For robots to interact effectively with human users they must be capable of coordinated, timely behavior in response to social context. The Adaptive Strategies for Sustainable Long-Term Social Interaction (ALIZ-E) project focuses on the design of long-term, adaptive social interaction between robots and child users in real-world settings. In this paper, we report on the iterative approach taken to scientific and technical developments toward this goal: advancing individual technical competencies and integrating them to form an autonomous robotic system for evaluation "in the wild." The first evaluation iterations have shown the potential of this methodology in terms of adaptation of the robot to the interactant and the resulting influences on engagement. This sets the foundation for an ongoing research program that seeks to develop technologies for social robot companions.

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ObjectivesPopulation-based health risk assessment and stratification are considered highly relevant for large-scale implementation of integrated care by facilitating services design and case identification. The principal objective of the study was to analyse five health-risk assessment strategies and health indicators used in the five regions participating in the Advancing Care Coordination and Telehealth Deployment (ACT) programme (http://www.act-programme.eu). The second purpose was to elaborate on strategies toward enhanced health risk predictive modelling in the clinical scenario.SettingsThe five ACT regions: Scotland (UK), Basque Country (ES), Catalonia (ES), Lombardy (I) and Groningen (NL).ParticipantsResponsible teams for regional data management in the five ACT regions.Primary and secondary outcome measuresWe characterised and compared risk assessment strategies among ACT regions by analysing operational health risk predictive modelling tools for population-based stratification, as well as available health indicators at regional level. The analysis of the risk assessment tool deployed in Catalonia in 2015 (GMAs, Adjusted Morbidity Groups) was used as a basis to propose how population-based analytics could contribute to clinical risk prediction.ResultsThere was consensus on the need for a population health approach to generate health risk predictive modelling. However, this strategy was fully in place only in two ACT regions: Basque Country and Catalonia. We found marked differences among regions in health risk predictive modelling tools and health indicators, and identified key factors constraining their comparability. The research proposes means to overcome current limitations and the use of population-based health risk prediction for enhanced clinical risk assessment.ConclusionsThe results indicate the need for further efforts to improve both comparability and flexibility of current population-based health risk predictive modelling approaches. Applicability and impact of the proposals for enhanced clinical risk assessment require prospective evaluation.

BackgroundAccording to the World Alzheimer Report (Prince, The Global Impact of Dementia: an Analysis of Prevalence, Incidence, Cost and Trends, 2015), 46.8 million people worldwide are nowadays living with dementia. And this number is estimated to approximate 131.5 million by 2050, with an increasing burden on society and families. The lack of medical treatments able to stop or slow down the course of the disease has moved the focus of interest toward the nonpharmacological approach and psychosocial therapies for people with/at risk of dementia, as in the Mild Cognitive Impairment (MCI) condition. The purpose of the present study is to test an individualized home-based multidimensional program aimed at enhancing the continuum of care for MCI and outpatients with dementia in early stage using technology.MethodsThe proposed study is a single blind randomized controlled trial (RCT) involving 30 subjects with MCI and Alzheimer’s disease (AD) randomly assigned to the intervention group (Ability group), who will receive the “Ability Program”, or to the active control group (ACG), who will receive “Treatment As Usual” (TAU). The protocol provides for three steps of assessment: at the baseline (T_0), after treatment, (T_1) and at follow-up (T_2) with a multidimensional evaluation battery including cognitive functioning, behavioral, functional, and quality of life measures. The Ability Program lasts 6 weeks, comprises tablet-delivered cognitive (5 days/week) and physical activities (7 days/week) combined with a set of devices for the measurement and monitoring from remote of vital and physical health parameters. The TAU equally lasts 6 weeks and includes paper and pencil cognitive activities (5 days/week), with clinician’s prescription to perform physical exercise every day and to monitor selected vital parameters.DiscussionResults of this study will inform on the efficacy of a technology-enhanced home care service to preserve cognitive and motor levels of functioning in MCI and AD, in order to slow down their loss of autonomy in daily life. The expected outcome is to ensure the continuity of care from clinical practice to the patient’s home, enabling also cost effectiveness and the empowerment of patient and caregiver in the care process, positively impacting on their quality of life.Trial registrationClinicalTrials.gov ID: NCT02746484 (registration date: 12/apr/2016 – retrospectively registered).

Background: In allergic rhinitis, a relevant outcome providing information on the effectiveness of interventions is needed. In MASK-air (Mobile Airways Sentinel Network), a visual analogue scale (VAS) for work is used as a relevant outcome. This study aimed to assess the performance of the work VAS work by comparing VAS work with other VAS measurements and symptom-medication scores obtained concurrently. Methods: All consecutive MASK-air users in 23 countries from 1 June 2016 to 31 October 2018 were included (14 189 users; 205 904 days). Geolocalized users selfassessed daily symptom control using the touchscreen functionality on their smart phone to click on VAS scores (ranging from 0 to 100) for overall symptoms (global), nose, eyes, asthma and work. Two symptom-medication scores were used: the modified EAACI CSMS score and the MASK control score for rhinitis. To assess data quality, the intra-individual response variability (IRV) index was calculated. Results: A strong correlation was observed between VAS work and other VAS. The highest levels for correlation with VAS work and variance explained in VAS work were found with VAS global, followed by VAS nose, eye and asthma. In comparison with VAS global, the mCSMS and MASK control score showed a lower correlation with VAS work. Results are unlikely to be explained by a low quality of data arising from repeated VAS measures. Conclusions: VAS work correlates with other outcomes (VAS global, nose, eye and asthma) but less well with a symptom-medication score. VAS work should be considered as a potentially useful AR outcome in intervention studies.