This study assesses racial and ethnic differences in trust in medical researchers and genome-sequencing knowledge among patients with idiopathic dilated cardiomyopathy.
Key Points
Question
What is the level of genetic knowledge and trust in medical researchers among Hispanic participants, non-Hispanic Black participants, and non-Hispanic White participants in a cardiovascular genetic study?
Findings
In this cross-sectional study of 1121 patients with dilated cardiomyopathy, the genome-sequencing knowledge level was lower in Hispanic and non-Hispanic Black patients than non-Hispanic White patients. Trust in medical researchers was lowest in non-Hispanic Black patients; a higher trust level was associated with a higher level of genome-sequencing knowledge within racial and ethnic groups.
Meaning
Large racial and ethnic differences in levels of genomic knowledge and trust in researchers were observed among patients with dilated cardiomyopathy in this study.
Abstract
Importance
Cardiovascular disease contributes outsized mortality in patients from underrepresented racial and ethnic groups. Understanding levels of trust in medical researchers and knowledge of genome sequencing may help identify barriers to research participation and develop strategies to educate patients about the role of genetics in cardiovascular disease.
Objective
To assess racial and ethnic differences in trust in medical researchers and genome-sequencing knowledge among patients with idiopathic dilated cardiomyopathy and determine the association between trust in medical researchers and genome-sequencing knowledge.
Design, Setting, and Participants
This cross-sectional study conducted by a consortium of 25 US heart failure programs included patients with idiopathic dilated cardiomyopathy defined as left ventricular systolic dysfunction and left ventricular enlargement after excluding usual clinical causes. Enrollment occurred from June 7, 2016, to March 15, 2020.
Main Outcomes and Measures
Percent distributions, means, and associations of genome-sequencing knowledge scores and research trust scores for Hispanic, non-Hispanic Black (hereafter referred to as Black), and non-Hispanic White participants (hereafter referred to as White).
Results
Among 1121 participants, mean (SD) age was 51.6 (13.6) years with 41.4% Black, 8.5% Hispanic, and 43.4% female. After accounting for site effects, the level of genome-sequencing knowledge was lower in Hispanic and Black participants compared with White participants (mean score difference, −2.6; 95% CI, −3.9 to −1.2 and mean score difference, −2.9; 95% CI, −3.6 to −2.2, respectively). The level of trust in researchers was lowest in Black participants (mean score, 27.7), followed by Hispanic participants (mean score, 29.4) and White participants (mean score, 33.9). Racial and ethnic differences remained after adjusting for education, age at enrollment, duration of dilated cardiomyopathy, and health status. A higher level of trust was associated with a higher level of genome-sequencing knowledge within different racial and ethnic groups.
Conclusions and Relevance
In this cross-sectional study, large racial and ethnic differences in levels of genome-sequencing knowledge and trust in medical researchers were observed among patients with dilated cardiomyopathy. Findings from this study can inform future studies that aim to enhance the uptake of genomic knowledge and level of trust in medical researchers.
Introduction
Because inclusion of diverse populations enhances the ability to identify genomic associations,1 greater emphasis has been placed on increased enrollment of participants from historically underrepresented racial and ethnic groups in cardiovascular and other genetic and genomic studies.2,3 Nevertheless, participation of individuals from diverse racial and ethnic groups, especially Black individuals in the US, has been hindered by long-standing mistrust of researchers, based at least in part on both historic and modern-day scientific misconduct.4,5,6 This history has made successful enrollment of participants from underrepresented racial and ethnic groups in cardiovascular genetic research especially challenging.7
General knowledge about genetics, genetic testing, and genome sequencing may enhance patient understanding of their disease and, thus, likely influence their decision to participate in genetic studies.8,9,10 Research conducted among individuals with cancer or those without established cardiovascular disease revealed that most individuals have limited general knowledge of genomic sequencing, although the level of knowledge was higher among non-Hispanic White individuals than individuals from other racial and ethnic groups.11,12,13,14 To date, to our knowledge, studies of factors that influence genomic sequencing knowledge have not been conducted among patients with established heart disease.
Trust in medical researchers also influences patients’ pursuit of medical care, adherence, health behaviors, and participation in research studies.15,16,17,18,19 In a recent study20 conducted among patients with stroke, decreased knowledge of stroke was found to be associated with mistrust in researchers among Black, Hispanic, Korean, and Chinese older adults in the US. When compared with other racial and ethnic groups, Black individuals in the US have been shown to be more likely to distrust medical research.5,21,22,23 Less is known about how trust in researchers varies by race and ethnicity among patients with established cardiovascular disease. Furthermore, little is known about the association between trust in medical researchers and genome-sequencing knowledge.
