Potential Applications of Social Robots in Robot-Assisted Interventions for Social Anxiety

Social robots in adult psychiatry: a summary of utilisation and impact

Social robots are increasingly becoming more prevalent in healthcare, including nursing, geriatric care, and treatment for children on the autism spectrum. Their assistance is believed to hold promise in mitigating the effects of staffing shortages and enhancing current mental health treatment. Nevertheless, the application of social robotics in psychiatry remains restricted and controversial. This scoping review aims to provide an overview of the literature on social robots in adult psychiatry concerning their use, effects, and acceptability. We conducted a literature search, including PubMed and PsycINFO, to identify literature on robot interventions for adult psychiatric patients. Methodological quality was assessed using the 'Mixed Methods Appraisal Tool'. Usage and target variables were unique to every included original study (N = 7) and suggested a wide range of possible implications for patient treatment and care. Social robots were used to reduce symptoms, improve functioning, and gain insights into characteristic features of specific mental health conditions. The included studies were concerned with the following diagnoses: schizophrenia (N = 3), autism spectrum disorder (N = 2), and intellectual disability (N = 2). The sample sizes were too small to generalise the outcome, but overall trends showed some positive effects on the selected symptoms. Observations and participant feedback suggested high acceptance and enjoyment of the users. Although the evidence regarding the benefits of robotic interventions in adult psychiatry is still low, it suffices to assume that investing in larger, randomised, and controlled trials is worthwhile and promising.

Systematic review registration

asprediced.org, identifier 128766.

Gait-to-Gait Emotional Human-Robot Interaction Utilizing Trajectories-Aware and Skeleton-Graph-Aware Spatial-Temporal Transformer

The emotional response of robotics is crucial for promoting the socially intelligent level of human-robot interaction (HRI). The development of machine learning has extensively stimulated research on emotional recognition for robots. Our research focuses on emotional gaits, a type of simple modality that stores a series of joint coordinates and is easy for humanoid robots to execute. However, a limited amount of research investigates emotional HRI systems based on gaits, indicating an existing gap in human emotion gait recognition and robotic emotional gait response. To address this challenge, we propose a Gait-to-Gait Emotional HRI system, emphasizing the development of an innovative emotion classification model. In our system, the humanoid robot NAO can recognize emotions from human gaits through our Trajectories-Aware and Skeleton-Graph-Aware Spatial-Temporal Transformer (TS-ST) and respond with pre-set emotional gaits that reflect the same emotion as the human presented. Our TS-ST outperforms the current state-of-the-art human-gait emotion recognition model applied to robots on the Emotion-Gait dataset.

Promoting hand hygiene in a chemotherapy day center: the role of a robot

BACKGROUND

Hand hygiene is a critical component of infection prevention in healthcare settings. Innovative strategies are required to enhance hand hygiene practices among patients and healthcare workers (HCWs).

METHODS

This study was conducted at the Chemotherapy Day Center of Queen Mary Hospital, Hong Kong. It comprised three phases: phase 1 involved observational audits of hand hygiene practices among patients and HCWs by infection control nurse (ICN); phase 2 included the installation of 53 pressure sensors on alcohol-based hand rub (AHR) bottles at designated sites to monitor usage; phase 3 introduced the robot named Temi Medic to promote hand hygiene through video broadcasts at strategic locations in the center. The mean counts of pressure sensor-equipped AHR per 100 attendances per day (hereafter referred to as the mean count) across phases 2 and 3 were analyzed.

RESULTS

A total of 2580 patient attended the center from April to September 2023. The ICN observed a significant increase in hand hygiene practices among patients at the entrance and reception area, rising from phase 1 (0.2%, 1/583) and phase 2 (0.5%, 3/656) to phase 3 (5.0%, 33/654) (p < 0.001). Meanwhile, the overall hand hygiene compliance among HCWs was 74.1% (1341/1810) throughout the study period. From phase 2 to phase 3, the mean counts of 7 AHR bottles designated for patient use (P1-P7) significantly increased (35 ± 17 vs. 64 ± 24, p < 0.001), as did the 33 AHR bottles shared by both patients and HCWs (207 ± 104 vs. 267 ± 113, p = 0.027). In contrast, there was no significant change in the mean count among the 13 AHR bottles designated for HCWs (H1-H13). The mean count of H1-H13 was significantly higher than that of P1-P7 throughout phases 2 and 3 (214 ± 93 vs. 49 ± 25, p < 0.001), indicating a 4.4-fold difference.

