Trial reportBMC psychiatry2021
A novel model to predict mental distress among medical graduate students in China.
Trial report in BMC psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- From positive psychology to practical empowerment: theoretical construction and pathway innovation in graduate student mental health education.Frontiers in psychology · 2026Pooled it
- Depressive symptoms precede and drive problematic smartphone use in Chinese medical students: a longitudinal network analysis.Frontiers in psychology · 2026Article
- Top-tier ranking university bring worse perception of medical learning environment to students: a cross-sectional study across 12 universities.Medical education online · 2025Article
- Association Between the Time of Exposure to Electronic Screen and Anxiety and Depression After Controlling Demographics, Exercises, and Lifestyles Among University Students.Neuropsychiatric disease and treatment · 2025Article
- Thinkings on the reform of medical education system in China.Medical education online · 2024Review
- Evaluation of Depression and Its Correlates in Terms of Demographics, Eating Habits, and Exercises Among University Students: A Multicenter Cross-Sectional Analysis.Neuropsychiatric disease and treatment · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPoor 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.
methodsThis 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.
resultsOne 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.
conclusionsThe 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 registrationNo. ChiCTR2000039574 , prospectively registered on 1 November 2020.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.