Smart Normal Labor: Healthcare Providers' Experience With an AI-Based Mobile App
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: The intervention group.
- Who it may be relevant to
- Registry conditions: Normal Labor. Basic parameters: No limits · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Egypt
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Smart Normal Labor From Healthcare Providers' Perspective: Evaluating Clinical Decision-Making Speed, Diagnostic Accuracy, Satisfaction, and Experience Using an AI-Based Mobile Application
Overview
Pregnancy and childbirth are uniquely important events in women's lives because they are accompanied by major physical, emotional, and psychological changes. Maternal satisfaction, emotional well-being, and perceptions of childbirth are strongly influenced by the quality of labor management. A woman's childbirth experience is shaped by multiple factors, including communication, autonomy, and active participation in the decision-making process. These factors are widely recognized as important indicators of the quality of maternity care. \[1\] Recent demographic changes and global population growth have placed increasing demands on healthcare systems, particularly maternal health services. High birth rates in some regions, combined with shortages of trained healthcare professionals, have created a need for scalable, adaptable, and innovative models of care. In response to these challenges, digital health technologies have emerged as promising tools to enhance the quality of maternity care and support both healthcare providers and pregnant women. \[2\]
Detailed description
General Objective
To evaluate the impact of an artificial intelligence (AI)-based smart normal labor application on healthcare providers' clinical decision-making speed, diagnostic accuracy, satisfaction, and overall clinical experience during the management of normal labor.
Specific Objectives
To assess the effect of the AI-based smart normal labor application on the speed of clinical decision-making among obstetricians and nurses during the management of normal labor.
To evaluate the effect of the AI-based smart normal labor application on diagnostic accuracy during the management of normal labor.
To evaluate healthcare providers' satisfaction with the AI-based smart normal labor application.
To assess healthcare providers' overall clinical experience while using the AI-based smart normal labor application during normal labor management.
To identify barriers and facilitators associated with the adoption and usability of the AI-based smart normal labor application in clinical practice.
Interventions
- Other The intervention group
participants who actively use the AI application during labor management,
Primary outcome measures
- Primary Outcome [Time frame: During labor management (from the onset of active labor until delivery, assessed up to 6-8 hours).]
Secondary outcome measures (1)
- Secondary Outcome [Time frame: During labor management (from the onset of active labor until delivery, assessed up to 6-8 hours).]
Eligibility criteria
Inclusion criteria
Participants must meet the following conditions to be included in the study:
- Healthcare providers (obstetricians and nurses) currently working in the Labor Kiosk, Obstetrics and Gynecology Department, or Outpatient Gynecology Clinics at Mansoura University Hospital.
- Direct involvement in the care and supervision of women in active labor.
- For the intervention group: previous exposure to and use of the AI-based smart normal labor application for a minimum defined period (e.g., 1 month).
- For the control group: no prior use of the AI-based application, following standard care practices.
- Willingness to participate and provide informed consent. Exclusion Criteria
Participants will be excluded if they:
- Are healthcare providers not directly involved in labor management (e.g., administrative staff or laboratory personnel).
- Have less than the minimum required clinical experience in labor management (e.g., <6 months).
- Are on leave or unavailable during the study period.
- Decline to participate or do not provide informed consent.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Allocation
- Non-randomized
- Model
- Parallel assignment
- Masking
- Single blind
- Primary purpose
- Health services research
Study locations
Egypt · 1 center
- Basma wageah Basma — Al Mansurah
Identifiers
NCT: NCT07720531 · Smart Normal Labor