Sense of meaning in life, self-acceptance, and prosocial behavior: an application of network analysis methods.

Objective: To explore the characteristics and core items of the network structure between school students' sense of meaning in life, self-acceptance, and prosocial behavior, and to provide a basis for understanding the relationship between their sense of meaning in life, self-acceptance and prosocial behavior and related interventions.

Methods: A survey of 1232 school students was conducted using the Self-Acceptance Scale, the prosocial Behavior Scale, and the Sense of Meaning of Life Scale. Network analysis was used to construct the network of prosocial behavior, self-acceptance, and sense of the meaning of life among school students, and the software R was used for statistical analysis and visualization.

Results: In the regularized bias correlation network of self-acceptance, prosocial behavior, and sense of meaning in life among school students, self-acceptance and self-appraisal, having meaning and self-appraisal, anonymity and altruism had the strongest correlation; emotionality, altruism, and urgency had the highest expected impact; and having meaning and self-appraisal had the highest expected impact of the bridge.

Conclusion: Self-acceptance, meaning in life, and prosocial behavior are interrelated; interventions targeting emotionality, altruism, and urgency in the prosocial behavior dimensions may maximize prosocial behavioral effects among college students.