Identifying caregiver-reported modifiable barriers to pediatric oncology clinical trial enrollment and participation

Background: Clinical trial (ClTr) participation is associated with improved childhood cancer outcomes, but significant so- cioeconomic and sociodemographic disparities in trial enrollment exist. Identifying modifiable barriers to participation such as household material hardship (HMH) and limited health literacy (HL), is essential to improving ClTr access. We com- pared differences in caregiver-reported barriers to pediatric oncology ClTr participation across socioeconomic status (SES) and racial/ethnic groups through a nationwide anonymous online survey of caregivers of children with cancer. We also explored associations between caregiver HL, HMH, and barriers to trial participation. Procedures: English- and/or Spanish-speaking caregivers of children diagnosed with cancer in the last 5 years completed the Research Participation Survey – Caregiver (RPS- C) to assess barriers to ClTr participation, the validated Health Literacy Survey-12 (HLS 19-Q12) health literacy assessment, and the WellRx questionnaire measuring HMH. Results: Of the 59 participants, 64% were socioeconomically under-resourced, 52.5% identified as racially/ethnically underrepresented, and 62% reported their child had not participated in a ClTr. Under- resourced caregivers reported higher RPS-C barrier scores than adequately resourced caregivers ( z=3.18, p=0.001). There were no significant differences in barrier scores across underrepresented vs represented racial/ethnic groups ( p=0.203). Lower HL (ρ=-0.557, p90%). Conclusions: Under-resourced SES, HMH, and lower HL were associated with increased barriers to ClTr participation. Caregivers described modifiable barriers that could be targets for intervention to improve ClTr participation and reduce disparities in childhood cancer outcomes. 1 Introduction Despite significant improvements in overall childhood cancer survival rates, sociodemographic disparities in childhood cancer outcomes persist. 1-6 Poverty is associated with disease outcomes in childhood cancers 5-8. Household material hardship (HMH) is a measure of tangible resource needs that has been operationalized and well-studied as a domain of poverty.8-11 HMH impacts nearly 30% of children with cancer at diagnosis 12 and increases over a child’s treatment course 13.Child and adolescent clinical trial (ClTr) participation is associated with improved cancer survival outcomes, likely due to access to the latest treatment regimens, risk stratification, supportive care, and intensive monitoring. 7,8 There are limited data regarding factors contributing to disparities in pediatric ClTr enrollment, especially from the caregivers’ perspective. Further- more, studies exploring disparities in pediatric oncology ClTr enrollment primarily have focused on racial, ethnic, age, and geographic disparities,14-17 which are factors that provide little opportunity for intervention. Therefore, we completed a cross-sectional anonymous survey among caregivers of children with cancer to identify modifiable barriers to ClTr enrollment and participation. Our co-primary study objectives were to (1) compare caregiver-reported barriers to enrollment and participation on ClTrs between under-resourced 1 Posted on 4 Jun 2025 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.174903860.03889595/v1 — This is a preprint and has not been peer-reviewed. Data may be preliminary. SES (household income and HMH groups) and adequately resourced SES groups, and (2) compare barriers between underrepresented racial/ethnic groups and represented racial/ethnic groups. Our secondary ob- jective was to compare HMH and HL across under-resourced and adequately resourced groups and across under-represented and represented groups. Finally, our exploratory aims were to (1) determine relationships between HL, HMH, and barriers to trial participation, (2) describe the most frequently reported barriers and facilitators to ClTr enrollment and participation, and (3) examine differences between barriers experi- enced prior to study and those experienced while on study among caregivers whose child had participated in a ClTr. We hypothesized that caregivers from the socioeconomically under-resourced group and from the racially/ethnically underrepresented group would report increased barriers to ClTr participation for their child compared to their adequately resourced and racially represented counterparts. In addition, we hypoth- esized that under-resourced and under-represented caregivers would have lower health literacy and more HMH than adequately resourced and represented caregivers. 