About this Research Topic

Background

The prevalence of mental health issues is rapidly increasing worldwide, whereas the gap between the need for treatment and the capacity to deliver it, is constantly increasing even in high-income countries. Though the COVID-19 pandemic had detrimental mental health consequences, including decreased cognition, decreased focus, performance problems, and changes in mood and behavior, it also offered new and advanced digital health applications within the fields of psychiatry and psychotherapy. These tools offer a promising new avenue for approaching mental health issues via a complementary to traditional care channel, that offers scalable interventions even in cases of lack of physical contact between the patient and the carer.

The tremendous increase in Artificial Intelligence (AI) applications allows the early identification of mood disorders and digital psychological interventions. Natural Language Processing (NLP) techniques enable computers to understand unstructured text from social media or conversational interactions, and thus to identify patterns of mental health deterioration, fine-grained phenotypic outcome measures in treatment, or even population trends to significant events that may influence our mood and/or mental health. Apart from text, voice and video data may be also employed for the identification of mental health patterns.

Another major NLP field is that of conversational agents that deliver appropriate contextual responses to complex language inputs, establishing thus an interactive communication with the users. Although there are important safety concerns regarding the quality of automated therapy for mental health issues, chatbots present a clear potential to offer a personalized therapeutic environment through a highly accessible and structured, safe, and comfortable digital environment.

In this Research Topic, we are looking to address key aspects of NLP applications in either the early identification of mental health deterioration patterns or in the applicability of conversational agents as a treatment approach. Our aim is to promote discussion regarding how NLP applications could result in novel therapeutics within the fields of digital psychiatry and psychotherapy. We also welcome studies reporting novel results that increase our understanding of the applicability, adherence, and effectiveness of AI-based, digital health solutions in the mental health field.

We particularly welcome submission of Original Research, Review, Methods, and Perspective articles on the following sub-topics:

• Systematic reviews, perspectives, or challenge articles in the application of NLP-based solutions in the fields of digital psychiatry and tele-psychotherapy.

• Research articles on the identification of mental health patterns from text, voice, or video data.

• Studies focusing on obtaining mental health information from social media.

• Telemedicine applications in the fields of psychotherapy or digital psychiatry.

• Outcomes of clinical trial regarding the effectiveness of NLP solutions in psychiatric treatment.

• Development of chatbots dedicated to identifying or/and differentially diagnosing mental disorders.

• Technical and evaluation aspects of web-based cognitive-behavioral therapeutic (CBT) apps implemented by means of conversational agents.

• Harmonization studies aiming to standardize the use and evaluation of chatbots in digital psychiatry.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Classification
• Clinical Trial
• Community Case Study
• Conceptual Analysis
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Classification
• Clinical Trial
• Community Case Study
• Conceptual Analysis
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Registered Report
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: mood disorders, mental health, chatbots, AI, NLP techniques, digital psychiatry, cognitive-behavioral therapeutics, mental disorders

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