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Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
Published on: May 31, 2019
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Modelling social care provision in an agent-based framework with kinship networks
Umberto Gostoli1, Eric Silverman1
1MRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Glasgow G2 3AX, UK.
Royal Society Open Science
|August 17, 2019
Summary
UK
Area of Science:
- Social Sciences
- Demography
- Gerontology
Background:
- The UK faces rising demand for aged social care due to demographic shifts: an aging population and declining birth rates.
- Informal care networks, typically provided by family and friends, currently supply approximately 50% of care in the UK.
- Concerns exist regarding future care availability, potentially necessitating significant public investment in formal care services.
Purpose of the Study:
- To develop and present an agent-based simulation model for social care provision in the UK.
- To explore how individual agent decisions influence overall care availability and need.
- To analyze the impact of demographic trends on social care provision.
Main Methods:
- An agent-based simulation was created to model social care provision.
- Agents make decisions on providing informal care or purchasing private care based on personal factors.
- Factors influencing agent decisions include health, employment, finances, relationship, and location.
Main Results:
- The simulation successfully replicated real-world patterns of care need and availability.
- The model demonstrates the complex interplay of individual choices and demographic pressures on care provision.
- Kinship networks and socioeconomic details were crucial in distributing care effectively within the simulation.
Conclusions:
- Agent-based modeling offers a robust method for understanding the complexities of social care provision.
- The simulation highlights the potential strain on informal care systems due to UK demographic trends.
- Future policy considerations should account for the intricate dynamics of individual care decisions and network structures.
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