CancerNCT07410689

SAFE.AI: Developing and Testing an AI-based Hybrid Chatbot for Financial Empowerment in Rural Cancer Care

A study testing Rule-Based Chatbot and Hybrid Chatbot in people with Cancer and Financial Toxicity, run by University of Utah at 1 site in United States.

Recruiting

Looking for participants now. Contact the study team or a site below to ask about taking part.

Sites and contacts

Official record

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Trial summary

Who is it for?: Ages 18 years and older
Conditions the study is for: Cancer, Financial Toxicity
What is being tested?: Rule-Based Chatbot and Hybrid Chatbot
Could I receive a placebo?: No, everyone receives an active treatment
How many people: 60 participants
Where: 1 siteUnited States
Study dates: Sep 2026to Dec 2027
Phase: Interventional
Are there results?: Not yet: the study is under way

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

Ages 18 years and older
All sexes
No healthy volunteers
Adult, Older adult

Who may be able to join

Adults (18 years and older)
Cancer patients or financially responsible caregivers of cancer patients who:
Reside in the Huntsman Cancer Institute's five-state catchment area (Utah, Idaho, Wyoming, Montana, and Nevada),
Are able to read and write in English, and
Live in a rural area, defined by endorsement of a residential ZIP code classified as non-metropolitan (RUCA codes 4-10) per the USDA Rural-Urban Commuting Area Codes.

Who cannot join

Respondents who do not live within this 5-state region--The SAFE toolkit material was developed for the Huntsman Cancer Institute patient population which serves UT, ID, MT, WY, \& NV
Respondents who only speak Spanish or other exclusively non-English speaking groups--The large language model for the chatbot will be developed in the English language. As non-English language training for the chatbot is not part of the scope of this study, participants who are unable to read and write in English may not be appropriate. As such, we will not be recruiting participants who only speak Spanish or other exclusively non-English speaking groups. Future studies will include adaptation of the chatbot to other languages.
Caregivers who are not primarily responsible for the financial aspects of patients' cancer care--The topic of financial hardship of cancer care may be less relevant for caregivers who are not financially involved in care.
Non-rural dwelling

Trial locations and contacts

1 site in 1 country. Contact the study team or a site near you to ask about taking part.

United States1 site, 1 recruiting

Huntsman Cancer Institute/ University of Utah
Salt Lake City, Utah, 84112
Djin Tay, PhD, RN, 801-646-6440, Djin.Tay@nurs.utah.edu
Djin Tay, PhD, RN
Recruiting

Other trials in United States

About this study

Read the detailed description

Costs of cancer care will approach $246 billion by 2030, making cancer one of the most expensive health conditions for individuals. Cancer-related financial hardships negatively impacts psychological wellbeing, health-related quality of life, medication adherence, and decisions to delay or forgo care. Rural cancer patients and families have a higher prevalence of financial hardships, incur greater travel-related expenses, face unique employment and income stressors, and have lower access to specialized cancer care services and providers-- including those that support financial needs.

Few financial toxicity interventions are designed for the needs of rural cancer patients and families. While financial navigation can effectively reduce cancer patients' out-of-pocket costs, cancer programs' financial and rural patient navigation services, including at the Huntsman Cancer Institute (HCI), are overstrained. Most centers respond to financial hardships reactively rather than proactively, and programs are less equipped to assist with non-medical sources of cancer costs, such as travel and employment hardships.

To address this gap, Self-Advocacy for Financial Empowerment (SAFE) resource toolkit with a community advisory board consisting of rural cancer patients, caregivers, and healthcare stakeholders. Community-engaged research also identified the need for individualized and accessible information about financial resources and supports, stigma as a barrier to seeking help, and the time and resource-intensive nature of financial navigation that limits the penetration and reach of these essential services among rural communities impacted by cancer.

Chatbots, or conversational agents, are a type of artificial intelligence (AI) system that applies machine learning to reproduce realistic human conversations. Scripted chatbots, based on clearly defined information boundaries, offer accurate, reliable, and individualized responses to questions. Conversely, AI-based chatbots that use large language models (LLM) like GPT4, can address ambiguous, open-ended questions while continuing to preserve privacy. Chatbots facilitate individualized, chunked information that enhances complex information communication, promotes users' privacy and support needs, and addresses workforce challenges.[

GARDE-Chat, an open-source platform, has been established for health system-level risk assessment and genetic testing for hereditary cancer at HCI. GARDE-Chat supports scripted, hybrid, and AI-chatbots. Prior to this pilot test, GARDE-Chat will be used to create a chatbot designed to provide responses for financial toxicity, based on the SAFE toolkit content and verified resources to develop the scripted version of the chatbot. A large language model component of the chatbot will be incorporated for the hybrid version that will enable users to ask more complex and open-ended questions, refined with community stakeholder input.

