Background: The present study investigates the suitability of various treatment outcome indicators to evaluate performance of mental health institutions that provide care to patients with severe mental illness. Several categorical approaches are compared to a reference indicator (continuous outcome) using pretest-posttest data of the Health of Nation Outcome Scales (HoNOS). Methods: Data from 10 institutions and 3189 patients were used, comprising outcomes of the first year of treatment by teams providing long-term care. Results: Findings revealed differences between continuous indicators (standardized pre-post difference score ES and ΔT) and categorical indicators (SEM, JTRCI, JTCS, JTRCI&CS, JTrevised) on their ranking of institutions, as well as substantial differences among categorical indicators; the outcome according to the traditional JT approach was most concordant with the continuous outcome indicators. Conclusions: For research comparing group averages, a continuous outcome indicator such as ES or ΔT is preferred, as this best preserves information from the original variable. Categorical outcomes can be used to illustrate what is accomplished in clinical terms. For categorical outcome, the classical Jacobson-Truax approach is preferred over the more complex method of Parabiaghi et al. with eight outcome categories. The latter may be valuable in clinical practice as it allows for a more detailed characterization of individual patients.
Existing research on the recognition of Activities of Daily Living (ADL) from simple sensor networks assumes that only a single person is present in the home. In real life there will be situations where the inhabitant receives visits from family members or professional health care givers. In such cases activity recognition is unreliable. In this paper, we investigate the problem of detecting multiple persons in an environment equipped with a sensor network consisting of binary sensors. We conduct a real-life experiment for detection of visits in the oce of the supervisor where the oce is equipped with a video camera to record the ground truth. We collected data during two months and used two models, a Naive Bayes Classier and a Hidden Markov Model for a visitor detection. An evaluation of these two models shows that we achieve an accuracy of 83% with the NBC and an accuracy of 92% with a HMM, respectively.
MULTIFILE
The psychosocial consequences of growing up with Heritable Connective Tissue Disorders (HCTD) are largely unknown. We aimed to assess Health-Related Quality of Life (HRQoL) and mental health of children and adolescents with HCTD. This observational multicenter study included 126 children, aged 4–18 years, with Marfan syndrome (MFS, n = 74), Loeys–Dietz syndrome (n = 8), molecular confirmed Ehlers–Danlos syndromes (n = 15), and hypermobile Ehlers–Danlos syndrome (hEDS, n = 29). HRQoL and mental health were assessed through the parent and child-reported Child Health Questionnaires (CHQ-PF50 and CHQ-CF45, respectively) and the parent-reported Strengths and Difficulties Questionnaire. Compared with a representative general population sample, parent-reported HRQoL of the HCTD-group showed significantly decreased Physical sum scores (p < 0.001, d = 0.9) and Psychosocial sum scores (p = 0.024, d = 0.2), indicating decreased HRQoL. Similar findings were obtained for child-reported HRQoL. The parent-reported mental health of the HCTD-group showed significantly increased Total difficulties sum scores (p = 0.01, d = 0.3), indicating decreased mental health. While the male and female MFS- and hEDS-subgroups both reported decreased HRQoL, only the hEDS-subgroup reported decreased mental health. In conclusion, children and adolescents with HCTD report decreased HRQoL and mental health, with most adverse outcomes reported in children with hEDS and least in those with MFS. These findings call for systematic monitoring and tailored interventions.
