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Articles de revues sur le sujet "Mental-health classification"

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Jacob, K. S., et Vikram Patel. « Classification of mental disorders : a global mental health perspective ». Lancet 383, no 9926 (avril 2014) : 1433–35. http://dx.doi.org/10.1016/s0140-6736(13)62382-x.

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Gupta, Daksh, Aashay Markale et Rishabh Kulkarni. « Mental Health Quantifier ». International Journal of Engineering and Advanced Technology 10, no 5 (30 juin 2021) : 187–90. http://dx.doi.org/10.35940/ijeat.e2694.0610521.

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The definition of mental disorders describes them as “health conditions involving changes in emotion, thinking or behavior or a combination of these”. Contemporary societies of 2020 still fall short in recognizing some of the most common afflictions as actual problems in people. Some of those are depression, anxiety and stress disorders. This paper proposes a Machine Learning based approach wherein the analysis of the multiple-choice inputs along with a neatly curated questionnaire based on feature extraction will be done and then supervised classification algorithms will be used to generate a mental health score as well as a detailed report based on responses the user gives.
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Yihai, Wei. « DEVELOPMENT OF A CLASSIFICATION MODEL FOR MENTAL HEALTH ». Young Scholars Journal, no 5-6 (2022) : 12–18. http://dx.doi.org/10.29013/ysj-22-5.6-12-18.

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Ahamat, Boolang R., et Helen Minnis. « Infant mental health : classification and relevance for clinicians ». Psychiatrist 36, no 6 (juin 2012) : 230–34. http://dx.doi.org/10.1192/pb.bp.110.033969.

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SummaryInfant mental health is a growing research area, but findings have not generally translated into new service developments. Recognising mental health problems in young infants is relevant for clinicians in all mental health specialties, but it can be a particular challenge to make diagnoses in very young children. Mental health classification systems are fraught with the difficulties of standardising diagnoses for infants, while trying to provide a clinically useful and relevant framework. The diagnostic classification DC:0–3 appears to have strengths, for example, a clear space to consider relationship disorders, and therefore encouraging a broad assessment of the child and family. More information is beginning to gather regarding infant mental health services around the world and assessment of this patient group in clinical practice. This commentary aims to help inform clinicians about this developing field.
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Grassi, Gaddomaria. « Mental Health Department accreditation. Classification and assessment criteria ». Epidemiologia e Psichiatria Sociale 13, no 2 (juin 2004) : 126–33. http://dx.doi.org/10.1017/s1121189x00003353.

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SummaryAims – To compare different accreditation categories in Italy and to suggest some criteria to assess them. Methods – The A. compare specific characteristics of different model of normative and professional accreditation and suggest some criteria to distinguish different type of accreditation programme and to assess quality and usefulness of an accreditation programme. Results and Conclusions – Different types of accreditation are attributed to some basic criteria: voluntary/by law, high/low stan- dard, assessment object. Criteria to assess the usefulness are: check list accuracy, support to quality improvement, documental bur- den, services impact.
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Wetzel, Janice Wood. « Universal Mental Health Classification Systems : Reclaiming Women's Experience ». Affilia 6, no 3 (octobre 1991) : 8–31. http://dx.doi.org/10.1177/088610999100600302.

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Šablevičius, M. « Taxonomic classification of mental disorders ». European Psychiatry 65, S1 (juin 2022) : S448. http://dx.doi.org/10.1192/j.eurpsy.2022.1138.