Understanding social demographic disparities in general genome-sequencing knowledge, trust in medical researchers, and their association may help identify barriers and opportunities to address concerns about participating in genomic research. Using data from the multisite DCM Precision Medicine Study, this study aimed to: (1) understand racial and ethnic differences in genome-sequencing knowledge and trust in medical researchers among patients with idiopathic dilated cardiomyopathy (DCM) and (2) examine if trust in medical researchers was associated with general genomic knowledge, and if so, whether the association differed by race and ethnicity.
Methods
The DCM Precision Medicine Study
The DCM Precision Medicine Study aimed to test the hypothesis that DCM has substantial genetic basis and to evaluate the effectiveness of a family communication intervention in improving the uptake of family-member clinical screening.24 The study recruited 1265 patients with DCM and nearly 2000 of their relatives.25 The institutional review boards at the Ohio State University and all clinical sites approved the initial study, followed by single institutional review board oversight at the University of Pennsylvania. All participants gave written informed consent. No educational materials regarding genetics or genetic testing were provided to participants beyond what was necessary to obtain informed consent. The consent process was administered by clinical research coordinators who had no genetics training or background. This analysis used the data from all eligible participants 18 years and older who completed a baseline patient life and family survey at the time of enrollment (n = 1121) (Figure 1). Study inclusion and exclusion criteria were previously reported.25 This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guidelines.
Figure 1. DCM Precision Medicine Study Participant Recruitment and Analyses.
Measure of Knowledge About Genome Sequencing
Participants’ knowledge of genome sequencing was assessed by a self-administered survey, using the 11-item questionnaire developed by Kaphingst et al.11 The questionnaire assessed a person’s general knowledge about the purpose of genome sequencing, implications of results, and its affect on disease diagnosis and treatment (eTable 1 in the Supplement). Participants were free to skip questions they did not wish to answer. The measure has 2 subscales: items 1 to 5 indicate knowledge of sequencing limitations (eg, “scientists know how all variants of genes will affect a person’s chances of developing diseases”) and items 6 to 10 indicate knowledge of sequencing benefits (eg, “genome sequencing may find variants in a person’s genes that will increase their chance of developing a disease in their lifetime”). Participants responded to these items on 5-point Likert scales (0 to 4) ranging from strongly agree to strongly disagree. Four negatively worded items were reverse scored so that higher scores reflect better knowledge.
To create total and subscale knowledge scores, responses of strongly agree were assigned a value of 2, agree a value of 1, and the rest a value of 0,11 so each subscale score ranged from 0 to 10.11 The total score was derived from 11 items including the last question “A person’s health habits, such as diet and exercise, can affect whether or not their genes cause diseases” and thus ranged from 0 to 22, with higher scores reflecting better knowledge.
Measure of Trust in Medical Researchers
The level of trust in medical researchers was also measured using the questionnaire developed by Mainous et al.15 Two subscales of trust were measured: participant deception (items 1 to 6) and researcher honesty (items 7 to 11) (eTable 2 in the Supplement). One item (“Most medical researchers would not lie to people to try to convince them to participate in a research study”) was omitted from the original questionnaire. An example of patient deception questions included, “To get people to take part in a study, medical researchers usually do not explain all of the dangers about participation.” An example of research honesty questions included, “Medical researchers are generally honest in telling participants about different treatment options available for their conditions.” Participants responded to these items on 5-point Likert scales (0 to 4) ranging from strongly agree to strongly disagree. Three negatively worded items were reverse scored so that strongly disagree reflected a greater trust in medical researchers.
The total trust score was the sum of all item scores after reversing negatively phrased items, ranging from 0 to 44. To create subscale trust scores, the sum of items for each subscale was multiplied by 2, so the range for participant deception subscale (6 items) ranged from 0 to 48 and the range for researcher honesty (5 items) ranged from 0 to 40.15 Higher scores reflected greater trust in researchers.
Other Demographic and Clinical Information Collected
Structured interviews collected participant demographic and health history information; medical record questionnaires summarized key cardiovascular clinical information.24,25 Race and ethnicity were included because of their relevance for health outcomes and were self-reported by participants using structured race (Native American or Alaska Native, Asian, African American, Native Hawaiian or Pacific Islander, White, more than 1 race, or unknown) and Hispanic ethnicity (yes, no, or unknown) categories. Educational attainment was obtained by asking participants how many years of school they had completed.