CONCLUSIONS

While HCWs maintained stable hand hygiene compliance, the introduction of the robot significantly improved hand hygiene practices among patients in the chemotherapy day center. This underscores the importance of integrating technology into routine practices to promote infection prevention and control in healthcare settings.

Artificial Intelligence and Its Revolutionary Role in Physical and Mental Rehabilitation: A Review of Recent Advancements

The integration of artificial intelligence (AI) technologies into physical and mental rehabilitation has the potential to significantly transform these fields. AI innovations, including machine learning algorithms, natural language processing, and computer vision, offer occupational therapists advanced tools to improve care quality. These technologies facilitate more precise assessments, the development of tailored intervention plans, more efficient treatment delivery, and enhanced outcome evaluation. This review explores the integration of AI across various aspects of rehabilitation, providing a thorough examination of recent advancements and current applications. It highlights how AI applications, such as natural language processing, computer vision, virtual reality, machine learning, and robotics, are shaping the future of physical and mental recovery in occupational therapy.

Leveraging AI for the diagnosis and treatment of autism spectrum disorder: Current trends and future prospects

The integration of artificial intelligence (AI) into the diagnosis and treatment of autism spectrum disorder (ASD) represents a promising frontier in healthcare. This review explores the current landscape and future prospects of AI technologies in ASD diagnostics and interventions. AI enables early detection and personalized assessment of ASD through the analysis of diverse data sources such as behavioural patterns, neuroimaging, genetics, and electronic health records. Machine learning algorithms exhibit high accuracy in distinguishing ASD from neurotypical development and other developmental disorders, facilitating timely interventions. Furthermore, AI-driven therapeutic interventions, including augmentative communication systems, virtual reality-based training, and robot-assisted therapies, show potential in improving social interactions and communication skills in individuals with ASD. Despite challenges such as data privacy and interpretability, the future of AI in ASD holds promise for refining diagnostic accuracy, deploying telehealth platforms, and tailoring treatment plans. By harnessing AI, clinicians can enhance ASD care delivery, empower patients, and advance our understanding of this complex condition.

Framework proposal for Role-Playing Games as mental health intervention: the Critical Skills methodology

Gamified interventions are an emerging approach in mental health treatment and prevention. Their positive effects on managing various clinical conditions stem from enhancing social skills. However, cost-effective options like Table-top Role-Playing Games (TTRPGs), which offer similar benefits to other game-based interventions, lack standardized methods for ensuring replicability. In this regard, the method outlined in this study endeavors, in a structured and guided manner drawing from the Consolidated Framework for Implementation Research (CFIR), to establish a six-step protocol for developing an intervention method utilizing TTRPGs. In all Steps, we aim to anchor ourselves in robust literature concerning social skills training (SST), cognitive behavioral therapy (CBT), and gamification comprehensively. Thus, the method presented encompasses the objectives of SST, the strategies of CBT, and the dynamics of gamification via TTRPGs. Furthermore, we demonstrate a possible application of the method to illustrate its feasibility. Ultimately, the final method is structured, evidence-based, easily applicable, cost-effective, and thus viable. Mental health professionals seeking a structured and instructional tool for protocol development will find support in the method proposed here.

Qhali: A Humanoid Robot for Assisting in Mental Health Treatment

In recent years, social assistive robots have gained significant acceptance in healthcare settings, particularly for tasks such as patient care and monitoring. This paper offers a comprehensive overview of the expressive humanoid robot, Qhali, with a focus on its industrial design, essential components, and validation in a controlled environment. The industrial design phase encompasses research, ideation, design, manufacturing, and implementation. Subsequently, the mechatronic system is detailed, covering sensing, actuation, control, energy, and software interface. Qhali's capabilities include autonomous execution of routines for mental health promotion and psychological testing. The software platform enables therapist-directed interventions, allowing the robot to convey emotional gestures through joint and head movements and simulate various facial expressions for more engaging interactions. Finally, with the robot fully operational, an initial behavioral experiment was conducted to validate Qhali's capability to deliver telepsychological interventions. The findings from this preliminary study indicate that participants reported enhancements in their emotional well-being, along with positive outcomes in their perception of the psychological intervention conducted with the humanoid robot.

