AI-Powered Documentation for Mental Health Providers: Retrospective Observational Mixed Methods Study.

In 2004, the American Academy of Pediatrics (AAP) Board of Directors formed the Task Force on Mental Health and charged it with developing strategies to improve the quality of child and adolescent mental health* services in primary care. The task force acknowledged early in its deliberations that enhancing the mental health care that pediatricians and other primary care clinicians† provide to children and adolescents will require systemic interventions at the national, state, and community levels to improve the financing of mental health care and access to mental health specialty resources. Systemic strategies toward achieving these improvements are the subject of other publications of the task force: “ Strategies for System Change in Children's Mental Health: A Chapter Action Kit ” (chapter action kit),1 “Improving Mental Health Services in Primary Care: Reducing Administrative and Financial Barriers to Access and Collaboration,”2 and “Enhancing Pediatric Mental Health Care: Strategies for Preparing a Community.”3 The task force also recognized that enhanced mental health practice will require competencies not currently achieved by many primary care clinicians; in the policy statement “The Future of Pediatrics: Mental Health Competencies for Pediatric Primary Care,”4 the task force collaborated with the AAP Committee on Psychosocial Aspects of Child and Family Health to outline these competencies and propose strategies for achieving them. This report offers strategies for preparing the primary care practice itself for provision of enhanced mental health care services. The task force proposes incrementally applying chronic care principles to the care of children with mental health and substance abuse problems as primary care clinicians apply them to the care of children with chronic medical conditions such as asthma. Most primary care clinicians will find that significant gaps exist between their current practice and the proposed ideal. The task force offers guidance in … Address correspondence to Jane Meschan Foy, MD, Department of Pediatrics, Wake Forest University School of Medicine, Medical Center Blvd, Winston-Salem, NC 27157. E-mail: jmfoy{at}wfubmc.edu

Predictors of Likelihood and Intensity of Past-Year Mental Health Service Use in an Active Canadian Military Sample

Digital phenotyping (DP) refers to the emerging field within digital (mental) health that involves the collection of data from individual’s digital devices (smartphones, wearable, Internet usage, etc.) to monitor and analyse their behaviours, activities and health-related patterns. That such ‘digital footprint’ data can be mined for behavioural insights is an intriguing idea, which has motivated an increasing amount of research activity, particularly in the field of digital mental health. Whilst of potentially revolutionary utility in (mental) healthcare, the idea of DP also raises a set of rich sociotechnical, ethical and philosophical considerations, and a cottage industry of sociotechnical and ethical critiques of DP has emerged, particularly within the humanities. Within this scene of early empirical investigation in the health/behavioural sciences on the one hand and general conceptual critiques from the humanities on the other, in this paper we instead explore a case for the potential utility of DP in circumstances of clinical mental health practice and examine its ethical dimensions in this context. After providing an explicatory framework for DP and making a case for it within this framework, we subsequently examine the ethical pros and cons of three topics pertaining to DP in clinical practice, namely (1) issues in psychometric assessment/testing, (2) the role and responsibilities of mental health practitioners with regard to DP technology, and (3) the value DP can afford clients in terms of self-awareness/empowerment and strengthening the therapeutic alliance with their clinician.

