Pediatric Drug Application

NCT06836674 | Completed

• 1 other identifier: 72867572-050.01.04-87
• Study Type: interventional
• Target: 150
• Locations: 1 country
• Sites: 1

Brief Summary

The aim of this study was to evaluate the effectiveness of jigsaw, metaverse and classical learning models in developing self-efficacy in medication administration of students taking pediatric nursing courses.

Conditions

Pediatric Nursing; Drugs, Investigational

Keywords

Pediatric Nursing; Pediatric Drug Application; Jigsaw; Metaverse; Classical Education

Outcome Measures

Primary Outcomes (1)

• Pediatric medication administration self-efficacy scale score

  The self-efficacy scale for medication administration in children for nursing students was developed by Bektaş et al. in 2021. The scale consists of 16 items and two sub-dimensions. The medication preparation sub-dimension for children (items for calculating and obtaining medication doses) is items 1, 2, 3, 4, 5, 6, 7, and 8; the medication administration sub-dimension (items for administering the obtained medication) is items 9, 10, 11, 12, 13, 14, 15, and 16. This scale is graded in a 5-point Likert-type scale and is listed as 1 = Definitely not sufficient, 2 = Somewhat sufficient, 3 = Partially sufficient, 4 = Sufficient, 5 = Definitely sufficient. The lowest score obtained from the scale is 16 and the highest score is 80. The scale has no cut-off point; as the score increases, the students' self-efficacy for pediatric medication administration increases. The scale has no reverse-scored items.

  4 month

Study Arms (3)

Intervention Group 1

EXPERIMENTAL

Intervention

Other: Jigsaw

Intervention Group 2

EXPERIMENTAL

Intervention

Other: Metaverse

Control Group

EXPERIMENTAL

Control Group

Other: Classical Education

Interventions

Jigsaw OTHER

In this learning method, students will be divided into main and expert groups. Then, an expert from each group will come and the student will be provided with expertise in the subject given to him/her by the instructor. After the student has specialized, he/she will return to his/her own group and will provide training to his/her friends on the subject he/she has specialized in under the supervision of the instructor of the course. During the student\'s specialization process on the subject given, the necessary literature support and controls will be provided by the instructor of the course.

Intervention Group 1

Metaverse OTHER

In this learning method, the topics determined on pediatric drug applications will be prepared weekly by the relevant instructor of the course and will be transferred to the metaverse and presented to the student in the form of weekly modules.

Intervention Group 2

Classical Education OTHER

In this learning method, the subjects determined by the instructor will be explained to the students in a laboratory environment by the instructor using a presentation (power point) method.

Control Group

Eligibility Criteria

• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• Taking the Child Health and Disease Nursing Course for the first time
• Volunteering to participate in the research

You may not qualify if:

• Not doing any treatment during the dates when the research data was collected
• Not taking any training or courses on drug applications in children in previous periods
• Not taking the course from the bottom

Sponsors & Collaborators

• Suleyman Demirel University: lead

Study Sites (1)

Suleyman Demirel University, Nursing Department

Isparta, 32200, Turkey (Türkiye)

Location

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Purpose: OTHER
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Assisstant Professor

Model Details: randomized controlled trial

Study Record Dates

• First Submitted: August 6, 2024
• First Posted: February 20, 2025
• Study Start: April 1, 2023
• Primary Completion: June 30, 2023
• Study Completion: June 30, 2023
• Last Updated: February 20, 2025

Record last verified: 2025-02

Locations

TU (1)