Abstract
Purpose
To evaluate the impact of a virtual oncology financial and legal navigation (OFLN) intervention on cancer-related financial toxicity (FT) and health-related quality of life (QOL) in pediatric and adolescent and young adult (PAYA) cancer patients and caregivers, as well as to assess the intervention’s acceptability and feasibility.
Methods
A single-arm trial was conducted in a PAYA oncology clinic between March 2024 and May 2025. Pre- and post-intervention surveys included the Comprehensive Score for Financial Toxicity (COST), Patient-Reported Outcomes Measurement Information System global health, anxiety and depression scales, National Comprehensive Cancer Network’s Distress Thermometer, and intervention acceptability, appropriateness, and feasibility of measures.
Results
The majority (36 patients and 88 caregivers) identified as female (73%), non-Hispanic White (85%), rural residents (61%), with incomes above the federal poverty level (71%). Participants reported moderate levels of FT at baseline with a mean COST of 20.9 (SD = 11.14) for patients and 19.3 (SD = 10.12) for caregivers and high levels of anxiety, depression, and distress. Among caregivers, there was a significant (P = .01) post-intervention increase in COST (indicating decreased FT). Almost all patients reported decreases in subjective stress and anxiety (94%) and feeling better prepared to navigate financial/legal issues. Participants rated the intervention highly across implementation outcomes of acceptability (76%), appropriateness (76%), and feasibility (75%), which was also supported by 89% enrollment and 95% retention rates.
Conclusion
Findings demonstrate that virtual OFLN has the potential to increase access to supportive care services, especially in rural communities. Additional research supporting scalability and uptake for widespread implementation is needed.
ClinicalTrials.gov ID: NCT07409662
Introduction
Pediatric and adolescent and young adult (PAYA) cancer patients and their caregivers face a range of compounding factors that contribute to financial toxicity (FT), including major life transitions such as entering higher-education and workforce settings and increased caregiver burden due to taking time off work to take care of patients.1-3 These stressors can lead to financial instability,4 legal complications,5 and psychological distress6 for patients6 and caregivers,7 affecting their overall quality of life (QOL). Oncology financial and legal navigation (OFLN) programs have been designed to help patients and caregivers better manage cancer-related FT.8,9 Via trained navigators, these programs provide structured support and customized financial and legal resources to help resolve needs.
Despite the establishment of financial navigation resources,9 many patients and caregivers still struggle with accessing timely and appropriate navigation support due to logistical constraints (ie, long travel times to treatment centers, inability to take time off work) and limited confidence and knowledge in navigating the intersecting complexities of health care and legal systems.10,11 Whereas financial navigation often focuses on access to financial assistance, legal navigation addresses the full spectrum of health-harming legal needs that can affect a person’s financial stability and access to care.5,7,8 These needs are further exacerbated within rural communities,12,13 where higher rates of poverty14 and lower levels of health literacy15 are compounded by geographic and systemic barriers.16-17
Previously, our team designed and implemented an in-person OFLN intervention within a PAYA oncology setting, wherein we demonstrated improvements in patient and caregiver levels of financial toxicity and QOL.18 This model recognizes that many financial challenges stem from underlying legal barriers. For example, loss of income may result from lack of awareness about work leave protections, whereas unaffordable medical bills may arise from insurance denials or inadequate coverage.19 However, delivering OFLN exclusively in-person may limit accessibility and reach, especially for rural residents. To help overcome these challenges and align with broader shifts in telemedicine health-care delivery, we developed and tested a virtual version of our in-person OFLN intervention in partnership with Triage Cancer—a national nonprofit organization and leading expert in providing virtual financial and legal education, coaching, and navigation to patients, caregivers, and health-care professionals.20 Intervention design and development were guided by our formative evaluation22 informed by the Consolidated Framework for Implementation Research (CFIR). Formative findings emphasized the need for universal access to OFLN regardless of screening outcomes to ensure early identification of hidden or unknown challenges and to promote OFLN standardization and the need for additional virtual OFLN resources to increase accessibility and reach. The purpose of this study was to evaluate the impact of our virtual OFLN intervention on the FT and QOL of PAYA cancer patients and their caregivers as well as assess the intervention’s acceptability and feasibility.
Methods
Study design, setting, and sample
We conducted a single-arm feasibility and acceptability trial of a virtual OFLN intervention in a PAYA oncology and hematology clinic affiliated with an NCI-Designated Comprehensive Cancer Center. Evaluation of the intervention was also guided by CFIR21 to identify multilevel factors influencing implementation under the following CFIR domains: intervention characteristics, characteristics of individuals, inner and outer setting, and process.22
The study clinic sees approximately 80 new PAYA cancer cases (ages 15 to 29 years old) with a substantial rural catchment area. Eligibility criteria included adult patients (aged 18 years and older) with a diagnosis of a PAYA cancer as well as caregivers of patients (any age) with a diagnosis of PAYA cancer; in active treatment (or caregiver of patient in active treatment); and all with the ability to read/write in English. Patients and caregivers were not matched (ie, nondyadic). The clinic includes a psychosocial team consisting of social workers and a financial counselor, who support patients/caregivers with basic support services such as transportation, food, lodging, applying for patient grants, and applying for insurance coverage. All study participants had access to existing clinic resources as part of usual care. Integrating OFLN within existing psychosocial services was central to our feasibility aims and supports our future goals to scale up in community oncology settings. The study protocol received approval from the university’s Institutional Review Board (IRB #85255).
