ArticleJournal of aging and health2019
Predicting Receipt of Social Security Administration Disability Benefits Using Biomarkers and Other Physiological Measures: Evidence From the Health and Retirement Study.
Article in Journal of aging and health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
5 authors.
Funding
Abstract
objectivesThe objective of this study was to assess how well physiological measures, including biomarkers and genetic indicators, predict receipt of Social Security Administration (SSA) disability benefits among U.S. adults aged 51 to 65 years.
methodWe used data from the 2006 to 2012 waves of the Health and Retirement Study (HRS), linked to SSA administrative data. Using logistic regression, we predicted benefit receipt (either Social Security Disability Insurance or Supplemental Security Income) using 19 distinct physiological markers, adjusting for age, sex, race, and select medication use. We then calculated the propensity (i.e., predicted probability) that each HRS respondent received benefits and assessed how well propensity score-based classifications could identify beneficiaries and nonbeneficiaries.
resultsThirteen percent of respondents received benefits. Using the propensity score cut point that maximized the sum of sensitivity and specificity, the model correctly predicted 75.9% of beneficiaries and 73.5% of nonbeneficiaries. DISCUSSION: Physiological measures have moderate power to predict SSA disability benefit receipt.
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