Background: Social robots integrated with serious games hold promise as innovative nonpharmacological strategies in dementia care. However, limited studies have adopted quantitative, platform-level comparisons from the perspective of formal caregivers, who are key stakeholders in technology implementation in dementia care settings.
Objective: This study aimed to evaluate the feasibility, usability, and overall user experience of a serious game-based interaction model delivered via a screen-equipped social robot, compared to a tablet-based version of the same model, from the perspective of formal dementia caregivers.
Methods: A cross-sectional comparative study was conducted with 120 formal dementia caregivers. Each caregiver individually interacted with both a screen-equipped social robot and a touchscreen tablet, delivering identical serious game content incorporating cognitive exercises, music therapy, and reminiscence. The robot featured multimodal interaction capabilities, including voice, gestures, movement, and facial expression display, while the tablet relied on standard touchscreen functions. Caregivers evaluated both platforms using the User Experience Questionnaire (UEQ), System Usability Scale (SUS), and a customized Technology Acceptance Model (TAM). Group comparisons were performed using t tests, with post hoc Benjamini-Hochberg correction applied to control for multiple comparisons.
Results: Caregivers generally favored the social robot over the tablet. The robot received higher total UEQ scores (mean 1.29, SD 1.14, vs mean 0.99, SD 1.08; P=.004), particularly in enjoyment (P=.002), friendliness (P=.006), clarity (P=.002), organization (P=.02), interest (P=.01), and innovation (P=.002). In the SUS, caregivers rated the robot higher for quick learning (mean 2.71, SD 0.79 vs mean 2.44, SD 0.81; P=.002), while overall SUS scores were comparable. TAM results indicated higher total scores for the robot (mean 4.03, SD 0.47 vs mean 3.67, SD 0.58; P=.002), with stronger ratings in perceived usefulness (P=.002), ease of use (P=.002), attitudes (P=.002), and behavioral intentions (P=.002). All P values are from 2-tailed t tests and were adjusted using the Benjamini-Hochberg procedure.
Conclusions: The social robot used in this study was perceived by formal dementia caregivers as providing a more favorable user experience and eliciting a stronger intention to use compared to a tablet-based platform. These findings support the feasibility of social robots as a platform for delivering technology-supported activities in dementia care and provide a foundation for future research on their implementation and outcomes in dementia care.
Background: As virtual reality (VR) technology becomes increasingly prevalent, its potential for collecting objective behavioral data in psychiatric settings has been widely recognized. However, the lack of standardized methodologies limits reproducibility and data integration across studies, particularly in assessing attention-deficit/hyperactivity disorder (ADHD) and associated behaviors, such as irritability and aggression.
Objective: This study examines the use of VR-based movement data to operationalize core ADHD symptoms (hyperactivity and inattention) and comorbid disruptive behaviors (irritability and aggression), aiming to identify reproducible and clinically actionable metrics and evaluate their explanatory power for each symptom domain to assess the overall use of these variables.
Methods: A total of 45 children (mean age 9.06, SD 2.11 years; n=14/45, 31% female) participated in the study and were divided into 2 groups: 28 (62%) diagnosed with ADHD and 17 (38%) controls. Seven VR-derived movement variables were analyzed: average speed, acceleration, total distance, area occupied, distance between the hands and head, frequency of movement, and time spent still. Correlation and stepwise regression analyses identified which variables best predicted ADHD symptoms and comorbid behaviors.
Results: Among the 7 VR-derived variables, average speed (mean r=0.460, SD 0.097) and total distance (mean r=0.442, SD 0.116) showed the broadest associations, each correlating with 8 measures. In contrast, frequency of movement was related only to hyperactivity (r=0.416; P=.004), suggesting strong but narrow predictive value. Stepwise regression identified total distance as the sole and strongest predictor of hyperactivity (R2=0.411) and, except for participant-reported irritability, yielded significant models for all other measures (mean R2=0.282, SD 0.064; all P<.05).
Conclusions: This study provides empirical evidence on VR-derived movement variables that can inform the development of standardized methodologies for ADHD and comorbid behavior assessment. The identified metrics and their predictive patterns offer a basis for integrating VR-based measures into future research and clinical applications.
Background: Dementia is a progressive neurodegenerative condition marked by cognitive decline and loss of functional independence. Among cognitive domains, executive dysfunction is a critical early contributor to reduced self-care capacity and increased caregiver burden. While cognitive assistive technologies have focused primarily on memory, few tools address executive function in real-time, daily tasks. To fill this gap, we developed a novel gamified cognitive prosthesis that integrates artificial intelligence (AI) and computer vision to guide users step-by-step through a simulated egg-cooking task. This system provides real-time audiovisual feedback to support planning, sequencing, and error correction.
Objective: This study aimed to evaluate whether the AI-based cognitive prosthesis improves task completion time and executive function performance in individuals with mild dementia.
