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The Impact of Artificial Intelligence-Based Health Intervention (AI-HEALS), Based on Symptom Management Theory, on Quality of Life and Related Outcomes in Postoperative Breast Cancer Patients

The objective of this clinical trial is to determine whether the AI-HEALS artificial intelligence-based mobile health intervention, grounded in symptom management theory, can improve health outcomes for adult women who have undergone surgery for Stage I-III breast cancer and are receiving adjuvant therapy. The primary research questions it aims to address are:

Can the AI-HEALS intervention improve the quality of life for patients who have undergone breast cancer surgery? Can the AI-HEALS intervention improve patients' levels of anxiety and depression, self-efficacy, self-health management abilities, and e-health literacy?

Researchers will compare patients receiving the AI-HEALS intervention with those receiving standard of care to determine the effect of the AI-HEALS intervention on relevant health outcomes for patients who have undergone breast cancer surgery.

Participants will:

  • Intervention Group: In addition to standard care, receive a 6-month, phased AI-HEALS artificial intelligence health intervention via WeChat, including daily symptom logging, personalized health content push notifications, completion of various online questionnaires, and participation in online follow-ups;
  • Control Group: Receive standard post-surgical care for breast cancer, paper-based and general WeChat health education, and telephone follow-ups at fixed time points;
  • All participants are required to complete questionnaires assessing quality of life, psychological well-being, and other relevant factors at baseline, 3 months into the intervention, and at the end of the 6-month intervention period.

調査の概要

状態

まだ募集していません

条件

研究の種類

介入

入学 (推定)

76

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

  • 名前:Guanhua Jiang, master degree
  • 電話番号:086+15083397959
  • メール:1226650459@qq.com

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

18年歳以上 (大人、高齢者)

健康ボランティアの受け入れ

いいえ

受講資格のある性別

女性

説明

Inclusion Criteria:

  • Age ≥ 18 years; patients with clinically and pathologically diagnosed Stage I-III breast cancer who have undergone surgery and received adjuvant treatments such as chemotherapy; patients who are proficient in using a smartphone and regularly use WeChat, so they can successfully receive and participate in the WeChat-based intervention program; patients who are willing to participate in the study and sign an informed consent form before the study begins.

Exclusion Criteria:

  • If participants cannot be reached by phone or WeChat during the study, or if no family members can be contacted; if participants are taking any psychiatric medications; if participants exhibit psychiatric symptoms during the study, such as confusion, difficulty speaking, or lack of cooperation; if participants have a serious systemic disease or severe physical dysfunction; or if participants are enrolled in other clinical trials. Any other reasons deemed to make participation inappropriate.

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:ランダム化
  • 介入モデル:並列代入
  • マスキング:独身

武器と介入

参加者グループ / アーム
介入・治療
実験的:Study Group

In addition to standard care, the intervention group received a 6-month AI-HEALS WeChat platform intervention based on symptom management theory, which implemented a closed-loop management process of "symptom assessment-personalized intervention-behavioral monitoring-feedback and adjustment" focused on symptom experience, symptom management behaviors, and environmental factors. Platform functionality was configured prior to the intervention; personal health records were established for patients within 24 hours of admission; and training on platform use was provided to both patients and caregivers.

This intervention integrates Symptom Management Theory (SMT) with WeChat-based artificial intelligence mobile health technology to establish a closed-loop management process comprising "symptom assessment-personalized intervention-behavioral monitoring-feedback and adjustment." This study employs a phased intervention strategy comprising the acute inpatient phase, the subacute home-based phase, and the long-term maintenance phase. By integrating natural language processing and reinforcement learning algorithms, the intervention content is dynamically adjusted based on patients' real-time symptom feedback and behavioral responses. Additionally, the involvement of family caregivers is incorporated throughout the entire intervention process to achieve dynamic, individualized, and continuous symptom management, distinguishing it from conventional nursing care and mobile health interventions not empowered by AI

介入なし:Control Group

The control group received standard postoperative care for breast cancer over a 6-month period: basic care for incisions, drainage tubes, and pain management was provided during the first 1-7 days of hospitalization, along with health education delivered verbally and via printed brochures, basic psychological counseling, and discharge instructions; At 1, 3, and 6 months post-surgery, general health information was sent via WeChat, followed by 10-15-minute telephone follow-ups to assess recovery and medication adherence, answer questions, and remind patients of follow-up appointments; no personalized interventions were provided.

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
時間枠
EORTC-QLQ-C30
時間枠:From enrollment through 6 months after the intervention
From enrollment through 6 months after the intervention
EORTC-QLQ-BR23
時間枠:From enrollment through 6 months after the intervention
From enrollment through 6 months after the intervention

二次結果の測定

結果測定
時間枠
Self-Rating Anxiety Scale, SAS
時間枠:From enrollment through 6 months after the intervention
From enrollment through 6 months after the intervention
Self-Rating Depression Scale, SDS
時間枠:From enrollment through 6 months after the intervention
From enrollment through 6 months after the intervention
General Self-Efficacy Scale, GSES
時間枠:From enrollment through 6 months after the intervention
From enrollment through 6 months after the intervention
Self-Health Management Ability Scale, SHMAS
時間枠:From enrollment through 6 months after the intervention
From enrollment through 6 months after the intervention
eHealth Literacy Scale, eHEALS
時間枠:From enrollment through 6 months after the intervention
From enrollment through 6 months after the intervention

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。

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12月1日

一次修了 (推定)

2028年11月1日

研究の完了 (推定)

2029年7月1日

試験登録日

最初に提出

2026年11月8日

QC基準を満たした最初の提出物

2026年11月8日

最初の投稿 (実際)

2026年11月13日

学習記録の更新

投稿された最後の更新 (実際)

2026年11月13日

QC基準を満たした最後の更新が送信されました

2026年11月8日

最終確認日

2026年11月1日

詳しくは

本研究に関する用語

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?

未定

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

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