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Introduction DSM-5, ICD-10, and ICD-11 classifications can be described as „incoherent“. Psychopathology depends on “time of damage and resilience” ratio. Continuums of mental disorders compose a table, like a periodic table of chemical elements. Similar psychopathology can have different neurobiological origin, and vice versa. Objectives Current classifications of mental disorders ICD-10, DSM-5, as well as the new ICD-11 being developed, do not show interrelations in pathogenesis between groups of mental disorders. This is a weak point of these classifications, although they serve a good purpose in relation to medical statistics and encoding requirements. Methods Taxonomic classification of mental disorders proposed in this empirical study reveals interrelations between diagnostic categories of mental disorders. Classification as an object of this empirical study is initially developed on author’s observation of psychopathology in clinical practice. It also relies on scientific data of genetics and neurobiology of mental disorders. Results The classification is based on two axes system. First axis reflects the time of damage of neural tissue in specific stage, i.e. neuron body genesis, neuron growths genesis, synaptic pruning or further neural information modeling. The second axis is connected with resilience. The two axes system includes in one continuum and connects into one classification table ( Figure 1) almost all diagnostic groups from ICD-10 or DSM-5 (with two exclusions: “organic” type mental disorders and pathology of myelination process). Conclusions This empirically derived concept of classification could be used in clinical practice in differential diagnosis, discovering heterogeneities in patients with same diagnostic “code”, planning treatment strategies, predicting course of mental disorders. Disclosure No significant relationships.
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Suli, Anastas, Ledia Lazëri et Livia Nano. « Mental health services in Albania ». International Psychiatry 1, no 4 (avril 2004) : 14–16. http://dx.doi.org/10.1192/s1749367600006731.

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Albania, situated in the western Balkans, has an area of 28 748 km2 and a population of 3 069 275 (year 2001), almost one-third of whom are aged 0–14 years. Life expectancy is estimated to be 70.4 years for both sexes (World Health Organization, 2003a). According to the World Health Organization's classification, Albania is a country with low child and low adult mortality rates. The nation's total expenditure on health in 2001 amounted to 3.7% of gross domestic product.
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Keeley, Jared W. « Accounting for Social Processes in the Development of Diagnostic Classification Systems : Commentary on the “Standards and Guidelines for the Development of Diagnostic Nomenclatures and Alternatives in Mental Health Research and Practice” ». Journal of Humanistic Psychology 59, no 3 (25 juillet 2018) : 446–52. http://dx.doi.org/10.1177/0022167818788494.

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Diagnostic classifications of mental disorders are complex systems that integrate both scientific and social priorities. The Task Force on Developing Humanistic Approaches to Psychological Diagnosis of the Society for Humanistic Psychology has released a set of guidelines intended to guide the development of mental health classifications. This commentary argues that the attention paid in the guidelines to social processes is a desirable and inherent component of the development of any classification. Social influences regarding the definition of the concepts and the processes by which people develop them are integrally intertwined, contrary to the common view that nonscientific factors should be excluded from classification systems as much as possible. These guidelines offer a much needed resource for developing future mental health classifications.
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Sartorius, N. « How many categories do we need ? » European Psychiatry 41, S1 (avril 2017) : 912. http://dx.doi.org/10.1017/s0924933800284514.

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Abstract of presentation by Prof. N. Sartorius.The presentation will discuss the dependence of the classification of mental disorders on its use. While scientists searching for causes of mental disorders or assessing the effectiveness of a new treatment will need highly homogenous groups of people showing a particular well defined syndrome, practicing clinicians will wish to limit the number of categories in a classification of mental disorders to a level which makes a difference in treatment or management. The World Health Organization has recognized this difference in need and preference and produced in the framework of the 10th Revision of the International Classification of diseases (ICD) a classification of mental disorders in three versions–a version for practicing psychiatrists, a version for use in scientific investigations and a version for use in primary health care. The three versions were translatable (“telescoped”) into each other. The field tests of the three versions of the classification demonstrated that they are easy to use, can be used reliably and fit the syndromes usually encountered in health care services. These findings further supported the Sir Aubrey Lewis’ proposal to accept the division of classifications into a public and several (or many) private versions translatable into each other.Disclosure of interestThe author has not supplied his declaration of competing interest.
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Thèses sur le sujet "Mental-health classification"

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Wittchen, Hans-Ulrich, Samia Härtling et Jürgen Hoyer. « Psychotherapy and Mental Health as a Psychological Science Discipline ». Karger, 2015. https://tud.qucosa.de/id/qucosa%3A71679.

