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Journal articles on the topic 'Mental-health classification'

Author: Grafiati

Published: 9 March 2023

Last updated: 31 July 2025

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1

Daksh, Gupta, Markale Aashay, and Kulkarni Rishabh. "Mental Health Quantifier." International Journal of Engineering and Advanced Technology (IJEAT) 10, no. 5 (2021): 187–90. https://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 t

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

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Sutranggono, Abi Nizar, Riyanarto Sarno, and Imam Ghozali. "Multi-Class Multi-Level Classification of Mental Health Disorders Based on Textual Data from Social Media." Journal of Information and Communication Technology 23, no. 1 (2024): 77–104. http://dx.doi.org/10.32890/jict2024.23.1.4.

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Mental health disorders pose a significant global public health challenge. Social media data provides insights into these conditions.Analysing text can help identify indications of mental health disorders through text-based analysis. However, despite the largenumber of studies on the analysis of mental health disorders, the predominant algorithm in the existing literature is the Multi-ClassSingle-Level (MCSL) classification algorithm, which is often used for simple classification tasks involving a limited number of classes.Typically, these classes are binary, representing either an unhealthy o

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Gupta, Daksh, Aashay Markale, and Rishabh Kulkarni. "Mental Health Quantifier." International Journal of Engineering and Advanced Technology 10, no. 5 (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

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5

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., and Helen Minnis. "Infant mental health: classification and relevance for clinicians." Psychiatrist 36, no. 6 (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 consi

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Grassi, Gaddomaria. "Mental Health Department accreditation. Classification and assessment criteria." Epidemiologia e Psichiatria Sociale 13, no. 2 (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, suppor

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Wetzel, Janice Wood. "Universal Mental Health Classification Systems: Reclaiming Women's Experience." Affilia 6, no. 3 (1991): 8–31. http://dx.doi.org/10.1177/088610999100600302.

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Basuki, Setio, Rizky Indrabayu, and Nico Ardia Effendy. "Automatic Categorization of Mental Health Frame in Indonesian X (Twitter) Text using Classification and Topic Detection Techniques." Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika 10, no. 2 (2025): 104–10. https://doi.org/10.23917/khif.v10i2.3328.

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This paper aims to develop a machine learning model to detect mental health frames in Indonesian-language tweets on the X (Twitter) platform. This research is motivated by the gap in automatically detecting mental health frames, despite the importance of mental health issues in Indonesia. This paper addresses the problem by applying classification and topic detection methods across various mental health frames through multiple stages. First, this paper examines various mental health frames, resulting in 7 main labels: Awareness, Classification, Feelings and Problematization, Accessibility and

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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 (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 d

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Barke, Aniket. "Mental Health Companion." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem30796.

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This research endeavors to address the critical challenge of timely identification and intervention in mental health disorders, particularly depression. Utilizing self- reported symptoms obtained through survey responses, alongside essential demographic and personal data, we aim to develop a predictive model for the early detection of mental health issues. The dataset, comprising diverse survey responses, provides a comprehensive understanding of participants' mental well-being. Employing advanced machine learning techniques, we seek to uncover patterns that can contribute to an effective pred

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Suli, Anastas, Ledia Lazëri, and Livia Nano. "Mental health services in Albania." International Psychiatry 1, no. 4 (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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Mulyani, Sri Hasta. "Enhancing Mental Health Disorders Classification using Convolutional Variational Autoencoder." International Journal of Informatics and Computation 6, no. 1 (2024): 1. http://dx.doi.org/10.35842/ijicom.v6i1.65.

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This research investigates the application of Convolutional Variational Autoencoder (CVAE) for multi-class classification of mental health disorders. The study utilizes a diverse dataset comprising five classes: Normal, Anxiety, Depression, Loneliness, and Stress. The CVAE model effectively captures spatial dependencies and learns latent representations from the mental health disorder data. The classification results demonstrate high precision, recall, and F1 scores for all classes, indicating the model's robustness in distinguishing between different disorders accurately. The research contrib

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Šablevičius, M. "Taxonomic classification of mental disorders." European Psychiatry 65, S1 (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 purp

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Sartorius, N. "How many categories do we need?" European Psychiatry 41, S1 (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

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Clark, Kelly N., Grace Blyth, Meagan Plant, Kyle Wilson, and Christine K. Malecki. "Dual-factor mental health in adolescence: Comparing classification methods." Journal of School Psychology 107 (December 2024): 101391. http://dx.doi.org/10.1016/j.jsp.2024.101391.

