Impact of Artificial Intelligence Discussion on Midwifery Students

March 18, 2026 updated by: Ayşe Gül Bursa, Fenerbahce University

The Impact of Artificial Intelligence-Assisted Case Discussion on Artificial Intelligence Attitude, Usage and Proficiency Among Midwifery Students

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.

Study Overview

Status

Status

Indicates the current recruitment status or the expanded access status.
Not yet recruiting

Conditions

Conditions

The disease, disorder, syndrome, illness, or injury that is being studied. On ClinicalTrials.gov, conditions may also include other health-related issues, such as lifespan, quality of life, and health risks.

Intervention / Treatment

Intervention / Treatment

A process or action that is the focus of a clinical study. Interventions include drugs, medical devices, procedures, vaccines, and other products that are either investigational or already available. Interventions can also include noninvasive approaches, such as education or modifying diet and exercise.

Detailed Description

Artificial intelligence (AI), which refers to computer-supported systems capable of performing tasks that require human intelligence, has become increasingly popular in all fields in recent years. AI is a technological system that can think, learn, perceive, make predictions, communicate, and make decisions like humans-or even better than humans. In short, AI can be described as a broad scientific field that simulates the natural intelligence demonstrated by humans through artificial means.

The ability of AI to process the data presented to the system, perform data analyses, generate new ideas, and reach different conclusions has increased the use of AI. These features may surpass human problem-solving and decision-making abilities in terms of speed, efficiency, and quality. Due to these advantages, the use of artificial intelligence in midwifery education has become inevitable.

The Australian College of Midwives (ACM) established the Select Committee on Adopting Artificial Intelligence in March 2024 to support and regulate the adoption of AI. This committee emphasized the necessity and priority of using AI in midwifery education. It also highlighted that midwives should be trained in the use of AI and should be an integral part of the design, implementation, and evaluation of all AI tools used in maternity care (ACM, 2024).

Regarding the use of AI in healthcare, the World Health Organization (WHO) has identified three strategic plans: enabling evidence-based standards, governance, policies, and guidance; facilitating shared investments and a global community of expertise; and implementing sustainable models for the adoption of AI programs at the country level (WHO, 2024). In line with these strategies, it is necessary to integrate AI applications into the midwifery profession.

With the influence of rapidly evolving technology, it has become inevitable to improve midwifery education. In traditional education methods, the instructor plays an active role while students remain passive. However, for learning to be effective, opportunities should be created for students to actively practice their skills and develop critical thinking abilities. Case-based learning in midwifery education is a method that can improve students' logical, clinical, and participatory skills while increasing their knowledge levels.

Supporting case-based learning with artificial intelligence tools can contribute to more accurate diagnosis and the development of clinical decision-making and problem-solving skills. In this way, it becomes possible to educate competent midwives who are confident and capable of using technology effectively.

The aim of this study is 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.

Study Type

Study Type

Describes the nature of a clinical study. Study types include interventional studies (also called clinical trials), observational studies (including patient registries), and expanded access.
Interventional

Enrollment (Estimated)

Enrollment

The number of participants in a clinical study. The "anticipated" enrollment is the target number of participants that the researchers need for the study.
81

Phase

Phase

The stage of a clinical trial studying a drug or biological product, based on definitions developed by the U.S. Food and Drug Administration (FDA). The phase is based on the study's objective, the number of participants, and other characteristics. There are five phases: Early Phase 1 (formerly listed as Phase 0), Phase 1, Phase 2, Phase 3, and Phase 4. Not Applicable is used to describe trials without FDA-defined phases, including trials of devices or behavioral interventions.
  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact

The name and contact information for the person who can answer enrollment questions for a clinical study. Each location where the study is being conducted may also have a specific contact, who may be better able to answer those questions.

Study Contact Backup

  • Name: Sinem Dinmez, Assistant Professor
  • Phone Number: +905063568804

Study Locations

  • Turkey (Türkiye)
    • Atasehır
      • Istanbul, Atasehır, Turkey (Türkiye), 34758
        • Fenerbahçe University

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Eligibility Criteria

The key requirements that people who want to participate in a clinical study must meet or the characteristics they must have. Eligibility criteria consist of both inclusion criteria (which are required for a person to participate in the study) and exclusion criteria (which prevent a person from participating). Types of eligibility criteria include whether a study accepts healthy volunteers, has age or age group requirements, or is limited by sex.

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • 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

Exclusion Criteria:

  • Using more than 20% absenteeism in field applications

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Health Services Research
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm

Participant Group / Arm

A group or subgroup of participants in a clinical trial that receives a specific intervention/treatment, or no intervention, according to the trial's protocol.
Intervention / Treatment

Intervention / Treatment

A process or action that is the focus of a clinical study. Interventions include drugs, medical devices, procedures, vaccines, and other products that are either investigational or already available. Interventions can also include noninvasive approaches, such as education or modifying diet and exercise.
Experimental: AI Case Group
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
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.
No Intervention: Control
Discussion of routinely implemented maintenance plan

What is the study measuring?

