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Pilot study of a culturally sensitive intervention to promote genetic counseling for breast cancer risk

BMC Health Services Research volume 22, Article number: 826 (2022) Cite this article

Abstract

Background

Despite the benefits of genetic counseling and testing, uptake of cancer genetic services is generally low and Black/African American (Black) women are substantially less likely to receive genetic services than non-Hispanic White women. Our team developed a culturally sensitive, narrative decision aid video to promote uptake of genetic counseling among Black women at risk for a hereditary breast cancer syndrome that can be incorporated in conjunction with population-based cancer risk assessment in a clinical setting. We report here a pilot study to demonstrate changes in intention to access genetic counseling and intervention satisfaction.

Methods

Black women who were personally unaffected by breast cancer and were recommended for genetic counseling based on family history screening in a mammography center were recruited at the time of the mammogram. A prospective, pre-post survey study design, guided by theoretical constructs, was used to evaluate baseline and immediate post-intervention psychosocial factors, including intention to participate in genetic counseling and intervention satisfaction.

Results

Pilot recruitment goals were met (n = 30). Pre-intervention, 50% of participants indicated that they were extremely likely to make a genetic counseling appointment, compared with 70% post-intervention (p = 0.05). After watching the intervention, 50% of participants indicated that the video changed their mind regarding genetic counseling.

Conclusions

This study demonstrated cultural satisfaction with a decision aid intervention designed to motivate Black women with hereditary breast cancer risk to attend a genetic counseling appointment. Our study showed that intention may be a specific and key construct to target in interventions designed to support decision-making about genetic services. Study results informed the design of a subsequent large scale, randomized implementation study.

Trial registration

Trial registration: Clinicaltrials.govNCT04082117.

Registered September 9, 2019.

Retrospectively registered.

Peer Review reports

Introduction

Carriers of germline mutations in cancer susceptibility genes have up to an 85% lifetime risk of developing breast cancer compared with 12% for the general population [1,2,3]. Cancer genetic risk assessment (CGRA) and genetic counseling allow those with hereditary breast cancer risk to make informed choices about genetic testing and cancer prevention options [4]. Genetic counselors determine whether genetic testing should be performed based on pedigree analysis, provide education and pretest counseling on genetic testing risks and benefits, interpret results of genetic testing in the context of cancer risk counseling, and facilitate cascade testing of at-risk family members [5]. Although genetic counseling and testing are a critical component of personalized cancer risk management, over 90% (~ 10.7 million) of those with hereditary susceptibility to breast and ovarian cancer in the U.S. have yet to be identified and tested [1, 6]. Underutilization is especially problematic for African American women, who are 40% more likely to die from breast cancer than non-Hispanic white (NHW) women. Breast cancers arising in Black women frequently share features that are common among BRCA1-associated cancers, such as younger age of onset, high tumor grade, and negative hormone receptor status, which all contribute to disparate breast cancer mortality rates [3, 7,8,9,10]. The U.S. Preventive Services Task Force (USPSTF) guidelines recommend incorporating assessment of family history into routine primary healthcare in order to identify women at risk for hereditary breast and ovarian cancer so that genetic counseling and testing can be provided for women at risk for hereditary breast cancer syndromes [11, 12].

Despite the benefits of genetic counseling and testing, uptake of cancer genetic services is generally low. This is particularly problematic among Black women, who are approximately 50% less likely to receive genetic services than NHW women due to multi-level barriers, including bias in provider referrals, lack of perceived benefit, barriers to access and lack of awareness of genetic services, and cost [1, 6, 13,14,15,16,17,18,19,20,21,22,23,24,25,26]. Increasing utilization of genetic services for Black women may reduce breast cancer mortality disparities by improving early detection and disease prevention among those at greatest risk. Moreover, it will help curtail the problem of underrepresentation of racially and socioeconomically diverse populations in genetic and genomic research [1, 13, 17, 27]. Our prior work demonstrated that it is feasible to implement a population-based approach to identify candidates for genetic counseling for hereditary breast cancer risk in community health centers located in underserved minority communities. This strategy addresses systemic barriers and improves the rate of provider referrals and access to genetic counseling [28]. However, only 16% of referred women attended a genetic counseling appointment even after receiving a recommendation from their physician, prompting the need for interventions that support informed decision-making about genetic counseling services for underserved minority women.

