Literature DB >> 15209937

Agreement between scales in the measurement of breast cancer risk perceptions.

Marilyn M Schapira1, Susan L Davids, Timothy L McAuliffe, Ann B Nattinger.   

Abstract

The objective of this article is to compare the accuracy and numeric responses of breast cancer risk perception as measured by a frequency scale and percentage scale. A cross-sectional survey was conducted. Perceptions of five-year and lifetime breast cancer risk were measured using a frequency and a percentage scale. Estimation error was calculated as the absolute difference between actual breast cancer risk as determined by the Gail model and perceived risk. Agreement between scales was determined by calculating the mean and standard deviation of the difference between numeric responses. The study was conducted among women enrolled in two primary care clinics associated with an academic medical center. Two-hundred-fifty-four participants were recruited from one of the two participating internal medicine clinics. Inclusion criteria included female gender and age 40-84 years. Exclusion criteria included a history of breast cancer, dementia, or a life expectancy of less than two years. The frequency scale was more accurate than the percentage scale in estimating lifetime risk (p= 0.05), but less accurate in estimating five-year risk (p < 0.02). Only 79 participants (31%) were considered consistent scale users, providing identical responses when using the frequency and percentage scale for a given risk estimate. Although the mean difference (percentage-frequency scale) for estimates of breast cancer lifetime risk was only 2.4, the empirically determined 90% limits of agreement between the frequency and percentage scale for lifetime risk were wide, from -30 to 40. Higher numeracy was associated with consistent use of scales (OR 1.61, 95% CI; 1.09-2.37). We report disagreement in breast cancer risk perceptions when measured by a frequency and a percentage scale. The accuracy and direction of bias associated with each scale varies according to the time frame of risk being assessed.

Entities:  

Mesh:

Year:  2004        PMID: 15209937     DOI: 10.1111/j.0272-4332.2004.00466.x

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


  27 in total

1.  The relationship of health numeracy to cancer screening.

Authors:  Marilyn M Schapira; Joan Neuner; Kathlyn E Fletcher; Mary Ann Gilligan; Elisabeth Hayes; Purushottam Laud
Journal:  J Cancer Educ       Date:  2011-03       Impact factor: 2.037

2.  Validation of a Short, 3-Item Version of the Subjective Numeracy Scale.

Authors:  Candace D McNaughton; Kerri L Cavanaugh; Sunil Kripalani; Russell L Rothman; Kenneth A Wallston
Journal:  Med Decis Making       Date:  2015-04-15       Impact factor: 2.583

3.  Other Ways of Knowing.

Authors:  Negin Hajizadeh; Melissa J Basile; Andrzej Kozikowski; Meredith Akerman; Tara Liberman; Thomas McGinn; Michael A Diefenbach
Journal:  Med Decis Making       Date:  2017-01-06       Impact factor: 2.583

4.  Patient perceptions of osteoporosis treatment thresholds.

Authors:  Joan M Neuner; Marilyn M Schapira
Journal:  J Rheumatol       Date:  2014-02-01       Impact factor: 4.666

5.  A framework for health numeracy: how patients use quantitative skills in health care.

Authors:  Marilyn M Schapira; Kathlyn E Fletcher; Mary Ann Gilligan; Toni K King; Purushottam W Laud; B Alexendra Matthews; Joan M Neuner; Elisabeth Hayes
Journal:  J Health Commun       Date:  2008 Jul-Aug

6.  Evaluating existing measures of health numeracy using item response theory.

Authors:  Marilyn M Schapira; Cindy M Walker; Sonya K Sedivy
Journal:  Patient Educ Couns       Date:  2009-05-13

7.  Understanding the role of numeracy in health: proposed theoretical framework and practical insights.

Authors:  Isaac M Lipkus; Ellen Peters
Journal:  Health Educ Behav       Date:  2009-10-15

8.  Linking numeracy and asthma-related quality of life.

Authors:  Andrea J Apter; Xingmei Wang; Daniel Bogen; Ian M Bennett; Rebecca M Jennings; Laura Garcia; Tamie Sharpe; Carmen Frazier; Thomas Ten Have
Journal:  Patient Educ Couns       Date:  2009-02-13

Review 9.  How numeracy influences risk comprehension and medical decision making.

Authors:  Valerie F Reyna; Wendy L Nelson; Paul K Han; Nathan F Dieckmann
Journal:  Psychol Bull       Date:  2009-11       Impact factor: 17.737

10.  Communicating Numerical Risk: Human Factors That Aid Understanding in Health Care.

Authors:  Priscila G Brust-Renck; Caisa E Royer; Valerie F Reyna
Journal:  Rev Hum Factors Ergon       Date:  2013-10
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.