Statistical Analysis
Characteristics of the study participants were described with means or percentages by racial and ethnic group (Hispanic, non-Hispanic Black [hereafter referred to as Black], and non-Hispanic White [hereafter referred to as White]). Mean scores of genome-sequencing knowledge and trust in researchers were described both overall and for each subscale, and were compared across subgroups defined by race and ethnicity, age at enrollment, duration of DCM, educational attainment, global health status, and geographic region of participating sites (Northeast, Midwest, South, and West). Continuous variables were categorized if they were not linearly associated with the knowledge and trust scores. Estimated marginal means were obtained using linear mixed models by averaging over the random site effect for all variables except geographic region; in this case, a linear regression model was used due to high correlation with site.
Levels of knowledge subscale scores were also categorized as low (scores of 0 to 5), medium (6 to 9), and high (10).11 The higher knowledge score group reflects better knowledge. The categorized knowledge subscale scores are presented by race and ethnicity in Figure 2. Estimated percentages for subgroups were obtained and compared using generalized linear mixed models with a multinomial outcome, cumulative logit link, and a site random effect.
Figure 2. Percent Distribution of Genome-Sequencing Knowledge Scores Among Patients With Idiopathic Dilated Cardiomyopathy, by Race and Ethnicity.
A, Levels of genome sequencing limitation knowledge were defined low for 0 to 5, medium for scores 6 to 9, high for scores 10. The differences between Hispanic and non-Hispanic White participants (hereafter referred to as White) and between non-Hispanic Black participants (hereafter referred to as Black) and White participants are statistically significant (N = 1066 [87 Hispanic participants, 434 Black participants, and 545 White participants]). Estimated percentages in each ordinal category at a typical site (ie, one at the mean or mode of the random-effects distribution) were obtained using a generalized linear mixed model with a multinomial outcome, cumulative logit link, and a site random effect. Model parameters were estimated using residual participant-specific pseudo likelihood, and the Kenward-Roger corrected covariance matrix was used for inference. Wald P values for differences in these percentages were obtained using the delta method with the standard normal distribution. Percentages may not sum to 100 due to rounding. B, Levels of genome sequencing benefit knowledge were defined low for 0 to 5, medium for scores 6 to 9, high for scores 10. The differences between White and Black participants are statistically significant (N = 1066 [87 Hispanic participants, 434 Black participants, and 545 White participants]). Estimated percentages in each ordinal category were obtained from a generalized linear model with a multinomial outcome and the cumulative logit link that did not include a site random effect because the estimation routine for the generalized linear mixed model converged with an estimated between-site variance on the boundary constraint of 0 when it was included. Wald P values for differences in these percentages were obtained using the delta method with the standard normal distribution. Percentages may not sum to 100 due to rounding.
Linear mixed models with a site random effect were used to examine the association between knowledge score (dependent variable) and trust in medical researchers, after adjustment for confounding variables. As the trust in medical researcher score was not linearly correlated with the knowledge score, it was categorized into 4 quartile groups (less than 25, 25 to 31, 32 to 36, 37 to 44). Confounding variables considered included age at enrollment, sex, race and ethnicity, educational attainment, geographic region, global health status, and duration of DCM. These factors could be independent predictors of genomic knowledge, although race and ethnicity reflect inequities in health, health care, education, and cultural differences in addition to systemic and structural racism.26 The effect modification of race and ethnicity was ascertained by assessing its interaction with the research trust.
All linear mixed model parameters were estimated using restricted maximum likelihood; all tests and Wald 95% CIs used the Kenward-Roger corrected covariance matrix and denominator degrees of freedom. Statistical comparisons were made based on the 2-sided significance level of .05. The Bonferroni correction method was used to adjust for multiple comparisons in subgroup analysis. All analyses were performed in SPSS version 28.0 and SAS/STAT 15.2 software, version 9.4 (TS1M7) of the SAS System for 64-bit Window (SAS Institute).
Results
For the 1121 participants analyzed in this study, mean (SD) age was 51.6 (13.6) years with 41.4% Black, 8.5% Hispanic, and 43.4% female. Hispanic and Black participants were younger at enrollment and at DCM diagnosis, had a lower level of educational attainment, and had poorer health status compared with White participants (Table 1). Black participants also had higher prevalence of comorbidities, such as obesity, hypertension, and diabetes, compared with Hispanic and White participants.
