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  • Writer's pictureElla

ISF grant for research on social networks of older gay and lesbian adults

Updated: Aug 3, 2023

Together with Prof. Yaacov Bachner, we received funding from the Israel Science Foundation (ISF) to conduct a five-year research project on the social relationships and mental health of older gay and lesbian adults in Israel.


The world population is rapidly aging; older lesbian and gay (LG) adults, however, are a distinct and understudied group within the larger aging population, with unique characteristics and needs. Compared to older heterosexual adults, LG older adults are at an increased risk for mental health problems, while also being at a greater risk for social isolation. Many have no children and are estranged from their families of origin, the result of which may be unique social environments (e.g., families of choice) that differ from those of older heterosexual adults. Although social relationships are integral to the mental health of heterosexual and LG older adults alike, the effects of the unique aspects of LG relationships, such as their “families of choice,” are not yet understood. Therefore, this research will aim at better understanding how the social relationships of LG adults can impact their mental health, with a focus on various mental health indicators relevant to aging among LGs.


For this project we will develop a conceptual model to examine the impact of social relationships on the mental health of older gay and lesbian adults in Israel over time, based on the theoretical frameworks of the Health Equity Promotion Model (HEPM) and the Convoy Model of Social Relations. The project will delve into meaningful and unique aspects of LG adults’ social ties, such as their level of commitment, stability, acceptance, and disclosure. Particular attention will be given to "families of choice," which are often the main source of support for LG adults, with understudied mental health implications. We will use a longitudinal design, necessary to assess changes and direction of causal effects, by measuring data at two time points.





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