高中生抑郁症状及影响因素间的关系:基于相关和交叉滞后网络分析*

陈婷, 孙岩, 李睿, 王艺锦

心理科学 ›› 2025, Vol. 48 ›› Issue (5) : 1233-1245.

PDF(1673 KB)
中文  |  English
PDF(1673 KB)
心理科学 ›› 2025, Vol. 48 ›› Issue (5) : 1233-1245. DOI: 10.16719/j.cnki.1671-6981.20250518
新时代社会心理服务研究

高中生抑郁症状及影响因素间的关系:基于相关和交叉滞后网络分析*

  • 陈婷, 孙岩**, 李睿, 王艺锦
作者信息 +

The Relationship between Depressive Symptoms and Influencing Factors among High School Students: Based on Correlation and Cross-Lagged Panel Network Analysis

  • Chen Ting, Sun Yan, Li Rui, Wang Yijin
Author information +
文章历史 +

摘要

采用问卷法对1308名高中生的抑郁症状及影响因素进行调查,探究高中生抑郁症状及抑郁与影响因素间的关系,结果发现:(1)高中生抑郁的核心症状是悲伤、消沉、难以开始和孤独,核心症状在两次测量中结果一致;(2)失败感和不被喜欢是高中生抑郁的核心预测症状;(3)积极情绪调节自我效能感、灾难化、积极重新评价和核心自我评价是高中生抑郁的核心预测因素,理性分析是女性高中生特有的核心预测因素。表明高中生抑郁的核心症状具有可重复性,女性高中生抑郁的核心影响因素存在性别特异性。因此,在高中生抑郁的预防和干预中,需重点关注核心症状和核心影响因素,还应对女性高中生制定针对性的干预措施。

Abstract

For Chinese adolescents, the high school stage is a critical period for the onset of depression, and this trend has been worsening over the years. Exploring effective methods for prevention and intervention of depression among high school students is of utmost importance. In recent years, an increasing number of researchers have started to utilize network theory of mental disorder to study the internal symptoms of depression. However, there has been inconsistency in the conclusions drawn from network analysis on the core symptoms of adolescent depression in the past. These studies are based on cross-sectional data at a certain point in time and cannot reflect the changes in symptoms over time, leading to different inferences about the importance of symptoms. Therefore, further research on the replicability of the relevant network of depressive symptoms is needed to enhance the reliability of cross-sectional data inference. This study constructed a correlational network of depressive symptoms at two time points, compared the differences in network structure and global strength, and tested whether symptoms with high centrality are consistent across time.
Depression is regarded as a multifaceted and multi-pathway complex process, necessitating a comprehensive examination of its developmental traits based on both the symptoms and influencing factors of depression. This study is guided by an emotional regulation framework and extensive theoretical and empirical evidence. Trait mindfulness, regulatory emotional self-efficacy, emotional empathy, and core self-evaluation were identified from individual factors, while parent-child relationship and friendship quality were identified from situational factors. Cognitive emotion regulation strategies were identified as strategic factors influencing depression among high school students. In addition, compared with male adolescents, female adolescents have significantly higher incidence rates and severity of depression, and their depressive symptoms gradually increase. The severity of depression in female adolescents can persist into adulthood. Cross-lagged panel network analysis can reflect the developmental nature of individual psychological characteristics. This study uses the cross-lagged panel network analysis to explore the dynamic relationship between depressive symptoms and influencing factors in high school students, particularly female high school students.
This study used a cluster random sampling method to select first and second year high school students from two high schools in Dalian and Beipiao cities in Liaoning Province for longitudinal investigation. The two assessments were conducted with a 6-month interval. Ultimately, 1308 participants (585 boys and 723 girls) completed both assessments, aged 15 to 19 years, with an average age of 16.68±0.76 years. Data management, common method bias testing, and descriptive statistical analysis were conducted using SPSS. Correlation network analysis and cross-lagged panel network models were analyzed using R packages, following methodological guidelines developed by the researchers.
The network analysis of depressive symptoms at two time points indicates that sadness, depressed, could not get “going”, and loneliness are central symptoms within the network, representing the core symptoms of depression. There are no significant differences in network structure and global strength between the symptom networks at the two time points, and the importance of core symptoms remains unchanged. Therefore, there is cross-temporal consistency in the inference of core symptoms. The cross-lagged panel network analysis of depressive symptoms among overall high school students and female high school students shows that the core predictive symptoms of depression are both a sense of feelings of failure and unliked. The results of the depression influencing factors cross-lagged panel network analysis showed that self-efficacy in positive emotion regulation, catastrophizing, positive reappraisal, and core self-evaluation were the core influencing factors of depression in high school students. Rational analysis is a core influencing factor of depression unique to female high school students.
In theory, targeting core nodes in a network would most significantly influence the overall network structure, ensuring effective and cost-efficient intervention. In practical applications, we can design intervention strategies focused on the core symptoms and significant predictive factors of depression. It is also possible to intensify interventions targeting core symptoms and important predictive factors within existing intervention plans. Additionally, specialized intervention programs should be developed for female high school students.

