Objective:To analyze the influencing factors for depression in primary school children aged 9-10 years in Jiangsu Province, and to construct a risk prediction model.Methods:A retrospective study.A total of 1 162 primary school children aged 9-10 years from 3 primary schools in 3 regions of Jiangsu Province were recruited.Their demographic data were collected, and they were surveyed by the Depression Anxiety Stress Scales-21 (DASS-21), the Strengths and Difficulties Questionnaire (SDQ), and the Family Environment Scale (FES). Children were divided into control group (1 059 cases) and depression group (103 cases) based on the depression scores obtained from the DASS-21 scale.Multivariate Logistic regression analysis was used to analyze the influencing factors for depression in primary school students aged 9-10 and construct a risk prediction model. Results:There were significant differences in the economic development region, physical activities, academic performance, student cadres, parents′ education level, frequency of parental quarrels, SDQ and FES dimension scores between control group and depression group (all P<0.05). Among them, economic development areas (Northern Jiangsu and Southern Jiangsu), student cadres, father′s education level (elementary school and below) and intimacy of the FES scale were protective factors for depression in elementary school children; while emotional symptoms, peer problems and the total difficulty score in the SDQ scale, and the conflict in the FES scale were the risk factors for depression in elementary school children.The prediction model was created based on the influencing factors: Logit ( P)=-1.390×economic development area (Northern Jiangsu) -1.508×economic development area (Southern Jiangsu) -1.248×student cadres -2.206×father′s education level (primary school and below) -1.145×father′s education level (junior high school)+ 3.316×emotional symptoms in the SDQ+ 0.979×peer problems in the SDQ+ 2.520×total difficulty score in the SDQ -1.697×cohesion in the FES + 0.760×conflict in the FES -0.678.The area under the curve of receiver operating characteristic was 0.931, with the sensitivity and specificity of 85.42% and 91.83%, respectively. Conclusions:The regional level of economic development, class or school cadres, father′s education level, peer problems, total difficulty score, cohesion and conflict in the family are influencing factors for depression among primary school children aged 9-10 years in Jiangsu Province.The created prediction model can effectively assess the depressive risk factors in this population, which is conductive to achieve the early recognition and intervention of depression in them.

Objective:To explore the speech features of female patients with anhedonic depression and their recognition of pleasure deficient symptoms.Methods:A total of 102 female depression patients who were hospitalized at Nanjing Brain Hospital from September 2020 to October 2021 were selected, including 62 anhedonic depression patients (anhedonic group) and 40 non-anhedonic depression patients (non-anhedonic group). A total of 50 female healthy controls were recruited during the same period.All participants were evaluated by the 17-item Hamilton depression scale (HAMD-17), Snaith-Hamilton pleasure scale (SHAPS), and the temporal experience of pleasure scale (TEPS), as well as voice acquisition.SPSS 23.0 software was used for data processing.Statistical analysis was conducted using one-way ANOVA, non-parametric tests, Logistic regression, and receiver operating characteristic curve.Results:Compared with the non-anhedonic group, the anhedonic group showed significant changes in 15 voice features(all P<0.05), including Mel-frequency cepstral coefficients, formant frequencies, intensity, and energy features.Among these features, Mel-frequency cepstral coefficients exhibited the highest accuracy in identifying anhedonic depression, with sensitivity of 47.5%, specificity of 91.9%, area under curve (AUC) of 0.751, 95% CI=0.686-0.866.Formant frequencies could identify female anhedonic depression, with a sensitivity of 90.0%, a specificity of 40.3%, an AUC of 0.647, and 95% CI=0.605-0.824.Energy features could identify anhedonic deficient depression, with a sensitivity of 60.0%, a specificity of 74.2%, an AUC of 0.679, and 95% CI=0.587-0.804.Intensity features could identify female anhedonic depression, with a sensitivity of 70.0%, a specificity of 58.1%, an AUC of 0.640, and 95% CI=0.554-0.769. Conclusion:Mel-frequency cepstral coefficients, formant frequencies, intensity features, and energy features may have specific changes in female patients with anhedonic depression.The Mel-frequency cepstral coefficients has the highest recognition accuracy for anhedonic symptoms in female depression patients, and is expected to become an objective evaluation index for female anhedonic depression.