Virtual OFLN intervention and workflow
We employed a standardized recruitment, enrollment, referral, navigation, and follow-up protocol to implement our OFLN. Before study initiation, clinic nurses along with research staff and Triage Cancer navigators received standardized training on the intervention protocol, available OFLN resources, referral pathways, documentation procedures, and communication strategies to promote consistent delivery across participants.23 Regular meetings and communication were maintained among the interdisciplinary study team to address implementation questions, reinforce protocol fidelity, and facilitate coordination.
Eligible patients and caregivers were recruited and enrolled between March 2024 and May 2025 by clinic nurses who collected electronic participant consents and baseline/preintervention REDCap surveys using iPads during clinic visits (see Supplementary File 1). Within 24 hours of enrollment, participants were referred by research staff to Triage Cancer navigators via their online project management platform. Upon receiving the referral, Triage Cancer navigators, consisting of 9 lawyers trained in providing OFLN services,20 reviewed preintervention survey responses to prepare for virtual sessions and sent emails to schedule a virtual session with participants. Nonresponders received a follow-up scheduling email (48 hours later), which was followed by a series of 4 alternating weekly emails and phone calls and ended with a referral back to the nurse recruiting team for follow-up during clinic visits.
During the virtual session, navigators used a standardized set of questions to further explore participant financial/legal needs identified in the presurvey. Based on the discussion, navigators determined personalized, actionable, and self-directed next steps to help participants find resolution to their issues related to work (eg, explaining workplace rights under the ADA or FMLA, helping manage disability insurance benefits), medical bills and finances (eg, appealing insurance denials, helping with bills/debt management), school (eg, applying for school accommodations), family (eg, accessing fertility preservation, childcare), planning ahead (eg, completing estate planning and medical decision-making documents), and applying for health insurance.
Within 24 hours of the virtual session, navigators sent a follow-up email to participants with customized resources and actionable steps that need to be taken to address needs from Triage Cancer’s standardized list of resources corresponding to each category of legal or financial concern. Resources included Triage Cancer’s educational resources, webinars, animated videos, quick guides, checklists, and interactive tools. Navigators also provided referrals to external community resources, such as legal aid, financial assistance, and state or federal government resources as well as to the study clinic social workers and financial counselor.
Postintervention REDCap survey links were emailed to participants 2 weeks after their virtual session, giving participants time to engage with the educational resources and any follow-up tasks. Research staff sent a series of 4 alternating weekly emails and phone calls reminding participants to complete surveys. Participants had the option to follow-up with navigators and request additional sessions, assistance and information.
Data collection and measures
Surveys were administered electronically using REDCap at baseline and 2 weeks after completion of intervention. A detailed description of survey instruments and scoring can be found in Supplementary File 1. Demographic survey questions were collected on age, gender, race, ethnicity, place of residence, education level, occupation, household income, insurance type, cancer type, and caregiver relationship to patient. Participants also selected choices from a prepopulated list of financial/legal concerns. FT was measured across 3 domains: psychological response, material conditions, and coping behaviors. Psychological response was measured using the 11-item Comprehensive Score for Financial Toxicity–Functional Assessment of Chronic Illness Therapy (COST-FACIT) scale.24 Material conditions were measured using 5 items from Section 6 of the Medical Expenditure Panel Survey (MEPS),25 on borrowing money, debt, and bankruptcy. Coping behaviors were also measured using 3 items from MEPS Section 625 to assess changes in cancer care (delaying/foregoing) due to costs. A total FT score was calculated using the 3 domains of FT.13,18,26 The National Comprehensive Cancer Network’s (NCCN) Distress Thermometer and accompanying problem list were used to evaluate psychological distress.27 Health-related QOL was assessed with the Patient-Reported Outcomes Measurement Information System (PROMIS) physical health and mental health subscales from the 10-item Global Health Scale (v.1.2),28 the 4-item PROMIS Emotional Distress—Anxiety Short Form 4a (v.1.0),29 and the 6-item PROMIS Emotional Distress—Depression Short Form 6 a (v.1.0).30 Consistent with the CFIR-guided evaluation, the virtual OFLN’s implementation outcomes were assessed using validated measures of acceptability, appropriateness, and feasibility using the Acceptability of Intervention (AIM), Intervention Appropriateness Measure (IAM), and the Feasibility of Intervention Measure (FIM).31
Data analysis
The responses gained from each tool were summarized at baseline with means, SDs, and the percentages of the highest potential score represented by each mean. The relationships at baseline between FT and PROMIS measures and distress were evaluated using Pearson’s correlation coefficient. Paired t tests were conducted separately for patients and caregivers within the study to assess pre- to post-intervention differences. Paired t tests also were conducted to examine outcomes by rural or urban residence within patients and caregivers. Data analyses were conducted with SPSS Statistics for Windows, v.29 (IBM Corp., Armonk, NY, USA).