Patients have long been concerned about the privacy of their health care information. How private is private'? is a question that echoes through the minds of patients every time they receive a stigmatizing diagnosis such as cancer, a sexually transmitted disease (STD), alcohol or drug dependency, a mental or emotional health problem, or trauma symptoms related to a personal and private experience. Federal regulations for health care providers that went into effect in April 2003 are touted as improving or ensuring the privacy of an individual's personal health information, but do they? We think not. The Health Insurance Portability and Accountability Act (HIPAA) of 1996 (PL. 104-191) is a multitiered, comprehensive, convoluted, and controversial federal law for sweeping health care reform. Although HIPAA is dramatically broader in scope than privacy protections for health care information, a provision for privacy in the form of a Privacy Rule is included in Title II of HIPAA under the Administrative Simplification regulations; this regulation has created widespread controversy, as well it should, juxtaposed with both civil liberties and the tenets of our profession's ethical code. In preparation for the Privacy Rule compliance date in April 2003, executives of covered entities (CEs), which include health plans, health care clearinghouses, and health care providers, were involuntarily plunged into a mire of federal definitions, acronyms, regulations, and procedures that spiked the jargon meter. veritable compliance melee erupted as a result of struggles to comply with the letter of the law in the face of inability to decipher what the letter of the law was. health care network-wide plethora of brochures, forms, and flyers, ostensibly aimed at protecting patient privacy better than ever before, spilled from the many months of compliance preparations by each CE. But contrary to the HIPAA hype about patient protection, and despite the glacier of paperwork for protecting privacy that was spawned by the Privacy Rule, critics of HIPAA claim that this federal law erodes patients' right to privacy. Citizens for Health filed papers in the U.S. district court in Philadelphia alleging that HIPAA regulations threaten essential liberties [privacy] guaranteed by the Constitution (Dougherty, 2003). Privacy and confidentiality are in greater jeopardy than ever because of two security issues inherent in compliance with HIPAA regulations. The first security issue stems from the fact that health care providers are forced to use the Internet for sharing information and for billing purposes. Second, and counter to HIPAA's alleged intent, is the issue of access to private health information. According to a statement issued by Citizens for Health, virtually all personal health information about every aspect of an individual's life can be used and disclosed routinely without notice, without the individual's consent and against his or her (Dougherty, 2003). In the first instance, patient confidentiality is compromised by the federal government, health care workers, hackers, and the legal system. The federal government realizes a savings of billions of tax dollars by computerizing Medicare and Medicaid programs and HIPAA, and, except in very small practices, makes electronic billing mandatory. Also, to facilitate quick information exchange in medical emergencies, there is a push for universal patient identifiers, which relates to the second security issue. nationwide linking of all medical records is possible with such identifiers (Gelman, Pollack, & Weiner, 1999). A national health ID so presages a national health database that Congress has consistently refused to fund the program (Privacilla.org, 2003, p.11). Even so, increasing amounts of new private health information will be traveling the electronic highways, in addition to what is already stored in computers by managed care companies, as the private insurance companies follow the government's lead. …