This is a randomized, two-arm, parallel-group pilot trial investigating a new chatbot tool designed to support cancer patients and caregivers, particularly those in rural communities. Approximately 60 participants will be randomized 1:1 to interact with either a hybrid chatbot or an AI-enabled chatbot. Participants will use their assigned chatbot to obtain clear and helpful information related to insurance, travel costs, and other financial aspects of cancer care. Enrolled participants will complete three surveys (pretest, posttest, and 2-week follow-up) and interact with the chatbot prior to the posttest. Participants can interact with the chatbot between the posttest and the 2-week followup as they choose. Participants will share feedback on the usefulness, ease of use, and overall experience using the chatbot and complete pre-and posttest measures to assess preliminary efficacy for secondary outcome measures. All research activities will be done online.

Conditions: Cancer, Financial Toxicity
Being tested: Rule-Based Chatbot, Hybrid Chatbot
Medical subject headings: Neoplasms, Financial Stress

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

Rule-Based ChatbotOther
The rule-based (scripted) SAFE.ai chatbot is a guided conversational tool built to provide structured, accurate, and consistent information to rural cancer patients and caregivers experiencing cancer-related financial toxicity.
This chatbot is grounded in the Self-Advocacy for Financial Empowerment (SAFE) resource toolkit, which was co-developed with a community advisory board (CAB) composed of rural patients, caregivers, nurses, and financial navigation experts across HCI's five-state catchment area. All scripted responses reflect priorities identified during qualitative needs assessment sessions, ensuring that content is culturally aligned with rural patient experiences and real-world financial challenges.
The chatbot follows a rule-based decision tree. Users progress through the conversation by selecting a response from a set of fixed options displayed on-screen. This ensures that all content is clinically vetted, safe, consistent, and aligned with evidence-based practices.
Hybrid ChatbotOther
The hybrid SAFE.ai chatbot builds on the existing rule-based system by integrating a large language model (LLM) layer to support more flexible, open-ended, and conversational interactions. While the rule-based chatbot provides structured conversations through predefined content, the hybrid approach allows users to ask complex or personalized questions about financial toxicity.
To ensure safety and accuracy, the hybrid chatbot is not allowed to generate responses from the open internet.
By combining the consistency of rule-based logic with the adaptability of an LLM, the hybrid chatbot will enable users to ask follow-up questions, describe nuanced financial situations, request clarification in their own words, and receive more tailored guidance while still ensuring adherence to SAFE content.

Study groups in NCT07410689
Study group	Role	What they receive
Rule-based Chatbot	Other	Participants randomized to this arm will be asked to use the rule-based chatbot. Receives: Other: Rule-Based Chatbot
Hybrid Chatbot	Other	Participants randomized to this arm will be asked to use the hybrid chatbot Receives: Other: Hybrid Chatbot

What is being measured

The primary outcome is the main question the study is designed to answer.

Single-Item Helpfulness Rating
Helpfulness is assessed using a 5-point Likert-scale item with response options ranging from Very unhelpful (1) to Very helpful (5). Total scores range from a minumum of 1 to a maximum of 5, with lower scores indicating lower perceived helpfulness, and higher scores indicating greater perceived helpfulness.
Measured: up to 2 weeks
System Usability Scale (SUS)
The SUS is a 10-item, 5 point Likert scale (0 = strongly disagree, 5 = strongly agree). Total scores range from a minimum of 0 to a maximum of 100, with lower values indicating less usability and higher values indicating higher usability.
Measured: up to 2 weeks
Acceptability of Intervention Measure (AIM)
The AIM is a 4-item, 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). Total scores range from a minimum of 4 a maximum of 20, with lower values indicating lower acceptability and higher values indicating higher acceptability.
Measured: up to 2 weeks
Chatbot User Satisfaction (CUS) - Satisfaction Subscale
The Satisfaction subscale of the CUS measure is a 5 item Likert-scale ( 1 = strongly disagree, 5 = strongly agree). Total scores range from a minimum of 5 to a maximum of 25, with lower values indicating lower user satisfaction, and higher values indicating higher satisfaction.
Measured: up to 2 weeks
Trust in Automated Systems Test (TOAST)
The TOAST is a 9-item 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Total scores range from a minimum of 9 to a maximum of 63, with lower values indicating lower trust, and higher values indicating higher trust.
Measured: up to 2 weeks

