JMIR Mental Health

Fetal alcohol spectrum disorder (FASD) is a common developmental disability that requires lifelong and ongoing support, but is often difficult to find due to a lack of trained professionals, limited funding and support available. Technology could provide cost-effective, accessible, and effective support to those living with FASD and their caregivers.

Telehealth implementation can be challenging for persons with serious mental illness (SMI), which may impact their quality of care and health outcomes. The literature on telehealth’s impacts on SMI care outcomes is mixed, necessitating further investigation.

The COVID-19 pandemic led to a global reduction in health care accessibility for both infected and noninfected patients, posing a particular burden on those with chronic conditions, including mental health issues. Peru experienced significant devastation from the pandemic, resulting in a collapsed health care system and leading to the world’s highest per capita mortality rate as a result of COVID-19. Understanding the trends in health care utilization, particularly in mental health care, is crucial for informing pandemic response efforts and guiding future recovery strategies.

Identifying individuals with depressive symptomatology (DS) promptly and effectively is of paramount importance for providing timely treatment. Machine learning models have shown promise in this area; however, studies often fall short in demonstrating the practical benefits of using these models and fail to provide tangible real-world applications.

Paranoia is a spectrum of fear-related experiences that spans diagnostic categories and is influenced by social and cognitive factors. The extent to which social media and other types of media use are associated with paranoia remains unclear.

Suicide is a leading cause of death worldwide. Journalistic reporting guidelines were created to curb the impact of unsafe reporting; however, how suicide is framed in news reports may differ by important characteristics such as the circumstances and the decedent’s gender.

Large language model (LLM)-powered services are gaining popularity in various applications due to their exceptional performance in many tasks, such as sentiment analysis and question answering. Recently, research has been exploring their potential use in digital health contexts, particularly in the mental health domain. However, implementing LLM-enhanced conversational artificial intelligence (CAI) presents significant ethical, technical, and clinical challenges. In this work, we discuss two challenges that affect the utilization of LLM-enhanced CAI for individuals with mental health issues, focusing on the use case of depressed patients: the tendency to humanize LLM-enhanced CAI and their lack of contextualized robustness. Our approach is interdisciplinary, relying on considerations from philosophy, psychology, and computer science. We argue that the humanization of LLM-enhanced CAI hinges on the reflection of what it means to simulate “human-like” features with LLMs and what role these systems should have in interactions with humans. Further, to ensure contextualizing robustness of LLMs requires considering the specificities of language production in depressed individuals, as well as its evolution over time. Finally, we provide a series of recommendations to foster the responsible design and deployment of LLM-enhanced CAI for the therapeutic support of individuals with depression.

Social Anxiety Disorder (SAD) is one of the most prevalent psychological disorders, and is generally co-occurring with elevated shame levels. Previous shame-specific interventions can significantly improve outcomes in social anxiety treatments. Recent review suggests that integrating a more direct shame intervention could potentially increase the effectiveness of Cognitive Behavioral Therapy. The Web-based CBT (WCBT) has proven efficacy, sustaining benefits for six months to four years. Previous evidence indicated that shame predicted the reduction of social anxiety and mediated between engagements in exposure and changes in social anxiety during WCBT.

Text-based digital media platforms have revolutionized communication and information sharing, providing valuable access to knowledge and understanding in the fields of mental health and suicide prevention.

Internet-based cognitive behavioral interventions (iCBTs) are efficacious treatments for depression and anxiety. However, it is unknown whether adding human guidance is feasible and beneficial within a large educational setting.

The focus of debates about conversational artificial intelligence (CAI) has largely been on social and ethical concerns that arise when we speak to machines—what is gained and what is lost when we replace our human interlocutors, including our human therapists, with AI. In this viewpoint, we focus instead on a distinct and growing phenomenon: letting machines speak for us. What is at stake when we replace our own efforts at interpersonal engagement with CAI? The purpose of these technologies is, in part, to remove effort, but effort has enormous value, and in some cases, even intrinsic value. This is true in many realms, but especially in interpersonal relationships. To make an effort for someone, irrespective of what that effort amounts to, often conveys value and meaning in itself. We elaborate on the meaning, worth, and significance that may be lost when we relinquish effort in our interpersonal engagements as well as on the opportunities for self-understanding and growth that we may forsake.

For people experiencing substance use or gambling disorders, web-based peer-supported forums are a space where they can share their experiences, gather around a collective goal, and find mutual support. Web-based peer support can help to overcome barriers to attending face-to-face meetings by enabling people experiencing addiction to seek support beyond their physical location and with the benefit of anonymity if desired. Understanding who participates in web-based peer-supported forums (and how), and the principles underpinning forums, can also assist those interested in designing or implementing similar platforms.