关键词

高中生 / 抑郁 / 相关网络分析 / 交叉滞后网络分析

Key words

high school students / depression / correlation network analysis / cross-lagged panel network analyses

引用本文

导出引用
陈婷, 孙岩, 李睿, 王艺锦. 高中生抑郁症状及影响因素间的关系:基于相关和交叉滞后网络分析*[J]. 心理科学. 2025, 48(5): 1233-1245 https://doi.org/10.16719/j.cnki.1671-6981.20250518
Chen Ting, Sun Yan, Li Rui, Wang Yijin. The Relationship between Depressive Symptoms and Influencing Factors among High School Students: Based on Correlation and Cross-Lagged Panel Network Analysis[J]. Journal of Psychological Science. 2025, 48(5): 1233-1245 https://doi.org/10.16719/j.cnki.1671-6981.20250518

参考文献

[1] 蔡玉清, 董书阳, 袁帅, 胡传鹏. (2020). 变量间的网络分析模型及其应用. 心理科学进展, 28(1), 178-195.
[2] 陈琛, 王力, 曹成琦, 李根. (2021). 心理病理学网络理论、方法与挑战. 心理科学进展, 29(10), 1724-1739.
[3] 陈慧, 何婷, 唐远琼, 唐怡欣, 陆风勇, 蔺秀云. (2021). 共情与青少年内外化问题的关系及影响机制. 心理发展与教育, 37(3), 439-446.
[4] 陈祉妍, 杨小冬, 李新影. (2009). 流调中心抑郁量表在我国青少年中的试用. 中国临床心理学杂志, 17(4), 443-445.
[5] 杜建政, 张翔, 赵燕. (2012). 核心自我评价的结构验证及其量表修订. 心理研究, 5(3), 54-60.
[6] 傅小兰, 张侃, 陈雪峰, 陈祉妍. (2023). 中国国民心理健康发展报告(2021-2022). 社会科学文献出版社..
[7] 黄顺森, 罗玉晗, 来枭雄, 简可雯, 徐梓婧, 王耘. (2022). 中国青少年抑郁的核心症状及性别、抑郁程度间的比较:基于网络分析方法. 心理科学, 45(5), 1115-1122.
[8] 黄垣成, 赵清玲, 李彩娜. (2021). 青少年早期抑郁和自伤的联合发展轨迹:人际因素的作用. 心理学报, 53(5), 515-526.
[9] 侯金芹, 陈祉妍. (2016). 青少年抑郁情绪的发展轨迹: 界定亚群组及其影响因素. 心理学报, 48(8), 957-968.
[10] 胡义秋, 何震, 曾子豪, 詹林, 申自力. (2023). 亲子关系对青少年抑郁的影响:认知灵活性和友谊质量的作用. 中国临床心理学杂志, 31(3), 682-687.
[11] 李鹏, 刘霞, 孙炳海, 张文海, 李红. (2018). 青少年抑郁的快感缺失的神经机制研究. 心理发展与教育, 34(2), 239-248.
[12] 李荣, 王玉龙, 赵婧斐. (2023). 父母冲突和友谊质量对青少年抑郁发展趋势的影响. 中国临床心理学杂志, 31(2), 455-458.
[13] 梁一鸣, 郑昊, 刘正奎. (2020). 震后儿童创伤后应激障碍的症状网络演化. 心理学报, 52(11), 1301-1315.
[14] 刘晓凤, 迟新丽, 张洁婷, 段文杰, 温宗堃. (2019). 儿童青少年正念量表 (CAMM) 在中国青少年群体中的信效度检验. 心理学探新, 39(3), 250-256.
[15] 罗伏生, 王小凤, 张珊明, 沈丹. (2010).青少年情绪调节认知策略的特征研究. 中国临床心理学杂志, 18(1), 93-96.
[16] 孟昭兰. (1989). 人类情绪. 上海人民出版社..
[17] 人民日报, 健康时报. (2022). 《2022国民抑郁症蓝皮书》. http://www.jksb.com.cn/html/life/psychology/2022/0704/177205.html
[18] 王琼, 陈慧玲, 胡伟, 许存. (2022). 校园人际谣言对初中生抑郁的影响: 有调节的中介模型. 中国临床心理学杂志, 30(3), 595-599.
[19] 王玉龙, 李荣, 陈慧玲, 蔺秀云. (2025). 父母冲突对早期青少年自伤的影响:抑郁的纵向中介作用.心理发展与教育, 41(2), 276-283.
[20] 文书锋, 汤冬玲, 俞国良. (2009). 情绪调节自我效能感的应用研究. 心理科学, 32(3), 666-668.
[21] 谢敏, 李峰, 罗玉晗, 柯李, 王侠, 王耘. (2022). 小学教师职业倦怠维度发展顺序探究——来自结构方程模型和交叉滞后网络分析模型的证据. 心理学报, 54(4), 371-384.
[22] 谢韵梓, 吴继霞, 王诗成, 阳泽. (2022). 儿童期情感忽视对大学生抑郁的影响:控制感与情绪调节自我效能感的链式中介作用. 心理发展与教育, 38(3), 407-417.
[23] 徐子纯, 依拉木江·阿布都艾尼, 孙睿, 周宵. (2023). 大学生复杂性创伤后应激障碍的网络结构及其性别差异研究.心理科学, 46(4),1008-1016.
[24] 闫静怡, 张雪倩, 孙琦, 董一漩, 刘华清. (2022). 非适应性认知情绪调节策略对高中生抑郁的影响:经验回避和认知融合的链式中介作用. 中国临床心理学杂志, 30(6), 1303-1307.
[25] 颜志强, 曾晓, 祝寿, 陈露. (2022). 青少年情绪共情和抑郁的关系:羞耻倾向和心理弹性的链式中介作用. 中国临床心理学杂志, 30(1), 77-80.
[26] 杨之旭, 彭海云, 辛素飞. (2024). 疫情后期青少年的抑郁和焦虑变迁趋势及其潜在因果:一项追踪研究. 心理学报, 56(4),482-496.
[27] 于晓琪, 张亚利, 俞国良. (2022). 2010~2020中国内地高中生心理健康问题检出率的元分析. 心理科学进展, 30(5), 978-990.
[28] 张凤凤, 董毅, 汪凯, 詹志禹, 谢伦芳. (2010). 中文版人际反应指针量表(IRI-C)的信度及效度研究. 中国临床心理学杂志, 18(2), 155-157.