Results
Demographic and clinical data
Thirty-six adult cancer patients and 88 caregivers enrolled in the study (Table 1, Figure 1). Fewer patients identified as female (44.1%) compared with caregivers (84.1%). Mean ages for patients and caregivers were 22.1 and 38.9 years, respectively, and most identified as non-Hispanic White (patients, 77.8%; caregivers, 87.5%). Most patients (63.9%) and caregivers (48.9%) reported some postsecondary education and were rural residents (patients, 61.1%; caregivers, 60.2%). Caregivers were predominantly employed full-time (58.0%), and patients were divided between being employed full-time (27.8%) and being a student (27.8%). Half of the patients and 44.3% of caregivers were insured through Medicaid or Medicare. About 1 in 5 participants reported annual incomes at or below the federal poverty level. Patients (41.7%) and caregivers (40.9%) reported finding it difficult or very difficult to live on their present income. Notably, 28% of patients and 46% of caregivers borrowed money/went into debt as a result of paying for cancer treatment, and 5% of all participants filed for bankruptcy. More than 30% of participants reported caregiver sacrifices related to work.
Table 1.
Descriptive summary of baseline demographic variables for patients and caregivers.
| Patients (n = 36) | Caregivers (n = 88) | |
|---|---|---|
| Female, n (%) | 16 (44.4) | 74 (84.1) |
| Age, years, mean (SD); range | 22.11 (4.09); 18 to 38 | 38.91 (9.12); 20 to 59 |
| Race and ethnicity, n (%) | ||
| White, non-Hispanic | 28 (77.8) | 77 (87.5) |
| White, Hispanic | 2 (5.6) | 4 (4.5) |
| Another race or more than one race, non-Hispanic | 4 (11.1) | 3 (3.4) |
| Missing race or ethnicity | 2 (5.6) | 4 (4.5) |
| Education, n (%) | ||
| Less than high school (≤8 years) | 0 | 3 (3.4) |
| Some high school (9 to 11 years) | 1 (2.8) | 7 (8.0) |
| Completed high school or GED | 12 (33.3) | 23 (26.1) |
| Vocational/technical | 2 (5.6) | 7 (8.0) |
| Some college credit | 18 (50.0) | 18 (20.5) |
| College graduate | 3 (8.3) | 18 (20.5) |
| Postgraduate | 0 | 12 (13.6) |
| Rural residence,a n (%) | ||
| Rural (RUCC codes 4 to 9) | 22 (61.1) | 53 (60.2) |
| Urban (RUCC codes 1 to 3) | 14 (38.9) | 35 (39.8) |
| Marital status, n (%) | ||
| Single | 30 (83.3) | 19 (21.6) |
| Married/domestic partner | 6 (16.7) | 50 (56.8) |
| Widowed | 0 | 1 (1.1) |
| Divorced | 0 | 12 (13.6) |
| Separated | 0 | 6 (6.8) |
| Employment status, n (%) | ||
| Employed (full-time) | 10 (27.8) | 51 (58.0) |
| Unemployed | 9 (25.0) | 19 (21.6) |
| Homemaker | 0 | 9 (10.2) |
| Student | 10 (27.8) | 5 (5.7) |
| Disabled | 7 (19.4) | 0 |
| Other | 0 | 4 (4.5) |
| Cancer type | ||
| Leukemia | 14 (38.9) | 42 (47.7) |
| Lymphoma (Hodgkins, non-Hodgkins, B-cell, T-cell) | 6 (16.7) | 13 (14.8) |
| Sarcoma | 8 (22.2) | 8 (9.1) |
| Brain/CNS | 3 (8.3) | 12 (13.6) |
| Kidney/Liver Related | 1 (2.8) | 6 (6.8) |
| PNS (neuroblastoma) | 0 | 5 (5.7) |
| Other (eg, bone cancer, germinoma) | 3 (8.3) | 1 (1.1) |
| More than one cancer type | 1 (2.8) | 1 (1.1) |
| Annual household income, n (%) | ||
| Below $13 000 | 6 (16.7) | 9 (10.2) |
| $13 000 to $20 000 | 1 (2.8) | 6 (6.8) |
| $20 000 to $50 000 | 11 (30.6) | 29 (33.0) |
| $50 000 to $75 000 | 6 (16.7) | 17 (19.3) |
| $75 000 to $100 000 | 2 (5.6) | 11 (12.5) |
| $100 000+ | 4 (11.1) | 11 (12.5) |
| Missing | 6 (16.7) | 5 (5.7) |
| Federal poverty level (FPL), n (%) | ||
| At or below FPL | 7 (19.4) | 18 (20.5) |
| Above FPL | 23 (63.9) | 65 (73.9) |
| Missing | 6 (16.7) | 5 (5.7) |
| Health insurance type, n (%) | ||
| Plan purchased through an employer or union | 14 (38.9) | 37 (42.0) |
| Plan purchased by self or family member | 2 (5.6) | 3 (3.4) |
| Medicare/Medicaid | 18 (50.0) | 39 (44.3) |
| Tricare | 1 (2.8) | 1 (1.1) |
| Other | 1 (2.8) | 3 (3.4) |
| None/Uninsured | 0 | 5 (5.7) |
| Feelings about your household’s present income, n (%) | ||
| Living comfortably | 9 (25.0) | 13 (14.8) |
| Getting by | 12 (33.3) | 39 (44.3) |
| Finding it difficult | 9 (25.0) | 29 (33.0) |
| Finding it very difficult | 6 (16.7) | 7 (8.0) |
| Borrowed money or went into debt, n (%) | 10 (27.8) | 40 (45.5) |
| Filed for bankruptcy, n (%) | 1 (2.8) | 5 (5.7) |
| Worried about having to pay large medical bills, n (%) | 16 (44.4) | 42 (47.7) |
| Unable to cover medical care costs, n (%) | 7 (19.4) | 8 (25.8) |
| Has one or more caregivers, n (%) | 31 (86.1) | – |
| Caregiver types, n (%) | ||
