Effects of the AI-HEALS intervention based on the Fogg behavior model on self-management in postoperative breast cancer patients: a randomized controlled trial study protocol
5 affiliations
- 1School of Nursing, Henan University of Science and Technology , , ,
- 2School of Public Health, Peking University , ,
- 3School and Hospital of Stomatology, Peking University , ,
- 4School of Medicine, Zhejiang University , ,
- 5The Fourth Central Hospital of Baoding City , ,
Abstract
Background: Breast cancer is the most common malignancy among women, and postoperative self-management is critically associated with long-term quality of life. Traditional clinical nursing and mobile health interventions frequently lack behavioral theory support, thereby failing to meet individualized rehabilitation needs. The Fogg Behavior Model (FBM) provides a theoretical framework for precise intervention through the dimensions of motivation, ability, and prompts. Accordingly, this study developed an FBM-based AI-HEALS intervention and will validate its effectiveness via a Randomized Controlled Trial (RCT) to optimize digital transitional care after breast cancer surgery.
Methods: The study will conduct a single-blind, single-center randomized controlled trial in the Fourth Central Hospital of Baoding City, Hebei Province, with female postoperative breast cancer patients aged ≥18 years with stage I-III breast cancer. The control group received routine care, while the intervention group received the AI-HEALS intervention plan in addition to the routine care. Primary outcomes include changes in self-management behavior at baseline and 4, 12, and 24 weeks of follow-up. Secondary outcomes encompass mental health status, self-management efficacy, quality of life, and physiological-related indicators.
Discussion: The aim of this study was to develop an intervention programme for postoperative self-management in breast cancer patients by using the Fogg Behavior Model (FBM) as the theoretical framework and the AI-HEALS system as the intervention platform. Although FBM has shown effectiveness in explaining and promoting health behaviors in various chronic disease populations, systematic studies of its application to postoperative breast cancer self-management are lacking. Our intervention framework aims to stimulate motivation, enhance ability, and provide timely prompts to overcome the limitations of single-component or non-theory-based interventions in complex home-based rehabilitation scenarios. The AI-HEALS system addresses the challenges of traditional mHealth interventions—such as insufficient theoretical grounding, lack of personalisation, and inadequate handling of action triggers—and is expected to improve patients' self-management behaviors, mental health, and quality of life through precise knowledge delivery, dynamic AI-powered question-and-answer support, and full-cycle follow-up management. The development of the AI-HEALS system helps to reduce the burden on healthcare professionals, improve the distribution of healthcare resources, and have potential health economic benefits.
Clinical trial registration: https://www.chictr.org.cn/showproj.html?proj=317062 , Identifier: ChiCTR2600126533.
Related
- Evaluation of Intraperitoneal Instillation Combined with Port-Site Infiltration of 0.5% Bupivacaine for Postoperative Pain Management in Laparoscopic Cholecystectomy: A Prospective Randomized Controlled Trial
- Study of weight loss intervention to find an effective strategy for obesity management and the TARGET of weight loss amount for reducing health disorders (SLIM-TARGET): a randomized controlled trial
- The impact of intraoperative use of the inhaled anesthetic desflurane on postoperative recovery quality after noncardiac surgery: a meta-analysis of randomized controlled trials
- Compound chamomile and lidocaine hydrochloride gel for postoperative sore throat after nasotracheal intubation: a randomized controlled trial
- Efficacy of Stellate Ganglion Block for Preventing Postoperative Atrial Fibrillation After Cardiac Surgery: A Randomized, Double‐Blind, Placebo‐Controlled Trial
BibTeX
@article{heng2026effects,
title = {{Effects of the AI-HEALS intervention based on the Fogg behavior model on self-management in postoperative breast cancer patients: a randomized controlled trial study protocol}},
author = {Lidan Heng and Jing Wang and Siyu Chen and Zixu Zhang and Wei Zhang and Lihua Nie and Weina Lv and Dandan Yang and Sen Li and Huitao Wang},
journal = {Frontiers in public health},
year = {2026},
month = oct,
doi = {10.3389/fpubh.2026.1909032},
url = {https://europepmc.org/article/PMC/PMC13690810},
note = {CC BY},
}
RIS
TY - JOUR
TI - Effects of the AI-HEALS intervention based on the Fogg behavior model on self-management in postoperative breast cancer patients: a randomized controlled trial study protocol
AU - Lidan Heng
AU - Jing Wang
AU - Siyu Chen
AU - Zixu Zhang
AU - Wei Zhang
AU - Lihua Nie
AU - Weina Lv
AU - Dandan Yang
AU - Sen Li
AU - Huitao Wang
PY - 2026
DA - 2026/10/09
JO - Frontiers in public health
DO - 10.3389/fpubh.2026.1909032
UR - https://europepmc.org/article/PMC/PMC13690810
AB - Background: Breast cancer is the most common malignancy among women, and postoperative self-management is critically associated with long-term quality of life. Traditional clinical nursing and mobile health interventions frequently lack behavioral theory support, thereby failing to meet individualized rehabilitation needs. The Fogg Behavior Model (FBM) provides a theoretical framework for precise intervention through the dimensions of motivation, ability, and prompts. Accordingly, this study developed an FBM-based AI-HEALS intervention and will validate its effectiveness via a Randomized Controlled Trial (RCT) to optimize digital transitional care after breast cancer surgery. Methods: The study will conduct a single-blind, single-center randomized controlled trial in the Fourth Central Hospital of Baoding City, Hebei Province, with female postoperative breast cancer patients aged ≥18 years with stage I-III breast cancer. The control group received routine care, while the intervention group received the AI-HEALS intervention plan in addition to the routine care. Primary outcomes include changes in self-management behavior at baseline and 4, 12, and 24 weeks of follow-up. Secondary outcomes encompass mental health status, self-management efficacy, quality of life, and physiological-related indicators. Discussion: The aim of this study was to develop an intervention programme for postoperative self-management in breast cancer patients by using the Fogg Behavior Model (FBM) as the theoretical framework and the AI-HEALS system as the intervention platform. Although FBM has shown effectiveness in explaining and promoting health behaviors in various chronic disease populations, systematic studies of its application to postoperative breast cancer self-management are lacking. Our intervention framework aims to stimulate motivation, enhance ability, and provide timely prompts to overcome the limitations of single-component or non-theory-based interventions in complex home-based rehabilitation scenarios. The AI-HEALS system addresses the challenges of traditional mHealth interventions—such as insufficient theoretical grounding, lack of personalisation, and inadequate handling of action triggers—and is expected to improve patients' self-management behaviors, mental health, and quality of life through precise knowledge delivery, dynamic AI-powered question-and-answer support, and full-cycle follow-up management. The development of the AI-HEALS system helps to reduce the burden on healthcare professionals, improve the distribution of healthcare resources, and have potential health economic benefits. Clinical trial registration: https://www.chictr.org.cn/showproj.html?proj=317062 , Identifier: ChiCTR2600126533.
SN - 2296-2565
ER -