[29] 张锦涛, 刘勤学, 邓林园, 方晓义, 刘朝莹, 兰菁. (2011). 青少年亲子关系与网络成瘾: 孤独感的中介作用. 心理发展与教育, 27(6), 641-647.
[30] 张少华, 桑标, 潘婷婷, 刘影. (2022). 不同抑郁症状青少年调节不同强度情绪时策略选择的差异. 心理科学, 45(3), 574-583.
[31] 张野, 张珊珊, 孙冰如, 申婷. (2022). 初中生校园排斥对抑郁的影响:反刍思维与特质正念的作用. 心理科学, 45(3), 584-590.
[32] 曾子豪, 胡义秋, 刘双金, 彭丽仪, 杨琴, 王宏才, 何震, 姚星星. (2025). 学校人际关系与血清素系统多基因累积遗传风险对青少年抑郁的影响. 心理发展与教育,41(3), 436-447.
[33] 朱熊兆, 罗伏生, 姚树桥, Auerbach, R. P. & Abela, J. R. Z. (2007). 认知情绪调节问卷中文版(CERQ-C)的信效度研究. 中国临床心理学杂志, 15(2), 121-124.
[34] Alcalde E., Rouquette A., Wiernik E., & Rigal L. (2024). How do men and women differ in their depressive symptomatology? A gendered network analysis of depressive symptoms in a French population-based cohort. Journal of Affective Disorders, 353, 1-10.
[35] Bandura A., Caprara G. V., Barbaranelli C., Gerbino M., & Pastorelli C. (2003). Role of affective self-regulatory efficacy on diverse spheres of psychosocial functioning. Child Development, 74(3), 769-782.
[36] Bardeen, J. R., & Fergus, T. A. (2020). Emotion regulation self-efficacy mediates the relation between happiness emotion goals and depressive symptoms: A cross-lagged panel design. Emotion, 20(5), 910-915.
[37] Berking M., Wirtz C. M., Svaldi J., & Hofmann S. G. (2014). Emotion regulation predicts symptoms of depression over five years. Behaviour Research and Therapy, 57, 13-20.
[38] Berlim M. T., Richard-Devantoy S., Dos Santos N. R., & Turecki G. (2021). The network structure of core depressive symptom-domains in major depressive disorder following antidepressant treatment: A randomized clinical trial. Psychological Medicine, 51(14), 2399-2413.
[39] Bernasco E. L., Van der Graaff J., Meeus W. H., & Branje S. (2022). Peer victimization, internalizing problems, and the buffering role of friendship quality: Disaggregating between-and within-person associations. Journal of Youth and Adolescence, 51(8), 1653-1666.
[40] Borsboom, D. (2017). A network theory of mental disorders. World Psychiatry, 16(1), 5-13.
[41] Borsboom, D., & Cramer, A. O. (2013). Network analysis: An integrative approach to the structure of psychopathology. Annual Review of Clinical Psychology, 9(1), 91-121.
[42] Bringmann L. F., Albers C., Bockting C., Borsboom D., Ceulemans E., Cramer A., & Wichers M. (2022). Psychopathological networks: Theory, methods and practice. Behaviour Research and Therapy, 149, 104011.
[43] Buchnan C. M., Maccoby E. E., & Dornbush S. M. (1991). Caught between parents: Adolescents' experience in divorced homes. Child Development, 62(5), 1008-1029.
[44] Caprara G. V., Di Giunta L., Eisenberg N., Gerbino M., Pastorelli C., & Tramontano C. (2008). Assessing regulatory emotional self-efficacy in three countries. Psychological Assessment, 20(3), 227-237.
[45] Cheeta S., Beevers J., Chambers S., Szameitat A., & Chandler C. (2021). Seeing sadness: Comorbid effects of loneliness and depression on emotional face processing. Brain and Behavior, 11(7), e02189.