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Jones, Kevin Matthew. "The history of psychiatric classification and mental health statistics." Significance 22, no. 2 (2025): 12–17. https://doi.org/10.1093/jrssig/qmaf006.

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Abstract The official collection of mental health data began in the nineteenth-century asylums of England, and debate around classification still rages today. Kevin Matthew Jones shares a fascinating exploration of the historical links between diagnosis and mental health statistics

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Sartorius, N. "Ethical Issues Arising in Revising Classifications of Mental Disorders." European Psychiatry 24, S1 (2009): 1. http://dx.doi.org/10.1016/s0924-9338(09)70333-5.

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The classification of mental disorders in the International Classification of Diseases (ICD) will be revised in the course of the next three years and its publication (as the 11th Revision of the ICD) will be published, after the approval of the World Health Assembly in 2014. In parallel, the American Psychiatric Association created a Task Force which has begun work on the proposals for the revision of its Diagnostic and Statistical Manual which is to be published as the DSM 5th Revision, in 2012. The World Health Organization has established a special advisory group that should assist it in d

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Pokhilenko, Irina, Mencia R. Gutierrez-Colosia, Luca M. M. Janssen, et al. "Clarifying terminology and definitions in education services for mental health users: A disambiguation study." PLOS ONE 19, no. 7 (2024): e0306539. http://dx.doi.org/10.1371/journal.pone.0306539.

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In the wake of the mental health crisis in children and adolescents, the coordination of education and mental health services has become a global priority. However, differing terminologies and classifications across sectors, hinder effective comparison. The classification in education focuses mainly on outputs like qualifications or throughputs like teaching programs. This proof-of-concept study tested the applicability of a standard classification of health services, the Description and Evaluation of Services and DirectoriEs (DESDE), to evaluate education services for mental health users in t

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Stone, Louise, Elizabeth Waldron, and Heather Nowak. "Making a good mental health diagnosis: Science, art and ethics." Australian Journal of General Practice 49, no. 12 (2020): 797–802. http://dx.doi.org/10.31128/ajgp-08-20-5606.

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Background There are limitations to psychiatric classification, which affects the utility of diagnosis in general practice. Objective The aim of this article is to explore the principles of science, art and ethics to create clinically useful psychiatric diagnoses in general practice. Discussion Psychiatric classification systems provide useful constructs for clinical practice and research. Evidence-based treatments are based on the classification of mental illnesses. However, while classification is necessary, it is not sufficient to provide a full understanding of ‘what is going on’. A good p

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Tran, Nam, Jeffrey W. Poss, Christopher Perlman, and John P. Hirdes. "Case-Mix Classification for Mental Health Care in Community Settings: A Scoping Review." Health Services Insights 12 (January 2019): 117863291986224. http://dx.doi.org/10.1177/1178632919862248.

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As mental health care transitions from facility-based care to community-based services, methods to classify patients in terms of their expected health care resource use are an essential tool to balance the health care needs and equitable allocation of health care resources. This study performed a scoping review to summarize the nature, extent, and range of research on case-mix classifications used to predict mental health care resource use in community settings. This study identified 17 eligible studies with 32 case-mix classification systems published since the 1980s. Most of these studies ca

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Al-zanam, Adel Aref Ali, Omer Hussein Abdou Elsayed Hussein Alhomery, and Choo Peng Tan. "Mental Health State Classification Using Facial Emotion Recognition and Detection." International Journal on Advanced Science, Engineering and Information Technology 13, no. 6 (2023): 2274–81. http://dx.doi.org/10.18517/ijaseit.v13i6.19055.

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Analyzing and understanding emotion can help in various aspects, such as realizing oneâ€™s attitude, behavior, etc. By understanding oneâ€™s emotions, one's mental health state can be calculated, which can help in the medical field by classifying whether one is mentally stable or not. Facial Recognition is one of the many fields of computer vision that utilizes convolutional networks or Conv Nets to perform, train, and learn. Conv Nets and other machine learning algorithms have evolved to adapt better to larger datasets. One of the advancements in Conv Nets and machines is the introduction of

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Al-zanam, Adel Aref Ali, Omer Hussein Abdou Elsayed Hussein Alhomery, and Choo Peng Tan. "Mental Health State Classification Using Facial Emotion Recognition and Detection." International Journal on Advanced Science, Engineering and Information Technology 13, no. 6 (2023): 2274–81. http://dx.doi.org/10.18517/ijaseit.13.6.19055.