The League: A person-centred approach to the development of social robotics for paediatric anxiety

BACKGROUND

Social robots are promising tools to improve the quality of life of children and youth living with anxiety and should be developed based on the priorities of end users. However, pathways to include young people in patient-oriented research, particularly in the overlap between technology and mental health, have been historically limited.

OBJECTIVE

In this work, we describe engagement with experts with lived experiences of paediatric anxiety in a social robotics research programme. We report the experiences of patient advisors in a co-creation process and identify considerations for other research groups looking to involve end users in technology development in the field of youth mental health.

DESIGN

We engaged individuals with a lived experience of paediatric anxiety (current, recent past, or from a parent perspective) using three different models over the course of three years. Two initial patient partners were involved during project development, eight were engaged as part of an advisory panel ('the League') during study development and data analysis and four contributed as ongoing collaborators in an advisory role. League members completed a preparticipation expectation survey and a postparticipation experience survey.

FINDINGS

Eight individuals from a range of anxiety-related diagnostic groups participated in the League as patient partners. Members were teenagers (n = 3), young adults aged 22-26 years who had connected with a youth mental health service as children within the past eight years (n = 3) or parents of children presently living with anxiety (n = 2). Preferred methods of communication, expectations and reasons for participating were collected. The League provided specific and actionable feedback on the design of workshops on the topic of social robotics, which was implemented. They reported that their experiences were positive and fairly compensated, but communication and sustained engagement over time were challenges. Issues of ethics and language related to patient-centred brain health technology research are discussed.

CONCLUSIONS

There is an ethical imperative to meaningfully incorporate the voices of youth and young adults with psychiatric conditions in the development of devices intended to support their mental health and quality of life.

PATIENT OR PUBLIC CONTRIBUTION

Six young people and two parents with lived experiences of paediatric anxiety participated in all stages of developing a research programme on social robotics to support paediatric mental health in a community context. They also provided input during the preparation of this manuscript.

Attachment to robots and therapeutic efficiency in mental health

Previous studies in the mental health context have demonstrated that interactions with social robots can improve the mood and cognitive capacities of their users, and enhance their quality of life. In this Perspective article, our goal is to systematize the possible roles of social robots and to point out that different roles require different levels of attachment. We argue that the attachment between the client and the (robot) therapist is a fundamental ingredient of any helping relationship and that the full potential of using social robots in mental health settings can only be realized if the strength of attachment is appropriately correlated with the type of relationship established.

The Role of Coherent Robot Behavior and Embodiment in Emotion Perception and Recognition During Human-Robot Interaction: Experimental Study

BACKGROUND

Social robots are becoming increasingly important as companions in our daily lives. Consequently, humans expect to interact with them using the same mental models applied to human-human interactions, including the use of cospeech gestures. Research efforts have been devoted to understanding users' needs and developing robot's behavioral models that can perceive the user state and properly plan a reaction. Despite the efforts made, some challenges regarding the effect of robot embodiment and behavior in the perception of emotions remain open.

OBJECTIVE

The aim of this study is dual. First, it aims to assess the role of the robot's cospeech gestures and embodiment in the user's perceived emotions in terms of valence (stimulus pleasantness), arousal (intensity of evoked emotion), and dominance (degree of control exerted by the stimulus). Second, it aims to evaluate the robot's accuracy in identifying positive, negative, and neutral emotions displayed by interacting humans using 3 supervised machine learning algorithms: support vector machine, random forest, and K-nearest neighbor.

METHODS

Pepper robot was used to elicit the 3 emotions in humans using a set of 60 images retrieved from a standardized database. In particular, 2 experimental conditions for emotion elicitation were performed with Pepper robot: with a static behavior or with a robot that expresses coherent (COH) cospeech behavior. Furthermore, to evaluate the role of the robot embodiment, the third elicitation was performed by asking the participant to interact with a PC, where a graphical interface showed the same images. Each participant was requested to undergo only 1 of the 3 experimental conditions.

