Summary
Previous research has investigated the relationship between unemployment and health from a perspective of an isolated individual. HEALFAM takes a novel approach and examines how transition to unemployment triggers diffusion of ill mental and physical health within families. It investigates how becoming unemployed affects health outcomes of partners, children and elderly parents of the unemployed and whether the magnitudes of these influences differ across families and societies. Thus, instead of viewing the unemployed as functioning in isolation, HEALFAM assesses the consequences of unemployment for family members taking a multi-actor perspective and international comparative approach.
Guided by the life course theoretical framework, which views health and well-being as a process rather than a state and calls for considering interrelatedness of individuals, HEALFAM employs longitudinal data that provide information about multiple members of families. In order to analyse these datasets, HEALFAM uses longitudinal dyadic data analysis techniques as well as multilevel models for longitudinal data.
HEALFAM aims to open a new frontline of research on health and wellbeing from a life course perspective. It benefits from my knowledge on three interrelated social phenomena: (1) the role of labour market career and experiences of unemployment (2) family structure and intra-family resources (3) social antecedents of health and wellbeing among family members. It draws on high quality register and panel survey data as well as the expertise at the interdisciplinary research centres that I am connected to at Umeå University. Through international collaborations, it brings together experts in multiple disciplines carrying out research taking a life course perspective.
Guided by the life course theoretical framework, which views health and well-being as a process rather than a state and calls for considering interrelatedness of individuals, HEALFAM employs longitudinal data that provide information about multiple members of families. In order to analyse these datasets, HEALFAM uses longitudinal dyadic data analysis techniques as well as multilevel models for longitudinal data.
HEALFAM aims to open a new frontline of research on health and wellbeing from a life course perspective. It benefits from my knowledge on three interrelated social phenomena: (1) the role of labour market career and experiences of unemployment (2) family structure and intra-family resources (3) social antecedents of health and wellbeing among family members. It draws on high quality register and panel survey data as well as the expertise at the interdisciplinary research centres that I am connected to at Umeå University. Through international collaborations, it brings together experts in multiple disciplines carrying out research taking a life course perspective.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/802631 |
| Start date: | 01-03-2019 |
| End date: | 31-12-2025 |
| Total budget - Public funding: | 1 477 556,25 Euro - 1 477 556,00 Euro |
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Original description
Previous research has investigated the relationship between unemployment and health from a perspective of an isolated individual. HEALFAM takes a novel approach and examines how transition to unemployment triggers diffusion of ill mental and physical health within families. It investigates how becoming unemployed affects health outcomes of partners, children and elderly parents of the unemployed and whether the magnitudes of these influences differ across families and societies. Thus, instead of viewing the unemployed as functioning in isolation, HEALFAM assesses the consequences of unemployment for family members taking a multi-actor perspective and international comparative approach.Guided by the life course theoretical framework, which views health and well-being as a process rather than a state and calls for considering interrelatedness of individuals, HEALFAM employs longitudinal data that provide information about multiple members of families. In order to analyse these datasets, HEALFAM uses longitudinal dyadic data analysis techniques as well as multilevel models for longitudinal data.
HEALFAM aims to open a new frontline of research on health and wellbeing from a life course perspective. It benefits from my knowledge on three interrelated social phenomena: (1) the role of labour market career and experiences of unemployment (2) family structure and intra-family resources (3) social antecedents of health and wellbeing among family members. It draws on high quality register and panel survey data as well as the expertise at the interdisciplinary research centres that I am connected to at Umeå University. Through international collaborations, it brings together experts in multiple disciplines carrying out research taking a life course perspective.
Status
SIGNEDCall topic
ERC-2018-STGUpdate Date
27-04-2024
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