Obsessive-compulsive symptoms is a common psychological phenomenon among college students. There is a wealth of cross-sectional research examining the overall development trend of obsessive-compulsive symptoms among college students, but there is a lack of research on the development trajectory of obsessive-compulsive symptoms among college students.
To investigate the development trajectory and influencing factors of compulsive symptoms among college students through longitudinal tracking.
The study employed a cluster random sampling method to select freshman students from Xinjiang Normal University as the research subjects, and conducted three follow-up tests using the obsessive-symptom and anxiety subscales in the Symptom Checklist 90 (SCL-90) over a period of 3 years. The first test was initiated in November 2020 (T1) , followed by the second test in March 2022 (T2) , and the third test in March 2023 (T3) . The survey results were analyzed using latent variable growth modeling.
Data analysis was conducted using 3 289 valid samples who participated in all three measurements. Among the 3 289 college students, there were 1 966 females (59.8%) , 2 352 Han nationality (71.5%) , with an average age at the first survey of (21.0±0.7) years old. The scores of anxiety subscales in the SCL-90 were (1.48±0.51) scores at T1, (1.38±0.45) scores at T2 and (1.33±0.43) scores at T3; The scores of obsessive-symptom subscales in the SCL-90 were (1.75±0.58) scores at T1, (1.66±0.55) scores at T2 and (1.53±0.53) scores at T3. Pearson correlation analysis showed that there was a positive correlation between obsessive-compulsive symptoms and anxiety in college students at each time point (P<0.05) . The unconditional linear model showed a good fit, with a significant positive intercept (P<0.001) and a significant negative slope (P<0.001) , and a negative correlation between the intercept and slope (r=-0.033, P<0.001) , indicating that the scores of compulsive symptoms among college students showed a downward trend, with a higher starting level leading to a faster rate of decline. Inclusion of gender covariates (male=0, female=1) , it was found that gender had a positive predictive effect on intercept (β=0.105, P<0.001) , but had no significant predictive effect on slope (β<0.001, P>0.05) , indicating that female college students had a higher initial level of obsessive-compulsive symptoms than male students, and there was no significant difference in decline rate. After including anxiety as a covariate, it was found that anxiety positively affected obsessive-compulsive symptoms at each time point (P<0.001) . It was also found that gender had a positive predictive effect on the slope (β=0.017, P<0.05) , but had no significant predictive effect on the intercept (β=0.012, P>0.05) , indicating that after controlling for the influence of anxiety, the decline rate of obsessive symptoms in female college students was significantly lower than that in male college students.
Obsessive-compulsive symptoms among college students decrease with the increase of grade, and a high starting level does not necessarily lead to long-term distress. Anxiety hinders the alleviation of obsessive-compulsive symptoms and influences the emergence of obsessive-compulsive symptoms in female college students and the decline rate of obsessive-compulsive symptoms in male college students to a greater extent.
The incidence of major depressive disorder (MDD) in adolescents is annually elevated. Non-suicidal self-injury (NSSI) is a common clinical manifestation of MDD. Evidence suggested that vitamin D and lipid levels are associated with MDD, but whether they are related to NSSI is unclear.
To compare the levels of 25 (OH) D3 and blood lipids in MDD adolescents with or without NSSI behavior, and to explore their diagnostic value for NSSI.
A total of 129 MDD adolescents who received treatment in the Department of Psychiatry, Chaohu Hospital of Anhui Medical University and the Fourth People's Hospital of Hefei from October 2020 to March 2022 were recruited. They were assigned into NSSI group (n=77) and non-NSSI group (n=52) based on the diagnostic criteria of NSSI in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) . The Positive and Negative Suicide Ideation (PANSI) , Insomnia Severity Index (ISI) , and Center for Epidemiological Survey, Depression Scale (CES-D) were used to evaluate the clinical symptoms. Fasting venous blood samples were collected to measure the levels of 25 (OH) D3 and blood lipids, and compared between groups. In addition, multivariate Logistic regression analysis was performed to identify influencing factors for NSSI behavior in MDD adolescents. The diagnostic value of 25 (OH) D3 and lipid levels in NSSI behaviors was assessed by plotting the receiver operating characteristic (ROC) curves.
The age of the NSSI group was significantly lower than that of the non-NSSI group, whereas the total scores of PANSI, ISI, and CES-D were significantly higher than those of the non-NSSI group (P<0.05) . The level of 25 (OH) D3 in the NSSI group was significantly lower than that in the non-NSSI group, whereas the levels of total cholesterol (TC) , high-density lipoprotein cholesterol (HDL-C) , and low-density lipoprotein cholesterol (LDL-C) were significantly higher than those in the non-NSSI group (P<0.05) . Multivariate Logistic regression analysis showed that both LDL-C (OR=5.695, 95%CI=2.422-13.388, P<0.001) and 25 (OH) D3 (OR=0.871, 95%CI=0.768-0.987, P<0.05) were the influencing factors of MDD adolescents with NSSI. The area under curve (AUC) of LDL-C and 25 (OH) D3 levels in assessing the risk of developing NSSI behavior in MDD adolescents was 0.73 (95%CI=0.65-0.82, P<0.001) and 0.62 (95%CI=0.52-0.72, P=0.023) , respectively. Their optimal cut-off value was 1.89 mmol/L and 19.15 μg/L, respectively. The AUC of 25 (OH) D3 combined with LDL-C levels [ln (p/1-p) =1.364X1-0.143X2-0.161, where X1 and X2 was LDL-C and 25 (OH) D3, respectively] in diagnosing NSSI behavior in MDD adolescents was 0.77 (95%CI=0.69-0.85, P<0.001) , with 77.92% of sensitivity and 67.31% of specificity.
25 (OH) D3 and lipid levels are out of normal ranges in MDD adolescents with NSSI. Measurement of LDL-C combined with 25 (OH) D3 levels may provide information to predict the occurrence of NSSI behaviors in MDD adolescents. A regular measurement of LDL-C and 25 (OH) D3 and a dynamic monitor is valuable to provide symptomatic supports.
