Understanding MMPI-2 response structure between schizophrenia and healthy individuals
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Article number | 918999 |
| Journal / Publication | Frontiers in Psychiatry |
| Volume | 13 |
| Online published | 28 Jul 2022 |
| Publication status | Published - 2022 |
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| DOI | DOI |
|---|---|
| Attachment(s) | Documents
Publisher's Copyright Statement
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| Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85135849883&origin=recordpage |
| Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(103ed1dd-4249-4159-b43f-8ab25382bb1a).html |
Abstract
Background: Using Minnesota Multiphasic Personality Inventory-2 (MMPI-2) clinical scales to evaluate clinical symptoms in schizophrenia is a well-studied topic. Nonetheless, research focuses less on how these clinical scales interact with each other.
Aims: Investigates the network structure and interaction of the MMPI-2 clinical scales between healthy individuals and patients with schizophrenia through the Bayesian network.
Method: Data was collected from Wuhan Psychiatric Hospital from March 2008 to May 2018. A total of 714 patients with schizophrenia and 714 healthy subjects were identified through propensity score matching according to the criteria of the International Classification of Diseases (ICD-11). Separated MMPI-2 clinical scales Bayesian networks were built for healthy subjects and patients with schizophrenia, respectively.
Results: The Bayesian network showed that the lower 7 scale was a consequence of the correlation between the lower 2 scale and the greater 8 scale. A solely lower 7 scale does yield neither a lower 2 scale nor a higher 8 scale. The proposed method showed 72% of accuracy with 78% area under the ROC curve (AUC), similar to the previous studies.
Limitations: The proposed method simplified the continuous Bayesian network to predict binary outcomes, including other categorical data is not explored. Besides, the participants might only represent an endemic as they come from a single hospital.
Conclusion: This study identified MMPI-2 clinical scales correlation and built separated Bayesian networks to investigate the difference between patients with schizophrenia and healthy people. These differences may contribute to a better understanding of the clinical symptoms of schizophrenia and provide medical professionals with new perspectives for diagnosis.
© 2022 Hsu, Ye, Dai, Jing, Tsui, Yip, Liand Zhang.
Aims: Investigates the network structure and interaction of the MMPI-2 clinical scales between healthy individuals and patients with schizophrenia through the Bayesian network.
Method: Data was collected from Wuhan Psychiatric Hospital from March 2008 to May 2018. A total of 714 patients with schizophrenia and 714 healthy subjects were identified through propensity score matching according to the criteria of the International Classification of Diseases (ICD-11). Separated MMPI-2 clinical scales Bayesian networks were built for healthy subjects and patients with schizophrenia, respectively.
Results: The Bayesian network showed that the lower 7 scale was a consequence of the correlation between the lower 2 scale and the greater 8 scale. A solely lower 7 scale does yield neither a lower 2 scale nor a higher 8 scale. The proposed method showed 72% of accuracy with 78% area under the ROC curve (AUC), similar to the previous studies.
Limitations: The proposed method simplified the continuous Bayesian network to predict binary outcomes, including other categorical data is not explored. Besides, the participants might only represent an endemic as they come from a single hospital.
Conclusion: This study identified MMPI-2 clinical scales correlation and built separated Bayesian networks to investigate the difference between patients with schizophrenia and healthy people. These differences may contribute to a better understanding of the clinical symptoms of schizophrenia and provide medical professionals with new perspectives for diagnosis.
© 2022 Hsu, Ye, Dai, Jing, Tsui, Yip, Liand Zhang.
Research Area(s)
- Bayesian network, MMPI-2, network classification, personality assessment, schizophrenia
Citation Format(s)
Understanding MMPI-2 response structure between schizophrenia and healthy individuals. / Hsu, Yu Cheng; Ye, Zhiyu; Dai, Lisha et al.
In: Frontiers in Psychiatry, Vol. 13, 918999, 2022.
In: Frontiers in Psychiatry, Vol. 13, 918999, 2022.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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