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COVID-19 has severely impacted mental health in vulnerable demographics, in particular older adults, who face unprecedented isolation. Consequences, while globally severe, are acutely pronounced in low- and middle-income countries (LMICs) confronting pronounced gaps in resources and clinician accessibility. Social robots are well-recognized for their potential to support mental health, yet user compliance (i.e., trust) demands seamless affective human-robot interactions; natural ‘human-like’ conversations are required in simple, inexpensive, deployable platforms. We present the design, development, and pilot testing of a multimodal robotic framework fusing verbal (contextual speech) and nonverbal (facial expressions) social cues, aimed to improve engagement in human-robot interaction and ultimately facilitate mental health telemedicine during and beyond the COVID-19 pandemic. We report the design optimization of a hybrid face robot, which combines digital facial expressions based on mathematical affect space mapping with static 3D facial features. We further introduce a contextual virtual assistant with integrated cloud-based AI coupled to the robot’s facial representation of emotions, such that the robot adapts its emotional response to users’ speech in real-time. Experiments with healthy participants demonstrate emotion recognition exceeding 90% for happy, tired, sad, angry, surprised and stern/disgusted robotic emotions. When separated, stern and disgusted are occasionally transposed (70%+ accuracy overall) but are easily distinguishable from other emotions. A qualitative user experience analysis indicates overall enthusiastic and engaging reception to human-robot multimodal interaction with the new framework. The robot has been modified to enable clinical telemedicine for cognitive engagement with older adults and people with dementia (PwD) in LMICs. The mechanically simple and low-cost social robot has been deployed in pilot tests to support older individuals and PwD at the Schizophrenia Research Foundation (SCARF) in Chennai, India. A procedure for deployment addressing challenges in cultural acceptance, end-user acclimatization and resource allocation is further introduced. Results indicate strong promise to stimulate human-robot psychosocial interaction through the hybrid-face robotic system. Future work is targeting deployment for telemedicine to mitigate the mental health impact of COVID-19 on older adults and PwD in both LMICs and higher income regions.

This feasibility and pilot study aimed to develop and field-test a 14-session virtual Cognitive Stimulation Therapy (vCST) programme for people living with dementia, developed as a result of services moving online during the COVID-19 pandemic. Methods: The vCST protocol was developed using the existing group CST manual, through stakeholder consultation with people living with dementia, caregivers, CST group facilitators and dementia service managers. This protocol was then field-tested with 10 groups of people living with dementia in the Brazil, China (Hong Kong), India, Ireland and the UK, and feedback on the protocol was gathered from 14 facilitators. Results: Field testing in five countries indicated acceptability to group facilitators and participants. Feedback from these groups was used to refine the developed protocol. The final vCST protocol is proposed, including session materials for delivery of CST over videoconferencing and a framework for offering CST virtually in global settings. Conclusion: vCST is a feasible online intervention for many people living with dementia. We recommend that it is offered to those unable to access traditional in-person CST for health reasons, lack of transport or COVID-19 restrictions. Further research is needed to explore if participant outcomes are comparable to in-person CST groups.

The World Alzheimer's Report estimates that 4.1 million people in India have dementia. Caregivers of persons with dementia face physical, psychological, social and financial problems related to caring for a person with dementia. Literature on the caregiving experience however is highly specific to the sociocultural context and cannot be generalized. In low and middle income countries much of the caregiving takes place in people's homes and is provided by family caregivers. Aim This study aims to explore the needs and challenges of family caregivers in Chennai, India. Method Focus group discussions and in-depth interviews were conducted using a topic guide. Participants were divided based on socio-economic status to ensure homogeneity. An inductive thematic approach was used to analyse and code the data. A total of 19 participants took part in the study. Results The results capture the experience of caregivers of persons with dementia in seeking help and accessing treatment. Priority caregiver needs were identified, including the need for sensitised, skilled health workers, information on dementia and advanced care needs and cost effective services. Conclusion The findings of this study strongly support the need to strengthen health systems capacity, make the health care services dementia friendly and cost effective. The influence of culture in shaping help seeking was evident in our findings. Interventions for caregivers and persons with dementia need to be developed and tested so they might be made fit for purpose and scaled up. It will be important to identify how these services can be adapted for use in low and middle income country resource setting like India.

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