12 resultados para Anxiety Inventory

em Helda - Digital Repository of University of Helsinki


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This study is part of the Mood Disorders Project conducted by the Department of Mental Health and Alcohol Research, National Public Health Institute, and consists of a general population survey sample and a major depressive disorder (MDD) patient cohort from Vantaa Depression Study (VDS). The general population survey study was conducted in 2003 in the cities of Espoo and Vantaa. The VDS is a collaborative depression research project between the Department of Mental Health and Alcohol Research of the National Public Health Institute and the Department of Psychiatry of the Peijas Medical Care District (PMCD) beginning in 1997. It is a prospective, naturalistic cohort study of 269 secondary-level care psychiatric out- and inpatients with a new episode of Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) MDD. In the general population survey study, a total of 900 participants (300 from Espoo, 600 from Vantaa) aged 20 70 years were randomly drawn from the Population Register Centre in Finland. A self-report booklet, including the Eysenck Personality Inventory (EPI), the Temperament and Character Inventory Revised (TCI-R), the Beck Depression Inventory and the Beck Anxiety Inventory was mailed to all subjects. Altogether 441 participants responded (94 returned only the shortened version without TCI-R) and gave their informed consent. VDS involved screening all patients aged 20-60 years (n=806) in the PMCD for a possible new episode of DSM-IV MDD. 542 consenting patients were interviewed with a semi-structured interview (the WHO Schedules for Clinical Assessment in Neuropsychiatry, version 2.0). 269 patients with a current DSM-IV MDD were included in the study and further interviewed with semi-structured interviews to assess all other axis I and II psychiatric diagnoses. Exclusion criteria were DSM-IV bipolar I and II, schizoaffective disorder, schizophrenia or another psychosis, organic and substance-induced mood disorders. In the present study are included those 193 (139 females, 54 males) individuals who could be followed up at both 6 and 18 months, and their depression had remained unipolar. Personality was investigated with the EPI. Personality dimensions associated not only to the symptoms of depression, but also to the symptoms of anxiety among general population and in depressive patients, as well as to comorbid disorders in MDD patients, supporting the dimensional view of depression and anxiety. Among the general population High Harm Avoidance and low Self-Directedness associated moderately, whereas low extraversion and high neuroticism strongly with the depressive and anxiety symptoms. The personality dimensions, especially high Harm Avoidance, low Self-Directedness and high neuroticism were also somewhat predictive of self-reported use of health care services for psychiatric reasons, and lifetime mental disorder. Moreover, high Harm Avoidance associated with a family history of mental disorder. In depressive patients, neuroticism scores were found to decline markedly and extraversion scores to increase somewhat with recovery. The predictive value of the changes in symptoms of depression and anxiety in explaining follow-up neuroticism was about 1/3 of that of baseline neuroticism. In contrast to neuroticism, the scores of extraversion showed no dependence on the symptoms of anxiety, and the change in the symptoms of depression explained only 1/20 of the follow-up extraversion compared with baseline extraversion. No evidence was found of the scar effect during a one-year follow-up period. Finally, even after controlling for symptoms of both depression and anxiety, depressive patients had a somewhat higher level of neuroticism (odds ratio 1.11, p=0.001) and a slightly lower level of extraversion (odds ratio 0.92, p=0.003) than subjects in the general population. Among MDD patients, a positive dose-exposure relationship appeared to exist between neuroticism and prevalence and number of comorbid axis I and II disorders. A negative relationship existed between level of extraversion and prevalence of comorbid social phobia and cluster C personality disorders. Personality dimensions are associated with the symptoms of depression and anxiety. Futhermore these findings support the hypothesis that high neuroticism and somewhat low extraversion might be vulnerability factors for MDD, and that high neuroticism and low extraversion predispose to comorbid axis I and II disorders among patients with MDD.

