Characterization and assessment of executive functions through a virtual cooking task in euthymic patients with bipolar disorder.

Bipolar disorder (BD) implies impairments in executive functions during euthymia that interfere in psychosocial functioning. Virtual reality assessments may confer advantages respect to traditional assessments in terms of efficiency and ecological validity. The aim of this study was to validate a novel Virtual Cooking Task (VCT) for executive functions assessment in euthymic patients with BD.

Assessing Executive Functioning in Schizophrenia: Concurrent and Discriminative Validity of a Novel Virtual Cooking Task.

Deficits in executive functions (EF) are strongly related to real-life functioning and negative symptoms (NS) in schizophrenia. Recently, virtual reality has enabled more ecologically valid approaches to assess EF in simulated "real-life" scenarios among which the virtual cooking task (VCT) has gained attention. However, the clinical implications of the VCT in schizophrenia have not been investigated exhaustively.

Biosignal comparison for autism assessment using machine learning models and virtual reality.

Clinical assessment procedures encounter challenges in terms of objectivity because they rely on subjective data. Computational psychiatry proposes overcoming this limitation by introducing biosignal-based assessments able to detect clinical biomarkers, while virtual reality (VR) can offer ecological settings for measurement. Autism spectrum disorder (ASD) is a neurodevelopmental disorder where many biosignals have been tested to improve assessment procedures.

Social Signal Processing in Affective Virtual Reality: Human-Shaped Agents Increase Electrodermal Activity in an Elicited Negative Environment.

Prior research on affect elicitation indicates that stimuli with social content (pictures or videos) are more arousing than nonsocial stimuli. In particular, they elicit stronger physiological arousal as measured by electrodermal activity (EDA; i.e.

An Online Attachment Style Recognition System Based on Voice and Machine Learning.

Attachment styles are known to have significant associations with mental and physical health. Specifically, insecure attachment leads individuals to higher risk of suffering from mental disorders and chronic diseases. The aim of this study is to develop an attachment recognition model that can distinguish between secure and insecure attachment styles from voice recordings, exploring the importance of acoustic features while also evaluating gender differences.

The whole-body motor skills of children with autism spectrum disorder taking goal-directed actions in virtual reality.

Many symptoms of the autism spectrum disorder (ASD) are evident in early infancy, but ASD is usually diagnosed much later by procedures lacking objective measurements. It is necessary to anticipate the identification of ASD by improving the objectivity of the procedure and the use of ecological settings. In this context, atypical motor skills are reaching consensus as a promising ASD biomarker, regardless of the level of symptom severity.

A Scoping Review and a Taxonomy to Assess the Impact of Mobile Apps on Cancer Care Management.

Mobile Health (mHealth) has a great potential to enhance the self-management of cancer patients and survivors. Our study aimed to perform a scoping review to evaluate the impact and trends of mobile application-based interventions on adherence and their effects on health outcomes among the cancer population. In addition, we aimed to develop a taxonomy of mobile-app-based interventions to assist app developers and healthcare researchers in creating future mHealth cancer care solutions.

How priming with body odors affects decision speeds in consumer behavior.

To date, odor research has primarily focused on the behavioral effects of common odors on consumer perception and choices. We report a study that examines, for the first time, the effects of human body odor cues on consumer purchase behaviors. The influence of human chemosignals produced in three conditions, namely happiness, fear, a relaxed condition (rest), and a control condition (no odor), were examined on willingness to pay (WTP) judgments across various products.

A Digital Health Intervention for Stress and Anxiety Relief in Perioperative Care: Protocol for a Feasibility Randomized Controlled Trial.

Background: Stress and anxiety are psychophysiological responses commonly experienced by patients during the perioperative process that can increase presurgical and postsurgical complications to a comprehensive and positive recovery. Preventing and intervening in stress and anxiety can help patients achieve positive health and well-being outcomes. Similarly, the provision of education about surgery can be a crucial component and is inversely correlated with preoperative anxiety levels.

An Artificial Intelligence-Driven Digital Health Solution to Support Clinical Management of Patients With Long COVID-19: Protocol for a Prospective Multicenter Observational Study.

Background: COVID-19 pandemic has revealed the weaknesses of most health systems around the world, collapsing them and depleting their available health care resources. Fortunately, the development and enforcement of specific public health policies, such as vaccination, mask wearing, and social distancing, among others, has reduced the prevalence and complications associated with COVID-19 in its acute phase. However, the aftermath of the global pandemic has called for an efficient approach to manage patients with long COVID-19.

Digital health for emotional and self-management support of caregivers of children receiving growth hormone treatment: a feasibility study protocol.

Background: Caregivers of children undergoing growth hormone treatment often face stress and stigma. In this regard, family-centered approaches are increasingly considered, wherein caregivers' mental wellbeing is taken into account to optimize children's health-related outcomes and behaviors (e.g.

Combining Virtual Reality and Machine Learning for Leadership Styles Recognition.

The aim of this study was to evaluate the viability of a new selection procedure based on machine learning (ML) and virtual reality (VR). Specifically, decision-making behaviours and eye-gaze patterns were used to classify individuals based on their leadership styles while immersed in virtual environments that represented social workplace situations. The virtual environments were designed using an evidence-centred design approach.

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.

Eye gaze as a biomarker in the recognition of autism spectrum disorder using virtual reality and machine learning: A proof of concept for diagnosis.

