems to contradict the questionnaire results.  She found that Taketo Murata , one of Milgram’s research assistants, had divided participants into ‘doubters’ (who thought the shocks were fake) and ‘believers’ (who thought the shocks were real. When Murata looked at the data, he found the believers were more disobedient and gave only low intensity shocks.

Nonetheless, Milgram’s case was strengthened by David Rosenhan’s (1969) replication, after which 70% of his participants claimed to have believed. (Interestingly, Rosenhan also achieved a compliance rate of 85% going all the way to 450v! His sample size, it should be noted, though, was only 20.)

Orne & Holland also claimed that the research lacked mundane realism . The research set-up is unlike real life as it was an artificial, controlled, environment. (How often in real life do people electrocute others for failing a word pair association test?) Consequently, they claimed the findings have low ecological validity as they lack generalisability to real-life settings. However, Milgram argued that, in this case, experimental realism compensated for a lack of mundane realism.

Alex Haslam & Steve Reicher (2012) also dispute the study’s internal validity on the grounds that only the fourth of the researcher’s standardised prompts is a true command – the first 3 are justifications – and they point out that it is use of the fourth prompt at which participants quit, meaning it wasn’t in fact a study about agency and obedience. Haslam & Reicher propose that the study is really about resolving 2 conflicting ‘voices’ – the pleas of the learner and the demands of the researcher – and they link the issue of whom the teacher identifies most with to Social Identity Theory . If they are correct, then the teacher’s responses would have been governed more by the the PURPLE vMEME’s concern with who to belong to than BLUE’s compulsion to do the ‘right thing’. Interestingly, point 10 of Milgram’s original 13 factors explaining obedience (before he focused so heavily on Agentic Shift Theory ) is in accord with Haslam & Reicher.

Milgram’s situationalist explanation of obedience in carrying out atrocities has been challenged by David Mandel (1998) whose research has uncovered much evidence of German soldiers willingly taking part in the maltreatment and extermination of Jews.

Most notoriously he quoted the example of the Józefów massacre of 13 July 1942 in Poland. Having notified his men that he had received orders to carry out a mass killing of Jews, Major Wilhelm Trapp of the Reserve Police Battalion 101 told his men that those who did not “ feel up to the task of killing Jews” could be assigned to other duties. In spite of it being made clear by Trapp that no stigma would be attached to choosing not to participate, only a dozen of the approximately 500 men chose to extricate themselves from the killing.

Mandel notes instances where German soldiers and concentration camp guards did not require close supervision and the suffering of their victims seemed to cause no moral strain whatsoever. He asserts that opportunities for professional advancement and the lucrative personal gain from plundering Jews and their corpses almost certainly were motivating factors in some instances. To Mandel, Milgram offered little more than an ‘obedience alibi’ for the behaviour of Holocaust perpetrators.

On a technical level the experiment is open to criticisms of population validity – how representative of the general population the 40 local men really were – and gender bias as no females participated.

The fact that the experiment took place in prestigious Yale University, with ‘Jack Williams’ looking and sounding like a competent research assistant (rather than the high school Biology teacher he really was) may have helped some of the participants convince themselves they were in a genuine experiment. To test the importance of the setting, Milgram switched a future version of the experiment to an industrial setting away from the university.

A limitation with Milgram’s research is that he himself did not provide a clear, in-depth explanation for the high levels of obedience to authority that he obtained. Rather it is through the work of others – eg: Darley and the application of the Gravesian approach – that more in-depth explanations can be put forward. While he made a great deal out of the 65% who had obeyed all the way to 450v, Milgram never really explored the issue of why 35% refused to go all the way. Nor does Milgram focus overly on the differences between the 2 first experiments. By making the ‘trauma’ Mr Wallace was going through audible in the second (classic) experiment, Milgram reduced the 100% obedience of the first experiment by 35%.

In fairness, a strength of the study was that it was well-controlled so that all participants experienced the same conditions, allowing cause-and-effect to be inferred. The high levels of control also meant that the study was replicable .

The ‘Obedience’ movie In 1965 Milgram boosted his burgeoning notoriety with the release of ‘Obedience’ , a movie documentary of a repeat of the classic study. Below is an edited compilation of clips from the movie – copyright © 1991 Alexandra Milgram.

According to such commentators as Hugh Coolican (1996), most people who see the movie are convinced that the behaviour of the participants in ‘Obedience’ is authentic and that the stress caused by their moral strain is real.

However, ‘Obedience’ may not be quite what it appears to be, according to Kathryn Millard (2011).

In fact, the raw footage for ‘Obedience’ was shot over a weekend in May 1962, using what Milgram called ‘Condition 25’, a slight variation on the classic study. He used the same actors to play ‘Mr Wallace’ and ‘Jack Williams’ as always and the participants were genuinely naïve. The camera filmed through the same 2-way mirror Milgram used to observe proceedings.