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The psychological sciences offer a large spectrum of theories, principles, and methodological approaches to understand mental health, normal and abnormal functions and behaviours, as well as mental disorders. Based on continued research progress, psychology has derived a wide range of effective interventions for behaviour change and the prevention, treatment and rehabilitation of mental disorders. Thus, psychology and clinical psychology in particular should be regarded as the ‘mother’ science for psychotherapy and psychotherapeutic practice. This paper provides a selective overview of the scope, strengths and gaps in psychological research to depict the advances needed to inform future research agendas on mental disorders and psychological interventions in the context of psychotherapy. Most maladaptive health behaviours and mental disorders can be conceptualised as the result of developmental dysfunctions of psychological functions and processes, and as associated neurobiological and genetic processes in interaction with behaviour and the environment. An integrative translational model, linking basic and experimental research with clinical research and population-based prospective longitudinal studies is proposed for improving identification of critical core vulnerability and risk factors and core pathogenic mechanisms. The proposed framework is expected to allow a more stringent delineation of targeted preventive and therapeutic psychological interventions and an optimisation and better understanding of cognitive-behavioural therapies and other psychological interventions. Based on a European consultation process, a ‘Science of Behaviour Change’ programme with the promise of improved diagnosis, treatment and prevention of both healthrisk behaviour constellations and mental disorders is proposed.
Psychologie als «Mutterwissenschaft» für Psychotherapie und psychische Gesundheit Psychologie als Wissenschaft bietet ein breites Spektrum an Theorien, Grundlagen und methodischen Ansätzen, um psychische Gesundheit, normale und gestörte Funktionen und Verhaltensweisen sowie psychische Störungen zu erforschen und zu «verstehen». Auf dieser Grundlage haben sich in der Klinischen Psychologie vielfältige effektive, psychologisch begründete Interventionen für die Prävention, Behandlung und Rehabilitation von psychischen Störungen ausdifferenziert. Damit ist die Psychologie als «Mutterwissenschaft » der Psychotherapie und psychotherapeutische Praxis anzusehen. Der Beitrag versucht auf der Grundlage einer Stärken-/Schwächen-Analyse der psychologischen Forschung diejenigen Themenbereiche zu definieren, die für Erkenntnisfortschritte bei psychischen Störungen und die psychotherapeutische Interventionsforschung besonders vielversprechend sein könnten. Dysfunktionale bzw. abweichende Verhaltensweisen wie auch psychische Störungen lassen sich als entwicklungsbezogene Störungen psychologischer Funktionen und Prozesse und damit assoziierter neurobiologischer und genetischer Prozesse konzeptualisieren. Für eine verbesserte Identifikation von zentralen Vulnerabilitäts- und Risikofaktoren sowie ätiologisch relevanten Schlüsselprozessen wird ein integratives translationales Modell vorgeschlagen, welches die Grundlagen- und experimentelle Forschung mit klinischer Forschung, Translation und Public-health-Implikationen verknüpft. Damit soll auf der einen Seite eine stringentere Ableitung gezielter Interventionen erleichtert werden, andererseits aber auch eine bessere Identifikation der zentralen Wirkfaktoren und Wirkprozesse psychologischer Therapien ermöglicht werden. Basierend auf einem europäischen Experten-Beratungsprozess wird ein EU-Programm ‘The science of behavior change’ angeregt.
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Holz, Manuel. « Health Inequalities in Germany : Assessing Differences in Health of Migrants and Native Germans Using a Propensity Score Matching Approach and the SF-12 Physical and Mental Health Scale ». Technische Universität Chemnitz, 2019. https://monarch.qucosa.de/id/qucosa%3A38385.

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The aim of the study is to compare health outcomes of migrants and the native German population, testing for the existence of a Healthy Immigrant Effect (HIE). The study contributes a broad theoretical analysis of the HIE and makes use of a wide spectrum of variables to model health (using the SF-12). The HIE is marked by an observed health advantage for migrants, when compared to the host population, which declines with the years since migration. Assessing different types of selection processes, it is assumed that mass migration to post-industrial countries is characterized by favouring the inflow of healthy individuals from weaker economies working in the low-wage sector due to the cost aspect of migration and differences in wages for adequate work. Socioeconomic and -structural differences of migrant and host population as well as psychosocial stressors like acculturation cause the deteroriation of the health adavantage with increasing years since migration. Using cross-sectional data from the 2016 wave of the Socio-Economic Panel this study compares health outcomes (generated from the SF-12) between recent migrants (≤ 10 years since migration), non-recent migrants (> 10 years since migration) and the German native population. Propensity score matching analyses reveal a health advantage for recent migrants compared to non-recent migrants as well as to the German native population, while non-recent migrants remain statistically indistinguishable from the native German population, implying a health assimilation effect.
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Kalckreuth, Sophie, Friederike Trefflich et Christine Rummel-Kluge. « Mental health related Internet use among psychiatric patients : a cross-sectional analysis ». BioMed Central, 2014. https://ul.qucosa.de/id/qucosa%3A13091.