Secondary outcomes (5)

Self-reported Financial Worry
Financial Worry will be assessed by the COST (COmprehensive Score for financial Toxicity) assessment. COST is a 12-item, 5-point Likert scale (0=Not at All to 4 =Very Much). Total scores range from a minimum of 0 to a maximum of 44, with lower scores indicating worse Financial Well-Being and higher scores indicating better Financial Well-Being.
This outcome measure will report mean COST score.
Measured: up to 2 weeks
Health-Related Quality of Life (QOL)
Health-related quality of life will be assessed with the 36-item short-form Health Survey (SF-36). The SF-36 has two subscales, the Physical Component Summary (PCS) and the Mental Component Summary (MCS). Each subscale ranges from 0-100, with lower scores indicating worse QOL and higher scores indicating better QOL.
This outcome measure will report the mean PCS and MCS scores.
Measured: up to 2 weeks
Self-Efficacy for Coping with Cancer
Self-efficacy for coping with cancer will be assessed with the Cancer Behavior Inventory-Brief Version (CBI-B) questionnaire. CBI-B is a 12-item, 9-point Likert scale (1=Not at All Confident to 9=Totally Confident).
Total CBI-B scores range from 9 to 108, with lower scores indicating worse self-efficacy and higher scores indicating better self-efficacy.
Measured: up to 2 weeks
Psychosocial Distress
Psychosocial distress will be measured by the Patient Health Questionnaire-4 (PHQ-4). PHQ-4 is a 4-item, 4-point Likert scale (0 = Not at All to 3 = Nearly every day).
Total PHQ-4 scores range from 0 to 12, with lower scores indicating less psychosocial distress and higher scores indicating more severe psychosocial distress.
Measured: up to 2 weeks
User Engagement with SAFE.AI
User engagement with the SAFE.AI will be assessed using an engagement instrument developed for evaluating AI chatbots in a posttest survey.
Measured: up to 2 weeks

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

Sep 2026Dec 2027

First posted13 Feb 2026
Study startSep 2026 (estimated)
Primary completionDec 2027 (estimated)
Study completionDec 2027 (estimated)

Resources

Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
Publications (35)Papers the sponsor has linked to this study.
Other trials for CancerStudies of the same condition, open and under way.
What the trial phases meanHow a treatment moves from first tests in people to approval.

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design

Study type: Interventional
Phase: Phase N/A
Primary purpose: Supportive care
Allocation: Randomised
Intervention model: Parallel groups
Masking: None (open label)
Enrolment: 60 participants (estimated)

IDs, dates and publications

ClinicalTrials.gov ID: NCT07410689
Sponsor's protocol ID: 193501
Status last verified: Sep 2026
First submitted: 31 Dec 2025
Last updated: 25 Sep 2026
Results posted: No
Data monitoring committee: No
FDA-regulated drug: No
FDA-regulated device: No