Decision aids promote positive health behavior change, improve health outcomes and mitigate health literacy barriers. Relatively little work has been conducted to understand the decision-making process among racial/ethnic minority women recommended for genetic counseling for breast cancer risk, or to develop culturally-tailored decision aids to promote uptake of genetic services [27, 29,30,31,32,33]. The tools developed to date are primarily to supplement information provided in genetic counseling sessions, are largely print or telephone-based, are often not developed with input from end-users, do not support familial communication, and for the most part are not targeted to specific cultural groups [27, 30, 34, 35]. To address this need, we developed a culturally sensitive narrative intervention to facilitate decisions about genetic counseling among Black women at risk for hereditary breast cancer syndromes. The intervention was delivered in conjunction with population-based cancer risk assessment in a clinical setting with medically underserved Black women. The decision aid was grounded in a robust theoretical model of health behavior (the Integrative Model of Behavioral Prediction, IMBP), and development of the intervention was informed by Black women with a family history of breast cancer who were recommended for genetic counseling, by breast cancer advocates, and by primary healthcare providers [36]. Here we report findings from a pilot study with the narrative intervention to demonstrate changes in intention to access genetic counseling and intervention satisfaction. We tested the effect of the intervention on measures of knowledge, self-efficacy, normative beliefs, and intentions to engage in genetic counseling.

Methods

Study design

A prospective, pre-post survey study design was used to evaluate baseline and immediate post-intervention intentions, knowledge, and beliefs regarding genetic counseling, as well as to assess satisfaction with the video intervention. The study was registered at Clinicaltrials.gov (NCT04082117) and was approved by the Institutional Review Board at the University of Illinois at Chicago (#2016–1219). All study participants provided written informed consent.

Study population

The study was conducted in a mammography center at a safety net academic medical center in Chicago, IL, between August 2019 and October 2019. Eligibility criteria included: 1) Black women between the ages of 25 to 69 years old presenting for a screening or diagnostic mammogram; 2) no personal history of breast cancer; 3) never attended an appointment with a genetic counselor; 4) underwent breast cancer risk assessment at the time of the mammogram; and 4) were recommended for genetic counseling based on family history of breast and/or ovarian cancer. Formal power calculations are difficult to perform for pilot studies. A sample size of n = 30 is commonly recommended for pilot studies [37]. We followed that practice and enrolled 30 participants.

Breast Cancer risk assessment

The participating mammography center conducted family history screening for hereditary cancer risk as a routine component of the evaluation for all women undergoing screening or diagnostic breast imaging beginning in 2018. Risk assessment was conducted at the time women checked-in for the mammogram using a software application (CancerIQ®) on tablet computers and patient-reported information on family cancer history. Women who met national guideline criteria for genetic counseling referral [38] due to hereditary breast cancer risk were advised by mammography center staff to obtain a referral from their primary care physician (PCP) to the Hereditary Cancer Clinic at our institution. PCPs were notified of the recommendation for genetic counseling referral. Participants for this study were recruited from the group of women who received a recommendation for genetic counseling as a result of the risk assessment performed at the time of their mammogram.

Study recruitment and participation

Radiology technicians gave a study recruitment flyer to all women who were recommended for genetic counseling and briefly described the study to eligible women using a recruitment script. Women who expressed interest in participating in the study were directed to a privacy-protected area in the mammography center where research personnel completed eligibility screening and informed consent. Research personnel then administered a pre-viewing survey, played the six-minute narrative decision aid on a laptop computer for the participant to view, and then administered a post-viewing survey. Women completing all study activities received a stipend for research participation.

Data collection

The pre-viewing survey and post-viewing survey were administered by research personnel using an electronic data capture and management system (REDCap) with an encrypted laptop computer. The initial study protocol included review of the electronic health record 6 months after completion of study recruitment to determine rates of attendance at a genetic counseling session. However, due to clinic restrictions that were initiated in 2020 due to the COVID-19 pandemic, all elective outpatient appointments were cancelled, so the 6-month medical record review was not completed.

