King M-C, Marks JH, Mandell JB. The New York breast Cancer study group. Breast and ovarian cancer risks due to inherited mutations in BRCA1 and BRCA2. Science. 2003;302(5645):643–6. https://doi.org/10.1126/science.1088759.
Article
CAS
PubMed
Google Scholar
Petrucelli N, Daly M, Pal T. BRCA1- and BRCA2-associated hereditary breast and ovarian Cancer. In: Adam M, Ardinger H, Pagon R, et al., editors. GeneReviews. Seattle: University of Washington; 2016.
Google Scholar
Giardiello F, Allen J, Axilbund J, Boland C, Burke C, Burt R, et al. Guidelines on genetic evaluation and management of lynch syndrome: a consensus statement by the US multi-society task force on colorectal Cancer. Gastroenterology. 2014;147(2):502–6. https://doi.org/10.1053/j.gastro.2014.04.001.
Article
PubMed
Google Scholar
Curras-Freixes M, Inglada-Perez L, Mancikova V, Montero-Conde C, Leton R, et al. Recommendations for somatic and germline genetic testing of single pheochoromocytoma and paraganglioma based on findings from a series of 329 patients. J Med Genet. 2015;52(10):647–56. https://doi.org/10.1136/jmedgenet-2015-103218.
Article
CAS
PubMed
Google Scholar
Brito J, Asi N, Bancos I, Gionfriddo M, Zeballos-Palacios C, et al. Testing for germline mutations in sporadic pheocromocytoma/paraganglioma: a systematic review. Clin Endocrinol. 2015;82(3):338–45. https://doi.org/10.1111/cen.12530.
Article
CAS
Google Scholar
Judkins T, Leclair B, Bowles K, Gutin N, Trost J, McCulloch J, et al. Development and analytical validation of a 25-gene next generation sequencing panel that includes the BRCA1 and BRCA2 genes to assess hereditary cancer risk. BMC Cancer. 2015;15(1):215. https://doi.org/10.1186/s12885-015-1224-y.
Article
CAS
PubMed
PubMed Central
Google Scholar
National Cancer Institute. Genetics of Breast and Gynecologic Cancers Rockville: National Cancer Institute; 2015 [Available from: http://www.cancer.gov/cancertopics/pdq/genetics/breast-and-ovarian/HealthProfessional/page3.
Zhang S, Royer R, Li S, McLaughlin J, Rosen B, Risch H, et al. Frequencies of BRCA1 and BRCA2 mutations among 1,342 unselected patients with invasive ovarian cancer. Gynecol Oncol. 2011;121(2):353–7. https://doi.org/10.1016/j.ygyno.2011.01.020.
Article
CAS
PubMed
Google Scholar
Hampel H, Frankel W, Martin E, et al. Screening for the lynch syndrome (hereditary nonpolyposis colorectal cancer). N Engl J Med. 2005;352(18):1851–60. https://doi.org/10.1056/NEJMoa043146.
Article
CAS
PubMed
Google Scholar
Yurgelun MB, Kulke MH, Fuchs CS, Allen BA, Uno H, Hornick JL, et al. Cancer susceptibility gene mutations in individuals with colorectal cancer. J Clin Oncol. 2017;35(10):1086–95. https://doi.org/10.1200/JCO.2016.71.0012.
Article
CAS
PubMed
PubMed Central
Google Scholar
Shindo K, Yu J, Suenaga M, Fesharakizadeh S, Cho C, Macgregor-Das A, et al. Deleterious germline mutations in patients with apparently sporadic pancreatic adenocarcinoma. J Clin Oncol. 2017;35(30):3382–90. https://doi.org/10.1200/JCO.2017.72.3502.
Article
CAS
PubMed
PubMed Central
Google Scholar
Madelker D, et al. Mutation detection in patients with advanced cancer by universal sequencing of cancer-related genes in tumor and normal DNA vs guideline-based germline testing. J Am Med Assoc. 2017;318(9):825–35. https://doi.org/10.1001/jama.2017.11137.
Article
Google Scholar
Pritchard CC, Mateo J, Walsh MF, De Sarkar N, Abida W, Beltran H, et al. Inherited DNA-repair gene mutations in men with metastatic prostate cancer. N Engl J Med. 2016;375(5):443–53. https://doi.org/10.1056/NEJMoa1603144.
Article
CAS
PubMed
PubMed Central
Google Scholar
Hall MJ, Forman AD, Pilarski R, Wiesner G, Giri VN. Gene panel testing for inherited cancer risk. J Natl Compr Cancer Netw. 2014;12(9):1339–46. https://doi.org/10.6004/jnccn.2014.0128.
Article
Google Scholar
Hiraki S, Rinella ES, Schnabel F, Oratz R, Ostrer H. Cancer risk assessment using genetic panel testing: considerations for clinical application. J Genet Couns. 2014;23(4):604–17. https://doi.org/10.1007/s10897-014-9695-6.
Article
PubMed
Google Scholar
Kurian AW, Hare EE, Mills MA, Kingham KE, McPherson L, Whittemore AS, et al. Clinical evaluation of a multiple-gene sequencing panel for hereditary cancer risk assessment. J Clin Oncol. 2014;32(19):2001–9. https://doi.org/10.1200/JCO.2013.53.6607.
