Investigation of the Relationship Between Digital Game Addiction and Musculoskeletal System Disorders

NCT ID: NCT06843772

Last Updated: 2025-09-05

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

40 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-03-01

Study Completion Date

2025-08-10

Brief Summary

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The aim of this study is to examine the effects of digital game addiction on the musculoskeletal system and the reflections of these effects on the quality of life of adults.

Detailed Description

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This study will be conducted with a cross-sectional design in order to examine the relationship between digital game addiction and musculoskeletal disorders. The methods to be used in the research are as follows: Participant Information: The study will include adults aged 18-39 who play digital games in internet cafes for at least 3 hours a day, 4-5 days a week. Participants will be asked to fill out a form to collect demographic information. This form will include information such as age, gender, weekly game playing frequency (by hour and day), and physical activity levels. Scales to be Used: The following measurement tools will be used in the study to evaluate the effects of digital game addiction on the musculoskeletal system. Digital Game Addiction Scale, Arm, Shoulder and Hand Problems Questionnaire, Pittsburgh Sleep Quality, Cornell Musculoskeletal Disorder Questionnaire.

Conditions

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Game Addiction, Video

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

TREATMENT

Blinding Strategy

SINGLE

Outcome Assessors

Study Groups

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control

People who do not have any exercise program

Group Type ACTIVE_COMPARATOR

ergonomic training

Intervention Type OTHER

will receive ergonomic training.

exercise

People who will have an exercise program

Group Type EXPERIMENTAL

ergonomic training

Intervention Type OTHER

will receive ergonomic training.

exercise

Intervention Type OTHER

People who will receive an exercise program. Participants will receive ergonomic training along with the exercise program.

Interventions

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ergonomic training

will receive ergonomic training.

Intervention Type OTHER

exercise

People who will receive an exercise program. Participants will receive ergonomic training along with the exercise program.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Adults aged 18-39.
* Individuals who play digital games at least 4-5 days a week, at least 3 hours a day.
* Individuals who voluntarily participate in the study and sign the ethical consent form.

Exclusion Criteria

* Individuals with existing serious health problems related to the musculoskeletal system or sleep patterns.
* Individuals who suffered trauma or serious injuries related to the musculoskeletal system during the study period.
* Individuals with psychological disorders such as depression or anxiety disorder.
Minimum Eligible Age

18 Years

Maximum Eligible Age

39 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Uskudar University

OTHER

Sponsor Role lead

Responsible Party

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Doç.Dr.Ömer Şevgin

Asst. Prof. Dr.

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Lobaba Chiah

Role: STUDY_CHAIR

Uskudar University

Locations

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Uskudar university

Istanbul, , Turkey (Türkiye)

Site Status

Countries

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Turkey (Türkiye)

References

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Ahmed S, Samuel AJ, Mishra A, Rahman MS, Islam MA, Rashaduzzaman M, Roy SK, Akter R, Islam MJ. Mobile game addiction and its association with musculoskeletal pain among students: A cross-sectional study. PLoS One. 2024 Aug 26;19(8):e0308674. doi: 10.1371/journal.pone.0308674. eCollection 2024.

Reference Type BACKGROUND
PMID: 39186761 (View on PubMed)

Brevers D, King DL, Billieux J. Delineating adaptive esports involvement from maladaptive gaming: a self-regulation perspective. Curr Opin Psychol. 2020 Dec;36:141-146. doi: 10.1016/j.copsyc.2020.07.025. Epub 2020 Aug 3.

Reference Type BACKGROUND
PMID: 32795945 (View on PubMed)

Gulu M, Yagin FH, Gocer I, Yapici H, Ayyildiz E, Clemente FM, Ardigo LP, Zadeh AK, Prieto-Gonzalez P, Nobari H. Exploring obesity, physical activity, and digital game addiction levels among adolescents: A study on machine learning-based prediction of digital game addiction. Front Psychol. 2023 Mar 3;14:1097145. doi: 10.3389/fpsyg.2023.1097145. eCollection 2023.

Reference Type BACKGROUND
PMID: 36936011 (View on PubMed)

Other Identifiers

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Uskudar22

Identifier Type: -

Identifier Source: org_study_id

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