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Compulsory admission procedures of patients with mental disorders vary between countries in Europe. The Ethics Committee of the European Psychiatric Association (EPA) launched a survey on involuntary admission procedures of patients with mental disorders in 40 countries to gather information from all National Psychiatric Associations that are members of the EPA to develop recommendations for improving involuntary admission processes and promote voluntary care.
The survey focused on legislation of involuntary admissions and key actors involved in the admission procedure as well as most common reasons for involuntary admissions.
We analyzed the survey categorical data in themes, which highlight that both medical and legal actors are involved in involuntary admission procedures.
We conclude that legal reasons for compulsory admission should be reworded in order to remove stigmatization of the patient, that raising awareness about involuntary admission procedures and patient rights with both patients and family advocacy groups is paramount, that communication about procedures should be widely available in lay-language for the general population, and that training sessions and guidance should be available for legal and medical practitioners. Finally, people working in the field need to be constantly aware about the ethical challenges surrounding compulsory admissions.
Neurological soft signs (NSS) are characterized by abnormalities in motor, sensory, and integrative functions. NSS have been regarded as a result of neurodevelopmental dysfunction, and as evidence of a central nervous system defect, resulting in considerable sociopsychological dysfunction. During the last decade there has been growing evidence of brain dysfunction in severe aggressive behavior. As a symptom, aggression overlaps a number of psychiatric disorders, but it is commonly associated with antisocial personality disorder. The aim of the present study was to examine NSS in an adult criminal population using the scale by Rossi et al. . Subjects comprised 14 homicidal men with antisocial personality disorder recruited from a forensic psychiatric examination. Ten age- and gender-matched healthy volunteers as well as eight patients with schizophrenia, but no history of physical aggression, served as controls. The NSS scores of antisocial offenders were significantly increased compared with those of the healthy controls, whereas no significant differences were observed between the scores of offenders and those of patients with schizophrenia. It can be speculated that NSS indicate a nonspecific vulnerability factor in several psychiatric syndromes, which are further influenced by a variety of genetic and environmental components. One of these syndromes may be antisocial personality disorder with severe aggression.
Aggressive and disruptive behaviors often precede the onset of schizophrenia. In this register-based follow-up study with a case-control design, we wanted to investigate if serious delinquency was associated with future diagnoses of schizophrenia or schizoaffective disorder (here, broadly defined schizophrenia) among a nationwide consecutive sample of 15- to 19-year-old Finnish delinquents sent for a forensic psychiatric examination in 1989–2010.
The sample comprised 313 delinquents with no past or current psychotic disorder. For each delinquent, four age-, gender- and place of birth -matched controls were randomly selected from the Central Population Register. Five controls (0.4%) had been treated for schizophrenia before their respective index-dates and were thus excluded from further analysis, leaving us with a control population of 1247 individuals. The subjects were followed till death, emigration or the end of 2015, whichever occurred first. Diagnoses were obtained from the Care Register for Health Care.
Forty (12.8%) of the delinquents and 11 (0.9%) of the controls were diagnosed with schizophrenia later in life (HR 16.6, 95% CI 8.53–32.39, P < 0.001). Almost half of the pretrial adolescents with later schizophrenia were diagnosed within 5 years of the forensic psychiatric examination, but latency was longer among the other half of the sample, reaching up to 20.5 years.
The study supports the previous research indicating a potential link between serious delinquency and later schizophrenia. Accurate psychiatric assessments should be made in correctional services but also later in life so that any possible psychotic symptoms can be detected in individuals with a history of serious delinquency even if there were no signs of psychosis before or at the time of the crime. Future research should explore which factors influence the delinquent's risk of developing later schizophrenia.
Structured self-reports, such as Beck's Depression Inventory (BDI) are widely used in assessing adolescents’ psychological wellbeing.
To investigate what factors are associated with discrepancies between BDI scores and diagnostic assessment in adolescent psychiatric patients and general population.
To recognize what factors may contribute to high BDI scores besides depressive symptoms.
The study population consisted of 206 adolescents (13–17 years old) who were hospitalised for the first time in adolescent psychiatry and 203 age and gender matched adolescents recruited from schools in the same region. Study subjects filled self-reports on depression symptoms (BDI-21), substance misuse (AUDIT), psychiatric symptoms (SCL-90), defense styles (DSQ-40) and self-image (OSIQ). Diagnostics was based on K-SADS-PL interview, and/or clinical interview and clinical records when available. Information on background and life events was gathered from study subjects.
We compared subjects who scored in BDI-21 either 0–15 points or 16–63 points firstly among subjects who did not fill diagnostic criteria for current unipolar depression and secondly among those who did fulfill the diagnostic criteria. High BDI-21 scores in subjects without depression diagnosis were associated with female sex, older age, several adverse life events, higher psychiatric co-morbidity, worse self-image and more immature, neurotic and image-distorting defense styles (and less mature defense style). Low BDI-21 scores among subjects with depression diagnosis were associated with male sex, more positive self-image and less immature defense style.
High BDI-21 scores may reflect a broad range of challenges in an adolescent's psychological development even in the absence of depression.
Disclosure of interest
The authors have not supplied their declaration of competing interest.
