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NCT Number: NCT07720531

Smart Normal Labor: Healthcare Providers' Experience With an AI-Based Mobile App

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]

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Key information

Conditions

Normal Labor

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

The intervention group

Other

participants who actively use the AI application during labor management,

Primary outcomes

  1. Primary Outcome

    Time frame: During labor management (from the onset of active labor until delivery, assessed up to 6-8 hours).

    The time required for healthcare providers to make appropriate clinical decisions during the management of normal labor, measured using a structured clinical decision-making assessment tool.

Secondary outcomes

  1. Secondary Outcome

    Time frame: During labor management (from the onset of active labor until delivery, assessed up to 6-8 hours).

    Clinical decision-making accuracy will be assessed using a validated Clinical Decision-Making Checklist for Normal Labor. Total scores range from [minimum] to [maximum], with higher scores indicating greater clinical decision-making accuracy.

Study contacts

Contact information is provided by the study sponsor or research team.

Basma W Basma

CONTACT

[email protected]

01552602703

Sponsors and collaborators

Lead sponsor

Delta University for Science and Technology

Other

Registry information

Official study title

Smart Normal Labor From Healthcare Providers' Perspective: Evaluating Clinical Decision-Making Speed, Diagnostic Accuracy, Satisfaction, and Experience Using an AI-Based Mobile Application

Acronym: Smart labor

Important dates

Study start
2026
Primary completion
2026
Study completion
2026
First posted
Jul 22, 2026
Registry last updated
Jul 22, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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