Table 1. Characteristics of the Study Patients With Idiopathic Dilated Cardiomyopathy by Race and Ethnicity.
| Characteristic | No. (%)a | |||
|---|---|---|---|---|
| Total | Hispanic | Non-Hispanic | ||
| Black | White | |||
| Totalb | 1121 (100.0) | 95 (100.0) | 464 (100.0) | 562 (100.0) |
| Age, y | ||||
| At enrollment | ||||
| <45 | 354 (31.6) | 40 (42.1) | 157 (33.8) | 157 (27.9) |
| 45-64 | 562 (50.1) | 42 (44.2) | 251 (51.9) | 279 (49.6) |
| ≥65 | 205 (18.3) | 13 (13.7) | 66 (14.2) | 126 (22.4) |
| At DCM diagnosisc | ||||
| <45 | 590 (52.7) | 61 (64.2) | 256 (55.2) | 273 (48.7) |
| 45-64 | 455 (40.6) | 25 (26.3) | 187 (40.3) | 243 (43.3) |
| ≥65 | 75 (6.7) | 9 (9.5) | 21 (4.5) | 45 (8.0) |
| Sex | ||||
| Female | 487 (43.4) | 39 (41.1) | 202 (43.5) | 246 (43.8) |
| Male | 634 (56.6) | 56 (58.9) | 262 (56.5) | 316 (56.2) |
| Tobacco use (ever), yes | 450 (40.1) | 36 (37.9) | 179 (38.6) | 235 (41.8) |
| Geographic location | ||||
| Northeast | 139 (12.4) | 7 (7.4) | 44 (9.5) | 88 (15.7) |
| Midwest | 382 (34.1) | 5 (5.3) | 134 (28.9) | 243 (43.2) |
| South | 422 (37.6) | 31 (32.6) | 253 (54.5) | 138 (24.6) |
| West | 178 (15.9) | 52 (54.7) | 33 (7.1) | 93 (16.5) |
| Education, yc | ||||
| ≤12 | 424 (38.9) | 49 (53.3) | 207 (46.7) | 168 (30.3) |
| >12 | 665 (61.1) | 43 (46.7) | 236 (53.3) | 386 (69.7) |
| Global health statusc | ||||
| Very good/excellent | 200 (17.9) | 14 (14.7) | 55 (11.9) | 131 (23.5) |
| Good | 392 (35.2) | 34 (35.8) | 143 (31.0) | 215 (38.5) |
| Fair | 377 (33.8) | 35 (36.8) | 188 (40.7) | 154 (27.6) |
| Poor | 146 (13.1) | 12 (12.6) | 76 (16.5) | 58 (10.4) |
| Duration of DCM, median (IQR), yc | 5.2 (10.8) | 4.6 (10.1) | 5.3 (9.2) | 5.2 (12.4) |
| BMI (Obesity ≥30) | 545 (48.6) | 41 (43.2) | 256 (55.2) | 248 (44.1) |
| Hypertension | 593 (52.9) | 53 (55.8) | 307 (66.2) | 233 (41.5) |
| Diabetes | 274 (24.4) | 25 (26.3) | 141 (30.4) | 108 (19.2) |
| Cancer | 63 (5.6) | 5 (5.3) | 21 (4.5) | 37 (6.6) |
| Lung disease | 50 (4.5) | 2 (2.1) | 22 (4.7) | 26 (4.6) |
| Echo LVEF, mean (SD), %c | 23.4 (9.8) | 22.1 (9.6) | 21.9 (8.6) | 24.8 (10.5) |
Abbreviations: BMI, body mass index; DCM, dilated cardiomyopathy; IQR, interquartile range; LVEF, left ventricular ejection fraction.
Percentages may not sum to 100 due to rounding.
Analyses excluded those who did not complete full questionnaires for either trust or genome-sequencing knowledge.
Excluded missing values for age at diagnosis (n = 1), educational attainment (n = 32), duration of DCM (n = 1), global health status (n = 6), and LVEF (n = 6).
Knowledge of Genome Sequencing
Mean total knowledge and sequencing limitation subscale scores were higher in participants 65 years and older than those under 65 years (Table 2). Compared with White participants, Black participants had a lower mean total score (difference, −2.9; 95% CI, −3.6 to −2.2) and lower mean scores on sequencing limitation subscale (difference, −1.9; 95% CI, −2.4 to −1.6) and sequencing benefit subscale (difference, −0.9; 95% CI, −1.2 to −0.5). Hispanic participants also had lower total knowledge mean score (difference, −2.6; 95% CI, −3.9 to −1.2) and sequencing limitation subscale score (difference, −2.0; 95% CI, −2.8 to −1.3) compared with White participants. Participants with more than 12 years of education had higher mean total (difference, 2.2; 95% CI, 1.7-2.8) and subscale knowledge scores (difference, 1.6; 95% CI, 1.2-1.9 for limitation subscale and difference, 0.6; 95% CI, 0.3-0.9 for benefit subscale). Mean total and subscale scores were higher among those reporting good/very good/excellent health status than those reporting fair/poor status. Knowledge limitation scores were lower for participants enrolled in the South compared with other regions. Differences in mean total and subscale scores by subgroups of DCM duration and sex did not reach statistical significance. The association of total knowledge scores with race and ethnicity remained statistically significant after adjustment for educational attainment, age at enrollment, duration of DCM, and global health status (eTable 3 in the Supplement).