Culturally sensitive decision aid to promote genetic counseling

A culturally sensitive, narrative decision aid was developed by the study team to promote uptake of genetic counseling among Black women at risk for a hereditary breast cancer syndrome [36]. Development of the intervention was guided by the IMBP theoretical framework, which asserts that the primary driver of engaging in a health behavior is forming an intention to do so. The process of forming an intention is determined by three cognitive domains (expected outcomes of engaging in the behavior, cultural norms, and self-efficacy beliefs). The IMBP further proposes that the relationship between intention to engage in a health behavior and carrying through on the intention may be impacted by contextual factors [39]. In order to ensure that the intervention is culturally sensitive for Black women, we employed Kreuter’s framework for achieving cultural appropriateness in health promotion programs [40]. Details about intervention design methodology were previously published [36]. Briefly, phase 1 consisted of in-depth, semi-structured interviews and story circles with Black women recommended for genetic counseling by their PCP based on their family history of breast/ovarian cancer [28, 36]. Importantly, the majority of study participants did not attend a genetic counseling session even though it was recommended by their PCP. One-on-one interviews garnered information about motivating and facilitating factors and barriers to genetic counseling attendance. Story circles sought to understand women’s personal and familial experiences related to breast cancer. A script was developed for the narrative intervention based on themes that emerged from in-depth interviews and story circles. Phase 2 consisted of a series of focus groups conducted with three cohorts: an independent group of Black women with a family history of breast cancer who had not undergone genetic counseling and did not participate in one-on-one interviews, primary care providers at a federally qualified health center, and representatives from breast cancer advocacy organizations. Focus groups provided feedback on the script and the final video production. The decision aid that was produced is a six-minute narrative video that tells the story of an Black women recommended for genetic counseling due to the presence of breast cancer in her family. A link to the narrative intervention is provided at the end of this manuscript.

Survey instrument

Original and adapted pre- and post- survey questions, guided by the IMBP theoretical constructs, assessed participants’ intentions, knowledge, perceived normative beliefs, barriers, self-efficacy beliefs, attitudes, and environmental constraints. Intentions regarding genetic counseling attendance were measured with six items. Responses for four of these items were measured on a 5-point likert scale ranging from 1 (extremely likely) to 5 (extremely unlikely); one item was open-ended; and one item was single response. Knowledge about genetic counseling was measured by six true/false adapted items [41]. Perceived normative beliefs were measured with two adapted yes/no items [42]. Barriers to genetic counseling were captured by four original items (yes/no). Self-efficacy beliefs were also measured with four adapted items with responses captured by a 5-point likert scale ranging from 1 (strongly agree) to 5 (strongly disagree) [43, 44]. Attitudes about the importance of genetic counseling were measured with one original item using a 10-point likert scale ranging from 0 (not at all important) to 10 (very important). Environmental constraints were only measured at pre-test since the intervention was not designed to impact these factors and were measured with original six true/false items. Nine original questions assessed satisfaction with the video, with responses captures as a 5-point Likert scale ranging from 1 (either strongly agree or extremely likely to 5 (strongly disagree or extremely or unlikely) [45] or as yes/no response for three questions, and one open-ended response.

Statistical analysis

Demographic characteristics of participants were summarized with descriptive statistics. Survey responses were summarized as frequencies and percentages. Responses of “no” and “not sure” were combined into the same response group. Pre- and post-intervention responses were compared using McNemar’s test for paired data. For data from pre- and post-intervention survey items with a dichotomous response (extremely vs. somewhat likely) p-values were computed using McNemar’s test of marginal homogeneity (symmetric table cell proportions). For data from pre- and post-intervention survey items with a 3 × 3 response (extremely likely, somewhat likely, or neither likely nor unlikely) p-values were computed using the generalization of the McNemar’s test, commonly referred to as generalized McNemar’s test or Stuart-Maxwell test for homogeneity of the marginal distributions [46]. Analyses were conducted using SAS version 9.4 (Cary, NC). A two-sided p-value less than 0.05 was considered statistically significant.

URL link to the intervention: https://youtu.be/_bR81v_nCaM

Results

Thirty Black women enrolled in this study and completed all study activities. The median age among participants was 53 years (interquartile range 48–60); ages ranged from 30 to 69.

Intentions regarding genetic counseling

Before viewing the intervention, 50% of participants indicated that they were extremely likely to make a genetic counseling appointment, compared with 70% of participants after the viewing (p = 0.05) (Table 1). After watching the intervention, 50% of study participants indicated that the video changed their mind regarding genetic counseling (Table 2). Additionally, after viewing the video more than half of participants (63.3%) indicated they would make an appointment to speak with a genetic counselor within the next 6 months.

Table 1 Pre- and Post-intervention Responses to Items Measuring Intentions Regarding Genetic Counseling (n = 30)
Full size table
Table 2 Post-Intervention Satisfaction with the Video Intervention (n = 30)
Full size table

Normative beliefs and barriers

At baseline, 77% of participants believed their family would be interested in learning more about genetic counseling because of cancer in their family (Table 3). This increased to 94% (p = 0.02) following the intervention. Eleven women (37%) indicated that they anticipated experiencing barriers or would have difficulties attending a genetic counseling session before the intervention. There was a decrease in this proportion following the intervention (20%, p = 0.06). Only 7 women responded to the item asking if they believed they could overcome any difficulty they may have in attending a genetic counseling session. At baseline, 3 women responded yes, and 5 women responded yes following the intervention.