Article
CAS
PubMed
PubMed Central
Google Scholar
Maxwell KN, Wubbenhorst B, D'Andrea K, et al. Prevalence of mutations in a panel of breast cancer susceptibility genes in BRCA1/2-negative patients with early-onset breast cancer. Genet Med. 2015;17:630–8.
Desmond A, Kurian AW, Gabree M, Mills MA, Anderson MJ, Kobayashi Y, et al. Clinical actionability of multigene panel testing for hereditary breast and ovarian cancer risk assessment. JAMA Oncol. 2015;1(7):943–51. https://doi.org/10.1001/jamaoncol.2015.2690.
Article
PubMed
Google Scholar
Slavin TP, Niell-Swiller M, Solomon I, Nehoray B, Rybak C, Blazer KR, et al. Clinical application of multigene panels: challenges of next-generation counseling and cancer risk management. Front Oncol. 2015;5:208.
PubMed
PubMed Central
Google Scholar
Pennington KP, Swisher EM. Hereditary ovarian cancer: beyond the usual suspects. Gynecol Oncol. 2012;124(2):347–53. https://doi.org/10.1016/j.ygyno.2011.12.415.
Article
CAS
PubMed
Google Scholar
Domchek SM, Bradbury A, Garber JE, Offit K, Robson ME. Multiplex genetic testing for cancer susceptibility: out on the high wire without a net? J Clin Oncol. 2013;31(10):1267–70. https://doi.org/10.1200/JCO.2012.46.9403.
Article
PubMed
Google Scholar
Mandelker D, Zhang L, Kemel Y, Stadler ZK, Joseph V, Zehir A, et al. Mutation detection in patients with advanced Cancer by universal sequencing of Cancer-related genes in tumor and Normal DNA vs guideline-based Germline testing. JAMA. 2017;318(9):825–35. https://doi.org/10.1001/jama.2017.11137.
Article
PubMed
PubMed Central
Google Scholar
Pearlman R, Frankel W, Swanson B, et al. Prevalence and spectrum of germline cancer susceptibility gene mutations among patietns with early onset colorectal cancer. JAMA Oncol. 2017;3(4):464–71. https://doi.org/10.1001/jamaoncol.2016.5194.
Article
PubMed
PubMed Central
Google Scholar
Stoffel E, Koeppe E, Everett J, et al. Germline genetic features of young individuals with colorectal cancer. Gastroenterology. 2018;154(4):897–905. https://doi.org/10.1053/j.gastro.2017.11.004.
Article
CAS
PubMed
Google Scholar
Kapoor N, Curcio L, Blakemore C, et al. Multigene panel testing detects equal rates of pathogenic BRCA1/2 mutations and has a higher diagnostic yield compared to limited BRCA1/2 analysis along in patients at risk for hereditary breast cancer. Ann Surg Oncol. 2015;22(10):3282–8. https://doi.org/10.1245/s10434-015-4754-2.
Article
PubMed
Google Scholar
Ricker C, Culver JO, Lowstuter K, Sturgeon D, Sturgeon JD, Chanock CR, et al. Increased yield of actionable mutations using multi-gene panels to assess hereditary cancer susceptibility in an ethnically diverse clinical cohort. Cancer Genet. 2016;209(4):130–7. https://doi.org/10.1016/j.cancergen.2015.12.013.
Article
CAS
PubMed
PubMed Central
Google Scholar
Susswein LR, Marshall ML, Nusbaum R, Vogel Postula KJ, Weissman SM, Yackowski L, et al. Pathogenic and likely pathogenic variant prevalence among the first 10,000 patients referred for next-generation cancer panel testing. Genet Med. 2016;18(8):823–32. https://doi.org/10.1038/gim.2015.166.
Article
CAS
PubMed
Google Scholar
Yurgelun MB, Allen B, Kaldate RR, Bowles KR, Judkins T, Kaushik P, et al. Identification of a variety of mutations in Cancer predisposition genes in patients with suspected lynch syndrome. Gastroenterology. 2015;149(3):604–13 e20. https://doi.org/10.1053/j.gastro.2015.05.006.
Article
CAS
PubMed
Google Scholar
Giri VN, Knudsen K, Kelly W, et al. Role of genetic testing for inherited prostate cancer risk: Philadelphia prostate Cancer consensus conference 2017. J Clin Oncol. 2018;36(4):414–24. https://doi.org/10.1200/JCO.2017.74.1173.
Article
CAS
PubMed
Google Scholar
Hampel H. Genetic counseling and cascade genetic testing in lynch syndrome. Familial Cancer. 2016;15(3):423–7. https://doi.org/10.1007/s10689-016-9893-5.
Article
PubMed
Google Scholar
Samini G, Bernardini M, Brody L, Caga-Anan C, Campbell I, Chenevix-Trench G. Traceback: a proposed framework to increase identification and genetic counseling of BRCA1 and BRCA2 mutation carriers through family-based outreach. J Clin Oncol. 2017;35(20):2329–37. https://doi.org/10.1200/JCO.2016.70.3439.
