Abstract: This paper addresses persistent structural deficiencies in China's psychological crisis intervention system for public emergencies, particularly fragmented inter-departmental coordination, inadequate risk identification, weak plan-execution linkages, and the absence of long-term evaluation, and proposes an integrated theoretical and operational framework for system optimization in the digital-intelligent era. Beyond synthesizing existing policy experiences, the paper makes three principal innovative contributions.
First, from a research perspective, the paper systematically introduces the Disaster Management Cycle (DMC) theory, comprising the four interconnected phases of prevention, preparedness, response, and recovery, into the analysis of China's psychological crisis intervention system, and adapts the framework to Chinese institutional realities. Rather than treating crisis intervention as a series of event-driven actions, the framework conceptualizes it as a continuous, self-iterating cycle in which experiences and evaluation outcomes from each phase feed forward into the next, enabling sustained system improvement. This shifts the analytical lens from isolated process optimization toward a holistic structural understanding of crisis governance.
Second, in terms of theoretical mechanism, the paper proposes that the effective functioning of the system depends on three structural capacities, that is, institutionalization, cross-sectoral coordination, and digital-intelligent empowerment, and systematically maps them onto the four DMC phases, producing a 3 × 4 analytical matrix that specifies their differentiated roles. In the prevention phase, institutionalization clarifies risk-monitoring responsibilities and data governance standards; coordination links education, medical, and community systems; and digital-intelligent technologies enable multi-source data integration and AI-driven risk surveillance. In the preparedness phase, institutionalization mandates psychological intervention as a routinized component of emergency management; coordination builds multi-stakeholder service networks; and digital platforms convert paper-based plans into executable workflows with intelligent resource allocation. The response phase requires unified command structures, professional accreditation standards, and intelligent assessment-and-dispatch systems supporting tiered triage. The recovery phase emphasizes sustained funding mechanisms, integrated long-term support networks, and digital databases enabling continuous outcome evaluation.
Building on this matrix, the paper introduces a “technology-institution co-evolutionary mechanism” as its central theoretical contribution. Departing from prevailing views that treat digital-intelligent technology as a discrete efficiency tool, the paper argues that digital-intelligent capacity functions effectively only when embedded within institutional norms and coordination structures, while simultaneously transforming those very arrangements. Data accumulated and evidence-based evaluations generated in the recovery phase feed back through institutional channels into the prevention and preparedness phases, completing a “data collection-effectiveness assessment-institutional optimization” loop. This reframes digital-intelligent technology from an efficiency aid into a structural driver capable of dissolving administrative silos and reconfiguring interdepartmental collaboration.
Third, in model construction, the paper proposes an “optimization pathway model for the digital-intelligent psychological crisis intervention system”, which integrates institutional rules, organizational coordination, and technological capacity into a dynamic four-phase loop. The model offers both an analytical framework for understanding long-term system operation and actionable guidance for empirical research and policy practice.
The paper makes four additional substantive contributions. (1) It diagnoses stage-specific bottlenecks in China's current system: cross-departmental data fragmentation in prevention, plan-execution gaps in preparedness, multi-headed management in response, and resource-trauma temporal mismatches in recovery. (2) It explicitly addresses governance risks accompanying digital-intelligent transformation, privacy and data security, algorithmic misjudgment and accountability allocation, the digital divide, and online intervention ethics, arguing that such risks should be institutionally absorbed through stage-differentiated regulatory rules rather than left to technical solutions alone. (3) It emphasizes cultural adaptability, contending that algorithmic design must incorporate China's collectivist orientation, family-centered structure, and indigenous help-seeking patterns to achieve genuine usability and cultural sensitivity. (4) It proposes a multi-stakeholder governance structure incorporating individuals, families, communities, and social organizations across all four phases, supplementing the top-down government-and-professional model and fostering a more resilient social-psychological support community.
By systematically integrating institutional rules, organizational coordination, and technological capacity within a dynamic four-phase loop, this paper advances both theoretical understanding and practical guidance for psychological crisis governance. It provides a coherent reference for transforming China's psychological crisis intervention system from event-driven to normalized operation, from short-term intervention to long-term support, and from experience-based to data-driven decision-making. The paper contributes a Chinese perspective to international research on disaster mental health systems and offers a transferable analytical framework for other countries navigating similar challenges in digital-era public mental health governance.

Key words: public emergencies, psychological crisis intervention system, digital and intelligent technologies, public mental health