Publications

Mariotto AB, Enewold L, Zhao J, Zeruto CA, Yabroff KR. Medical Care Costs Associated with Cancer Survivorship in the United States. Cancer Epidemiol Biomarkers Prev. 2020 Jul;29(7):1304-1312. doi: 10.1158/1055-9965.EPI-19-1534. Epub 2020 Jun 10.
PubMed 32522832
Carrera PM, Kantarjian HM, Blinder VS. The financial burden and distress of patients with cancer: Understanding and stepping-up action on the financial toxicity of cancer treatment. CA Cancer J Clin. 2018 Mar;68(2):153-165. doi: 10.3322/caac.21443. Epub 2018 Jan 16.
PubMed 29338071
Lyman GH, Kuderer N. Financial Toxicity, Financial Abuse, or Financial Torture: Let's Call It What It is! Cancer Invest. 2020 Mar;38(3):139-142. doi: 10.1080/07357907.2020.1735084. Epub 2020 Mar 4. No abstract available.
PubMed 32093505
Pisu M, Henrikson NB, Banegas MP, Yabroff KR. Costs of cancer along the care continuum: What we can expect based on recent literature. Cancer. 2018 Nov 1;124(21):4181-4191. doi: 10.1002/cncr.31643. Epub 2018 Oct 17.
PubMed 30475400
Yabroff KR, Mariotto A, Tangka F, Zhao J, Islami F, Sung H, Sherman RL, Henley SJ, Jemal A, Ward EM. Annual Report to the Nation on the Status of Cancer, Part 2: Patient Economic Burden Associated With Cancer Care. J Natl Cancer Inst. 2021 Nov 29;113(12):1670-1682. doi: 10.1093/jnci/djab192.
PubMed 34698839
Knight TG, Deal AM, Dusetzina SB, Muss HB, Choi SK, Bensen JT, Williams GR. Financial Toxicity in Adults With Cancer: Adverse Outcomes and Noncompliance. J Oncol Pract. 2018 Oct 24:JOP1800120. doi: 10.1200/JOP.18.00120. Online ahead of print.
PubMed 30355027
Allcott N, Dunham L, Levy D, Carr J, Stitzenberg K. Financial burden amongst cancer patients treated with curative intent surgery alone. Am J Surg. 2019 Sep;218(3):452-456. doi: 10.1016/j.amjsurg.2019.01.033. Epub 2019 Jan 31.
PubMed 30771864
Williams CP, Gallagher KD, Deehr K, Aswani MS, Azuero A, Daniel CL, Ford EW, Ingram SA, Balch AJ, Rocque GB. Quantifying treatment preferences and their association with financial toxicity in women with breast cancer. Cancer. 2021 Feb 1;127(3):449-457. doi: 10.1002/cncr.33287. Epub 2020 Oct 27.
PubMed 33108023
Belcher SM, Lee H, Nguyen J, Curseen K, Lal A, Zarrabi AJ, Gantz L, Rosenzweig MQ, Hill JL, Yeager KA. Financial Hardship and Quality of Life Among Patients With Advanced Cancer Receiving Outpatient Palliative Care: A Pilot Study. Cancer Nurs. 2023 Jan-Feb 01;46(1):3-13. doi: 10.1097/NCC.0000000000001052. Epub 2021 Dec 31.
PubMed 34974507
Zahnd WE, Davis MM, Rotter JS, Vanderpool RC, Perry CK, Shannon J, Ko LK, Wheeler SB, Odahowski CL, Farris PE, Eberth JM. Rural-urban differences in financial burden among cancer survivors: an analysis of a nationally representative survey. Support Care Cancer. 2019 Dec;27(12):4779-4786. doi: 10.1007/s00520-019-04742-z. Epub 2019 Apr 10.
PubMed 30972645
Petermann V, Zahnd WE, Vanderpool RC, Eberth JM, Rohweder C, Teal R, Vu M, Stradtman L, Frost E, Trapl E, Koopman Gonzalez S, Vu T, Ko LK, Cole A, Farris PE, Shannon J, Lee J, Askelson N, Seegmiller L, White A, Edward J, Davis M, Wheeler SB. How cancer programs identify and address the financial burdens of rural cancer patients. Support Care Cancer. 2022 Mar;30(3):2047-2058. doi: 10.1007/s00520-021-06577-z. Epub 2021 Oct 16.
PubMed 34655327
Charlton M, Schlichting J, Chioreso C, Ward M, Vikas P. Challenges of Rural Cancer Care in the United States. Oncology (Williston Park). 2015 Sep;29(9):633-40.
PubMed 26384798
Spencer JC, Rotter JS, Eberth JM, Zahnd WE, Vanderpool RC, Ko LK, Davis MM, Troester MA, Olshan AF, Wheeler SB. Employment Changes Following Breast Cancer Diagnosis: The Effects of Race and Place. J Natl Cancer Inst. 2020 Jun 1;112(6):647-650. doi: 10.1093/jnci/djz197.
PubMed 31599949
Kent EE, Lee S, Asad S, Dobbins EE, Aimone EV, Park EM. "If I wasn't in a rural area, I would definitely have more support": social needs identified by rural cancer caregivers and hospital staff. J Psychosoc Oncol. 2023;41(4):393-410. doi: 10.1080/07347332.2022.2129547. Epub 2022 Oct 10.
PubMed 36214743
Zhang M, Wang X, Shao M, Li T, Guo S, Yang Y, Yu L, Bin M, Li D, Zhou H, Yao L, Chen C, Wang T. Financial toxicity of informal caregivers of colorectal cancer patients: A cross-sectional study. Eur J Oncol Nurs. 2024 Apr;69:102519. doi: 10.1016/j.ejon.2024.102519. Epub 2024 Feb 9.
PubMed 38402718

Interested in taking part?

