Clarifying terminology and definitions in education services for mental health users: A disambiguation study.

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 the context of Spain and The Netherlands. It was conducted alongside the PECUNIA project, that sought to develop methods for the assessment of mental health costs and outcomes in different sectors. The study followed an ontoterminology approach involving: 1) identification of services from a predefined list of 46 resource-use items, 2) disambiguation of identified services with the DESDE, and classifying them as accurate, ambiguous, vague or confuse; and 3) external validation by an expert panel. The analysis was conducted at the level of type of resource, target population and care provision. From the initial list, only ten of the resources could be categorized as services using DESDE, and not activities, interventions or professionals. Only four of them (8,65%) were accurate across all disambiguation categories. Experts were unaware of terminology problems in classification of service provision in the education sector. Classifications and glossaries can clarify service naming, description and costing allowing comparative effectiveness analysis and facilitating cross-sectoral planning. This should be grounded in common methodologies, tools, and units of analysis.

Replication and reliability of Parkinson's disease clinical subtypes.

BACKGROUND: We recently identified three distinct Parkinson's disease subtypes: "motor only" (predominant motor deficits with intact cognition and psychiatric function); "psychiatric & motor" (prominent psychiatric symptoms and moderate motor deficits); "cognitive & motor" (cognitive and motor deficits). OBJECTIVE: We used an independent cohort to replicate and assess reliability of these Parkinson's disease subtypes. METHODS: We tested our original subtype classification with an independent cohort (N = 100) of Parkinson's disease participants without dementia and the same comprehensive evaluations assessing motor, cognitive, and psychiatric function. Next, we combined the original (N = 162) and replication (N = 100) datasets to test the classification model with the full combined dataset (N = 262). We also generated 10 random split-half samples of the combined dataset to establish the reliability of the subtype classifications. Latent class analyses were applied to the replication, combined, and split-half samples to determine subtype classification. RESULTS: First, LCA supported the three-class solution - Motor Only, Psychiatric & Motor, and Cognitive & Motor- in the replication sample. Next, using the larger, combined sample, LCA again supported the three subtype groups, with the emergence of a potential fourth group defined by more severe motor deficits. Finally, split-half analyses showed that the three-class model also had the best fit in 13/20 (65%) split-half samples; two-class and four-class solutions provided the best model fit in five (25%) and two (10%) split-half replications, respectively. CONCLUSIONS: These results support the reproducibility and reliability of the Parkinson's disease behavioral subtypes of motor only, psychiatric & motor, and cognitive & motor groups.

Primary care physicians' perceptions of artificial intelligence systems in the care of adolescents' mental health.

BACKGROUND: Given that mental health problems in adolescence may have lifelong impacts, the role of primary care physicians (PCPs) in identifying and managing these issues is important. Artificial Intelligence (AI) may offer solutions to the current challenges involved in mental health care. We therefore explored PCPs' challenges in addressing adolescents' mental health, along with their attitudes towards using AI to assist them in their tasks. METHODS: We used purposeful sampling to recruit PCPs for a virtual Focus Group (FG). The virtual FG lasted 75 minutes and was moderated by two facilitators. A life transcription was produced by an online meeting software. Transcribed data was cleaned, followed by a priori and inductive coding and thematic analysis. RESULTS: We reached out to 35 potential participants via email. Seven agreed to participate, and ultimately four took part in the FG. PCPs perceived that AI systems have the potential to be cost-effective, credible, and useful in collecting large amounts of patients' data, and relatively credible. They envisioned AI assisting with tasks such as diagnoses and establishing treatment plans. However, they feared that reliance on AI might result in a loss of clinical competency. PCPs wanted AI systems to be user-friendly, and they were willing to assist in achieving this goal if it was within their scope of practice and they were compensated for their contribution. They stressed a need for regulatory bodies to deal with medicolegal and ethical aspects of AI and clear guidelines to reduce or eliminate the potential of patient harm. CONCLUSION: This study provides the groundwork for assessing PCPs' perceptions of AI systems' features and characteristics, potential applications, possible negative aspects, and requirements for using them. A future study of adolescents' perspectives on integrating AI into mental healthcare might contribute a fuller understanding of the potential of AI for this population.

