Artificial Intelligence-Supported Nursing Program for Sleep Quality in People With an Ostomy

Summary

Individuals living with an intestinal or urinary stoma frequently report disturbed sleep. Night-time pouch filling and leakage, odour and gas concerns, restricted sleeping positions, peristomal skin problems and the need for night-time pouch emptying interrupt sleep, while anxiety, depressive symptoms, altered body image and social withdrawal add to this burden. Poor sleep in this population has been associated with reduced quality of life and impaired daytime functioning; however, most of the available evidence is cross-sectional and based exclusively on self-reported measures. Nursing interventions that specifically target sleep in people with a stoma are few, generally consist of a single component, and have rarely been tested in randomised designs or alongside objective sleep measurement.

This trial evaluates an Artificial Intelligence-Supported Multimodal Nursing Intervention (AI-MNI) developed to improve sleep quality in adults living with a stoma. The intervention was designed in line with the Medical Research Council framework for complex interventions and is delivered over four weeks through the institutional web-based learning management system. It comprises five structured modules: stoma care and night-time comfort; sleep hygiene and night routine; psychological wellbeing and relaxation techniques; body image, self-esteem and sexual health; and physical activity and daily energy management. Each module combines written material, video, visual guides, checklists and short knowledge checks. A rule-based chatbot embedded in the platform supports participants by prioritising content, suggesting review of relevant material and responding to questions within a pre-approved educational content set; it does not provide diagnosis, treatment advice or clinical decision support. All content was evaluated for content validity by an expert panel before implementation.

The study is a two-arm, parallel-group randomised controlled trial conducted in the stomatherapy unit of a university hospital. Forty-two adults (21 per group) with a colostomy, ileostomy or urostomy of at least three months' duration and a Pittsburgh Sleep Quality Index (PSQI) global score greater than 5 will be allocated in a 1:1 ratio using permuted block randomisation with variable block sizes, stratified by sex and stoma type. Allocation is concealed through a central, password-protected web-based system, and statistical analyses are performed by a statistician blinded to group codes. The intervention group receives AI-MNI in addition to standard care; the control group receives standard care alone and is offered access to the programme after the final assessment (delayed-access design). Assessments are conducted at baseline (T0), at the first month (T1) and at the third month (T2). The primary outcome is the change in PSQI global score from baseline to the first month, with the third-month assessment used to examine whether any improvement is maintained. Secondary outcomes are objective sleep parameters (total sleep time, sleep efficiency, sleep stage indicators and sleep onset latency) recorded with a consumer wrist-worn device on three consecutive nights at each assessment point, and stoma-specific quality of life. Module completion, session duration and level of interaction are reported as process outcomes. Analyses follow the intention-to-treat principle and are based primarily on linear mixed-effects models.

Conditions

• Ostomy
• Sleep Quality
• Quality of Life

Interventions

BEHAVIORAL

AI-MNI: Artificial Intelligence-Supported Multimodal Nursing Intervention

Four-week, module-based digital nursing intervention delivered through the institutional web-based learning management system, in addition to standard stomatherapy care. Five modules address stoma care and night-time comfort; sleep hygiene and night routine; psychological wellbeing and relaxation techniques; body image, self-esteem and sexual health; and physical activity and daily energy management. Each module combines written material, video, visual guides, checklists and short knowledge checks, and all modules are available throughout the four-week period. A rule-based chatbot embedded in the platform prioritises content, suggests review of relevant material and answers questions within a pre-approved educational content set; it does not provide diagnosis, treatment advice or clinical decision support. Content validity was established with an expert panel, and platform use (module completion, session duration, interaction) is recorded as a process outcome.

Sponsors & Collaborators

• Koç University

  lead OTHER

Study Design

Allocation

RANDOMIZED

Purpose

SUPPORTIVE_CARE

Masking

NONE

Model

PARALLEL

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2026-10-15

Primary Completion

2027-03-15

Completion

2027-07-15

Countries

• Turkey (Türkiye)

Study Locations