2 Methods This study was a cross-sectional, anonymous online composite of surveys including a demographics ques- tionnaire, the HLS19-Q12 HL assessment, the Caregiver Research Participation Survey, and the Well Rx questionnaire screening for HMH (see Measures section for additional survey details). Surveys were accessed through a SurveyMonkey link in English and in Spanish. English or Spanish-speaking adult caregivers of children ages 0-25 years who were diagnosed with cancer within the past 5 years were eligible to participate. Participants also were required to have internet access in order to complete the electronic surveys. Study recruitment flyers containing the link to the study in text and as a QR code were shared in English and Spanish via websites, social media platforms, and newsletters of advocacy groups, caregiver support groups, local pediatric oncology clinics, and community organizations (Table S1). Flyers also were shared with healthcare professionals throughout the United States, the Children’s Oncology Group (COG) Diversity and Health Disparities Committee, and the Therapeutic Advances in Childhood Leukemia & Lymphoma (TACL) Health Disparities Working Group. The composite survey was active for four months (August 2024- December 2024). With unequal sample sizes with a 2:1 ratio of adequately resourced versus under-resourced groups and represented versus underrepresented groups, recruitment of 39 caregivers would provide 81.8% power to detect an effect size of 1 (mean difference in barriers between groups = 1 SD) with a two-tailed 0.05 significance t-test. We sought to enroll at least 45 caregivers to account for dropouts. To facilitate diverse participant enrollment, we sought to enroll > 40% from an under-resourced group and > 40% from an underrepresented racial group. Once caregivers accessed the survey online, they completed an electronic pre-enrollment eligibility screening and provided informed consent. All measures were administered anonymously; no personally identifiable information was collected. All questions were mandatory to minimize missing data. Respondents who chose not to answer all the questions were not able to proceed with survey completion. All participants were provided with a link to Findhelp throughout the surveys and at the conclusion of the study as a resource to address any identified unmet needs. Findhelp is a vetted national and multilingual database of community support resources by ZIP code addressing social determinants of health (SDOH) including food insecurity, housing instability, access to healthcare, employment and educational support, legal needs, and financial hardship.18 This study was deemed exempt from full IRB review (#IRB002015) due to anonymous, non-invasive, and low risk data collection. 2.3 Sample groups Underserved SES groups were defined by endorsing household income endorsing HMH, specifically food insecurity as measured by the validated Hunger Vital Sign assessment, 19 (2) or by housing instability 20. Per the NIH 1993 Revitalization Act study, underrepresented racial/ethnic groups were defined as people who identify as African American or Black, American Indian and Alaska Native, Hispanic/Latine, Native Hawaiian, Asian, and other Pacific Islander. 21 2 Posted on 4 Jun 2025 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.174903860.03889595/v1 — This is a preprint and has not been peer-reviewed. Data may be preliminary. 2.6 Measures 2.6.1 Sociodemographic Questionnaire Caregivers answered questions about sociodemographic variables including income, HMH, race, ethnicity, sex, ZIP code, neighborhood characteristics (i.e., urban/suburban/rural), and primary language. Caregivers also provided information about their child’s cancer diagnosis and treatment course. 