Background: The aim was to examine the longitudinal occurrence and persistence of behavioural and psychological symptoms of dementia (BPSD) in Alzheimer’s disease (AD). Methods: Following 60 patients with mild to severe AD over a period of 2 years with annual evaluations, the prospective occurrence and persistence of BPSD in AD were determined by using the Behavioural Abnormalities in AD Rating scale (BEHAVE-AD). Clinical and demographic features of the AD patients were analysed for their association with course features of these symptoms. Results: All of the 60 AD patients experienced BPSD at some point during the 2-year period, particularly agitation was present in every patient within this period. 2-year persistence of BPSD in AD was frequently observed in patients with agitation and with depressiveness, with less frequency in patients with anxiety and aggressiveness, but not in patients with delusions or hallucinations. 2-year persistent aggressiveness was associated with older age and more functional impairment. More functional impairment was also related to 2-year non-persistent hallucinations. Conclusions: Counselling AD patients and their families and tailoring therapeutic strategies should take into account the different modi of BPSD in AD occurring and persisting longitudinally and interacting with functional disturbances.

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Designing effective model-based reinforcement learning algorithms is difficult because the ease of data generation must be weighed against the bias of modelgenerated data. In this paper, we study the role of model usage in policy optimization both theoretically and empirically. We first formulate and analyze a model-based reinforcement learning algorithm with a guarantee of monotonic improvement at each step. In practice, this analysis is overly pessimistic and suggests that real off-policy data is always preferable to model-generated on-policy data, but we show that an empirical estimate of model generalization can be incorporated into such analysis to justify model usage. Motivated by this analysis, we then demonstrate that a simple procedure of using short model-generated rollouts branched from real data has the benefits of more complicated model-based algorithms without the usual pitfalls. In particular, this approach surpasses the sample efficiency of prior model-based methods, matches the asymptotic performance of the best model-free algorithms, and scales to horizons that cause other model-based methods to fail entirely.Preprint. Under review.

Objective: To evaluate a novel specific psychological intervention aimed at improving coping in patients with systemic lupus erythematosus (SLE). Methods: 34 community living SLE patients were recruited for the study. Intervention was undertaken in groups of up to eight patients and in two blocks over six months each. Eight patients were enrolled as a waiting list group. The 18 group sessions focused on information about the disease and specific problems of SLE patients, combining psychoeducative and psychotherapeutic elements. Psychological and medical evaluations were conducted at baseline and after three, six, and 12 months, using validated instruments. Results: The 34 SLE patients (91% female, mean age 42 years) improved significantly over a six month period on most of the psychological measuring instruments applied, such as depression, anxiety, and overall mental burden. The waiting list group showed no significant changes. Conclusions: Conceptualised psychoeducational support may produce a significant and sustained improvement in coping skills of SLE patients and hence in their quality of life.

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