AI-Powered Interview Simulation to Improve Employability and Reduce Anxiety in Nursing and Midwifery Students

NCT ID: NCT07061132

Last Updated: 2025-07-11

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

Get a concise snapshot of the trial, including recruitment status, study phase, enrollment targets, and key timeline milestones.

Recruitment Status

ACTIVE_NOT_RECRUITING

Clinical Phase

NA

Total Enrollment

90 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-05-08

Study Completion Date

2025-08-30

Brief Summary

Review the sponsor-provided synopsis that highlights what the study is about and why it is being conducted.

This randomized controlled trial aims to evaluate the effectiveness of a ChatGPT-based job interview simulation on the employment perceptions and interview-related anxiety of senior nursing and midwifery students. Transitioning from education to professional practice in healthcare is a critical phase that directly influences employability and career readiness. Particularly for nursing and midwifery students, the ability to navigate job interviews with confidence plays a pivotal role in shaping their future career paths. As such, innovative and digital interventions are needed to better prepare students for this process.

Grounded in Bandura's Social Cognitive Theory and the Technology Acceptance Model (TAM), the study explores how AI-driven simulations affect students' self-efficacy, perceived utility, and usability, and ultimately their career-related outlook. The intervention involves a structured, text-based job interview simulation powered by ChatGPT-4o, during which students respond to a series of nine professionally tailored questions. These questions are aligned with international competency frameworks such as those from ICN (2008) and ICM (2024), focusing on themes like professionalism, teamwork, evidence-based care, communication, and leadership. At the end of the simulation, the chatbot provides brief, constructive feedback to the participant.

A total of 102 final-year students from Koç University and Istanbul University-Cerrahpaşa will be recruited using stratified randomization. Participants will be assigned to either an intervention group, which will complete the ChatGPT simulation, or a control group, which will not receive any interview intervention but will complete the same pre- and post-test questionnaires. Key outcome measures include the Perceived Future Employability Scale (PFE), the Interview Anxiety Scale (MASI-T), and a simulation experience form for the intervention group. Quantitative data will be analyzed using SPSS with appropriate parametric and non-parametric tests based on data distribution, and an intention-to-treat (ITT) approach will be adopted.

To ensure the integrity of the experiment, blinding procedures, strict confidentiality, and group separation protocols will be applied. The simulation will be conducted individually on research-owned devices in private rooms, and no personal or textual data will be saved from the AI interactions. Ethical approval has been obtained from Koç University Social and Behavioral Ethics Committee. Participation is voluntary, informed consent will be collected, and all processes will comply with the Helsinki Declaration and Turkish Personal Data Protection Law.

Ultimately, this study seeks to offer evidence on the pedagogical utility of AI-based simulation tools in preparing healthcare students for employment, while also contributing to the broader field of digital transformation in health education.

Detailed Description

Dive into the extended narrative that explains the scientific background, objectives, and procedures in greater depth.

This study introduces an innovative AI-based intervention aimed at enhancing employability preparation among senior nursing and midwifery students through a simulated job interview experience. The intervention is structured around a generative artificial intelligence model (ChatGPT-4o), which delivers a dynamic, text-based interaction mimicking realistic interview settings. The chatbot prompts are informed by international professional competency frameworks and were developed with input from nursing educators, digital learning experts, and HR professionals.

The conceptual basis of the study combines Social Cognitive Theory and the Technology Acceptance Model, allowing exploration of how simulated, interactive environments contribute to professional readiness. In particular, the study investigates the influence of self-efficacy beliefs and user perception of AI technology on employment-related attitudes.

To ensure validity and usability, a pilot implementation was conducted prior to full deployment. This included iterative testing of the chatbot dialogue flow, question clarity, and interview timing, with input from students outside the main sample. Minor refinements were applied to optimize realism and reduce cognitive overload during simulation.

The AI interaction does not involve natural language learning or data retention; its sole function is to facilitate reflective engagement in a structured scenario. All responses are deleted after the session to comply with data protection standards. The chatbot-generated feedback is non-evaluative and designed to reinforce confidence.

Quantitative analysis will be supplemented with descriptive insights from a post-simulation feedback form that captures students' subjective experience, perceived preparedness, and usability impressions. This mixed-methods integration supports a comprehensive understanding of the intervention's practical and pedagogical value.

Ultimately, the project aims to contribute to the responsible implementation of AI tools in health professions education, particularly in the context of employability, professional identity formation, and digital literacy.

Conditions

See the medical conditions and disease areas that this research is targeting or investigating.

