A novel model to predict mental distress among medical graduate students in China
Abstract Background Poor mental health was reported among medical graduate students in some studies. Identification of risk factors for predicting the mental health is capable of reducing psychological distress among medical graduate students. Therefore, the aim of the study was to identify potentia...
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| Format: | Article |
| Language: | English |
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BMC
2021-11-01
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| Series: | BMC Psychiatry |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12888-021-03573-9 |
| _version_ | 1818928462545551360 |
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| author | Fei Guo Min Yi Li Sun Ting Luo Ruili Han Lanlan Zheng Shengyang Jin Jun Wang Mingxing Lei Changjun Gao |
| author_facet | Fei Guo Min Yi Li Sun Ting Luo Ruili Han Lanlan Zheng Shengyang Jin Jun Wang Mingxing Lei Changjun Gao |
| author_sort | Fei Guo |
| collection | DOAJ |
| description | Abstract Background Poor mental health was reported among medical graduate students in some studies. Identification of risk factors for predicting the mental health is capable of reducing psychological distress among medical graduate students. Therefore, the aim of the study was to identify potential risk factors relating to mental health and further create a novel prediction model to calculate the risk of mental distress among medical graduate students. Methods This study collected and analyzed 1079 medical graduate students via an online questionnaire. Included participants were randomly classified into a training group and a validation group. A model was developed in the training group and validation of the model was performed in the validation group. The predictive performance of the model was assessed using the discrimination and calibration. Results One thousand and fifteen participants were enrolled and then randomly divided into the training group (n = 508) and the validation group (n = 507). The prevalence of severe mental distress was 14.96% in the training group, and 16.77% in the validation group. The model was developed using the six variables, including the year of study, type of student, daily research time, monthly income, scientific learning style, and feeling of time stress. The area under the receiver operating characteristic curve (AUROC) and calibration slope for the model were 0.70 and 0.90 (95% CI: 0.65 ~ 1.15) in the training group, respectively, and 0.66 and 0.80 (95% CI, 0.51 ~ 1.09) in the validation group, respectively. Conclusions The study identified six risk factors for predicting anxiety and depression and successfully created a prediction model. The model may be a useful tool that can identify the mental status among medical graduate students. Trial registration No. ChiCTR2000039574 , prospectively registered on 1 November 2020. |
| first_indexed | 2024-12-20T03:29:18Z |
| format | Article |
| id | doaj.art-95161aa91a89446ab1e322138762ae8a |
| institution | Directory Open Access Journal |
| issn | 1471-244X |
| language | English |
| last_indexed | 2024-12-20T03:29:18Z |
| publishDate | 2021-11-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Psychiatry |
| spelling | doaj.art-95161aa91a89446ab1e322138762ae8a2022-12-21T19:55:01ZengBMCBMC Psychiatry1471-244X2021-11-0121111210.1186/s12888-021-03573-9A novel model to predict mental distress among medical graduate students in ChinaFei Guo0Min Yi1Li Sun2Ting Luo3Ruili Han4Lanlan Zheng5Shengyang Jin6Jun Wang7Mingxing Lei8Changjun Gao9Department of Anesthesiology, The Second Affiliated Hospital of Air Force Medical UniversityInstitute of Medical Information, Chinese Academy of Medical Sciences/Peking Union Medical CollegeDepartment of Anesthesiology, The Second Affiliated Hospital of Air Force Medical UniversityDepartment of Obstetrics and Gynecology, the Second Xiangya Hospital of Central South UniversityDepartment of Anesthesiology, The Second Affiliated Hospital of Air Force Medical UniversityDepartment of Anesthesiology, The Second Affiliated Hospital of Air Force Medical UniversityPlastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Anesthesiology, Shaanxi Provincial Armed Police HospitalChinese PLA Medical SchoolDepartment of Anesthesiology, The Second Affiliated Hospital of Air Force Medical UniversityAbstract Background Poor mental health was reported among medical graduate students in some studies. Identification of risk factors for predicting the mental health is capable of reducing psychological distress among medical graduate students. Therefore, the aim of the study was to identify potential risk factors relating to mental health and further create a novel prediction model to calculate the risk of mental distress among medical graduate students. Methods This study collected and analyzed 1079 medical graduate students via an online questionnaire. Included participants were randomly classified into a training group and a validation group. A model was developed in the training group and validation of the model was performed in the validation group. The predictive performance of the model was assessed using the discrimination and calibration. Results One thousand and fifteen participants were enrolled and then randomly divided into the training group (n = 508) and the validation group (n = 507). The prevalence of severe mental distress was 14.96% in the training group, and 16.77% in the validation group. The model was developed using the six variables, including the year of study, type of student, daily research time, monthly income, scientific learning style, and feeling of time stress. The area under the receiver operating characteristic curve (AUROC) and calibration slope for the model were 0.70 and 0.90 (95% CI: 0.65 ~ 1.15) in the training group, respectively, and 0.66 and 0.80 (95% CI, 0.51 ~ 1.09) in the validation group, respectively. Conclusions The study identified six risk factors for predicting anxiety and depression and successfully created a prediction model. The model may be a useful tool that can identify the mental status among medical graduate students. Trial registration No. ChiCTR2000039574 , prospectively registered on 1 November 2020.https://doi.org/10.1186/s12888-021-03573-9Mental distressPrediction modelMedical graduate student |
| spellingShingle | Fei Guo Min Yi Li Sun Ting Luo Ruili Han Lanlan Zheng Shengyang Jin Jun Wang Mingxing Lei Changjun Gao A novel model to predict mental distress among medical graduate students in China BMC Psychiatry Mental distress Prediction model Medical graduate student |
| title | A novel model to predict mental distress among medical graduate students in China |
| title_full | A novel model to predict mental distress among medical graduate students in China |
| title_fullStr | A novel model to predict mental distress among medical graduate students in China |
| title_full_unstemmed | A novel model to predict mental distress among medical graduate students in China |
| title_short | A novel model to predict mental distress among medical graduate students in China |
| title_sort | novel model to predict mental distress among medical graduate students in china |
| topic | Mental distress Prediction model Medical graduate student |
| url | https://doi.org/10.1186/s12888-021-03573-9 |
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