scholarly journals Book Review: Counseling for people with severe mental illness - Theory and case study. Young, K.W., Commercial Press (Hong Kong), 2013

2016 ◽  
Vol 1 (1) ◽  
pp. 68
Author(s):  
Lan-ying Zhu ◽  
Man C.M. Tsui ◽  
Da Li
Keyword(s):  
Mental Illness ◽  
Severe Mental Illness ◽  
Social Exclusion ◽  
Royal College ◽  
Social Stigma ◽  
Short Term ◽  
Commercial Press

<p>Globally, severe mental illness (SMI) causes both short-term and long-term disabilities (Royal College of Psychiatrists, 2009). In China, there are about 16 million people with SMI (Phillips et al., 2009).<strong> </strong>Secondary handicaps due to social stigma are common which result in severe deprivation of community re-integration (Social Exclusion Unit, 2004). Such alarming situations further highlight the pressing needs of developing culturally sensitive counseling strategies and practices.</p>

scholarly journals Smoking cessation in severe mental illness: combined long-term quit rates from the UK SCIMITAR trials programme

2019 ◽  
pp. 1-3 ◽  
Author(s):  
Simon Gilbody ◽  
Emily Peckham ◽  
Della Bailey ◽  
Catherine Arundel ◽  
Paul Heron ◽  
...  
Keyword(s):  
Mental Illness ◽  
Smoking Cessation ◽  
Severe Mental Illness ◽  
Short Term ◽  
Cessation Intervention ◽  
Term Trial ◽  
Short And Long Term ◽  
The Uk ◽  
Full Trial

Summary Smoking contributes to health inequalities for people with severe mental illness (SMI). Although smoking cessation interventions are effective in the short term, there are few long-term trial-based estimates of abstinence. The SCIMITAR trials programme includes the largest trial to date of a smoking cessation intervention for people with SMI, but this was underpowered to detect anticipated long-term quit rates. By pooling pilot and full-trial data we found that quit rates were maintained at 12 months (OR = 1.67, 95% CI 1.02–2.73, P = 0.04). Policymakers can now be confident that bespoke smoking cessation interventions produce successful short- and long-term quitting.

scholarly journals Cost Analysis of a High Support Housing Initiative for Persons with Severe Mental Illness and Long-Term Psychiatric Hospitalization

2018 ◽  
Vol 63 (7) ◽  
pp. 492-500 ◽  
Author(s):  
David Rudoler ◽  
Claire de Oliveira ◽  
Binu Jacob ◽  
Melonie Hopkins ◽  
Paul Kurdyak
Keyword(s):  
Mental Health ◽  
Mental Illness ◽  
Cost Saving ◽  
Cost Analysis ◽  
Severe Mental Illness ◽  
Inpatient Care ◽  
Cost Savings ◽  
Support Housing ◽  
High Support

Objective: The objective of this article was to conduct a cost analysis comparing the costs of a supportive housing intervention to inpatient care for clients with severe mental illness who were designated alternative-level care while inpatient at the Centre for Addiction and Mental Health in Toronto. The intervention, called the High Support Housing Initiative, was implemented in 2013 through a collaboration between 15 agencies in the Toronto area. Method: The perspective of this cost analysis was that of the Ontario Ministry of Health and Long-Term Care. We compared the cost of inpatient mental health care to high-support housing. Cost data were derived from a variety of sources, including health administrative data, expenditures reported by housing providers, and document analysis. Results: The High Support Housing Initiative was cost saving relative to inpatient care. The average cost savings per diem were between $140 and $160. This amounts to an annual cost savings of approximately $51,000 to $58,000. When tested through sensitivity analysis, the intervention remained cost saving in most scenarios; however, the result was highly sensitive to health system costs for clients of the High Support Housing Initiative program. Conclusions: This study suggests the High Support Housing Initiative is potentially cost saving relative to inpatient hospitalization at the Centre for Addiction and Mental Health.