Table 2. Levels of Genome-Sequencing Knowledge and Trust in Researchers Among Patients With Idiopathic Dilated Cardiomyopathy by Demographic and Clinical Characteristics.
| Characteristic | Genome-sequencing knowledge | Trust in medical researchers | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Total scorea,b | Sequencinga | Total scorea,c | Participant deceptiona | Researcher honestya | ||||||||
| Limitation | Benefits | |||||||||||
| Mean (SE) | P value | Mean (SE) | P value | Mean (SE) | P value | Mean (SE) | P value | Mean (SE) | P value | Mean (SE) | P value | |
| No. | 1064 | NA | 1066 | NA | 1066 | NA | 1066 | NA | 1066 | NA | 1066 | NA |
| Total | 7.8 (0.25) | NA | 3.0 (0.17) | NA | 4.2 (0.09) | NA | 30.9 (0.43) | NA | 33.3 (0.59) | NA | 28.5 (0.33) | NA |
| Age at enrollment, y | ||||||||||||
| <65 | 7.7 (0.25) | .01 | 2.9 (0.17) | .01 | 4.1 (0.10) | .08 | 30.9 (0.44) | .81 | 33.2 (0.60) | .89 | 28.6 (0.34) | .47 |
| ≥65 | 8.6 (0.38) | 3.5 (0.23) | 4.5 (0.19) | 30.8 (0.65) | 33.4 (0.88) | 28.2 (0.55) | ||||||
| Duration of DCM, yb | ||||||||||||
| <5 | 7.8 (0.29) | .61 | 2.9 (0.18) | .25 | 4.2 (0.12) | .99 | 30.7 (0.49) | .40 | 33.1 (0.66) | .50 | 28.3 (0.39) | .35 |
| ≥5 | 7.9 (0.29) | 3.1 (0.18) | 4.2 (0.12) | 31.1 (0.48) | 33.5 (0.65) | 28.7 (0.39) | ||||||
| Sex | ||||||||||||
| Female | 7.6 (0.30) | .10 | 3.0 (0.19) | .67 | 4.0 (0.13) | .07 | 30.8 (0.51) | .70 | 33.0 (0.69) | .43 | 28.6 (0.41) | .75 |
| Male | 8.0 (0.28) | 3.0 (0.18) | 4.3 (0.11) | 31.0 (0.47) | 33.5 (0.66) | 28.4 (0.37) | ||||||
| Race and ethnicityd | ||||||||||||
| Hispanic | 6.7 (0.54) | <.001 | 2.0 (0.31) | <.001 | 4.0 (0.37)e | <.001 | 29.4 (0.80) | <.001 | 30.8 (1.06) | <.001 | 28.0 (0.73) | <.001 |
| Non-Hispanic | ||||||||||||
| Black | 6.4 (0.28) | 2.1 (0.17) | 3.7 (0.12)e | 27.7 (0.39) | 29.2 (0.53) | 26.2 (0.35) | ||||||
| White | 9.3 (0.26) | 4.0 (0.16) | 4.6 (0.07)e | 33.9 (0.36) | 37.2 (0.49) | 30.6 (0.32) | ||||||
| Educational attainment, yb | ||||||||||||
| ≤12 | 6.6 (0.28) | <.001 | 2.1 (0.17) | <.001 | 3.8 (0.12)e | <.001 | 29.4 (0.49) | <.001 | 31.2 (0.66) | <.001 | 27.6 (0.41) | <.001 |
| >12 | 8.8 (0.24) | 3.7 (0.16) | 4.4 (0.09)e | 32.0 (0.45) | 34.9 (0.60) | 29.3 (0.37) | ||||||
| Global health statusb | ||||||||||||
| Good/very good/excellent | 8.3 (0.28) | .002 | 3.2 (0.18) | .01 | 4.4 (0.11) | .01 | 31.4 (0.48) | .02 | 33.9 (0.65) | .04 | 29.0 (0.39) | .02 |
| Fair/poor | 7.4 (0.28) | 2.8 (0.18) | 4.0 (0.12) | 30.3 (0.49) | 32.6 (0.66) | 28.0 (0.39) | ||||||
| Geographic location | ||||||||||||
| Northeast | 8.3 (0.38) | .001 | 3.4 (0.23) | <.001 | 4.3 (0.19) | .44 | 31.4 (0.65) | <.001 | 34.3 (0.83) | <.001 | 28.6 (0.60) | <.001 |
| Midwest | 8.5 (0.25) | 3.6 (0.15) | 4.3 (0.13) | 32.5 (0.40) | 35.4 (0.50) | 29.5 (0.36) | ||||||
| South | 7.3 (0.22) | 2.6 (0.12) | 4.0 (0.13) | 29.0 (0.38) | 30.5 (0.52) | 27.5 (0.33) | ||||||
| West | 8.3 (0.36) | 3.3 (0.20) | 4.3 (0.20) | 32.0 (0.58) | 35.1 (0.77) | 29.0 (0.53) | ||||||
Abbreviations: DCM, dilated cardiomyopathy; NA, not applicable.
