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An Artificial Intelligence-Powered Supportive Care Chatbot to Address the Supportive Care Needs of Young Adult Cancer Survivors

2026年8月13日 更新者: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.

調査の概要

研究の種類

介入

入学 (推定)

30

段階

  • 適用できない

連絡先と場所

このセクションには、調査を実施する担当者の連絡先の詳細と、この調査が実施されている場所に関する情報が記載されています。

研究連絡先

研究場所

    • Michigan
      • Ann Arbor、Michigan、アメリカ、48109
        • University of Michigan Rogel Cancer Center
        • コンタクト:
        • 主任研究者:
          • Robert Knoerl

参加基準

研究者は、適格基準と呼ばれる特定の説明に適合する人を探します。これらの基準のいくつかの例は、人の一般的な健康状態または以前の治療です。

適格基準

就学可能な年齢

  • 大人

健康ボランティアの受け入れ

いいえ

説明

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

研究計画

このセクションでは、研究がどのように設計され、研究が何を測定しているかなど、研究計画の詳細を提供します。

研究はどのように設計されていますか?

デザインの詳細

  • 主な目的:支持療法
  • 割り当て:なし
  • 介入モデル:単一グループの割り当て
  • マスキング:なし(オープンラベル)

武器と介入

参加者グループ / アーム
介入・治療
実験的: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.
補助研究
補助研究
Interact with AI-powered supportive care chatbot
他の名前:
  • AI Intervention
  • AI-based Intervention

この研究は何を測定していますか?

主要な結果の測定

結果測定
メジャーの説明
時間枠
Acceptability of AI-powered supportive care chatbot
時間枠:At end of intervention, assessed up to 12 weeks
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.
At end of intervention, assessed up to 12 weeks
Demand of AI-powered supportive care chatbot
時間枠:Up to 12 months
Demand will be demonstrated by successful recruitment of the target sample (N=30) within 12 months.
Up to 12 months
Implementation of AI-powered supportive care chatbot
時間枠:During intervention use, assessed up to 12 weeks
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.
During intervention use, assessed up to 12 weeks
Retention
時間枠:Up to 12 weeks
Retention will be considered feasible if ≥ 80% of participants complete 4-week assessments, and ≥ 50% elect to continue to the optional extended use period.
Up to 12 weeks
Usability of AI-powered supportive care chatbot
時間枠:At end of intervention, assessed up to 12 weeks
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.
At end of intervention, assessed up to 12 weeks
Patient Reported Outcomes Measurement Information System measure
時間枠:At baseline, 4 weeks, and/or 12 weeks
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.
At baseline, 4 weeks, and/or 12 weeks
Digital Health Literacy Scale
時間枠:At baseline
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.
At baseline
Interview themes and subthemes
時間枠:At end of intervention, assessed up to 12 weeks
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.
At end of intervention, assessed up to 12 weeks

協力者と研究者

ここでは、この調査に関係する人々や組織を見つけることができます。

捜査官

  • 主任研究者:Robert Knoerl、University of Michigan Rogel Cancer Center

研究記録日

これらの日付は、ClinicalTrials.gov への研究記録と要約結果の提出の進捗状況を追跡します。研究記録と報告された結果は、国立医学図書館 (NLM) によって審査され、公開 Web サイトに掲載される前に、特定の品質管理基準を満たしていることが確認されます。

主要日程の研究

研究開始 (推定)

2026年10月1日

一次修了 (推定)

2028年10月1日

研究の完了 (推定)

2028年10月1日

試験登録日

最初に提出

2026年7月30日

QC基準を満たした最初の提出物

2026年8月13日

最初の投稿 (実際)

2026年8月19日

学習記録の更新

投稿された最後の更新 (実際)

2026年8月19日

QC基準を満たした最後の更新が送信されました

2026年8月13日

最終確認日

2026年7月1日

詳しくは

本研究に関する用語

その他の研究ID番号

  • UMCC 2026.025
  • NCI-2026-05454 (レジストリ識別子:CTRP (Clinical Trial Reporting Program))
  • HUM00288074 (その他の識別子:University of Michigan Rogel Cancer Center)

個々の参加者データ (IPD) の計画

個々の参加者データ (IPD) を共有する予定はありますか?

はい

IPD プランの説明

De-identified participant data will be shared with other researchers upon reasonable request and execution of a data transfer agreement.

IPD 共有時間枠

After publication of results and within 7 years after study completion.

IPD 共有アクセス基準

De-identified participant data will be shared with other researchers upon reasonable request and execution of a data transfer agreement.

IPD 共有サポート情報タイプ

  • STUDY_PROTOCOL
  • SAP
  • ICF
  • ANALYTIC_CODE
  • CSR

医薬品およびデバイス情報、研究文書

米国FDA規制医薬品の研究

いいえ

米国FDA規制機器製品の研究

いいえ

米国で製造され、米国から輸出された製品。

いいえ

この情報は、Web サイト clinicaltrials.gov から変更なしで直接取得したものです。研究の詳細を変更、削除、または更新するリクエストがある場合は、register@clinicaltrials.gov。 までご連絡ください。 clinicaltrials.gov に変更が加えられるとすぐに、ウェブサイトでも自動的に更新されます。

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