ArticleThe International journal on drug policy2021
Using conjoint analysis to study health policy changes: An example from a cohort of persons who use drugs.
Article in The International journal on drug policy, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
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Who cites it
1 citing paper in PubMed, 4 citations in OpenAlex.
- Is This Safe? Examining Safety Assessments of Illicit Drug Purchasing on Social Media Using Conjoint Analysis.Substance use & misuse · 2024Article
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
backgroundHistorically, persons who use drugs (PWUDs) in the United States have often lacked health insurance, as Medicaid did not cover low-income adults. The Affordable Care Act of 2010 (ACA) increased access to insurance in states, such as Kentucky, that expanded their Medicaid programs. A cohort study of PWUDs in Kentucky found the prevalence of being insured increased from 34% pre-ACA to 87% post-ACA. However, changes to Medicaid were proposed that intended to restrict access to this program. This manuscript describes the feasibility and utility of conjoint analysis, an innovative method for studying decision-making, to identify potential impacts of health policy changes on PWUDs.
methodsIBM SPSS's "orthogonal design" command was used to construct 12 policy profiles that presented varying combinations of the proposed policy changes to Kentucky's Medicaid plan. Each policy profile presented information on (1) monthly premium costs, (2) penalties for not paying monthly premiums, (3) weekly work requirements, and (4) if their preferred physician accepted the plan for payment. Readability of the policy profiles was analyzed using the Readable.io application. The policy profiles were included in a recent follow-up of a longitudinal cohort of PWUDs in Appalachian Kentucky (n = 355). Participants rated the likelihood of enrolling in each policy profile's Medicaid plan, using a scale ranging from 0=not at all likely to 10=extremely likely. Data were analyzed using SPSS's conjoint analysis commands.
resultsReadability results indicated the policy profiles required a 3
conclusionsThis research demonstrates the feasibility of using conjoint analysis to study the impacts of potential policy changes on PWUDs.
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Registered trials
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