However, it was 1965 before the completed film was made publicly available. Why did it take Milgram so long to make the movie available? Millard (p660) comments on the finished product: “‘Obedience’ is as much art as science, as much drama as experiment. It was carefully art-directed, scripted, shot and edited to accentuate dramatic tension within a seemingly neutral setting. These are compelling images constructed by an accomplished dramatist and filmmaker.”

Ethical issues with the classic study As Diana Baumrind stated only too clearly in 1964, there are serious ethical issues with Milgram’s experiments . She expressed concern that such behaviours – especially deception – could damage trust in psychologists and their research.

When Milgram began his experiments, the concept of ethical guidelines was in relative infancy. Despite details of the inhumane medical and psychological experiments conducted in the Nazi concentration camps and Japanese facilities like the notorious Unit 731 becoming more widely known, ethical guidelines were developed and adopted relatively slowly. As Thomas Blass (2004, p71) put it: “There were no formal ethical guidelines for the protection of the human subjects. Researchers tended to use their own judgement about whether their research posed an ethical problem…ethical questions…took a back seat to scientific value.”

The first ethical dilemma with Milgram’s experiment is deception. The researcher deceived the participants, who were made to believe that they were truly inflicting pain on the learners and were purposely put in a position of high stress. According to James Nairne (2011), some teachers even believed they had badly hurt, or even killed the learner, causing them a lot of distress.

Milgram also lied about the purpose of the experiment. While it was truly to measure obedience, he told his participants that he was studying the effects of punishment on learning.  This meant the participants couldn’t give fully-informed consent . Although the participants were debriefed after the experiment was over, Nairne asserts many critics believe that it wasn’t enough because it didn’t prevent the subsequent psychological damage that could have affected the participants.

Then there is the question of harm. Clearly the moral strain most participants experienced caused them considerable stress – psychological harm . According to Blass (p115), though, Milgram claimed that “relatively few subjects experienced greater tension than a nail-biting patron at a good Hitchcock thriller” .

However, 2 participants gave accounts to Blass (p116) that contradict Milgram:-

• William Menold  said, “It was hell in there… .[I was] hysterically laughing, but it was not funny laughter…It was so bizarre. And I mean, I completely lost it, my reasoning power” . He said that he couldn’t believe “that somebody could get [him] to do that stuff” .
• Herbert Winer  said that his experience of the experiment was “very difficult to describe…the way [his] feelings changed [about it], and the conflict and tension that arose” , and that his “own heart condition went into an extremely tense and conflicted state” . Talking about the debrief at the end of the study, Winer said he “was angry at having been deceived… resented the whole situation [and] was a little embarrassed at not having stopped earlier” .

Responding to the post-experiment questionnaire a year after the classic study, 84% said they were either glad or very glad to have taken part, 15% were neither glad nor sorry to have taken part and 1.3% were either sorry or very sorry to have taken part. 74% stated that they had learned something of personal importance. The questionnaire seems to justify Milgram’s argument about tension and stress.

Of course, when physiological harm is considered, in the classic study, 3 men had full-blown seizures!

In terms of the ethical guidelines to come, Milgram breached the participants’ privacy by watching them through a 2-way mirror and filming one set of volunteers;. Their right to withdraw was not denied outright but it was undermined by Jack Williams’ verbal prods. Milgram did respect the participants’ confidentiality. None was ever named unless they came forward themselves. In the ‘Obedience’ movie, the 14 volunteers who resisted the researcher’s pressure are well-represented; but only one man out of the 26 who went to 450v is shown. Presumably the other 25 refused to give their permission to be included. Clearly Milgram also respected their r ight to have their data withdrawn .

As for debrief , Milgram effectively created the modern debrief.

After the 1963 publication such was the professional outrage at what Milgram had put his participants through – though he suggested it was the results people found unacceptable more than the methodology – that his membership of the American Psychological Association (APA) was suspended. Later, however, the APA gave Milgram a major award for his obedience experiments!

Obedience Experiment Variations In 1974 Milgram published details of a whole series of variations on the original 1962 ‘Obedience Experiment’. He wanted to investigate reasons for the high levels of obedience – how much the concept of agency could be validated and how much moral strain participants could take. So, in a systematic way, he changed one variable at a time to see what the effect was. Apart from that one change, Milgram replicated the original experiment precisely. In all, Milgram studied over 1,000 participants.

