ADAPTIVE PERFORMANCE ASSESSMENT AND EVIDENCE-BASED SCALING OF PUBLIC ADMINISTRATION FOR THE COMPREHENSIVE PSYCHOSOCIAL RECOVERY OF SERVICE MEMBERS AND VETERANS IN UKRAINE

Abstract

The article provides a theoretical and methodological justification for an adaptive performance-assessment model for public administration of the comprehensive psychosocial recovery of service members and veterans in Ukraine. The problem is considered as a public-governance task that extends beyond the delivery of individual medical, psychological or social services and requires the management of a continuous interagency pathway from needs assessment to functional, social and professional reintegration. The aim of the study is to define the architecture, performance domains, indicator rules, feedback procedures and evidence gates that can transform monitoring from a reporting function into an instrument for adaptive decision-making. The study applies systems, institutional and process approaches; normative and comparative analysis; theory-of-change logic; results-based management; indicator design; and structural-functional modelling. The proposed model distinguishes strategic, regional and operational levels of governance and links them through a common results chain: resources – processes – outputs – short-term outcomes – medium-term outcomes – long-term public value. Eight performance domains are defined: accessibility and timeliness; continuity of the individual pathway; service quality and rights protection; psychosocial and functional outcomes; family and social reintegration; professional and economic reintegration; governance capacity and data quality; equity and resilience. For operationalisation, each indicator is assigned an indicator passport containing its definition, formula, source, periodicity, disaggregation rules, responsible data owner, target range and predetermined management response. A normalised domain score is proposed for analytical comparison, while critical rights, safety or data-protection events operate as non-compensatory red flags and cannot be concealed by a high aggregate score. The model includes an adaptive loop linking data verification, problem detection, causal analysis, correction of objectives and mechanisms, implementation and repeated measurement. Evidence-based scaling is organised through five decision gates: readiness for piloting, early pilot, full pilot cycle, interregional replication and national institutionalisation. The scientific contribution lies in integrating person-centred outcome measurement, public-administration capacity, data governance and evidence-based scaling within a single adaptive architecture. The practical significance is the possibility of using the model for interagency programme management, regional comparison, evidence-informed budgeting, digital pathway design and the gradual institutionalisation of an integrated system of psychosocial recovery in Ukraine.

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