Assessing the Need for Higher Levels of Care Among Problem Gambling Outpatients

Most treatment for gambling disorder is provided on an outpatient basis. Only a small number of jurisdictions in North America provide higher levels of gambling treatment, such as residential or intensive outpatient (IOP) care, despite the potential need for these services. Further, there appear to be few guidelines for determining appropriate level of gambling treatment. The aim of the present study was to assess the appropriateness of higher levels of problem gambling care among clients receiving outpatient treatment. Problem gamblers and their therapists independently completed questionnaires that assessed the need and desire for residential and IOP treatment. About 42% of problem gambling outpatients noted that they would be “probably” or “definitely” willing to attend residential treatment, and about half indicated they would be equally likely to attend IOP. Therapists recommended about a third of their clients as appropriate for higher levels of care. For both client and therapist assessments, there was a significant association between desire or recommendation for level of treatment and severity of gambling and co-occurring problems. Further, therapist recommendations for level of care were significantly associated with client willingness to attend higher levels of treatment. Our data reveal the potential need for higher levels of care for problem gambling, as evaluated by clients and their therapists. Policy implications for the funding of residential and IOP treatment are discussed.     

Correlation and variable importance in random forests

This paper is about variable selection with the random forests algorithm in presence of correlated predictors. In high-dimensional regression or classification frameworks, variable selection is a difficult task, that becomes even more challenging in the presence of highly correlated predictors. Firstly we provide a theoretical study of the permutation importance measure for an additive regression model. This allows us to describe how the correlation between predictors impacts the permutation importance. Our results motivate the use of the recursive feature elimination (RFE) algorithm for variable selection in this context. This algorithm recursively eliminates the variables using permutation importance measure as a ranking criterion. Next various simulation experiments illustrate the efficiency of the RFE algorithm for selecting a small number of variables together with a good prediction error. Finally, this selection algorithm is tested on the Landsat Satellite data from the UCI Machine Learning Repository.     

The Case Study Method in Psychodynamic Psychology: Focus on Addiction

The case study method has been essential in psychoanalysis and psychodynamic therapy, since it is the only way to describe and explore the deepest levels of the human psyche. Addiction is no more and no less than a particular psychological mechanism, identical at its core to other psychological compulsions, and is therefore best understood and reported by this method that explores the mind in depth. We will discuss the value of the case report method in general and in specific with regard to psychoanalysis and addiction, criticisms raised about this method, and comparisons of it with nomothetic research.     

‘By Helping Others,We Helped Ourselves:’ Volunteering and Social Integration of Ex-Soviet Immigrants in Israel

Recent immigrants seldom join the ranks of volunteers for various social causes. Immigrants from former socialist countries have been shown to be particularly averse to organized forms of volunteering for reasons rooted in their past, including forced forms of collectivism imposed by the state. In this qualitative study, we explored the perceptions and practices of volunteering among ex-Soviet immigrants (mostly educated middle-aged women) who ran a project for the benefit of elderly. Our findings show that most volunteers chose causes targeting fellow immigrants, their resettlement and well-being, and were motivated by the wish to build co-ethnic support network and overcome marginalization in the Israeli society. Other volunteers were driven by the need for self-actualization in the context of underemployment and occupational downgrading. Personal empowerment and higher identification with the receiving society were the most salient outcomes of volunteering for our informants. We conclude that for some immigrants, volunteering can serve as a strategy of social integration.     

The Nigerian Civil Registration and Vital Statistics System: Contexts,Institutions, Operation

