Psychology Research and Behavior Management (Mar 2024)

Attention-Dominated Cognitive Dysfunction May Be a Biological Marker for Distinguishing SA from SI in Adolescents: A Network Analysis Study Based on Adolescent Depression

  • Wang Q,
  • Wen M,
  • Fan S,
  • Liu J,
  • Wang X,
  • Guo W,
  • Hu J,
  • Zhang J,
  • Li B,
  • Zhang L,
  • Zhang Y,
  • Li K

Journal volume & issue
Vol. Volume 17
pp. 945 – 956

Abstract

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Qi Wang,1,2,* Min Wen,2,3,* Shaohang Fan,2,4 Jinning Liu,2 Xiaowen Wang,5 Wentao Guo,2 Jinyun Hu,6 Jialan Zhang,2 Bing Li,2,7 Lili Zhang,2,7 Yunshu Zhang,1,2,7 Keqing Li2,7 1Clinical Medicine College, Hebei University, Hebei, People’s Republic of China; 2Hebei Provincial Mental Health Center, Hebei, People’s Republic of China; 3Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan, People’s Republic of China; 4School of Psychology and Mental Health, North China University of Science and Technology, Tangshan, People’s Republic of China; 5Psychosomatic Medicine Department, Jiangxi Provincial People’s Hospital, Nanchang, People’s Republic of China; 6Psychiatric Department, The Second People’s Hospital of Yuxi, Yunnan, People’s Republic of China; 7Hebei Provincial Key Laboratory of Major Mental and Behavioral Disorders, Hebei, People’s Republic of China*These authors contributed equally to this workCorrespondence: Keqing Li, Hebei Provincial Mental Health Center, Hebei, People’s Republic of China, Email [email protected] Yunshu Zhang, Hebei Provincial Mental Health Center, Hebei, People’s Republic of China, Email [email protected]: Suicidal behavior is strongly correlated with depressive symptoms and the degree of suicidal ideation. Cognitive impairment may have varying degrees of influence on suicidal ideation (SI) and suicidal attempts (SA). The aim of this study was to identify the cognitive biomarkers that distinguish suicidal ideation from suicidal attempts in adolescents.Methods: The cross-sectional sample comprised 54 adolescents with major depressive disorder (MDD) and 32 healthy controls (HC). The THINC-it was utilized to assess cognitive function of all the samples. Suicidal ideation was examined by the Positive and Negative Suicide Ideation Scale (PANSI). Based on the type of data, one-way ANOVA or Kruskal–Wallis was performed to investigate group differences. Bonferroni post-hoc analysis was employed for regulating type I error for pairwise comparisons. Network analysis was used to compare the networks associated with suicidal ideation, depression symptoms, and cognitive function between SA and SI.Results: The depression symptoms (HAMD-17) (F=72.515, P< 0.001) and suicidal ideation (PANSI) (F=267.952, P< 0.001) in the SA were higher than those in the SI. Analysis of between-group differences showed SA performed worse in THINC-it, especially in “Spotter (SP)” (P=0.033), “Objective cognition score (OS)” (P=0.027) and “Composite score (CS)” (P=0.017). Compared with SI, network analysis revealed that SA had a unique network of cognitive function, depressive symptoms, and suicidal ideation. Nevertheless, both networks exhibit comparable performance concerning the node strength of cognitive function. Within their separate networks, the aspects of CS, OS, and SP have emerged as the three most crucial elements.Conclusion: Adolescents with SI or SA exhibit a broad spectrum of cognitive impairments. Attention impairment can be beneficial in discerning between SI and SA. Future interventions for adolescent suicide can center on attention and the comprehensive cognitive ability that it represents.Keywords: attention impairment, suicide ideation, suicide attempts, adolescent, THINC-it tool, network analysis

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