2.6.2 Research Participation Survey – Caregiver Form (RPS-C) The RPS-C is a measure created by the research team and designed with collaborative input from patient advocates who previously underwent treatment for childhood cancer. The team consisted of pediatric oncol- ogists, psychologists, a neuropsychologist, and post-baccalaureate research assistants in the National Cancer Institute’s Pediatric Oncology Branch’s multidisciplinary Patient Engagement Committee. The measure first asks caregivers whether their child participated in a ClTr during their cancer treatment. Using branch logic, those who reported past participation were prompted to answer questions about barriers or challenges they considered prior to enrollment and barriers experienced while participating in the ClTr. If the respondent’s child did not participate in a ClTr during treatment, they noted if they would consider having their child participate in a future ClTr (yes/no). Regardless of their response, they were given the same barrier items as caregivers who had enrolled their child in a ClTr had received about factors that would influence their decision to enroll or not enroll their child in the future. Caregivers of children with past ClTr participa- tion were asked about facilitators that motivated them to enroll their child and benefits the child or family experienced while on study. Questions about barriers and facilitators were answered on a 1-5 Likert scale (1 = not at all true, 5 = very true). The barriers score was calculated by averaging the raw scores across all barrier items in accordance with established methods for analyzing Likert scale data. 22,23 Respondents additionally were able to list other barriers not described in the survey through an open-ended question. Higher RPS-C barriers scores indicated more barriers to CLTr enrollment and participation. The RPS-C barriers scores demonstrated good internal reliability in our sample of caregivers whose children had enrolled in a ClTr (prior to enrollment α = 0.844, while on study α = 0.885) as well as those who had not previously enrolled in a ClTr ( α = 0.818). Facilitator scores also demonstrated strong reliability ( α = 0.862). 2.6.3 Health Literacy Survey-12 (HLS 19-Q12) The HLS 19-Q12 is a 12-item validated measure of HL available in English and Spanish that utilizes a 1-5 Likert scale (1=very easy, 4=very difficult, 5=don’t know) to assess participants’ comfort “finding, assessing, and utilizing health services and health information.”24 For example, respondents are asked how easy or hard it would be to judge the advantages and disadvantages of treatment, follow their doctor’s advice, and make decisions about their health and wellbeing. A total score is obtained by taking the mean of all items and standardizing them to a 0-100 scale. Additionally, scores are categorized as Excellent ( >83.33), Sufficient (66.67 to 83.33), Problematic (50 to < 66.67), or Inadequate (<50). The HLS 19-Q12 exhibited strong internal reliability in our sample ( α = 0.92). 2.6.4 WellRx Screening Tool The WellRx is a 13-item screening tool widely utilized in healthcare settings among English and Spanish- speaking individuals to assess for HMH that may impact families across four domains: food security, economic stability, education, and neighborhood/physical environment. The measure employs yes/no items to assess HMH and recent health services utilization.25 While there is not a validated method of scoring this measure, we chose to sum items 1-8 to calculate a composite score, with higher scores indicating more HMH. Items 9-13 ask about healthcare utilization and unmet needs beyond the scope of HMH and therefore were not included in analyses. This abbreviated WellRx (items 1-8) exhibited strong internal reliability in our sample (α = 0.80). 2.8 Data Analysis Data were cleaned using R 26 and analyzed using SPSS version 29. 27 Descriptive statistics were calculated 3 Posted on 4 Jun 2025 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.174903860.03889595/v1 — This is a preprint and has not been peer-reviewed. Data may be preliminary. for all variables. Results of the Shapiro-Wilk test for normality indicated that some variables were not normally distributed (e.g., RPS-C barrier scores among caregivers whose children had not been on a past ClTr, WellRx Sum; p s < 0.05). Therefore, nonparametric tests were used in relevant analyses. Because the same barrier items were given to caregivers regardless of whether their child participated in a ClTr, past ClTr participation was examined as a covariate in exploratory analyses. To analyze our primary and secondary objectives, we used Independent Samples t-test or Mann Whitney U tests. To analyze exploratory objectives, we conducted Pearson or Spearman correlations, Independent Samples t-tests or Mann Whitney U tests, ANCOVA or Quade nonparametric ANCOVA, and the Kruskal-Wallis test to assess relationships between sociodemographic characteristics, HL, and RPS-C composite barrier scores. We computed a paired-samples t-test to examine differences in barriers scores reported prior to enrollment versus while on ClTr. Finally, we calculated descriptive statistics of the RPS-C as a composite score as well as by individual items and subscales. 