Each site lists its own contact. Pick the site nearest to you.

Talk to your doctor first and take this page with you. Only the study team can confirm whether you can join.

Questions to ask the study team

What is the study trying to find out?
What would I need to do, and how often would I visit?
Could I receive a placebo instead of the treatment?
What are the possible risks and benefits for me?
Will it cost me anything? Are travel or time paid for?
Can I keep seeing my own doctor during the study?
What happens when the study ends?

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Study at a glance

From the registry record, last updated by the sponsor on 25 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.

Official title: SAFE.AI: Developing and Testing an AI-based Hybrid Chatbot for Financial Empowerment in Rural Cancer Care
ClinicalTrials.gov ID: NCT07410689
Acronym / sponsor ID: 193501
Conditions: Cancer, Financial Toxicity
Study type: Interventional
Recruitment status: Recruiting
Enrolment: 60 participants (estimated)
Lead sponsor: University of UtahUniversity, hospital or other
Collaborators: Huntsman Cancer Institute
Study start: Sep 2026 (estimated)
Primary completion: Dec 2027 (estimated)
Study completion: Dec 2027 (estimated)
First posted: 13 Feb 2026 (actual)
Results: Not posted in the source record

Clinical summary

The research question as the sponsor registered it. This describes what the study plans to test, not what it found.

Detailed description

Study design

Primary purpose: Supportive care
Allocation: Randomised
Intervention model: Parallel groups
Masking: None (open label)
Number of arms: 2

Arm	Type	Receives
Rule-based Chatbot	Other	Other: Rule-Based ChatbotParticipants randomized to this arm will be asked to use the rule-based chatbot.
Hybrid Chatbot	Other	Other: Hybrid ChatbotParticipants randomized to this arm will be asked to use the hybrid chatbot

Who may qualify

Ages: 18 years and older
Sex: All
Healthy volunteers: Not accepted
Age groups: Adult, Older adult

Key inclusion criteria (5 listed)

Adults (18 years and older)
Cancer patients or financially responsible caregivers of cancer patients who:
Reside in the Huntsman Cancer Institute's five-state catchment area (Utah, Idaho, Wyoming, Montana, and Nevada),
Are able to read and write in English, and
Live in a rural area, defined by endorsement of a residential ZIP code classified as non-metropolitan (RUCA codes 4-10) per the USDA Rural-Urban Commuting Area Codes.

Key exclusion criteria (4 listed)

Respondents who do not live within this 5-state region--The SAFE toolkit material was developed for the Huntsman Cancer Institute patient population which serves UT, ID, MT, WY, \& NV
Respondents who only speak Spanish or other exclusively non-English speaking groups--The large language model for the chatbot will be developed in the English language. As non-English language training for the chatbot is not part of the scope of this study, participants who are unable to read and write in English may not be appropriate. As such, we will not be recruiting participants who only speak Spanish or other exclusively non-English speaking groups. Future studies will include adaptation of the chatbot to other languages.
Caregivers who are not primarily responsible for the financial aspects of patients' cancer care--The topic of financial hardship of cancer care may be less relevant for caregivers who are not financially involved in care.
Non-rural dwelling

Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.

