Karen B Eden1, Paula Scariati2, Krystal Klein1, Lindsey Watson1, Mark Remiker3, Michelle Hribar1, Vanessa Forro3, LeAnn Michaels3, Heidi D Nelson1,4. 1. 1 Department of Medical Informatics and Clinical Epidemiology, Oregon Health and Science University , Portland, Oregon. 2. 2 Marin General Hospital , Greenbrae, California. 3. 3 Oregon Rural Practice-Based Research Network, Oregon Health and Science University , Portland, Oregon. 4. 4 Providence Cancer Center , Providence Health and Services, Portland, Oregon.
Abstract
BACKGROUND: Clinical guidelines recommend a personalized approach to mammography screening for women in their forties; however, methods to do so are lacking. An evidence-based mammography screening decision aid was developed as an electronic mobile application and evaluated in a before-after study. METHODS: The decision aid (Mammopad) included modules on breast cancer, mammography, risk assessment, and priority setting about screening. Women aged 40-49 years who were patients of rural primary care clinics, had no major risk factors for breast cancer, and no mammography during the previous year were invited to use the decision aid. Twenty women participated in pretesting of the decision aid and 75 additional women completed the before-after study. The primary outcome was decisional conflict measured before and after using Mammopad. Secondary outcomes included decision self-efficacy and intention to begin or continue mammography screening. Differences comparing measures before versus after use were determined using Wilcoxon signed rank tests. RESULTS: After using Mammopad, women reported reduced decisional conflict based on mean Decisional Conflict Scale scores overall (46.33 versus 8.33; Z = -7.225; p < 0.001) and on all subscales (p < 0.001). Women also reported increased mean Decision Self-Efficacy Scale scores (79.67 versus 95.73; Z = 6.816, p < 0.001). Although 19% of women changed their screening intentions, this was not statistically significant. CONCLUSIONS: Women reported less conflict about their decisions for mammography screening, and felt more confident to make decisions after using Mammopad. This approach may help guide women through the decision making process to determine personalized screening choices that are appropriate for them.
BACKGROUND: Clinical guidelines recommend a personalized approach to mammography screening for women in their forties; however, methods to do so are lacking. An evidence-based mammography screening decision aid was developed as an electronic mobile application and evaluated in a before-after study. METHODS: The decision aid (Mammopad) included modules on breast cancer, mammography, risk assessment, and priority setting about screening. Women aged 40-49 years who were patients of rural primary care clinics, had no major risk factors for breast cancer, and no mammography during the previous year were invited to use the decision aid. Twenty women participated in pretesting of the decision aid and 75 additional women completed the before-after study. The primary outcome was decisional conflict measured before and after using Mammopad. Secondary outcomes included decision self-efficacy and intention to begin or continue mammography screening. Differences comparing measures before versus after use were determined using Wilcoxon signed rank tests. RESULTS: After using Mammopad, women reported reduced decisional conflict based on mean Decisional Conflict Scale scores overall (46.33 versus 8.33; Z = -7.225; p < 0.001) and on all subscales (p < 0.001). Women also reported increased mean Decision Self-Efficacy Scale scores (79.67 versus 95.73; Z = 6.816, p < 0.001). Although 19% of women changed their screening intentions, this was not statistically significant. CONCLUSIONS:Women reported less conflict about their decisions for mammography screening, and felt more confident to make decisions after using Mammopad. This approach may help guide women through the decision making process to determine personalized screening choices that are appropriate for them.
Authors: Heidi D Nelson; Miranda Pappas; Bernadette Zakher; Jennifer Priest Mitchell; Leila Okinaka-Hu; Rongwei Fu Journal: Ann Intern Med Date: 2014-02-18 Impact factor: 25.391
Authors: G A Colditz; W C Willett; D J Hunter; M J Stampfer; J E Manson; C H Hennekens; B A Rosner Journal: JAMA Date: 1993-07-21 Impact factor: 56.272
Authors: Dawn Stacey; France Légaré; Nananda F Col; Carol L Bennett; Michael J Barry; Karen B Eden; Margaret Holmes-Rovner; Hilary Llewellyn-Thomas; Anne Lyddiatt; Richard Thomson; Lyndal Trevena; Julie H C Wu Journal: Cochrane Database Syst Rev Date: 2014-01-28
Authors: Mara A Schonberg; Mary Beth Hamel; Roger B Davis; M Cecilia Griggs; Christina C Wee; Angela Fagerlin; Edward R Marcantonio Journal: JAMA Intern Med Date: 2014-03 Impact factor: 21.873
Authors: Joel E Pacyna; Carmen Radecki Breitkopf; Sarah M Jenkins; Erica J Sutton; Caroline Horrow; Iftikhar J Kullo; Richard R Sharp Journal: J Med Genet Date: 2018-12-22 Impact factor: 6.318
Authors: Barry G Saver; Kathleen M Mazor; Roger Luckmann; Sarah L Cutrona; Marcela Hayes; Tatyana Gorodetsky; Nancy Esparza; Gonzalo Bacigalupe Journal: Ann Fam Med Date: 2017-01-06 Impact factor: 5.166
Authors: Lori L DuBenske; Sarina Schrager; Helene McDowell; Lee G Wilke; Amy Trentham-Dietz; Elizabeth S Burnside Journal: Breast J Date: 2017-03-02 Impact factor: 2.431
Authors: Karen B Eden; Ilya Ivlev; Katherine L Bensching; Gabriel Franta; Alyssa R Hersh; James Case; Rongwei Fu; Heidi D Nelson Journal: J Womens Health (Larchmt) Date: 2020-03-10 Impact factor: 2.681