Poverty transitions in severe mental illness: longitudinal analysis of social drift in China, 1994–2015

2021 ◽  
pp. 1-9
Author(s):  
Yue-Hui Yu ◽  
Wei Luo ◽  
Bo Liu ◽  
Wei-Hong Kuang ◽  
Larry Davidson ◽  
...  
Keyword(s):  
Mental Illness ◽  
Severe Mental Illness ◽  
Poverty Rate ◽  
International Classification Of Disease ◽  
Fast Change ◽  
The Social ◽  
Poverty Transitions ◽  
Icd 10 ◽  
Persistent Poverty

Abstract Background Although poverty associated with severe mental illness (SMI) has been documented in many studies, little long-term evidence of social drift exists. This study aimed to unravel the poverty transitions among persons with SMI in a fast change community in China. Methods Two mental health surveys, using the International Classification of Disease (ICD-10), were conducted in the same six townships of Xinjin county, Chengdu, China in 1994 and 2015. A total of 308 persons with SMI identified in 1994 were followed up in 2015. The profiles of poverty transitions were identified and regression modelling methods were applied to determine the predictive factors of poverty transitions. Results The poverty rate of persons with SMI increased from 39.9% to 49.4% in 1994 and 2015. A larger proportion of them had fallen into poverty (27.3%) rather than moved out of it (17.8%). Those persons with SMI who had lost work ability, had physical illness and more severe mental disabilities in 1994, as well as those who had experienced negative changes on these factors were more likely to live in persistent poverty or fall into poverty. Higher education level and medical treatment were major protective factors of falling into poverty. Conclusions This study shows long-term evidence on the social drift of persons with SMI during the period of rapid social development in China. Further targeted poverty alleviation interventions should be crucial for improving treatment and mental recovery and alleviating poverty related to SMI.

Social stigma in severe mental illness in Tunisia: Clinical and socio-demographic correlates

2017 ◽  
Vol 41 (S1) ◽  
pp. S577-S577 ◽  
Author(s):  
U. Ouali ◽  
R. Jomli ◽  
R. Nefzi ◽  
H. Ouertani ◽  
F. Nacef
Keyword(s):  
Mental Illness ◽  
Severe Mental Illness ◽  
Cultural Context ◽  
Social Inclusion ◽  
Psychiatric Patients ◽  
Social Stigma ◽  
Cross Sectional Study ◽  
Local Context ◽  
Cross Sectional ◽  
Competing Interest

IntroductionMental patients generally internalize some of the negative conceptions about how most people view them: they might be considered incompetent or untrustworthy or believe that people would not want to hire, or marry someone with mental illness. A lot of research on stigma has been conducted in western countries; however, little is still known on the situation in Arab-Muslim societies.ObjectivesTo evaluate social stigma as viewed by patients suffering from severe mental illness (SMI)MethodsThis is a cross-sectional study on clinically stabilized patients with schizophrenia and Bipolar Disorder (BD) according to DSM IV, who were interviewed in our out-patients clinic with the help of a semi-structured questionnaire, containing 8 opinions on the social inclusion and stigmatization of psychiatric patients, with special reference to the local cultural context (e.g.: “It is better to hide mental illness in order to preserve the reputation of my family”)ResultsWe included 104 patients, 51% with schizophrenia and 49% with BD. Mean age was 38.4 years (18–74 years); 59.6% were males. Overall social stigma scores were high. Social stigma in patients was correlated with gender, age, place of residence and diagnosis. Patients with BD showed significantly less social stigma than patients with schizophrenia.ConclusionOur results show the need for a better understanding of this phenomenon in patients with SMI, but also within Tunisian society, in order to elaborate anti stigma strategies adapted to the local context.Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals Short-term outcome of mothers with severe mental illness admitted to a mother baby unit

2021 ◽  
Vol 63 (3) ◽  
pp. 245
Author(s):  
Sundarnag Ganjekar ◽  
Vishwas Yadawad ◽  
Harish Thippeswamy ◽  
PrabhaS Chandra ◽  
Geetha Desai
Keyword(s):  
Mental Illness ◽  
Severe Mental Illness ◽  
Short Term ◽  
Term Outcome ◽  
Short Term Outcome

