Development and validation of an automated machine for self-injury assessment via young Koreans' natural writings.
Self-injury is common in all countries, and 20% of South Korean youths experience self-injury. One of the barriers to assessment and treatment planning is the tendency of young self-injurers to conceal their identities. Following a new stream of research that uses online text data to assess psycholo...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0316619 |
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| author | Seoyoung Kim Dong-Gwi Lee |
| author_facet | Seoyoung Kim Dong-Gwi Lee |
| author_sort | Seoyoung Kim |
| collection | DOAJ |
| description | Self-injury is common in all countries, and 20% of South Korean youths experience self-injury. One of the barriers to assessment and treatment planning is the tendency of young self-injurers to conceal their identities. Following a new stream of research that uses online text data to assess psychological symptoms as they are described in online posts, this study developed a computerized machine that can analyze South Korean self-injurers' writing in assessing their self-injury severity. Based on 16,645 online posts, Study 1 developed a machine called the Korean Self-Injurious Text Reviewer (K-SITR) using Latent Dirichlet Allocation topic modeling and machine learning. The K-SITR's text-assessment results were statistically indistinguishable from those of professional counselors. Study 2 confirmed the validity of the K-SITR through a survey of 47 young Koreans who had experienced self-injury. Results showed that the K-SITR scores converged with participants' self-injury frequency and duration and discriminated from other heterogenous factors. The K-SITR also had incremental validity over two popular self-injury questionnaires. This study provides a new measure that may reduce the tendency of young self-injurers to self-conceal compared to traditional direct-item questionnaires. |
| format | Article |
| id | doaj-art-d0f56ad116164991812017be5cff375e |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-d0f56ad116164991812017be5cff375e2025-02-05T05:31:18ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01201e031661910.1371/journal.pone.0316619Development and validation of an automated machine for self-injury assessment via young Koreans' natural writings.Seoyoung KimDong-Gwi LeeSelf-injury is common in all countries, and 20% of South Korean youths experience self-injury. One of the barriers to assessment and treatment planning is the tendency of young self-injurers to conceal their identities. Following a new stream of research that uses online text data to assess psychological symptoms as they are described in online posts, this study developed a computerized machine that can analyze South Korean self-injurers' writing in assessing their self-injury severity. Based on 16,645 online posts, Study 1 developed a machine called the Korean Self-Injurious Text Reviewer (K-SITR) using Latent Dirichlet Allocation topic modeling and machine learning. The K-SITR's text-assessment results were statistically indistinguishable from those of professional counselors. Study 2 confirmed the validity of the K-SITR through a survey of 47 young Koreans who had experienced self-injury. Results showed that the K-SITR scores converged with participants' self-injury frequency and duration and discriminated from other heterogenous factors. The K-SITR also had incremental validity over two popular self-injury questionnaires. This study provides a new measure that may reduce the tendency of young self-injurers to self-conceal compared to traditional direct-item questionnaires.https://doi.org/10.1371/journal.pone.0316619 |
| spellingShingle | Seoyoung Kim Dong-Gwi Lee Development and validation of an automated machine for self-injury assessment via young Koreans' natural writings. PLoS ONE |
| title | Development and validation of an automated machine for self-injury assessment via young Koreans' natural writings. |
| title_full | Development and validation of an automated machine for self-injury assessment via young Koreans' natural writings. |
| title_fullStr | Development and validation of an automated machine for self-injury assessment via young Koreans' natural writings. |
| title_full_unstemmed | Development and validation of an automated machine for self-injury assessment via young Koreans' natural writings. |
| title_short | Development and validation of an automated machine for self-injury assessment via young Koreans' natural writings. |
| title_sort | development and validation of an automated machine for self injury assessment via young koreans natural writings |
| url | https://doi.org/10.1371/journal.pone.0316619 |
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