Article
Google Scholar
Katapodi M, Viassolo V, Caiata-Zufferey M, Nikolaidis C, Buhrer-Landolt R, Buerki N, et al. Cancer predisposition cascade screening for hereditary breast/ovarian cancer and lynch syndromes in Switzerland: study protocol. JMIR Res Prot. 2017;6(9):e184. https://doi.org/10.2196/resprot.8138.
Article
Google Scholar
Dinh T, Rosner B, Atwood J, Boland C, et al. Health benefits and cost-effectiveness of primary genetic screening for lynch syndrome in the general population. Cancer Prev Res. 2011;4(1):9–22. https://doi.org/10.1158/1940-6207.CAPR-10-0262.
Article
Google Scholar
Li Y, Arellano A, Bare L, et al. A multigene test could cost-effectively help extend life expectancy for women at risk of hereditary breast cancer. Value Health. 2017;20(4):547–55. https://doi.org/10.1016/j.jval.2017.01.006.
Article
CAS
PubMed
Google Scholar
Luba D, Disario J, Rock C, et al. Community practice implementation of a self-administered version of PREMM1,2,6 to assess risk for lynch syndrome. Clin Gastroenterol Hepatol. 2018;16(1):49–58. https://doi.org/10.1016/j.cgh.2017.06.038.
Article
PubMed
Google Scholar
Gou F, et al. Use of BRCA mutation test in the U.S. 2004-2014. Prev Med. 2017;52(6):702–9.
Cropper C, Woodson AH, Arun B, Barcenas C, Litton J, Noblin S, et al. Evaluating the NCCN criteria for recommending BRCA1 and BRCA2 genetic testing in patients with breast cancer. J Natl Compr Cancer Netw. 2017;15(6):797–803. https://doi.org/10.6004/jnccn.2017.0107.
Article
CAS
Google Scholar
Gilpin C, Carson N, Hunter A. A preliminary validation of a family history assessment form to select women at risk for breast or ovarian cancer for referral to a genetics center. Clin Genet. 2000;58(4):299–308. https://doi.org/10.1034/j.1399-0004.2000.580408.x.
Article
CAS
PubMed
Google Scholar
Parmigiani G, Chen S, Iversen E Jr. Validity of models for predicting BRCA1 and BRCA2 mutations. Ann Intern Med. 2007;147(7):441–50. https://doi.org/10.7326/0003-4819-147-7-200710020-00002.
Article
PubMed
PubMed Central
Google Scholar
Bellcross C, Lemke A, Paper L, et al. Evaluation of a breast/ovarian cancer genetics referral screening tool in a mammography population. Genet Med. 2009;11(11):783–9. https://doi.org/10.1097/GIM.0b013e3181b9b04a.
Article
PubMed
Google Scholar
Hoskins K, Zwaagstra A, Ranz M. Validation of a tool for identifying women at high risk for hereditary breast cancer in population-based screening. Cancer. 2006;107(8):1769–76. https://doi.org/10.1002/cncr.22202.
Article
PubMed
Google Scholar
Ashton-Prolla P, Giacomazzi J, Schmidt A, et al. Development and validation of a simple questionnaire for the identification of hereditary breast cancer in primary care. BMC Cancer. 2009;9(1):283. https://doi.org/10.1186/1471-2407-9-283.
Article
PubMed
PubMed Central
Google Scholar
Khoury MJ, Feero WG, Valdez R. Family history and personal genomics as tools for improving health in an era of evidence-based medicine. Am J Prev Med. 2010;39(2):184–8. https://doi.org/10.1016/j.amepre.2010.03.019.
Article
PubMed
Google Scholar
U.S. Preventive Services Task Force. Risk assessment, genetic counseling, and genetic testing for BRCA-related cancer: recommendation statement. Am Fam Physician. 2020;101(4):233–8.
Google Scholar
Centers for Medicare & Medicaid Services. Affordable Care Act Implementation FAQs - Set 12 Baltimore: Centers for Medicare & Medicaid Services. https://www.cms.gov/CCIIO/Resources/Fact-Sheets-and-FAQs/aca_implementation_faqs12. Accessed 1 Mar 2021.
Acheson LS, Weisner GL, Zyzanski SJ, Goodwin MA, Stange KC. Family history-taking in community family practice: implications for genetic screening. Genet Medicine. 2000;2(3):180–5. https://doi.org/10.1097/00125817-200005000-00004.
Article
CAS
Google Scholar
Fuller M, Myers M, Webb T, Tabangin M, Prows C. Primary care providers' responses to patient-centered family history. J Genet Couns. 2010;19(1):84–96. https://doi.org/10.1007/s10897-009-9264-6.
Article
PubMed
Google Scholar
Valdez R, Yoon PW, Qureshi N, Green RF, Khoury MJ. Family history in public health practice: a genomic tool for disease prevention and health promotion. Annu Rev Public Health. 2010;31(1):69–87. https://doi.org/10.1146/annurev.publhealth.012809.103621.
Article
PubMed
Google Scholar
Ginsburg O, Ashton-Prolla P, Cantor A, Mariosa D, Brennan P. The role of genomics in global cancer prevention. Nat Rev Clin Oncol. 2020; ePub before press.
