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The mental health of the human population, particularly in India during and after the COVID-19 pandemic is a major concern. All age groups have undergone mental stress during and after COVID-19, especially college students in urban areas and individuals belonging to the age group from 16 to 25. Early detection of mental stress among urban students will help in the resolution of major related issues that may hurt one's career. Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) have enabled the prediction of mental health status. Numerous studies have been conducted using various approaches, but there is still no agreement on how to predict mental symptoms across age groups. In the current study, proposed DL, Long Short-Term Memory (LSTM), and ML models, namely Support Vector Machine (SVM), ADA Boost, Random Forest (RF), K-Nearest Neighbor (K-NN), Logistic Regression (LR), and Multi-Layer Perceptron (MLP) are trained and tested on a real-world dataset. The DL LSTM model outperformed the conventional ML models with an accuracy of 100%. [ABSTRACT FROM AUTHOR]

Introduction Despite being one of the oldest treatments in the field of Psychiatry, Electroconvulsive therapy (ECT) is used worldwide for various severe and treatment-resistant psychiatric disorders, establishing itself as one of the fastest and most effective treatments. Objectives The primary aim of this study was to describe a nationwide epidemiological perspective of the use of ECT in hospitalized psychiatric patients. The secondary aims were to characterize clinical and sociodemographic trends of hospitalized patients who needed ECT. Methods A retrospective-observational study was conducted using an administrative database which gathered all hospitalizations registered in Portuguese public hospitals from 2008 to 2015. We selected all hospitalizations with a procedure code 94.27 - Other electroshock therapy defined by the International Classification of Diseases version-9, Clinical Modification.The variables included in the study were birth date, sex, residence address, primary and secondary diagnoses, admission date, discharge date, length of stay (LoS), discharge status from each single hospitalization episode. Results There were a total of 879 hospitalizations with ECT during the 8-year period of the study. Most of the hospitalizations occurred in female patients (53.4 vs 46.6%), belonging to the age group of 51-70 years old, with a mean age of 50.5 years old. The median LoS was 43.0 days with an IQR of 27.0-68.0 days. The specific primary diagnosis most frequent in all hospitalizations was Major depressive disorder, recurrent episode representing 19.6% of all ECT related hospitalizations. Conclusions In Portugal most of the patients who received ECT were women above middle age, and depressive disorders were the most common indication.

The expansion of research on deep brain stimulation (DBS) and adaptive DBS (aDBS) raises important neuroethics and policy questions related to data sharing. However, there has been little empirical research on the perspectives of experts developing these technologies. We conducted semi-structured, open-ended interviews with aDBS researchers regarding their data sharing practices and their perspectives on ethical and policy issues related to sharing. Researchers expressed support for and a commitment to sharing, with most saying that they were either sharing their data or would share in the future and that doing so was important for advancing the field. However, those who are sharing reported a variety of sharing partners, suggesting heterogeneity in sharing practices and lack of the broad sharing that would reflect principles of open science. Researchers described several concerns and barriers related to sharing, including privacy and confidentiality, the usability of shared data by others, ownership and control of data (including potential commercialization), and limited resources for sharing. They also suggested potential solutions to these challenges, including additional safeguards to address privacy issues, standardization and transparency in analysis to address issues of data usability, professional norms and heightened cooperation to address issues of ownership and control, and streamlining of data transmission to address resource limitations. Researchers also offered a range of views on the sensitivity of neural activity data (NAD) and data related to mental health in the context of sharing. These findings are an important input to deliberations by researchers, policymakers, neuroethicists, and other stakeholders as they navigate ethics and policy questions related to aDBS research. [ABSTRACT FROM AUTHOR]