Neuropsychiatric Complications of Hypervitaminosis D: Diagnosis, Evaluation, and Treatment.

The Psychiatric Consultation Service at Massachusetts General Hospital sees medical and surgical inpatients with comorbid psychiatric symptoms and conditions. During their twice-weekly rounds, Dr Stern and other members of the Consultation Service discuss diagnosis and management of hospitalized patients with complex medical or surgical problems who also demonstrate psychiatric symptoms or conditions. These discussions have given rise to rounds reports that will prove useful for clinicians practicing at the interface of medicine and psychiatry.Prim Care Companion CNS Disord 2024;26(3):23f03680. Author affiliations are listed at the end of this article.

[A case report of anti-NMDA receptor encephalitis with mental disturbances manifestation]. / Klinicheskoe nablyudenie anti-NMDA-retseptornogo entsefalita, protekayushchego s psikhicheskimi narusheniyami.

Presented clinical observation of anti-NMDA-receptor encephalitis, which was first described in 2007, is rare and to date has not been sufficiently studied. The disease often manifests with psychopathological symptoms and catatonia, so patients are transferred into a mental healthcare institution and often require intensive care and resuscitation, due to the development of life-threatening respiratory and hemodynamic disorders. Diagnosis is based on detection of autoantibodies to the NR1- and NR2 subunits of the glutamate NMDA receptor in blood serum and cerebrospinal fluid. Pathogenesis-based therapy includes the administration of glucocorticoids and intravenous immunoglobulins, plasmapheresis, as well as the introduction of monoclonal antibodies in also used, and in severe cases, cytostatics are prescribed. The widespread comorbidity of anti-NMDA receptor encephalitis with ovarian neoplasms in women (up to 60%) requires appropriate diagnosis and early removal of ovarian neoplasms when they are detected. With timely diagnosis and adequate treatment strategies, the outcome of this rare disorder is usually positive.

Enhancing the accuracy of register-based metrics: Comparing methods for handling overlapping psychiatric register entries in Finnish healthcare registers.

OBJECTIVES: Healthcare registers are invaluable resources for research. Partly overlapping register entries and preliminary diagnoses may introduce bias. We compare various methods to address this issue and provide fully reproducible open-source R scripts. METHODS: We used all Finnish healthcare registers 1969-2020, including inpatient, outpatient and primary care. Four distinct models were formulated based on previous reports to identify actual admissions, discharges, and discharge diagnoses. We calculated the annual number of treatment events and patients, and the median length of hospital stay (LOS). We compared these metrics to non-processed data. Additionally, we analyzed the lifetime number of individuals with registered mental disorders. RESULTS: Overall, 2,130,468 individuals had a registered medical contact related to mental disorders. After processing, the annual number of inpatient episodes decreased by 5.85%-10.87% and LOS increased by up to 3 days (27.27%) in years 2011-2020. The number of individuals with lifetime diagnoses reduced by more than 1 percent point (pp) in two categories: schizophrenia spectrum (3.69-3.81pp) and organic mental disorders (1.2-1.27pp). CONCLUSIONS: The methods employed in pre-processing register data significantly impact the number of inpatient episodes and LOS. Regarding lifetime incidence of mental disorders, schizophrenia spectrum disorders require a particular focus on data pre-processing.

Prevalence of mental, behavioural or neurodevelopmental disorders according to the International Classification of Diseases 11: a scoping review protocol.

INTRODUCTION: Due to a change in diagnostic prerequisites and the inclusion of novel diagnostic entities, the implementation of the 11th revision of the International Classification of Diseases (ICD-11) will presumably change prevalence rates of specific mental, behavioural or neurodevelopmental disorders and result in an altered prevalence rate for this grouping overall. This scoping review aims to summarise the characteristics of primary studies examining the prevalence of mental, behavioural or neurodevelopmental disorders based on ICD-11 criteria. The knowledge attained through this review will primarily characterise the methodological approaches of this research field and additionally assist in deciding which psychiatric diagnoses are-given the current literature-most relevant for subsequent systematic reviews and meta-analyses intended to approximate the magnitude of prevalence rates while providing a first glimpse of the range of expected (differences in) prevalence rates in these conditions. METHODS AND ANALYSIS: MEDLINE, Embase, Web of Science and PsycINFO will be searched from 2011 to present without any language filters. This scoping review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Review guidelines.We will consider (a) cross-sectional and longitudinal studies (b) focusing on the prevalence rates of mental, behavioural or neurodevelopmental disorders (c) using ICD-11 criteria for inclusion. The omission of (a) case numbers and sample size, (b) study period and period of data collection or (c) diagnostic procedures on full-text level is considered an exclusion criterion.This screening will be conducted by two reviewers independently from one another and a third reviewer will be consulted with disagreements. Data extraction and synthesis will focus on outlining methodological aspects. ETHICS AND DISSEMINATION: We intend to publish our review in a scientific journal. As the primary data are publicly available, we do not require research ethics approval.