Cordaid’s Post-Disaster Shelter Strategy in Haiti: Linking Relief and Development

2014 ◽  
Vol 39 (3) ◽  
pp. 77-85
Author(s):  
Harmen Janse ◽  
Kees van der Flier
Keyword(s):  
Urban Area ◽  
Urban Areas ◽  
Life Support ◽  
Comparative Case Study ◽  
Urban Context ◽  
Short Term ◽  
Stage Of Development ◽  
Post Disaster

Haiti was struck by a heavy earthquake in 2010 and international aid poured into the country. News reports in 2011 were not very positive about the results of post-disaster reconstruction: “The relief efforts are only putting Haiti on life-support instead of evolving into the next stage of development”. One of the non-governmental organisations (NGOs) involved in Haiti was Cordaid, implementing a ‘transitional shelter strategy’ to support the transformation of neigh-bourhoods from a state of life-support into a state of self-sustaining development. The strategy was implemented in both a rural and an urban area. The main feature of the strategy was the provision of structures that could be adapted from simple shelters to permanent houses. Since the results of the strategy were mixed and ambiguous, a comparative case study was conducted to evaluate the shelter strategy in both areas. The objective was to draw lessons about what has to be taken into account when formulating future urban shelter strategies. The case study is discussed in this article. The main finding from the case study is that producing the intended number of shelters within the financial and time budgets that were set (efficiency), was more difficult in the urban area than in the rural area. But the conditions for linking relief and development (effectiveness) are more favourable in the urban context. NGOs may achieve long-term (effective) results in the urban context when a lower efficiency can be justified. That is why NGOs need to engage in a debate about the extent to which they are able to focus on long-term shelter or housing strategies. The important element in the debate is communication with the donors who are often focused on short-term relief measures. However urban areas cannot be rebuilt with only short-term interventions. The link between relief and development has to be made by a process-orientated approach focusing on capacities of local participants.

Disaster Management and Continuity Planning in Libraries

2016 ◽  
Vol 5 (1) ◽  
pp. 26-41 ◽  
Author(s):  
Rebecca Hamilton ◽  
Diane Brown
Keyword(s):  
Success Factor ◽  
Short Term ◽  
Continuity Planning ◽  
Critical Success ◽  
Business Operations ◽  
Asset Recovery ◽  
Disaster Preparation

Libraries are taking on new roles in a disaster and with that comes strategic responsibilities beyond traditional asset recovery activities. In the past, library disaster plans have emphasized recovery of materials. Here, the emphasis is on continuing business operations. Libraries have become the centers of communication for their communities in a crisis. This article will demonstrate the essential role of libraries before, during and after a disaster, both short term and long term and how to get a seat at the table with community planners by demonstrating the functions that are critical to recovery. A literature review and case study are used to develop these recommendations. A critical success factor is to use a disaster preparation methodology that includes a business continuity plan.

scholarly journals Challenges in modelling isoprene and monoterpene emission dynamics of Arctic plants: a case study from a subarctic tundra heath

2016 ◽  
Vol 13 (24) ◽  
pp. 6651-6667 ◽  
Author(s):  
Jing Tang ◽  
Guy Schurgers ◽  
Hanna Valolahti ◽  
Patrick Faubert ◽  
Päivi Tiiva ◽  
...  
Keyword(s):  
Response Curve ◽  
Large Scale ◽  
Ecosystem Model ◽  
The Arctic ◽  
Short Term ◽  
Response Curves ◽  
Arctic Plants ◽  
Scale Modelling