| Parent(s) only | 12 (38.7) | – |
| Spouse/partner only | 4 (12.9) | – |
| Friend only | 3 (9.7) | – |
| Grandparents only | 2 (6.5) | – |
|
9 (29.0) | – |
| Family, unspecified | 1 (3.2) | – |
| Caregiver sacrifices, n (%) | ||
| Take extended paid time off from work | 12 (33.3) | 27 (30.7) |
| Take extended unpaid time off from work | 16 (44.4) | 54 (61.4) |
| Reduced work hours | 14 (38.9) | 43 (48.9) |
| Reduced work duties | 6 (16.7) | 16 (18.2) |
| Changed employment status | 7 (19.4) | 26 (29.5) |
| None of the above | 10 (27.8) | 5 (5.7) |
| Age of patients of caregiver participants, median (range) | – | 9.5 (1 mos - 24 yrs) |
| <1 year, n (%) | – | 1 (1.1) |
| 1 to 10 years | – | 45 (51.1) |
| 11 to 17 years | – | 23 (26.1) |
| 18 to 24 years | – | 19 (21.6) |
Place of residence was categorized using RUCC (Rural-Urban Continuum Codes), using RUCC 4 to 9 to designate rural (nonmetro) residence and RUCC 1 to 3 to designate urban (metro) residence.
Figure 1.
CONSORT flow diagram depicting participant screening, enrollment, receipt of the virtual oncology financial and legal navigation (OFLN) intervention, follow-up assessments, and inclusion in the final analyses.
OFLN delivery and processes
Average time from enrollment to intervention was 13 business days (range 3 to 52 days), with an 89% study enrollment rate and 95% retention rate (Figure 1). Virtual sessions averaged 21 minutes per participant (range 4 to 59 minutes). For navigators, pre-session call preparation took an average of 28 minutes (range 2 minutes to 1.5 hours) and post-session preparation of customized resources and follow-up email took an average of 16 minutes (range 1 to 39 minutes). Among patients, the most common OFLN needs were related to school accommodations (33.3%), applying to college (27.8%), disability insurance (25.0%), fertility preservation (19.4%), understanding health insurance options (19.4%), and applying for financial assistance (19.4%; see Table 2). Caregivers most frequently requested assistance with finding and applying for financial assistance (29.5%), replacing lost wages (27.3%) and paying medical bills (25.0%), debt management (18%), and FMLA (18%). Navigators most frequently referred participants to Triage Cancer quick guides (84%), recorded webinars (69%), cancerfinances.org (56%), checklists and worksheets (52%), AYA (27%) and caregiver (28%) guides and animated videos (27%; see Supplementary File 2).
Table 2.
Descriptive summary of baseline patient- and caregiver-reported outcomes and financial and legal assistance.
| Patients (n = 36) | Caregivers (n = 88) | |
|---|---|---|
| COST-FACITa ≤24, n (%) | 21 (58.3) | 58 (65.9) |
| Distressb >4, n (%) | 16 (44.4) | 54 (61.4) |
| DT Problem List: Practical problems, n (%) | ||
| Insurance/financial | 7 (19.4) | 32 (36.4) |
| Work/school | 12 (33.3) | 23 (26.1) |
| Transportation | 5 (13.9) | 23 (26.1) |
| Food | 6 (16.7) | 17 (19.3) |
| Childcare | 0 | 17 (19.3) |
| Housing | 2 (5.6) | 11 (12.5) |
| Treatment decisions | 4 (11.1) | 5 (5.7) |
| DT Problem List:b Family problems, n (%) | ||
| Family health issues | 6 (16.7) | 32 (36.4) |
| Ability to have children | 9 (25.0) | 4 (4.5) |
| Dealing with children | 2 (5.6) | 20 (22.7) |
| Dealing with partner | 3 (8.3) | 15 (17.0) |
| Most frequently requested financial or legal assistance, n (%) | ||
| Work—Disability insurance | 9 (25.0) | 10 (11.4) |
| Work—Unemployment benefits | 6 (16.7) | 15 (17.0) |
| Work—Accommodation | 5 (13.9) | 12 (13.6) |
| Work—Replacing lost wages | 4 (11.1) | 24 (27.3) |
| Work—FMLA | 3 (8.3) | 16 (18.2) |
| Work—Taking time off | 4 (11.1) | 14 (15.9) |
| School—Accommodation | 12 (33.3) | 15 (17.0) |
| School—Applying to college | 10 (27.8) | 9 (10.2) |
| Medical bills and finances—Financial assistance | 7 (19.4) | 26 (29.5) |
| Medical bills and finances—Debt management | 5 (13.9) | 16 (18.2) |
| Medical bills and finances—Help with bills | 2 (5.6) | 22 (25.0) |
| Health insurance—Understanding options | 7 (19.4) | 7 (8.0) |
| Health insurance—Medicaid | 3 (8.3) | 14 (15.9) |
| Family—Fertility preservation | 7 (19.4) | 6 (6.8) |
| Planning ahead—Medical decision-making | 5 (13.9) | 2 (2.3) |
COST-FACIT = Comprehensive Score for Financial Toxicity–Functional Assessment of Chronic Illness Therapy. The possible score range is 0 to 44, and lower scores indicate greater financial toxicity. ≤24 is an established cutoff indicating greater FT.