Severe psychiatric disorders are associated with increased risk of dementia.

BACKGROUND: Individuals with psychiatric disorders have an increased risk of developing dementia. Most cross-sectional studies suffer from selection bias, underdiagnosis and poor population representation, while there is only limited evidence from longitudinal studies on the role of anxiety, bipolar and psychotic disorders. Electronic health records (EHRs) permit large cohorts to be followed across the lifespan and include a wide range of diagnostic information. OBJECTIVE: To assess the association between four groups of psychiatric disorders (schizophrenia, bipolar disorder/mania, depression and anxiety) with dementia in two large population-based samples with EHR. METHODS: Using EHR on nearly 1 million adult individuals in Wales, and from 228 937 UK Biobank participants, we studied the relationships between schizophrenia, mania/bipolar disorder, depression, anxiety and subsequent risk of dementia. FINDINGS: In Secure Anonymised Information Linkage, there was a steep increase in the incidence of a first diagnosis of psychiatric disorder in the years prior to the diagnosis of dementia, reaching a peak in the year prior to dementia diagnosis for all psychiatric diagnoses. Psychiatric disorders, except anxiety, were highly significantly associated with a subsequent diagnosis of dementia: HRs=2.87, 2.80, 1.63 for schizophrenia, mania/bipolar disorder and depression, respectively. A similar pattern was found in the UK Biobank (HRs=4.46, 3.65, 2.39, respectively) and anxiety was also associated with dementia (HR=1.34). Increased risk of dementia was observed for all ages at onset of psychiatric diagnoses when these were divided into 10-year bins. CONCLUSIONS: Psychiatric disorders are associated with an increased risk of subsequent dementia, with a greater risk of more severe disorders. CLINICAL IMPLICATIONS: A late onset of psychiatric disorders should alert clinicians of possible incipient dementia.

Forensic Neurology and the Role of Neurologists in Forensic Evaluations.

Forensic psychiatrists may be asked to opine on neurological evidence or neurological diseases outside the scope of their expertise. This article discusses the value of involving experts trained in behavioral neurology in such cases. First, we describe the field of behavioral neurology and neuropsychiatry, the subspecialty available to both neurologists and psychiatrists focused on the behavioral, cognitive, and neuropsychiatric manifestations of neurological diseases. Next, we discuss the added value of behavioral neurologists in forensic cases, including assisting in the diagnostic evaluation for complex neuropsychiatric diseases, using expertise in localization to provide a strong scientific basis for linking neurodiagnostic testing to relevant neuropsychiatric symptoms, and assisting in relating these symptoms to the relevant legal question in cases where such symptoms may be less familiar to forensic psychiatrists, such as frontal lobe syndromes. We discuss approaches to integrating behavioral neurology with forensic psychiatry, highlighting the need for collaboration and mentorship between disciplines. Finally, we discuss several forensic cases highlighting the additional value of experts trained in behavioral neurology. We conclude that forensic psychiatrists should involve behavioral neurology experts when encountering neurological evidence that falls outside their scope of expertise, and the need for further cross-disciplinary collaboration and training.

Predictors of Criminal Sentiments Scale-Modified Scores in Outpatients with Legal System Involvement.

