Background: Loneliness 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.
Objective: The 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.
Methods: A 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.
Results: The 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.
Conclusions: Digital 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 Registration: Australia New Zealand Clinical Trials Registry ACTRN12620000786998; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380113

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.

A growing shortfall exists between the number of older individuals who require healthcare support and the number of qualified healthcare professionals who can provide this. Robots offer the potential to provide healthcare support to patients both at home and in healthcare settings. However, in order for robots to be successfully implemented in these environments, they need to behave in ways that are appropriate and acceptable to human users. One way to identify appropriate social behaviours for healthcare robots is to model their behaviour on interactions between healthcare professionals and patients. This literature review aimed to inform healthcare robotics research by highlighting communication behaviours that are important within the context of healthcare. The review focussed on relevant research in human clinical interactions, followed by a review of similar factors in social robotics research. Three databases were searched for terms relating to healthcare professional communication behaviours associated with patient outcomes. The results identified key communication behaviours that can convey clinical empathy, including humour, self-disclosure, facial expressions, eye gaze, body posture, and gestures. A further search was conducted to identify research examining these key behaviours within the context of social and healthcare robotics. Research into these factors in human–robot interaction in healthcare is limited to date, and this review provides a useful guide for future research.

Improving Interactions with Healthcare Robots: A Review of Communication Behaviours in Social and Healthcare Contexts

Body surface gastric mapping (BSGM) is a new clinical tool for gastric motility diagnostics, providing high‐resolution data on gastric myoelectrical activity. Artifact contamination was a key challenge to reliable test interpretation in traditional electrogastrography. This study aimed to introduce and validate an automated artifact detection and rejection system for clinical BSGM applications.

An automated artifact detection and rejection system for body surface gastric mapping

Social cues and implications for designing expert and competent artificial agents: A systematic review

INTRODUCTION: Body surface gastric mapping (BSGM) is a new noninvasive test of gastric function. BSGM offers several novel and improved biomarkers of gastric function capable of differentiating patients with overlapping symptom profiles. The aim of this study was to define normative reference intervals for BSGM spectral metrics in a population of healthy controls. METHODS: BSGM was performed in healthy controls using Gastric Alimetry (Alimetry, New Zealand) comprising a stretchable high-resolution array (8 × 8 electrodes; 196 cm2), wearable Reader, and validated symptom-logging App. The evaluation encompassed a fasting baseline (30 minutes), 482 kCal meal, and 4-hour postprandial recording. Normative reference intervals were calculated for BSGM metrics including the Principal Gastric Frequency, Gastric Alimetry Rhythm Index (a measure of the concentration of power in the gastric frequency band over time), body mass index (BMI)–adjusted amplitude (μV), and fed:fasted amplitude ratio. Data were reported as median and reference interval (5th and/or 95th percentiles). RESULTS: A total of 110 subjects (55% female, median age 32 years [interquartile range 24–50], median BMI 23.8 kg/m2 [interquartile range 21.4–26.9]) were included. The median Principal Gastric Frequency was 3.04 cycles per minute; reference interval: 2.65–3.35 cycles per minute. The median Gastric Alimetry Rhythm Index was 0.50; reference interval: ≥0.25. The median BMI-adjusted amplitude was 37.6 μV; reference interval: 20–70 μV. The median fed:fasted amplitude ratio was 1.85; reference interval ≥1.08. A higher BMI was associated with a shorter meal-response duration (P = 0.014). DISCUSSION: This study provides normative reference intervals for BSGM spectral data to inform diagnostic interpretations of abnormal gastric function.

Normative Values for Body Surface Gastric Mapping Evaluations of Gastric Motility Using Gastric Alimetry: Spectral Analysis

Embodied conversational agents (ECAs) are increasingly used in healthcare and other settings to improve self-management and provide companionship. Their ability to form close relationships with people is important for enhancing effectiveness and engagement. Several studies have looked at enhancing relationships with ECAs through design features focused on behaviours, appearance, or language. However, this evidence is yet to be systematically synthesized. This systematic review evaluates the effect of different design features on relationship quality with ECAs. A systematic search was conducted on electronic databases EMBASE, PsychInfo, PubMed, MEDLINE, Cochrane Library, SCOPUS, and Web of Science in January–February 2019. 43 studies were included for review that evaluated the effect of a design feature on relationship quality and social perceptions or behaviours towards an ECA. Results synthesize effective design features and lay a scientific framework for improving relationships with ECAs in healthcare and other applications. Risk of bias for included studies was generally low, however there were some limitations in the research quality pertaining to outcome measurement and the reporting of statistics. Further research is needed to understand how to make ECAs effective and engaging for all consumers.