NCCN DT = National Comprehensive Cancer Network Distress Thermometer and Problem List. The possible score range is 0 to 10, and higher scores indicate greater distress.
Baseline patient and caregiver outcomes
At baseline, the mean COST-FACIT scores for patients was 20.9 (±11.1) or 47.5% of the maximum score, and the mean for caregivers was 19.3 (±10.1) or 43.9% of the maximum score (Table 3). Mean PROMIS physical health and mental health t-scores were better than average for both patients and caregivers. Mean t-scores for anxiety were 68.6% and 73.0% of the maximum score for patients and caregivers, respectively. For depression, the mean t-scores for patients and caregivers were 63.9% and 66.6% of the maximum score, respectively. For distress, the mean for patients was 3.72 (±2.65), or 37.2% of the maximum score, whereas the mean for caregivers was 5.19 (±2.88), or 51.9% of the maximum score. Caregivers had significantly higher distress (P = .009) and better physical health (P = .02) than patients. There were no significant differences in rural vs urban patients and caregivers in baseline outcomes.
Table 3.
Mean (SD), score range (maximum possible score), and mean as percentage of maximum possible score for baseline outcomes for patients and caregivers.
| Patients (n = 36) Mean (SD); range [maximum possible] <mean as % of maximum> | Caregivers (n = 88) Mean (SD); range [maximum possible] <mean as % of maximum> | |
|---|---|---|
| Total financial toxicity scorea |
|
|
| Financial toxicity: psychological response (COST-FACIT) |
|
|
| Financial toxicity: material conditions |
|
|
| Financial toxicity: coping behaviors |
|
|
| PROMIS Physical Health |
|
|
| PROMIS Mental Health |
|
|
| PROMIS Anxiety |
|
|
| PROMIS Depression |
|
|
| Feelings about your household’s income |
|
|
| Distressb |
|
|
Abbreviations: COST-FACIT = Comprehensive Score for Financial Toxicity–Functional Assessment of Chronic Illness Therapy; NCCN = National Comprehensive Cancer Network; PROMIS = Patient-Reported Outcomes Measurement Information System.
Total Financial Toxicity score includes average of reverse-coded COST-FACIT (so all measures have the same polarity), material condition, and coping behavior scores. Higher scores indicate greater financial toxicity.
NCCN Distress Thermometer. Higher scores indicate greater distress.
Pre- to Post-Intervention changes
Among caregivers, there was a significant pre- to post-intervention increase in COST-FACIT (P = .01; Table 4), indicating a reduction in FT. Patients reported a decrease in physical health (P = .02) and an increase in anxiety (P = .005). When examining outcomes in rural vs urban caregivers, only rural caregivers increased significantly in COST-FACIT (P = .008; Table 5). Rural, but not urban, patients reported a decrease (P = .04) in physical health. In our subjective measure of pre- to post-intervention changes in stress and anxiety, the majority of patients (93.5%) and caregivers (66.2%) strongly agreed or agreed that their stress and/or anxiety decreased because of the intervention (Table 6).
Table 4.
Paired t tests of study outcomes for patients and caregivers.
| Patients (n = 31) |
Caregivers (n = 74) |
|||
|---|---|---|---|---|
| Meana (SD) | Paired t(P) | Meana (SD) | Paired t(P) | |
| Total financial toxicity scoreb | −0.01 (0.23) | −0.18 (.86) | −0.01 (0.19) | −0.57 (.57) |
| Financial toxicity: psychological response (COST-FACIT) | 0.19 (6.59) | 0.16 (.87) | 1.46 (4.87) | 2.59 (.01) |
| Financial toxicity: material conditions | 0.29 (0.94) | 1.72 (.10) | 0.20 (1.19) | 1.46 (.15) |
| Financial toxicity: coping behaviors | −0.26 (1.26) | −1.14 (.27) | 0.00 (0.76) | 0.00 (1.00) |
| Feelings about your household’s income | −0.26 (0.82) | −1.76 (.09) | 0.14 (0.63) | 1.86 (.07) |
| Distressc | 0.29 (2.48) | 0.65 (.52) | −0.41 (2.44) | −1.43 (.16) |
| PROMIS Physical Health | −2.70 (6.34) | −2.37 (.02) | −1.04 (5.35) | −1.67 (.10) |
| PROMIS Mental Health | −1.87 (7.58) | −1.37 (.18) | −0.36 (5.62) | −0.56 (.58) |
| PROMIS Anxiety | 4.44 (8.17) | 3.02 (.005) | −0.63 (7.88) | −0.69 (.50) |
| PROMIS Depression | 2.80 (9.08) | 1.72 (.10) | −0.36 (8.01) | −0.39 (.70) |
Abbreviations: COST-FACIT = Comprehensive Score for Financial Toxicity–Functional Assessment of Chronic Illness Therapy; NCCN = National Comprehensive Cancer Network; PROMIS = Patient-Reported Outcomes Measurement Information System.
Each difference is defined as the preintervention score subtracted from the postintervention score, and average change scores are shown in the table.