3 Results 3.1 Caregiver and child demographics Of the 75 eligible participants who consented to the study and answered at least one survey question, 59 (79%) completed all measures (Figure 1). The majority (88%) completed the survey in English. Caregivers were mostly female (80%) and the biological parent of their child (98%). The sample was geographically diverse, representing 15 U.S. states spanning across the country (Figure S1). Over half (64%) of caregivers endorsed HMH and over half (52.5%) of participants identified as an underrepresented race/ethnicity. Most caregivers had private insurance (63%). The median time between survey completion and date of their child’s diagnosis was two years (see Table 1 for detailed demographics). Children of caregivers participating in the study experienced a broad range of cancers, with leukemia being the most frequently reported diagnosis (35%) (Table 1). Most children were ages 1-10 years (48.3%) or 11-18 years (36.2%) at diagnosis. All children were insured either privately (60%) or publicly (40%) and predominantly lived in two-parent households (69%). Over half (62%) had not participated in a ClTr as part of their cancer treatment. 3.2 Descriptive data Among caregivers whose child had participated in a ClTr, mean RPS-C barriers scores prior to enrollment (M = 2.16) were significantly higher than scores reflecting barriers experienced while on ClTr ( M = 1.75; t = 5.95, p < 0.001). The mean HLS19-Q12 score of 66.32 was near the border of Problematic and Sufficient, with 42% of caregivers scoring in the Problematic HL range (Table 2). 3.3 RPS-C scores across SES and racial/ethnic groups Under-resourced caregivers reported higher composite barrier scores ( M = 2.3) than adequately resourced caregivers (M = 1.8,z = 3.18, p = 0.001). In exploratory analyses, this relationship remained significant while covarying for past ClTr participation (F = 5.379, p < 0.001). When looking solely across income categories, composite barrier scores were not significantly different while covarying past trial participation ( $39,535 M = 2.11) ( p > 0.05). No significant differences were observed in composite barrier scores across underrepresented (M = 2.11) and represented (M = 2.14) racial/ethnic groups when comparing the groups directly ( z = -0.326, p = 0.74) or in exploratory analyses covarying past ClTr participation ( F = 0.12,p = 0.73). 3.4 Comparison of WellRx scores across SES and race/ethnicity groups Under-resourced caregivers ( M = 2.39) reported significantly higher composite WellRx scores than ade- quately resourced caregivers (M = 0.19, z = 3.99, p < 0.001). WellRx scores were not significantly different across represented (M = 1.29) and underrepresented ( M = 2.41) racial/ethnic groups ( z = 1.6, p = 0.12). 3.5 Relationship between WellRx scores, HL scores, and RPS-C scores 4 Posted on 4 Jun 2025 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.174903860.03889595/v1 — This is a preprint and has not been peer-reviewed. Data may be preliminary. HL scores were negatively correlated with composite RPS-C barrier scores ( r = -0.506, p < 0.001), meaning lower caregiver HL was associated with increased barriers to ClTr enrollment and participation. Results of the Kruskal-Wallis test indicated significant differences in composite RPS-C barrier scores across HL categories (H = 13.57, p < 0.01). Post-hoc comparisons showed that caregivers with Excellent, Sufficient, and Problematic HL scores had significantly lower barrier scores than those in the Inadequate HL category (all p s 0.05). In terms of WellRx scores, more HMH were associated with higher composite RPS-C barrier scores ( rho = 0.562, p = 0.006). 