Table 3 Pre- and Post-intervention Responses to Items Measuring Normative Beliefs, Barriers, and Self-efficacy (n = 30)
Full size table

Self-efficacy

Before the intervention only 17% of participants were confident that they could pay for genetic counseling services (Table 3). This increased significantly to 40% (p = 0.02) following the intervention. The proportion of women indicating that they were confident that they knew who to call to make an appointment to attend a genetic counseling session increased from nine (30%) to twenty women (67%, p = 0.001) following the intervention.

Environmental constraints

When asked about health care in general, 50% of women indicated they often worry about the cost of medical care and 63% (n = 19) indicated they did not know how much their medical expenses will cost when seeing a doctor. Despite this, 83% (n = 25) indicated they could easily get needed medical care when needed, and over 90% felt comfortable asking their doctor questions and making and getting to and from medical appointments.

Video satisfaction

The majority of participants enjoyed watching the video and felt they could relate to the actors (Table 2). All but one participant indicated they would share the video with family and friends, and 90% (n = 27) of participants thought the video would motivate their loved ones to engage with their doctors about genetic counseling. Four participants indicated they would make changes to the video. Women who did specify suggested changes recommended giving more details about the personal benefit a woman gains from genetic counseling in addition to limitations of genetic counseling.

Knowledge

The intervention was designed to motivate attendance at a genetic counseling session. As expected, knowledge about genetic counseling did not change significantly after viewing the intervention (Table 4).

Table 4 Pre- and Post-intervention Responses to Items Measuring Knowledge of Genetic Counseling
Full size table

Discussion

This study demonstrated changes in intention to attend genetic counseling and satisfaction with a decision aid intervention designed to motivate Black women with hereditary breast cancer risk to attend a genetic counseling appointment. The intervention has now been thoroughly evaluated for cultural appropriateness using qualitative research with focus groups in earlier work [36], and now with a quantitative analysis. Moreover, the intervention significantly increased participants’ intentions to attend a genetic counseling session, which was the primary objective of the intervention. The results of this pilot study underscore the value of multiple qualitative methods (i.e., one-on-one interviews, story circles, and focus groups) and a narrative approach when designing interventions to promote uptake of genomically-informed cancer care in underrepresented racial/ethnic minority groups.

Evidence-based decision aid interventions increase patient knowledge, supplement clinical consultations, improve congruence with patient values, reduce decisional conflicts, and help patients make informed decisions [29, 30, 47, 48]. A recent systematic review that aimed to identify published resources to support decision-making related to BRCA1 and BRCA2 genetic testing in women with breast cancer found that all studies examined (n = 9) described gains in knowledge about hereditary breast cancer, but lacked a theoretical justification for why or how interventions impacted outcomes [30]. Use of a theoretical framework in decision support tool development can inform which theoretical concepts may be most impactful to target in intervention development and inform how and why specific intervention components may or may not impact outcomes [30]. Guided by the IMBP theoretical framework of health behavior, our study showed that intention may be a specific and key construct to target in interventions designed to support decision-making about genetic services. Additionally, the majority of studies that examined the effectiveness of decision support interventions for women with family histories of breast or ovarian cancer were conducted with primarily non-Hispanic white study participants [30, 33, 48] and few studies have assessed factors that influence decision-making regarding genetic counseling utilization among high-risk Black women. The results presented here confirm the relevance of the cognitive domains in the IMBP for racial/ethnic minority women, and the effectiveness of health behavior interventions that are designed to address beliefs mapping to constructs of that theoretical model. Our study also expands understanding of psychosocial factors that may be salient to this group of focus.

This pilot study has limitations. It was intended to inform the design of a subsequent large scale implementation study, and therefore the sample size was relatively small by design. The sample size resulted in sparse data or zero cells for some survey responses, which precluded us from presenting p-values for every pre/post comparison. The intervention was designed for urban Black women with a family history of breast cancer. It is unclear whether this intervention would have the same effect with women from other racial/ethnic groups or in other geographic settings, or with different family cancer histories. Additionally, we were unable to complete planned analysis of genetic counseling uptake at 6 months post-intervention since clinic restrictions resulting from the COVID-19 pandemic prevented women from scheduling a non-urgent appointment. However, it is likely that a multilevel approach that also addresses barriers to scheduling and attending the consultation will be necessary in order to maximize uptake of cancer genetic services among underserved, high-risk Black women. We are testing this hypothesis in a randomized trial (NCT 04378751) that will couple additional evidence-based strategies (patient navigation and transportation assistance) with the decision aid in order to increase utilization of genetic counseling in this patient population. We will also assess implementation feasibility with clinical providers. An additional limitation of this study is that we did not test the effect of the decision aid on diffusion of knowledge about genetic risk and counseling among the social networks of Black women recommended for genetic counseling. This is an important aspect of a population health approach to cancer genetics and risk assessment, since the benefits of population screening for genetic risk can be amplified by identifying and testing at-risk family members of patients found to carry a pathogenic variant (cascade testing). We are addressing this issue in the ongoing randomized trial.