Financial toxicity total score includes average of reverse-coded COST-FACIT (so all measures have the same polarity), material condition, and coping behavior scores.
NCCN Distress Thermometer.
Table 5.
Paired t tests of study outcomes for patients and caregivers, rural vs urban residence.
| Patients | Rural (n = 21) |
Urban (n = 10) |
||
|---|---|---|---|---|
| Meana (SD) | Paired t (P) | Meana (SD) | Paired t (P) | |
| Total financial toxicity scoreb | 0.00 (0.24) | 0.02 (.99) | −0.03 (0.23) | −0.35 (.73) |
| Financial toxicity: psychological response (COST-FACIT) | −0.14 (7.49) | −0.09 (.93) | 0.90 (4.41) | 0.65 (.54) |
| Financial toxicity: material conditions | 0.33 (0.80) | 1.92 (.07) | 0.20 (1.23) | 0.51 (.62) |
| Financial toxicity: coping behaviors | −0.29 (1.45) | −0.90 (.38) | −0.20 (0.79) | −0.80 (.44) |
| Feelings about your household’s income | −0.24 (0.89) | −1.23 (.23) | −0.30 (0.68) | −1.41 (.19) |
| Distressc | 0.52 (2.60) | 0.92 (.37) | −0.20 (2.25) | −0.28 (.79) |
| PROMIS Physical Health | −3.48 (7.18) | −2.22 (.04) | −1.07 (3.85) | −0.88 (.40) |
| PROMIS Mental Health | −2.94 (6.65) | −2.03 (.06) | 0.39 (9.22) | 0.13 (.90) |
| PROMIS Anxiety | 3.50 (7.79) | 2.06 (.05) | 6.42 (9.03) | 2.25 (.05) |
| PROMIS Depression | 3.30 (10.21) | 1.48 (.16) | 1.75 (6.43) | 0.86 (.41) |
| Caregivers | Rural (n = 45) |
Urban (n = 29) |
||
|---|---|---|---|---|
| Mean a (SD) | Paired t (P) | Mean a (SD) | Paired t (P) | |
| Total financial toxicity scoreb | −0.01 (0.19) | −0.46 (.65) | −0.01 (0.21) | −0.34 (.74) |
| Financial toxicity: psychological response | 1.92 (4.61) | 2.79 (.008) | 0.76 (5.24) | 0.78 (.44) |
| Financial toxicity: material conditions | 0.22 (1.04) | 1.43 (.16) | 0.17 (1.42) | 0.66 (.52) |
| Financial toxicity: coping behaviors | 0.07 (0.84) | 0.54 (.60) | −0.10 (0.62) | −0.90 (.38) |
| Feelings about your household’s income | 0.24 (0.61) | 2.69 (.01) | −0.03 (0.63) | −0.30 (.77) |
| Distressc | −0.11 (2.31) | −0.32 (.75) | −0.86 (2.62) | −1.78 (.09) |
| PROMIS Physical Health | −1.45 (5.35) | −1.82 (.08) | −0.40 (5.39) | −0.40 (.70) |
| PROMIS Mental Health | −0.05 (5.56) | −0.06 (.96) | −0.86 (5.77) | −0.80 (.43) |
| PROMIS Anxiety | −0.17 (7.72) | −0.15 (.88) | −1.34 (8.21) | −0.88 (.39) |
| PROMIS Depression | −0.40 (8.10) | −0.34 (.74) | −0.30 (8.00) | −0.20 (.84) |
Abbreviations: COST-FACIT = Comprehensive Score for Financial Toxicity–Functional Assessment of Chronic Illness Therapy; NCCN = National Comprehensive Cancer Network; PROMIS = Patient-Reported Outcomes Measurement Information System.
Each difference is defined as the preintervention score subtracted from the postintervention score, and average change scores are shown in the table.
Financial toxicity total score includes average of reverse-coded COST-FACIT (so all measures have the same polarity), material condition, and coping behavior scores.
NCCN Distress Thermometer.
Table 6.
Implementation outcomes for patients and caregivers.
| Evaluation Measure | Patients (n = 31) | Caregivers (n = 74) |
|---|---|---|
| Feasibility of Intervention Measure, mean (SD), range | 3.98 (0.73), 3 to 5 | 4.02 (0.69), 3 to 5 |
| Acceptability of Intervention Measure, mean (SD), range | 4.06 (0.69), 3 to 5 | 4.07 (0.67), 3 to 5 |
| Intervention Appropriateness Measure, mean (SD), range | 4.02 (0.74), 3 to 5 | 4.07 (0.70), 3 to 5 |
| Total score, mean (SD); Rangea | 4.02 (0.69), 3 to 5 | 4.05 (0.67), 3 to 5 |
| My stress and/or anxiety levels decreased as a result of the information received from navigators, n (%) | ||
| Strongly Agree/Agree | 29 (93.5) | 49 (66.2) |
| Disagree/Strongly disagree | 2 (6.5) | 25 (33.8) |
| Navigators answered my question(s), n (%) | ||
| Strongly Agree/Agree | 31 (100.0) | 58 (78.4) |
| Disagree/Strongly disagree | 0 | 16 (21.6) |
| After speaking with navigators I had actionable next steps, n (%) | ||
| Strongly Agree/Agree | 30 (96.8) | 54 (73.0) |
| Disagree/Strongly disagree | 1 (3.2) | 20 (27.0) |
| Materials and resources sent by navigators were helpful, n (%) | ||
| Strongly Agree/Agree | 31 (100.0) | 57 (77.0) |
| Disagree/Strongly disagree | 0 | 17 (23.0) |
| I am better prepared after speaking with navigators, n (%) | ||
| Strongly Agree/Agree | 31 (100.0) | 55 (74.3) |
| Disagree/Strongly disagree | 0 | 19 (25.7) |
See supplementary file for details on feasibility, acceptability, and intervention appropriateness measures.