The Criminal Sentiments Scale-Modified (CSS-M) has been widely used as a measure of criminal attitudes. This analysis examined CSS-M scores in a large sample of outpatients with serious mental illnesses and a criminal legal system history. We compared total and subscale scores in our sample to scores from two other previously published U.S. studies in which the CSS-M was used, and evaluated associations between total CSS-M score and nine variables (age, educational attainment, gender, race, marital status, employment status, diagnostic category, substance use disorder comorbidity, and adverse childhood experiences (ACE) score). Scores were higher than in two prior U.S. studies involving other types of samples. Independently significant predictors of higher CSS-M scores included being younger (P < .001), having a higher ACE score (P < .001), being male (P = 03), not identifying as White (P < 001), not having a psychotic disorder (P < 001), and having a comorbid substance use disorder (P = 002). Future research should test the hypothesis that these factors increase risk for arrest and that arrest events, and subsequent criminal legal system involvement, are characterized by negative experiences and perceptions of poor procedural justice, which in turn underpin the negative opinions referred to as "criminal sentiments" or criminal attitudes.

Forensic Neurology and the Role of Neurologists in Forensic Evaluations.

There is a clear need for experts with the requisite knowledge and experience to offer medicolegal opinions pertaining to various neuropsychiatric conditions. There is also an important distinction between clinical and medicolegal roles, and the need for training and expertise applicable to forensic assessment. But there remain few available experts with credentials spanning neuropsychiatry and forensic assessment. This creates a dilemma whereby parties involved in litigation featuring neuropsychiatric illness or injury are frequently forced to choose between experts with either knowledge and skills applicable to neuropsychiatric conditions or experts with skills and experience applicable to forensic assessment. Either choice introduces risk. Whether flawed medicolegal opinions are a consequence of deficient medical knowledge or an inadequate forensic evaluation process, the result remains the same, with triers of fact potentially being exposed to problematic testimony. There is, however, a more fundamental problem that implicates patient care more broadly: spurious dichotomies created by the historical segregation of psychiatry and neurology. Optimizing clinical care for patients with neuropsychiatric conditions, improving medical education in support of such care, and enabling forensic neuropsychiatric assessment must then start with more proactive efforts to reintegrate psychiatry and neurology.

The Evolving Standard of Care for Autoimmune Neuropsychiatric Illness.

In recent decades, there has been increasing biomedical and public understanding of the role of autoimmunity in neuropsychiatric illness. Popular media have highlighted patients with psychiatric illnesses who were eventually diagnosed with autoimmune neuropsychiatric illnesses such as anti- N-methyl-D-aspartate receptor encephalitis. Coverage of these cases has often drawn attention to the effects of misdiagnosis or delayed diagnosis of such diseases in psychiatric patients. Autoimmune encephalitis can have varied presentations and often involves evaluation and management from multiple medical specialties. As a result, there remains considerable uncertainty regarding how courts might gauge the legal standard of care with regard to psychiatric workup of new-onset psychiatric symptoms, and the degree to which autoimmune encephalitis must be considered. In this article we provide a brief overview of autoimmune encephalitis and autoimmune psychosis, including current diagnostic approaches to these conditions. We review case law regarding the standard of care for psychiatric disorders caused by general medical conditions. Finally, we provide a medicolegal perspective on the responsibilities of psychiatrists and other mental health professionals in the evaluation of possible autoimmune encephalitis.

Motives and modifying factors for giving or rejecting psychiatric diagnoses in general medicine and psychiatry - a qualitative interview study.

BACKGROUND: There is a discussion among general practitioners and psychiatrists regarding over-diagnosing versus under-reporting of psychiatric diagnoses. A deeper understanding of this topic is relevant for providing reasonable health care and for planning future studies. A crucial factor to understanding this discussion is the difference in the prevalence of a disease in each sector. One way to attain knowledge about such prevalences is the analysis of routine care data of the sector in question. However, diagnosis-related data might be modified by several additional influencing factors. AIMS: This study aims to explore what kind of motives and modifying factors play a role for or against giving psychiatric diagnoses in psychiatric and general medical settings. METHODS: Twenty-six semi-structured interviews were conducted with German physicians in the fields of general medicine and psychiatry. Interviews were analysed using content analysis. RESULTS: The analysis revealed three major motivational categories for finding a diagnosis: (1) "objective matters" such as "categorisation for research"; (2) "functional and performance-related factors" such as "requirement for medication", "billing aspects" that go with certain diagnoses or "access to adequate care" and (3) "Individual factors" such as the "personality of a physician". Similarly, factors emerged that lead to not making psychiatric diagnoses like "fear of stigmatization among patients" or "detrimental insurance status with psychiatric diagnosis". Additionally participants mentioned other reasons for "not diagnosing a psychiatric diagnosis", such as "coding of other clinical pictures". CONCLUSION: The diagnostic process is a complex phenomenon that goes far beyond the identification of medical findings. This insight should be considered when processing and interpreting secondary data for designing health care systems or designing a study.

