Предрогнозна оцінка структури майна і капіталу промислового підприємства

Однією зі складових управління фінансами підприємства є прогнозування фінансового стану, яке дозволяє виявити здатність підприємства до стійкого функціонування і розвитку в умовах зміни зовнішнього і внутрішнього середовища господарювання. Сьогодні неможна недооцінювати роль прогнозування, оскільки функціонування підприємства завжди пов'язане з невизначеністю майбутніх наслідків дій того або іншого управлінського рішення. Однією із дисциплінуючих умов прогнозування фінансового стану промислових підприємств виступає оцінка їх фінансового стану у динаміці взагалі та предпрогнозна оцінка структури майна і капіталу зокрема.Одной из составляющих управления финансами предприятия является прогнозирование финансового состояния, которое позволяет выявить способность предприятия к стойкому функционированию и развитию в условиях изменения внешней и внутренней среды ведения хозяйства. Сегодня невозможно недооценивать роль прогнозирования, поскольку функционирование предприятия всегда связано с неопределенностью будущих последствий действий того или другого управленческого решения. Одним из дисциплинирующих условий прогнозирования финансового состояния промышленных предприятий выступает оценка их финансового состояния в динамике вообще и предпрогнозируемая оценка структуры имущества и капитала в частности

Ethnicity and baseline symptomatology in patients with an At Risk Mental State for psychosis

Ethnicity has been associated with different incidence rates and different symptom profiles in young patients with psychotic-like disorders. No studies so far have examined the effect of ethnicity on symptoms in people with an At Risk Mental State (ARMS). In this cross-sectional study, we analysed the relationship between ethnicity and baseline data on the severity of psychopathology scores in 201 help-seeking patients who met the ARMS criteria and agreed to participate in the Dutch Early Detection and Intervention (EDIE-NL) trial. Eighty-seven of these patients had a non-Dutch ethnicity. We explored the possible mediating role of ethnic identity. Higher rates of negative symptoms, and of anhedonia in particular, were found in the ethnic minority group. This result could be attributed mainly to the Moroccan-Dutch and Turkish-Dutch subgroups, who also presented with more depression symptoms when the groups were examined separately. The ethnic minority group displayed a lower level of ethnic group identity compared to the immigrants of the International Comparative Study of Ethnocultural Youth (ICSEY). Ethnic identity was inversely related to symptoms in the Moroccan-Dutch patient group. The prevalence of more severe negative symptoms and depression symptoms in ethnic minority groups deserves more attention, as the experience of attenuated positive symptoms when accompanied by negative symptoms or distress has proven to be predictive for transition to a first psychotic episod

Nurses' perceptions of aids and obstacles to the provision of optimal end of life care in ICU

Contains fulltext : 172380.pdf (publisher's version ) (Open Access

On the use of mixed Markov models for intensive longitudinal data

Markov modeling presents an attractive analytical framework for researchers who are interested in state-switching processes occurring within a person, dyad, family, group, or other system over time. Markov modeling is flexible and can be used with various types of data to study observed or latent state-switching processes, and can include subject-specific random effects to account for heterogeneity. We focus on the application of mixed Markov models to intensive longitudinal data sets in psychology, which are becoming ever more common and provide a rich description of each subject's process. We examine how specifications of a Markov model change when continuous random effect distributions are included, and how mixed Markov models can be used in the intensive longitudinal research context. Advantages of Bayesian estimation are discussed and the approach is illustrated by two empirical applications.status: publishe

On the Use of Mixed Markov Models for Intensive Longitudinal Data

<p>Markov modeling presents an attractive analytical framework for researchers who are interested in state-switching processes occurring within a person, dyad, family, group, or other system over time. Markov modeling is flexible and can be used with various types of data to study observed or latent state-switching processes, and can include subject-specific random effects to account for heterogeneity. We focus on the application of mixed Markov models to intensive longitudinal data sets in psychology, which are becoming ever more common and provide a rich description of each subject’s process. We examine how specifications of a Markov model change when continuous random effect distributions are included, and how mixed Markov models can be used in the intensive longitudinal research context. Advantages of Bayesian estimation are discussed and the approach is illustrated by two empirical applications.</p

COMT Val158Met genotype and cannabis use in people with an At Risk Mental State for psychosis: Exploring Gene x Environment interactions

Epidemiological and retrospective studies suggest a cannabis x catechol-O-methyltransferase (COMT) Val(158)Met interaction effect on development of psychosis. The aim of this study was to examine this interaction and its association with severity of subclinical symptoms in people with an At Risk Mental State (ARMS) for psychosis. Severity of symptoms, cannabis use and genotype were assessed at baseline in 147 help-seeking young adults who met the ARMS criteria and agreed to participate in the Dutch Early Detection and Intervention (EDIE-NL) trial. Cannabis use and COMT Val-allele showed an interaction effect in ARMS subjects. Subjects who were weekly cannabis users at some point prior to entering the study showed more severe positive symptoms. This effect increased if they were carriers of the COMT Val-allele and even more so if they were homozygous for the Val-allele. Our results suggest that the COMT Val(158)Met polymorphism moderates the effect of regular cannabis use on severity of subclinical psychotic symptom

The effect of childhood adversity on 4-year outcome in individuals at ultra high risk for psychosis in the Dutch Early Detection Intervention Evaluation (EDIE-NL) Trial

Childhood adversity is associated with a range of mental disorders, functional impairment and higher health care costs in adulthood. In this study we evaluated if childhood adversity was predictive of adverse clinical and functional outcomes and health care costs in a sample of patients at ultra-high risk (UHR) for developing a psychosis. Structural Equation Modeling was used to examine the effect of childhood adversity on depression, anxiety, transition to psychosis and overall functioning at 4-year follow-up. In addition, we evaluated economic costs of childhood adversity in terms of health care use and productivity loss. Data pertain to 105 UHR participants of the Dutch Early Detection and Intervention Evaluation (EDIE-NL). Physical abuse was associated with higher depression rates (b=0.381, p=0.012) and lower social functional outcome (b=−0.219, p=0.017) at 4-year follow-up. In addition, emotional neglect was negatively associated with social functioning (b=−0.313, p=0.018). We did not find evidence that childhood adversity was associated with transition to psychosis, but the experience of childhood adversity was associated with excess health care costs at follow-up. The data indicate long-term negative effects of childhood adversity on depression, social functioning and health care costs at follow-up in a sample of UHR patients.Multivariate analysis of psychological dat