Effect of a Chatbot on Nursing Students' Self-Efficacy in Pediatric Medication Administration

NCT07700290 | Completed

• 1 other identifier: CHATBOT-PED-USKUDAR
• Study Type: interventional
• Target: 106
• Locations: 1 country
• Sites: 1

Brief Summary

This study looked at whether a chatbot can help nursing students feel more confident about giving medicines to children. Giving medicines to children is difficult because doses depend on the child's weight, and mistakes can be harmful. Third-year nursing students starting their pediatric clinical placement took part. They were divided by chance into two groups. Both groups received the usual training. One group also used a chatbot that helped with medicine dose calculations and answered questions about giving medicines to children, based on a trusted nursing textbook. The other group used only the usual references. Students' confidence in giving medicines to children was measured with a questionnaire before and after the placement. The study compared how much each group's confidence changed to see whether the chatbot added a benefit beyond the usual training.

Conditions

Nursing Education; Medication Administration; Self-Efficacy; Patient Safety

Keywords

chatbot; Artificial Intelligence; Nursing Students; Pediatric Nursing; Medication Administration; Self-Efficacy; Digital Health Education

Outcome Measures

Primary Outcomes (1)

• Self-efficacy in pediatric medication administration

  Self-efficacy measured with the Medication Administration Self-Efficacy Scale in Children for Nursing Students (MASSCNS), a 16-item, 5-point Likert scale with total scores ranging from 16 to 80. Higher scores indicate greater self-efficacy. Change from pre-test to post-test was compared between groups.

  Baseline (before the pediatric clinical placement) and post-intervention (after completion of the placement, approximately at the end of the clinical rotation). Baseline (Day 1) and post-intervention (Week 8)

Study Arms (2)

Experimental group

EXPERIMENTAL

Participants received the routine curriculum and additionally used a web-based chatbot (a dose calculator and a book-based question-answer assistant) before and during the pediatric clinical placement.

Behavioral: Chatbot-supported training

Control group

NO INTERVENTION

Participants received the routine curriculum and accessed standard clinical references only, without the chatbot.

Interventions

Chatbot-supported training BEHAVIORAL

A web-based chatbot accessible via mobile and desktop browsers, containing two modules: an advanced dose calculator that computes required drug amount and volume from the child's weight, prescribed dose, and drug concentration; and a question-answer assistant that responds to pediatric medication questions using content drawn solely from a validated pediatric nursing reference textbook.

Experimental group

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Third-year nursing student
• Entering the pediatric (child health and diseases) clinical placement for the first time
• Owning a smartphone or computer
• Providing voluntary informed consent to participate

You may not qualify if:

• Previous completion of a pediatric clinical placement
• Prior participation in a similar educational intervention

Sponsors & Collaborators

• Tugba KARAKUS TURKER: lead

Study Sites (1)

Üsküdar Univercity

Istanbul, Turkey (Türkiye)

Location

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: OUTCOMES ASSESSOR
• Purpose: OTHER
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Principal Investigator

Model Details: Two-group parallel pre-test-post-test randomized controlled trial

Study Record Dates

• First Submitted: July 5, 2026
• First Posted: July 14, 2026
• Study Start: January 1, 2026
• Primary Completion: July 1, 2026
• Study Completion: July 1, 2026
• Last Updated: July 14, 2026

Record last verified: 2026-07

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)