RESULTS

A total of 60 participants were recruited for this study, 20 for each experimental condition for a total of 3600 interactions. The results showed significant differences (P<.05) in valence, arousal, and dominance when stimulated with the Pepper robot behaving COH with respect to the PC condition, thus underlying the importance of the robot's nonverbal communication and embodiment. A higher valence score was obtained for the elicitation of the robot (COH and robot with static behavior) with respect to the PC. For emotion recognition, the K-nearest neighbor classifiers achieved the best accuracy results. In particular, the COH modality achieved the highest level of accuracy (0.97) when compared with the static behavior and PC elicitations (0.88 and 0.94, respectively).

CONCLUSIONS

The results suggest that the use of multimodal communication channels, such as cospeech and visual channels, as in the COH modality, may improve the recognition accuracy of the user's emotional state and can reinforce the perceived emotion. Future studies should investigate the effect of age, culture, and cognitive profile on the emotion perception and recognition going beyond the limitation of this work.

Research Hotspots and Trends of Social Robot Interaction Design: A Bibliometric Analysis

(1) Background: Social robot interaction design is crucial for determining user acceptance and experience. However, few studies have systematically discussed the current focus and future research directions of social robot interaction design from a bibliometric perspective. Therefore, we conducted this study in order to identify the latest research progress and evolution trajectory of research hotspots in social robot interaction design over the last decade. (2) Methods: We conducted a comprehensive review based on 2416 papers related to social robot interaction design obtained from the Web of Science (WOS) database. Our review utilized bibliometric techniques and integrated VOSviewer and CiteSpace to construct a knowledge map. (3) Conclusions: The current research hotspots of social robot interaction design mainly focus on #1 the study of human-robot relationships in social robots, #2 research on the emotional design of social robots, #3 research on social robots for children's psychotherapy, #4 research on companion robots for elderly rehabilitation, and #5 research on educational social robots. The reference co-citation analysis identifies the classic literature that forms the basis of the current research, which provides theoretical guidance and methods for the current research. Finally, we discuss several future research directions and challenges in this field.

Human-Robot Collaboration for Healthcare: A Narrative Review

Robotic applications have often quickly transitioned from industrial to social. Because of this, robots can now engage with people in a natural way and blend in with their surroundings. Due to the lack of medical professionals, growing healthcare costs, and the exponential rise in the population of vulnerable groups like the ill, elderly, and children with developmental disabilities, the use of social robots in the healthcare system is expanding. As a result, social robots are employed in the medical field to entertain and educate hospitalized patients about health issues, as well as to assist the elderly and sick. They are also employed in the dispensing of medications, rehabilitation, and emotional and geriatric care. Thus, social robots raise the standard and effectiveness of medical care. This article explains how patients and healthcare professionals collaborate with robots in the healthcare industry. The objectives of this collaboration are to resolve moral and legal concerns, improve patient outcomes, and improve healthcare delivery. It has a broad range of uses, including telemedicine, rehabilitation, and robotic surgical support. Human-robot interaction is the term used to describe interactions between social robots and people. Many obstacles stand in the way of human-robot interaction in healthcare, including safety concerns, acceptability issues, appropriateness, usefulness, and the worry that robots may replace human carers. In the end, these difficulties result in a poor adoption rate for robotic technology. As a result, the applications and difficulties of human-robot interaction in healthcare are thoroughly evaluated in this research. This study also reviews future safety prospects from human-robot interaction in healthcare, as well as ethical and usability issues including privacy, trust, and safety, and our aims to provide a comprehensive overview of the use of robots in healthcare, including their applications, benefits, challenges, and prospects, to facilitate a deeper understanding of this evolving field.

Hold My Hand: Development of a Force Controller and System Architecture for Joint Walking with a Companion Robot

In recent years, there has been a growing interest in the development of robotic systems for improving the quality of life of individuals of all ages. Specifically, humanoid robots offer advantages in terms of friendliness and ease of use in such applications. This article proposes a novel system architecture that enables a commercial humanoid robot, specifically the Pepper robot, to walk side-by-side while holding hands, and communicating by responding to the surrounding environment. To achieve this control, an observer is required to estimate the force applied to the robot. This was accomplished by comparing joint torques calculated from the dynamics model to actual current measurements. Additionally, object recognition was performed using Pepper's camera to facilitate communication in response to surrounding objects. By integrating these components, the system has demonstrated its capability to achieve its intended purpose.