Some of the variations are discussed in the clip below from the  ‘O bedience’  movie…

Photo copyright © 1991 Alexandra Milgram

What Milgram effectively found was that increasing the proximity of the ‘learner’ to the ‘teacher’ – thus making the learner’s plight more obvious – decreased the % of participants who went to 450v. Decreasing the proximity of learner to teacher increased the % of participants going all the way.  For example, with the learner just one metre from the teacher, seen and heard, obedience decreased to 40%. When learner started expressing reluctance at 150v, the teacher being required to force the learner’s hand down onto the ‘electric plate’ reduced obedience to 30%. (However, the mean shock level was still nearly 270v.)

Decreasing the authority and/or proximity of the researcher also had the effect of decreasing obedience while increasing the researcher’s authority increased obedience. Percentages of participants going to 450v when…

• Having only to pull a switch to signal an ‘assistant teacher’ ( confederate of the researcher) to administer the shocks on the teacher’s behalf,  the assistant obeyed without question all the way – 92.5%
• Being told that the learner had only agreed to a limited contract – “you let me out when I say so” – 40%
• The researcher phoned in commands or commands were on pre-recorded on tape – 23% (Some of the teachers cheated in this condition and either pretended to administer shocks or gave lower ones than instructed)
• Another participant (confederate of the researcher) took over the authority role (using the researcher’s brief) when the researcher had to leave the room – 20%
• 2 fellow ‘teachers’ (confederates of the researcher) were in the room – one reading the list of word pairs, the other informing ‘Mr Wallace’ whether he was right or wrong – and the naive participant  required to administer the shocks – with one ‘upset’ confederate quitting at 150v and the other at 210v – 10%, with 50% refusing to carry on past 150v (Interestingly, Milgram carried out an alternative version of this experiment in which 2 confederate teachers gave shocks without protest and chiding the real participant when he expressed discomfort with the procedure, resulting in 72.5% going all the way)
• 2 researchers were arguing – one telling the participant to stop and the other to continue – 0%
• The teachers were allowed to set their own voltage levels resulting in lower levels of shock being administered (Only one participant went to 450v and 95% refused to administer any more shocks after the learner protested for the first time)

Milgram also considered whether the location of the experiments had any bearing on the authority of the experimenter. He moved the experiment to some run- down offices in nearby industrial Bridgeport, ostensibly run by a private firm, Research Associates of Bridgeport, and had the researcher not wearing the scientist’s lab coat but a warehouseman’s overall. In that condition he found that only 47.5% would go to the full 450v.

Background was also investigated. Participants who had gone on to higher education were less obedient overall –  possibly because they had learned to think independently and may also have gone on to higher positions in life where they were used to giving orders, rather than receiving them. Correspondingly, participants with a military background, used to receiving orders, tended to be more obedient. Roman Catholics tended to be the most obedient from amongst those who were members of Christian churches.

To counter the accusations of  gender bias  with regard to the classic study, Milgram replicated those conditions with 40 local women and found that gender made no difference –  65% went all the way!

A small number of participants in one of the experiments were rated on   Lawrence Kohlberg’s   Stages of Moral Development –  34 according to Milgram  and 27 according to Kohlberg (1984). While the number of defiant participants (8) was small –  too small to be anything other than ‘suggestive’ (Milgram) –  they undoubtedly scored higher on Kohlberg’s scale –  at a Post- Conventional level, indicating the ORANGE and/or GREEN vMEMES were dominating their selfplexes . Accordingly, the more obedient could be deemed to be at a Conventional level and concerned just with obeying the legitimate authority , indicating BLUE was dominant.

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IResearchNet

Ecological Validity

Ecological validity definition.

Ecological validity is the extent to which research findings would generalize to settings typical of everyday life. As such, ecological validity is a particular form of external validity. Whereas external validity refers to the overall extent to which findings generalize across people, places, and time, ecological validity refers more specifically to the extent to which findings generalize to the settings and people common in today’s society.

Ecological Validity Background and Distinctions

In this regard, ecological validity is closely related to the concept of mundane realism. Experimental tasks are said to have mundane realism when they closely resemble activities that are common in natural settings. For example, activities in an experiment might be realistic in this mundane way when participants are asked to read a newspaper story about an obscure issue in a foreign country. This study might be considered as having a great deal of mundane realism because it uses activities common in everyday life (reading a newspaper). Yet the study may also be considered as lacking in experimental realism (the extent to which the activities are meaningful and have an impact on participants) if the topic of the newspaper article is uninteresting and fails to engage participants.

Ecological validity does not simply reflect an absence of experimental realism, because there are certainly many engaging and influential activities that form core aspects of everyday life. In fact, one might distinguish between mundane realism and ecological validity by noting that, in the real world, people would be relatively unlikely to spend time reading a newspaper article about a topic about which they know and care very little. Thus, although newspaper reading itself seems to reflect everyday activities quite well (mundane realism), the use of that activity in the experimental setting may diverge from the ways and reasons people typically read newspapers. That is, findings based on the use of this activity may lack ecological validity.