You have accessThe ASHA LeaderBottom Line1 Sep 2011Patient Information Privacy Basics Kate RomanowJD Kate Romanow Google Scholar More articles by this author , JD https://doi.org/10.1044/leader.BML1.16092011.3 SectionsAbout ToolsAdd to favorites ShareFacebookTwitterLinked In ASHA recently hosted an online private-practice institute for audiologists and speech-language pathologists that focused on how to establish, manage, and grow a profitable private practice. Recorded lectures covered topics such as strategic business planning, fees and pricing, employment law basics, managing a fee-for-service practice, increasing referrals, using web-based and social media marketing, coding updates, Medicare billing, and claims and denials. Many of the participants in one of the sessions, “Data Privacy, Security, and Enforcement: HIPAA and More,” raised several questions during and after the institute on the Health Insurance Portability and Accountability Act (HIPAA). This article clarifies points discussed during the institute to help other clinicians understand HIPAA policies. The HIPAA privacy rule protects personal health information and outlines patients’ rights with respect to that information, while allowing disclosure of information needed for patient care. The HIPAA security rule specifies a series of administrative, physical, and technical safeguards that ensure the confidentiality, integrity, and availability of electronic protected health information. Electronic protected health information includes, for example, patient data stored on a computer hard drive, or data transmitted via a computer for billing purposes. The following questions and answers outline basic HIPAA privacy and security regulations. Q: Do the HIPAA regulations apply to me? HIPAA compliance is required by all “covered entities,” defined as health plans, health care clearinghouses, and health care providers that transmit any health information in electronic form in connection with “transactions” covered under HIPAA. If you are a provider who, for example, sends patient information electronically to a billing company, then you are a “covered entity” and must comply with HIPAA regulations. Q: What transactions are covered under HIPAA? HIPAA regulations define “transaction” as the transmission of information between two parties to carry out financial or administrative activities related to health care. It includes the following types of information transmissions: Health care claims or equivalent encounter information. Health care payment and remittance advice. Coordination of benefits. Health care claim status. Enrollment and disenrollment in a health plan. Eligibility for a health plan. Health plan premium payments. Referral certification and authorization. First report of injury. Health claims attachments. Other transactions that the secretary of health and human services may prescribe by regulation (45 C.F.R. Section 160.103). Q: What does “electronic form” mean? HIPAA does not define “electronic form.” It does, however, define “electronic media” as the following: Electronic storage media including memory devices in computers (hard drives) and any removable/transportable digital memory medium, such as magnetic tape or disk, optical disk, or digital memory card. Transmission media used to exchange information already in electronic storage media. Transmission media include, for example, the Internet, extranet (using Internet technology to link a business with information accessible only to collaborating parties), dial-up lines, leased lines, private networks, and the physical movement of removable/transportable electronic storage media. Certain transmissions, including those by paper (facsimile) and by voice (telephone), are not considered e-transmissions via electronic media because the information did not exist in electronic form before the transmission (45 C.F.R. Section 160.103). Q: If I am a covered entity, what do I need to do to comply with HIPAA? You must protect the privacy of patient information. You must safeguard patient information sent electronically. For example, you must inform patients about the HIPAA privacy practices you observe and train employees about HIPAA requirements. Q: Are there sample notices of privacy practices? More information about HIPAA privacy notices is available at the Department of Health and Human Services website. ASHA includes a sample notice of privacy practices in its Practice Management Tools for SLPs available in the ASHA online store. Q: Where I can get more information? ASHA’s reimbursement web page includes an extensive section on HIPAA. An article in The ASHA Leader also outlines some basics. The Office of Civil Rights, which enforces the privacy and security rule, has information on its website. The Workgroup for Electronic Data Interchange [PDF] (of which ASHA is a member) has information to help small practices comply with HIPAA. The full HIPAA regulations are available at the Department of Health and Human Services website. (Be aware, however, that the most current version may not be posted.) Author Notes Kate Romanow, JD, director of health care regulatory advocacy, can be reached at [email protected]. Advertising Disclaimer | Advertise With Us Advertising Disclaimer | Advertise With Us Additional Resources FiguresSourcesRelatedDetails Volume 16Issue 9September 2011 Get Permissions Add to your Mendeley library History Published in print: Sep 1, 2011 Metrics Current downloads: 271 Topicsasha-topicsleader_do_tagasha-article-typesleader-topicsCopyright & Permissions© 2011 American Speech-Language-Hearing AssociationLoading ...

In the last two decades, new communication technologies have dramatically changed the world in which mental health professionals and their patients live. Developments such as e-mail, online chat groups, Web pages, search engines, and electronic databases are directly or indirectly affecting most people's routines and expectations. Other developments are poised do so in the near future. Already, for example, patients are acquiring both good and bad advice and information on the Web; many expect be able reach their therapists by e-mail. And already there is pressure from third party payers for providers submit claims electronically. These technological breakthroughs have the potential make mental health care more widely available and accessible, affordable, acceptable patients, and adaptable special needs. But many mental health professionals, as well as those who train them, are skeptical about integrating the new capabilities into their services and question the ethical and legal appropriateness of doing so. Those unfamiliar with the technologies tend be particularly doubtful. How much e-mail contact with patients should I encourage or permit, and for what purposes? Why should I set up a Web site and how do I do so and what should I put on it? Should I refer patients chat groups or Web-based discussion forums? Could video-conferencing be a helpful tool in some cases and what is involved? How do I avoid trouble if I dare experiment with innovations? And last but not least, will the results of my experimentation be cost-effective? In this wide-ranging and practical handbook, five experts, each with a different vantage point and training, systematically guide readers through the new practice arenas already made possible by current information technologies--ranging from Internet-wired offices wearable computers--and point those on the horizon. Throughout, the authors clearly define terminology for the beginner and illuminate their points with rich, clinical vignettes and first-person accounts of the experience of pioneering practitioners. The book includes: *an extensive overview of legal and regulatory issues, such as those raised by the Health Insurance Portability and Accountability Act (HIPAA); *concrete technical, ethical and managerial suggestions summarized in a seven-step Online Consultation Risk Management model; and *How to resource lists and sample documents of use beginners and experienced professionals alike. For better or worse, no mental health professional today can avoid confronting the issues presented by the new technologies. The Mental Health Professional and the New Technologies: A Handbook for Practice Today will enormously simplify the job of thinking through the issues and making clinically, ethically, and legally prudent decisions. Contents: Preface. Introduction Technology in Mental and Behavioral Health. Technicalities. A Professional Online Presence. Professional Web Site Considerations. Audio & Videoconferencing. Computer-Aided Assessment. Computer-Aided Psychotherapy. Electronic Practice Management and the Computer-Based Patient Record. Legal, Regulatory and Reimbursement Issues. Standards of Practice. Online Consultation: Training. Online Consultation: Referrals, Client Education, and Consent. Online Consultation: Delivering Clinical Care. The Near Future. The Distant Future. Epilogue: A Checklist of Immediate Steps. Appendices: Comparative Studies of Psycho-Technologies in Mental Health. Sample Listserv Guidelines. Draft International Convention for Telemedicine and Telehealth. Patient Consent Form.

