ZenG:AR neurofeedback for meditative mixed reality

In this paper we present ZenG, a neurofeedback ARapplication concept based on Zen Gardening to fostercreativity, self-awareness, and relaxation through embodiedinteractions in a mixed reality environment. We developedan initial prototype which combined physiological sensingthrough EEG with AR visualisation on the Magic LeapDisplay. We evaluated the prototype through preliminaryuser testing with 12 adults. Results suggest users found theexperience to be enjoyable and relaxing, however theapplication could be improved by including more featuresand functionality. ZenG shows the potential for AR toprovide immersive and interactive environments that couldpromote creativity and relaxation, providing solid groundsfor further research

A Digital Human for Delivering a Remote Loneliness and Stress Intervention to At-Risk Younger and Older Adults During the COVID-19 Pandemic: Randomized Pilot Trial

BackgroundLoneliness is a growing public health issue that has been exacerbated in vulnerable groups during the COVID-19 pandemic. Computer agents are capable of delivering psychological therapies through the internet; however, there is limited research on their acceptability to date. ObjectiveThe objectives of this study were to evaluate (1) the feasibility and acceptability of a remote loneliness and stress intervention with digital human delivery to at-risk adults and (2) the feasibility of the study methods in preparation for a randomized controlled trial. MethodsA parallel randomized pilot trial with a mixed design was conducted. Participants were adults aged 18 to 69 years with an underlying medical condition or aged 70 years or older with a Mini-Mental State Examination score of >24 (ie, at greater risk of developing severe COVID-19). Participants took part from their place of residence (independent living retirement village, 20; community dwelling, 7; nursing home, 3). Participants were randomly allocated to the intervention or waitlist control group that received the intervention 1 week later. The intervention involved completing cognitive behavioral and positive psychology exercises with a digital human facilitator on a website for at least 15 minutes per day over 1 week. The exercises targeted loneliness, stress, and psychological well-being. Feasibility was evaluated using dropout rates and behavioral observation data. Acceptability was evaluated from behavioral engagement data, the Friendship Questionnaire (adapted), self-report items, and qualitative questions. Psychological measures were administered to evaluate the feasibility of the trial methods and included the UCLA Loneliness Scale, the 4-item Perceived Stress Scale, a 1-item COVID-19 distress measure, the Flourishing Scale, and the Scale of Positive and Negative Experiences. ResultsThe study recruited 30 participants (15 per group). Participants were 22 older adults and 8 younger adults with a health condition. Six participants dropped out of the study. Thus, the data of 24 participants were analyzed (intervention group, 12; waitlist group, 12). The digital human intervention and trial methods were generally found to be feasible and acceptable in younger and older adults living independently, based on intervention completion, and behavioral, qualitative, and some self-report data. The intervention and trial methods were less feasible to nursing home residents who required caregiver assistance. Acceptability could be improved with additional content, tailoring to the population, and changes to the digital human’s design. ConclusionsDigital humans are a promising and novel technological solution for providing at-risk adults with access to remote psychological support during the COVID-19 pandemic. Research should further examine design techniques to improve their acceptability in this application and investigate intervention effectiveness in a randomized controlled trial. Trial RegistrationAustralia New Zealand Clinical Trials Registry ACTRN12620000786998; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=38011

Friends from the Future: A Scoping Review of Research into Robots and Computer Agents to Combat Loneliness in Older People

BACKGROUND AND AIM: Loneliness is a common problem in older adults and contributes to poor health. This scoping review aimed to synthesize and report evidence on the effectiveness of interventions using social robots or computer agents to reduce loneliness in older adults and to explore intervention strategies. METHODS: The review adhered to the Arksey and O’Malley process for conducting scoping reviews. The SCOPUS, PUBMED, Web of Science, EMBASE, CINAHL, PsycINFO, ACM Digital Library and IEEE Xplore databases were searched in November, 2020. A two-step selection process identified eligible research. Information was extracted from papers and entered into an Excel coding sheet and summarised. Quality assessments were conducted using the Mixed Methods Appraisal Tool. RESULTS: Twenty-nine studies were included, of which most were of moderate to high quality. Eighteen were observational and 11 were experimental. Twenty-four used robots, four used computer agents and one study used both. The majority of results showed that robots or computer agents positively impacted at least one loneliness outcome measure. Some unintended negative consequences on social outcomes were reported, such as sadness when the robot was removed. Overall, the interventions helped to combat loneliness by acting as a direct companion (69%), a catalyst for social interaction (41%), facilitating remote communication with others (10%) and reminding users of upcoming social engagements (3%). CONCLUSION: Evidence to date suggests that robots can help combat loneliness in older adults, but there is insufficient research on computer agents. Common strategies for reducing loneliness include direct companionship and enabling social interactions. Future research could investigate other strategies used in human interventions (eg, addressing maladaptive social cognition and improving social skills), and the effects of design features on efficacy. It is recommended that more robust experimental and mixed methods research be conducted, using a combination of validated self-report, observational, and interview measures of loneliness