Estimated marginal means were obtained using linear mixed models by averaging over the random site effect, except for the variable geographic location. The scores of genome-sequencing knowledge ranged from 0 to 22 for total scores (11 items) and 0 to 10 for each of the 2 subscales (5 items for each). Higher scores indicate greater knowledge. The scores of trust in researchers ranged from 0 to 44 for total scores (11 items), 0 to 48 for the participant deception subscale (6 items), and 0 to 40 for the researcher honesty subscale (5 items). Higher scores indicate greater trust in medical researchers.
Excluded missing values for total knowledge score (n = 2), duration of DCM (n = 1), educational attainment (n = 27), and global health status (n = 5).
Excluded missing values for duration of DCM (n = 1), educational attainment (n = 30), and global health status (n = 6).
Race and ethnicity were self-reported.
Estimated from generalized estimating equation linear model because G-matrix was nonpositive definite.
Percent distributions of responses to each item in the genome-sequencing knowledge questionnaire are presented in eTable 1 in the Supplement. When asked if they agreed or disagreed with the statement that “Genome sequencing may find variants in a person’s genes that they can pass on to their children,” 16.7% of participants neither agreed nor disagreed and 2.1% disagreed or strongly disagreed. When asked if they agreed or disagreed with the statement that “Genome sequencing may find variants in a person’s genes that will increase their chance of developing a disease in their lifetime,” 19.4% of the participants neither agreed nor disagreed with the statement and 5.3% disagreed or strongly disagreed.
Figure 2 presents the distributions of genome-sequencing knowledge subscale scores (low, medium, and high) by race and ethnicity. Overall, 84.6% of participants with DCM had a low level of knowledge about genome sequencing limitation (Figure 2 A). The percentage with a low level of such knowledge was significantly higher among Hispanic participants (95.8%) and Black participants (93.9%) than White participants (73.5%). As to genome-sequencing benefit (Figure 2 B), 81.0% of the participants had a low level of such knowledge. The percentage with a low level was significantly higher among Black participants (87.4%) compared with White participants (76.1%). The percentage with a low level was higher among Hispanic participants than White participants but the difference did not reach statistical significance.
Trust in Medical Researchers
Table 2 presents mean levels of trust for total and 2 subscales (higher levels imply greater trust) by selected race and ethnicity and other social demographic subgroups. Mean total trust and subscale (participant deception and researcher honesty) scores were lowest in Black participants (27.7, 29.2, and 26.2, respectively), followed by Hispanic participants (29.4, 30.8, and 28.0, respectively), and highest in White participants (33.9, 37.2, and 30.6, respectively). Participants with more than 12 years of education had higher mean total trust score and subscale scores compared with those with 12 years or less of education. Mean total and subscale scores were higher among those reporting good/very good/excellent health status than those reporting fair/poor status. Total and subscale trust scores were lower for participants enrolled in the South compared with other regions. There were no differences in mean total and subscale scores by age at enrollment, duration of DCM, and sex. The racial and ethnic disparities in research trust remained statistically significant after adjusting for educational attainment and other confounding factors (eTable 4 in the Supplement).
Percent distributions of responses to 11 items in the trust questionnaire are presented in eTable 2 in the Supplement. When asked if they agreed with the statement that “Participants should be concerned about being deceived or misled by medical researchers,” 23.9% of participants responded agree or strongly agree. About 9.6% of participants agreed with the statement that “Medical researchers act differently toward minority subjects than toward White subjects.”
