DialysisBot: Design, Implementation, and Evaluation of an AI-based Conversational Agent to Support Self-management in Patients Undergoing Hemodialysis
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 40
- 试验地点
- 1
- 主要终点
- Feasibility of the DialysisBot Intervention
研究概览
简要总结
End-stage kidney disease requiring hemodialysis is a chronic condition with substantial clinical, functional, and psychosocial burden. Maintaining an adequate health status between dialysis sessions depends largely on patients' ability to self-manage key aspects of treatment, including fluid restriction, dietary control, and vascular access care. Adherence in this population remains frequently suboptimal, and elevated interdialytic weight gain (IDWG), hyperphosphatemia, and hyperkalemia are among the most common complications associated with non-adherence.
DialysisBot is a multiplatform, artificial intelligence-based conversational agent designed to support hemodialysis patients in the day-to-day self-management of their disease. The system combines a generative large language model for natural dialogue management, a fine-tuned BERT classifier for recognizing the domain of each patient request (diet, fluid intake, vascular access care, or organizational aspects of dialysis), and a vector-similarity retrieval engine that limits every response to a clinically validated knowledge base preloaded by the research team and approved by the hospital institution. The system performs no autonomous web search. When the cosine similarity between a user query and the indexed reference documents falls below a predefined threshold, the system withholds a clinical answer and instead informs the patient that it cannot respond, directing them to contact healthcare staff; this mechanism is the main technical safeguard against hallucinated or unvalidated responses.
This is a prospective experimental pilot study evaluating the feasibility, acceptability, impact, and user satisfaction associated with DialysisBot as a self-management support tool for patients undergoing hemodialysis. Secondary objectives include assessing support for dietary management (phosphorus, potassium, and sodium restriction), support for interdialytic fluid intake control, whether system-provided guidance on vascular access management (arteriovenous fistula and central venous catheter) is put into practice and consistent with current standards of care, the impact on treatment adherence, and the barriers, facilitators, and overall user experience associated with the intervention.
The study is organized into two methodological phases: a quantitative longitudinal phase (T0 baseline, T1 at 1 month, T2 at 3 months) using standardized patient-reported outcome measures and routine clinical parameters, followed by a qualitative phase conducted after T2, based on semi-structured interviews analyzed through reflexive thematic analysis. A convenience sample of 20-40 adult patients undergoing chronic hemodialysis, recruited through a participating dialysis center and/or an online patient community, will be enrolled and trained on the application before use. As a pilot feasibility study, its results are intended to inform the design and sample size of future, larger-scale confirmatory trials.
详细描述
Background and Rationale
Patients with end-stage renal disease undergoing chronic hemodialysis must manage a demanding interdialytic regimen, including fluid restriction, dietary control of phosphorus, potassium, and sodium intake, and vascular access care (arteriovenous fistula or central venous catheter). The cognitive and behavioral burden of this regimen, combined with limited continuous support outside dialysis sessions, contributes to often suboptimal adherence. Elevated interdialytic weight gain, hyperphosphatemia, and hyperkalemia are well-documented consequences of non-adherence and are associated with increased morbidity.
mHealth technologies and AI-based conversational agents (chatbots) have shown growing potential to support patients with chronic conditions by improving access to personalized health information, increasing patient engagement, and promoting appropriate self-management behaviors, particularly in populations with limited access to traditional educational resources. Systematic reviews have reported positive effects of conversational agents on clinical and behavioral outcomes in chronic disease, and a recent scoping review mapping mHealth use among dialysis patients found that self-management applications were associated with improvements in interdialytic weight gain, phosphatemia, potassium levels, and adherence to dietary prescriptions.
Despite this promising evidence base, data specific to AI-based chatbots in the hemodialysis population remain limited. To date, neither the international literature nor Italian clinical practice offers a validated conversational agent specifically designed for this population; the gap concerns both the lack of purpose-built solutions and the absence of systematic feasibility, acceptability, and impact evaluations in real-world clinical settings. This study addresses this gap by implementing and evaluating the clinical feasibility, safety, and impact of DialysisBot, hypothesizing that such an intervention may contribute to patient empowerment, reduce interdialytic complications, and improve overall quality of care.
Study Objectives
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Supportive Care
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Age ≥ 18 years
- •Patients undergoing chronic hemodialysis treatment
- •Availability of a compatible digital device (smartphone, tablet, or computer)
- •Adequate understanding of the Italian language
- •Sufficient basic digital literacy
- •Signed informed consent A purposive subsample (n = 10-15) of enrolled participants will additionally take part in semi-structured qualitative interviews at the end of the study.
排除标准
- •Age under 18 years
- •Significant cognitive impairment preventing use of the application
- •Significant inability to use digital tools
- •Absence of signed informed consent
研究组 & 干预措施
DialysisBot: AI Conversational Agent for Self-Management Support
All enrolled participants receive access to DialysisBot, a multiplatform AI-based conversational agent designed to support self-management in patients undergoing chronic hemodialysis. The intervention combines a generative large language model for natural dialogue, a fine-tuned BERT classifier for intent recognition (diet, fluid intake, vascular access care), and a vector-similarity retrieval engine restricting responses to a clinically validated knowledge base approved by the research team and the hospital institution. Before starting use of the application, participants receive individual training, including a guided walkthrough of the interface, an integrated digital user manual, and ongoing technical support for the duration of the study (approximately 3 months, from baseline/T0 to the final assessment/T2). Participants use DialysisBot as needed in their daily self-management routine between dialysis sessions, with no comparator or control group.
干预措施: DialysisBot (Behavioral)
结局指标
主要结局
Feasibility of the DialysisBot Intervention
时间窗: Baseline (T0) through 3 months (T2)
Feasibility will be assessed through four indicators: recruitment rate (proportion of eligible patients who consent to participate), retention rate (proportion of participants completing the study at the final assessment), questionnaire completion rate (proportion of instruments adequately completed from the intermediate to the final assessment), and application engagement (mean number of weekly patient-system interactions, derived from anonymized system logs).
Usability of DialysisBot
时间窗: 1 month (T1)
Usability will be assessed using the Italian version of the Chatbot Usability Scale (BUS-11), an 11-item, 5-point Likert scale (1 = strongly disagree to 5 = strongly agree) validated for AI-based conversational systems. Total score ranges from 11 to 55; higher scores indicate greater perceived usability. \[Time Frame: 1 month (T1)\]
Change in Treatment Adherence Indicators
时间窗: Baseline (T0), 1 month (T1), and 3 months (T2)
Adherence will be measured through routinely collected clinical parameters: interdialytic weight gain (IDWG, from pre- and post-dialysis body weight), serum phosphate (mmol/L), serum potassium (mmol/L), and attendance rate at scheduled dialysis sessions (%).
次要结局
- Change in Health-Related Quality of Life(Baseline (T0) compared to 3 months (T2))
研究者
Elena Barile
Elena Barile
University of Rome Tor Vergata