Effects of Emotional Expressiveness of a Female Digital Human on Loneliness, Stress, Perceived Support, and Closeness Across Genders: Randomized Controlled Trial

BackgroundLoneliness is a growing public health problem that has been exacerbated in vulnerable groups during the COVID-19 pandemic. Social support interventions have been shown to reduce loneliness, including when delivered through technology. Digital humans are a new type of computer agent that show promise as supportive peers in health care. For digital humans to be effective and engaging support persons, it is important that they develop closeness with people. Closeness can be increased by emotional expressiveness, particularly in female relationships. However, it is unknown whether emotional expressiveness improves relationships with digital humans and affects physiological responses. ObjectiveThe aim of this study is to investigate whether emotional expression by a digital human can affect psychological and physiological outcomes and whether the effects are moderated by the user’s gender. MethodsA community sample of 198 adults (101 women, 95 men, and 2 gender-diverse individuals) was block-randomized by gender to complete a 15-minute self-disclosure conversation with a female digital human in 1 of 6 conditions. In these conditions, the digital human varied in modality richness and emotional expression on the face and in the voice (emotional, neutral, or no face; emotional or neutral voice). Perceived loneliness, closeness, social support, caring perceptions, and stress were measured after each interaction. Heart rate, skin temperature, and electrodermal activity were assessed during each interaction. 3-way factorial analyses of variance with post hoc tests were conducted. ResultsEmotional expression in the voice was associated with greater perceptions of caring and physiological arousal during the interaction, and unexpectedly, with lower feelings of support. User gender moderated the effect of emotional expressiveness on several outcomes. For women, an emotional voice was associated with increased closeness, social support, and caring perceptions, whereas for men, a neutral voice increased these outcomes. For women, interacting with a neutral face was associated with lower loneliness and subjective stress compared with no face. Interacting with no face (ie, a voice-only black screen) resulted in lower loneliness and subjective stress for men, compared with a neutral or emotional face. No significant results were found for heart rate or skin temperature. However, average electrodermal activity was significantly higher for men while interacting with an emotional voice. ConclusionsEmotional expressiveness in a female digital human has different effects on loneliness, social, and physiological outcomes for men and women. The results inform the design of digital human support persons and have theoretical implications. Further research is needed to evaluate how more pronounced emotional facial expressions in a digital human might affect the results. Trial RegistrationAustralia New Zealand Clinical Trials Registry (ANZCTR) ACTRN12621000865819; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=381816&isRevie

Comparing the Feasibility and Acceptability of a Virtual Human, Teletherapy, and an e-Manual in Delivering a Stress Management Intervention to Distressed Adult Women: Pilot Study