Methods: We conducted a pilot study involving 12 patients with mild dementia and 7 age-matched healthy controls. Participants were asked to complete a 6-step gamified egg boiling task under 2 conditions: with and without guidance. The task was evaluated using a custom "Daily Task Completion Test" and a modified executive function performance test (EFPT) adapted to the cooking activity. Demographic and clinical data (age, sex, education, Mini-Mental State Examination, Clinical Dementia Rating, activities of daily living, instrumental activities of daily living, and Dementia Severity Rating Scale) were recorded. The System Usability Scale (SUS) was also collected postintervention.
Results: In the mild dementia group, AI assistance significantly reduced median task completion time from 134.75 (IQR 92.50-134.75) to 92.00 (IQR 65.00-92.00; P=.03) seconds, and significantly improved the Executive Function Performance Test (EFPT) scores from 4.25 (IQR 1.75-4.25) to 1.00 (IQR 0.00-1.00; P=.005), reflecting a 31.7% improvement in efficiency and a 76.5% reduction in required assistance. No significant changes were observed in the control group. The mean SUS score was 80.53 (SD 24.97), indicating high usability. The AI system achieved a cumulative recognition precision of 0.93 (SD 0.07) and cumulative recall of 0.94 (SD 0.11).
Conclusions: This pilot study provides preliminary evidence that an AI-based cognitive prosthesis can enhance executive function and task performance in individuals with mild dementia. The results support the feasibility of using real-time AI guidance in everyday tasks to promote independence. Given its modular design and promising usability profile, this system may serve as the foundation for future digital therapeutics targeting executive dysfunction. Larger, longitudinal studies are warranted to evaluate sustained cognitive and functional benefits.
Background: Schizophrenia is a severe mental illness that affects the cognitive, social, and daily functions of patients. Physical activity has been found to be important for maintaining these functions in patients with schizophrenia, but many lack the motivation to participate in physical activities.
Objective: This study aimed to explore the efficacy of active video games (AVGs) on the behavioral intention and cognitive function of patients with schizophrenia.
Methods: In this experimental study, 103 participants were recruited from 2 medical centers. All participants were randomly assigned to the experimental or control group, and 82 participants (n=41, 50% in the experimental group and n=41, 50% in the control group) completed all the processes of our protocol. The experimental group was provided with AVGs for 30 minutes twice per week for 6 weeks. The Mini Mental State Examination and a behavioral intention questionnaire were administered before and after playing the AVGs. Data were collected between April 2021 and January 2022. Generalized estimating equations and 2-tailed paired t tests were used for data analysis.
Results: The experimental group showed significant improvements in behavioral intention to participate in AVGs compared with the control group at both T1 (β=4.88; P=.009) and T2 (β=4.24; P=.04). In addition, the experimental group experienced significant improvements in orientation (T2: β=0.66; P=.04) and language (T2: β=0.28; P=.03) among cognitive functions compared to the control group. In contrast, there was no significant change in these variables in the control group.
Conclusions: Playing AVGs can effectively enhance the behavioral intention of patients with schizophrenia to participate in physical activity and exercise and significantly improve their orientation and language. AVGs are inexpensive and easily operated tools for people with mental or physical disabilities.
Trial registration: ClinicalTrials.gov NCT05933356; https://clinicaltrials.gov/study/NCT05933356.
Background: Online games developed to improve mental health symptoms are reportedly effective among game users. However, it has not been verified whether massive multiplayer online games (MMOGs) developed for leisure purposes are effective in improving users' mental health symptoms.
Objective: Based on 2 theoretical frameworks, this study examined whether MMOGs improve depression and social anxiety. First, behavioral activation theory posits that depressive symptoms improve through the repetition of reward-linked behaviors. Second, inhibitory learning theory suggests that exposure to social stimuli (eg, being the center of attention) previously perceived as threatening reduces fear responses over time.
Methods: Participants were Pigg Party users with at least 3 months of previous experience. Overall, 1105 participants were randomly assigned to either the experimental (n=548) or waitlist groups (n=557). Participants in the experimental group were instructed to ring a friend's room bell (an action that clearly draws attention) on weekdays and to customize their avatars on weekends. Those completing ≥60% of the tasks received additional monthly rewards. The waitlist group received no interventions but was given random additional rewards. Both groups completed questionnaires on depression (Quick Inventory of Depressive Symptomatology) and social anxiety (Brief Liebowitz Social Anxiety Scale) at baseline, and again at 1, 2, and 3 months.
Results: The experimental group showed a significantly higher frequency of bell ringing compared to that of the waitlist group (standardized mean difference [SMD]=0.13), whereas no significant difference was observed between the groups in avatar customization frequency. As predicted, the experimental group showed a significantly greater reduction in depressive symptoms, with a small effect size observed (SMD=-0.12). However, no significant difference was determined between groups in social anxiety symptoms.
Conclusions: This study demonstrated that MMOGs, when combined with administrator-led interventions, can reduce users' depressive symptoms, albeit with a small effect size. Further studies are needed to test the intervention effects on social anxiety symptoms in MMOGs, with improved exposure scenarios.
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