Grindedal E, Herabm C, Karsrud I, et al. Current guidelines for BRCA testing of breast cancer patietns are insufficient to detect all mutation carriers. BMC Cancer. 2017;17(1):438. https://doi.org/10.1186/s12885-017-3422-2.
Article
PubMed
PubMed Central
Google Scholar
Hull L, Haas J, Simon S, et al. Provider discussions of genetic tests with U.S. womend at risk for BRCA mutation. Am J Prev Med. 2018;54(2):221–8. https://doi.org/10.1016/j.amepre.2017.10.015.
Article
PubMed
Google Scholar
Acheson L. Fostering applications of genetics in primary care: what will it take? Genet Med. 2003;5(2):63–5. https://doi.org/10.1097/01.GIM.0000056946.67707.67.
Article
PubMed
Google Scholar
Rich EC, Burke W, Heaton CJ, Haga S, Pinsky L, Short P, et al. Reconsidering the family history in primary care. J Gen Intern Med. 2004;19(3):273–80. https://doi.org/10.1111/j.1525-1497.2004.30401.x.
Article
PubMed
PubMed Central
Google Scholar
Green RF, Olney RS. Connecting generations: family history an important tool in pediatrics, public health. AAP News. 2007;28:26.
Google Scholar
Kelly KM, Ferketich AK, Sturm AC, Porter K, Sweet K, Kemp K, et al. Cancer risk and risk communication in urban, lower-income neighborhoods. Prev Med. 2009;48(4):392–6. https://doi.org/10.1016/j.ypmed.2009.01.009.
Article
PubMed
Google Scholar
Kelly KM, Love MM, Pearce KA, Porter K, Barron MA, Andrykowski M. Cancer risk assessment by rural and Appalachian family medicine physicians. J Rural Health. 2009;25(4):372–7. https://doi.org/10.1111/j.1748-0361.2009.00246.x.
Article
PubMed
PubMed Central
Google Scholar
Delikurt T, Williamson G, Anastasiadou V, Skirton H. A systematic review of factors that act as barriers to patient referral to genetic services. Eur J Hum Genet. 2015;23(6):739–45. https://doi.org/10.1038/ejhg.2014.180.
Article
PubMed
Google Scholar
Mikat-Stevens NA, Larson IA, Tarini BA. Primary-care providers' perceived barriers to integration of genetics services: a systematic review of the literature. Genet Med. 2015;17(3):169–76. https://doi.org/10.1038/gim.2014.101.
Article
PubMed
Google Scholar
Mowery DL, Kawamoto K, Bradshaw R, Kohlmann W, Schiffman JD, Weir C, et al. Determining onset for familial breast and colorectal cancer from family history comments in the electronic health record. AMIA Jt Summits Transl Sci Proc. 2019;2019:173–81.
PubMed
PubMed Central
Google Scholar
Gupta S, Provenzale D, Llor X, Halverson AL, Grady W, Chung DC, et al. Genetic/familial high-risk assessment: colorectal, version 2.2019: featured updates to the NCCN guidelines. J Natl Compr Cancer Netw. 2019;17(9):1032–41. https://doi.org/10.6004/jnccn.2019.0044.
Article
Google Scholar
Daly MB, Pilarski R, Yurgelun MB, Berry MP, Buys SS, Dickson P, et al. Genetic/familial high-risk assessment: breast, ovarian, and pancreatic, version 1.2020: featured updates to the NCCN guidelines. J Natl Compr Cancer Netw. 2020;18(4):380–91. https://doi.org/10.6004/jnccn.2020.0017.
Article
Google Scholar
Del Fiol G, Kohlmann W, Bradshaw R, Weir C, Flynn M, Hess R, et al. Standards-based clinical decision support platform to manage patients who meet guideline-based criteria for genetic evaluation of familial cancer. J Clin Oncol Clin Cancer Inform. 2020;4:1–9.
Google Scholar
Hoskovec JM, Bennett RL, Carey ME, DaVanzo JE, Dougherty MJ, Hahn SE, et al. Projecting the supply and demand for certified genetic counselors: a workforce study. J Genet Couns. 2018;27(1):16–20. https://doi.org/10.1007/s10897-017-0158-8.
Article
PubMed
Google Scholar
Attard C, Carmany E, Trepanier A. Genetic counselor workflow study: the times are they a-changin? J Genet Couns. 2019;28(1):130–40. https://doi.org/10.1002/jgc4.1041.
Article
PubMed
Google Scholar
Maiese D, Keehn A, Lyon M, Flannery D, Watson M. Current conditions in medical genetics practice. Genet Med. 2019;21(8):1874–7. https://doi.org/10.1038/s41436-018-0417-6.
Article
PubMed
PubMed Central
Google Scholar
Buchanan A, Rahm A, Williams J. Alternate service delivery models in cancer genetic counseling: a mini-review. Front Oncol. 2016;6:120.
