Augmenting Reddit Posts to Determine Wellness Dimensions impacting Mental Health

Abstract

Amid ongoing health crisis, there is a growing necessity to discern possible signs of Wellness Dimensions (WD) 1 manifested in self-narrated text. As the distribution of WD on social media data is intrinsically imbalanced, we experiment the generative NLP models for data augmentation to enable further improvement in the prescreening task of classifying WD. To this end, we propose a simple yet effective data augmentation approach through promptbased Generative NLP models, and evaluate the ROUGE scores and syntactic/semantic similarity among existing interpretations and augmented data. Our approach with ChatGPT model surpasses all the other methods and achieves improvement over baselines such as Easy-Data Augmentation and Backtranslation. Introducing data augmentation to generate more training samples and balanced dataset, results in the improved F-score and the Matthew's Correlation Coefficient for upto 13.11% and 15.95%, respectively.

Applications of Large Language Models in Psychiatry: A Systematic Review

“…Subsequent screening based on titles and abstracts led to the exclusion of 255 papers, primarily due to their irrelevance or lack of discussion on LLMs, leaving 33 articles for full-text evaluation. Upon detailed examination, 16 studies were found to meet our inclusion criteria and were thus selected for the final review (23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38). The process of study selection and the results at each stage are comprehensively illustrated in Figure 2, the PRISMA flowchart.…”

“…Our findings demonstrate LLMs, especially ChatGPT and GPT-4, potential as a valuable tool in psychiatry, offering diverse applications from clinical support to educational roles. Studies like Liyanage et al and Mazumdar et al showcased its efficacy in data augmentation and mental health disorder classification (32,36).…”

“…However, concerns about its limitations and safety in clinical scenarios were evident, ChatGPT's diverse applications, from clinical data analysis to formulating psychodynamic profiles, which contribute to a more efficient, accessible, and versatile approach in mental healthcare (19,20,36,37). Moreover, in light of the COVID-19 pandemic's impact on mental health and the growing demand for digital interventions, Mitsea et al's research highlights the significant role of AI in enhancing digitally assisted mindfulness training for self-regulation and mental well-being, further enriching the scope of AI applications in mental healthcare (40).…”

“…In highlighting key studies, Liyanage et al found that ChatGPT was effective in enhancing Reddit post analysis for wellness classification (36). Levkovich et al observed ChatGPT's unbiased approach in depression diagnosis, contrasting with biases noted in primary care physicians' methods, especially due to gender and socioeconomic status (31).…”

“…• Liyanage et al used ChatGPT models to augment data from Reddit posts, enhancing classifier performance in identifying Wellness Dimensions. This resulted in improvements in the F-score of up to 13.11% (36).…”