We evaluated the seal-like robot PARO in the context of multi-sensory behavioral therapy in a local nursing home. Participants were 10 elderly nursing home residents with varying levels of dementia. We report three principle findings from our observations of interactions between the residents, PARO, and a therapist during seven weekly therapy sessions. Firstly, we show PARO provides indirect benefits for users by increasing their activity in particular modalities of social interaction, including visual, verbal, and physical interaction, which vary between primary and non-primary interactors. Secondly, PARO's positive effects on older adults' activity levels show steady growth over the duration of our study, suggesting they are not due to short-term “novelty effects.” Finally, we show a variety of ways in which individual participants interacted with PARO and relate this to the “interpretive flexibility” of its design.

The use of scientific quantitative methods to support decision making is becoming necessary in healthcare systems, especially for Health Technology Assessment (HTA), which is a particularly complex decision making processes. This paper, after introducing three case studies in which the AHP was used to elicit user needs, generalize the method employed, provides recommendations and discusses critical methodological aspects, which the authors consider crucial when applying AHP to user need elicitation studies in HTA. The users of medical devices can include patients, healthcare professionals (with very different specializations), hospital managers, politician and general public. The AHP proved to be an effective method to elicit user needs, especially if some adjustments to the hierarchy design and to the questionnaires layout are followed.

This paper presents an integrated geographical (‘sp atially explicit’) and multivariate approach to add ress complex planning situations for wildlife conservati on and assist decision-making. Geographic Information System (GIS) and Analytic Hierarchy Pro cess (AHP) were combined and applied to ecological and decisional variables and their assoc iati n with known occurrences of barn owls ( Tyto alba) in an area of Wales (UK). The output is presented as geographic distribution maps showing the environmental conditions that are potentially suita ble for the species and ‘heat maps’ for the benefit of decision-making process. The application of the AHP allowed a detailed understanding of how the relative importance of each variable was elicited. This is paramount to define a fully understandable framework of decision-making that can be easily rea dapted to different geographical scenarios and with different species.