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Background. Evidence of cognitive dysfunction in depressive and anxiety disorders is growing. However, the neuropsychological profile of young adults has received only little systematic investigation, although depressive and anxiety disorders are major public health problems for this age group. Available studies have typically failed to account for psychiatric comorbidity, and samples derived from population-based settings have also seldom been investigated. Burnout-related cognitive functioning has previously been investigated in only few studies, again all using clinical samples and wide age groups. Aims. Based on the information gained by conducting a comprehensive review, studies on cognitive impairment in depressive and anxiety disorders among young adults are rare. The present study examined cognitive functioning in young adults with a history of unipolar depressive or anxiety disorders in comparison to healthy peers, and associations of current burnout symptoms with cognitive functioning, in a population-based setting. The aim was also to determine whether cognitive deficits vary as a function of different disorder characteristics, such as severity, psychiatric comorbidity, age at onset, or the treatments received. Methods. Verbal and visual short-term memory, verbal long-term memory and learning, attention, psychomotor processing speed, verbal intelligence, and executive functioning were measured in a population-based sample of 21-35 year olds. Performance was compared firstly between participants with pure non-psychotic depression (n=68) and healthy peers (n=70), secondly between pure (n=69) and comorbid depression (n=57), and thirdly between participants with anxiety disorders (n=76) and healthy peers (n=71). The diagnostic procedure was based on the SCID interview. Fourthly, the associations of current burnout symptoms, measured with the Maslach Burnout Inventory General Survey, and neuropsychological test performance were investigated among working young adults (n=225). Results. Young adults with depressive or anxiety disorders, with or without psychiatric comorbidity, were not found to have major cognitive impairments when compared to healthy peers. Only mildly compromised verbal learning was found among depressed participants. Pure and comorbid depression groups did not differ in cognitive functioning, either. Among depressed participants, those who had received treatment showed more impaired verbal memory and executive functioning, and earlier onset corresponded with more impaired executive functioning. In anxiety disorders, psychotropic medication and low psychosocial functioning were associated with deficits in executive functioning, psychomotor processing speed, and visual short-term memory. Current burnout symptoms were associated with better performance in verbal working memory and verbal intelligence. However, lower examiner-rated social and occupational functioning was associated with problems in verbal attention, memory, and learning. Conclusions. Depression, anxiety disorders, or burnout symptoms may not be associated with major cognitive deficits among young adults derived from the general population. Even psychiatric comorbidity may not aggravate cognitive functioning in depressive or anxiety disorders among these young adults. However, treatment-seeking in depression was found to be associated with cognitive deficits, suggesting that these deficits relate to increased distress. Additionally, early-onset depression, found to be associated with executive dysfunction, may represent a more severe form of the disorder. In anxiety disorders, those with low symptom-related psychosocial functioning may have cognitive impairment. An association with self-reported burnout symptoms and cognitive deficits was not detected, but individuals with low social and occupational functioning may have impaired cognition.

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Occupational burnout and heath Occupational burnout is assumed to be a negative consequence of chronic work stress. In this study, it was explored in the framework of occupational health psychology, which focusses on psychologically mediated processes between work and health. The objectives were to examine the overlap between burnout and ill health in relation to mental disorders, musculoskeletal disorders, and cardiovascular diseases, which are the three commonest disease groups causing work disability in Finland; to study whether burnout can be distinguished from ill health by its relation to work characteristics and work disability; and to determine the socio-demographic correlates of burnout at the population level. A nationally representative sample of the Finnish working population aged 30 to 64 years (n = 3151-3424) from the multidisciplinary epidemiological Health 2000 Study was used. Burnout was measured with the Maslach Burnout Inventory - General Survey. The diagnoses of common mental disorders were based on the standardized mental health interview (the Composite International Diagnostic Interview), and physical illnesses were determined in a comprehensive clinical health examination by a research physician. Medically certified sickness absences exceeding 9 work days during a 2-year period were extracted from a register of The Social Insurance Institution of Finland. Work stress was operationalized according to the job strain model. Gender, age, education, occupational status, and marital status were recorded as socio-demographic factors. Occupational burnout was related to an increased prevalence of depressive and anxiety disorders and alcohol dependence among the men and women. Burnout was also related to musculoskeletal disorders among the women and cardiovascular diseases among the men independently of socio-demographic factors, physical strenuousness of work, health behaviour, and depressive symptoms. The odds of having at least one long, medically-certified sickness absence were higher for employees with burnout than for their colleagues without burnout. For severe burnout, this association was independent of co-occurring common mental disorders and physical illnesses for both genders, as was also the case for mild burnout among the women. In a subgroup of the men with absences, severe burnout was related to a greater number of absence days than among the women with absences. High job strain was associated with a higher occurrence of burnout and depressive disorders than low job strain was. Of these, the association between job strain and burnout was stronger, and it persisted after control for socio-demographic factors, health behaviour, physical illnesses, and various indicators of mental health. In contrast, job strain was not related to depressive disorders after burnout was accounted for. Among the working population over 30 years of age, burnout was positively associated with age. There was also a tendency towards higher levels of burnout among the women with low educational attainment and occupational status and among the unmarried men. In conclusion, a considerable overlap was found between burnout, mental disorders, and physical illnesses. Still, burnout did not seem to be totally redundant with respect to ill health. Burnout may be more strongly related to stressful work characteristics than depressive disorders are. In addition, burnout seems to be an independent risk factor for work disability, and it could possibly be used as a marker of health-impairing work stress. However, burnout may represent a different kind of risk factor for men and women, and this possibility needs to be taken into account in the promotion of occupational health.

