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Background:Health systems are in the need for novel approaches to tackle the challenges from the demographic transition to ageing populations. An effective approach to face these challenges is integrated care delivery. Implementing Comprehensive Geriatric Assessments (CGAs) in Health Ageing might be highly relevant to incorporate this approach. However, this implementation should be supported by Digital Health Interventions (DHIs) in order to reach their full capacity.Research Objective:To identify the DHIs facilitating the administration of CGAs used in long-term care and home care settings and provide an insight on their characteristics and stage of maturity and evaluation.Method:A search strategy was conducted in PubMed, CINAHL, and Web of Science, targeting studies evaluating the DHIs facilitating the administration of CGAs used in long-term care and home care settings. Studies in English and Spanish and published up to July 26, 2021 were considered.Preliminary results of the ongoing study:A total of four papers describing three digital platforms supporting the administration of the CGAs were identified. Information on implementation reported less completion of some sections affecting the CGAs outcomes, assessments mostly being the responsibility of nurses, and missing data related with less quality of care. Limitations and barriers regarding their usability and feasibility were also identified.Conclusion:The inclusion of safe data storage, automatic notifications for assessment completion, automatic calculation of final outcomes, and facilitation of multidisciplinary assessments, were identified as key features to enhance the implementation of digital platforms facilitating the administration of CGAs. Nonetheless, information regarding technical features and hardware information of the digital platforms was scarce.This project is part of the Marie Skłodowska Curie Actions Innovative Training Network H2020-MSCA-ITN, under grant agreement number 813196

Background:In a search for innovative dementia care strategies, a new research fields have been dedicated to design social robots for older adults with cognitive impairments and dementia in order to promote their quality of life through communication and social interactions. Although the results are promising, the quality of studies on effectiveness of social robots in elderly adults is still low due to several methodological limitations (1). Then, we aim to review the methodologies used so far for conducting studies with social robots in clinical and social settings with people with dementia and elderly adults.Method:Searches in Medline (PubMed), Web of Science, PsycInfo, and Cinahl yielded 33 studies included in the final review after applying inclusion and exclusion criteria. Reviews were conducted by two authors independently.Result:Across 33 papers, 23 different social robots were examined on elderly adults and PwD, investigating feasibility, usability and effectiveness. A variety of study designs such as RCTs, mixed methods, cross-sectional and cohort were employed. Individual and group-based interventions took place in private households, LTCFs and labs within a single session or multiple sessions. Data were collected through observation, questionnaires, interview and physiological tests. Most revealed improvements were found in mood, engagement and participation. However, improvements in QoL, depression and cognition were not significant.Conclusion:Despite the promising results, due to the insufficient methodology, failures and ambitious findings remain within the many aspects of the enquiry. Appropriate RCT designs with large sample sizes and individual intervention sessions might be established for effectiveness studies. For feasibility/usability studies, a cohort design with long-term intervention would serve best. We also recommend a mixed method of data collection for any of three effectiveness, feasibility and usability study aims. Multiple interaction sessions running for more than one month might help researches to draw significant results and reveal the long-term impact of the robots.