Overview of the role of robots in upper limb disabilities rehabilitation: a scoping review

BACKGROUND

Neuromotor rehabilitation and improvement of upper limb functions are necessary to improve the life quality of patients who have experienced injuries or have pathological outcomes. Modern approaches, such as robotic-assisted rehabilitation can help to improve rehabilitation processes and thus improve upper limb functions. Therefore, the aim of this study was to investigate the role of robots in upper limb disability improvement and rehabilitation.

METHODS

This scoping review was conducted by search in PubMed, Web of Science, Scopus, and IEEE (January 2012- February 2022). Articles related to upper limb rehabilitation robots were selected. The methodological quality of all the included studies will be appraised using the Mixed Methods Appraisal Tool (MMAT). We used an 18-field data extraction form to extract data from articles and extracted the information such as study year, country, type of study, purpose, illness or accident leading to disability, level of disability, assistive technologies, number of participants in the study, sex, age, rehabilitated part of the upper limb using a robot, duration and frequency of treatment, methods of performing rehabilitation exercises, type of evaluation, number of participants in the evaluation process, duration of intervention, study outcomes, and study conclusions. The selection of articles and data extraction was made by three authors based on inclusion and exclusion criteria. Disagreements were resolved through consultation with the fifth author. Inclusion criteria were articles involving upper limb rehabilitation robots, articles about upper limb disability caused by any illness or injury, and articles published in English. Also, articles involving other than upper limb rehabilitation robots, robots related to rehabilitation of diseases other than upper limb, systematic reviews, reviews, and meta-analyses, books, book chapters, letters to the editor, and conference papers were also excluded. Descriptive statistics methods (frequency and percentage) were used to analyses the data.

RESULTS

We finally included 55 relevant articles. Most of the studies were done in Italy (33.82%). Most robots were used to rehabilitate stroke patients (80%). About 60.52% of the studies used games and virtual reality rehabilitate the upper limb disabilities using robots. Among the 14 types of applied evaluation methods, "evaluation and measurement of upper limb function and dexterity" was the most applied evaluation method. "Improvement in musculoskeletal functions", "no adverse effect on patients", and "Safe and reliable treatment" were the most cited outcomes, respectively.

CONCLUSIONS

Our findings show that robots can improve musculoskeletal functions (musculoskeletal strength, sensation, perception, vibration, muscle coordination, less spasticity, flexibility, and range of motion) and empower people by providing a variety of rehabilitation capabilities.

Educational Robotics: Development of computational thinking in collaborative online learning

In the previous study the work experience on organization of teaching Robotics to secondary school students at school lessons and in study groups was introduced. This study which was conducted within 2019 and 2021 covered the period of distant learning caused by COVID-19 pandemic and even post-pandemic period, when a part of school students continued learning online. The study deals with the problem of developing school students' computational thinking in online learning. We consider computational thinking as a set of cognitive skills of solving educational and cognitive problems. The research questions raised were aimed at solving the problem of the influence of Educational Robotics on developing computational thinking. During the research we have found out that due to the adaptability of robots, Educational Robotics, the development of individual learning programs, and the arrangement of collaborative online learning are instruments and a solution to the problem of developing computational thinking. The main components of computational thinking, which were studied within those 3 years, are the following: algorithmic thinking, ability to program, and efficiency in team work. The influence of the learning strategy we chose enabled us to determine the level of computational thinking and its dependence on learning Robotics. We used statistical criteria in order to summarize the results of our research. The statistics provided suggests progress in the indicator tracked. Based on the experimental data received we approximated reliability (R2) and relevant exponential equation (trend lines). The research we carried out also has led to the general conclusion that Educational Robotics helps to create synergistic learning environment for stimulating students' motivation, collaboration, self-efficacy and creativity.

Update on treatments for anxiety-related disorders

PURPOSE OF REVIEW

This review examines recent evidence that informs the treatment of anxiety-related disorders.

RECENT FINDINGS

In addition to selective serotonin reuptake inhibitors (SSRIs), serotonin and norepinephrine reuptake inhibitors (SNRIs), and benzodiazepines, agomelatine has demonstrated efficacy in treating generalized anxiety disorder (GAD). Other novel products, such as ketamine, psilocybin and cannabidiol, are in the process of gathering evidence in support of the treatment of anxiety disorders. In psychological therapy, various psychological treatments for anxiety disorders, such as mindfulness-based intervention, acceptance and commitment therapy, psychodynamic therapy, emotion-focused therapy and dialectical behavioural therapy, have been tried. Still, most therapies have not proven superior to cognitive behavioural therapy (CBT). In very preliminary findings: Repetitive transcranial magnetic stimulation (rTMS) was effective in GAD; transcranial direct current stimulation (tDCS) was effective for social anxiety disorder (SAD) and GAD and augmented exposure therapy for specific fears. Internet and mobile-based interventions have comparable efficacy to face-to-face therapy.

