A Novel Integrating Virtual Reality Approach for the Assessment of the Attachment Behavioral System

Realizing consumers' existential dreams via product marketing and mixed reality: a perspective based on affective neuroscience theories

In an era of swift societal changes and escalating consumerism, this paper presents an exploration of an innovative approach that integrates product marketing strategies, mixed reality (MR) technology, and affective neuroscience theories to actualize consumers' existential dreams. MR, with its unique capacity to blend the virtual and real worlds, can enhance the consumer experience by creating immersive, personalized environments that resonate with consumers' existential aspirations. Insights from affective neuroscience, specifically the brain's processing of emotions, guide the development of emotionally engaging marketing strategies, which strengthen the connection between consumers, products, and brands. These integrated strategies not only present a novel blueprint for companies to deepen consumer engagement but also promise more fulfilling and meaningful consumer experiences. Moreover, this approach contributes to societal well-being and prosperity, marking a significant stride in the field of marketing.

Review of Psychophysiological and Psychotherapeutic Studies of Stress Using Virtual Reality Technologies

This review addresses the use of virtual reality technologies in the psychophysiology and psychotherapy of stress. Studies using virtual reality both to introduce subjects into a state of stress and to help reduce stress reactions are reviewed. Methods developed for treating patients suffering from stress-related disorders (in particular, PTSD and phobias) are described. In many cases, reductions in stress reactions with the help of virtual reality systems are achieved not only at the self-report (experiential) level, but also at the level of central and peripheral nervous system measures. This allows virtual reality to be regarded as a modern, inexpensive, and effective method, firstly, for introducing subjects into a state of stress with the aim of testing various hypotheses in psychophysiology and, secondly, to reduce stress reactions.

Recognizing Personality Traits Using Consumer Behavior Patterns in a Virtual Retail Store

Virtual reality (VR) is a useful tool to study consumer behavior while they are immersed in a realistic scenario. Among several other factors, personality traits have been shown to have a substantial influence on purchasing behavior. The primary objective of this study was to classify consumers based on the Big Five personality domains using their behavior while performing different tasks in a virtual shop. The personality recognition was ascertained using behavioral measures received from VR hardware, including eye-tracking, navigation, posture and interaction. Responses from 60 participants were collected while performing free and directed search tasks in a virtual hypermarket. A set of behavioral features was processed, and the personality domains were recognized using a statistical supervised machine learning classifier algorithm via a support vector machine. The results suggest that the open-mindedness personality type can be classified using eye gaze patterns, while extraversion is related to posture and interactions. However, a combination of signals must be exhibited to detect conscientiousness and negative emotionality. The combination of all measures and tasks provides better classification accuracy for all personality domains. The study indicates that a consumer's personality can be recognized using the behavioral sensors included in commercial VR devices during a purchase in a virtual retail store.

The Effects of Virtual Reality on Anxiety and Self-Efficacy Among Patients With Cancer: A Pilot Study

OBJECTIVES

To examine the impact of a nurse-led intervention on anxiety levels and perceived self-efficacy to cope in patients receiving first-time chemotherapy using a customized prechemotherapy educational virtual reality (VR) video.

SAMPLE & SETTING

35 patients with cancer receiving first-time chemotherapy participated in this study at a large suburban cancer center in Newark, Delaware.

METHODS & VARIABLES

A single-group, quasi-experimental pilot study was conducted to examine the feasibility of a customized prechemotherapy educational VR video in patients receiving first-time chemotherapy. The State-Trait Anxiety Inventory, heart rate, and blood pressure were used to measure anxiety, and the Cancer Behavior Inventory-Brief Version measured perceived self-efficacy to cope with cancer. Measures were taken pre- and postintervention, and patient satisfaction was examined postintervention.

RESULTS

Anxiety level, heart rate, and blood pressure significantly decreased from baseline to postintervention, and perceived self-efficacy to cope significantly increased from baseline to postintervention.

IMPLICATIONS FOR NURSING

Personalized prechemotherapy educational VR videos could be further examined as an innovative nursing intervention to meet the health, emotional, and educational needs of diverse patient populations.