Primary Outcome Measures

Primary Outcome Measures

In a clinical study's protocol, the planned outcome measure that is the most important for evaluating the effect of an intervention/treatment. Most clinical studies have one primary outcome measure, but some have more than one.
Outcome Measure
Measure Description
Time Frame
Level of artificial intelligence usage
Time Frame: Through study completion, an average of 3 months
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
Time Frame: Through study completion, an average of 3 months
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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Sponsor

The organization or person who initiates the study and who has authority and control over the study.
Fenerbahce University

Investigators

Investigators

A researcher involved in a clinical study. Related terms include site principal investigator, site sub-investigator, study chair, study director, and study principal investigator.
  • Study Director: Sinem Dinmez, Assistant Professor, Mudanya University
  • Study Director: Zeynep Ogul, Assistant Professor

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

Study Start

The actual date on which the first participant was enrolled in a clinical study. The "anticipated" study start date is the date that the researchers think will be the study start date.
March 16, 2026

Primary Completion (Estimated)

Primary Completion

The date on which the last participant in a clinical study was examined or received an intervention to collect final data for the primary outcome measure. Whether the clinical study ended according to the protocol or was terminated does not affect this date. For clinical studies with more than one primary outcome measure with different completion dates, this term refers to the date on which data collection is completed for all the primary outcome measures. The "anticipated" primary completion date is the date that the researchers think will be the primary completion date for the study.
June 8, 2026

Study Completion (Estimated)

Study Completion

The date on which the last participant in a clinical study was examined or received an intervention/treatment to collect final data for the primary outcome measures, secondary outcome measures, and adverse events (that is, the last participant's last visit). The "anticipated" study completion date is the date that the researchers think will be the study completion date.
July 20, 2026

Study Registration Dates

First Submitted

First Submitted

The date on which the study sponsor or investigator first submitted a study record to ClinicalTrials.gov. There is typically a delay of a few days between the first submitted date and the record's availability on ClinicalTrials.gov (the first posted date).
March 13, 2026

First Submitted That Met QC Criteria

First Submitted That Met QC Criteria

The date on which the study sponsor or investigator first submits a study record that is consistent with National Library of Medicine (NLM) quality control (QC) review criteria. The sponsor or investigator may need to revise and submit a study record one or more times before NLM's QC review criteria are met. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
March 18, 2026

First Posted (Actual)

First Posted

The date on which the study record was first available on ClinicalTrials.gov after National Library of Medicine (NLM) quality control (QC) review has concluded. There is typically a delay of a few days between the date the study sponsor or investigator submitted the study record and the first posted date.
March 24, 2026

Study Record Updates

Last Update Posted (Actual)

Last Update Posted

The most recent date on which changes to a study record were made available on ClinicalTrials.gov. There may be a delay between when the changes were submitted to ClinicalTrials.gov by the study's sponsor or investigator (the last update submitted date) and the last update posted date.
March 24, 2026

Last Update Submitted That Met QC Criteria

Last Update Submitted That Met QC Criteria

The most recent date on which the study sponsor or investigator submitted changes to a study record that are consistent with National Library of Medicine (NLM) quality control (QC) review criteria. It is the responsibility of the sponsor or investigator to ensure that the study record is consistent with the NLM QC review criteria.
March 18, 2026

Last Verified

Last Verified

The most recent date on which the study sponsor or investigator confirmed the information about a clinical study on ClinicalTrials.gov as accurate and current. If a study with a recruitment status of recruiting; not yet recruiting; or active, not recruiting has not been confirmed within the past 2 years, the study's recruitment status is shown as unknown.
March 1, 2026

More Information

Terms related to this study

Keywords

Other Study ID Numbers

Other Study ID Numbers

Identifiers or ID numbers other than the NCT number that are assigned to a clinical study by the study's sponsor, funders, or others. These numbers may include unique identifiers from other trial registries and National Institutes of Health grant numbers.
  • Fenerbahce U Midwifery

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

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

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Healthy

Clinical Trials on Experimental AI Case Group

Search Similar Trials

Sponsors and Collaborators

Medical Conditions

Drug Interventions

Conditions

Rare Diseases

Drug Interventions

Dietary Supplements

Sponsor/Collaborators

Locations

Cookie Settings

We use cookies to ensure that we give you the best experience on our website. For more details carefully read our Privacy and Cookies Policy. ...>>>You can change your preferences or withdraw your consent at any time by deleting the cookies from your website or computer as described in the policy. Please accept it and choose your preferences by ticking the corresponding boxes in the "Manage Settings" section below. Please carefully read our Terms of Service before you proceed with using any part of this website.
«Manage Settings