An Artificial Intelligence-Powered Supportive Care Chatbot to Address the Supportive Care Needs of Young Adult Cancer Survivors
13 augustus 2026 bijgewerkt door: University of Michigan Rogel Cancer Center
Feasibility, Usability, and Acceptability of an AI-Powered MASCC Supportive Care Platform Among Young Adults With Cancer
This clinical trial studies whether an artificial intelligence (AI)-powered supportive care chatbot is helpful for addressing the supportive care needs of young adult cancer survivors.
Young adult cancer survivors often experience ongoing and distressing symptoms following treatment, including extreme tiredness and lack of energy, anxiety, and difficulty sleeping.
Young adult cancer survivors report a variety of strategies to self-manage these symptoms; however, there remains a gap in targeted interventions focused on the needs in young adult survivors.
The AI-powered supportive care chatbot is designed to provide evidence-based information on supportive care for young adult cancer survivors.
Users interact with the chatbot by entering free-text questions or selecting from predefined topics to receive tailored educational responses related to supportive care across the cancer continuum, including treatment effects, symptom management, care transitions, and life after cancer.
The AI-powered supportive care chatbot may be an effective way to help address the supportive care needs of young adult cancer survivors.
Studie Overzicht
Toestand
Nog niet aan het werven
Interventie / Behandeling
Studietype
Ingrijpend
Inschrijving (Geschat)
30
Fase
- Niet toepasbaar
Contacten en locaties
In dit gedeelte vindt u de contactgegevens van degenen die het onderzoek uitvoeren en informatie over waar dit onderzoek wordt uitgevoerd.
Studiecontact
- Naam: Robert Knoerl
- Telefoonnummer: 734-764-8617
- E-mail: rjknoerl@med.umich.edu
Studie Locaties
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Michigan
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Ann Arbor, Michigan, Verenigde Staten, 48109
- University of Michigan Rogel Cancer Center
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Contact:
- Robert Knoerl
- Telefoonnummer: 734-764-8617
- E-mail: rjknoerl@med.umich.edu
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Hoofdonderzoeker:
- Robert Knoerl
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Deelname Criteria
Onderzoekers zoeken naar mensen die aan een bepaalde beschrijving voldoen, de zogenaamde geschiktheidscriteria. Enkele voorbeelden van deze criteria zijn iemands algemene gezondheidstoestand of eerdere behandelingen.
Geschiktheidscriteria
Leeftijden die in aanmerking komen voor studie
- Volwassen
Accepteert gezonde vrijwilligers
Nee
Beschrijving
Inclusion Criteria:
- 18 - 39 years old
- Able to speak/read English
- Completed primary cancer treatment (e.g., surgery, radiation, chemotherapy, immunotherapy) at least one month prior to the time of consent. Although, participants will be eligible if they are receiving maintenance treatments
- Report at least one moderate to severe symptom, side effect, or supportive care concern from cancer or its treatment
- Able to access Wi-Fi/internet
- Willing to complete surveys electronically
Exclusion Criteria:
- Completed cancer treatment more than three years ago
Studie plan
Dit gedeelte bevat details van het studieplan, inclusief hoe de studie is opgezet en wat de studie meet.
Hoe is de studie opgezet?
Ontwerpdetails
- Primair doel: Ondersteunende zorg
- Toewijzing: NVT
- Interventioneel model: Opdracht voor een enkele groep
- Masker: Geen (open label)
Wapens en interventies
Deelnemersgroep / Arm |
Interventie / Behandeling |
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Experimenteel: Supportive care (AI-powered supportive care chatbot)
Patients interact with AI-powered supportive care chatbot in a self-directed manner for 4 weeks.
Following the initial 4-week use period, patients choose to either continue to use the chatbot for an additional 8 weeks or conclude study participation.
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Nevenstudies
Nevenstudies
Interact with AI-powered supportive care chatbot
Andere namen:
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Wat meet het onderzoek?
Primaire uitkomstmaten
Uitkomstmaat |
Maatregel Beschrijving |
Tijdsspanne |
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Acceptability of AI-powered supportive care chatbot
Tijdsspanne: At end of intervention, assessed up to 12 weeks
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Acceptability will be supported if mean scores on the Acceptability E-Scale are ≥ 4 (on a 5-point scale).
Will be described (i.e., means, medians, standard deviations, and ranges) at the post-intervention time point.
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At end of intervention, assessed up to 12 weeks
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Demand of AI-powered supportive care chatbot
Tijdsspanne: Up to 12 months
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Demand will be demonstrated by successful recruitment of the target sample (N=30) within 12 months.
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Up to 12 months
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Implementation of AI-powered supportive care chatbot
Tijdsspanne: During intervention use, assessed up to 12 weeks
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Implementation will be assessed by engagement with the chatbot, defined as ≥ 70% of participants reporting at least one use per week during the initial 4-week period, rather than a fixed duration of use, given the self-directed nature of the intervention.
Will be described (i.e., means, medians, standard deviations, and ranges) weekly.
Given the pilot nature of the study, no hypothesis testing or formal comparisons will be conducted.
