Literature DB >> 12926563

How do individuals apply risk information when choosing among health care interventions?

Dorte Gyrd-Hansen1, Ivar Sønbø Kristiansen, Jørgen Nexøe, Jesper Bo Nielsen.   

Abstract

A sample of 3,201 Danes was subjected to personal interviews in which they were asked to state their preferences for risk-reducing health care interventions based on information on absolute risk reduction (ARR) and relative risk reduction (RRR). The aim of the study was to measure the relative weighting of different types of risk information under various circumstances. The effect of presenting questions, and of explicitly formulating RRR, was analyzed. A preference for increases in RRR was demonstrated. There was a stronger inclination to choose the intervention that offered the highest RRR if RRR was explicitly stated. Individuals with more than 10 years of schooling also demonstrated a preference for increased ARR, but only when facing individually framed choices. In a social choice context, preferences for RRR remained intact, but the magnitude of ARR had no impact on choices. Results imply that social framing may induce a propensity to prefer interventions that target high-risk populations. Those respondents who had received < or = 10 years of schooling demonstrated preferences for RRR but not ARR, and no impact of social framing was observed.

Mesh:

Year:  2003        PMID: 12926563     DOI: 10.1111/1539-6924.00348

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  7 in total

1.  Communicating risk using absolute risk reduction or prolongation of life formats: cluster-randomised trial in general practice.

Authors:  Charlotte Gry Harmsen; Ivar Sønbø Kristiansen; Pia Veldt Larsen; Jørgen Nexøe; Henrik Støvring; Dorte Gyrd-Hansen; Jesper Bo Nielsen; Adrian Edwards; Dorte Ejg Jarbøl
Journal:  Br J Gen Pract       Date:  2014-04       Impact factor: 5.386

2.  Individual health discount rate in patients with ulcerative colitis.

Authors:  Akbar K Waljee; Arden M Morris; Jennifer F Waljee; Peter D R Higgins
Journal:  Inflamm Bowel Dis       Date:  2010-11-16       Impact factor: 5.325

3.  The Inability to Calculate Predictive Values: an Old Problem that Has Not Gone Away.

Authors:  Steven D Stovitz
Journal:  Med Sci Educ       Date:  2020-04-08

4.  Numeracy and communication with patients: they are counting on us.

Authors:  Andrea J Apter; Michael K Paasche-Orlow; Janine T Remillard; Ian M Bennett; Elana Pearl Ben-Joseph; Rosanna M Batista; James Hyde; Rima E Rudd
Journal:  J Gen Intern Med       Date:  2008-10-02       Impact factor: 5.128

5.  Providing additional information about the benefits of statins in a leaflet for patients with coronary heart disease: a qualitative study of the impact on attitudes and beliefs.

Authors:  Rebecca Dickinson; David K Raynor; Peter Knapp; Jan MacDonald
Journal:  BMJ Open       Date:  2016-12-02       Impact factor: 2.692

6.  Using discounting biases, risk characteristics, and perceived control improves preventive programs.

Authors:  Monica Ortendahl
Journal:  Int J Biomed Sci       Date:  2007-06

7.  Shared decision-making based on different features of risk in the context of diabetes mellitus and rheumatoid arthritis.

Authors:  Monica Ortendahl
Journal:  Ther Clin Risk Manag       Date:  2007-12       Impact factor: 2.423

  7 in total

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