3.6 Caregiver-reported barriers and facilitators of ClTr participation For caregivers whose children had participated in a ClTr, the most frequently reported barriers identi- fied before enrollment were concerns about adverse treatment effects (77%), concerns about the treatment being adequately studied (77%), and difficulty understanding the study (73%). Once enrolled, the most frequently reported barriers were about potential adverse effects of treatment (82%) and concerns about the treatment being adequately studied (64%), their child receiving a placebo (55%), difficulty paying for food/rent/transportation/bills at home (55%), and lack of childcare or care for another family member (55%). For caregivers whose child had not enrolled on a ClTr, the vast majority worried about their child taking a treatment that had not been well-studied (92%), experiencing side effects (89%), and receiving a placebo (89%, Figure 2). See figures S2-S5 for distribution of RPS-C barriers and facilitators. Nine caregivers provided free-text responses about barriers to trial participation including lack of an available trial, diffi- culty understanding study information, transportation requirements, and insurance barriers. These free-text responses mirrored existing RPS-C items. Regarding facilitators or factors influencing their decision to have their child participate on a trial, caregivers most frequently reported that their child’s oncologist recommended the study (91%) and the opportunity to help medical/research communities learn more about their child’s condition (91%). Four caregivers re- iterated in the free-text responses they were motivated to enroll their child because their child’s oncologist recommended it, there were a lack of other treatment options, and because they believed the treatment would be beneficial and safer for their child. Caregiver-endorsed benefits for their child included receiving treatment (86%) and their child learning more about their cancer (82%). Regarding family benefits, caregivers most frequently reported learning more about their child’s cancer (77%) and meeting other families whose child had a similar diagnosis (64%, Figure S5). 4 Discussion Our findings demonstrate a strong relationship between SES (poverty/HMH) and caregiver-reported barriers to enrolling their child in pediatric oncology ClTrs. Further supporting this relationship, HMH scores were positively correlated with barriers to ClTr enrollment. Additionally, many caregivers identified specific aspects of HMH, such as difficulty affording food, rent, and bills at home as barriers that made it difficult to consider ClTr enrollment and to continue ClTr participation if they did successfully enroll (Figures S2-S4). These findings suggest that poverty and HMH-mediated barriers to accessing pediatric oncology ClTrs may contribute to differential childhood cancer outcomes. Poverty has known associations with adverse outcomes and decreased OS in childhood cancer.7,8,28 Prior studies conducted in healthcare settings have demonstrated that both poverty and HMH are modifiable through linkage to established anti-poverty government measures and community resources,9-11 and that amelioration of poverty and HMH are associated with improvements in childhood health outcomes. 29-32 The COG strongly recommends systematic screening regarding SDOH including HMH and financial strain from diagnosis through survivorship. 33,34 Our findings underscore the importance of such screenings and associated interventions. Future research should prospectively assess whether systematically identifying and providing resources to address HMH diminishes known disparities in ClTr participation and whether it improves childhood cancer outcomes. Our findings additionally elucidate a relationship between caregiver HL and barriers to ClTr enrollment. Importantly, caregivers in the Inadequate HL category had higher barrier scores than each of the other three categories (Problematic, Sufficient, and Excellent), suggesting that even some improvement in HL may help 5 Posted on 4 Jun 2025 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.174903860.03889595/v1 — This is a preprint and has not been peer-reviewed. Data may be preliminary. overcome barriers to clinical trials participation and those with the lowest HL level should be prioritized for intervention. HL is a known modifiable risk factor for health disparities 35 associated with important cancer outcomes such as oral chemotherapy adherence in adult patients 36 and is often lower among those of lower SES, racial and ethnic minorities, and those with limited English proficiency. 37,38 While there is evidence that HL interventions can improve pediatric clinical outcomes and healthcare utilization in other populations,39-41 there is a dearth of literature exploring HL-based interventions within pediatric oncology populations and specifically regarding their impact on ClTr participation. Our study consistently identified caregiver misconceptions about pediatric oncology ClTr methodology as barriers to ClTr participation, such as concerns about their child receiving a placebo instead of treatment. As such, one HL intervention to be studied in the future could focus on provider communication and counseling around pediatric oncology ClTrs as a means of improving caregiver HL. Our study did not identify an association between race/ethnicity and barriers to ClTr participation despite known health disparities among these groups. 