ArticleSocial science research2023
The ties that transplant: The social capital determinants of the living kidney donor relationship distribution.
Article in Social science research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Relationships, race/ethnicity, gender, age, and living kidney donation evaluation willingness.Transplant immunology · 2024Article
- Roles, Relationships, Resources, and Renal Exchange: Applying Social Capital Theory to Role Effects on Living Kidney Donation Behaviors.Socius : sociological research for a dynamic worldArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
The network perspective on social capital decomposes it into ego's network size, alters' relevant resources, and social factors moderating access to alters' resources, but rarely examines how it is distributed across relationship types. Using this approach, I investigate the situationally-relevant social capital relationship distribution and its association with health-related social support, with an application to the living kidney donor relationship distribution. Analyzing an original survey of transplant candidates (N = 72) and their reports on their family and friends (N = 1548), I compare the tie count, donation-relevant biomedical resource, and tie strength relationship distributions to administrative data on the national distribution of living kidney donor relationships. I find that the tie strength relationship distribution matches the completed living kidney donor relationship distribution far better than the tie count and donation-relevant biomedical resource relationship distributions. These conclusions are upheld in race- and gender-stratified analyses and are robust across alternative approaches.
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Registered trials
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