The Health Insurance Portability and Accountability Act (HIPAA) of 1996 has made an impact on the operation of health-care organizations. HIPAA includes 5 titles, and its regulations are complex. Many are familiar with the HIPAA aspects that address protection of the privacy and security of patients' medical records. There are new rules to HIPAA that address the implementation of electronic medical records. HIPAA provides rules for protected health information (PHI) and what should be protected and secured. The privacy rule regulates the use and disclosure of PHI and sets standards that an entity working with health data must follow to protect patients' private medical information. The HIPAA security rule complements the privacy rule and requires entities to implement physical, technical, and administrative safeguards to protect the privacy of PHI. This article-part 1 of a 2-part series-is a refresher on HIPAA, its history, its rules, its implications, and the role that imaging professionals play.

With increasing adoption of digitized patient records and physician’s notes, managing patient records and medical data has become a major challenge for healthcare providers. Hence, cloud based healthcare services have flooded the market with their promise of ubiquitous access, scalability and low cost. The Health Insurance Portability and Accountability Act (HIPAA) regulates the privacy and security of this data maintained by the healthcare providers and all cloud based healthcare services in the United States must comply with it. The HIPAA Privacy Rule protects the privacy of individually identifiable health information, called protected health information (PHI). The Security Rule protects a subset of information covered by the Privacy Rule, which includes all individually identifiable health information a covered entity creates, receives, maintains or transmits in electronic form. We have developed a semantically rich Web Ontology Language (OWL) ontology to define the HIPAA privacy and security rules. This ontology extends the service lifecycle ontology that we have developed for automatically acquiring and consuming cloud based services in that it helps define healthcare domain specific security and privacy measures. Our HIPAA ontology defines in detail the concepts that have been specified in the act. Using this ontology in conjunction with our Cloud lifecycle ontology and incorporating the compliance and security guidelines in, users can discover and acquire Healthcare services that will comply with HIPAA security requirements. In this paper we describe this ontology.

Purpose: This review aimed to investigate the effectiveness of digital school-based mental health interventions for adolescents in Sub-Saharan Africa. Method: The authors conducted a comprehensive search of digital school-based mental health interventions to identify studies conducted in Sub-Saharan Africa targeting adolescents between the ages of (10–19) years. Peer-reviewed studies published in English between 2009 and May 2023 were obtained through electronic bibliographic databases. Result: Only one study met the full inclusion criteria for this review. The included study tested a digital mental health intervention (“Shamiri Digital”) for treating depression, anxiety, and well-being in adolescents. The “Shamiri Digital” intervention demonstrated positive outcomes on depressive symptoms within the full sample. Discussion: The dearth of studies investigating digital mental health solutions for adolescents in low-income countries demonstrates a critical gap in intervention and research for adolescent mental health in resource constrictive settings