Abstract. The Arctic is warming at twice the global average speed, and the warming-induced increases in biogenic volatile organic compounds (BVOCs) emissions from Arctic plants are expected to be drastic. The current global models' estimations of minimal BVOC emissions from the Arctic are based on very few observations and have been challenged increasingly by field data. This study applied a dynamic ecosystem model, LPJ-GUESS, as a platform to investigate short-term and long-term BVOC emission responses to Arctic climate warming. Field observations in a subarctic tundra heath with long-term (13-year) warming treatments were extensively used for parameterizing and evaluating BVOC-related processes (photosynthesis, emission responses to temperature and vegetation composition). We propose an adjusted temperature (T) response curve for Arctic plants with much stronger T sensitivity than the commonly used algorithms for large-scale modelling. The simulated emission responses to 2 °C warming between the adjusted and original T response curves were evaluated against the observed warming responses (WRs) at short-term scales. Moreover, the model responses to warming by 4 and 8 °C were also investigated as a sensitivity test. The model showed reasonable agreement to the observed vegetation CO2 fluxes in the main growing season as well as day-to-day variability of isoprene and monoterpene emissions. The observed relatively high WRs were better captured by the adjusted T response curve than by the common one. During 1999–2012, the modelled annual mean isoprene and monoterpene emissions were 20 and 8 mg C m−2 yr−1, with an increase by 55 and 57 % for 2 °C summertime warming, respectively. Warming by 4 and 8 °C for the same period further elevated isoprene emission for all years, but the impacts on monoterpene emissions levelled off during the last few years. At hour-day scale, the WRs seem to be strongly impacted by canopy air T, while at the day–year scale, the WRs are a combined effect of plant functional type (PFT) dynamics and instantaneous BVOC responses to warming. The identified challenges in estimating Arctic BVOC emissions are (1) correct leaf T estimation, (2) PFT parameterization accounting for plant emission features as well as physiological responses to warming, and (3) representation of long-term vegetation changes in the past and the future.

scholarly journals Alternatives to groundwater abstraction as a measure to stop land subsidence: a case study of Semarang, Indonesia

2019 ◽  
Vol 125 ◽  
pp. 01003 ◽  
Author(s):  
Wesley Beek ◽  
Bart Letitre ◽  
H. Hadiyanto ◽  
S. Sudarno
Keyword(s):  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Drinking Water Treatment ◽  
Decision Makers ◽  
Groundwater Abstraction ◽  
Short Term ◽  
Treatment Services

The Water as Leverage project aims to lay a blueprint for urban coastal areas around the world that are facing a variety of water-related issues. The blueprint is based upon three real case studies in Bangladesh, India and Indonesia. The case of Indonesia focuses on Semarang, a city that faces issues like flooding, increased water demand, and a lack of wastewater treatment. In this report I summarise the different techniques available to tackling these issues. Along with this I provide a cost-benefit analysis to support decision makers. For a short term it is recommended to produce industrial water from (polluted) surface water as a means to offer an alternative to groundwater abstraction. On a long term it is recommended to install additional wastewater and drinking water treatment services to facilitate better hygiene and a higher quality of life.

Time Series Forecasting in Retail Sales Using LSTM and Prophet

2021 ◽  
pp. 241-262
Author(s):  
Clony Junior ◽  
Pedro Gusmão ◽  
José Moreira ◽  
Ana Maria M. Tome
Keyword(s):  
Time Series ◽  
Data Science ◽  
Short Term Memory ◽  
Special Kind ◽  
Time Series Forecasting ◽  
Short Term ◽  
Term Memory ◽  
Use Of Time

Data science highlights fields of study and research such as time series, which, although widely explored in the past, gain new perspectives in the context of this discipline. This chapter presents two approaches to time series forecasting, long short-term memory (LSTM), a special kind of recurrent neural network (RNN), and Prophet, an open-source library developed by Facebook for time series forecasting. With a focus on developing forecasting processes by data mining or machine learning experts, LSTM uses gating mechanisms to deal with long-term dependencies, reducing the short-term memory effect inherent to the traditional RNN. On the other hand, Prophet encapsulates statistical and computational complexity to allow broad use of time series forecasting, prioritizing the expert's business knowledge through exploration and experimentation. Both approaches were applied to a retail time series. This case study comprises daily and half-hourly forecasts, and the performance of both methods was measured using the standard metrics.

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