[Electroencephalography: features of the obtained data and its applicability in psychiatry]. / Elektroentsefalografiya: osobennosti poluchaemykh dannykh i ikh primenimost' v psikhiatrii.

Presently, there is an increased interest in expanding the range of diagnostic and scientific applications of electroencephalography (EEG). The method is attractive due to non-invasiveness, availability of equipment with a wide range of modifications for various purposes, and the ability to track the dynamics of brain electrical activity directly and with high temporal resolution. Spectral, coherency and other types of analysis provide volumetric information about its power, frequency distribution, spatial organization of signal and its self-similarity in dynamics or in different sections at a time. The development of computing technologies provides processing of volumetric data obtained using EEG and a qualitatively new level of their analysis using various mathematical models. This review discusses benefits and limitations of using the EEG in scientific research, currently known interpretation of the obtained data and its physiological and pathological correlates. It is expected to determine the complex relationship between the parameters of brain electrical activity and various functional and pathological conditions. The possibility of using EEG characteristics as biomarkers of various physiological and pathological conditions is being considered. Electronic databases, including MEDLINE (on PubMed), Google Scholar and Russian Scientific Citation Index (RSCI, on elibrary.ru), scientific journals and books were searched to find relevant studies.

Optimising the use of electronic medical records for large scale research in psychiatry.

The explosion and abundance of digital data could facilitate large-scale research for psychiatry and mental health. Research using so-called "real world data"-such as electronic medical/health records-can be resource-efficient, facilitate rapid hypothesis generation and testing, complement existing evidence (e.g. from trials and evidence-synthesis) and may enable a route to translate evidence into clinically effective, outcomes-driven care for patient populations that may be under-represented. However, the interpretation and processing of real-world data sources is complex because the clinically important 'signal' is often contained in both structured and unstructured (narrative or "free-text") data. Techniques for extracting meaningful information (signal) from unstructured text exist and have advanced the re-use of routinely collected clinical data, but these techniques require cautious evaluation. In this paper, we survey the opportunities, risks and progress made in the use of electronic medical record (real-world) data for psychiatric research.

[Integrative medicine for patients suffering from addictive disorders alongside other pathologies in general practice]. / Clinique intégrative des addictions coexistant avec d'autres pathologies en médecine générale.

People suffering from substance use disorders frequently suffer from concomitant affections such as other addictions, psychiatric, somatic or social problems. Clarifying objectives and priorities with the patient and coordination of care are the priority in the follow up suggested in this article. We present a clinical example in which the modality of care is adapted depending on the evolution of the patient's needs. The follow up by a general practitioner can be pursued in parallel to specialized care. The modality of this collaboration will have to adapt to the patients' and healthcare workers' needs. This follow-up aims to provide good quality health care all the while supporting the healthcare providers who can, sometimes, feel helplessness.

Les personnes souffrant d'un trouble de l'utilisation de substances présentent fréquemment plusieurs affections parallèles telles que d'autres problématiques addictologiques, psychiatriques, somatiques ou sociales. La clarification des objectifs et priorités avec le patient ainsi que la coordination des soins sont au premier plan de la prise en charge proposée dans cet article. Nous présentons, au travers d'une vignette clinique, un exemple de suivi pour lequel la modalité de prise en charge s'adapte aux besoins changeants du patient au cours du temps. Le suivi par un médecin généraliste peut être combiné à un suivi spécialisé. Le mode de collaboration devra s'adapter aux besoins des soignants et du patient. Ce suivi visera à assurer des soins de qualité tout en soutenant les soignants face à un possible sentiment d'impuissance.

Impact of a Mental Health Screening Process in a Pediatric Emergency Department.

