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

NCT06118424 | Completed

• 1 other identifier: SakaryaU-metinyildiz-005
• Study Type: interventional
• Target: 80
• Locations: 1 country
• Sites: 1

Brief 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

Keywords

Digital Manipulation; deepfake; The Believability of What Doesn't Exist; Nursing Education

Outcome Measures

Primary Outcomes (3)

• Teaching Material Motivation Scale

  Teaching Material Motivation Scale Teaching Material Motivation Instructional Material Motivation Scale: It was developed to measure the effect of instructional materials on students' motivation. The scale is a 5-point Likert-type scale consisting of 36 items. Each item in the scale will be scored from 1 (Not True) to 5 (Very True) by the students. Accordingly, the lowest score on the scale is 36, and the highest score is 180. An increase in the score on the scale indicates an increase in motivation.

  Evaluated at the end of 6 weeks.

• Course Interest Scale

  Student Interest Scale; Developed by (Mazer, 2013) in order to evaluate its relationship with variables such as learning motivation, effective learning, and level of participation in the lesson, the Class Interest Scale is a 5-point Likert-type measurement tool consisting of 16 items and two sub-dimensions (affective and cognitive interest). et al (2015) ("1" Strongly disagree, "2" Disagree, "3" Undecided, "4" Agree, "5" Totally Agree). There is no reverse coded item in the scale. Affective interest sub-dimension of the scale consists of 9 items and cognitive interest sub-dimension consists of 7 items. As the scale score increases, the interest increases.

  Evaluated at the end of 6 weeks

• Attitude Scale Towards Learning

  Attitude Scale Towards Learning:Attitude Scale Towards Learning: The scale developed by Çetin et al. was developed to determine students' attitudes. As a result of all validity and reliability analyzes, there are 34 items in total. Of these scale items, 25 are positive and 9 are negative. The five-point Likert scale is "Totally Agree", "Strongly Agree", "Partly Agree", "Disagree", "Strongly Disagree". The highest attitude score that can be obtained from the scale is 170 and the lowest attitude score is 34. As the attitude score increases, the positive attitude increases.

  Evaluated at the end of 6 weeks

Study Arms (2)

deepfake group

EXPERIMENTAL

The experimental group was trained and monitored with deep fake videos every week for 6 weeks.

Behavioral: deepfake video

Control group

NO INTERVENTION

The control group was given a pre-test before the study and a post-test at the end of the study, without any intervention.

Interventions

deepfake video BEHAVIORAL

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.

deepfake group

Eligibility Criteria

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

You may qualify if:

• th year students of Muş Alparslan University, Faculty of Health Sciences, Department of Nursing 18 years and older Volunteer

You may not qualify if:

• Not being a 4th year nursing student, Not volunteering

Sponsors & Collaborators

• Sakarya University: lead

Study Sites (1)

Sakarya University

Sakarya, 54000, Turkey (Türkiye)

Location

Study Officials

• Sakarya University

  Sakarya University

  STUDY DIRECTOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Purpose: PREVENTION
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Nurse (Asst.Prof.Dr.)

Study Record Dates

• First Submitted: October 31, 2023
• First Posted: November 7, 2023
• Study Start: March 1, 2023
• Primary Completion: June 1, 2023
• Study Completion: October 1, 2023
• Last Updated: November 7, 2023

Record last verified: 2023-10

Locations

TU (1)