Summary
Older adults’ daily experiences were shown to be detrimental to their Successful Ageing. Empirical studies demonstrate that the type and quality of daily activities are constitutive for senior citizens' Quality of Life, and for how many more years they would like to live. Meanwhile, there are very few studies collecting data on daily activities from respondents aged 65+. Even fewer collect information on respondent’s evaluation of these activities. This project aims to give voice to the respondents by collecting data on everyday events and their subjective perception by individuals aged 65+. It will use a time-use approach, i.e, Experience Sampling Method (ESM) including important methodological innovations. Three algorithms will be used to collect different but compatible sets of time-based data and allow for comparative analyses between them. Data collection will take one week per person and each individual will provide information on 15-50 time-points. First algorithm will use classic ESM approach to provide information on how events are plotted across the day and the week, and how wellbeing fluctuates depending on time and day. Second algorithm will allow respondents recording events which are meaningful to them and most detrimental to their wellbeing. Third algorithm will provide information on events considered essential for how a day is structured. Altogether the three datasets will be used to answer questions about the dynamics of elderly’s days, how they experience different activities and how these experiences affect their wellbeing and quality of life. We aim at promoting this project as bringing essential new knowledge not only for policy-makers but also for practitioners and elderly individuals themselves. Along with scientific publications, easy-to-understand brochures including main findings and recommendations will be made available online.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/840113 |
| Start date: | 01-08-2019 |
| End date: | 31-07-2021 |
| Total budget - Public funding: | 186 167,04 Euro - 186 167,00 Euro |
Cordis data
Original description
Older adults’ daily experiences were shown to be detrimental to their Successful Ageing. Empirical studies demonstrate that the type and quality of daily activities are constitutive for senior citizens' Quality of Life, and for how many more years they would like to live. Meanwhile, there are very few studies collecting data on daily activities from respondents aged 65+. Even fewer collect information on respondent’s evaluation of these activities. This project aims to give voice to the respondents by collecting data on everyday events and their subjective perception by individuals aged 65+. It will use a time-use approach, i.e, Experience Sampling Method (ESM) including important methodological innovations. Three algorithms will be used to collect different but compatible sets of time-based data and allow for comparative analyses between them. Data collection will take one week per person and each individual will provide information on 15-50 time-points. First algorithm will use classic ESM approach to provide information on how events are plotted across the day and the week, and how wellbeing fluctuates depending on time and day. Second algorithm will allow respondents recording events which are meaningful to them and most detrimental to their wellbeing. Third algorithm will provide information on events considered essential for how a day is structured. Altogether the three datasets will be used to answer questions about the dynamics of elderly’s days, how they experience different activities and how these experiences affect their wellbeing and quality of life. We aim at promoting this project as bringing essential new knowledge not only for policy-makers but also for practitioners and elderly individuals themselves. Along with scientific publications, easy-to-understand brochures including main findings and recommendations will be made available online.Status
CLOSEDCall topic
MSCA-IF-2018Update Date
28-04-2024
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