Background <p>As the number of single-parent families continues to rise, concerns about the mental health of children in these families have grown. Network theory offers a novel approach to understanding and intervening in cases of depression by examining the interconnections among depressive symptoms. This study aims to explore the differences in depressive symptom networks between children from two-parent and single-parent families at the symptom level using network analysis.</p> Methods <p>This study was conducted from September to October 2022 in Nanchong, Sichuan Province, China. The survey data were collected from 49,109 upper elementary school students as part of a universal screening program. Depressive symptoms were assessed using the Center for Epidemiological Studies Depression Scale (CES-D). Using the <i>NetworkComparisonTest</i> (NCT), the CES-D networks were compared between children from two-parent and single-parent families, as well as between single-father and single-mother families.</p> Results <p>In the depression symptom networks of children from two-parent and single-parent families, <i>Sad</i> (Strength = 1.10) was the most central symptom in two-parent family networks, whereas <i>Not enjoying life</i> (Strength = 1.20) was the most central symptom in single-parent families. Network connections were denser in single-parent families than in two-parent families (global strength: S = 8.50 vs. 8.11,&#xa0;<i>p</i> = 0.02). <i>Restless sleep</i> had higher strength centrality in single-parent families than in two-parent families (strength difference = 0.12<i>, p</i>.<sub>adjust</sub> = 0.01). However, global strength and structure did not differ between single-father and single-mother networks.</p> Conclusion <p>These findings provide deeper insights into the structure of depressive symptoms among children from single-parent families. Targeting central symptoms in interventions may offer new strategies for preventing depression in this population.</p>

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A large-sample (N = 49,109) network analysis of depressive symptoms in children from single-parent and two-parent families

  • Yujia Liao,
  • Xiangyu Deng,
  • Jie Gong,
  • Yao Peng,
  • Xianyong An,
  • Qianyu Zhang,
  • Xuerong Liu,
  • Xiaobing Tian

摘要

Background

As the number of single-parent families continues to rise, concerns about the mental health of children in these families have grown. Network theory offers a novel approach to understanding and intervening in cases of depression by examining the interconnections among depressive symptoms. This study aims to explore the differences in depressive symptom networks between children from two-parent and single-parent families at the symptom level using network analysis.

Methods

This study was conducted from September to October 2022 in Nanchong, Sichuan Province, China. The survey data were collected from 49,109 upper elementary school students as part of a universal screening program. Depressive symptoms were assessed using the Center for Epidemiological Studies Depression Scale (CES-D). Using the NetworkComparisonTest (NCT), the CES-D networks were compared between children from two-parent and single-parent families, as well as between single-father and single-mother families.

Results

In the depression symptom networks of children from two-parent and single-parent families, Sad (Strength = 1.10) was the most central symptom in two-parent family networks, whereas Not enjoying life (Strength = 1.20) was the most central symptom in single-parent families. Network connections were denser in single-parent families than in two-parent families (global strength: S = 8.50 vs. 8.11, p = 0.02). Restless sleep had higher strength centrality in single-parent families than in two-parent families (strength difference = 0.12, p.adjust = 0.01). However, global strength and structure did not differ between single-father and single-mother networks.

Conclusion

These findings provide deeper insights into the structure of depressive symptoms among children from single-parent families. Targeting central symptoms in interventions may offer new strategies for preventing depression in this population.