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

NCT ID: NCT06118424

Last Updated: 2023-11-07

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 80 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2023-03-01
• Study Completion Date: 2023-10-01

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.

Detailed Description

Data collection tools used in the study:

Data Collection Tools

1. Introductory information form: It consists of questions regarding the demographic characteristics of the students.

2. Instructional Material Motivation Scale (TMMÖ) Developed by Keller (2010) and adapted into Turkish by Dinçer et al. (2016), the Instructional Material Motivation Scale (TMMÖ) was developed to measure the effect of teaching materials on students' motivation. The original language of the scale is English. In Keller's original PMS scale, some of the items were designed as positive and some as negative. Accordingly, items 3, 7, 12, 15, 19, 22, 26, 29, 31 and 34 of the scale (10 items in total) are negative; Other items are positive. ÖMMÖ scale is a Likert-type scale consisting of 36 items. Each item on the scale will be scored by students from 1 (Not True) to 5 (Very True). Accordingly, the lowest score on the scale is 36 and the highest score is 180. In the reliability analysis, the reliability coefficient (Cronbach Alpha value) was found to be 0.92.

3. Course Interest Scale: Student interest; The Course Interest Scale, developed by , in order to evaluate its relationship with variables such as learning motivation, effective learning, and course participation level, is a 5-point Likert-type measurement tool consisting of 16 items and two sub-dimensions (affective and cognitive interest). The study was adapted by Akın et al. (2015). ("1" Strongly Disagree, "2" Disagree, "3" Neutral, "4" Agree, "5" Completely Agree). There are no reverse coded items in the scale. The highest and lowest scores that can be obtained from the scale are 45 and 9, respectively, for the affective interest sub-dimension; 35 and 7 for the cognitive interest sub-dimension. As a result of the analyses, a two-dimensional structure was obtained with factor loadings ranging between .73 and .90. The affective interest sub-dimension of the scale consists of 9 items and the cognitive interest sub-dimension consists of 7 items. Cronbach's alpha internal consistency reliability coefficients of the scale were found to be .95 for the affective interest sub-dimension and .88 for the cognitive interest sub-dimension.

4. Attitude Scale towards Learning: The scale developed by Çetin et al. was developed to determine the attitudes of students. As a result of all validity and reliability analyses, ÖYTÖ contains a total of 34 items. Of these scale items, 25 are positive and 9 are negative. The scale, which is graded in a five-point Likert style, is "Totally Agree", "To a Great extent", "Partly Agree", "I Disagree", "Totally Disagree". The highest attitude score that can be obtained from the scale is 170 and the lowest attitude score is 34. The 9 negative items in the scale are reverse scored. The Cronbach Alpha internal consistency coefficient of the scale was found to be 0.94 for the overall scale.

Path Followed in the Study:

Week 1: Branches were allocated randomly Week 1: Experimental and Control Group Pretest was conducted Week 6: Post-Test was given after the last training

Conditions

Educational Problems

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: PREVENTION
• Blinding Strategy: SINGLE

Study Groups

deepfake group

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

Group Type: EXPERIMENTAL

deepfake video

Intervention Type: 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.

Control group

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

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

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.

Intervention Type: BEHAVIORAL

Eligibility Criteria

Inclusion Criteria

4th year students of Muş Alparslan University, Faculty of Health Sciences, Department of Nursing 18 years and older Volunteer

Exclusion Criteria

Not being a 4th year nursing student, Not volunteering

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Sakarya University

OTHER

Sponsor Role: lead

Responsible Party

Metin Yildiz

Nurse (Asst.Prof.Dr.)

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Sakarya University

Role: STUDY_DIRECTOR

Sakarya University

Locations

Sakarya University

Sakarya, , Turkey (Türkiye)

Countries

Turkey (Türkiye)

Other Identifiers

SakaryaU-metinyildiz-005

Identifier Type: -

Identifier Source: org_study_id