Article
PubMed
PubMed Central
Google Scholar
Kinney AY, Steffen LE, Brumbach BH, Kohlmann W, Du R, Lee JH, et al. Randomized noninferiority trial of telephone delivery of BRCA1/2 genetic counseling compared with in-person counseling: 1-year follow-up. J Clin Oncol. 2016;34(24):2914–24. https://doi.org/10.1200/JCO.2015.65.9557.
Article
PubMed
PubMed Central
Google Scholar
Schwartz MD, Valdimarsdottir HB, Peshkin BN, Mandelblatt JS, Nusbaum R, Huang A-T, et al. Randomized noninferiority trial of telephone versus in-person genetic counseling for hereditary breast and ovarian cancer. J Clin Oncol. 2014;32(7):618–26. https://doi.org/10.1200/JCO.2013.51.3226.
Article
PubMed
PubMed Central
Google Scholar
Sutphen R, Davila B, Shappell H, Holtje T, Vadaparampil S, Friedman S, et al. Real world experience with cancer genetic counseling via telephone. Familial Cancer. 2010;9(4):681–9. https://doi.org/10.1007/s10689-010-9369-y.
Article
PubMed
PubMed Central
Google Scholar
McCuaig J, Armel S, Care M, Volenik A, Kim R, Metcalfe K. Next-generation service delivery: a scoping review of patient outcomes associated with alternative models of genetic counseling and genetic testing for hereditary cancer. Cancers. 2018;10(11):435. https://doi.org/10.3390/cancers10110435.
Article
PubMed Central
Google Scholar
Voils C, Venne V, Weidenbacher H, Sperber N, Datta S. Comparison of telephone and televideo modes for delivery of genetic counseling: a randomized trial. J Genet Couns. 2018;27(2):339–48. https://doi.org/10.1007/s10897-017-0189-1.
Article
PubMed
Google Scholar
Butrick M, Kelly S, Peshkin BN, Luta G, Nusbaum R, Hooker GW, et al. Disparities in uptake of BRCA1/2 genetic testing in a randomized trial of telephone counseling. Genet Med. 2015;17(6):467–75. https://doi.org/10.1038/gim.2014.125.
Article
PubMed
Google Scholar
Steffen L, Du R, Gammon A, Mandelblatt J, Kohlmann W, Lee J, et al. Genetic testing in a population-based sample of breast and ovarian cancer survivors from the REACH randomized trial: cost barriers and moderators of counseling mode. Cancer Epidemiol Biomark Prev. 2017;26(12):1772–80. https://doi.org/10.1158/1055-9965.EPI-17-0389.
Article
Google Scholar
Cohen S, Huziak R, Gustafson S, Grubs R. Analysis of advantages, limitations, and barriers of genetic counseling service delivery models. J Genet Couns. 2016;25(5):1010–8. https://doi.org/10.1007/s10897-016-9932-2.
Article
PubMed
Google Scholar
Green MJ, Peterson SK, Baker MW, Friedman LC, Harper GR, Rubinstein WS, et al. Use of an educational computer program before genetic counseling for breast cancer susceptibility: Effects on duration and content of counseling sessions. Genet Med. 2005;7(4):221–9. https://doi.org/10.1097/01.gim.0000159905.13125.86.
Article
PubMed
PubMed Central
Google Scholar
Green MJ, Peterson SK, Baker MW, Harper GR, Friedman LC, Rubinstein WS, et al. Effect of a computer-based decision aid on knowledge, perceptions, and intentions about genetic testing for breast cancer susceptibility: a randomized controlled trial. JAMA. 2004;292(4):442–52. https://doi.org/10.1001/jama.292.4.442.
Article
CAS
PubMed
PubMed Central
Google Scholar
Trepanier A, Allain D. Models of service delivery for cancer genetic risk assessment and counseling. J Genet Couns. 2014;23(2):239–53. https://doi.org/10.1007/s10897-013-9655-6.
Article
PubMed
Google Scholar
Keshavan M. Key players in the direct-to-consumer lab testing market: MedCityNews; 2016. Available from: https://medcitynews.com/2016/01/20-key-players-in-the-direct-to-consumer-lab-testing-market/.
Google Scholar
van der Wouden C, Carere D. Maitland-van der zee a. consumer perceptions of interactions with primary care providers after direct-to-consumer personal genomic testing. Ann Intern Med. 2016;164(8):513–22. https://doi.org/10.7326/M15-0995.
Article
PubMed
Google Scholar
Burke W, Trinidad S. The deceptive appeal of direct-to-consumer genetics. Ann Intern Med. 2016;164(8):564–5. https://doi.org/10.7326/M16-0257.
Article
PubMed
Google Scholar
Tandy-Connor S, Guiltinan J, Kremply K, LaDuca H, Reineke P, Gutierrez S, et al. False-positive results released by direct-to-consumer genetic tests highlight the importance of clinical confirmation testing for appropriate patient care. Genet Med. 2018;20(12):1515–21. https://doi.org/10.1038/gim.2018.38.
Article
PubMed
PubMed Central
Google Scholar
Hamilton J, Abdiwahab E, Edwards H, Fan M, Jdayani A, Breslau E. Primary care providers' cancer genetic-testing related knowledge, attitudes, and communication behaviors: a systematic review and research agenda. J Gen Intern Med. 2017;32(3):315–24. https://doi.org/10.1007/s11606-016-3943-4.
