Impact of AI-Based Research Training on Nursing Students
Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age18+
SponsorShahid Beheshti University of Medical Sciences
About this trial
The goal of this clinical trial is to find out whether an artificial intelligence (AI)-powered research training course can improve nursing students' research skills, attitudes toward artificial intelligence, and readiness to use AI in research and education.
The main questions this study aims to answer are:
Does AI-powered research training improve nursing students' understanding of research methods?
Does this training improve nursing students' attitudes toward artificial intelligence?
Does the course increase nursing students' readiness and confidence to use artificial intelligence in research-related activities?
Researchers will compare nursing students who take an AI-powered research training course with students who receive usual education without AI-based training.
Participants will:
Be randomly assigned to either the AI-powered research training group or the usual education group
Complete online questionnaires about research skills, attitudes toward artificial intelligence, and readiness to use AI
Attend assessments at three time points: before the course, immediately after the course, and three months later
The AI-powered research training course includes structured sessions on research methods and the responsible use of artificial intelligence tools for literature review, research design, data analysis support, and academic writing. The results of this study may help improve research education and support the safe and effective use of artificial intelligence in nursing education and research.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Enrolled in a nursing program (bachelor's, master's, or doctoral level) at one of the participating universities during the study term.
Completion of at least one course in research methodology in their program curriculum.
Willingness to participate and to provide written informed consent.
Disqualifiers
Prior completion of advanced courses specifically on research-oriented AI or formal AI certification programs.
Inability to attend the scheduled intervention sessions or to access the online learning platform.
Not complete the study questionnaires at all required time points
Withdrawal of consent or failure to complete baseline assessments.
Trial design
Design model
Parallel
Treatments tested in this trial
AI-Powered Research Training Course
Other interventionThe intervention is an artificial intelligence (AI)-powered research training course designed to integrate core research methodology with the practical and responsible use of AI tools. The course consists of eight structured sessions delivered over approximately four weeks and targets nursing students with prior exposure to basic research methods. Unlike traditional research courses, this intervention embeds AI as a supportive research tool across all stages of the research process rather than as a standalone technical subject. Participants learn how AI can assist with selecting research topics, searching and organizing scientific literature, developing research questions, supporting study design decisions, managing references, and drafting research reports, while maintaining critical judgment and methodological rigor. The training emphasizes ethical and responsible use of AI, including issues related to data privacy, transparency, plagiarism prevention, and algorithmic bias.
Treatment groups
104 Participants
are divided into 2 treatment groupsGroup A: AI-Powered Research Training CourseExperimental treatment 1 intervention
Group B: Standard educationNo intervention 0 interventions
Trial outcomes
Primary outcomes
1
Readiness to use artificial intelligence: Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS)
Readiness to use AI will be conceptualized as technical expertise, positive attitudes, and self-confidence in adopting AI tools for research and clinical tasks (29). It will be assessed using the Persian version of the Medical Artificial Intelligence Readiness Scale for Medical Students (MAIRS-MS), a validated 20-item, 4-domain tool (Cognition, Ability, Vision, Ethics) with 5-point Likert items (total score 20-100). Higher scores will indicate greater readiness. The instrument will have demonstrated acceptable reliability (Cronbach's α ≥ 0.80) and structural validity in prior Iranian studies (24,25). Domain and total scores will be calculated for all participants.
Time frame
baseline (T0, pre-intervention), immediately after course completion (T1), and three months after course completion (T2).Secondary outcomes
1
Research literacy: a researcher-developed Research Literacy Questionnaire
Research literacy will be defined as the knowledge and skills in research methodology, study design, data collection, and analysis that will enable researchers to conduct valid studies (5). It will be measured using a researcher-developed 20-item true/false/don't-know questionnaire adapted from Brody et al. (27). Responses will be scored as correct if they match the statement's truth, with a total score of 0-20; higher scores will indicate greater research literacy. The questionnaire will be developed based on the literature, will undergo face and content validation by experts (CVI/CVR), and will be pilot-tested with 50-100 participants to assess item properties, internal consistency (Cronbach's alpha), and 10-14-day test-retest reliability. All participants will complete the questionnaire at each time point, and all data will be included in the intention-to-treat analysis.
Time frame
baseline (T0, pre-intervention), immediately after course completion (T1), and three months after course completion (T2).2
Attitude toward artificial intelligence: AI Attitude Scale (AIAS-4)
Attitudes toward artificial intelligence (AI) will be characterized by an individual's beliefs and affective dispositions regarding the applications and implications of AI (26). The evaluation of this attitude will employ the AI Attitude Scale (AIAS-4), a unidimensional instrument consisting of four items, each rated on a scale from 1 to 10, thereby resulting in a total score that ranges from 4 to 40; higher scores indicate more favorable attitudes toward AI. In the absence of a Persian version of the psychometric AIAS-4, the scale will be translated and culturally adapted through a standard forward-backward translation process, supplemented by cognitive interviews with 10 nursing students, and reviewed by an expert panel. Content validity will be assessed through the Content Validity Index (CVI) and the Content Validity Ratio (CVR). The translated instrument will be pilot-tested with 20 participants, and internal consistency will be evaluated using Cronbach's alpha.
Time frame
baseline (T0, pre-intervention), immediately after course completion (T1), and three months after course completion (T2).Locations
Sponsors and contacts
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Source ClinicalTrials.gov
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