ArticleMedical decision making : an international journal of the Society for Medical Decision Making2023
Testing Explanations for Skepticism of Personalized Risk Information.
Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
3 citing papers in PubMed, 5 citations in OpenAlex.
- A field experiment to improve initial patient engagement for hypertension prevention in South Korea.Scientific reports · 2025Article
- Usual prevention in unusual settings: A scoping review of place-based health interventions in public-facing businesses.PloS one · 2025Article
- Mammography Screening Preferences Among Screening-Eligible Women in Their 40s : A National U.S. Survey.Annals of internal medicine · 2024Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundThe promise of precision medicine could be stymied if people do not accept the legitimacy of personalized risk information. We tested 4 explanations for skepticism of personalized diabetes risk information.
methodWe recruited participants (
resultsOf the participants, 18% believed that their diabetes risk was lower than the information provided, 40% believed their risk was higher, and 42% accepted the information. Information evaluation skills were not supported as a risk skepticism explanation. Motivated reasoning received some support; higher diabetes risk and more negative affect toward the information were associated with risk underestimation, but spontaneous self-affirmation and information avoidance were not moderators. For Bayesian updating, more surprise was associated with overestimation. For personal relevance, belonging to a marginalized racial/ethnic group was associated with underestimation.
conclusionThere are likely multiple cognitive, affective, and motivational explanations for risk skepticism. Understanding these explanations and developing interventions that address them will increase the effectiveness of precision medicine and facilitate its widespread implementation.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.