Large-Scale Land Acquisitions

This book examines large-scale land acquisitions, o

An engineering and economic evaluation of some mixed-mode waste heat rejection systems

Originally presented as the first author's thesis, (Sc. D.)--in the M.I.T. Dept. of Nuclear Engineering, 1977Includes bibliographical references (p. 336-342

Intensive Case Management for Addiction to promote engagement with care of people with severe mental and substance use disorders: an observational study.

Co-occurring severe mental and substance use disorders are associated with physical, psychological and social complications such as homelessness and unemployment. People with severe mental and substance use disorders are difficult to engage with care. The lack of treatment worsens their health and social conditions and increases treatment costs, as emergency department visits arise. Case management has proved to be effective in promoting engagement with care of people with severe mental and substance use disorders. However, this impact seemed mainly related to the case management model. The Intensive Case Management for Addiction (ICMA) aimed to improve engagement with care of people with severe mental and substance use disorders, insufficiently engaged with standard treatment. This innovative multidisciplinary mobile team programme combined Assertive Community Treatment and Critical Time Intervention methodologies. The aim of the study was to observe the impact of ICMA upon service use, treatment adherence and quality of support networks. Participants' psychosocial and mental functioning, and substance use were also assessed throughout the intervention. The study was observational. Eligible participants were all the people entering the programme during the first year of implementation (April 2014-April 2015). Data were collected through structured questionnaires and medical charts. Assessments were conducted at baseline and at 12 months follow-up or at the end of the programme if completed earlier. McNemar-Bowker's Test, General Linear Model repeated-measures analysis of variance and non-parametric Wilcoxon Signed Rank tests were used for the analysis. A total of 30 participants took part in the study. Results showed a significant reduction in the number of participants visiting the general emergency department compared to baseline. A significantly decreased number of psychiatric emergency department visits was also registered. Moreover, at follow-up participants improved significantly their treatment adherence, clinical status, social functioning, and substance intake and frequency of use. These promising results highlight the efficacy of the ICMA. The intervention improved engagement with care and the psychosocial situation of people with severe mental and substance use disorders, with consequent direct impact on their substance misuse

Internal and Predictive Validity of the French Health of the Nation Outcome Scales: Need for Future Directions.

The Health of the Nation Outcome Scales (HoNOS) is a widely used measure of health and social functioning of people with mental illness. The goals of this study were to verify the internal validity of the one factor and several four-factor scoring structures and to evaluate the predictive validity of HoNOS items with regards to duration of hospitalization, probability of readmission in the following year and time before readmission. 6175 hospital stays at the department of psychiatry of Lausanne University Hospital were screened and the first HoNOS of each patient was taken into account (N = 2722). Data were analyzed through Confirmatory Factor Analysis (CFA) and the predictive validity of HoNOS items was evaluated with two approaches: item level regressions and latent class analysis (LCA). CFA indicated that the suggested factor structures were not supported by the data. Predictive validity of the 12 items was weak but LCA revealed five distinct and meaningful profiles that were related to length of stay or readmission. HoNOS may be more adapted to the evaluation of patients case-mix rather than to the individual level and concepts such as predictive validity may be more appropriate than internal validity to guide its use

Feasibility and Accessibility of a Tailored Intervention for Informal Caregivers of People with Severe Psychiatric Disorders: a Pilot Study

Objectives: This study aimed to assess the acceptability and feasibility of a new tailored intervention for informal caregivers: the Ensemble (Together) program. Methods: An open pre–post within-subject comparison pilot study was conducted. Twenty-one informal caregivers completed the five-session Ensemble program. Two measurement tools were used: The Brief Symptom Inventory (BSI) and the Life Orientation Scale (LOT-R). Results: The results showed that informal caregivers were in need of individual support and were ready to participate in the Ensemble program independent of the patient’s diagnosis or stage of illness. The participants were very satisfied, and 95.4% completed the program. The preliminary results also showed that in five sessions, informal caregivers’ Global Severity Index measured by the BSI and their optimism about their future (measured by the LOT-R) were significantly improved. Conclusion: This pilot study provided preliminary results concerning the feasibility and acceptability of the tailored Ensemble program and indicates the need for a randomized trial. The Ensemble program is appropriate for both the acute and chronic phases of disease. Individualized brief and useful interventions for informal caregivers may provide more positive outcomes in care

Patients' Needs for Care in Public Mental Health: Unity and Diversity of Self-Assessed Needs for Care.

PURPOSE: Needs assessment is recognized to be a key element of mental health care. Patients tend to present heterogeneous profiles of needs. However, there is no consensus in previous research about how patients' needs are organized. This study investigates both general and specific dimensions of patients' needs for care. METHODS: Patients' needs were assessed with ELADEB, an 18-domain self-report scale. The use of a self-assessment scale represents a unique way of obtaining patients' perceptions. A patient-centered psychiatric practice facilitates empowerment as it is based on the patients' personal motivations, needs, and wants. Four seventy-one patients' profiles were analyzed through exploratory factor analysis. RESULTS: A four-factor bifactor model, including one general factor and three specific factors of needs, was most adequate. Specific factors were (a) "finances" and "administrative tasks"; (b) "transports," "public places," "self-care," "housework," and "food"; and (c) "family," "children," "intimate relationships," and "friendship." CONCLUSION: As revealed by the general factor, patients expressing urgent needs in some domains are also more susceptible to report urgent needs in several other domains. This general factor relates to high versus low utilizers of public mental healthcare. Patients also present specific needs in life domains, which are organized in three dimensions: management, functional disabilities, and familial and interpersonal relationships. These dimensions relate to the different types of existing social support described in the literature

Predicting involuntary hospitalization in psychiatry: A machine learning investigation.

Coercion in psychiatry is a controversial issue. Identifying its predictors and their interaction using traditional statistical methods is difficult, given the large number of variables involved. The purpose of this study was to use machine-learning (ML) models to identify socio-demographic, clinical and procedural characteristics that predict the use of compulsory admission on a large sample of psychiatric patients. We retrospectively analyzed the routinely collected data of all psychiatric admissions that occurred between 2013 and 2017 in the canton of Vaud, Switzerland (N = 25,584). The main predictors of involuntary hospitalization were identified using two ML algorithms: Classification and Regression Tree (CART) and Random Forests (RFs). Their predictive power was compared with that obtained through traditional logistic regression. Sensitivity analyses were also performed and missing data were imputed through multiple imputation using chain equations. The three models achieved similar predictive balanced accuracy, ranging between 68 and 72%. CART showed the lowest predictive power (68%) but the most parsimonious model, allowing to estimate the probability of being involuntarily admitted with only three checks: aggressive behaviors, who referred the patient to hospital and primary diagnosis. The results of CART and RFs on the imputed data were almost identical to those obtained on the original data, confirming the robustness of our models. Identifying predictors of coercion is essential to efficiently target the development of professional training, preventive strategies and alternative interventions. ML methodologies could offer new effective tools to achieve this goal, providing accurate but simple models that could be used in clinical practice