[46] Clark, D. A., & Beck, A. T. (2010). Cognitive theory and therapy of anxiety and depression: Convergence with neurobiological findings. Trends in Cognitive Sciences, 14(9), 418-424.
[47] Cox D. W., Kealy D., Kahn J. H., McCloskey K. D., Joyce A. S., & Ogrodniczuk J. S. (2020). Depressive symptoms’ impact on personality disorder treatment: Depressive symptoms amplifying the interpersonal benefits of negative-affect expression. Journal of Affective Disorders, 272, 318-325.
[48] Coyne J. C., Schwenk T. L., & Smolinski M. (1991). Recognizing depression: A comparison of family physician ratings, self-report, and interview measures. The Journal of the American Board of Family Practice, 4(4), 207-215.
[49] Cramer A. O., Van Borkulo C. D., Giltay E. J., Van Der Maas, H. L., Kendler K. S., Scheffer M., & Borsboom D. (2016). Major depression as a complex dynamic system. PLoS ONE, 11(12), e0167490.
[50] Cui D., Liu L., & Li Y. (2023). Association between children' s empathy and depression: The moderating role of social preference. Child Psychiatry and Human Development, 54(3), 857-869.
[51] D' Agostino A., Covanti S., Rossi Monti M., & Starcevic V. (2017). Reconsidering emotion dysregulation. Psychiatric Quarterly, 88, 807-825.
[52] Doré, B. P. Silvers, J. A., & Ochsner, K. N. (2016). Toward a personalized science of emotion regulation. Social and Personality Psychology Compass, 10(4), 171-187.
[53] Eisma, M. C., & Buyukcan-Tetik, A. (2025). Prolonged grief symptoms predict social and emotional loneliness and depressive symptoms. Behavior Therapy, 56(1), 121-132.
[54] Epskamp S., Borsboom D., & Fried E. I. (2018). Estimating psychological networks and their accuracy: A tutorial paper. Behavior Research Methods, 50(1), 195-212.
[55] Erzen, E., & Çikrikci, Ö. (2018). The effect of loneliness on depression: A meta-analysis. International Journal of Social Psychiatry, 64(5), 427-435.
[56] Forbes M. K., Wright A. G., Markon K. E., & Krueger R. F. (2017). Evidence that psychopathology symptom networks have limited replicability. Journal of Abnormal Psychology, 126(7), 969-988.
[57] Furman, W., & Buhrmester, D. (2009). Methods and measures: The network of relationships inventory: Behavioral systems version. International Journal of Behavioral Development, 33(5),470-478.
[58] Garnefski N., Kraaij V., & Spinhoven P. (2001). Negative life events, cognitive emotion regulation and emotional problems. Personality and Individual differences, 30(8), 1311-1327.
[59] Gijzen M. W., Rasing S. P., Creemers D. H., Smit F., Engels R. C., & De Beurs D. (2021). Suicide ideation as a symptom of adolescent depression. A network analysis. Journal of Affective Disorders, 278, 68-77.
[60] Gossage L., Narayanan A., Dipnall J. F., Iusitini L., Sumich A., Berk M., Wrapson W., Tautolo, E. & Siegert, R. (2022). Risk factors for depression in Pacific adolescents in New Zealand: A network analysis. Journal of Affective Disorders, 311, 373-382.