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Analyzing and understanding emotion can help in various aspects, such as realizing oneâ€™s attitude, behavior, etc. By understanding oneâ€™s emotions, one's mental health state can be calculated, which can help in the medical field by classifying whether one is mentally stable or not. Facial Recognition is one of the many fields of computer vision that utilizes convolutional networks or Conv Nets to perform, train, and learn. Conv Nets and other machine learning algorithms have evolved to adapt better to larger datasets. One of the advancements in Conv Nets and machines is the introduction of

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SHIVANGI, JAIN, and GANGWAR MOHIT. "A MINING ANALYSIS OVER PSYCHIATRIC DATABASE FOR MENTAL HEALTH CLASSIFICATION." i-manager's Journal on Computer Science 5, no. 1 (2017): 7. http://dx.doi.org/10.26634/jcom.5.1.13792.

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De Jong, A. "Development of the International Classification of Mental Health Care (ICMHC)." Acta Psychiatrica Scandinavica 102 (October 2000): 8–13. http://dx.doi.org/10.1111/j.0902-4441.2000.acp28--04.x.

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de Jong, A. "Development of the International Classification of Mental Health Care (ICMHC)." Acta Psychiatrica Scandinavica 102, Supplement 405 (2000): 8–13. http://dx.doi.org/10.1111/j.0902-4441.2000.acp28[dash]04.x.

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Johnson, S., and L. Salvador-Carulla. "Description and classification of mental health services: a European perspective." European Psychiatry 13, no. 7 (1998): 333–41. http://dx.doi.org/10.1016/s0924-9338(99)80699-3.

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SummaryWhilst steady progress has been made in the development and dissemination of valid and reliable instruments for evaluation of patient outcomes, progress in establishing standard methodologies for description and classification of mental health services has been limited. Valid and reliable methods of describing and classifying services are needed in mental health services research for purposes including; i) comparison of levels of provision between catchment areas and countries; ii) reaching an understanding of the relationship between socio-demographic indicators and service use; iii) i

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Mahapatra, Prabhat. "Classification under Mental Health Act 1983 and consent to treatment." Psychiatric Bulletin 27, no. 10 (2003): 395. http://dx.doi.org/10.1017/s095560360000324x.

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Mahapatra, Prabhat. "Classification under Mental Health Act 1983 and consent to treatment." Psychiatric Bulletin 27, no. 10 (2003): 395. http://dx.doi.org/10.1192/pb.27.10.395.

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Moore, Stephanie A., Erin Dowdy, Karen Nylund-Gibson, and Michael J. Furlong. "An Empirical Approach to Complete Mental Health Classification in Adolescents." School Mental Health 11, no. 3 (2019): 438–53. http://dx.doi.org/10.1007/s12310-019-09311-7.

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Eaton, Nicholas R. "Measurement and mental health disparities: Psychopathology classification and identity assessment." Personality and Mental Health 14, no. 1 (2019): 76–87. http://dx.doi.org/10.1002/pmh.1449.

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Zhang, Feng, Kaylee Litson, and David F. Feldon. "Social predictors of doctoral student mental health and well-being." PLOS ONE 17, no. 9 (2022): e0274273. http://dx.doi.org/10.1371/journal.pone.0274273.

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Graduate students’ mental health and well-being is a prominent concern across various disciplines. However, early predictors of mental health and well-being in graduate education, specifically doctoral education, have rarely been studied. The present study evaluated both the underlying latent classification of individuals’ mental well-being and predictors of those classifications. Results estimated two latent classes of students’ mental health and well-being: one class with generally high levels of mental well-being and one with lower levels of mental well-being. Regression analyses showed tha

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Reis, Luciana Bicalho, Alexandra Iglesias, Meyrielle Belotti, and Camila Marchiori Pereira. "DEMANDAS E OFERTAS DA ATENÇÃO BÁSICA EM SAÚDE MENTAL INFANTOJUVENIL." Psicologia e Saúde em Debate 10, no. 1 (2024): 711–28. http://dx.doi.org/10.22289/2446-922x.v10n1a43.