Implementation outcomes
With respect to implementation outcomes, both patients and caregivers rated the intervention favorably (Table 6; see Supplementary File 3). The mean overall rating of the intervention was 4.02 (±0.69) and 4.05 (±0.67), respectively, out of a maximum potential score of 5. All patients and 78.4% of caregivers strongly agreed or agreed that Triage Cancer navigators answered all of their questions; that they had actional next steps after speaking with navigators (96.8% of patients, 73.0% of caregivers); that follow-up materials and resources sent by navigators were helpful (100% of patients, 77.0% of caregivers); and that they were better prepared after speaking with navigators (100% of patients, 74.3% of caregivers).
Discussion
After participation in our virtual OFLN intervention, caregivers experienced significant reductions in FT. The majority of patients and caregivers indicated reduced subjective stress and anxiety levels and felt equipped with clear, actionable steps to manage their financial and legal concerns after the intervention. At baseline, moderate FT along with high levels of anxiety and depression were reported; a pattern consistent with other survivor populations facing systemic and geographic barriers to supportive care services.17 The intervention received high ratings for feasibility, acceptability, and effectiveness from both patients and caregivers, which supports the intervention’s potential for implementation across multiple CFIR domains including intervention characteristics and implementation processes.
Consistent with our prior study findings at baseline,4,6,18 this cohort reported moderate levels of FT (COST-FACIT scores ranging from 17.50 [± 9.07]18 to 20.92 [±11.14] for patients and 19.31 [±10.12] to 21.11 [±6.45]18 for caregivers); high levels of anxiety (PROMIS Anxiety scores ranging from 55.69 [±9.10]18 to 56.01 [±10.31] for patients and 58.14 [±7.84]18 to 59.58 [±9.44] for caregivers); and high depression (PROMIS Depression scores ranging from 54.42 [±10.27]18 to 51.31 [±10.16] for patients and 53.38 [±8.79]18 to 53.46 [±9.77] for caregivers). Statistically significant postintervention reductions in FT among caregivers also mirror outcomes from our prior in-person OFLN intervention.18 Although we were unable to capture pre/post changes in FT among patients, subjective reports of reduced stress and or anxiety demonstrate psychosocial benefits of the intervention. Patient experiences of ongoing treatment-related stressors during active treatment likely influenced patient vs caregiver discordance in outcomes. Relatively younger age of patients, developmental stage, and/or limited experience navigating complex health and financial systems may have affected their understanding and effective utilization of intervention resources. Studies32 suggest that due to these factors, caregivers may experience more immediate or measurable gains from certain supportive interventions, whereas patient outcomes might be more modest or harder to detect. Further investigation on timing and type of measurement is needed to better understand discrepancies in subjective and standardized measures of stress and anxiety in OFLN studies.
Although we did not find differences in outcomes among rural vs urban participants at baseline, pre-post intervention outcomes showed significant increases in rural caregiver COST-FACIT (indicating reductions in FT) and worsening physical health among rural patients compared with their urban counterparts. Similarly, other studies have highlighted disparities in FT among rural populations12 due to travel constraints,16 limited health insurance coverage, and decreased access to health information and care.17 Greater reductions in FT among rural subgroups could be related to the virtual nature of the OFLN intervention that filled a critical service gap and helped participants overcome barriers to accessing resources locally. We also made proactive attempts to address limitations in broadband internet access in rural regions32,33 by enhancing participant engagement during clinic visits, providing iPads to access intervention resources, and using diverse methods of communication (ie, email, phone, text messaging). Tailoring virtual OFLN to the needs of rural cancer centers holds great potential for increasing access to resources and reducing the overall burden of cancer.34,35
Although prior research has shown the benefits of financial26,36,37 and, to a more limited extent, legal37 navigation and helped establish the feasibility of virtual supportive care interventions,37-41 this study is among the first to evaluate a combined, virtual financial and legal intervention engaging patients and caregivers in rural communities. Partnering with Triage Cancer, where all navigators are also licensed attorneys, increased our ability to provide comprehensive navigation around health-harming legal needs that often arise from financial needs.19 This study is also one of the first to train and mobilize clinic nurses to engage patients and caregivers in OFLN, resulting in increased study enrollment and retention rates.23 The intervention is highly scalable, because it builds on existing clinical infrastructure and can be adapted for use across different, and especially under-resourced, health-care settings with minimal training and resources. Providing access to OFLN for all patients and caregivers across the continuum of care facilitates proactive identification of FT risk factors and early engagement with navigation resources. At the policy level, findings underscore the need for reimbursement models and institutional support to sustain OFLN as essential components of comprehensive cancer care.