BackgroundThe gap between mental health needs and resources for Aboriginal and Torres Strait Islander people, the Indigenous people of Australia, is most marked in the prison population. Indigenous people are overrepresented in Australian prisons. In prison, this group experiences mental disorders to a greater degree than non-Indigenous prisoners. This group has also been found to experience mental disorder at a higher rate than Indigenous people in the community. In addition to pre-existing determinants of poor mental health, these high prevalence rates may reflect poor engagement in mainstream interventions or the efficacy of available interventions. In community populations, the use of digital mental health resources may help to increase access to well-being support. However, culturally appropriate digital tools have not been available to Indigenous people in prisons. The absence of feasibility and efficacy studies of these tools needs to be addressed.ObjectiveThe aim of this study is to determine the feasibility of the Stay Strong app as a digital well-being and mental health tool for use by Indigenous people in prison.MethodsDual government agency (health and corrective services) precondition requirements of implementation were identified and resolved. This was essential given that the Stay Strong app was to be delivered by an external health agency to Indigenous prisoners. Then, acceptability at a practice level was tested using postuse qualitative interviews with clients and practitioners of the Indigenous Mental Health Intervention Program. All Indigenous Mental Health Intervention Program practitioners (10/37, 27%) and client participants who had completed their second follow-up (review of the Stay Strong app; 27/37, 73%) during the study period were invited to participate.ResultsOwing to the innovative nature of this project, identifying and resolving the precondition requirements of implementation was challenging but provided support for the implementation of the app in practice. Acceptability of the app by clients and practitioners at a practice level was demonstrated, with nine themes emerging across the interviews: satisfaction with the current Stay Strong app, supported client goal setting, increased client self-insight, improved client empowerment, cultural appropriateness, enhanced engagement, ease of use, problems with using an Android emulator, and recommendations to improve personalization.ConclusionsThe Stay Strong Custody Project is a pioneering example of digital mental health tools being implemented within Australian prisons. Using the app within high-security prison settings was found to be feasible at both strategic and practice levels. Feedback from both clients and practitioners supported the use of the app as a culturally safe digital mental health and well-being tool for Aboriginal and Torres Strait Islander people in prison.