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Background: The Internet is of great importance in today’s health sector, as most Internet users utilize online functions for health related purposes. Concerning the mental health care sector, little data exist about the Internet use of psychiatric patients. It is the scope of this current study to analyze the quantity and pattern of Internet usage among mental health patients. Methods: Patients from all services of the Department of Psychiatry at a university hospital were surveyed by completing a 29-item questionnaire. The data analysis included evaluation of frequencies, as well as group comparisons. Results: 337 patients participated in the survey, of whom 79.5% were Internet users. Social media was utilized by less than half of the users: social networks (47.8%), forums (19.4%), chats (18.7%), blogs (12.3%). 70.9% used the Internet for mental health related reasons. The contents accessed by the patients included: information on mental disorders (57.8%), information on medication (43.7%), search for mental health services (38.8%), platforms with other patients (19.8%) and platforms with mental health professionals (17.2%). Differences in the pattern of use between users with low, medium and high frequency of Internet use were statistically significant for all entities of social media (p < 0.01), search for mental health services (p = 0.017) and usage of platforms with mental health professionals (p = 0. 048). The analysis of differences in Internet use depending on the participants’ type of mental disorder revealed no statistically significant differences, with one exception. Regarding the Internet’s role in mental health care, the participants showed differing opinions: 36.2% believe that the Internet has or may have helped them in coping with their mental disorder, while 38.4% stated the contrary. Conclusions: Most psychiatric patients are Internet users. Mental health related Internet use is common among patients, mainly for information seeking. The use of social media is generally less frequent. It varies significantly between different user types and was shown to be associated with high frequency of Internet use. The results illustrate the importance of the Internet in mental health related contexts and may contribute to the further development of mental health related online offers.
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Volkert, Jana, Sylke Andreas, Martin Härter, Maria Christina Dehoust, Susanne Sehner, Anna Suling, Berta Ausín et al. « Predisposing, enabling, and need factors of service utilization in the elderly with mental health problems ». Cambridge University Press, 2018. https://tud.qucosa.de/id/qucosa%3A70712.

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Background: Empirical data on the use of services due to mental health problems in older adults in Europe is lacking. The objective of this study is to identify factors associated with service utilization in the elderly. Methods: As part of the MentDis_ICF65+ study, N = 3,142 people aged 65–84 living in the community in six European and associated countries were interviewed. Based on Andersen’s behavioral model predisposing, enabling, and need factors were analyzed with logistic regression analyses. Results: Overall, 7% of elderly and 11% of those with a mental disorder had used a service due to mental health problems in the last 12 months. Factors significantly associated with underuse were male sex, lower education, living in the London catchment area, higher functional impairment and more comorbid mental disorders. The most frequently reported barrier to service use was personal beliefs, e.g. “I can deal with my problem on my own” (90%). Conclusion: Underutilization of mental health services among older people in the European community is common and interventions are needed to achieve an adequate use of services.
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Wille, Nora, Susanne Bettge, Hans-Ulrich Wittchen et Ulrike Ravens-Sieberer. « How impaired are children and adolescents by mental health problems ? Results of the BELLA study ». Technische Universität Dresden, 2008. https://tud.qucosa.de/id/qucosa%3A26677.