Virtual humans (VHs), teletherapy, and self-guided e-manuals may increase the accessibility of psychological interventions. However, there is limited research on how these technologies compare in terms of their feasibility and acceptability in delivering stress management interventions. We conducted a preliminary comparison of the feasibility and acceptability of a VH, teletherapy, and an e-manual at delivering 1 module of cognitive behavioral stress management (CBSM) to evaluate the feasibility of the trial methodology in preparation for a future randomized controlled trial (RCT). A pilot RCT was conducted with a parallel, mixed design. A community sample of distressed adult women were randomly allocated to receive 1 session of CBSM involving training in cognitive and behavioral techniques by a VH, teletherapy, or an e-manual plus homework over 2 weeks. Data were collected on the feasibility of the intervention technologies (technical support and homework access), trial methods (recruitment methods, questionnaire completion, and methodological difficulty observations), intervention acceptability (intervention completion, self-report ratings, therapist rapport, and trust), and acceptability of the trial methods (self-report ratings and observations). Qualitative data in the form of written responses to open-ended questions were collected to enrich and clarify the findings on intervention acceptability. Overall, 38 participants' data were analyzed. A VH (n=12), teletherapy (n=12), and an e-manual (n=14) were found to be feasible and acceptable for delivering 1 session of CBSM to distressed adult women based on the overall quantitative and qualitative findings. Technical difficulties were minimal and did not affect intervention completion, and no significant differences were found between the conditions (P=.31). The methodology was feasible, although improvements were identified for a future trial. All conditions achieved good satisfaction and perceived engagement ratings, and no significant group differences were found (P>.40). Participants had similar willingness to recommend each technology (P=.64). There was a nonsignificant trend toward participants feeling more open to using the VH and e-manual from home than teletherapy (P=.10). Rapport (P<.001) and trust (P=.048) were greater with the human teletherapist than with the VH. The qualitative findings enriched the quantitative results by revealing the unique strengths and limitations of each technology that may have influenced acceptability. A VH, teletherapy, and a self-guided e-manual were found to be feasible and acceptable methods of delivering 1 session of a stress management intervention to a community sample of adult women. The technologies were found to have unique strengths and limitations that may affect which works best for whom and in what circumstances. Future research should test additional CBSM modules for delivery by these technologies and conduct a larger RCT to compare their feasibility, acceptability, and effectiveness when delivering a longer home-based stress management program. Australian New Zealand Clinical Trials Registry ACTRN12620000859987; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380114&isReview=true

Effects of Cognitive Behavioral Stress Management Delivered by a Virtual Human, Teletherapy, and an E-Manual on Psychological and Physiological Outcomes in Adult Women: An Experimental Test

Technology may expand the reach of stress management to broader populations. However, issues with engagement can reduce intervention effectiveness. Technologies with highly social interfaces, such as virtual humans (VH), may offer advantages in this space. However, it is unclear how VH compare to telehealth and e-manuals at delivering psychological interventions. This experiment compared the effects of single laboratory session of Cognitive Behavioral Stress Management (CBSM) delivered by a VH (VH-CBSM), human telehealth (T-CBSM), and an e-manual (E-CBSM) on psychological and physiological outcomes in a community sample of stressed adult women. A pilot randomized controlled trial (RCT) with a parallel, mixed design was conducted. Adult women (M age =43.21, SD = 10.70) who self-identified as stressed were randomly allocated to VH-CBSM, T-CBSM, or E-CBSM involving one 90 min session and homework. Perceived stress, stress management skills, negative affect, optimism, relaxation, and physiological stress were measured. Mixed factorial ANOVAs and pairwise comparisons with Bonferroni correction investigated main and interaction effects of time and condition. Participants’ data (N = 38) were analysed (12 = VH-CBSM; 12 = T-CBSM; 14 = E-CBSM). Each condition significantly improved stress, negative affect, optimism, relaxation, and physiological stress over time with large effect sizes. No significant differences were found between conditions on outcomes. Overall, all three technologies showed promise for remotely delivering CBSM in a controlled setting. The findings suggest feasibility of the VH-CBSM delivery approach and support conducting a fully powered RCT to examine its effectiveness when delivering a full 10-week CBSM intervention

Relational agents and the mitigation of loneliness: protocol for a systematic review and meta-analysis

This review focuses specifically on loneliness (outcome) and comprises relational agents in multiple forms (social robotic and app-based)

Artificial intelligence for older people receiving long-term care:a systematic review of acceptability and effectiveness studies

Artificial intelligence (AI)-enhanced interventions show promise for improving the delivery of long-term care (LTC) services for older people. However, the research field is developmental and has yet to be systematically synthesised. This systematic review aimed to synthesise the literature on the acceptability and effectiveness of AI-enhanced interventions for older people receiving LTC services. We conducted a systematic search that identified 2720 records from Embase, Ovid, Global Health, PsycINFO, and Web of Science. 31 articles were included in the review that evaluated AI-enhanced social robots (n=22), environmental sensors (n=6), and wearable sensors (n=5) with older people receiving LTC services across 15 controlled and 14 non-controlled trials in high-income countries. Risk of bias was evaluated using the RoB 2, RoB 2 CRT, and ROBINS-I tools. Overall, AI-enhanced interventions were found to be somewhat acceptable to users with mixed evidence for their effectiveness across different health outcomes. The included studies were found to have high risk of bias which reduced confidence in the results. AI-enhanced interventions are promising innovations that could reshape the landscape of LTC globally. However, more trials are required to support their widespread implementation. Pathways are needed to support more high-quality trials, including in low-income and middle-income countries