Conclusion

We developed a culturally tailored narrative decision aid that meets the need for cost-effective interventions to facilitate informed decisions on genetic counseling and testing and communication about heritable cancer risks among medically underserved, Black women. Satisfaction with the intervention among the target audience was very high. The intervention increased self-efficacy and intentions to attend genetic counseling among high risk Black women, and it may facilitate cascade testing among at-risk family members. This intervention warrants further investigation as a component of population-based strategies to identify racial/ethnic minority women with hereditary breast cancer risk in an effort to curtail health disparities that may be perpetuated with advances in precision medicine [27, 36, 49].

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

CGRA:

Cancer Genetic Risk Assessment

IMBP:

Integrative Model of Behavioral Prediction

NHW:

Non-Hispanic White

PCP:

Primary Care Provider

USPSTF:

U.S. Preventive Services Task Force

References

  1. Cragun D, Weidner A, Lewis C, Bonner D, Kim J, Vadaparampil ST, et al. Racial disparities in BRCA testing and cancer risk management across a population-based sample of young breast cancer survivors. Cancer. 2017;123(13):2497–505.

    Article  CAS  PubMed  Google Scholar 

  2. Childers CP, Childers KK, Maggard-Gibbons M, Macinko J. National estimates of genetic testing in women with a history of breast or ovarian cancer. J Clin Oncol. 2017;35(34):3800–6.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Monticciolo DL, Newell MS, Moy L, Niell B, Monsees B, Sickles EA. Breast cancer screening in women at higher-than-average risk: recommendations from the ACR. J Am Coll Radiol. 2018;15(3):408–14.

    Article  PubMed  Google Scholar 

  4. American College of Surgeons. National Accreditation Program for Breast Centers Standards Manual: Genetic Evaluation and Management 2018 Available from: https://accreditation.facs.org/accreditationdocuments/NAPBC/Portal%20Resources/2018NAPBCStandardsManual.pdf.

    Google Scholar 

  5. American College of Obstetricians and Gynecologists. Cascade testing: testing women for known hereditary genetic mutations associated with cancer 2018 Available from: https://www.sgo.org/wp-content/uploads/2018/01/CO-727-Cascade-Testing-002.pdf.

    Google Scholar 

  6. Hughes KS. Genetic testing: what problem are we trying to solve? J Clin Oncol. 2017;35(34):3789–91.

    Article  PubMed  Google Scholar 

  7. John EM, Miron A, Gong G, Phipps AI, Felberg A, Li FP, et al. Prevalence of pathogenic BRCA1 mutation carriers in 5 US racial/ethnic groups. JAMA. 2007;298(24):2869–76.

    Article  CAS  PubMed  Google Scholar 

  8. Olopade OI, Fackenthal JD, Dunston G, Tainsky MA, Collins F, Whitfield-Broome C. Breast cancer genetics in African Americans. Cancer. 2003;97(S1):236–45.

    Article  CAS  PubMed  Google Scholar 

  9. Hall MJ, Reid JE, Burbidge LA, Pruss D, Deffenbaugh AM, Frye C, et al. BRCA1 and BRCA2 mutations in women of different ethnicities undergoing testing for hereditary breast-ovarian cancer. Cancer. 2009;115(10):2222–33.

    Article  CAS  PubMed  Google Scholar 

  10. DeSantis CE, Ma J, Sauer AG, Newman LA, Jemal A. Breast cancer statistics, 2017, racial disparity in mortality by state. CA Cancer J Clin. 2017;67(6):439–48.

    Article  PubMed  Google Scholar 

  11. U.S. Preventive Services Task Force. BRCA-Related Cancer:Risk Assessment, Genetic Counseling, and Genetic Testing 2013 Available from: https://www.uspreventiveservicestaskforce.org/Page/Document/RecommendationStatementFinal/brca-related-cancer-risk-assessment-genetic-counseling-and-genetic-testing.