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Background: The consideration of impairment plays a crucial role in detecting significant mental health problems in children whose symptoms do not meet diagnostic criteria. The assessment of impairment may be particularly relevant when only short screening instruments are applied in epidemiological surveys. Furthermore, differences between childrens’ and parents’ perceptions of present impairment and impairing symptoms are of interest with respect to treatment-seeking behaviour. Objectives: The objectives were to assess parent- and self-reported impairment due to mental health problems in a representative sample of children and adolescents; to describe the characteristics of highly impaired children with normal symptom scores; and to investigate the associations between symptoms in different problem areas and impairment. Methods: The mental health module of the German Health Interview and Examination Survey for Children and Adolescents (the BELLA study) examined mental health in a representative sub-sample of 2,863 families with children aged 7–17. Self-reported and parent-reported symptoms of mental health problems and associated impairment were identified by the extended version of the strengths and difficulties questionnaire (SDQ) in children 11 years and older. Results: Considerable levels of distress and functional impairment were found with 14.1% of the boys and 9.9% of the girls being severely impaired according to the parental reports. However, self-reported data shows a reversed gender-difference as well as lower levels of severe impairment (6.1% in boys; 10.0% in girls). Six percent of the sampled children suffer from pronounced impairment due to mental health problems but were not detected by screening for overall symptoms. Childrens’ and parents’ reports differed in regard to the association between reported symptom scores and associated impairment with children reporting higher impairment due to emotional problems. Conclusions: The assessment of impairment caused by mental health problems provides important information beyond the knowledge of symptoms and helps to identify an otherwise undetected high risk group. In the assessment of impairment, gender-specific issues have to be taken into account. Regarding the systematic differences between childrens’ and parents’ reports in the assessment of impairment, the child’s perspective should be given special attention.
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Herget, Sabine, Almut Rudolph, Anja Hilbert et Susann Blüher. « Psychosocial status and mental health in adolescents before and after bariatric surgery ». Universitätsbibliothek Leipzig, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-149664.

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Objective: As long-term results of conservative treatment for obesity are discouraging, bariatric surgery is becoming a treatment option for extremely obese adolescents. However, mental and behavioral problems need to be respected when treating this vulnerable target group. Methods: A detailed systematic literature review on pre- and post-operative depressive, anxiety and eating disorder symptoms of adolescent patients was performed in PsychINFO, PubMed and Medline electronic databases. Results: Twelve studies met the inclusion criteria. Although strength of evidence was limited, results suggested that pre-operatively a third of adolescents suffered from moderate to severe depressive disorder symptoms and a quarter from anxiety disorder symptoms, while a substantial number showed eating disorder symptoms. Post-operatively, levels of depressive disorder symptoms significantly improved. Original articles on outcomes of eating and anxiety disorder symptoms after weight loss surgery were not found. Conclusions: Further attention is needed on consistent clinical assessment of mental health disturbances and their consecutive treatment in adolescents. Future research should also focus on psychological and psychosocial predictors of weight loss after bariatric surgery.
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Ravens-Sieberer, Ulrike, Nora Wille, Michael Erhart, Susanne Bettge, Hans-Ulrich Wittchen, Aribert Rothenberger, Beate Herpertz-Dahlmann et al. « Prevalence of mental health problems among children and adolescents in Germany : Results of the BELLA study within the National Health Interview and Examination Survey ». Technische Universität Dresden, 2008. https://tud.qucosa.de/id/qucosa%3A26672.

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Background: Over the past decades the public health relevance of mental health conditions in children and adolescents has been of growing concern. However, so far no detailed epidemiological data has been available for a representative national sample in Germany. Objectives: The present paper reports prevalence rates of general and specific mental health problems among children and adolescents in Germany and describes the link between symptoms and impairment as well as the treatment situation. Methods: The mental health module (BELLA study) examines mental health problems in a representative sub-sample of 2,863 families with children aged 7–17 from the National Health Interview and Examination Survey among Children and Adolescents (KiGGS). Mental health problems were determined using the extended version of the strengths and difficulties questionnaire (SDQ). Further standardised screening measures were employed to screen for anxiety disorders (SCARED), conduct disorder (CBCL), attention deficit-/ hyperactivity disorder (FBBHKS, Conners’ Scale) and depressive disorders (CES-DC). Furthermore, substance abuse and suicidal tendencies were assessed. Health-related quality of life (HRQoL) and health care use were determined. Results Overall, 14.5% of the children and adolescents aged 7–17 fulfilled the criteria for at least one specific mental health problem associated with impairment, or had an overall mental health problem indicated by an abnormal SDQ score and present impairment. However, high comorbidity was found in the children concerned. Symptoms of overall mental health problems were present in 8.6% of the children and 6.6% of the adolescents. This number was reduced to prevalence rates of 6.3 and 4.9% when additional impairment was taken as a criterion. Irrespective of the type of disorder, fewer than half of the children affected were reported as receiving treatment. However, for those suffering from mental health problems, large impairments in HRQoL were observed. Conclusions: The observed prevalence of mental health problems as well as their large impact on well-being and functioning calls for early prevention. This is especially important with regard to the large decrease in HRQoL in the children and adolescents affected.
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Jacobi, Frank, Hans-Ulrich Wittchen, C. Hölting, M. Höfler, H. Pfister, N. Müller et R. Lieb. « Prevalence, co-morbidity and correlates of mental disorders in the general population : results from the German Health Interview and Examination Survey (GHS) ». Cambridge University Press, 2004. https://tud.qucosa.de/id/qucosa%3A26137.

