{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T13:51:33Z","timestamp":1783000293186,"version":"3.54.5"},"reference-count":49,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T00:00:00Z","timestamp":1744156800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Post-doctoral Foundation Project of Shenzhen Polytechnic University","award":["6024331008K"],"award-info":[{"award-number":["6024331008K"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>The rising prevalence of mental health disorders, particularly depression, highlights the need for improved approaches in therapeutic interventions. Traditional psychotherapy relies on subjective assessments, which can vary across therapists and sessions, making it challenging to track emotional progression and therapy effectiveness objectively. Leveraging the advancements in Natural Language Processing (NLP) and domain-specific Large Language Models (LLMs), this study introduces nBERT, a fine-tuned Bidirectional Encoder Representations from the Transformers (BERT) model integrated with the NRC Emotion Lexicon, to elevate emotion recognition in psychotherapy transcripts. The goal of this study is to provide a computational framework that aids in identifying emotional patterns, tracking patient-therapist emotional alignment, and assessing therapy outcomes. Addressing the challenge of emotion classification in text-based therapy sessions, where non-verbal cues are absent, nBERT demonstrates its ability to extract nuanced emotional insights from unstructured textual data, providing a data-driven approach to enhance mental health assessments. Trained on a dataset of 2021 psychotherapy transcripts, the model achieves an average precision of 91.53%, significantly outperforming baseline models. This capability not only improves diagnostic accuracy but also supports the customization of therapeutic strategies. By automating the interpretation of complex emotional dynamics in psychotherapy, nBERT exemplifies the transformative potential of NLP and LLMs in revolutionizing mental health care. Beyond psychotherapy, the framework enables broader LLM applications in the life sciences, including personalized medicine and precision healthcare.<\/jats:p>","DOI":"10.3390\/info16040301","type":"journal-article","created":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T07:49:02Z","timestamp":1744184942000},"page":"301","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["nBERT: Harnessing NLP for Emotion Recognition in Psychotherapy to Transform Mental Health Care"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5334-9001","authenticated-orcid":false,"given":"Abdur","family":"Rasool","sequence":"first","affiliation":[{"name":"Department of Information and Computer Sciences, University of Hawaii at Manoa, Honolulu, HI 96822, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7681-4324","authenticated-orcid":false,"given":"Saba","family":"Aslam","sequence":"additional","affiliation":[{"name":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-9043-0826","authenticated-orcid":false,"given":"Naeem","family":"Hussain","sequence":"additional","affiliation":[{"name":"College of Electronics and Information Engineering, Shenzhen University, Shenzhen 518060, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sharjeel","family":"Imtiaz","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Loadstop, Lake Forest, CA 92610, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1700-0299","authenticated-orcid":false,"given":"Waqar","family":"Riaz","sequence":"additional","affiliation":[{"name":"Institute of Intelligent Manufacturing Technology (IIMT), Shenzhen Polytechnic University, 4089 Shahe West Road, Shenzhen 518055, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e49074","DOI":"10.2196\/49074","article-title":"Understanding mental health issues in different subdomains of social networking services: Computational analysis of text-based Reddit posts","volume":"25","author":"Kim","year":"2023","journal-title":"J. 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