    Google Scholar 

  12. National Comprehensive Cancer Network. Genetic/Familial High-Risk Assessment: Breast and Ovarian 2019 Available from: https://www.nccn.org/professionals/physician_gls/pdf/genetics_screening.pdf.

    Google Scholar 

  13. 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):2610–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Armstrong K, Micco E, Carney A, Stopfer J, Putt M. Racial differences in the use of BRCA1/2 testing among women with a family history of breast or ovarian cancer. JAMA. 2005;293(14):1729–36.

    Article  CAS  PubMed  Google Scholar 

  15. Susswein LR, Skrzynia C, Lange LA, Booker JK, Graham ML, Evans JP. Increased uptake of BRCA1/2 genetic testing among African American women with a recent diagnosis of breast cancer. J Clin Oncol. 2008;26(1):32–6.

    Article  PubMed  Google Scholar 

  16. Levy DE, Byfield SD, Comstock CB, Garber JE, Syngal S, Crown WH, et al. Underutilization of BRCA1/2 testing to guide breast cancer treatment: black and Hispanic women particularly at risk. Genet Med. 2011;13(4):349.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Samimi G, Bernardini MQ, Brody LC, Caga-anan CF, Campbell IG, Chenevix-Trench G, et al. 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):2329–39.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Rana HQ, Cochrane SR, Hiller E, Akindele RN, Nibecker CM, Svoboda LA, et al. A comparison of cancer risk assessment and testing outcomes in patients from underserved vs. tertiary care settings. Journal of. Community Genetics. 2018;9(3):233–41.

    Article  Google Scholar 

  19. Burke W, Culver J, Pinsky L, Hall S, Reynolds SE, Yasui Y, et al. Genetic assessment of breast cancer risk in primary care practice. Am J Med Genet A. 2009;149(3):349–56.

    Article  Google Scholar 

  20. Guerra CE, Sherman M, Armstrong K. Diffusion of breast cancer risk assessment in primary care. J Am Board Fam Med. 2009;22(3):272–9.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Simon MS, Petrucelli N. Hereditary breast and ovarian cancer syndrome : the impact of race on uptake of genetic counseling and testing. Methods Mol Biol. 2009;471:487–500.

    Article  PubMed  Google Scholar 

  22. Schlich-Bakker KJ, ten Kroode HF, Wárlám-Rodenhuis CC, van den Bout J, Ausems MG. Barriers to participating in genetic counseling and BRCA testing during primary treatment for breast cancer. Genet Med. 2007;9(11):766–77.

    Article  PubMed  Google Scholar 

  23. Forman AD, Hall MJ. Influence of race/ethnicity on genetic counseling and testing for hereditary breast and ovarian cancer. Breast J. 2009;15:S56–62.

    Article  PubMed  Google Scholar 

  24. Sheppard VB, Mays D, Tercyak KP, LaVeist T. Medical mistrust influences black women’s level of engagement in BRCA1/2 genetic counseling and testing. J Natl Med Assoc. 2013;105(1):17–22.

    PubMed  Google Scholar 

  25. Jones T, McCarthy AM, Kim Y, Armstrong K. Predictors of BRCA 1/2 genetic testing among black women with breast cancer: a population-based study. Cancer Med. 2017;6(7):1787–98.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Thompson HS, Valdimarsdottir HB, Duteau-Buck C, Guevarra J, Bovbjerg DH, Richmond-Avellaneda C, et al. Psychosocial predictors of BRCA counseling and testing decisions among urban African-American women. Cancer Epidemiol Prev Biomarkers. 2002;11(12):1579–85.

    Google Scholar 

  27. Joseph G, Pasick RJ, Schillinger D, Luce J, Guerra C, Cheng JKY. Information mismatch: cancer risk counseling with diverse underserved patients. J Genet Couns. 2017;26(5):1090–104.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Hoskins KF, Tejeda S, Vijayasiri G, Chukwudozie IB, Remo MH, Shah HA, et al. A feasibility study of breast cancer genetic risk assessment in a federally qualified health center. Cancer. 2018;124(18):3733–41.

    Article  PubMed  Google Scholar 

  29. Stacey D, Légaré F, Lewis K, Barry MJ, Bennett CL, Eden KB, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 2017;4(4):Cd001431.

    PubMed  Google Scholar 

  30. Grimmett C, Pickett K, Shepherd J, Welch K, Recio-Saucedo A, Streit E, et al. Systematic review of the empirical investigation of resources to support decision-making regarding BRCA1 and BRCA2 genetic testing in women with breast cancer. Patient Educ Couns. 2018;101(5):779–88.

