This paper presents and evaluates a novel approach for automatically recommending multimedia content for use in group reminiscence therapy for people with Alzheimer's and other dementias. In recent years recommender systems have seen popularity in providing a personalised experience in information discovery tasks. This personalisation approach is naturally suited to tasks in healthcare, such as reminiscence therapy, where there has been a trend towards an increased emphasis on person-centred care. Building on recent work which has shown benefits to reminiscence therapy in a group setting, we develop and evaluate a system, REMPAD, which profiles people with Alzheimer's and other dementias, and provides multimedia content tailored to a given group context. In this paper we present our system and approach, and report on a user trial in residential care settings. In our evaluation we examine the potential to use early-aggregation and late-aggregation of group member preferences using case-based reasoning combined with a content-based method. We evaluate with respect to accuracy, utility and perceived usefulness. The results overall are positive and we find that our best-performing approach uses early aggregation CBR combined with a content-based method. Also, under different evaluation criteria, we note different performances, with certain configurations of our approach providing better accuracy and others providing better utility. © 2013 ACM.