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Background. The German National Health Interview and Examination Survey (GHS) is the first government mandated nationwide study to investigate jointly the prevalence of somatic and mental disorders within one study in the general adult population in Germany. This paper reports results from its Mental Health Supplement (GHS-MHS) on 4-week 12-month, and selected lifetime prevalence of a broad range of DSM-IV mental disorders, their co-morbidity and correlates in the community. Methods. The sample of the GHS-MHS (n=4181; multistage stratified random sample drawn from population registries ; conditional response rate: 87.6%) can be regarded as representative for the German population aged 18–65. Diagnoses are based on fully structured computer assisted clinical interviews (M-CIDI), conducted by clinically trained interviewers. Results. 12-month prevalence for any DSM-IV study disorder is 31% (lifetime: 43%; 4-week: 20%) with anxiety disorders, mood disorders and somatoform syndromes being the most frequent diagnoses. Retrospective age of onset information reveals that most disorders begin early in life. Comorbidity rates among mental disorders range from 44% to 94%. Correlates of increased rates of mental disorders and co-morbidity were: female gender (except for substance disorders), not being married, low social class, and poor somatic health status. Health care utilization for mental disorders depended on co-morbidity (30% in ‘pure’, 76% in highly co-morbid cases) and varied from 33% for substance use disorders to 75% for panic disorder. Conclusions. Results confirm and extend results from other national studies using the same assessment instruments with regard to prevalence, co-morbidity and sociodemographic correlates, covering a broader range of DSM-IV disorders [i.e. somatoform disorders, all anxiety disorders (except PTSD), mental disorders due to substance or general medical factor, eating disorders]. Intervention rates were higher than in previous studies, yet still low overall.
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Gopchandani, Sandhya. « Using Word Embeddings to Explore the Language of Depression on Twitter ». ScholarWorks @ UVM, 2019. https://scholarworks.uvm.edu/graddis/1072.

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How do people discuss mental health on social media? Can we train a computer program to recognize differences between discussions of depression and other topics? Can an algorithm predict that someone is depressed from their tweets alone? In this project, we collect tweets referencing “depression” and “depressed” over a seven year period, and train word embeddings to characterize linguistic structures within the corpus. We find that neural word embeddings capture the contextual differences between “depressed” and “healthy” language. We also looked at how context around words may have changed over time to get deeper understanding of contextual shifts in the word usage. Finally, we trained a deep learning network on a much smaller collection of tweets authored by individuals formally diagnosed with depression. The best performing model for the prediction task is Convolutional LSTM (CNN-LSTM) model with a F-score of 69% on test data. The results suggest social media could serve as a valuable screening tool for mental health.
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Wittchen, Hans-Ulrich. « Women-specific mental disorders in DSM-V : are we failing again ? » Technische Universität, 2010. https://tud.qucosa.de/id/qucosa%3A25035.

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Despite a wealth of studies on differences regarding the biobehavioral and social–psychological bases of mental disorders in men and women and repeated calls for increased attention, women-specific issues have so far not been comprehensively addressed in past diagnostic classification systems of mental disorders. There is also increasing evidence that this situation will not change significantly in the upcoming revisions of ICD-11 and DSM-V. This paper explores reasons for this continued failure, highlighting three major barriers: the fragmentation of the field of women's mental health research, lack of emphasis on diagnostic classificatory issues beyond a few selected clinical conditions, and finally, the “current rules of game” used by the current DSM-V Task Forces in the revision process of DSM-V. The paper calls for concerted efforts of researchers, clinicians, and other stakeholders within a more coherent and comprehensive framework aiming at broader coverage of women-specific diagnostic classificatory issues in future diagnostic systems.
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Livres sur le sujet "Mental-health classification"

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1946-, Stark Jack A., United States. President's Committee on Mental Retardation. et National Strategies Conference on Mental Illness in the Mentally Retarded (1985 : Washington, D.C.), dir. Mental retardation and mental health : Classification, diagnosis, treatment, services. New York : Springer-Verlag, 1988.