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In this study, a quality assessment method based on sampling of primary laser inventory units (microsegments) was analysed. The accuracy of a laser inventory carried out in Kuhmo was analysed as a case study. Field sample plots were measured on the sampled microsegments in the Kuhmo inventory area. Two main questions were considered. Did the ALS based inventory meet the accuracy requirements set for the provider and how should a reliable, cost-efficient and independent quality assessment be undertaken. The agreement between control measurement and ALS based inventory was analysed in four ways: 1) The root mean squared errors (RMSEs) and bias were calculated. 2) Scatter plots with 95% confidence intervals were plotted and the placing of identity lines was checked. 3) Bland-Altman plots were drawn so that the mean difference of attributes between the control method and ALS-method was calculated and plotted against average value of attributes. 4) The tolerance limits were defined and combined with Bland-Altman plots. The RMSE values were compared to a reference study from which the accuracy requirements had been set to the service provider. The accuracy requirements in Kuhmo were achieved, however comparison of RMSE values proved to be difficult. Field control measurements are costly and time-consuming, but they are considered to be robust. However, control measurements might include errors, which are difficult to take into account. Using the Bland-Altman plots none of the compared methods are considered to be completely exact, so this offers a fair way to interpret results of assessment. The tolerance limits to be set on order combined with Bland-Altman plots were suggested to be taken in practise. In addition, bias should be calculated for total area. Some other approaches for quality control were briefly examined. No method was found to fulfil all the required demands of statistical reliability, cost-efficiency, time efficiency, simplicity and speed of implementation. Some benefits and shortcomings of the studied methods were discussed.

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In recent years, concern has arisen over the effects of increasing carbon dioxide (CO2) in the earth's atmosphere due to the burning of fossil fuels. One way to mitigate increase in atmospheric CO2 concentration and climate change is carbon sequestration to forest vegeta-tion through photosynthesis. Comparable regional scale estimates for the carbon balance of forests are therefore needed for scientific and political purposes. The aim of the present dissertation was to improve methods for quantifying and verifying inventory-based carbon pool estimates of the boreal forests in the mineral soils. Ongoing forest inventories provide a data based on statistically sounded sampling for estimating the level of carbon stocks and stock changes, but improved modelling tools and comparison of methods are still needed. In this dissertation, the entire inventory-based large-scale forest carbon stock assessment method was presented together with some separate methods for enhancing and comparing it. The enhancement methods presented here include ways to quantify the biomass of understorey vegetation as well as to estimate the litter production of needles and branches. In addition, the optical remote sensing method illustrated in this dis-sertation can be used to compare with independent data. The forest inventory-based large-scale carbon stock assessment method demonstrated here provided reliable carbon estimates when compared with independent data. Future ac-tivity to improve the accuracy of this method could consist of reducing the uncertainties regarding belowground biomass and litter production as well as the soil compartment. The methods developed will serve the needs for UNFCCC reporting and the reporting under the Kyoto Protocol. This method is principally intended for analysts or planners interested in quantifying carbon over extensive forest areas.