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During intervention use, assessed up to 12 weeks
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Retention
Tijdsspanne: Up to 12 weeks
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Retention will be considered feasible if ≥ 80% of participants complete 4-week assessments, and ≥ 50% elect to continue to the optional extended use period.
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Up to 12 weeks
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Usability of AI-powered supportive care chatbot
Tijdsspanne: At end of intervention, assessed up to 12 weeks
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Usability will be supported if mean System Usability Scale scores are ≥ 70, indicating acceptable usability.
Will be described (i.e., means, medians, standard deviations, and ranges) at the post-intervention time point.
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At end of intervention, assessed up to 12 weeks
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Patient Reported Outcomes Measurement Information System measure
Tijdsspanne: At baseline, 4 weeks, and/or 12 weeks
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Will be summarized using descriptive statistics (e.g., means, medians, standard deviations, and ranges) at each time point.
Changes over time (baseline, post-intervention, as applicable) will be examined descriptively.
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At baseline, 4 weeks, and/or 12 weeks
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Digital Health Literacy Scale
Tijdsspanne: At baseline
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Will be summarized using descriptive statistics (e.g., means, medians, standard deviations, and ranges) at the baseline time point.
The Digital Health Literacy Scale is a 0 to 12 point score (based on 3 items), with higher scores indicating greater digital health care literacy.
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At baseline
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Interview themes and subthemes
Tijdsspanne: At end of intervention, assessed up to 12 weeks
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The audio-recorded interviews will be transcribed verbatim by a professional transcription company and verified for accuracy by another study team member.
The finalized transcripts will be imported into NVivo 12 (QSR International Pty Ltd).
Inductive content analysis will be used to analyze the interview transcripts.
Two study team members will review the transcripts and the interview guide to create an initial list of codes.
Three transcripts will be independently coded using the initial codebook.
After three interviews are coded, two study team members will meet to resolve any coding discrepancies and to revise the codebook further.
The same process will be repeated after three more interviews are coded.
After the codebook is finalized, one study team member will code the remaining interviews.
Subsequently, the study team will meet as a group to review the transcripts in their entirety, making sense of the data and generating potential major themes and subthemes.
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At end of intervention, assessed up to 12 weeks
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Medewerkers en onderzoekers
Hier vindt u mensen en organisaties die betrokken zijn bij dit onderzoek.
Onderzoekers
- Hoofdonderzoeker: Robert Knoerl, University of Michigan Rogel Cancer Center
Studie record data
Deze datums volgen de voortgang van het onderzoeksdossier en de samenvatting van de ingediende resultaten bij ClinicalTrials.gov. Studieverslagen en gerapporteerde resultaten worden beoordeeld door de National Library of Medicine (NLM) om er zeker van te zijn dat ze voldoen aan specifieke kwaliteitscontrolenormen voordat ze op de openbare website worden geplaatst.
Bestudeer belangrijke data
Studie start (Geschat)
1 oktober 2026
Primaire voltooiing (Geschat)
1 oktober 2028
Studie voltooiing (Geschat)
1 oktober 2028
Studieregistratiedata
Eerst ingediend
30 juli 2026
Eerst ingediend dat voldeed aan de QC-criteria
13 augustus 2026
Eerst geplaatst (Werkelijk)
19 augustus 2026
Updates van studierecords
Laatste update geplaatst (Werkelijk)
19 augustus 2026
Laatste update ingediend die voldeed aan QC-criteria
13 augustus 2026
Laatst geverifieerd
1 juli 2026
Meer informatie
Termen gerelateerd aan deze studie
Aanvullende relevante MeSH-voorwaarden
Andere studie-ID-nummers
- UMCC 2026.025
- NCI-2026-05454 (Register-ID: CTRP (Clinical Trial Reporting Program))
- HUM00288074 (Andere identificatie: University of Michigan Rogel Cancer Center)
Plan Individuele Deelnemersgegevens (IPD)
Bent u van plan om gegevens van individuele deelnemers (IPD) te delen?
JA
Beschrijving IPD-plan
De-identified participant data will be shared with other researchers upon reasonable request and execution of a data transfer agreement.
IPD-tijdsbestek voor delen
After publication of results and within 7 years after study completion.
IPD-toegangscriteria voor delen
De-identified participant data will be shared with other researchers upon reasonable request and execution of a data transfer agreement.
IPD delen Ondersteunend informatietype
- LEERPROTOCOOL
- SAP
- ICF
- ANALYTIC_CODE
- MVO
Informatie over medicijnen en apparaten, studiedocumenten
Bestudeert een door de Amerikaanse FDA gereguleerd geneesmiddel
Nee
Bestudeert een door de Amerikaanse FDA gereguleerd apparaatproduct
Nee
product vervaardigd in en geëxporteerd uit de V.S.
Nee
Deze informatie is zonder wijzigingen rechtstreeks van de website clinicaltrials.gov gehaald. Als u verzoeken heeft om uw onderzoeksgegevens te wijzigen, te verwijderen of bij te werken, neem dan contact op met register@clinicaltrials.gov. Zodra er een wijziging wordt doorgevoerd op clinicaltrials.gov, wordt deze ook automatisch bijgewerkt op onze website .