Association Between Genome-Sequencing Knowledge and Trust in Medical Researchers
Table 3 presents mean total knowledge scores by trust scores (quartile) with and without adjustment for race and ethnicity and educational attainment. Mean knowledge scores were higher for patients with trust scores at the third and fourth quartiles compared with those at the first quartile (model 1). The differences in mean knowledge scores slightly attenuated but remained statistically significant after controlling for race and ethnicity and educational attainment (models 2 and 3). Adjustments for age at enrollment, DCM duration, and health status resulted in few changes. There was no difference in the association of research trust with genomic knowledge by race and ethnicity in model 3.
Table 3. Association Between Knowledge of Genome Sequencing and Trust in Medical Researchers Among Patients With Idiopathic Dilated Cardiomyopathy.
| Model/variable | Adjusted mean knowledge scorea | Mean difference (95% CI) | P value |
|---|---|---|---|
| Model 1 b (trust score only), quartile | |||
| 1st (<25) | 5.80 | 1 [Reference] | NA |
| 2nd (≥25 to <32) | 6.45 | 0.65 (−0.09 to 1.39) | .50 |
| 3rd (≥32 to <37) | 8.50 | 2.70 (1.94-3.46) | <.001 |
| 4th (37 to 44) | 10.74 | 4.94 (4.20-5.68) | <.001 |
| Model 2 c (trust + race and ethnicity) | |||
| Trust, quartile | |||
| 1st (<25) | 5.92 | 1 [Reference] | NA |
| 2nd (≥25 to <32) | 6.35 | 0.42 (−0.31 to 1.16) | 1.00 |
| 3rd (≥32 to <37) | 8.07 | 2.15 (1.38-2.93) | <.001 |
| 4th (37-44) | 10.14 | 4.22 (3.45-5.00) | <.001 |
| Race and ethnicityd | |||
| Hispanic | 7.12 | −1.55 (−2.64 to −0.46) | .02 |
| Non-Hispanic | |||
| Black | 7.07 | −1.60 (−2.21 to −0.99) | <.001 |
| White | 8.67 | 1 [Reference] | NA |
| Model 3 e (trust + race and ethnicity + education attainment) | |||
| Trust, quartile | |||
| 1st (<25) | 5.95 | 1 [Reference] | NA |
| 2nd (≥25 to <32) | 6.37 | 0.41 (−0.33 to 1.15) | 1.00 |
| 3rd (≥32 to <37) | 7.90 | 1.95 (1.17-2.73) | <.001 |
| 4th (37-44) | 9.99 | 4.04 (3.26-4.82) | <.001 |
| Race and ethnicityd | |||
| Hispanic | 7.23 | −1.24 (−2.31 to −0.17) | .07 |
| Non-Hispanic | |||
| Black | 6.96 | −1.51 (−2.12 to −0.90) | <.001 |
| White | 8.47 | 1 [Reference] | NA |
| Education attainment, y | |||
| ≤12 | 6.83 | 1 [Reference] | NA |
| >12 | 8.28 | 1.45 (0.91-2.00) | <.001 |
Abbreviation: NA, not applicable.
Mean knowledge scores by trust in medical researchers across racial and ethnic groups were modeled using a linear mixed model with a site random effect. Model parameters were estimated using restricted maximum likelihood; all tests and Wald 95% CIs used the Kenward-Roger corrected covariance matrix and denominator degrees of freedom.
Model 1 included fixed effects for trust score quartile only.
Model 2 added fixed effects for race and ethnicity.
Race and ethnicity were self-reported.
Model 3 added a fixed effect for educational attainment to model 2. Adjusting for age at enrollment, health status, and duration of dilated cardiomyopathy did not alter the results (data not shown). There was no interaction between race and ethnicity and trust in medical researchers in model 3.
Discussion
This study identified a large percentage of patients with DCM who lacked general knowledge of genome sequencing capabilities and limitations, correlating with a low level of trust in medical researchers. Levels of knowledge and trust varied significantly by race and ethnicity, with lower level of genome-sequencing knowledge in Hispanic and Black patients and the lowest degree of trust in Black patients. Furthermore, this study indicated that the association between trust in medical researchers and genomic knowledge does not differ by racial and ethnic groups. Findings from this study underscore the importance of gaining trust in medical researchers and inform efforts in patient education about genetics and genomics. As precision medicine expands, increasing patients’ awareness about genetic and genomic knowledge will support informed decision-making and improve the informed consent process in cardiovascular research.