16,17 All participants in our underrepresented racial/ethnic group were also socioeconomically under-resourced, which limited our ability to fully delineate the impact of race on caregiver-reported barriers to ClTr participation compared to the impact of poverty/HMH. This pattern is consistent with known complex interactions among race, poverty, and their collective impact on health disparities. 35,42 Additional studies are required to investigate whether and to what extent SES contributes to known disparities in childhood cancer outcomes by race. 42 Strengths of this study include our population’s geographic diversity, spanning 15 U.S. states representative of all regions of the country, and that our study sample was both racially/ethnically and socioeconomi- cally reflective of the populations who have been underrepresented to date in pediatric oncology ClTrs. 43 Methodological strengths include a primary focus on the caregiver perspective, a survey completion rate (79%) congruent with expected online survey completion rates 44 as well as strong internal reliability of the RPS-C, WellRx, and HLS19-Q12 measures. This study also facilitated household-level assessment of poverty and HMH within the pediatric oncology population, which provides opportunity for future implementation and assessment of targeted anti-poverty interventions to reduce childhood cancer health disparities. Study limitations include the potential for self-selection bias by recruiting partially through pediatric oncol- ogy support groups as these caregivers may have been more open to sharing their experiences than caregivers without support group participation. The lack of racially underrepresented caregivers who were adequately resourced highlights a need for broader recruitment in future studies. Additionally, the cross-sectional nature of this study prohibited follow-up to learn how caregiver HMH, HL, and barriers to CT participation evolve over their child’s treatment course; future studies could prospectively follow families from diagnosis through clinical trial decision-making and end of participation with interval assessments of HMH, HL, and barriers. Study surveys only were able to be offered in English and Spanish. Provider-patient language discordance is a known barrier to pediatric oncology CT participation 14,45 suggesting that future studies should assess barriers to CT participation in other languages to better capture these experiences within a population that does not currently have equitable access to pediatric oncology clinical trials. In addition, caution should be used when interpreting results of the RPS-C and the WellRx, since scoring methods for these measures have not been validated. Finally, all participants were living in the U.S. It is unknown how the studied barriers would apply to ClTr’s conducted in other countries. In conclusion, studying a socioeconomically, racially/ethnically, and geographically diverse sample of care- givers of children with cancer demonstrated that low SES as measured by household income and HMH was significantly associated with increased caregiver-reported barriers to pediatric oncology ClTr enrollment and participation. Low caregiver HL and increased HMH also were associated with increased caregiver-reported barriers to ClTr participation. Importantly, modifiable barriers were identified, including understanding trial risks and benefits, HMH, and other SDOH such as missing school/work, transportation barriers, and lack of access to childcare. Further studies are warranted to explore which barriers may provide the most high-impact opportunities for intervention and to prospectively assess whether systematically identifying and addressing HMH, poverty, and caregiver HL can improve known disparities in ClTr enrollment and in 6 Posted on 4 Jun 2025 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.174903860.03889595/v1 — This is a preprint and has not been peer-reviewed. Data may be preliminary. childhood cancer outcomes.

