Experiences of Psychiatric Day-Care Patients during the Introductory Period in Japan

Psychiatric day care plays an important role as transitional support after discharge in Japan. However, interruption rate of the day care treatment is high during the introductory period. The purpose of this study was to clarify the experiences of psychiatric day-care patients during the introductory period and find an approach to care. A qualitative study with thirteen patients at the introductory period was designed to explore participant’s experiences through semi-structured interviews. At first, patients were confused about their attitude because they paid attention to themselves, and consequently closed their involvement with others. However, through therapeutic day care activities, they attempted to adapt themselves and gradually turned their attention toward others and accumulated interpersonal experiences. As interactions with others became more frequent, they became conscious of themselves and others. Finally, while having worries about the future, they looked toward recovery and became aware that they were changing. Experiences of patients during the introductory period were essential to their recovery and gave meaning to their day care usage. Nurses should collaborate with patients to determine whether day care would serve to open a patient’s life to new possibilities.

A Neural Paradigm forTime-Varying Motion Segmentation

This paper proposes a new neural algorithm to perform the segmentation of an observed scene into regions corresponding to different moving objects byanalyzing a time-varying images sequence. The method consists of a classificationstep, where the motion of small patches is characterized through an optimizationapproach, and a segmentation step merging neighboring patches characterized bythe same motion. Classification of motion is performed without optical flow computation, but considering only the spatial and temporal image gradients into anappropriate energy function minimized with a Hopfield-like neural network givingas output directly the 3D motion parameter estimates. Network convergence is accelerated by integrating the quantitative estimation of motion parameters with aqualitative estimate of dominant motion using the geometric theory of differentialequations.