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The objective was to understand the demands and offers of Primary Care with regard to mental health care for children and adolescents, from the perspective of workers. This is a qualitative research, made with 41 primary care (BA) health workers in a municipality in the Southeast region. As an adopted methodology semi-structured interviews were used and two focus groups, in the latter, 20 workers participated among those who were interviewed. This was followed by a lexical analysis of the Descending Hierarchical Classification type with the help of the IRAMUTEQ software, resulting in five clas

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Bai, Yuxin. "Deep Learning-based Pre-diagnosis and Analysis of Psychological Disorders." International Journal of Education and Humanities 6, no. 3 (2023): 126–30. http://dx.doi.org/10.54097/ijeh.v6i3.4763.

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At present, due to the lack of sufficient treatment institutions as well as professional psychotherapists, numerous patients with mental illnesses do not receive help from professional psychiatrists, thus worsening their conditions. In order to determine the condition of mental illness patients at an early stage, this paper applies natural language processing technology to the psychological field and proposes a text-based and deep learning model for mental illness recognition. The BERT (Bidirectional Encoder Representations from Transformers) pre-trained language model is used to complete the

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Ouliaris, Calina. "Considering context: lessons from global mental health." Australasian Psychiatry 28, no. 2 (2019): 210–12. http://dx.doi.org/10.1177/1039856219889318.

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Objective: The development of international mental health has been characterised by the globalisation of Western psychiatric nosology that is arguably ill-suited to developing countries. This piece highlights the limitations of our current classification systems and explores how we may seek to overcome these limitations by considering the context in which symptoms present. Conclusion: In developing a global model of psychiatric illnesses, it is important to emphasise contextual value judgements. Doing so welcomes integration of traditional models of care and encourages partnership across natio

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Berg, Ian. "Absence from School and Mental Health." British Journal of Psychiatry 161, no. 2 (1992): 154–66. http://dx.doi.org/10.1192/bjp.161.2.154.

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Severe school attendance problems, which once commanded a great deal of attention in child and adolescent psychiatry, have fallen from favour and are increasingly viewed as varieties of social impairment which may accompany disorders such as anxiety disturbances in the case of school refusal and conduct disturbances in the case of truancy. It is argued that this relegation of school attendance difficulties may have gone too far. As presenting complaints, albeit sometimes masked by apparent physical illness, they still have much to recommend them as indicators of a wide variety of present and f

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Nakamura, Eunice, Maëlle Planche, and Alain Ehrenberg. "The social aspects in the identification of children’s mental health problems in two health services in Paris, France." Interface - Comunicação, Saúde, Educação 22, no. 65 (2017): 411–22. http://dx.doi.org/10.1590/1807-57622016.0911.

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Children’s mental health problems were analyzed from a sociological approach addressing two questions: what are the main children’s behaviors identified and considered to be mental health problems, and what are the consequences of this classification for the debate on children’s problems in contemporary societies. This quantitative and qualitative study analyzed 275 patients’ records from two child mental health services (CMHS) in the northeast area of Paris, France. The majority of children were boys from six to 11 years old; requests were presented mainly by schools and parents; the main pro

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Adeeb, Rohullah, Hekmatullah Hekmat, and Abdullah Zahirzada. "Machine Learning-Based Classification of Mental Health Status on Social Media: A Case Study of Kunduz, Afghanistan." European International Journal of Multidisciplinary Research and Management Studies 5, no. 2 (2025): 6–11. https://doi.org/10.55640/eijmrms-05-02-02.

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The proliferation of user-generated content results from social media's rapid development. An interdisciplinary field called computational cyber-psychology uses machine learning techniques to investigate fundamental psychological tendencies. Our study uses social media usage patterns to infer users' mental health status. The emergence of social media platforms in Afghanistan has profoundly affected the country's young people. This study aims to implement a predictive model using three machine-learning algorithms. The three selected algorithms are Naïve Bayes, Random Forest, and K-Nearest Neigh

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Dorosevici-Duka, Alexandru, and Tatiana Rosca. "Psychodeontological prerogatives related to the stigma of patients affected by mental disorders." Vector European, no. 2 (November 2023): 155–64. http://dx.doi.org/10.52507/2345-1106.2023-2.30.

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The American Psychiatric Association defines mental illnesses as alterations in the cognitive, emotional or behavioral sphere (or a combination of these domains), which lead to suffering and/or problems in the person's social, professional or relational interaction skills. Given the range of possible symptoms, when talking about mental illnesses, reference should always be made to a standardized classification system, i.e. a list of disorders recognized to date, accompanied by their description and lists of symptoms and essential criteria for diagnosis. Currently, the most widely used manual i

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Bouch, Joe. "Classification." Advances in Psychiatric Treatment 16, no. 1 (2010): 1. http://dx.doi.org/10.1192/apt.16.1.1.