    Article  PubMed  Google Scholar 

  31. Lustria MLA, Noar SM, Cortese J, Van Stee SK, Glueckauf RL, Lee J. A Meta-analysis of web-delivered tailored health behavior change interventions. J Health Commun. 2013;18(9):1039–69.

    Article  PubMed  Google Scholar 

  32. Henderson VA, Barr KL, An LC, Guajardo C, Newhouse W, Mase R, et al. Community-based participatory research and user-centered design in a diabetes medication information and decision tool. Prog Community Health Partnersh. 2013;7(2):171–84.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Baroutsou V, Underhill-Blazey ML, Appenzeller-Herzog C, Katapodi MC. Interventions facilitating family communication of genetic testing results and Cascade screening in hereditary breast/ovarian Cancer or lynch syndrome: A Systematic Review and Meta-Analysis. Cancers (Basel). 2021;13(4):925.

    Article  Google Scholar 

  34. Roter D, Ellington L, Erby LH, Larson S, Dudley W. The genetic counseling video project (GCVP): models of practice. Am J Med Genet C: Semin Med Genet. 2006;142c(4):209–20.

    Article  CAS  Google Scholar 

  35. Vadaparampil ST, Malo TL, Nam KM, Nelson A, de la Cruz CZ, Quinn GP. From observation to intervention: development of a Psychoeducational intervention to increase uptake of BRCA genetic counseling among high-risk breast Cancer survivors. J Cancer Educ. 2014;29(4):709–19.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Henderson V, Chukwudozie IB, Comer-Hagans D, Coffey V, Grumbach G, Spencer S, et al. Development of a culturally sensitive narrative intervention to promote genetic counseling among African American women at risk for hereditary breast cancer. Cancer. 2021;127(14):2535–44.

    Article  PubMed  Google Scholar 

  37. Browne RH. On the use of a pilot sample for sample size determination. Stat Med. 1995;14(17):1933–40.

    Article  CAS  PubMed  Google Scholar 

  38. Daly MB, Pal T, Berry MP, Buys SS, Dickson P, Domchek SM, et al. Genetic/familial high-risk assessment: breast, ovarian, and pancreatic, version 2.2021, NCCN clinical practice guidelines in oncology. J Natl Compr Cancer Netw. 2021;19(1):77–102.

    Article  CAS  Google Scholar 

  39. Yzer M. The integrative model of behavioral prediction as a tool for designing health messages. Health Commun Message Design. 2012;2012:21–40.

    Google Scholar 

  40. Kreuter MW, Lukwago SN, Bucholtz RD, Clark EM, Sanders-Thompson V. Achieving cultural appropriateness in health promotion programs: targeted and tailored approaches. Health Educ Behav. 2003;30(2):133–46.

    Article  PubMed  Google Scholar 

  41. Maio M, Carrion P, Yaremco E, Austin JC. Awareness of genetic counseling and perceptions of its purpose: a survey of the Canadian public. J Genet Couns. 2013;22(6):762–70.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Sussner KM, Edwards TA, Thompson HS, Jandorf L, Kwate NO, Forman A, et al. Ethnic, racial and cultural identity and perceived benefits and barriers related to genetic testing for breast cancer among at-risk women of African descent in new York City. Public Health Genomics. 2011;14(6):356–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Sheppard VB, Mays D, LaVeist T, Tercyak KP. Medical mistrust influences black women's level of engagement in BRCA 1/2 genetic counseling and testing. J Natl Med Assoc. 2013;105(1):17–22.

    PubMed  Google Scholar 

  44. Schwarzer R, Jerusalem M. The general self-efficacy scale (GSE). Anxiety Stress Coping. 2010;12(1):329–45.

    Google Scholar 

  45. Sekhon M, Cartwright M, Francis JJ. Acceptability of healthcare interventions: an overview of reviews and development of a theoretical framework. BMC Health Serv Res. 2017;17(1):88.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Yang Z, Sun X, Hardin JW. Testing marginal homogeneity in matched-pair Polytomous data. Drug Inform J. 2012;46(4):434–8.

    Article  Google Scholar 

  47. Elwyn G, O'Connor A, Stacey D, Volk R, Edwards A, Coulter A, et al. Developing a quality criteria framework for patient decision aids: online international Delphi consensus process. BMJ. 2006;333(7565):417–22.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Jabaley T, Underhill-Blazey ML, Berry DL. Development and testing of a decision aid for unaffected women with a BRCA1 or BRCA2 mutation. J Cancer Educ. 2020;35(2):339–44.