[61] Greco L. A., Baer R. A., & Smith G. T. (2011). Assessing mindfulness in children and adolescents: Development and validation of the Child and Adolescent Mindfulness Measure (CAMM). Psychological Assessment, 23(3), 606-614.
[62] Hankin B. L., Young J. F., Abela J. R., Smolen A., Jenness J. L., Gulley L. D., & Oppenheimer C. W. (2015). Depression from childhood into late adolescence: Influence of gender, development, genetic susceptibility, and peer stress. Journal of Abnormal Psychology, 124(4), 803-816.
[63] Henkel V., Bussfeld P., Möller H. J., & Hegerl U. (2002). Cognitive-behavioural theories of helplessness/hopelessness: Valid models of depression? European Archives of Psychiatry and Clinical Neuroscience, 252, 240-249.
[64] Hoffmann F., Banzhaf C., Kanske P., Gärtner M., Bermpohl F., & Singer T. (2016). Empathy in depression: Egocentric and altercentric biases and the role of alexithymia. Journal of Affective Disorders, 199, 23-29.
[65] Hofmann S. G., Curtiss J., & McNally R. J. (2016). A complex network perspective on clinical science. Perspectives on Psychological Science, 11(5), 597-605.
[66] Huang Y. H., Hu H. X., Wang L. L., Zhang Y. J., Wang X., Wang Y., & Chan R. C. (2023). Relationships between childhood trauma and dimensional schizotypy: A network analysis and replication. Asian Journal of Psychiatry, 85, 103598.
[67] Ingram R. E., Miranda J., & Segal Z. (2006). Cognitive vulnerability to depression. In Cognitive Vulnerability to Emotional Disorders (pp. 73-102). Routledge.
[68] Iovoli F., Hall M., Nenadic I., Straube B., Alexander N., Jamalabadi H., & Rubel J. A. (2024). Exploring the complex interrelation between depressive symptoms, risk, and protective factors: A comprehensive network approach. Journal of Affective Disorders, 355, 12-21.
[69] Jones P. J., Heeren A., & McNally R. J. (2017). Commentary: A network theory of mental disorders. Frontiers in Psychology, 8, 1305.
[70] Kalajas-Tilga H., Koka A., Hein V., Tilga H., & Raudsepp L. (2020). Motivational processes in physical education and objectively measured physical activity among adolescents. Journal of Sport and Health Science, 9(5), 462-471.
[71] Kim D., Wang R., Kiss A., Bronskill S. E., Lanctot K. L., Herrmann N., & Gallagher D. (2020). Depression and increased risk of Alzheimer' s dementia: Longitudinal analyses of modifiable risk and sex - related factors: Developing topics. Alzheimer's and Dementia, 16(S10), e047436.
[72] Kuehner, C. (2003). Gender differences in unipolar depression: An update of epidemiological findings and possible explanations. Acta Psychiatrica Scandinavica, 108(3), 163-174.
[73] Luan, Z., & Bleidorn, W. (2020). Self-other personality agreement and internalizing problems in adolescence. Journal of Personality, 88(3), 568-583.
[74] Marchetti I., Pössel P., & Koster E. H. (2021). The architecture of cognitive vulnerability to depressive symptoms in adolescence: A longitudinal network analysis study. Research on Child and Adolescent Psychopathology, 49, 267-281.
