NCT07490665

Brief Summary

This study aimed to examine the effect of artificial intelligence-assisted case discussions on midwifery students' use and proficiency of artificial intelligence technologies and their clinical competency levels. With the rapid development of artificial intelligence, its integration into healthcare education has become increasingly important. Supporting case-based learning with AI tools may enhance students' clinical decision-making, problem-solving, and critical thinking skills. Therefore, this study evaluates the contribution of AI-assisted educational approaches to the professional development of midwifery students.

Trial Health

63
Monitor

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
81

participants targeted

Target at P75+ for not_applicable healthy

Timeline
1mo left

Started Mar 2026

Shorter than P25 for not_applicable healthy

Geographic Reach
1 country

1 active site

Status
not yet recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

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Study Timeline

Key milestones and dates

Study Progress73%
Mar 2026Jul 2026

First Submitted

Initial submission to the registry

March 13, 2026

Completed
3 days until next milestone

Study Start

First participant enrolled

March 16, 2026

Completed
8 days until next milestone

First Posted

Study publicly available on registry

March 24, 2026

Completed
3 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

June 8, 2026

Completed
1 month until next milestone

Study Completion

Last participant's last visit for all outcomes

July 20, 2026

Expected
Last Updated

March 24, 2026

Status Verified

March 1, 2026

Enrollment Period

3 months

First QC Date

March 13, 2026

Last Update Submit

March 18, 2026

Conditions

HealthyStudent

Keywords

Artificial IntelligenceMidwiferyClinical CompetenceProblem-Based LearningHealth Occupations

Outcome Measures

Primary Outcomes (2)

  • Level of artificial intelligence usage

    Changes in the level of AI usage among midwifery students after training, compared to baseline values. The Student Attitudes toward Artificial Intelligence Scale (SATAI), developed in 2025, will be used for measurement.The scale, developed using a five-point Likert scale (1=Strongly disagree and 5=Strongly agree), does not contain any reverse-coded items. The highest possible score on the scale is 130, and the lowest is 26, with higher scores reflecting more positive attitudes towards artificial intelligence.

    Through study completion, an average of 3 months

  • Usage and proficiency level

    This will be measured using the Generative Artificial Intelligence Use and Proficiency (GAAP) Scale, developed in 2024. Planned as a five-point Likert scale (fully reflecting = 5 points - not reflecting = 1 point), an increase in the score obtained from this scale indicates a high level of artificial intelligence use and proficiency. The minimum possible score on the scale is 19, and the maximum is 95.

    Through study completion, an average of 3 months

Study Arms (2)

AI Case Group

EXPERIMENTAL

Students in the experimental group will be presented with a case scenario and given 30 minutes to review it. During this time, they will be asked to develop a care plan for the case. Subsequently, within a 60-minute session, the researcher will present a care plan prepared with artificial intelligence assistance for the same case. A case discussion will then be conducted by comparing the care plans developed by the students with the AI-assisted care plan.

Behavioral: Experimental AI Case Group

Control

NO INTERVENTION

Discussion of routinely implemented maintenance plan

Interventions

Experimental AI Case GroupBEHAVIORAL

Students in the experimental group will be presented with a case scenario and given 30 minutes to review it. During this time, they will be asked to develop a care plan for the case. Subsequently, within a 60-minute session, the researcher will present a care plan prepared with artificial intelligence assistance for the same case. A case discussion will then be conducted by comparing the care plans developed by the students with the AI-assisted care plan.

AI Case Group

Eligibility Criteria

Sexfemale(Gender-based eligibility)
Gender Eligibility DetailsIn our country, midwifery students are mostly women.
Healthy VolunteersYes
Age GroupsChild (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

  • Being a 3rd/4th year student in the Midwifery department
  • Having previously taken courses on Healthy and High-Risk Pregnancy
  • Having prepared and presented at least one midwifery care plan

You may not qualify if:

  • Using more than 20% absenteeism in field applications

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Fenerbahce University

Istanbul, Atasehır, 34758, Turkey (Türkiye)

Location

Study Officials

  • Sinem Dinmez, Assistant Professor

    Mudanya University

    STUDY DIRECTOR

  • Zeynep Ogul, Assistant Professor

    STUDY DIRECTOR

Central Study Contacts

Ayşe G Bursa, Assistant Professor

CONTACT

+905062984670aysegul.bursa@fbu.edu.tr

Sinem Dinmez, Assistant Professor

CONTACT

+905063568804

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
SINGLE
Who Masked
PARTICIPANT
Purpose
HEALTH SERVICES RESEARCH
Intervention Model
PARALLEL
Model Details: As an intervention, an AI-powered maintenance plan will be discussed.
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Assistant Professor

Study Record Dates

First Submitted

March 13, 2026

First Posted

March 24, 2026

Study Start

March 16, 2026

Primary Completion

June 8, 2026

Study Completion (Estimated)

July 20, 2026

Last Updated

March 24, 2026

Record last verified: 2026-03

Data Sharing

IPD Sharing
Will not share

We are not considering an explosion yet because data collection has not begun.

Locations

TU(1)