Photo by Josh Riemer on Unsplash
 Introduction
 With the rapid advancements in neurotechnological machinery and improved analytical insights from machine learning in neuroscience, the availability of big brain data has increased tremendously. Neurological health research is done using digitized brain data.[1] There must be adequate data governance to secure the privacy of subjects participating in brain research and treatments. If not properly regulated, the research methods could lead to significant breaches of the subject’s autonomy and privacy. This paper will address the necessity for neuroprotection laws, which effectively govern the use of big brain data to ensure respect for patient privacy and autonomy.
 Background
 Artificial intelligence and machine learning can be integrated with neuroscience big brain data to drive research studies. This integrative technology allows patterns of electrical activity in neurons to be studied in detail.[2]Specifically, it uses a robotic system which can reason, plan, and exhibit biologically intelligent behavior. Machine learning is a method of computer programming where the code can adapt its behavior based on big brain data.[3] The big brain data is the collection of large amounts of information for the purpose of deciphering patterns through computer analysis using machine learning.[4] The information that these technologies provide is extensive enough to allow a researcher to read a patient’s mind. AI and machine learning technologies work by finding the underlying structure of brain data, which is then described by patterns known as latent factors, eventually resulting in an understanding of the brain’s temporal dynamics.[5]
 Through these technologies, researchers are able to decipher how the human brain computes its performances and thoughts. However, due to the extensive and complex nature of the data processed through AI and machine learning, researchers may gain access to personal information a patient may not wish to reveal. From a bioethical lens, tensions arise in the realm of patient autonomy. Patients are not able to control the transmission of data from their brains that is analyzed by researchers. Governing brain data through laws may enhance the extent of patient privacy in the case where brain data is being used through AI technologies.[6] A responsible approach to governing brain data would require a sophisticated legal structure.
 Analysis
 Impact on Patient Autonomy and Privacy 
 In research pertaining to big brain data, the consent forms do not fully cover the vast amounts of information that is collected. According to research, personal data has become the most sought out commodity to provide content to corporations and the web-based service industry. Unfortunately, data leaks that release private information frequently occur.[7] The storage of an individual’s data on technologies accessible on the internet during research studies makes it vulnerable to leaks, jeopardizing an individual’s privacy. These data leaks may cause the patient to be identified easily, as the degree of information provided by AI technologies are personalized and may be decoded through brain fingerprinting methods.[8]
 There has been an extensive growth in the development and use of AI. It is efficient in providing information to radiologists who diagnose various diseases including brain cancer and psychiatric disease, and AI assists in the delivery of telemedicine.[9] However, the ethical pitfall of reduced patient autonomy must be addressed by analyzing current AI technologies and creating more options for patient preference in how the data may be used. For instance, facial recognition technology[10] commonly used in health care produces more information than listed in common consent forms, threatening to undermine informed consent. Facial recognition software collects extensive data and may disclose more information than a person would prefer to provide despite being a useful tool for diagnosing medical and genetic conditions.[11] In addition, people may not be aware that their images are being used to generate more clinical data for other purposes. It is difficult to guarantee the data is anonymized. Consent requirements must include informing people about the complexity of the potential uses of the data; software developers should maximize patient privacy.[12] Furthermore, there is a “human element” in the use of AI technologies as medical providers control the use and the extent to which data is captured or accessed through the AI technologies.[13] People must understand the scope of the technology and have clear communication with the physician or health care provider about how the medical information will be used. 
 Existing Laws for Brain Data Governance 
 A strict system of defined legal responsibilities of medical providers will ensure a higher degree of patient privacy and autonomy when AI technologies and data from machine learning are used. Governing specific algorithmic data is crucial in safeguarding a patient’s privacy and developing a gold standard treatment protocol following the procurement of the information.[14] Certain AI technologies provide more data than others, and legal boundaries should be established to ensure strong performance, quality control, and scope for patient privacy and autonomy. For instance, currently AI technologies are being used in the realm of intensive neurological care. However, there is a significant level of patient uncertainty about how much control patients have over the data’s uses.[15] Calibrated legal and ethical standards will allow important brain data to be securely governed and monitored.
 Once brain signals are recorded and processed from one individual, the data may be merged with other data in Brain Computer Interface Technology (BCI).[16] To ensure a right and ability to retrieve personal data or pull it from the collection, specific regulations for varying types of data are needed.[17] The importance of consent and patient privacy must be considered through giving patients a transparent view of how brain data is governed.[18] The legal system must address discriminatory issues and risks to patients whose data is used in studies. Laws like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Protection Act (CCPA) can serve as effective models to protect aggregated data. These laws govern consumer information and ensure the compliance when personal data is collected.[19] California voters recently approved expansion of the CCPA to health data. The Washington Privacy Act, which would have provided rights to access, change, and withdraw personal data, failed to pass. Other states should improve privacy as well,[20] although a federal bill would be preferable. Scientists at the Heidelberg Academy of Sciences argue for data security to be governed in a manner that balances patient privacy and autonomy with the commercial interests of researchers.[21] The balance could be achieved through privacy protections like those in the Washington Privacy Act. Although the Health Insurance Portability and Accountability Act (HIPAA) provides an overall framework to deter the likelihood of dangers to patient protection and privacy, more thorough laws are warranted to combat pervasive data transfer and analysis that technology has brought to the health care industry.[22] Breaches of patient privacy under current HIPAA regulations include releasing patient information to a reporter without their consent and sending HIV data to a patient’s employer without consent.[23] HIPAA does not cover information being shared with outside contractors who do not have an agreement with technology companies to keep patient data confidential. HIPAA regulations also do not always address blatant breaches on patient data confidentiality.[24] Patients must be provided with methods to monitor the data being analyzed to be able to view the extent of private information being generated via AI technologies. In health research, the medical purposes of better diagnosis, earlier detection of diseases, or prevention are ethical justifications for the use of the data if it was collected with permission, the person understood and approved the uses of the data, and the data was deidentified.
 A standard governance framework is required in providing the fairest system of care to patients who allow their brain data to be examined. Informed consent in the neuroscience field could reaffirm the privacy and autonomy of patients by ensuring that they understand the type of information collected. Laws also could protect data after a patient’s death. Malpractice in the scope of brain data could give people a cause of action critical in safeguarding patient’s rights. Data breach lawsuits will become common but generally do not cover deidentified data that becomes part of big data collection. A more synchronized approach to the collection and consent process will encourage an understanding of how big data is used to diagnose and treat patients. Some altruistic people may even be more likely to consent if they know the largescale data collection is helpful to treat and diagnose people. Others should have the ability to opt out of sharing neurological data, especially when there is not certainty surrounding deidentification.[25]
 Conclusion
 Artificial intelligence and machine learning technologies have the potential to aid in the diagnosis and treatment of people globally by extracting and aggregating brain data specific to individuals. However, the secure use of the data is necessary to build trust between care providers and patients, as well as in balancing the bioethical principles of beneficence and patient autonomy. We must ensure the highest quality of care to patients, while protecting their privacy, informed consent, and clinical trust. More sophis