    Article  PubMed  Google Scholar 

  49. Cohen SA, Bradbury A, Henderson V, Hoskins K, Bednar E, Arun BK. Genetic counseling and testing in a community setting: quality, access, and efficiency. Am Soc Clin Oncol Educ Book. 2019;39:e34–44.

    Article  PubMed  Google Scholar 

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Acknowledgements

Not Applicable.

Funding

This research was supported by the GUIDE Cancer Research Training Project, through funding provided by the National Cancer Institute of the National Institutes of Health (Award #: P20CA202907/08). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Dr. Hoskins is supported by the Eileen Lindsay Heidrick Professorship in Oncology at the University of Illinois at Chicago. Dr. Henderson is supported through funding from the National Cancer Institute of the National Institutes of Health (Award #: K01CA248852). We also acknowledge a generous financial gift from Dr. Richard and Barbara Warnecke that supported the video production costs of the intervention.

Author information

Authors and Affiliations

  1. Fred Hutchinson Cancer Center, 1100 Fairview Ave. N, Seattle, WA, 98109, USA

    Vida Henderson

  2. University of Illinois Cancer Center, 818 S. Wolcott Ave MC 709 SRH, Chicago, IL, 60612, USA

    Jessica M. Madrigal, Le’ Chaun Kendall & Ifeanyi Beverly Chukwudozie

  3. University of Illinois College of Medicine, 1801 W Taylor St, Chicago, IL, 60612, USA

    Pooja Parekh

  4. Foundation for the National Institutes of Health, 11400 Rockville Pike #600, North Bethesda, MD, 20852, USA

    Jennifer Newsome

  5. University of Texas at Austin, 1501 Red River Street, Austin, TX, 78712, USA

    De Lawnia Comer-Hagans

  6. Governors State University College of Health and Human Services, 1 University Parkway, University Park, IL, 60484, USA

    Vickii Coffey, Giesela Grumbach, Shirley Spencer, Carolyn Rodgers & Catherine Balthazar

  7. University of Illinois at Chicago College of Applied Health Sciences, 1919 W Taylor St MC517, Chicago, IL, 60612, USA

    Ravneet Kaur

  8. University of Illinois Hospital and Health Sciences System, 1801 W Taylor St, Chicago, IL, 60612, USA

    Lara Balay & Tara Maga

  9. Texas State University, 601 University Drive, San Marcos, TX, 78666, USA

    Zo Ramamonjiarivelo

  10. Virginia Commonwealth University Massey Cancer Center, 401 College St Box 980037, Richmond, Virginia, 23298, USA

    Robert Winn

  11. National Institutes of Health, All of Us Research Program, 200 Independence Ave, SW, Washington, DC, 20201, USA

    Karriem Watson

  12. Cornell University College of Human Ecology, Martha Van Rensselaer Hall, Ithaca, NY, 14853, USA

    Angela Odoms-Young

  13. University of Illinois College of Medicine, University of Illinois Hospital and Health Sciences System, 1801 W Taylor St, Chicago, IL, 60612, USA

    Kent F. Hoskins

Authors
  1. Vida Henderson
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  2. Jessica M. Madrigal
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  3. Le’ Chaun Kendall
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  4. Pooja Parekh
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  5. Jennifer Newsome
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  6. Ifeanyi Beverly Chukwudozie
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  7. De Lawnia Comer-Hagans
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  16. Catherine Balthazar
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  17. Robert Winn
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  18. Karriem Watson
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  19. Angela Odoms-Young
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  20. Kent F. Hoskins
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Contributions

VH, KH: intervention development, study design, instrumentation, interpretation of data, writing, editing; JM: data analysis, interpretation; writing, editing; LK, PP: acquisition of data, study implementation; JN, IC, VC, GG, DC, SS, CR, RK, LB, TM, ZR, CB, RW, KW, AO: intervention development, study design. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Vida Henderson.

Ethics declarations

Ethics approval and consent to participate

Approval to conduct this human subjects research was obtained by the University of Illinois at Chicago institutional review board. All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Written informed consent was obtained from all patients for being included in the study.

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Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Supplementary Information

Additional file 1.

Pilot Study Pre and Post Survey.

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Henderson, V., Madrigal, J.M., Kendall, L.C. et al. Pilot study of a culturally sensitive intervention to promote genetic counseling for breast cancer risk. BMC Health Serv Res 22, 826 (2022). https://doi.org/10.1186/s12913-022-08193-x

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Keywords

BMC Health Services Research

ISSN: 1472-6963

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