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Digital Manipulation 'Deepfake' Technology and the Believability of What Doesn't Exist; Impact on Nursing Education

NCT06118424 · Status: COMPLETED · Phase: NA · Type: INTERVENTIONAL · Enrollment: 80

Last updated 2023-11-07

No results posted yet for this study

Summary

Aim of the research: In addition to traditional education methods, it is important to try different methods to increase interest, attitude and motivation in accordance with the requirements of the age. Our study was carried out to examine the attitudes of nursing students towards the course in line with the principle of attractiveness in education. In addition, the attitudes of the students were determined through deep mock videos. Method of the study: The research is planned to be conducted between March 2023 and June 2023. The population of the research consists of 4th year students of the Department of Nursing, Faculty of Health Sciences, Muş Alparslan University. In the research, the experimental and control groups were determined by randomisation. The sample of the study consisted of all volunteer students. The experimental group consisted of n:40 participants and the control group consisted of n:40 participants. In order to ensure homogeneity in the study, it was paid attention that different branches were in the same class. In order to ensure consistency between the observers, it was carried out in a course conducted by the same instructor.

The study was conducted in accordance with the CONSORT diagram. Data collection was carried out online. Participants answered questions about sociodemographic characteristics and scale items. It took approximately 15 minutes for the participants to answer the questions. The posttest was administered to the control group without any intervention. The experimental group was trained and monitored with deep mock videos every week. The data were evaluated using IBM SPSS Statistics 23 programme.

Conditions

  • Educational Problems

Interventions

BEHAVIORAL

deepfake video

The combination of the words deep and fake is called deepfake in the literature as deep learning. Deepfakes, which have recently become more widely known as a result of the shocking images and sound recordings of many people, from politicians to famous movie stars, are generally hyperrealistic videos in which people's faces and voices are used by other faces and voices without permission and manipulated digitally. Deepfakes rely on neural networks that analyze large data samples to learn to mimic a person's facial expressions, mannerisms, voice and tone. The process involves feeding a deep learning algorithm to exchange images of two people or faces.

Sponsors & Collaborators

  • Sakarya University

    lead OTHER

Principal Investigators

  • Sakarya University · Sakarya University

Study Design

Allocation
RANDOMIZED
Purpose
PREVENTION
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2023-03-01
Primary Completion
2023-06-01
Completion
2023-10-01

Countries

  • Turkey (Türkiye)

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06118424 on ClinicalTrials.gov