METHODOLOGICAL TRAINING OF FUTURE MASTER’S STUDENTS IN PSYCHOLOGY FOR SOCIAL SUPPORT FACILITATION DURING POST-TRAUMATIC INDIVIDUAL RECOVERY

This article substantiates a theoretical and methodological framework and proposes a practice-oriented toolkit for facilitating social support as a key resource for post-traumatic psychological recovery.The primary focus is on the professional training of Master's students in Psychology with a focus on developing specialized competencies aimed at restoring disrupted social networks and patterns of social support.The relevance of this study is shaped by the contemporary sociocultural context of Ukraine, where the mass disintegration of social ties due to armed conflict requires future psychologists to be capable of systemic design of environmental interventions.The theoretical section provides a detailed analysis of the "social erosion" model and S. E. Hobfoll's Conservation of Resources (COR) theory.Within this framework, social support is conceptualized as a dynamic buffer that protects personal resources from depletion and reduces the risk of PTSD chronicity.This study introduces an original vector model of social mapping, specifically adapted for Master's-level psychology curricula.This model offers an algorithmic approach to the diagnostics and correction of the client's social environment through four strategic vectors: 1) resource monitoring; 2) reconstructive search; 3) regulation of intensity; 4) quality correction.It is substantiated that the formation of the professional readiness of Master's students in psychology should be based on the step-by-step mastery of psychological assistance algorithms: the preparatory, diagnostic, interventional, and evaluative stages.Particular attention is paid to training future specialists in methods of neutralizing survivors' subjective barriers.The practical significance of the study is determined by the development and detailing of three strategic directions of psychological assistance: cognitivebehavioral, regulatory-emotional, and communicative-educational. The proposed algorithm directly corresponds to the requirements of the higher education