Abstract: The aging population is increasing rapidly worldwide, particularly in China, leading to a growing number of disabled elderly individuals with complex and dynamic psychological needs. Traditional psychological care models, which are often static, are inadequate to address these evolving and individualized needs. The present research proposes a novel framework for identifying and addressing the psychological needs of disabled elderly individuals, focusing on dynamic resource allocation, personalized care, and real-time feedback mechanisms. The goal is to optimize service delivery by continuously adapting to the changing psychological needs of elderly individuals, ensuring the efficient and effective use of resources.
The study adopts a mixed-methods approach, combining both qualitative and quantitative research methodologies to provide a comprehensive understanding of the psychological needs of disabled elderly individuals. The research design involves conducting in-depth interviews with elderly individuals, their caregivers, and healthcare providers. Additionally, surveys are carried out to assess various psychological needs, including emotional support, social interaction, spiritual comfort, and psychological counseling. Standardized psychological assessment tools, such as the Geriatric Depression Scale (GDS) and WHOQOL-OLD, were utilized to measure mental health and emotional distress. This comprehensive data collection approach enables the creation of personalized care profiles for each participant based on their unique psychological and social needs.
The research seeks to test several hypotheses. First, it hypothesizes that personalized psychological support services, which dynamically adjust based on real-time data, will significantly improve the mental health and well-being of elderly individuals. Second, it is proposed that integrating real-time feedback mechanisms into service delivery will enhance the responsiveness and effectiveness of psychological support, ensuring that services are continuously aligned with the evolving needs of the elderly. Third, the study investigates whether multi-stakeholder collaboration—including healthcare providers, family caregivers, and community resources—can lead to more effective, equitable, and holistic care for disabled elderly individuals.
To achieve these goals, we created personalized care profiles for each participant, identifying their unique psychological needs and adjusting interventions accordingly. The study also designed a dynamic feedback model that continuously adjusts resource allocation based on assessments of health status, social interaction, and psychological well-being. This feedback mechanism ensures that psychological support services are continuously aligned with the individual’s needs, providing adaptive and responsive care.
In addition to real-time data collection, the study incorporated a longitudinal design to track the long-term impact of dynamic, personalized care on mental health and quality of life. By monitoring participants' progress over time, the research can assess whether ongoing adjustments to care plans result in improved overall well-being.
The study also focuses on theoretical innovations that contribute to advancing the field of elderly care. These innovations include the development of four core theories: Dynamic Needs Hierarchy Theory, Resource Precision Matching Theory, Closed-loop Feedback Optimization Theory, and System Collaborative Optimization Theory. Each theory addresses specific challenges in providing psychological care to disabled elderly individuals, particularly in ensuring that care is personalized, dynamic, and collaborative.
Dynamic Needs Hierarchy Theory extends traditional models by proposing that psychological needs are not fixed but fluctuate depending on various factors such as health, family support, and social circumstances. This theory offers a more adaptable approach to care, recognizing the need for flexibility in addressing changing psychological priorities. Resource Precision Matching Theory introduces an approach for precisely allocating psychological resources based on the intensity and urgency of individual needs. By matching resources with the specific requirements of elderly individuals, this theory ensures that services are delivered efficiently and equitably, particularly for vulnerable populations. Closed-loop Feedback Optimization Theory emphasizes the use of dynamic feedback loops to continuously adjust care plans based on real-time assessments of the elderly's needs, improving the efficiency and responsiveness of psychological support services. Lastly, System Collaborative Optimization Theory highlights the importance of multi-stakeholder collaboration, ensuring that psychological care involves coordinated efforts from healthcare providers, families, and communities to deliver comprehensive and equitable care.
In conclusion, this study presents an innovative framework for identifying and addressing the psychological needs of disabled elderly individuals. By integrating dynamic feedback mechanisms, personalized care, and multi-stakeholder collaboration, the framework provides a flexible and adaptive approach to psychological support. The research also introduces several theoretical innovations that advance the field of elderly care, offering new insights into the dynamic, personalized, and collaborative nature of care. This framework has the potential to significantly improve the quality of life and mental health of elderly individuals, especially the disabled. Moreover, it can be applied to enhance elderly care systems globally.

Key words: disabled older adults, psychological support needs, dynamic feedback, resource allocation, need adaptation