Literature DB >> 15171107

Gail model risk assessment and risk perceptions.

John M Quillin1, Elizabeth Fries, Donna McClish, Ellen Shaw de Paredes, Joann Bodurtha.   

Abstract

Patients can benefit from accessible breast cancer risk information. The Gail model is a well-known means of providing risk information to patients and for guiding clinical decisions. Risk presentation often includes 5-year and life-time percent chances for a woman to develop breast cancer. How do women perceive their risks after Gail model risk assessment? This exploratory study used a randomized clinical trial design to address this question among women not previously selected for breast cancer risk. Results suggest a brief risk assessment intervention changes quantitative and comparative risk perceptions and improves accuracy. This study improves our understanding of risk perceptions by evaluating an intervention in a population not previously selected for high-risk status and measuring perceptions in a variety of formats.

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Year:  2004        PMID: 15171107     DOI: 10.1023/b:jobm.0000019852.53048.b3

Source DB:  PubMed          Journal:  J Behav Med        ISSN: 0160-7715


  32 in total

1.  Gail model breast cancer risk components are poor predictors of risk perception and screening behavior.

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Journal:  Breast Cancer Res Treat       Date:  1996       Impact factor: 4.872

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Review 5.  Application of breast cancer risk prediction models in clinical practice.

Authors:  Susan M Domchek; Andrea Eisen; Kathleen Calzone; Jill Stopfer; Anne Blackwood; Barbara L Weber
Journal:  J Clin Oncol       Date:  2003-02-15       Impact factor: 44.544

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Authors:  N R Abu-Rustum; H Herbolsheimer
Journal:  Gynecol Oncol       Date:  2001-05       Impact factor: 5.482

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Authors:  Noreen C Facione
Journal:  Cancer Pract       Date:  2002 Sep-Oct

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Journal:  Health Psychol       Date:  1996-03       Impact factor: 4.267

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Journal:  Stat Med       Date:  1989-06       Impact factor: 2.373

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  14 in total

1.  Understanding Decision Making about Breast Cancer Prevention in Action: The Intersection of Perceived Risk, Perceived Control, and Social Context: NRG Oncology/NSABP DMP-1.

Authors:  Christine M Gunn; Barbara G Bokhour; Victoria A Parker; Tracy A Battaglia; Patricia A Parker; Angela Fagerlin; Worta McCaskill-Stevens; Hanna Bandos; Sarah B Blakeslee; Christine Holmberg
Journal:  Med Decis Making       Date:  2019-02-25       Impact factor: 2.583

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Authors:  Amy McQueen; Paul R Swank; Lori A Bastian; Sally W Vernon
Journal:  Health Psychol       Date:  2008-01       Impact factor: 4.267

3.  Exploring Explanatory Models of Risk in Breast Cancer Risk Counseling Discussions: NSABP/NRG Oncology Decision-Making Project 1.

Authors:  Christine M Gunn; Barbara Bokhour; Victoria A Parker; Patricia A Parker; Sarah Blakeslee; Hanna Bandos; Christine Holmberg
Journal:  Cancer Nurs       Date:  2019 Jan/Feb       Impact factor: 2.592

4.  Breast cancer risk assessment in 64,659 women at a single high-volume mammography clinic.

Authors:  John T Brinton; Lora D Barke; Mary E Freivogel; Stacy Jackson; Colin I O'Donnell; Deborah H Glueck
Journal:  Acad Radiol       Date:  2011-11-03       Impact factor: 3.173

5.  Breast cancer risk assessment in socioeconomically disadvantaged urban communities.

Authors:  Chyongchiou Jeng Lin; Bruce Block; Mary Patricia Nowalk; Mattie Woods; Edmund M Ricci; Keith H Morgenlander; Dwight E Heron
Journal:  J Natl Med Assoc       Date:  2007-07       Impact factor: 1.798

6.  Conceptual problems in laypersons' understanding of individualized cancer risk: a qualitative study.

Authors:  Paul K J Han; Thomas C Lehman; Holly Massett; Simon J C Lee; William M P Klein; Andrew N Freedman
Journal:  Health Expect       Date:  2009-03       Impact factor: 3.377

7.  Spiritual coping, family history, and perceived risk for breast cancer--can we make sense of it?

Authors:  John M Quillin; Donna K McClish; Resa M Jones; Karen Burruss; Joann N Bodurtha
Journal:  J Genet Couns       Date:  2006-09-30       Impact factor: 2.537

8.  Responses to provision of personalised cancer risk information: a qualitative interview study with members of the public.

Authors:  Juliet A Usher-Smith; Barbora Silarova; Artitaya Lophatananon; Robbie Duschinsky; Jackie Campbell; Joanne Warcaba; Kenneth Muir
Journal:  BMC Public Health       Date:  2017-12-22       Impact factor: 3.295

9.  Recruiting diverse patients to a breast cancer risk communication trial--waiting rooms can improve access.

Authors:  Joann N Bodurtha; John M Quillin; Kelly A Tracy; Joseph Borzelleca; Donna McClish; Diane Baer Wilson; Resa M Jones; Julie Quillin; Deborah Bowen
Journal:  J Natl Med Assoc       Date:  2007-08       Impact factor: 1.798

10.  Mammography screening after risk-tailored messages: the women improving screening through education and risk assessment (WISER) randomized, controlled trial.

Authors:  Joann Bodurtha; John M Quillin; Kelly A Tracy; Joseph Borzelleca; Donna McClish; Diane Baer Wilson; Resa M Jones; Julie Quillin; Deborah Bowen
Journal:  J Womens Health (Larchmt)       Date:  2009 Jan-Feb       Impact factor: 2.681

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