Limitations
Though the virtual OFLN format broadens access, it also can present challenges in sustaining participant engagement. Limited observable reductions in patient FT in this study could be related to completing self-directed activities outside of the clinical setting, the younger age of patients who may be financially dependent on caregivers or have fewer independent financial responsibilities, and the inclusion of participants without prescreened/identified needs. To reduce potential confounding effects from the existing psychosocial infrastructure, standardized referral pathways and documentation procedures were in place to ensure standardized delivery of psychosocial support and analyses focused on within-group changes. This design was appropriate for the feasibility and acceptability stage of testing and provides a foundation for future pragmatic trials. Limitations to generalizability include a sample that is predominantly non-Hispanic White with incomes above FPL and lack of clinical data (ie, years since diagnosis, types of treatment).
Conclusions
This study is among the first to implement a virtual OFLN intervention in a setting serving a predominately rural, PAYA cancer population, and it demonstrates the potential to decrease FT. Findings have broader implications for sustainability in cancer care delivery. With increasing reliance on Medicaid reimbursement for hospitals, and with many facing Medicaid loss due to current policy changes,35 timely support to navigation resources is critical. During these uncertain and stressful coverage transitions, our virtual OFLN program has the potential to ensure survivors do not lose coverage and secure alternative financial resources. Given the feasibility, acceptability, and preliminary efficacy of both our in-person and virtual OFLN interventions, our future research will test a stepped care approach to OFLN in a randomized control trial. This approach will allow us to customize our OFLN intensity based on the FT levels of patients and caregivers increasing implementability in resource-constrained cancer centers. Virtual OFLN offers a scalable and accessible solution to address cancer-related FT and improve the QOL of patients and caregivers.
Supplementary Material
Acknowledgments
The funders were not involved in data collection, analysis or interpretation of the data, writing of the manuscript, or the decision to submit the manuscript for publication. The study was supported by the University of Kentucky Markey Cancer Center (P30CA177558). HF was supported by the American Cancer Society (IRG-22 to 152- 34-IRG and POST-BACC-22 to 1042000-01-DPBACC). Disclaimers: JD serves as the Vice Chair of the Kentucky Pediatric Cancer Research Trust Fund. JE serves on the scientific advisory board of Triage Cancer. Prior Presentation: Abstract has been accepted for presentation at the 2025 ASCO Quality Care Symposium and was invited for simultaneous publication by JCO Oncology Practice.
Contributor Information
Jean S Edward, School of Nursing, University of Louisville, Louisville, KY, United States; Brown Cancer Center, University of Louisville, Louisville, KY, United States.
Lynn J Andreae, Center for Health, Engagement, and Transformation, College of Medicine, University of Kentucky, Lexington, KY, United States.
Haafsah Fariduddin, College of Medicine, University of Kentucky, Lexington, KY, United States.
Elizabeth Ruschman, College of Medicine, University of Kentucky, Lexington, KY, United States.
Lori Eisele, School of Nursing, University of Louisville, Louisville, KY, United States.
Mackenzie Caldwell, College of Medicine, University of Kentucky, Lexington, KY, United States.
Joanna Doran, Triage Cancer, Chicago, IL, United States.
Monica Bryant, Triage Cancer, Chicago, IL, United States.
Jordan Heflin, Department of Pediatrics, College of Medicine, University of Kentucky, Lexington, KY, United States.
Brent Shelton, Brown Cancer Center, University of Louisville, Louisville, KY, United States; Markey Cancer Center, University of Kentucky, Lexington, KY, United States.
John D’Orazio, Department of Pediatrics, College of Medicine, University of Kentucky, Lexington, KY, United States.
Kimberly D Northrip, Department of Pediatrics, College of Medicine, University of Kentucky, Lexington, KY, United States.
Author contributions
Jean Edward (Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing—original draft, Writing—review & editing), Lynn J. Andreae (Conceptualization, Data curation, Formal analysis, Methodology, Resources, Validation, Visualization, Writing—original draft, Writing—review & editing), Haafsah Fariduddin (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing—original draft, Writing—review & editing), Elizabeth Ruschman (Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing—original draft, Writing—review & editing), Lori Eisele (Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing—original draft, Writing—review & editing), Mackenzie Caldwell (Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing—original draft, Writing—review & editing), Joanna Doran (Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing—original draft, Writing—review & editing), Monica Bryant (Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing—original draft, Writing—review & editing), Jordan Heflin (Conceptualization, Data curation, Investigation, Resources, Supervision, Validation, Writing—original draft, Writing—review & editing), Brent Shelton (Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Supervision, Writing—review & editing), and John D’Orazio (Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing—original draft, Writing—review & editing), Kimberly D. Northrip (Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Writing—original draft, Writing—review & editing)
Funding
This research was funded by the Kentucky Cabinet for Health and Family Services, Kentucky Pediatric Cancer Research Trust Fund.
Conflicts of interest
All other authors declare no conflicts of interest.
Data availability
The individual-level data underlying this study cannot be shared due to restrictions specified in the informed consent approved by the Institutional Review Board, which limits data use to the approved research team in order to protect participant privacy and confidentiality. Deidentified summary-level data supporting the findings of this study are available from the corresponding author upon reasonable request.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The individual-level data underlying this study cannot be shared due to restrictions specified in the informed consent approved by the Institutional Review Board, which limits data use to the approved research team in order to protect participant privacy and confidentiality. Deidentified summary-level data supporting the findings of this study are available from the corresponding author upon reasonable request.