Literature DB >> 11126159

Telling people about screening programmes and screening test results: how can we do it better?

E Goyder1, A Barratt, L M Irwig.   

Abstract

To make an informed choice about whether to be screened, people need information that allows them to weigh up the benefits and harms of screening. To understand their screening test results they require even more information. Yet currently, people attending a screening programme or considering a screening test may only be told that the test can detect disease or risk factors for disease, and that early intervention improves outcomes. When given their test results, people are generally only told the test was abnormal ("positive") or normal ("negative"). We believe that information given before and after the screening test can, and should, be improved. This will probably require information that includes both the benefits and harms of screening and is probabilistic. Indeed, we believe the traditional dichotomisation of screening test results into positive and negative is problematic, and could be replaced by standard use of risks or probabilistic data before and after screening. The relevant risk data could be explained in a range of ways, for example, quantitatively, qualitatively, and/or by "anchoring" to everyday experiences. In this paper we explore why dichotomisation of screening test results is problematic and look at the adverse consequences of presenting test results in terms of true and false, positive and negative. We present some ideas on alternative ways of providing information on screening programmes and screening test results. Our aim is to stimulate debate about these issues and to provide some starting points which could be further developed and evaluated in a wide range of screening programmes.

Entities:  

Mesh:

Year:  2000        PMID: 11126159     DOI: 10.1136/jms.7.3.123

Source DB:  PubMed          Journal:  J Med Screen        ISSN: 0969-1413            Impact factor:   2.136


  9 in total

1.  Should we abandon the concept of giving patients "positive" and "negative" screening results? No: we should do better at explaining results.

Authors:  J E Haddow
Journal:  West J Med       Date:  2001-06

Review 2.  Cancer screening.

Authors:  A Barratt; P Mannes; L Irwig; L Trevena; J Craig; L Rychetnik
Journal:  J Epidemiol Community Health       Date:  2002-12       Impact factor: 3.710

Review 3.  What are the chances? Evaluating risk and benefit information in consumer health materials.

Authors:  Jacquelyn Burkell
Journal:  J Med Libr Assoc       Date:  2004-04

4.  "What does this mean?" How Web-based consumer health information fails to support information seeking in the pursuit of informed consent for screening test decisions.

Authors:  Jacquelyn Burkell; D Grant Campbell
Journal:  J Med Libr Assoc       Date:  2005-07

5.  "Couldn't you have done just as well without the screening?". A qualitative study of benefits from screening as perceived by people without a high cardiovascular risk score.

Authors:  Karen-Dorthe Bach Nielsen; Lise Dyhr; Torsten Lauritzen; Kirsti Malterud
Journal:  Scand J Prim Health Care       Date:  2009       Impact factor: 2.581

6.  Acceptability of screening for early detection of liver disease in hazardous/harmful drinkers in primary care.

Authors:  Caroline Eyles; Michael Moore; Nicholas Sheron; Paul Roderick; Wendy O'Brien; Geraldine M Leydon
Journal:  Br J Gen Pract       Date:  2013-08       Impact factor: 5.386

7.  Education and role modelling for clinical decisions with female cancer patients.

Authors:  Rhonda F Brown; Phyllis N Butow; Merin Anne Sharrock; Michael Henman; Fran Boyle; David Goldstein; Martin H N Tattersall
Journal:  Health Expect       Date:  2004-12       Impact factor: 3.377

8.  Optimising faecal occult blood screening:retrospective analysis of NHS Bowel Cancer Screening data to improve the screening algorithm.

Authors:  J Geraghty; P Butler; H Seaman; J Snowball; S Sarkar; R Blanks; S Halloran; K Bodger; C J Rees
Journal:  Br J Cancer       Date:  2014-09-16       Impact factor: 7.640

9.  Determinants of motivation to quit in smokers screened for the early detection of lung cancer: a qualitative study.

Authors:  Ben Young; Kavita Vedhara; Denise Kendrick; Roberta Littleford; John F R Robertson; Frank M Sullivan; Stuart Schembri; Roshan das Nair
Journal:  BMC Public Health       Date:  2018-11-20       Impact factor: 3.295

  9 in total

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