The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) includes numerous alterations to specific disorders, as well as fundamental conceptual and organizational changes. The purpose of this article is to review three fundamental conceptual changes in DSM-5: the harmonization of the manual with the International Statistical Classification of Diseases and Related Health Problems, the introduction of spectrum disorders and dimensional ratings, and the new organization of the manual. For each change, potential benefits and shortcomings are discussed in terms of innovation, limitations and clinical implications.Keywords: DSM-5, ICD-10, classification, diagnosis, spectrum disordersThe DSM is probably one of the most widely referenced texts in the mental health field. Considering this scope of influence, the release of its latest edition, DSM-5 (American Psychiatric Association [APA], 2013), has garnered considerable interest among professionals, patient advocacy groups and the public alike (Paris, 2013). Reactions have ranged from enthusiastic support (McCarron, 2013) to concern (Welch, Klassen, Borisova, & Clothier, 2013) and even calls to reject the manual's use outright (Frances, 2013; Frances & Widiger; 2012). The strength of this reaction-both positive and negative-reflects the scope of change. DSM-5 attempts to integrate almost 20 years of burgeoning research in psychopathology, classification and treatment outcomes that have emerged since the publication of DSM-IV (APA, 1994), the last major revision of the manual's criteria sets. While DSM-5 has made numerous alterations to specific disorders, fundamental conceptual and organizational changes have had the most substantial impact on reshaping the manual (APA, 2013; Regier, Kuhl, & Kupfer, 2013).The purpose of this article is to review three of these fundamental conceptual changes: the harmonization of the manual with the ICD, the introduction of spectrum disorders and dimensional ratings, and the new organization of the manual. For each of these innovations, three questions will be addressed. First, what was the basis for introducing the change as an innovation to the manual? Here the rationale and potential contribution of the change will be discussed. Special attention will be paid to issues such as enhanced diagnostic accuracy, coverage and clinical utility. Second, does the innovation have any potential drawbacks or limitations? For example, to what extent could the innovation contribute to over or underdiagnosis, limit access to treatment, or pose some harm like increased stigmatization? Third, what are the practical consequences of the innovation relative to how clinical mental health counselors provide care for their clients? This section considers the impact on day-to-day practice and how the diagnostic process itself may be transformed. The conclusion section ties these three threads of innovations together and discusses implications for mental health practice in the 21st century.DSM and ICD HarmonyThere are two major classification systems for mental disorders: the DSM, used primarily in North America, and the ICD, used worldwide under the auspices of the World Health Organization (WHO). The ICD is a much broader classification encompassing causes of death, illness, injury and related health issues with one chapter dedicated to mental and behavioral disorders (Stein, Lund, & Nesse, 2013). As part of the United Nations Charter, countries around the world have agreed to use the ICD codes to report mortality, morbidity and other health information so that uniform statistics can be compiled. In the United States, the ICD codes are the official codes approved by the Health Insurance Portability and Accountability Act (HIPAA), which are used by insurance companies, Medicare, Medicaid and other health-related agencies (Goodheart, 2014). The code numbers that the DSM has always used are derived from whatever the official version of ICD is at that time. …