Article
PubMed
Google Scholar
Doak CC, Doak LG, Root JH. Teaching Patients with Low Literacy Skills. In: Teaching patients with low literacy skills. 2nd ed. Philadelphia: J.B. Lippincott Company; 1996.
Google Scholar
Mayer RE, Dow GT, Mayer S. Multimedia learning in an interactive self-explaining environment: what works in the design of agent-based microworlds. J Educ Psychol. 2003;95(4):806–13. https://doi.org/10.1037/0022-0663.95.4.806.
Article
Google Scholar
Agency for Healthcare Research and Quality. Health literacy universal precautions toolkit 2010. Available from: http://www.ahrq.gov/qual/literacy/index.html.
Google Scholar
Bibault J-E, Chaix B, Nectoux P, Pienkowski A, Guillemase A, Brouard B. Healthcare ex Machina: are conversational agents ready for prime time in oncology? Clin Transl Rad Oncol. 2019;16:55–9. https://doi.org/10.1016/j.ctro.2019.04.002.
Article
Google Scholar
Fitzpatrick K, Darcy A, Vierhile M. Delivering cognitive behavior therapy to young adults with symptoms of depression and anxiety using a fully automated conversational agent (Woebot): a randomized controlled trial. JMIR Mental Health. 2017;4(2):e19. https://doi.org/10.2196/mental.7785.
Article
PubMed
PubMed Central
Google Scholar
Ly K, Ly A-M, Andersson G. A fully automated conversational agent for promoting mental wellbeing: a pilot RCT using mixed methods. Internet Interv. 2017;10:39–46. https://doi.org/10.1016/j.invent.2017.10.002.
Article
PubMed
PubMed Central
Google Scholar
Owens O, Felder T, Tavakoli A, Revels A, Friedman D, Hughes-Halbert C, et al. Evaluation of a computer-based decision aid for promoting informed prostate cancer screening decisions among African American men: iDecide. Am J Health Promot. 2018;33(2):267–78. https://doi.org/10.1177/0890117118786866.
Article
PubMed
Google Scholar
Pereira J, Diaz O. Using health chatbots for behavior change: a mapping study. J Med Syst. 2019;43(5):135. https://doi.org/10.1007/s10916-019-1237-1.
Article
PubMed
Google Scholar
Gordon E, Babu D, Laney D. The future is now: technology’s impact on the practice of genetic counseling. Am J Med Genet. 2018;178(1):15–23. https://doi.org/10.1002/ajmg.c.31599.
Article
PubMed
Google Scholar
Biesecker B. Genetic counseling and the central tenets of practice. Cold Spring Harbor Perspect Med. 2020;10(3):a038968.
Flannery D. Challenges and opportunities for effective delivery of clinical genetic services in the U.S. healthcare system. Curr Opin Pediatr. 2018;30(6):740–5. https://doi.org/10.1097/MOP.0000000000000693.
Article
PubMed
Google Scholar
Rashkin M, Bowes J, Dunaway K, Dhaliwal J, Loomis E, Riffle S, et al. Genetic counseling, 2030: an on-demand service tailored to the needs of a price conscious, genetically literate, and busy world. J Genet Couns. 2019;28(2):456–65. https://doi.org/10.1002/jgc4.1123.
Article
PubMed
Google Scholar
Schmidlen T, Schwartz M, Diloreto K, Kirchner H, Sturm A. Patient assessment of chatbots for the scalable delivery of genetic counseling. J Genet Couns. 2019;28(6):1166–77. https://doi.org/10.1002/jgc4.1169.
Article
PubMed
Google Scholar
Nadarzynski T, MIles O, Cowie A, Ridge D. Acceptability of artificial intelligence (AI)-led chatbot services in healthcare: a mixed methods study. Digital Health. 2019;5:1–12.
Google Scholar
Roberts MC, Kennedy AE, Chambers DA, Khoury MJ. The current state of implementation science in genomic medicine: opportunities for improvement. Genet Med. 2017;19(8):858–63. https://doi.org/10.1038/gim.2016.210.
Article
PubMed
PubMed Central
Google Scholar
Institute of Medicine. Unequal treatment: understanding racial and ethnic disparities in health Care. Washington, DC: National Academy Press; 2002.
Google Scholar
Halbert C, Harrison B. Genetic counseling among minority populations in the era of precision medicine. Am J Med Genet. 2018;178(1):68–74. https://doi.org/10.1002/ajmg.c.31604.
Article
PubMed
Google Scholar
Pierle J, Mahon S. Genetic service delivery models: exploring approaches to care for families with hereditary cancer risk. Clin J Oncol Nurs. 2019;23(1):60–7. https://doi.org/10.1188/19.CJON.60-67.
Article
PubMed
Google Scholar
Hall M, Olopade OI. Confronting genetic testing disparities: knowledge is power. J Am Med Assoc. 2005;293(14):1783–5. https://doi.org/10.1001/jama.293.14.1783.
Article
CAS
Google Scholar
Hall MJ, Olopade OI. Disparities in genetic testing: thinking outside the BRCA box. J Clin Oncol. 2006;24(14):2197–203. https://doi.org/10.1200/JCO.2006.05.5889.
