Abd Yusof, NF and Lin, C orcid.org/0000-0003-3454-2468 (2021) Routine outcome monitoring in psychotherapy treatment using sentiment-topic modelling approach. International Journal on Advanced Science, Engineering and Information Technology, 11 (6). 2428. ISSN 2088-5334
Abstract
Despite the importance of emphasizing the right psychotherapy treatment for an individual patient, assessing the outcome
of the therapy session is equally crucial. Evidence showed that continuous monitoring of patient's progress could significantly improve
the therapy outcomes to an expected change. The patient's progress can be tracked closely to help clinicians identify not progressing in
the treatment by monitoring the outcome. This monitoring can help the clinician consider any necessary actions for the patient's
treatment as early as possible, e.g., recommend different types of treatment or adjust the style of approach. Currently, the evaluation
system is based on the clinical-rated and self-report questionnaires that measure patients' progress pre-and post-treatment. While
outcome monitoring tends to improve therapy outcomes, there are many challenges in the current method, e.g., time and financial
burden for administering questionnaires, scoring, and analyzing the results. Therefore, a computational method for measuring and
monitoring patient progress throughout treatment is needed to enhance the likelihood of positive treatment outcomes. This paper
focuses on developing a computational method using a Dynamic Joint-Sentiment-Topic model (dJST) to measure and monitor the
patient treatment outcome by tracking patient’s current and recurrent views of topic and sentiment. We identified the sentiment and
topic trend evolved throughout treatments for each therapy session on the author's level. Our results show that this computational
method could potentially lead to an inexpensive clinical monitoring tool to evaluate patients' progress during psychotherapy.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2021 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | depression; progress monitoring outcome; Psychotherapy treatment; sentiment-topic model |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 23 Nov 2022 10:48 |
Last Modified: | 23 Nov 2022 10:48 |
Status: | Published |
Publisher: | Insight Society |
Refereed: | Yes |
Identification Number: | 10.18517/ijaseit.11.6.13602 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:193589 |