Youth Mental health concerns among young individuals have spurred interest in innovative interventions. Automated Conversational Agents (CAs) represent a promising avenue for addressing psychiatric well-being, offering a digital alternative to traditional approaches.
Overview of Automated Conversational Agents:
CAs, leveraging text, speech, and sensory expressions, mimic human interaction, providing a platform for youth mental health support. However, existing research primarily targets adult populations, overlooking the distinct needs of youth.
Scope of the Review:
In this review, researchers scrutinized the potential of automated CAs in bolstering the mental wellness of individuals aged ≤25 years. Employing a rigorous methodology, they surveyed primary research studies across diverse platforms and communication modalities.
Key Findings:
From a pool of nearly 10,000 records, the analysis focused on 25 eligible studies encompassing 1,707 participants. The review identified 21 distinct CAs, predominantly disembodied chatbots and virtual representations, with notable systems including Paro, Nao, and Woebot.
Technological Insights:
Dialog systems employed by CAs primarily relied on machine learning and natural language processing. The targeted youth mental health outcomes spanned anxiety, depression, general distress, and mood disorders, with Cognitive Behavioral Theory and positive psychology emerging as prevalent theoretical frameworks.
Participant Characteristics:
Participants, primarily recruited from educational and healthcare settings, exhibited a mean age of 17 years, with a notable representation of females. Feasibility outcomes, including engagement and acceptability, underscored the potential of automated CAs in fostering user satisfaction and system usability.
Clinical Efficacy:
Studies revealed promising outcomes in anxiety and depression management, with significant improvements observed in controlled trials. Notably, CAs demonstrated efficacy in alleviating medical procedure-related anxiety, signifying their versatility across diverse contexts.
Challenges and Future Directions:
Despite notable strides, safety concerns and limited sample sizes warrant further investigation. Future reviews should prioritize safety research, explore a broader spectrum of clinical issues, and assess cost-effectiveness to ensure accessibility across diverse socio-economic landscapes.
Conclusion:
The burgeoning field of automated conversational agents holds immense promise in revolutionizing youth mental health interventions. By embracing interdisciplinary collaboration and methodological rigor, researchers can unlock the full potential of digital solutions, paving the way for equitable mental health support for generations to come.