[75] McNally R. J., Robinaugh D. J., Wu G. W., Wang L., Deserno M. K., & Borsboom D. (2015). Mental disorders as causal systems: A network approach to posttraumatic stress disorder. Clinical Psychological Science, 3(6), 836-849.
[76] Mullarkey M. C., Marchetti I., & Beevers C. G. (2019). Using network analysis to identify central symptoms of adolescent depression. Journal of Clinical Child and Adolescent Psychology, 48(4), 656-668.
[77] Murri M. B., Caruso R., Christensen A. P., Folesani F., Nanni M. G., & Grassi L. (2023). The facets of psychopathology in patients with cancer: Cross-sectional and longitudinal network analyses. Journal of Psychosomatic Research, 165, 111139.
[78] Nieto-Casado F. J., Antolín-Suárez L., Rodríguez-Meirinhos A., & Oliva A. (2022). Effect of parental competences on anxious-depressive symptoms and suicidal ideation in adolescents: Exploring the mediating role of mindfulness. Children and Youth Services Review, 138, 106526.
[79] OECD. (2019). PISA 2018 results (Volume III): What school life means for students' lives. OECD Publishing.
[80] Panayiotou M., Black L., Carmichael-Murphy P., Qualter P., & Humphrey N. (2023). Time spent on social media among the least influential factors in adolescent mental health: Preliminary results from a panel network analysis. Nature Mental Health, 1(5), 316-326.
[81] Parhiala P., Torppa M., Vasalampi K., Eklund K., Poikkeus A. M., & Aro T. (2018). Profiles of school motivation and emotional well-being among adolescents: Associations with math and reading performance. Learning and Individual Differences, 61, 196-204.
[82] Pössel P., Burton S. M., Cauley B., Sawyer M. G., Spence S. H., & Sheffield J. (2018). Associations between social support from family, friends, and teachers and depressive symptoms in adolescents. Journal of Youth and Adolescence, 47, 398-412.
[83] Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385-401.
[84] Ratcliffe, M. (2018). The interpersonal structure of depression. Psychoanalytic Psychotherapy, 32(2), 122-139.
[85] Rottenberg J., Gross J. J., Wilhelm F. H., Najmi S., & Gotlib I. H. (2002). Crying threshold and intensity in major depressive disorder. Journal of Abnormal Psychology, 111(2), 302.
[86] Rubin M., Bicki A., Papini S., Smits J. A., Telch M. J., & Gray J. S. (2021). Distinct trajectories of depressive symptoms in early and middle adolescence: Preliminary evidence from longitudinal network analysis. Journal of Psychiatric Research, 142, 198-203.
[87] Santos Jr H., Fried E. I., Asafu-Adjei J., & Ruiz R. J. (2017). Network structure of perinatal depressive symptoms in Latinas: Relationship to stress and reproductive biomarkers. Research in Nursing and Health, 40(3), 218-228.
[88] Segal, Z. V. (1988). Appraisal of the self-schema construct in cognitive models of depression. Psychological Bulletin, 103(2), 147-162.