Employment Anxiety Perceived Employability Educational Technology Artificial Intelligence (AI) Nursing Education Research Midwifery Education Simulation Training

Study Design

Understand how the trial is structured, including allocation methods, masking strategies, primary purpose, and other design elements.

Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Interventional Study Model: Parallel Assignment Model Description: Participants will be randomly assigned to one of two parallel groups. The intervention group will receive a ChatGPT-based job interview simulation, while the control group will receive no intervention. Both groups will complete identical pre- and post-intervention assessments.
Primary Study Purpose

OTHER

Blinding Strategy

DOUBLE

Participants Investigators
Group assignment was concealed using a sealed-envelope method. Randomization was conducted by an independent researcher who was not involved in data collection or intervention delivery. Both participants and investigators were unaware of group allocation until the day of implementation.

Study Groups

Review each arm or cohort in the study, along with the interventions and objectives associated with them.

AI-Based Interview Simulation Group

Arm Description:

Participants in this arm will complete a structured, AI-powered job interview simulation using ChatGPT-4o. The simulation will consist of nine competency-based questions aligned with international nursing and midwifery standards. The interaction will be conducted individually in written format, and the chatbot will provide short, supportive feedback at the end. No text data will be saved. This simulation is designed to enhance participants' employability perception and reduce their interview-related anxiety.

Group Type EXPERIMENTAL

AI-Based Interview Simulation

Intervention Type OTHER

The intervention group participated in a structured, text-based job interview simulation supported by ChatGPT-4o, using nine standardized prompts based on ICN (2008) and ICM (2024) core competencies. Developed by experts in simulation and nursing education, the intervention aimed to enhance self-efficacy and reduce interview-related anxiety. Each session lasted 15-20 minutes and concluded with structured feedback provided by ChatGPT. Participants were also offered an optional preparation guide with 40 reflective questions across themes such as communication, anxiety, and self-awareness. This preparation was not mandatory and not included in the simulation time.

No-Intervention Control Group

Participants in this arm will not receive any intervention during the study period. They will complete the same pre-test and post-test assessments as the intervention group but will not participate in the AI-powered interview simulation. After the study concludes, they may optionally be offered access to the simulation for educational purposes, but no data will be collected from that session.

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

Learn about the drugs, procedures, or behavioral strategies being tested and how they are applied within this trial.

AI-Based Interview Simulation

The intervention group participated in a structured, text-based job interview simulation supported by ChatGPT-4o, using nine standardized prompts based on ICN (2008) and ICM (2024) core competencies. Developed by experts in simulation and nursing education, the intervention aimed to enhance self-efficacy and reduce interview-related anxiety. Each session lasted 15-20 minutes and concluded with structured feedback provided by ChatGPT. Participants were also offered an optional preparation guide with 40 reflective questions across themes such as communication, anxiety, and self-awareness. This preparation was not mandatory and not included in the simulation time.

Intervention Type OTHER

Eligibility Criteria

Check the participation requirements, including inclusion and exclusion rules, age limits, and whether healthy volunteers are accepted.

Inclusion Criteria

Must be 18 years of age or older

Must be a senior-year student enrolled in a nursing or midwifery program

Must voluntarily agree to participate in the study

Must provide written informed consent

Exclusion Criteria

Unable to participate in the intervention or assessments due to extended absence or medical leave

Fails to complete either the pre-test or post-test assessments

Previous participation in the pilot phase of the study

Prior exposure to the ChatGPT-based interview simulation used in this study
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

Meet the organizations funding or collaborating on the study and learn about their roles.

Koç University

OTHER

Sponsor Role lead

Responsible Party

Identify the individual or organization who holds primary responsibility for the study information submitted to regulators.

Seda Sarikose

Asst. prof.

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

Learn about the lead researchers overseeing the trial and their institutional affiliations.

SEDA SARIKOSE, Asst. Prof.

Role: PRINCIPAL_INVESTIGATOR

Koc University School of Nursing

Locations

Explore where the study is taking place and check the recruitment status at each participating site.

Koç University School of Nursing

Istanbul, , Turkey (Türkiye)

Site Status

Countries

Review the countries where the study has at least one active or historical site.

Turkey (Türkiye)

Other Identifiers

Review additional registry numbers or institutional identifiers associated with this trial.

2025.203.IRB3.080

Identifier Type: OTHER

Identifier Source: secondary_id

2025.203.IRB3.080

Identifier Type: -

Identifier Source: org_study_id

More Related Trials

Additional clinical trials that may be relevant based on similarity analysis.