SUMMARY

Pharmacotherapy of anxiety disorders is expanding to novel products. Despite trying other psychological therapies for anxiety disorders, most therapies were comparable to but not superior to CBT. rTMS and tDCS were also used and show early promise for GAD, but further studies are needed. Most internet or mobile app based psychological therapies were based on CBT, and some can be considered as alternatives to in-person face-to-face therapy.

A study on the effects of perceived playfulness and emotional support in interactive learning environments for German language acquisition-A role-playing library system case

Introduction

This study examines the emotional support offered by the non-player characters (NPCs) in an interactive learning environment, as well as the effects of the perceived playfulness of the interactive system on German language learning.

Method

We developed a role-playing library system to serve this purpose. 2,377 Chinese Internet users were surveyed using online questionnaire.

Results

A theoretical model of emotion- driven learning (ELM) was proposed based on the analysis results of valid recovered data. Additionally, NPCs were found to be effective in improving learning outcomes through emotional support.

Discussion

An interactive education system may be able to enhance the perceived playfulness of learning in order to enhance the learning experience.

Implementation of Actors’ Emotional Talent into Social Robots Through Capture of Human Head’s Motion and Basic Expression

The paper presents an initial step towards employing the advantages of educational theatre and implementing them into social robotics in order to enhance the emotional skills of a child and at the same time to augment robots with actors’ emotional talent. Emotional child-robot interaction helps to catch quickly a child’s attention and enhance information perception during learning and verbalization in children with communication disorders. An innovative approach for learning through art by transferring actors’ emotional and social talents to socially assistive robots is presented and the technical and artistic challenges of tracking and translating movements expressing emotions from an actor to a robot are considered. The goal is to augment the robot intervention in order to enhance a child’s learning skills by stimulating attention, improving timing of understanding emotions, establishing emotional contact and teamwork. The paper introduces a novel approach to capture movements and expressions of a human head, to process data from brain and inertial tracking devices and to transfer them into a socially assistive robot.

A Survey on Recent Advances in Social Robotics

Over decades, social robotics has evolved as a concept that presently covers different areas of application, and interacts with different domains in technology, education, medicine and others. Today, it is possible to envision social robots in tasks that were not expected years ago, and that is not only due to the evolution of social robots, but also to the evolution of the vision humans have for them. This survey addresses recent advances in social robotics from different perspectives. Different contexts and areas of application of social robots are addressed, as well as modalities of interaction with humans. Different robotic platforms used in social contexts are shown and discussed. Relationships of social robotics with advances in other technological areas are surveyed, and methods and metrics used for the human evaluation of the interaction with robots are presented. The future of social robotics is also envisioned based on surveyed works and from different points of view.

A Pediatric Patient With Autism Spectrum Disorder and Comorbid Compulsive Behaviors Treated With Robot-Assisted Relaxation: A Case Report

The nature of autism spectrum disorders (ASDs) presents significant challenges, especially with regard to comorbidities and drug treatments. Parents and caregivers are often hesitant towards psychotropic medications, mainly due to the fear of side effects. Problems arise when comorbid symptomatology reaches extreme levels, leading to functional decline in the patients. We discuss the case of a 13-year-old girl diagnosed with autism disorder who presented with a long history of social, interpersonal, and academic challenges. The patient was hospitalized with the complaint of a persistent, non-painful, and unpleasant sensation in the perineal area that eventually resulted in repetitive and compulsive behaviors. Robot-enhanced relaxation training was introduced to support the patient since she declined to undergo any form of talk therapy. The aim of the intervention was to prevent the irritation from escalating and promote self-regulation skills. The results, based on parent reporting, indicated that the patient acquired relaxation skills, experienced some positive effects on emotional regulation, and showed a decrease in the duration of her disruptive behaviors upon completing the relaxation training. This case report provides evidence that robot-assisted relaxation training may be effective in dealing with ASD-related behavioral disturbances and comorbid anxiety.