The Effect of Design Features on Relationship Quality with Embodied Conversational Agents: A Systematic Review

As we approach a time in which social robots will be used in home and healthcare settings, there is a critical need to research robot behaviors that can increase user acceptance and comfort. The use of humor by physicians during patient interactions is associated with a number of positive patient health outcomes. However, no research to date has examined the effect of humor on user outcomes when used by a healthcare robot. This study examined the use of humor by a healthcare robot in a scripted interaction in a simulated medical setting. An experiment was conducted with 91 healthy participants (73 female, mean age 25 years). Participants were randomly allocated to interact with either a humorous or neutral robot in a flu vaccination scenario. Perceptions of the robot were assessed using the Godspeed questionnaire, an empathy questionnaire, and Asch personality scale, at two time points (before and after the interaction). Participant laughing was observed during the interaction. Repeated measures between group ANOVA showed that robot use of humor resulted in significantly greater perceptions of the robot’s likeability and safety. The humorous robot was also rated as having significantly more empathy, and a more sociable personality. Participants in the humorous condition were also more likely to rate the robot’s personality as happy, talkative, and frivolous, compared to participants in the neutral condition. Significantly more participants laughed during the interaction with the humorous robot, than with the neutral robot. Together, these findings suggest that the use of humor by a healthcare robot may increase positive user evaluations. This research has implications for both theory and clinical applications.

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Use of Humor by a Healthcare Robot Positively Affects User Perceptions and Behavior

BackgroundFunctional gastroduodenal disorders include functional dyspepsia, chronic nausea and vomiting syndromes, and gastroparesis. These disorders are common, but their overlapping symptomatology poses challenges to diagnosis, research, and therapy. This study aimed to introduce and validate a standardized patient symptom-logging system and App to aid in the accurate reporting of gastroduodenal symptoms for clinical and research applications. MethodsThe system was implemented in an iOS App including pictographic symptom illustrations, and two validation studies were conducted. To assess convergent and concurrent validity, a diverse cohort with chronic gastroduodenal symptoms undertook App-based symptom logging for 4-hours after a test meal. Individual and total post-prandial symptom scores were averaged and correlated against two previously validated instruments: PAGI-SYM (for convergent validity) and PAGI-QOL (for concurrent validity). To assess face and content validity, semi-structured qualitative interviews were conducted with patients. Key ResultsApp-based symptom reporting demonstrated robust convergent validity with PAGI-SYM measures of nausea (rS=0.68), early satiation (rS=0.55), bloating (rS=0.48), heartburn (rS=0.47), upper gut pain (rS=0.40) and excessive fullness (rS=0.40); all p<0.001 (n=79). The total App-reported Gastric Symptom Burden Score correlated positively with PAGI-SYM (rS=0.56; convergent validity; p<0.001), and negatively with PAGI-QOL (rS=-0.34; concurrent validity; p=0.002). Interviews demonstrated that the pictograms had adequate face and content validity. Conclusions and InferencesThe continuous patient symptom-logging App demonstrated robust convergent, concurrent, face, and content validity when used within a 4-hour post-prandial test protocol. The App will enable standardized symptom reporting and is anticipated to provide utility in both research and clinical practice.

https://medrxiv.org/content/10.1101/2021.09.06.21263001v1.full.pdf

Gabrielle Sebaratnam

Papers

The Effect of Design Features on Relationship Quality with Embodied Conversational Agents: A Systematic Review

An automated artifact detection and rejection system for body surface gastric mapping

Use of Humor by a Healthcare Robot Positively Affects User Perceptions and Behavior

A standardized system and App for continuous patient symptom logging in gastroduodenal disorders: design, implementation, and validation

306: the impact of sleeve gastrectomy on the gastric conduction system measured by body surface gastric mapping