Search results

Antipsychotic drugs are often used outside their licensed indication to manage aggression in adults with intellectual disabilities in the absence of a diagnosed psychiatric disorder. The current case series shows that antipsychotics could be effective, but they are often used with non‐drug measures and sometimes cause side‐effects. Clinicians did not always carry out a thorough assessment followed by a formulation before prescribing medications, as recommended in the national and international guides (Deb et al, 2009; Unwin & Deb, 2010). It is also apparent that clinicians did not carry out tests to detect side‐effects of risperidone such as metabolic syndrome. Clinicians should use psychotropic medication for a minimum period of time and at the lowest possible dose, and should consider non‐drug management of aggression at the outset and at a regular interval.

This chapter aims at shedding light upon how transforming or detrending a series can substantially impact predictions of mixed causal-noncausal (MAR) models, namely dynamic processes that depend not only on their lags but also on their leads. MAR models have been successfully implemented on commodity prices as they allow to generate nonlinear features such as locally explosive episodes (denoted here as bubbles) in a strictly stationary setting. The authors consider multiple detrending methods and investigate, using Monte Carlo simulations, to what extent they preserve the bubble patterns observed in the raw data. MAR models relies on the dynamics observed in the series alone and does not require economical background to construct a structural model, which can sometimes be intricate to specify or which may lack parsimony. The authors investigate oil prices and estimate probabilities of crashes before and during the first 2020 wave of the COVID-19 pandemic. The authors consider three different mechanical detrending methods and compare them to a detrending performed using the level of strategic petroleum reserves.

Given the recent explosion of interest in streaming data and online algorithms, clustering of time series subsequences has received much attention. In this work we make a surprising claim. Clustering of time series subsequences is completely meaningless. More concretely, clusters extracted from these time series are forced to obey a certain constraint that is pathologically unlikely to be satisfied by any dataset, and because of this, the clusters extracted by any clustering algorithm are essentially random. While this constraint can be intuitively demonstrated with a simple illustration and is simple to prove, it has never appeared in the literature. We can justify calling our claim surprising, since it invalidates the contribution of dozens of previously published papers. We will justify our claim with a theorem, illustrative examples, and a comprehensive set of experiments on reimplementations of previous work.

For this discussion, assume there are n sample observations of the dependent variable y at unique locations. In spatial samples, often each observation is uniquely associated with a particular location or region, so that observations and regions are equivalent. Spatial dependence arises when an observation at one location, say y i is dependent on “neighboring” observations y j, y j∈ϒi. We use ϒi to denote the set of observations that are “neighboring” to observation i, where some metric is used to define the set of observations that are spatially connected to observation i. For general definitions of the sets ϒi,i=1,…,n, typically at least one observation exhibits simultaneous dependence, so that an observation y j, also depends on y i. That is, the set ϒj contains the observation y i, creating simultaneous dependence among observations. This situation constitutes a difference between time series analysis and spatial analysis. In time series, temporal dependence relations could be such that a “one-period-behind relation” exists, ruling out simultaneous dependence among observations. The time series one-observation-behind relation could arise if spatial observations were located along a line and the dependence of each observation were strictly on the observation located to the left. However, this is not in general true of spatial samples, requiring construction of estimation and inference methods that accommodate the more plausible case of simultaneous dependence among observations.

There are limited risk assessment tools validated for use with the internet child abuse material (I/CAM) offender cohort. Developed through a multi-stage process, the purpose of this paper is to present the “Estimated Risk for Internet Child Sexual Offending” (ERICSO), a new tool for I/CAM offender assessment, including demographic, collection, nature of engagement and social domains, plus a structured professional judgement section. Validation studies remain ongoing.

This paper presents a case series analysis of six Australian men, including two Aboriginal men, convicted of I/CAM offences to pilot proposed ERICSO domains and commence validation against the short self-esteem scale, University of California Los Angles loneliness scale, internet sex screening test and the sexual violence risk-20 V2.

Participants of all ages generally reported histories of mental health diagnosis and/or treatment and substance abuse. Two participants reported prior sexual offending, one for I/CAM offences. Participants expressed sexual preferences for female child victims and were convicted of possessing thousands of I/CAM files. Two participants reported accessing I/CAM for over six and 10 years, respectively, before detection by law enforcement.

Preliminary implications indicate ERICSO higher scores are consistent with I/CAM offenders having more online sexual behaviour diversity and more areas of risk/treatment need. For example, participants with problematic self-esteem and loneliness in our data set have higher ERICSO scores. Social connectedness may be a relevant factor though definitive conclusions cannot be drawn from the small sample size.

The ERICSO presents novel assessment of factors in considering treatment targets in addressing both illegal I/CAM and problematic legal sexual behaviours.

This paper presents the first estimates of Spanish infrastructure stock and investment for the period 1845–1935. Several sources and techniques have been used in the estimation, and the new series are reasonably reliable to the standards of historical statistics. Two distinct periods may be distinguished in the series: the years before 1895 (characterized by the prominence of railroads) and the period 1895–1935 (when most investment was addressed to other assets). The new series allow a preliminary comparison of the Spanish infrastructure endowment with that of the most advanced countries, showing a gradual process of convergence before 1936.

New asymptotic approximations are established for the Wald and t statistics in the presence of unknown but strong autocorrelation. The asymptotic theory extends the usual fixed-smoothing asymptotics under weak dependence to allow for near-unit-root and weak-unit-root processes. As the locality parameter that characterizes the neighborhood of the autoregressive root increases from zero to infinity, the new fixed-smoothing asymptotic distribution changes smoothly from the unit-root fixed-smoothing asymptotics to the usual fixed-smoothing asymptotics under weak dependence. Simulations show that the new approximation is more accurate than the usual fixed-smoothing approximation.

The purpose of this paper is to present a series of cases of international students being treated in a specialized early intervention service for first-episode psychosis (FEP), describing the particular challenges that arise in this process, and to provide recommendations addressing these challenges.

Two researchers independently reviewed the charts of seven international students and discussed them with their treating clinicians. Recurring themes were identified through an iterative process of discussion and consensus.

Four themes were identified which demonstrated specific challenges faced by international students being treated for FEP: difficulty maintaining student visa status, limited social and family support, financial and health insurance issues, and service disengagement.

The study suggests that international students with FEP may present with numerous and unique challenges, thereby requiring special attention in their treatment. Although these are preliminary findings based on a small case series, the findings can inform recommendations for mental health services in cities with a sizeable international student population and guide future research on this topic.