Article
PubMed
Google Scholar
Fisher E, Pratt R, Esch R, Kocher M, Wilson KR, Lee W, et al. The role of race and ethnicity in views toward and participation in genetic studies and precision medicine research in the United States: a systematic review of qualitative and quantitative studies. Mol Genet Gen Med. 2019;8(2):e1099.
McCarthy AM, Bristol M, Domchek SM, Groeneveld PW, Kim Y, Motanya UN, et al. Health care segregation, physician recommendation, and racial disparities in BRCA1/2 testing among women with breast cancer. J Clin Oncol. 2016;34(22):2610–8. https://doi.org/10.1200/JCO.2015.66.0019.
Article
CAS
PubMed
PubMed Central
Google Scholar
Alford SH, McBride CM, Reid RJ, Larson EB, Baxevanis AD, Brody LC. Participation in genetic testing research varies by social group. Public Health Gen. 2011;14(2):85–93. https://doi.org/10.1159/000294277.
Article
Google Scholar
Defining rural population. Available from: https://www.hrsa.gov/rural-health/about-us/definition/index.html. Accessed 26 Feb 2021.
Caldwell JT, Ford CL, Wallace SP, Wang MC, Takahashi LM. Intersection of living in a rural versus urban area and race/ethnicity in explaining access to health care in the United States. Am J Public Health. 2016;106(8):1463–9. https://doi.org/10.2105/AJPH.2016.303212.
Article
PubMed
PubMed Central
Google Scholar
Bhuyan SS, Wang Y, Opoku S, Lin G. Rural-urban differences in acute myocardial infarction mortality: evidence from Nebraska. J Cardiovasc Dis Res. 2013;4(4):209–13. https://doi.org/10.1016/j.jcdr.2014.01.006.
Article
PubMed
Google Scholar
Weaver KE, Geiger AM, Lu L, Case LD. Rural-urban disparities in health status among US cancer survivors. Cancer. 2013;119(5):1050–7. https://doi.org/10.1002/cncr.27840.
Article
PubMed
Google Scholar
Blake K, Moss J, Gaysynsky A, Srinivasan S, Croyle R. Making the case for investment in rural cancer control: an analysis of rural cancer incidence, mortality, and funding trends. Cancer Epidemiol Biomark Prev. 2017;26(7):992–7. https://doi.org/10.1158/1055-9965.EPI-17-0092.
Article
Google Scholar
Henley S, Anderson R, Thomas C, Massetti G, Peaker B, Richardson L. Invasive cancer incidence, 2004-2013, and deaths, 2006-2015, in nonmetropolitan and metropolitan counties - United States. MMWR. 2017;66(14):1–13. https://doi.org/10.15585/mmwr.ss6614a1.
Article
PubMed
PubMed Central
Google Scholar
Zahnd W, James A, Jenkins W, Izadi S, Fogleman A, Steward D, et al. Rural-urban differences in cancer incidence and trends in the United States. Cancer Epidemiol Biomark Prev. 2018;27(11):1265–74. https://doi.org/10.1158/1055-9965.EPI-17-0430.
Article
Google Scholar
George R, Kovak K, Cox SL. Aligning policy to promote cascade genetic screening for prevention and early diagnosis of heritable diseases. J Genet Couns. 2015;24(3):388–99. https://doi.org/10.1007/s10897-014-9805-5.
Article
PubMed
Google Scholar
Villegas C, Haga S. Access to genetic counselors in the southern United States. J Personalized Med. 2019;9(3):33. https://doi.org/10.3390/jpm9030033.
Article
Google Scholar
Radford C, Prince A, Lewis K, Pal T. Factors which impact the delivery of genetic risk assessment services focused on inherited cancer genomics: expanding the role and reach of certified genetics professionals. J Genet Couns. 2014;23(4):522–30. https://doi.org/10.1007/s10897-013-9668-1.
Article
PubMed
Google Scholar
Glasgow R, Klesges L, Dzewaltowski D, Estabrooks P, TM V. Evaluating the impact of health promotion programs: using the RE-AIM framework to form summary measures for decision making involving complex issues. Health Educ Res. 2006;21(5):688–94. https://doi.org/10.1093/her/cyl081.
Article
PubMed
Google Scholar
Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. 1999;89(9):1322–7. https://doi.org/10.2105/AJPH.89.9.1322.
Article
CAS
PubMed
PubMed Central
Google Scholar
National Comprehensive Cancer Network. Breast Cancer Screening and Diagnosis Version I.2017. 2017.
Google Scholar
National Comprehensive Cancer Network. Genetic/Familial High-Risk Assessment: Colorectal Version 3.2017. 2017.
Google Scholar
National Comprehensive Cancer Network. Genetic/familial high-risk assessment: breast/ovarian, Version I 2018 2018.
Google Scholar
National Comprehensive Cancer Network. Colorectal Cancer Screening Version 2.2017 2017.
Google Scholar
National Comprehensive Cancer Network. Prostate Cancer Early Detection Version 2.2017 2017.