Common challenges in the youth mental health system include low access, poor uptake, poor adherence, and limited overall effectiveness. Digital technologies offer promise, yet challenges in real-world integration and uptake persist. Moderated Online Social Therapy (MOST) aims to overcome these problems by integrating a comprehensive digital platform into existing youth mental health services. Theory of change (ToC) frameworks can help articulate how and why complex interventions work and what conditions are required for success. The objective of this study is to create a ToC for MOST to explain how it works, why it works, who benefits and how, and what conditions are required for its success. We used a multimethod approach to construct a ToC for MOST. The synthesis aimed to assess the real-world impact of MOST, a digital platform designed to enhance face-to-face youth mental health services, and to guide its iterative refinement. Data were gathered from 2 completed and 4 ongoing randomized controlled trials, 11 pilot studies, and over 1000 co-design sessions using MOST. Additionally, published qualitative findings from diverse clinical contexts and a review of related digital mental health literature were included. The study culminated in an updated ToC framework informed by expert feedback. The final ToC was produced in both narrative and table form and captured components common in program logic and ToC frameworks. The MOST ToC captured several assumptions about digital mental health adoption, including factors such as the readiness of young people and service providers to embrace digital platforms. External considerations included high service demand and a potential lack of infrastructure to support integration. Young people and service providers face several challenges and pain points MOST seeks to address, such as limited accessibility, high demand, poor engagement, and a lack of personalized support. Self-determination theory, transdiagnostic psychological treatment approaches, and evidence-based implementation theories and their associated mechanisms are drawn upon to frame the intervention components that make up the platform. Platform usage data are captured and linked to short-, medium-, and long-term intended outcomes, such as reductions in mental health symptoms, improvements in functioning and quality of life, reductions in hospital visits, and reduced overall mental health care costs. The MOST ToC serves as a strategic framework for refining MOST over time. The creation of the ToC helped guide the development of therapeutic content personalization, user engagement enhancement, and clinician adoption through specialized implementation frameworks. While powerful, the ToC approach has its limitations, such as a lack of standardized methodology and the amount of resourcing required for its development. Nonetheless, it provides an invaluable roadmap for iterative development, evaluation, and scaling of MOST and offers a replicable model for other digital health interventions aiming for targeted, evidence-based impact.

The central place of psychiatry in health care worldwide.

Starting in 2008, the Veterans Health Administration required mental health (MH) provider integration in nursing homes, called Community Living Centers (CLCs), to promote access to quality MH services. This project aimed to understand MH practice patterns and service integration in the CLC and to identify facilitators and barriers to integrated MH services. CLC physician and nurse leaders, and MH providers, were invited to participate in national surveys in the fall of 2022. Survey questions were designed to assess MH provider staffing and workload, organizational alignment and resources, practice and services provided, training and resource needs, MH provider satisfaction and burnout, integration, and CLC team functioning and morale. Questions included structured and open-ended formats. A total of 107 CLC MH providers and 85 CLC leaders completed their respective surveys. Descriptive and bivariate analyses were performed with quantitative data, and conventional content analysis procedures were used to analyze open-ended text responses. Findings highlighted that CLC MH providers care for Veterans with complex presentations across a range of treating specialties requiring many specialized skills, and MH integration is important and valued by CLC leaders. Results support Veterans Administration MH integration efforts and highlight the need for and importance of MH services in the CLC. MH provider job satisfaction and burnout were significantly related to team functioning, morale, and support. Findings will inform ongoing development of CLC MH practice resources and serve as a baseline for further evaluation. (PsycInfo Database Record (c) 2026 APA, all rights reserved).