Civil Registration and Vital Statistics (CRVS) Systems are playing increasing roles in national and global data infrastructure, facilitating the achievement of key developmental goals. The performance of CRVS systems in many developing countries including Nigeria is sub optimal and information on their structure and operations scanty. This paper characterizes the statutory, institutional, and operational elements and social contexts of the Nigerian CRVS System. It includes a context analysis of the system and a review of improvement strategies and interventions. The paper shows that the Nigerian CRVS System is built on viable statutory and institutional platforms—the constitutional enshrinement of: universal, compulsory and continuous civil registration and, a central registration institution—the National Population Commission (NPC). NPC has registration hierarchy and infrastructure deployed at every level of political administration and mechanisms for efficient coordination of registration and production of vital statistics on live-births, deaths and stillbirths amongst other vital events. The major weaknesses of the system include inadequate financing and deployment of registration facilities, conflicting statutes and institutional arrangements for the registration of key events like death and stillbirths. Other weaknesses include intra-organizational conflicts in resource allocation and weak ICT infrastructure within the NPC. These are compounded by overarching contextual issues namely registration unfriendly sociocultural norms, weak national data infrastructure, systemic corruption, poverty and undeveloped civic culture. Domestic initiatives and interventions to improve the system have focused on birth registration, while multilateral interventions have only made a modest impact on the system. Thus, holistic in-country improvement initiatives supported with robust interventions are imperative to overcome weaknesses in the Nigerian CRVS system. However fundamental improvements in CRVS systems in developing countries like Nigeria may likely only follow sustainable solutions to overarching contextual issues especially poor infrastructure, weak institutions, poverty and systemic corruption.     

Approximate Bayesian inference in semi-mechanistic models

Inference of interaction networks represented by systems of differential equations is a challenging problem in many scientific disciplines. In the present article, we follow a semi-mechanistic modelling approach based on gradient matching. We investigate the extent to which key factors, including the kinetic model, statistical formulation and numerical methods, impact upon performance at network reconstruction. We emphasize general lessons for computational statisticians when faced with the challenge of model selection, and we assess the accuracy of various alternative paradigms, including recent widely applicable information criteria and different numerical procedures for approximating Bayes factors. We conduct the comparative evaluation with a novel inferential pipeline that systematically disambiguates confounding factors via an ANOVA scheme.     

Heterogeneous climate effects on human migration in Indonesia

We examine the effect of anomalous temperatures, rainfall levels, and monsoon timing on migration outcomes in Indonesia. Using panel data from the Indonesian Family Life Survey and high-resolution climate data, we assess whether intra- and inter-province moves are used as a response to climatic shocks. We evaluate the relative importance of temperature, rainfall, and monsoon timing for migration. Only temperature and monsoon timing have significant effects, and these do not operate in the direction commonly assumed. Estimated effects vary according to individuals’ gender, membership in a farm household, and location. We also analyze climate effects on sources of household income, which highlights the multi-phasic nature of household responses. Results undermine narratives of a uniform global migratory response to climate change and highlight the heterogeneous use of migration as a response to such changes. By extending previous research on environmentally induced migration in Indonesia, we also highlight the sensitivity of estimates to alternative climate and migration measures.     

Disruptive Organisation

Organizations are driven by continuous change. Global, socio-economic and technological megatrends – demographic changes and digitalization – are the reasons for transformation. Traditional organization forms are not in line with customers‘ need. Disruptive modes of development and innovations have been intensively discussed elsewhere. The topic of disruptive organization have not been discussed towards internal and external customer relations, although of high relevance. 129 Managers answered on communication ways and the purpose of upcoming meaning for the working place/office. Two new models and five concrete recommendations have been established for upcoming future organization.     

Estimation of the cumulative incidence function under multiple dependent and independent censoring mechanisms

Competing risks occur in a time-to-event analysis in which a patient can experience one of several types of events. Traditional methods for handling competing risks data presuppose one censoring process, which is assumed to be independent. In a controlled clinical trial, censoring can occur for several reasons: some independent, others dependent. We propose an estimator of the cumulative incidence function in the presence of both independent and dependent censoring mechanisms. We rely on semi-parametric theory to derive an augmented inverse probability of censoring weighted (AIPCW) estimator. We demonstrate the efficiency gained when using the AIPCW estimator compared to a non-augmented estimator via simulations. We then apply our method to evaluate the safety and efficacy of three anti-HIV regimens in a randomized trial conducted by the AIDS Clinical Trial Group, ACTG A5095.     

Discussion of “Nonparametric Bayesian Inference in Applications”: Bayesian nonparametric methods in econometrics

The use of Bayesian nonparametrics models has increased rapidly over the last few decades driven by increasing computational power and the development of efficient Markov chain Monte Carlo algorithms. We review some applications of these models in economic applications including: volatility modelling (using both stochastic volatility models and GARCH-type models) with Dirichlet process mixture models, uses in portfolio allocation problems, long memory models with flexible forms of time-dependence, flexible extension of the dynamic Nelson-Siegel model for interest rate yields and multivariate time series models used in macroeconometrics.