Interventions

Intervention	Type	Arms
Rule-Based ChatbotThe rule-based (scripted) SAFE.ai chatbot is a guided conversational tool built to provide structured, accurate, and consistent information to rural cancer patients and caregivers experiencing cancer-related financial toxicity. This chatbot is grounded in the Self-Advocacy for Financial Empowerment (SAFE) resource toolkit, which was co-developed with a community advisory board (CAB) composed of rural patients, caregivers, nurses, and financial navigation experts across HCI's five-state catchment area. All scripted responses reflect priorities identified during qualitative needs assessment sessions, ensuring that content is culturally aligned with rural patient experiences and real-world financial challenges. The chatbot follows a rule-based decision tree. Users progress through the conversation by selecting a response from a set of fixed options displayed on-screen. This ensures that all content is clinically vetted, safe, consistent, and aligned with evidence-based practices.	Other	Rule-based Chatbot
Hybrid ChatbotThe hybrid SAFE.ai chatbot builds on the existing rule-based system by integrating a large language model (LLM) layer to support more flexible, open-ended, and conversational interactions. While the rule-based chatbot provides structured conversations through predefined content, the hybrid approach allows users to ask complex or personalized questions about financial toxicity. To ensure safety and accuracy, the hybrid chatbot is not allowed to generate responses from the open internet. By combining the consistency of rule-based logic with the adaptability of an LLM, the hybrid chatbot will enable users to ask follow-up questions, describe nuanced financial situations, request clarification in their own words, and receive more tailored guidance while still ensuring adherence to SAFE content.	Other	Hybrid Chatbot

Primary outcome

Single-Item Helpfulness Rating
Time frame: up to 2 weeks
Helpfulness is assessed using a 5-point Likert-scale item with response options ranging from Very unhelpful (1) to Very helpful (5). Total scores range from a minumum of 1 to a maximum of 5, with lower scores indicating lower perceived helpfulness, and higher scores indicating greater perceived helpfulness.
System Usability Scale (SUS)
Time frame: up to 2 weeks
The SUS is a 10-item, 5 point Likert scale (0 = strongly disagree, 5 = strongly agree). Total scores range from a minimum of 0 to a maximum of 100, with lower values indicating less usability and higher values indicating higher usability.
Acceptability of Intervention Measure (AIM)
Time frame: up to 2 weeks
The AIM is a 4-item, 5-point Likert scale (1 = strongly disagree, 5 = strongly agree). Total scores range from a minimum of 4 a maximum of 20, with lower values indicating lower acceptability and higher values indicating higher acceptability.
Chatbot User Satisfaction (CUS) - Satisfaction Subscale
Time frame: up to 2 weeks
The Satisfaction subscale of the CUS measure is a 5 item Likert-scale ( 1 = strongly disagree, 5 = strongly agree). Total scores range from a minimum of 5 to a maximum of 25, with lower values indicating lower user satisfaction, and higher values indicating higher satisfaction.
Trust in Automated Systems Test (TOAST)
Time frame: up to 2 weeks
The TOAST is a 9-item 7-point Likert scale (1 = strongly disagree, 7 = strongly agree). Total scores range from a minimum of 9 to a maximum of 63, with lower values indicating lower trust, and higher values indicating higher trust.

5 secondary outcomes

Self-reported Financial Worry
Time frame: up to 2 weeks
Health-Related Quality of Life (QOL)
Time frame: up to 2 weeks
Self-Efficacy for Coping with Cancer
Time frame: up to 2 weeks
Psychosocial Distress
Time frame: up to 2 weeks
User Engagement with SAFE.AI
Time frame: up to 2 weeks

Results and safety

This study is still under way. Results are not available in the source record yet.