This study would not have been possible without the crucial contributions of participating caregivers, of the NIH Pediatric Oncology Patient Advocates, and of childhood cancer caregiver support groups and community resources including Leukemia and Lymphoma Society, Cactus Cancer Society, Gilda’s Club, Coalition Against Childhood Cancer, ASK Childhood Cancer Foundation, Candlelighters regional chapters, and B+. In addition, this study was supported by the Center for Cancer Research Health Disparities Award at the National Cancer Institute, by the Intramural Program of the National Cancer Institute, National Institutes of Health, and by the Johns Hopkins Hospital Division of Pediatric Oncology. Conflict of Interest Statement None of the authors have any conflicts of interest to disclose. Table 1 Caregiver and child characteristics N % Caregiver Characteristics Socioeconomic Group Under-resourced 38 64% Appropriately resourced 21 46% Endorsed Household Material Hardship 38 64 % Food insecurity 25 43% Housing instability 17 29% Low household income 16 28% Sex Female 47 79.7% Male 12 20.3% Representation in Research Represented 28 47.5% Underrepresented 31 52.5% Race and ethnicity White, non-Hispanic 28 47.5% Black 9 15% White, Hispanic 7 12% Asian American/Pacific Islander 6 10.2% Hispanic (self- reported as race and ethnicity) 6 10.2% American Indian or Alaskan Native 3 5.1% Neighborhood Suburban 31 52.5% Urban 20 33.9% Rural 8 13.6% Primary Language English 49 83.1% Spanish 8 13.6% Other 2 3.4% Child Characteristics Age at Diagnosis (N = 58, Median = 9, SD = 6.8) <1 y 2 3.4% 1-10 y 28 48.3% 11-18 y 21 36.2% 19-25 y 7 12.1% Cancer type 7 Posted on 4 Jun 2025 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.174903860.03889595/v1 — This is a preprint and has not been peer-reviewed. Data may be preliminary. Table 1 Caregiver and child characteristics Leukemia 21 35% B-ALL 16 T-ALL/T-LLy 2 AML 3 Other lymphoma 4 6.7% Neuroblastoma 6 10% Brain tumor 6 10% Ewing Sarcoma 4 6.7% Osteosarcoma 3 5% Rhabdomyosarcoma 2 3.3% Other sarcoma 5 8.3% Germ Cell Tumors 3 5% Hepatoblastoma 2 3.3% Wilm’s Tumor 2 3.3% Other 2 3.3% Cancer Treatments/Outcomes (N > 59 due to combination therapies) Chemotherapy 55 93.2% Resection 28 47.5% Radiotherapy 25 42.4% Immunotherapy 7 11.9% Transplant 6 10.2% Relapse 9 15.3% Clinical trial participation (N =59) Yes 22 38% No 37 62% Child Insurance status Private 35 59% Public 24 41% Types of Public Insurance (N = 24) Medicaid 16 69.6% Medical Assistance 5 21.7% TRICARE 2 8.7% Table 2. Descriptive statistics for study measures Study Variable N Median Mean SD Range Skewness Kurtosis RPS-C Composite Barriers Score a 59 1.98 2.1366 0.59 1.13-4.47 1.186 2.572 RPS-C Barriers subscale: no CT experience b 37 1.94 2.1256 0.61 1.41-4.47 1.662 4.40 RPS-C Barriers subscale: pre-enrollment barriers c 22 2.06 2.1551 0.57 1.13-3.15 0.24 -0.808 RPS-C Barriers subscale: barriers on study d 22 1.67 1.7455 0.56 1-3 0.683 -0.037 RPS-C Facilitators subscale: facilitators on study e 22 2.5 2.5545 0.76 1.4-4.2 0.305 -0.205 WellRx Score 59 0 1.61 2.068 0-7 1.079 0.049 HLS19-Q12 Score 53 f 66.67 66.32 18.69 19.44-100 -0.305 0.201 Excellent Health Literacy ( >83.33) 9 Sufficient Health Literacy (66.67 to 83.33) 13 Inadequate Health Literacy (50 to <66.67) 9 Problematic Health Literacy (50 to <66.67) 22 8 Posted on 4 Jun 2025 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.174903860.03889595/v1 — This is a preprint and has not been peer-reviewed. Data may be preliminary. a Scores reflect barriers experienced prior to enrollment among caregivers whose child had been on a CT and barriers expressed by caregivers whose did not enroll their child on a CT. b Scores reflect anticipated barriers to enrollment expressed by caregivers whose child had not been on a CT. c Scores reflect barriers experienced prior to enrollment among caregivers whose child had been on a CT. d Scores represent barriers experienced during trial participation. e Scores represent facilitators and reasons for enrollment among caregivers whose child had been on a CT. f Per HLS19-Q12 scoring instructions, scores are invalidated if caregivers provide “I don’t know” responses on > 20% of the items (n = 6/59 caregivers). Figure 1: Study consort diagram 9 Posted on 4 Jun 2025 — The copyright holder is the author/funder. All rights reserved. No reuse without permission. — https://doi.org/10.22541/au.174903860.03889595/v1 — This is a preprint and has not been peer-reviewed. Data may be preliminary. https://www.findhelp.org/

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