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1946-, Stark Jack A., UnitedStates. President's Committee on Mental Retardation. et National Strategy Conference on Mental Illness in the Mentally Retarded (1985 : Washington), dir. Mental retardation andmental health : Classification, diagnosis, treatment, services. New York : Springer-Verlag, 1988.

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B, Payne Dorris, dir. Psychiatric-mental health nursing. 4e éd. [New Hyde Park, N.Y.] : Medical Examination Pub. Co., 1986.

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Mental health & mental illness. 6e éd. Philadelphia : Lippincott-Raven, 1998.

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1930-, Morgan Arthur James, et Morgan Arthur James 1930-, dir. Mental health and mental illness. 3e éd. Philadelphia : Lippincott, 1985.

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Mental health and mental illness. 4e éd. Philadelphia : Lippincott, 1990.

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Mental health and mental illness. 5e éd. Philadelphia : J.B. Lippincott Co., 1994.

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Maj, Mario. Psychiatric diagnosis and classification. New York : John Wiley, 2002.

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Carthew, Richard. Mental health services : How a classification of people and services describes and helps mental health services : a briefing paper. [Bristol] : NHS Information Authority, 2000.

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American Association on Mental Retardation., dir. Mental retardation : Definition, classification, and systems of supports : workbook. Washington, D.C : American Association on Mental Retardation, 2002.

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Chapitres de livres sur le sujet "Mental-health classification"

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Klinkman, Michael, Christopher Dowrick et Sandra Fortes. « Mental health classification in primary care ». Dans Companion to Primary Care Mental Health, 166–77. London : CRC Press, 2022. http://dx.doi.org/10.1201/9781846198465-13.

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O’Reilly, Michelle, et Jessica Nina Lester. « Classification Systems and Diagnostic Processes ». Dans Examining Mental Health through Social Constructionism, 53–73. Cham : Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60095-6_3.

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Rebello, Tahilia J., Danielle M. Polland, Adina C. Heckelman, Elizabeth Magill, Geoffrey M. Reed et Kathleen M. Pike. « Classification : The Foundation and Essential Catalyst for Advancing Mental Health Globally ». Dans Innovations in Global Mental Health, 1–16. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-70134-9_111-1.

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Rebello, Tahilia J., Danielle M. Polland, Adina C. Heckelman, Elizabeth Magill, Geoffrey M. Reed et Kathleen M. Pike. « Classification : The Foundation and Essential Catalyst for Advancing Mental Health Globally ». Dans Innovations in Global Mental Health, 1271–86. Cham : Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-57296-9_111.

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León, Carlos A. « Anxiety Disorders : Considerations from the Perspectives of Primary Mental Health Care ». Dans Clinical Psychopathology Nomenclature and Classification, 783–88. Boston, MA : Springer US, 1985. http://dx.doi.org/10.1007/978-1-4899-5049-9_132.

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Stiffler, Meghan C., et Bridget V. Dever. « History of Screening Practices, Mental Health Assessment, and Classification in the USA ». Dans Mental Health Screening at School, 5–26. Cham : Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19171-3_2.

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L’Abate, Luciano. « Interactive Practice Exercises for Psychiatric Classification ». Dans Sourcebook of Interactive Practice Exercises in Mental Health, 95–332. New York, NY : Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-1354-8_11.

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Sartorius, Norman. « The Programmes of the World Health Organization Directed to the Improvement of Nomenclature and Classification in Mental Health ». Dans Clinical Psychopathology Nomenclature and Classification, 23–29. Boston, MA : Springer US, 1985. http://dx.doi.org/10.1007/978-1-4899-5049-9_3.

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Nielsen, Rune Kristian Lundedal. « Gaming Disorder - a "lousy" and "meaningless" label ». Dans Mental Health | Atmospheres | Video Games, 21–34. Bielefeld, Germany : transcript Verlag, 2022. http://dx.doi.org/10.14361/9783839462645-004.