The island of Ireland is partitioned into Northern Ireland and the Republic of Ireland. In both jurisdictions, there have been important developments in mental health and mental capacity law, and associated policies and services. This includes an emphasis on developing more comprehensive approaches to collecting data on outcomes and so there is an opportunity to align these processes to enable comparison and shared learning across the border. This article explores: legal and policy developments; international approaches to mental health outcomes; and the type of data that would be helpful to collect to better understand the use of mental health and mental capacity laws. It is argued that an inclusive strategy to developing a comprehensive, integrated and aligned approach to collecting and analysing data would benefit citizens, policy makers and professionals. • Currently there are barriers to comparing mental health data within countries and across borders. • Legal and policy developments on the island of Ireland have created an opportunity to align data. • The use of compulsory powers should be considered in their wider context and monitored closely. • Aligning data on needs, services and outcomes would facilitate comparison and learning. [ABSTRACT FROM AUTHOR]

Background: Sharing patient data can help drive scientific advances and improve patient care, but service users are concerned about how their data are used. When the National Health Service proposes to scrape general practitioner records, it is very important that we understand these concerns in some depth., Objective: This study aims to investigate views of mental health service users on acceptable data sharing to provide clear recommendations for future data sharing systems., Methods: A total of 4 focus groups with 4 member-checking groups were conducted via the internet between October 2020 and March 2021, with a total of 22 service users in the United Kingdom. Thematic analysis was used to identify the themes., Results: Six main themes, with several subthemes were identified, such as the purpose of data sharing-for profit, public good, and continuation of care; discrimination through the misattribution of physical symptoms to mental health conditions (ie, diagnostic overshadowing) alongside the discrimination of individuals or groups within society (ie, institutional discrimination); safeguarding data by preserving anonymity and confidentiality, strengthening security measures, and holding organizations accountable; data accuracy and informed consent-increasing transparency about data use and choice; and incorporating service user involvement in system governance to provide insight and increase security., Conclusions: This study extends the limited research on the views and concerns of mental health service users regarding acceptable data sharing. If adopted, the recommendations should improve the confidence of service users in sharing their data. The five recommendations include screening to ensure that data sharing benefits the public, providing service users with information about how their data are shared and what for, highlighting the existing safeguarding procedures, incorporating service user involvement, and developing tailored training for health care professionals to address issues of diagnostic overshadowing and inaccurate health records. Adopting such systems would aid in data sharing for legitimate interests that will benefit patients and the National Health Service., (©Abimbola Adanijo, Caoimhe McWilliams, Til Wykes, Sagar Jilka. Originally published in JMIR Mental Health (https://mental.jmir.org), 03.09.2021.)

Introduction: Despite being one of the oldest treatments in the field of Psychiatry, Electroconvulsive therapy (ECT) is used worldwide for various severe and treatment-resistant psychiatric disorders, establishing itself as one of the fastest and most effective treatments. Objectives:Theprimaryaimof this studywas todescribeanationwide epidemiological perspective of the use of ECT in hospitalized psychiatric patients. The secondary aims were to characterize clinical and sociodemographic trends of hospitalized patients who needed ECT. Methods:Aretrospective-observational study was conducted using an administrative database which gathered all hospitalizations registered in Portuguese public hospitals from 2008 to 2015. We selected all hospitalizations with a procedure code 94.27 - Other electroshock therapy defined by the International Classification of Diseases version-9, Clinical Modification. The variables included in the study were birth date, sex, residence address, primary and secondary diagnoses, admission date, discharge date, length of stay (LoS), discharge status from each single hospitalization episode. Results: There were a total of 879 hospitalizations with ECT during the 8-year period of the study. Most of the hospitalizations occurred in female patients (53.4 vs 46.6%), belonging to the age group of 51-70 years old, with a mean age of 50.5 years old. The median LoS was 43.0 days with an IQR of 27.0-68.0 days. The specific primary diagnosis most frequent in all hospitalizations was Major depressive disorder, recurrent episode representing 19.6% of all ECT related hospitalizations. Conclusions: In Portugal most of the patients who received ECT were women above middle age, and depressive disorders were the most common indication. [ABSTRACT FROM AUTHOR]