Lisa A Howell1, Tabetha A Brockman2, Pamela S Sinicrope3, Christi A Patten3, Paul A Decker4, Shawna L Ehlers1, Noralane M Lindor5, Sandra K Nigon5, Gloria M Petersen6. 1. Department of Psychology and Psychiatry, 200 First St. SW, Mayo Clinic Rochester, MN 55905, USA. 2. Behavioral Health Research Program, Mayo Clinic Rochester, 200 First St. SW, Rochester, MN 55905, USA. 3. Department of Psychology and Psychiatry, 200 First St. SW, Mayo Clinic Rochester, MN 55905, USA ; Behavioral Health Research Program, Mayo Clinic Rochester, 200 First St. SW, Rochester, MN 55905, USA. 4. Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic Rochester, 200 First St. SW, Rochester, MN 55905, USA. 5. Department of Medical Genetics, Mayo Clinic Rochester, 200 First St. SW, Rochester, MN 55905, USA. 6. Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic Rochester, 200 First St. SW, Rochester, MN 55905, USA.
Abstract
BACKGROUND: Cancer is a shared family experience, and thus the purpose of this study was to assess receptivity and preferences for cancer risk reduction programs among at-risk family members with two or more relatives affected with colorectal cancer (CRC). METHODS: The sample comprised 401 at-risk family members with two or more relatives affected with CRC from the Colon Cancer Family Registry. In March 2009, respondents completed a mailed survey assessing receptivity and preferences for participating in cancer risk reduction programs and evaluated their relationship to demographic, medical, and psychosocial variables. Multivariable generalized estimating equation approaches were used to model preferences. RESULTS: Overall, 81% of respondents were receptive to a lifestyle cancer risk reduction program; of these, about half (54%) preferred to participate with their family. Program preferences included: weight management (36%) and nutrition (31%); delivered through the internet (41%) or mail (39%). In a multivariate model, a greater level of concern about cancer (p<0.001), female gender (p=0.002), and higher education (p=0.016) were significantly correlated with willingness to participate in lifestyle programs. CONCLUSIONS: Family members of those with CRC are receptive to cancer risk reduction programs that focus on weight management and nutrition delivered via the internet or mail. Future research is needed to determine how best to incorporate a family-based approach that addresses the cancer experience when designing lifestyle intervention programs.
BACKGROUND:Cancer is a shared family experience, and thus the purpose of this study was to assess receptivity and preferences for cancer risk reduction programs among at-risk family members with two or more relatives affected with colorectal cancer (CRC). METHODS: The sample comprised 401 at-risk family members with two or more relatives affected with CRC from the Colon Cancer Family Registry. In March 2009, respondents completed a mailed survey assessing receptivity and preferences for participating in cancer risk reduction programs and evaluated their relationship to demographic, medical, and psychosocial variables. Multivariable generalized estimating equation approaches were used to model preferences. RESULTS: Overall, 81% of respondents were receptive to a lifestyle cancer risk reduction program; of these, about half (54%) preferred to participate with their family. Program preferences included: weight management (36%) and nutrition (31%); delivered through the internet (41%) or mail (39%). In a multivariate model, a greater level of concern about cancer (p<0.001), female gender (p=0.002), and higher education (p=0.016) were significantly correlated with willingness to participate in lifestyle programs. CONCLUSIONS: Family members of those with CRC are receptive to cancer risk reduction programs that focus on weight management and nutrition delivered via the internet or mail. Future research is needed to determine how best to incorporate a family-based approach that addresses the cancer experience when designing lifestyle intervention programs.
Authors: Ying Bao; Katharina Nimptsch; Jeffrey A Meyerhardt; Andrew T Chan; Kimmie Ng; Dominique S Michaud; Jennie C Brand-Miller; Walter C Willett; Edward Giovannucci; Charles S Fuchs Journal: Cancer Epidemiol Biomarkers Prev Date: 2010-10-05 Impact factor: 4.254
Authors: Carolyn Rabin; Michelle L Rogers; Bernardine M Pinto; Justin M Nash; Georita M Frierson; Peter C Trask Journal: Soc Sci Med Date: 2006-10-24 Impact factor: 4.634
Authors: Julie K Bassett; Gianluca Severi; Dallas R English; Laura Baglietto; Kavitha Krishnan; John L Hopper; Graham G Giles Journal: Cancer Epidemiol Biomarkers Prev Date: 2010-09-24 Impact factor: 4.254
Authors: Catherine Speechly; Charles Bridges-Webb; Suzanne McKenzie; Yvonne Zurynski; Alison Lucas Journal: Aust J Prim Health Date: 2010 Impact factor: 1.307
Authors: E de Vries; I Soerjomataram; V E P P Lemmens; J W W Coebergh; J J Barendregt; A Oenema; H Møller; H Brenner; Andrew G Renehan Journal: Eur J Cancer Date: 2010-09 Impact factor: 9.162
Authors: Gloria M Petersen; Mariza de Andrade; Michael Goggins; Ralph H Hruban; Melissa Bondy; Jeannette F Korczak; Steven Gallinger; Henry T Lynch; Sapna Syngal; Kari G Rabe; Daniela Seminara; Alison P Klein Journal: Cancer Epidemiol Biomarkers Prev Date: 2006-04 Impact factor: 4.254
Authors: Andrea L Cheville; Lori Rhudy; Jeffrey R Basford; Joan M Griffin; Ann Marie Flores Journal: Arch Phys Med Rehabil Date: 2016-08-31 Impact factor: 3.966
Authors: Karen Milton; Karen Poole; Ainslea Cross; Sophie Gasson; Kajal Gokal; Karen Lyons; Richard Pulsford; Andy Jones Journal: Eur J Cancer Care (Engl) Date: 2022-03-13 Impact factor: 2.328
Authors: Lisa A Howell; Tabetha A Brockman; Pamela S Sinicrope; Christi A Patten; Paul A Decker; Allan Busta; Shawn Stoddard; Sheila R McNallan; Ping Yang Journal: Adv Cancer Prev Date: 2016-06-20