In this sense, ecological validity is also related to psychological realism (the extent to which the psychological processes operating in an experiment also occur in everyday life). When discussing psychological realism, it is important to distinguish between the specific activities and materials used in a study (mundane realism), the likely impact of the activities and materials (experimental realism), and the types of psychological processes that participants use to complete the activities in the study. Even if the activities in a study bear little resemblance to real-world activities (low mundane realism) and have relatively little impact on participants (low experimental realism), the thought processes that participants use in the study may be quite common in the real world (high psychological realism). For example, if a study involves judging words as quickly as possible as they appear on a computer screen, this would not be a typical activity in everyday life, and the words may not create strong reactions in research participants. However, if the words are activating concepts that then help people to quickly comprehend the next word on the screen, this may demonstrate a psychological process (concept activation) that is extremely common in everyday life.

Researchers might reasonably ask whether ecological validity is always valued. To be sure, all else being equal, researchers would prefer that their findings replicate in real-world settings. However, as noted earlier, psychological processes that would operate in many everyday settings may be more efficiently and effectively tested using methods that remove much of the messiness (lack of experimental control) of real-world settings. Especially when one is testing specific psychological theories and doing so by isolating particular variables within the theory, ecological or even external validity more generally may not be of the utmost importance. When seeking to intervene in specific applied settings, however, one would certainly want to make sure that the intervention of interest is able to influence behavior even with all of the messiness of the natural environment. This may be more likely if the intervention is developed on the basis of research that incorporates as many features of the real-world environment as possible.

Despite ecological validity being relevant to which settings a result might generalize, the reader should note that ecological validity is not the same as external validity. There is no guarantee that an effect found in a specific, ecologically valid setting is more likely to generalize across settings (a key aspect of external validity) than is an effect found in a more artificial laboratory setting. Although a study conducted in a coffee shop might produce results that are more likely to generalize to coffee shops, the results of the study may be no more likely to generalize across many settings (such as courtrooms, boardrooms, or classrooms) than a study conducted in a laboratory where background noise is more carefully controlled. Support for external validity can be garnered from replications of an effect at different points in time and in different places, even if all of those places are quite artificial and all lack ecological validity.

References:

• Aronson, E., Wilson, T. D., & Brewer, M. B. (1998). Experimentation in social psychology. In D. Gilbert, S. Fiske, & G. Lindzey (Eds.), The handbook of social psychology (4th ed., pp. 99-142). New York: McGraw-Hill.
• Reis, H. T., & Judd, C. M. (Eds.). (2000). Handbook of research methods in social and personality psychology. New York: Cambridge University Press.
• Sansone, C., Morf, C. C., & Painter, A. T. (Eds.). (2004). The SAGE handbook of methods in social psychology. Thousand Oaks, CA: Sage.
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Ecological Validity, External Validity, and Mundane Realism in Hearing Science

Beechey, Timothy

Hearing Sciences – Scottish Section, School of Medicine, University of Nottingham, Glasgow, United Kingdom.

Received February 10, 2021; accepted November 30, 2021; published online ahead of print January 13, 2022.

The authors have no conflict of interest to disclose.

Address for correspondence to: Timothy Beechey, Hearing Sciences – Scottish Section, Level 3 New Lister Building, Glasgow Royal Infirmary, Glasgow G31 2ER, United Kingdom. E-mail: [email protected]

Tests of hearing function are typically conducted in conditions very different from those in which people need to hear and communicate. Even when test conditions are more similar, they cannot represent the diversity of situations that may be encountered by individuals in daily life. As a consequence, it is necessary to consider external validity: the extent to which findings are likely to generalize to conditions beyond those in which data are collected. External validity has long been a concern in many fields and has led to the development of theories and methods aimed at improving generalizability of laboratory findings. Within hearing science, along with related fields, efforts to address generalizability have come to focus heavily on realism: the extent to which laboratory conditions are similar to conditions found in everyday settings of interest. In fact, it seems that realism is now tacitly equated with generalizability. The term that has recently been applied to this approach by many researchers is ecological validity . Recent usage of the term ecological validity within hearing science, as well as other fields, is problematic for three related reasons: (i) it encourages the conflation of the separate concepts of realism and validity; (ii) it diverts attention from the need for methods of quantifying generalization directly; and (iii) it masks a useful longstanding definition of ecological validity within the field of ecological psychology. The definition of ecological validity first used within ecological psychology—the correlation between cues received at the peripheral nervous system and the identity of distant objects or events in the environment—is entirely different from its current usage in hearing science and many related fields. However, as part of an experimental approach known as representative design , the original concept of ecological validity can play a valuable role in facilitating generalizability. This paper will argue that separate existing terms should be used when referring to realism and generalizability, and that the definition of ecological validity provided by the Lens Model may be a valuable conceptual tool within hearing science.

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