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YM He. "Online Assessment of Mental Health Micromedia for College Students Incorporating Bayesian Network Algorithm." International Journal of Maritime Engineering 1, no. 1 (2024): 83–96. http://dx.doi.org/10.5750/ijme.v1i1.1340.

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Mental health issues among college students are a growing concern, necessitating effective assessment methods to identify individuals at risk and provide timely interventions. In this paper, we propose and evaluate several computational models for mental health assessment based on demographic, academic, and psychological factors. Hence, this paper implemented the Probabilistic Deep Belief Bayesian Network (PDBBN) to classify students' mental health attributes. The proposed PDBBN network computes the probabilistic value of the mental health assessment of the students. With the estimation of the

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Patil, Ms Namrata. "“Mental Health Chatbot Using Natural Language Processing and Machine Learning Techniques”." International Scientific Journal of Engineering and Management 04, no. 06 (2025): 1–9. https://doi.org/10.55041/isjem04052.

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ABSTRACT: The rising demand for accessible mental health care has driven the development of AI-powered solutions capable of offering emotional support in real time. This research presents a web-based mental health chatbot that leverages Natural Language Processing (NLP) and machine learning to identify user emotions and intents, offering supportive responses through a hybrid system combining rule-based logic and BERT-based classification. The chatbot includes features such as CBT-style affirmations, self-assessment tests, journaling tools, and emergency support, ensuring both functionality and

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Goodfellow, Benjamin, Kairi Kõlves, and Diego De Leo. "Contemporary Classifications of Suicidal Behaviors." Crisis 41, no. 3 (2020): 179–86. http://dx.doi.org/10.1027/0227-5910/a000622.

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Abstract. Background: The absence of agreed-upon terminology, definitions, and operational classifications has hampered research in the field of suicidology for many decades. Aims and Method: We systematically reviewed contemporary classifications of suicidal behavior using the scope of the classification (comprehensive vs. restricted or single behaviors), and the presence or absence of a classification scheme and an operational definition of intent as features to enable analysis and comparison. Results: A chronological perspective shows that classification systems tend to be more and more pre

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Bramley, Michelle, Karen Peasley, Lisa Langtree, and Kerry Innes. "The ICD-10-AM Mental Health Manual: An Integrated Classification and Diagnostic Tool for Community-Based Mental Health Services." Health Information Management 30, no. 4 (2002): 1–4. http://dx.doi.org/10.1177/183335830203000402.

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Harrington, Richard. "Diagnostic classification systems." Psychiatry 4, no. 6 (2005): 10–12. http://dx.doi.org/10.1383/psyt.4.6.10.66356.

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Harrington, Richard. "Diagnostic classification systems." Psychiatry 7, no. 6 (2008): 231–34. http://dx.doi.org/10.1016/j.mppsy.2008.04.006.

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Snowden, Austyn. "Classification of schizophrenia. Part 2: the nonsense of mental health illness." British Journal of Nursing 18, no. 20 (2009): 1228–32. http://dx.doi.org/10.12968/bjon.2009.18.20.45113.

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Cuthbert, Bruce, and Thomas Insel. "Classification issues in women’s mental health: clinical utility and etiological mechanisms." Archives of Women's Mental Health 13, no. 1 (2010): 57–59. http://dx.doi.org/10.1007/s00737-009-0132-z.

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Parkhomchuk, Mykola, and Nataliia Zenkovych. "CLASSIFICATION OF MENTAL HEALTH CENTER WITHIN THE STRUCTURE OF HEALTHCARE INSTITUTIONS." Current problems of architecture and urban planning, no. 71 (March 28, 2025): 565–76. https://doi.org/10.32347/2077-3455.2025.71.565-576.

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Abstract:

A clear classification of healthcare facilities and psychiatric institutions is crucial for the effective delivery of medical care, as it aids in service organization, resource planning, and ensuring high standards of treatment. With the growing prevalence of mental disorders and the need to provide access to quality medical care, proper classification becomes the foundation for creating a comprehensive and integrated system of medical institutions. This article examines the typology, specifics, urban structure placement, functions, planning structure, and necessary equipment for mental health

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Wagay, Faheem Ahmad, Jahiruddin, and Yasir Altaf. "MentalRoBERTa-Caps: A capsule-enhanced transformer model for mental health classification." MethodsX 15 (December 2025): 103483. https://doi.org/10.1016/j.mex.2025.103483.

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