Research links

Official record on ClinicalTrials.govLast updated by the sponsor 25 Sep 2026.
Background: PubMed 32522832Mariotto AB, Enewold L, Zhao J, Zeruto CA, Yabroff KR. Medical Care Costs Associated with Cancer Survivorship in the United States. Cancer Epidemiol Biomarkers Prev. 2020 Jul;29(7):1304-1312. doi: 10.1158/1055-9965.EPI-19-1534. Epub 2020 Jun 10.
Background: PubMed 29338071Carrera PM, Kantarjian HM, Blinder VS. The financial burden and distress of patients with cancer: Understanding and stepping-up action on the financial toxicity of cancer treatment. CA Cancer J Clin. 2018 Mar;68(2):153-165. doi: 10.3322/caac.21443. Epub 2018 Jan 16.
Background: PubMed 32093505Lyman GH, Kuderer N. Financial Toxicity, Financial Abuse, or Financial Torture: Let's Call It What It is! Cancer Invest. 2020 Mar;38(3):139-142. doi: 10.1080/07357907.2020.1735084. Epub 2020 Mar 4. No abstract available.
Background: PubMed 30475400Pisu M, Henrikson NB, Banegas MP, Yabroff KR. Costs of cancer along the care continuum: What we can expect based on recent literature. Cancer. 2018 Nov 1;124(21):4181-4191. doi: 10.1002/cncr.31643. Epub 2018 Oct 17.
Background: PubMed 34698839Yabroff KR, Mariotto A, Tangka F, Zhao J, Islami F, Sung H, Sherman RL, Henley SJ, Jemal A, Ward EM. Annual Report to the Nation on the Status of Cancer, Part 2: Patient Economic Burden Associated With Cancer Care. J Natl Cancer Inst. 2021 Nov 29;113(12):1670-1682. doi: 10.1093/jnci/djab192.
Background: PubMed 30355027Knight TG, Deal AM, Dusetzina SB, Muss HB, Choi SK, Bensen JT, Williams GR. Financial Toxicity in Adults With Cancer: Adverse Outcomes and Noncompliance. J Oncol Pract. 2018 Oct 24:JOP1800120. doi: 10.1200/JOP.18.00120. Online ahead of print.
Background: PubMed 30771864Allcott N, Dunham L, Levy D, Carr J, Stitzenberg K. Financial burden amongst cancer patients treated with curative intent surgery alone. Am J Surg. 2019 Sep;218(3):452-456. doi: 10.1016/j.amjsurg.2019.01.033. Epub 2019 Jan 31.
Background: PubMed 33108023Williams CP, Gallagher KD, Deehr K, Aswani MS, Azuero A, Daniel CL, Ford EW, Ingram SA, Balch AJ, Rocque GB. Quantifying treatment preferences and their association with financial toxicity in women with breast cancer. Cancer. 2021 Feb 1;127(3):449-457. doi: 10.1002/cncr.33287. Epub 2020 Oct 27.
Background: PubMed 34974507Belcher SM, Lee H, Nguyen J, Curseen K, Lal A, Zarrabi AJ, Gantz L, Rosenzweig MQ, Hill JL, Yeager KA. Financial Hardship and Quality of Life Among Patients With Advanced Cancer Receiving Outpatient Palliative Care: A Pilot Study. Cancer Nurs. 2023 Jan-Feb 01;46(1):3-13. doi: 10.1097/NCC.0000000000001052. Epub 2021 Dec 31.
Background: PubMed 30972645Zahnd WE, Davis MM, Rotter JS, Vanderpool RC, Perry CK, Shannon J, Ko LK, Wheeler SB, Odahowski CL, Farris PE, Eberth JM. Rural-urban differences in financial burden among cancer survivors: an analysis of a nationally representative survey. Support Care Cancer. 2019 Dec;27(12):4779-4786. doi: 10.1007/s00520-019-04742-z. Epub 2019 Apr 10.
Background: PubMed 34655327Petermann V, Zahnd WE, Vanderpool RC, Eberth JM, Rohweder C, Teal R, Vu M, Stradtman L, Frost E, Trapl E, Koopman Gonzalez S, Vu T, Ko LK, Cole A, Farris PE, Shannon J, Lee J, Askelson N, Seegmiller L, White A, Edward J, Davis M, Wheeler SB. How cancer programs identify and address the financial burdens of rural cancer patients. Support Care Cancer. 2022 Mar;30(3):2047-2058. doi: 10.1007/s00520-021-06577-z. Epub 2021 Oct 16.
Background: PubMed 26384798Charlton M, Schlichting J, Chioreso C, Ward M, Vikas P. Challenges of Rural Cancer Care in the United States. Oncology (Williston Park). 2015 Sep;29(9):633-40.

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Referral and contact

AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.

Huntsman Cancer Institute/ University of Utah

Salt Lake City, United States

801-646-6440

Djin.Tay@nurs.utah.edu

Djin Tay, PhD, RN principal investigator

Huntsman Cancer Institute

1 site in 1 country: see every site and its status.

Questions about this trial

What is this clinical trial studying?

A study testing Rule-Based Chatbot and Hybrid Chatbot in people with Cancer and Financial Toxicity, run by University of Utah at 1 site in United States.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 5 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: looking for participants now, as of the sponsor's last update on 25 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

This study is still under way. Results are not available in the source record yet.

How can a doctor refer a patient or contact the research team?

Each site lists its own contact: choose the nearest one under Trial locations. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Single-Item Helpfulness Rating (time frame: up to 2 weeks). The study lists 5 primary outcomes in all. It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT07410689, which also lists 35 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 25 Sep 2026.