An Immersive Serious Game for the Behavioral Assessment of Psychological Needs

Motivation is an essential component in mental health and well-being. In this area, researchers have identified four psychological needs that drive human behavior: attachment, self-esteem, orientation and control, and maximization of pleasure and minimization of distress. Various self-reported scales and interviews tools have been developed to assess these dimensions. Despite the validity of these, they are showing limitations in terms of abstractation and decontextualization and biases, such as social desirability bias, that can affect responses veracity. Conversely, virtual serious games (VSGs), that are games with specific purposes, can potentially provide more ecologically valid and objective assessments than traditional approaches. Starting from these premises, the aim of this study was to investigate the feasibility of a VSG to assess the four personality needs. Sixty subjects participated in five VSG sessions. Results showed that the VSG was able to recognize attachment, self-esteem, and orientation and control needs with a high accuracy, and to a lesser extent maximization of pleasure and minimization of distress need. In conclusion, this study showed the feasibility to use a VSG to enhance the assessment of psychological behavioral-based need, overcoming biases presented by traditional assessment.

Emotion Recognition in Immersive Virtual Reality: From Statistics to Affective Computing

Emotions play a critical role in our daily lives, so the understanding and recognition of emotional responses is crucial for human research. Affective computing research has mostly used non-immersive two-dimensional (2D) images or videos to elicit emotional states. However, immersive virtual reality, which allows researchers to simulate environments in controlled laboratory conditions with high levels of sense of presence and interactivity, is becoming more popular in emotion research. Moreover, its synergy with implicit measurements and machine-learning techniques has the potential to impact transversely in many research areas, opening new opportunities for the scientific community. This paper presents a systematic review of the emotion recognition research undertaken with physiological and behavioural measures using head-mounted displays as elicitation devices. The results highlight the evolution of the field, give a clear perspective using aggregated analysis, reveal the current open issues and provide guidelines for future research.

Development and Calibration of an Eye-Tracking Fixation Identification Algorithm for Immersive Virtual Reality

Fixation identification is an essential task in the extraction of relevant information from gaze patterns; various algorithms are used in the identification process. However, the thresholds used in the algorithms greatly affect their sensitivity. Moreover, the application of these algorithm to eye-tracking technologies integrated into head-mounted displays, where the subject's head position is unrestricted, is still an open issue. Therefore, the adaptation of eye-tracking algorithms and their thresholds to immersive virtual reality frameworks needs to be validated. This study presents the development of a dispersion-threshold identification algorithm applied to data obtained from an eye-tracking system integrated into a head-mounted display. Rules-based criteria are proposed to calibrate the thresholds of the algorithm through different features, such as number of fixations and the percentage of points which belong to a fixation. The results show that distance-dispersion thresholds between 1-1.6° and time windows between 0.25-0.4 s are the acceptable range parameters, with 1° and 0.25 s being the optimum. The work presents a calibrated algorithm to be applied in future experiments with eye-tracking integrated into head-mounted displays and guidelines for calibrating fixation identification algorithms.

Virtual Reality in Marketing: A Framework, Review, and Research Agenda

Marketing scholars and practitioners are showing increasing interest in Extended Reality (XR) technologies (XRs), such as virtual reality (VR), augmented reality (AR), and mixed reality (MR), as very promising technological tools for producing satisfactory consumer experiences that mirror those experienced in physical stores. However, most of the studies published to date lack a certain measure of methodological rigor in their characterization of XR technologies and in the assessment techniques used to characterize the consumer experience, which limits the generalization of the results. We argue that it is necessary to define a rigorous methodological framework for the use of XRs in marketing. This article reviews the literature on XRs in marketing, and provides a conceptual framework to organize this disparate body of work.

Affective computing in virtual reality: emotion recognition from brain and heartbeat dynamics using wearable sensors

Affective Computing has emerged as an important field of study that aims to develop systems that can automatically recognize emotions. Up to the present, elicitation has been carried out with non-immersive stimuli. This study, on the other hand, aims to develop an emotion recognition system for affective states evoked through Immersive Virtual Environments. Four alternative virtual rooms were designed to elicit four possible arousal-valence combinations, as described in each quadrant of the Circumplex Model of Affects. An experiment involving the recording of the electroencephalography (EEG) and electrocardiography (ECG) of sixty participants was carried out. A set of features was extracted from these signals using various state-of-the-art metrics that quantify brain and cardiovascular linear and nonlinear dynamics, which were input into a Support Vector Machine classifier to predict the subject’s arousal and valence perception. The model’s accuracy was 75.00% along the arousal dimension and 71.21% along the valence dimension. Our findings validate the use of Immersive Virtual Environments to elicit and automatically recognize different emotional states from neural and cardiac dynamics; this development could have novel applications in fields as diverse as Architecture, Health, Education and Videogames.