[89] Shaw, S. K., & Dallos, R. (2005). Attachment and adolescent depression: The impact of early attachment experiences. Attachment and Human Development, 7(4), 409-424.
[90] Simione L., Raffone A., & Mirolli M. (2021). Acceptance, and not its interaction with attention monitoring, increases psychological well-being: Testing the monitor and acceptance theory of mindfulness. Mindfulness, 12, 1398-1411.
[91] Smith-Adcock, S., & Kerpelman, J. L. (2022). Interpersonal stress, interpersonal competence, and gender matter for adolescents' depressive symptoms: Considerations for counselors. Journal of Counseling and Development, 100(1), 64-74.
[92] Song L., Fang P., Jiang Z., Li S., Song X., & Wan Y. (2022). Mediating effects of parent-child relationship on the association between childhood maltreatment and depressive symptoms among adolescents. Child Abuse and Neglect, 131, 105408.
[93] Swann Jr W. B., Chang-Schneider C., & Larsen McClarty K. (2007). Do people's self-views matter? Self-concept and self-esteem in everyday life. American Psychologist, 62(2), 84-94.
[94] Thoits, P. A. (1995). Stress, coping, and social support processes: Where are we? What next? Journal of Health and Social Behavior, 36, 53-79.
[95] Wasil A. R., Venturo-Conerly K. E., Shinde S., Patel V., & Jones P. J. (2020). Applying network analysis to understand depression and substance use in Indian adolescents. Journal of Affective Disorders, 265, 278-286.
[96] Watson R., Harvey K., McCabe C., & Reynolds S. (2020). Understanding anhedonia: A qualitative study exploring loss of interest and pleasure in adolescent depression. European Child and Adolescent Psychiatry, 29, 489-499.
[97] Wolpert, L. (2008). Depression in an evolutionary context. Philosophy, Ethics, and Humanities in Medicine, 3, 1-3.
[98] Ydhag C. C., Månsson N., & Osman A. (2021). Momentums of success, illusio and habitus: High-achieving upper secondary students' reasons for seeking academic success. International Journal of Educational Research, 109, 101805.
[99] Zagaria A., Vacca M., Cerolini S., Terrasi M., Bacaro V., Ballesio A., Baglion C., Spinhoven P., & & Lombardo C. (2023). Differential associations of cognitive emotion regulation strategies with depression, anxiety, and insomnia in adolescence and early adulthood. International Journal of Environmental Research and Public Health, 20(10), 5857.
[100] Zimmerman M., Ellison W., Young D., Chelminski I., & Dalrymple K. (2015). How many different ways do patients meet the diagnostic criteria for major depressive disorder? Comprehensive Psychiatry, 56, 29-34.
[101] Zou S., Song X., Tan W., Deng F., Zhang H., Xu H., .. & Yin L. (2022). Core self-evaluation as mediator between depressive symptoms and suicidal ideation in adolescents. Journal of Affective Disorders, 302, 361-366.

基金

*本研究得到国家社会科学基金教育学一般课题(BHA220134)的资助

PDF(1673 KB)

评审附件

Accesses

Citation

Detail

段落导航
相关文章

/