Improving participation of diverse patient populations is essential for genetic and genomic research,1,2,3 as has been emphasized in the All of Us program,27 a large genomic screening study by the US National Institutes of Health. As shown here, higher genomic sequencing knowledge was associated with better research trust across different racial and ethnic groups, suggesting that lower level of trust could affect the uptake of genomic knowledge. Additionally, Hispanic and Black patients tended to have a lower level of general genomic knowledge compared with White patients even after accounting for the effect of research trust and educational attainment. These results imply that routinely incorporating targeted educational discussions about genomic sequencing in the recruitment and consent process may present a first step toward improving informed decision-making about participating in genetic and genomic cardiovascular research in diverse populations.
The overall research trust scores measured in the DCM Precision Medicine Study were higher than the scores reported by the original study that used data from 512 randomly selected adults in South Carolina.15 That study reported an overall mean trust score of 28.7 for White individuals in the US and 24.1 for Black individuals in the US, whereas in the current study the mean total scores were 27.7 for Black individuals in the US and 33.9 for White individuals in the US. Without considering Hispanic origin, the mean overall trust score was 33.3 for White individuals in the US and 27.6 for Black individuals in the US in the current study (data not shown). The differences may be mainly caused by the fact that that the current study was conducted among patients who had already enrolled in the DCM study, and their level of trust in research may be higher than those who were not willing to participate.15 This may also be explained in part due to higher trust levels of participants in their medical physician, who in this study was the one to recruit the participants, which has been shown to correlate with trust in genomic research.28 The decision to participate in a research study is multifactorial and trust in researchers as a whole is different than trust in individual researchers. Racial- and ethnic-specific trust in medical research is a deep and far-reaching issue, reflecting inequities in health and health care due to systemic and interpersonal racism that will take significant effort as a society and time to build back in these communities.29
Limitations
This study has limitations. First, the analyses were based on patients who already consented and participated in the DCM Precision Medicine Study. These patients may have been more likely than those who were not enrolled to have better knowledge of genome sequencing and better trust in medical researchers. Although no specific educational materials regarding genetics or genomics were provided to participants, the general information about the goal of this genetic study stated in the consent form might have helped participants understand the purpose of genome sequencing to the extent, depending on a participant’s educational level. If true, the actual levels of genome-sequencing knowledge and trust in medical researchers could be even lower among all patients with DCM. Second, patients with DCM in this study were recruited from advanced heart failure programs. It is known that such patients tend to be sicker than those in primary and secondary care settings. However, it is unknown if these patients differ from those seen in primary and secondary care settings regarding their knowledge of genome sequencing and trust of medical research. Nevertheless, caution should be made when generalizing the results to patients in primary and secondary care settings. Third, the wording of the genome sequencing knowledge questionnaire may not be easy for participants to understand. Based on our data, however, the Cronbach α is 0.83 for items of sequencing limitation knowledge and 0.87 for genome sequencing benefit knowledge, indicating an acceptable internal consistency of the questions by participants. Fourth, the original trust questionnaire was developed based on a large sample including only 25 African American individuals. Yet our data indicated a good internal consistency of the questionnaire items for Black participants demonstrated by a Cronbach α of .85 for participant deception subscale and .71 for research honesty subscale. Fifth, this cross-sectional study can only demonstrate an association, rather than a causal relationship between genomic knowledge and trust in researchers.
Conclusions
Notwithstanding these limitations, the results from this cross-sectional study may inform the consent process for genetic research aiming to study diverse participants. Advancing genetic research is critical to improving future clinical practice in cardiovascular disease30 and beyond,27 as genome sequencing will likely become an increasingly important part of the clinical evaluation and management of all patients. Ensuring that these research advances are tested and implemented equitably across diverse patient populations will be an essential component of eliminating health disparities.
eTable 1. Distribution of level of genome sequencing knowledge scale items among patients with idiopathic dilated cardiomyopathy
eTable 2. Distribution of level of trust in medical researchers scale items among patients with idiopathic dilated cardiomyopathy
eTable 3. Genome-sequencing knowledge in relation to race and ethnicity: Results from linear mixed effect regression model
eTable 4. Trust in medical researchers in relation to race and ethnicity: Results from linear mixed effect regression model
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eTable 1. Distribution of level of genome sequencing knowledge scale items among patients with idiopathic dilated cardiomyopathy
eTable 2. Distribution of level of trust in medical researchers scale items among patients with idiopathic dilated cardiomyopathy
eTable 3. Genome-sequencing knowledge in relation to race and ethnicity: Results from linear mixed effect regression model
eTable 4. Trust in medical researchers in relation to race and ethnicity: Results from linear mixed effect regression model