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Markov random fields (MRF) are popular in image processing applications to describe spatial dependencies between image units. Here, we take a look at the theory and the models of MRFs with an application to improve forest inventory estimates. Typically, autocorrelation between study units is a nuisance in statistical inference, but we take an advantage of the dependencies to smooth noisy measurements by borrowing information from the neighbouring units. We build a stochastic spatial model, which we estimate with a Markov chain Monte Carlo simulation method. The smooth values are validated against another data set increasing our confidence that the estimates are more accurate than the originals.

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This dissertation develops a strategic management accounting perspective of inventory routing. The thesis studies the drivers of cost efficiency gains by identifying the role of the underlying cost structure, demand, information sharing, forecasting accuracy, service levels, vehicle fleet, planning horizon and other strategic factors as well as the interaction effects among these factors with respect to performance outcomes. The task is to enhance the knowledge of the strategic situations that favor the implementation of inventory routing systems, understanding cause-and-effect relationships, linkages and gaining a holistic view of the value proposition of inventory routing. The thesis applies an exploratory case study design, which is based on normative quantitative empirical research using optimization, simulation and factor analysis. Data and results are drawn from a real world application to cash supply chains. The first research paper shows that performance gains require a common cost component and cannot be explained by simple linear or affine cost structures. Inventory management and distribution decisions become separable in the absence of a set-dependent cost structure, and neither economies of scope nor coordination problems are present in this case. The second research paper analyzes whether information sharing improves the overall forecasting accuracy. Analysis suggests that the potential for information sharing is limited to coordination of replenishments and that central information do not yield more accurate forecasts based on joint forecasting. The third research paper develops a novel formulation of the stochastic inventory routing model that accounts for minimal service levels and forecasting accuracy. The developed model allows studying the interaction of minimal service levels and forecasting accuracy with the underlying cost structure in inventory routing. Interestingly, results show that the factors minimal service level and forecasting accuracy are not statistically significant, and subsequently not relevant for the strategic decision problem to introduce inventory routing, or in other words, to effectively internalize inventory management and distribution decisions at the supplier. Consequently the main contribution of this thesis is the result that cost benefits of inventory routing are derived from the joint decision model that accounts for the underlying set-dependent cost structure rather than the level of information sharing. This result suggests that the value of information sharing of demand and inventory data is likely to be overstated in prior literature. In other words, cost benefits of inventory routing are primarily determined by the cost structure (i.e. level of fixed costs and transportation costs) rather than the level of information sharing, joint forecasting, forecasting accuracy or service levels.

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Two methods of pre-harvest inventory were designed and tested on three cutting sites containing a total of 197 500 m3 of wood. These sites were located on flat-ground boreal forests located in northwestern Quebec. Both methods studied involved scaling of trees harvested to clear the road path one year (or more) prior to harvest of adjacent cut-blocks. The first method (ROAD) considers the total road right-of-way volume divided by the total road area cleared. The resulting volume per hectare is then multiplied by the total cut-block area scheduled for harvest during the following year to obtain the total estimated cutting volume. The second method (STRATIFIED) also involves scaling of trees cleared from the road. However, in STRATIFIED, log scaling data are stratified by forest stand location. A volume per hectare is calculated for each stretch of road that crosses a single forest stand. This volume per hectare is then multiplied by the remaining area of the same forest stand scheduled for harvest one year later. The sum of all resulting estimated volumes per stand gives the total estimated cutting-volume for all cut-blocks adjacent to the studied road. A third method (MNR) was also used to estimate cut-volumes of the sites studied. This method represents the actual existing technique for estimating cutting volume in the province of Quebec. It involves summing the cut volume for all forest stands. The cut volume is estimated by multiplying the area of each stand by its estimated volume per hectare obtained from standard stock tables provided by the governement. The resulting total estimated volume per cut-block for all three methods was then compared with the actual measured cut-block volume (MEASURED). This analysis revealed a significant difference between MEASURED and MNR methods with the MNR volume estimate being 30 % higher than MEASURED. However, no significant difference from MEASURED was observed for volume estimates for the ROAD and STRATIFIED methods which respectively had estimated cutting volumes 19 % and 5 % lower than MEASURED. Thus the ROAD and STRATIFIED methods are good ways to estimate cut-block volumes after road right-of-way harvest for conditions similar to those examined in this study.