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Objective@#To construct a nonsuicidal selfinjury (NSSI) risk prediction model for middle school students using different machine learning algorithms and evaluate the models effectiveness, so as to provide guidance for the prevention and control of NSSI in campus.@*Methods@#In March 2023, a total of 3 372 middle and high school students from schools in Nanchang, Fuzhou and Shangrao cities in Jiangxi Province were selected by combining stratified random cluster sampling and convenient sampling methods. Questionnaire surveys were conducted using various instruments including general information questionnaire, Selfesteem Scale, Ottawa Selfinjury Scale, Social Support Assessment Scale, Chinese Version of the Olweus Bullying Questionnaire, Event Attribution Style Scale, Adolescent Resilience Scale, and Adolescent Life Events Scale. Data were divided into training set (n=2 361) and test set (n=1 011) at a ratio of 7∶3, and variables were selected based on univariate and LASSO regression results. Four machine learning algorithms including namely random forest, support vector machine, Logistic regression and XGBoost, were used to construct NSSI risk prediction models, and the models performance was evaluated and compared using metrics including area under curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value and F1 score.@*Results@#The detection rate of NSSI among middle school students was 34.4%. Univariate analysis showed that there were statistically significant differences in NSSI detection rates among middle school students of different grades, genders, registered residence locations, whether they were class cadres and four types of bullying (physical, verbal, relational bullying and cyberbullying) (χ2=27.17, 15.81, 11.54, 4.63;68.22, 140.63, 77.81, 13.95, P<0.05). NSSI was included as the dependent variable in the LASSO regression model for variable screening, and the results regression identified 10 predictive variables including grade level, selfesteem, subjective support, support utilization, verbal bullying, emotional control, interpersonal relationships, punishment, loss of relatives and property, and health and adaptation issues. The AUC values of random forest, support vector machine, Logistic regression, and XGBoost algorithms were 0.76, 0.76, 0.76 and 0.77, respectively, with no statistically significant differences between pairwise comparisons (Z=-0.59-0.82, P>0.05). Sensitivity values were 0.62, 0.61, 0.62 and 0.61, respectively. Specificity values were 0.74, 0.78, 0.78 and 0.78, respectively. Positive predictive values were 0.56, 0.59, 0.60 and 0.59, respectively. Negative predictive values were 0.79, 0.79, 0.80 and 0.79, respectively. F1 scores were 0.59, 0.60, 0.61 and 0.60, respectively.@*Conclusions@#All four nonsuicidal selfinjury risk prediction models perform well, with the Logistic regression model slightly outperforming the others. Schools and parents should pay attention to the predictive factors corresponding to NSSI, so as to reduce the occurrence of NSSI among middle school students.
RESUMO
<p><b>OBJECTIVE</b>To evaluate the influence of small-dose dexmedetomidine infusion on recovery of patients undergoing vertebral operation.</p><p><b>METHODS</b>Sixty ASA I-II patients undergoing vertebral operation were randomly divided into two groups (n=30). In group I, dexmedetomidine infusion was pumped at the rate of 0.5 µg·kg(-1)·h(-1) from tracheal intubation to incision suture, and in group II, 0.9%saline was pumped instead. The mean arterial pressure, heart rate, Riker Sedation-Agitation Scale and Ramesay sedation score were recorded at the time points of autonomous respiration (T1), eye opening (T2), extubation (T3), 1 min after extubation (T4), 10 min after extubation (T5), and 30 min after extubation (T6).</p><p><b>RESULTS</b>The recovery time of autonomous respiration and eye opening time in group I were significantly longer than those in group II, and the extubation time was significantly shorter in group I (P<0.05). Riker Sedation-Agitation Scale scores in group II were significantly higher than those in group I at T2 and T4, and Ramesay sedation scores in group I were significantly higher than those in group II at T1, T2 and T5 (P<0.05). The mean arterial pressure and heart rate at each time point was significantly lower in group I than in group II (P<0.05), especially at T3 and T4 (P<0.01). In both groups, the mean arterial pressure and heart rate at T3 and T4 were significantly higher than those at rest (P<0.05).</p><p><b>CONCLUSIONS</b>Small-dose dexmedetomidine infusion can reduce dysphoria and lower the risks during recovery from general anesthesia following vertebral operation.</p>