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In this article, Rune K. L. Nielsen critically examines the World Health Organization's decision to include "Gaming Disorder" as a "disorder due to addictive behavior" in the International Classification of Diseases (ICD-11). Whether gaming should be recognized as an addictive behavior is hotly debated in the research community. Nielsen argues that the current debate is not likely to subside any time soon as both sides surprisingly agree that we don't know e.g., what Gaming Disorder is, what it looks like, how dangerous or problematic it is, or whether it is best understood as a disorder or as a symptom.
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Berrios, German E., et Ivana S. Marková. « The epistemology and classification of ‘madness’ since the eighteenth century ». Dans The Routledge History of Madness and Mental Health, 115–34. Milton Park, Abingdon, Oxon ; New York, NY : Routledge, 2017. | : Routledge, 2017. http://dx.doi.org/10.4324/9781315202211-7.

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Actes de conférences sur le sujet "Mental-health classification"

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Pink, Glen, Will Radford et Ben Hachey. « Classification of mental health forum posts ». Dans Proceedings of the Third Workshop on Computational Lingusitics and Clinical Psychology. Stroudsburg, PA, USA : Association for Computational Linguistics, 2016. http://dx.doi.org/10.18653/v1/w16-0324.

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Surana, Praatibh, Mirza Yusuf et Sanjay Singh. « Severity Classification of Mental Health Related Tweets ». Dans 2021 IEEE International Conference on Distributed Computing, VLSI, Electrical Circuits and Robotics (DISCOVER). IEEE, 2021. http://dx.doi.org/10.1109/discover52564.2021.9663651.

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Gangbo, Suvarna, et Ganeshayya Shidaganti. « Classification of Student Mental Health Prediction Using LSTM ». Dans 2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT). IEEE, 2022. http://dx.doi.org/10.1109/gcat55367.2022.9972061.

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Laijawala, Vidit, Aadesh Aachaliya, Hardik Jatta et Vijaya Pinjarkar. « Classification Algorithms based Mental Health Prediction using Data Mining ». Dans 2020 5th International Conference on Communication and Electronics Systems (ICCES). IEEE, 2020. http://dx.doi.org/10.1109/icces48766.2020.9137856.

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Vaughan, Neil, Maurice Mulvenna et Raymond B. Bond. « Colour Coded Emotion Classification in Mental Health Social Media ». Dans Proceedings of the 32nd International BCS Human Computer Interaction Conference. BCS Learning & Development, 2018. http://dx.doi.org/10.14236/ewic/hci2018.172.

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Shickel, Benjamin, Scott Siegel, Martin Heesacker, Sherry Benton et Parisa Rashidi. « Automatic Detection and Classification of Cognitive Distortions in Mental Health Text ». Dans 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE). IEEE, 2020. http://dx.doi.org/10.1109/bibe50027.2020.00052.

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« Classification of Mental and Behavioural Disorders and the Issue of Destigmatization of Mentally Sick ». Dans Congress on mental health meeting the needs of the XXI century. Gorodets, 2016. http://dx.doi.org/10.22343/mental-health-congress-compendium268-271.

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Elmunsyah, Hakkun, Risalatul Mu'awanah, Triyanna Widiyaningtyas, Ilham A. E. Zaeni et Felix Andika Dwiyanto. « Classification of Employee Mental Health Disorder Treatment with K-Nearest Neighbor Algorithm ». Dans 2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE). IEEE, 2019. http://dx.doi.org/10.1109/iceeie47180.2019.8981418.

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Herus, Olha, Tereza Klymus, Marta Kozak et Uljana Yatschyn. « MENTAL HEALTH REHABILITATION IN ICD CLASSIFICATION FOR PEOPLE WITH DISABILITY IN UKRAINE ». Dans International Scientific and Practical Conference “Partnerships for Social Change : 20 Years of Experience”, Devoted to the 20th Anniversary of Canada-Ukraine “Reforming Social Services” Project (1999-2003). NDSAN (MFC - coordinator of the NDSAN), 2019. http://dx.doi.org/10.32437/pscproceedings.issue-2019.hkky.11.

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Zhang, Xiaokun. « Research on Mental Health Rating Algorithm Based on Big Data Classification Algorithm ». Dans ICISCAE 2021 : 2021 IEEE 4th International Conference on Information Systems and Computer Aided Education. New York, NY, USA : ACM, 2021. http://dx.doi.org/10.1145/3482632.3482656.

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