The core symptoms of autism spectrum disorder (ASD) mainly relate to social communication and interactions. ASD assessment involves expert observations in neutral settings, which introduces limitations and biases related to lack of objectivity and does not capture performance in real-world settings. To overcome these limitations, advances in technologies (e.

Assessment of the Autism Spectrum Disorder Based on Machine Learning and Social Visual Attention: A Systematic Review.

The assessment of autism spectrum disorder (ASD) is based on semi-structured procedures addressed to children and caregivers. Such methods rely on the evaluation of behavioural symptoms rather than on the objective evaluation of psychophysiological underpinnings. Advances in research provided evidence of modern procedures for the early assessment of ASD, involving both machine learning (ML) techniques and biomarkers, as eye movements (EM) towards social stimuli.

Why Do We Take Risks? Perception of the Situation and Risk Proneness Predict Domain-Specific Risk Taking.

Risk taking (RT) is a component of the decision-making process in situations that involve uncertainty and in which the probability of each outcome - rewards and/or negative consequences - is already known. The influence of cognitive and emotional processes in decision making may affect how risky situations are addressed. First, inaccurate assessments of situations may constitute a perceptual bias in decision making, which might influence RT.

The Virtual Cooking Task: A Preliminary Comparison Between Neuropsychological and Ecological Virtual Reality Tests to Assess Executive Functions Alterations in Patients Affected by Alcohol Use Disorder.

Alcohol use disorder (AUD) is a major global problem. Neuropsychological studies have shown that AUD causes deficits in executive functions (EFs), a set of higher order cognitive skills that govern individual behavior in everyday situations. Many standardized neuropsychological tests are used to evaluate EF.

The Spheres & Shield Maze Task: A Virtual Reality Serious Game for the Assessment of Risk Taking in Decision Making.

Risk taking (RT) is an essential component in decision-making process that depicts the propensity to make risky decisions. RT assessment has traditionally focused on self-report questionnaires. These classical tools have shown clear distance from real-life responses.

Machine Learning and Virtual Reality on Body Movements' Behaviors to Classify Children with Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is mostly diagnosed according to behavioral symptoms in sensory, social, and motor domains. Improper motor functioning, during diagnosis, involves the qualitative evaluation of stereotyped and repetitive behaviors, while quantitative methods that classify body movements' frequencies of children with ASD are less addressed. Recent advances in neuroscience, technology, and data analysis techniques are improving the quantitative and ecological validity methods to measure specific functioning in ASD children.

Application of Supervised Machine Learning for Behavioral Biomarkers of Autism Spectrum Disorder Based on Electrodermal Activity and Virtual Reality.

Objective: Sensory processing is the ability to capture, elaborate, and integrate information through the five senses and is impaired in over 90% of children with autism spectrum disorder (ASD). The ASD population shows hyper-hypo sensitiveness to sensory stimuli that can generate alteration in information processing, affecting cognitive and social responses to daily life situations. Structured and semi-structured interviews are generally used for ASD assessment, and the evaluation relies on the examiner's subjectivity and expertise, which can lead to misleading outcomes.

A Virtual Versus an Augmented Reality Cooking Task Based-Tools: A Behavioral and Physiological Study on the Assessment of Executive Functions.

Virtual reality (VR) and augmented reality (AR) are two novel graphics immersive techniques (GIT) that, in the last decade, have been attracting the attention of many researchers, especially in psychological research. VR can provide 3D real-life synthetic environments in which controllers allow human interaction. AR overlays synthetic elements to the real world and the human gaze to target allow hand gesture to act with synthetic elements.

Are 3D virtual environments better than 2D interfaces in serious games performance? An explorative study for the assessment of executive functions.

Executive functions refer to higher-order cognitive processes that supervise and guide goal-directed and adaptive behaviors in response to everyday situations. The traditional measures used to assess executive functions include paper-and-pencil tests and/or computerized tests that have been found to have a moderate level of ecological validity in predicting real-world performance. Serious games (SG) represent a novel methodological approach, allowing investigating subjects' performance in real-simulated situations.

The Past, Present, and Future of Virtual and Augmented Reality Research: A Network and Cluster Analysis of the Literature.

The recent appearance of low cost virtual reality (VR) technologies - like the Oculus Rift, the HTC Vive and the Sony PlayStation VR - and Mixed Reality Interfaces (MRITF) - like the Hololens - is attracting the attention of users and researchers suggesting it may be the next largest stepping stone in technological innovation. However, the history of VR technology is longer than it may seem: the concept of VR was formulated in the 1960s and the first commercial VR tools appeared in the late 1980s. For this reason, during the last 20 years, 100s of researchers explored the processes, effects, and applications of this technology producing 1000s of scientific papers.

EXPANSE: A novel narrative serious game for the behavioral assessment of cognitive abilities.

EFs are a set of processes that supports many cognitive domains as goal setting, monitoring, planning, and cognitive-behavioural flexible control. Currently, many standardized paper-and-pencil tests or scales are used to assess EFs. These tests are easy to administer, score, and interpret but present some limitations in terms of generalizability of behaviours in real life.

Virtual Reality as an Emerging Methodology for Leadership Assessment and Training.

In developed countries, companies are now substantially reliant on the skills and abilities of their leaders to tackle a variety of complex issues. There is a growing consensus that leadership development training and assessment methods should adopt more holistic methodologies, including those associated with the emotional and neuroendocrine aspects of learning. Recent research into the assessment of leadership competencies has proposed the use of objective methods and measurements based on neuroscience.