Google Scholar
DeMarco T, Peshkin B, Mars B, Tercyak K. Patient satisfaction with cancer genetic counseling: a psychometric anaysis of the genetic counseling satisfaction scale. J Genet Couns. 2004;13(4):293–304. https://doi.org/10.1023/B:JOGC.0000035523.96133.bc.
Article
PubMed
PubMed Central
Google Scholar
Peshkin BN, Kelly S, Nusbaum RH, Similuk M, DeMarco TA, Hooker GW, et al. Patient perceptions of telephone vs. in-person BRCA1/BRCA2 genetic counseling. J Genet Couns. 2015;25:472–82.
Article
PubMed
PubMed Central
Google Scholar
Kaphingst KA, McBride CM, Wade CH, Baxevanis AD, Reid RJ, Larson EB, et al. Patients' understanding of and responses to multiplex genetic susceptibility test results. Genet Med. 2012;14(7):681–7. https://doi.org/10.1038/gim.2012.22.
Article
PubMed
PubMed Central
Google Scholar
Lumish HS, Steinfeld H, Koval C, Russo D, Levinson E, Wynn J, et al. Impact of panel gene testing for hereditary breast and ovarian cancer on patients. J Genet Couns. 2017;26(5):1116–29. https://doi.org/10.1007/s10897-017-0090-y.
Article
PubMed
PubMed Central
Google Scholar
Roberts JS, Gornick MC, Carere DA, Uhlmann WR, Ruffin MT, Green RC. Direct-to-consumer genetic testing: user motivations, decision making, and perceived utility of results. Public Health Genomics. 2017;20(1):36–45. https://doi.org/10.1159/000455006.
Article
PubMed
Google Scholar
Brehaut J, O'Connor A, Wood T, Hack T, Siminoff L, Gordon E, et al. Validation of a decision regret scale. Med Decis Mak. 2003;23(4):281–92. https://doi.org/10.1177/0272989X03256005.
Article
Google Scholar
Underhill-Blazey M, Stopfer J, Chittenden A, Nayak MM, Lansang K, Lederman R, et al. Development and testing of the KnowGene scale to assess general genetic knowledge related to multigene panel testing. Patient Educ Couns. 2019;102(8):1558–64. https://doi.org/10.1016/j.pec.2019.04.014.
Article
PubMed
Google Scholar
Cella D, Hughes C, Peterman A, Chang C-H, Peshkin BN, Schwartz MD, et al. A brief assessment of concerns associated with genetic testing for cancer: the multidimensional impact of Cancer risk assessment (MICRA) questionnaire. Health Psychol. 2002;21(6):564–72. https://doi.org/10.1037/0278-6133.21.6.564.
Article
PubMed
Google Scholar
Fagerlin A, Zikmund-Fisher BJ, Ubel PA, Jankovic A, Derry HA, Smith DM. Measuring numeracy without a math test: development of the subjective numeracy scale. Med Decis Mak. 2007;27(5):672–80. https://doi.org/10.1177/0272989X07304449.
Article
Google Scholar
Chew LD, Griffin JM, Partin MR, Noorbaloochi S, Grill JP, Snyder A, et al. Validation of screening questions for limited health literacy in a large VA outpatient population. J Gen Intern Med. 2008;23(5):561–6. https://doi.org/10.1007/s11606-008-0520-5.
Article
PubMed
PubMed Central
Google Scholar
Norman CD, Skinner HA. eHEALS: the eHealth literacy scale. J Med Internet Res. 2006;8(4):e27. https://doi.org/10.2196/jmir.8.4.e27.
Article
PubMed
PubMed Central
Google Scholar
Parrott R, Silk K, Krieger JR, Harris T, Condit C. Behavioral health outcomes associated with religious faith and media exposure about human genetics. Health Commun. 2004;16(1):29–45. https://doi.org/10.1207/S15327027HC1601_3.
Article
PubMed
Google Scholar
Hesse BW, Nelson DE, Kreps GL, Croyle RT, Arora NK, Rimer BK, et al. Trust and sources of health information: the impact of the internet and its implications for health care providers: findings from the first health information National Trends Survey. Arch Intern Med. 2005;165(22):2618–24. https://doi.org/10.1001/archinte.165.22.2618.
Article
PubMed
Google Scholar
Nelson DE, Kreps GL, Hesse BW, Croyle RT, Willis G, Arora NK, et al. The health information National Trends Survey (HINTS): development, design, and dissemination. J Health Commun. 2004;9(5):443–60. https://doi.org/10.1080/10810730490504233.
Article
PubMed
Google Scholar
Dutta-Bergman M. Trusted online sources of health information: differences in demographics, health beliefs, and health-information orientation. J Med Internet Res. 2003;5(3):e21. https://doi.org/10.2196/jmir.5.3.e21.
Article
PubMed
PubMed Central
Google Scholar
Conway LG, Woodard SR, Zubrod A. Social psychological measurements of COVID-19: coronavirus perceived threat, government response, impacts, and experiences questionnaires; 2020.
Google Scholar
National Cancer Institute. Cancer Moonshot Blue Ribbon Panel Report 2016. Bethesda: National institutes of health, National Cancer Institute; 2016.
Google Scholar