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

21. juli 2026 opdateret af: Basma Wageah Mohamed Mohamed Elrefay, Delta University for Science and Technology

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

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]

Studieoversigt

Status

Rekruttering

Betingelser

Intervention / Behandling

Detaljeret beskrivelse

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.

Undersøgelsestype

Interventionel

Tilmelding (Anslået)

427

Fase

  • Ikke anvendelig

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiekontakt

Studiesteder

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

  • Barn
  • Voksen
  • Ældre voksen

Tager imod sunde frivillige

Ja

Beskrivelse

Inclusion Criteria

Participants must meet the following conditions to be included in the study:

  1. Healthcare providers (obstetricians and nurses) currently working in the Labor Kiosk, Obstetrics and Gynecology Department, or Outpatient Gynecology Clinics at Mansoura University Hospital.
  2. Direct involvement in the care and supervision of women in active labor.
  3. 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).
  4. For the control group: no prior use of the AI-based application, following standard care practices.
  5. Willingness to participate and provide informed consent. Exclusion Criteria

Participants will be excluded if they:

  1. Are healthcare providers not directly involved in labor management (e.g., administrative staff or laboratory personnel).
  2. Have less than the minimum required clinical experience in labor management (e.g., <6 months).
  3. Are on leave or unavailable during the study period.
  4. Decline to participate or do not provide informed consent.

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

  • Primært formål: Sundhedstjenesteforskning
  • Tildeling: Ikke-randomiseret
  • Interventionel model: Parallel tildeling
  • Maskning: Enkelt

Våben og indgreb

Deltagergruppe / Arm
Intervention / Behandling
Eksperimentel: AI-Based Smart Normal Labor Application
Healthcare providers use the AI-based Smart Normal Labor Application during the management of normal labor to support clinical decision-making, labor monitoring, and timely identification of labor-related conditions.
Andet: The intervention group
participants who actively use the AI application during labor management,
Ingen indgriben: Routine Care Group
Healthcare providers provide routine normal labor management according to standard institutional protocols without using the AI-based Smart Normal Labor Application.

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Primary Outcome
Tidsramme: 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.
During labor management (from the onset of active labor until delivery, assessed up to 6-8 hours).

Sekundære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Secondary Outcome
Tidsramme: 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.
During labor management (from the onset of active labor until delivery, assessed up to 6-8 hours).

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

Delta University for Science and Technology

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Faktiske)

6. maj 2026

Primær færdiggørelse (Faktiske)

21. juli 2026

Studieafslutning (Anslået)

30. juli 2026

Datoer for studieregistrering

Først indsendt

4. april 2026

Først indsendt, der opfyldte QC-kriterier

21. juli 2026

Først opslået (Faktiske)

22. juli 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

22. juli 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

21. juli 2026

Sidst verificeret

1. januar 2026

Mere information

Begreber relateret til denne undersøgelse

Nøgleord

Andre undersøgelses-id-numre

  • Smart Normal Labor

Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter

Studerer et amerikansk FDA-reguleret lægemiddelprodukt

Ingen

Studerer et amerikansk FDA-reguleret enhedsprodukt

Ingen

Disse oplysninger blev hentet direkte fra webstedet clinicaltrials.gov uden ændringer. Hvis du har nogen anmodninger om at ændre, fjerne eller opdatere dine undersøgelsesoplysninger, bedes du kontakte register@clinicaltrials.gov. Så snart en ændring er implementeret på clinicaltrials.gov, vil denne også blive opdateret automatisk på vores hjemmeside .

Kliniske forsøg med Normalt arbejde

Kliniske forsøg med The intervention group

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