Abstract
BACKGROUND: Halbert L. Dunn's concept of wellness is a multi-dimensional aspect encompassing social and mental well-being. Neglecting these dimensions over time can have a negative impact on an individual's mental health. The manual efforts employed in in-person therapy sessions reveal that underlying factors of mental disturbance if triggered, may lead to severe mental health disorders. OBJECTIVE: In our research, we introduce a fine-grained approach focused on identifying indicators of wellness dimensions and mark their presence in self-narrated human-writings on Reddit social media platform. DESIGN AND METHOD: We present the MultiWD dataset, a curated collection comprising 3281 instances, as a specifically designed and annotated dataset that facilitates the identification of multiple wellness dimensions in Reddit posts. In our study, we introduce the task of identifying wellness dimensions and utilize state-of-the-art classifiers to solve this multi-label classification task. RESULTS: Our findings highlights the best and comparative performance of fine-tuned large language models with fine-tuned BERT model. As such, we set BERT as a baseline model to tag wellness dimensions in a user-penned text with F1 score of 76.69. CONCLUSION: Our findings underscore the need of trustworthy and domain-specific knowledge infusion to develop more comprehensive and contextually-aware AI models for tagging and extracting wellness dimensions.