Scholars and policy makers need systematic assessments of the validity of the measures produced by V-Dem. In Chapter 6, we present our approach to comparative data validation – the set of steps we take to evaluate the precision, accuracy, and reliability of our measures, both in isolation and compared to extant measures of the same concepts. Our approach assesses the degree to which measures align with shared concepts (content validation), shared rules of translation (data generation assessment), and shared realities (convergent validation). Within convergent validity, we execute two convergent validity tests. First, we examine convergent validity as it is typically conceived – examining convergence between V-Dem measures and extant measures. Second, we evaluate the level of convergence across coders, considering the individual coder and country traits that predict coder convergence. Throughout the chapter, we focus on three indices included in the V-Dem data set: polyarchy, corruption, and core civil society. These three concepts collectively provide a “hard test” for the validity of our data, representing a range of existing measurement approaches, challenges, and solutions.
This chapter sets forth the conceptual scheme for the V–Dem project. We begin by discussing the concept of democracy. Next, we lay out seven principles by which this key concept may be understood – electoral, liberal, majoritarian, consensual, participatory, deliberative, and egalitarian. Each defines a “variety“ of democracy, and together they offer a fairly comprehensive accounting of the concept as used in the world today. Next, we show how this seven-part framework fits into our overall thinking about democracy, including multiple levels of disaggregation – to components, subcomponents, and indicators. The final section of the chapter discusses several important caveats and clarifications pertaining to this ambitious taxonomic exercise.
This chapter recounts how a project of this scale came together and why it has succeeded. Five main factors were responsible for V–Dem’s success: timing, inclusion, deliberation, administrative centralization, and fund–raising. First, planning for V-Dem began at a time when both social scientists and practitioners were realizing that they needed better democracy measures. This made it possible to recruit collaborators and find funding. Second, the leaders of the project were always eager to expand the team to acquire whatever expertise they lacked and share credit with everyone who contributed. Third, the project leaders practiced an intensely deliberative decision–making style to ensure that all points of view were consulted and only decisions that won wide acceptance were adopted. Fourth, centralizing the execution of the agreed–upon tasks helped tremendously by streamlining processes and promoting standardization, documentation, professionalization, and coordination of a large number of intricate steps. Finally, successful fund–raising from a mix of both research foundations and bilateral and multilateral organizations has been critical.
In this chapter we focus on the measurement of five key principles of democracy – electoral, liberal, participatory, deliberative, and egalitarian. For each principle, we discuss (1) the theoretical rationale for the selected indicators, (2) whether these indicators are correlated strongly enough to warrant being collapsed into an index, and (3) the justification of aggregation rules for moving from indicators to components and from components to higher–level indices. In each section we also (4) highlight the top– and bottom–five countries on each principle of democracy in early (1812 or 1912) and late (2012) years of our sample period, as well as the aggregate trend over the whole time period 1789–2017 (where applicable). Finally, we (5) look at how the different principles are intercorrelated in order to assess the trade–offs involved between the conceptual parsimony achieved by aggregating to a few general concepts and the retention of useful variation permitted by aggregating less.
Four characteristics of V-Dem data present distinct opportunities and challenges for explanatory analysis: (1) the large number of democracy indicators (i.e., variables), (2) the measurement of concepts by multiple coders filtered through the V-Dem measurement model, (3) the large number of years in the data set, and 4) the ex ante potential for dependence across countries (generically referred to as spatial dependence). This chapter discusses 3 challenges and 10 opportunities that are implied by these characteristics. At the end of this chapter, we also discuss three assumptions that are implicit in most analyses of observational indicators of macro-features at the national level, which aim to draw conclusions about causal relationships.
Varieties of Democracy is the essential user's guide to The Varieties of Democracy project (V-Dem), one of the most ambitious data collection efforts in comparative politics. This global research collaboration sparked a dramatic change in how we study the nature, causes, and consequences of democracy. This book is ambitious in scope: more than a reference guide, it raises standards for causal inferences in democratization research and introduces new, measurable, concepts of democracy and many political institutions. Varieties of Democracy enables anyone interested in democracy - teachers, students, journalists, activists, researchers and others - to analyze V-Dem data in new and exciting ways. This book creates opportunities for V-Dem data to be used in education, research, news analysis, advocacy, policy work, and elsewhere. V-Dem is rapidly becoming the preferred source for democracy data.
Users of V–Dem data should take care to understand how the data are generated because the data collection strategies have consequences for the validity, reliability, and proper interpretation of the values. Chapters 4 and 5 explain how we process the data after collecting the raw scores and how we aggregate the most specific indicators into more general indices. In this chapter we explain where the raw scores come from. We distinguish among the different types of data that V–Dem reports and describe the processes that produce each type and the infrastructure required to execute these processes.
V-Dem relies on country experts who code a host of ordinal variables, providing subjective ratings of latent – that is, not directly observable – regime characteristics. Sets of around five experts rate each case, and each rater works independently. Our statistical tools model patterns of disagreement between experts, who may offer divergent ratings because of differences of opinion, variation in scale conceptualization, or mistakes. These tools allow us to aggregate ratings into point estimates of latent concepts and quantify our uncertainty around these estimates. This chapter describes item response theory models that can account and adjust for differential item functioning (i.e., differences in how experts apply ordinal scales to cases) and variation in rater reliability (i.e., random error). We also discuss key challenges specific to applying item response theory to expert–coded cross-national panel data, explain how we address them, highlight potential problems with our current framework, and describe long-term plans for improving our models and estimates. Finally, we provide an overview of the end–user–accessible products of the V-Dem measurement model.