Efficacy of community groups as a social prescription for senior health—insights from a natural experiment during the COVID-19 lockdown
Abstract Loneliness and associated physical and cognitive health decline among the aging population is an important medical concern, exacerbated in times of abnormal isolation like the 2020–2021 Covid-19 pandemic lockdown. In this backdrop, recent “social prescribing” based health policy initiatives...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-10-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-024-75262-y |
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| Summary: | Abstract Loneliness and associated physical and cognitive health decline among the aging population is an important medical concern, exacerbated in times of abnormal isolation like the 2020–2021 Covid-19 pandemic lockdown. In this backdrop, recent “social prescribing” based health policy initiatives such as community groups as a support structure for the aging population assumes great importance. In this paper, we evaluate and quantify the impact of such social prescribing policies in combatting loneliness and related health degeneration of the aging population in times of abnormal isolation. To this end, we conduct a natural experiment across a sample of 618 individuals aged 65 and over with varying access to community groups during the Covid-19 lockdown period. Using a random-effects, probit model to compare the differences in health outcomes of participants with access to community groups (target) with those without access (control), we find that the target group was 2.65 times less likely to suffer from loneliness as compared to the control group, along with lower incidences of reported cardiovascular and cognitive health decline. These initial findings provide preliminary support in favor of the interventional power of social prescription tools in mitigating loneliness and its consequent negative health impact on the aging population. |
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| ISSN: | 2045-2322 |