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This study presents a learning method for analyzing depression through text using a mix of Recurrent Neural Networks (RNNs) and Transformer frameworks to pinpoint subtle linguistic cues linked to depression. While natural language processing (NLP) ...

The number of university students with suicidal thoughts is alarmingly high, and there is a general taboo about suicidal thoughts. This study aimed to investigate whether a serious game could promote engagement and increase knowledge about suicidal ...

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Guidance on how to evaluate accuracy and algorithmic fairness across subgroups is missing for clinical models that flag patients for an intervention but when health care resources to administer that intervention are limited. We aimed to ...

Recent increases in self-harm and suicide rates among youth have coincided with prevalent social media use; therefore, making these sensitive topics of critical importance to the HCI research community. We analyzed 1,224 direct message conversations (...

Suicide is a significant public health issue that devastates individuals and society. Early warning systems are crucial in preventing suicide. The purpose of this research is to create a deep learning model to identify suicide risk using a ...

Online social networks can be used for mental healthcare monitoring using Artificial Intelligence and Machine Learning techniques for detecting various mental health disorders and corresponding risk assessment. Recent research in this domain has ...

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Suicide risk prediction algorithms at the Veterans Health Administration (VHA) do not include predictors based on the 3-Step Theory of suicide (3ST), which builds on hopelessness, psychological pain, connectedness, and capacity for ...

Online social networking (SN) data presents a data stream that is rich in context and temporal information. It holds promise for predicting suicidal thoughts and behaviors. The fusion of SN data with machine learning algorithms offers a potential ...

Since depression often results in suicidal thoughts and leaves a person severely disabled daily, there is an elevated risk of premature mortality due to mental problems caused by depression. Therefore, it's crucial to identify the patient's ...

• More than two-thirds of suicides each year are caused by depression, which is the most common mental illness.
• Social media posts can be a useful tool for tracking a variety of mental health conditions, including depression.
• The ...

Mental health has become a major concern in recent years. Social media have been increasingly used as platforms to gain insight into a person’s mental health condition by analysing the posts and comments, which are textual in nature. ...

• The proposed method detects depression from Bangla social media texts.
• The ...

Annually, tens of thousands of lives are affected by suicide, including those who die by suicide, attempt non-fatal suicidal behaviors, and suffer from suicidal thoughts and ideation as well as friends and family affected by the loss ...

• People who feel that they don't matter seek out help in online communities.
• ...

Suicide is a major cause of death. It is also a complex public health issue and often preventable with timely intervention. Overall, the rate of suicide is increasing for various reasons. In our study, we use an association rule analysis to find ...

Suicide deaths due to depression and mental stress are growing rapidly at an alarming rate. People freely express their feelings and emotions on social network sites while they feel hesitant to express such feelings during face-to-face ...

Psychological health, i.e., citizens’ emotional and mental well-being, is one of the most neglected public health issues. Depression is the most common mental health issue and the leading cause of suicide and self-injurious behavior. ...

• It is imperative to develop real-time, scalable, and inexpensive mental health assessment & surveillance systems for detection of mental health disorders.

Background: With the development of Internet, many people with suicide risk tend to express their thoughts on social media platforms. AI-based model can early identify social media users with suicide risk and analyze their cognitive and ...

Many high-risk individuals do not use mental health services. This is a concern for mental health and suicide prevention efforts, and requires an examination of the role of decision-making style upon willingness to seek help. To consider whether ...

• An online survey looked at risk, decisional styles, and willingness to seek help.
• A preference for online assistance was associated with hypervigilance.
• A reluctance to seek offline help was documented from online activity.

The Internet's design and raison d'être are complete freedom, but complete freedom might lead to anarchy and to harmful and anti-social activities. In this paper I address the concepts of moral and social responsibility, applying them to the Internet ...

Suicidal Ideation (SI) is characterized by a desire to die and, in many cases, even planning a suicide with writing notes or farewell letters. As a digital phenotyping-based application, the Boamente tool remotely detects patterns that indicate SI ...

Suicide is a growing public health concern. The method currently assessing suicide risk is very subjective, which may limit the efficacy and accuracy of forecasting efforts. It has been suggested that artificial intelligence (AI) has potential ...

Suicide has always been a key issue of social and health organizations and research of scholars. In recent years, with the increasing popularity of Internet and social media, more and more people record their lives and feelings in social media, ...