Published January 1, 2025 | Version v1
Journal article Open

The effect of social support provided to poor children on their emotional state and hope levels

  • 1. Hitit Univ, Iskilip Vocat Sch, Iskilip, Corum, Turkiye
  • 2. Hitit Univ, Fac Nursing, Corum, Turkiye

Description

Introduction: The aim of the study is to determine the effect of social support provided to children living in poverty aged 8-12 on their emotional states and levels of hope. Methods: This quasi-experimental study compares data obtained from the children in the "first encounter", "first month" and "third month". Data were collected in person through the "Introductory Information Form", "Multidimensional Scale of Perceived Social Support", "Children's Emotion Regulation Scale" and "Children's Hope Scale". p <0.05 was considered statistically significant. Results: Statistically, the comparison of the total mean scores of the children on the "Multidimensional Scale of Perceived Social Support" was highly significant (p <= 0.001). The comparison of the total mean scores of the "Children's Emotion Regulation Scale" was statistically significant (p <= 0.021). The comparison of the total average scores of the children's "Child Hope Scale" was statistically highly significant (p <= 0.001). A positive relationship was found between the children's hope levels and emotional states and the average scores obtained in the 3rd month (p = 0.044). Conclusion: The children's average scores on the scales increased after the first encounter. Providing social support positively affected children living in poverty. Implications to practice: Implications to practice: Providing social support to children in poverty positively impacts their emotional states and hope levels, emphasizing the crucial role of healthcare professionals, particularly pediatric nurses, in addressing the needs of vulnerable populations. These findings align with global health goals, such as "No Poverty" and "Good Health and Well-Being." (c) 2025 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

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