OBJECTIVE: The aim of this study was to describe how specific mental health-trained social workers can assist in the evaluations and follow-up of patients presenting with mental health concerns in the pediatric emergency department (ED). METHODS: Work was performed at a quaternary children's hospital ED with 95,000 annual ED visits across 2 locations. Patients requiring mental health services identified based on presenting complaint or from universal suicide screen were included. Emergency department team first evaluates the patients for medical screening and then consults a team of social workers specialized in acute mental health screening (AMHS). The team evaluates and provides recommendation for disposition and assists in plan completion. For patients not admitted, AMHS team makes 24- and 48-hour calls to ensure safety. We collected and analyzed the data on all eligible patients from September 2015 through June 2019 for (1) demographic information, (2) trends in number of consults to AMHS, (3) disposition plans and trends by year, and (4) frequency of follow-up phone calls. RESULTS: A total of 5950 patient visits were reviewed, for 4454 distinct patients. Most patients were 12 to 17 years of age, female, and White, with Medicaid being the predominant insurance. The most common chief complaint was suicidal ideation/plan/attempt. Self-referrals were the majority of assessments, and 59% of patients were already receiving mental health services. Median team response time was 19 minutes. There was an upward trend in consults. Psychiatric hospitalization was the most common disposition; more than 95% of the other visits had timely follow-up phone calls. CONCLUSION: Despite an increasing number of patients presenting to the ED with mental health crisis, safe and efficient management is possible with ED staff-social worker partnership. This approach can ensure that eligible patients receive consistent and evidence-based evaluations and can allow ED clinicians to respond to medical emergencies that require their attention.

Building diagnostic neuroimaging biomarkers for psychiatric disorders using reverse inference approaches: A viable route?

The advent of structural magnetic resonance imaging (sMRI) at the end of the 20th century opened the way toward a deeper understanding of the neurophysiology of psychiatric disorders, substantiating regional structural abnormalities underlying this group of clinical conditions. However, despite abundant and flourishing scientific research, sMRI methodologies are not currently integrated into daily diagnostic practice. One reason behind this failed translation may be the prevailing approach to logical reasoning in neuroimaging: The forward inference via frequentist-based statistics. This reasoning prevents clinicians from obtaining information about the selectivity of results, which are therefore of limited use regarding the definition of biomarkers and refinement of diagnostic processes. Recently, another type of inferential approach has started to emerge in the neuroimaging field: The reverse inference via Bayesian statistics. Here, we introduce the key concepts of this approach, with a particular emphasis on the clinical sMRI environment. We survey recent findings showing significant potential for clinical translation. Clinical opportunities and challenges for developing reverse inference-based neural markers for psychiatry are also discussed. We propose that a systematic sharing of imaging data across the human brain mapping community is an essential first step toward a paradigmatic clinical shift. We conclude that a defined synergy between forward-based and reverse-based sMRI research can illuminate current discussions on diagnostic brain markers, offering clarity on key issues and fostering new tailored diagnostic avenues.

Dual-factor Models of Mental Health: A Systematic Review of Empirical Evidence.

Objective: Dual-factor models of mental health propose that mental health includes two interrelated yet distinct dimensions - psychopathology and well-being. However, there is no systematization of the evidence following these models. This review aims to address the following research question: what evidence exists using dual-factor models? Method: The current systematic review was conducted using PRISMA guidelines on the following databases: Web-of-science, Scopus, Academic Search Complete, APA PsycArticles, APA PsycInfo, Psychology and Behavioral Sciences Collection, ERIC, and MEDLINE. The screening process resulted in 85 manuscripts that tested the assumptions of dual-factor models. Results: Evidence revealed psychometric substantiation on the two-dimensionality of the dual-factor model, and 85% of the manuscripts provided evidence related to classifying participants into different mental health groups. Most studies showed that the Complete Mental Health or Positive Mental Health group is the most prevalent status group, and longitudinal evidence suggests that most participants (around 50%-64%) remain in the same group across time. Regarding the factors associated with mental health status groups, studies reviewed in this manuscript focus mainly on school-related outcomes, followed by supportive relationships, sociodemographic characteristics, psychological assets, individual attributes, physical health, and stressful events. Conclusions: This review highlights the importance of considering the two dimensions of mental health when conceptualizing, operationalizing, and measuring mental health. Fostering mental health must go beyond reducing symptoms, and practitioners would be able to include well-being-related interventions in their regular practice to improve individuals' mental health outcomes.