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Journals / Kırşehir Ahi Evran Üniversitesi Sağlık Bilimleri Dergisi / 2026 / Cilt: 10 Sayı: 1

THE RELATIONSHIP BETWEEN AI-BASED POSTURE ANALYSIS AND TECHNOLOGY ADDICTION IN UNIVERSITY STUDENTS

ÜNİVERSİTE ÖĞRENCİLERİNDE YAPAY ZEKÂ DESTEKLİ POSTÜR ANALİZİ VE TEKNOLOJİ BAĞIMLILIĞI İLE İLİŞKİSİ

Ceren Keleş0009-0002-4574-0996
Secem Nur Arslan0009-0008-8898-7706
Emine Gökçe Turak0009-0007-7791-0132
Mehtap Kondak(AVRASYA ÜNİVERSİTESİ)0000-0001-9736-0640
Pages
81–103
Publication Date
2026-04-17
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The findings are important in terms of identifying early postural changes potentially linked to technology use in young individuals and for informing the development of preventive educational programs.

📌 3 Key Takeaways

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Objective & Hypothesis:This study aimed to examine the relationship between artificial intelligence-assisted posture analysis, technology addiction, and screen time among university students studying in the field of health sciences.
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Key Findings & Data:The study included 100 voluntary students who met the inclusion criteria.
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Conclusion & Impact:The findings are important in terms of identifying early postural changes potentially linked to technology use in young individuals and for informing the development of preventive educational programs.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:omurga · öğrenciler · postür

Abstract

This study aimed to examine the relationship between artificial intelligence-assisted posture analysis, technology addiction, and screen time among university students studying in the field of health sciences. The study included 100 voluntary students who met the inclusion criteria. The data was collected by Technology Addiction Scale, and screen time was determined based on the average screen time data retrieved from smartphones. Postural analysis was conducted using the artificial intelligence-based APECS: AI Posture Evaluation application. There was no statistically significant relationship between screen time and postural parameters (p>0.05). However analysis by gender revealed that male students had significantly higher technology addiction scores compared to female students (p=0.038). Additionally a significant and positive correlation was found between the technology addiction score and the postural parameter evaluating ankle rotation (p=0.001). This study demonstrates the applicability of artificial intelligence-based posture analysis methods among university students. The method provided more objective, rapid, and reproducible results compared to traditional observational approaches. The findings are important in terms of identifying early postural changes potentially linked to technology use in young individuals and for informing the development of preventive educational programs.

Özet

Bu çalışmada, sağlık bilimleri alanında öğrenim gören üniversite öğrencilerinde yapay zekâ destekli postür analizleri ile teknoloji bağımlılığı ve ekran süresi arasındaki ilişkinin incelenmesi amaçlanmıştır. Çalışmaya, belirlenen kriterlere uygun 100 gönüllü öğrenci dahil edilmiştir. Veriler, Teknoloji Bağımlılık Ölçeği, akıllı telefonlardan alınan ortalama ekran süresi verisiyle toplanmıştır. Postür analizi, yapay zekâ tabanlı APECS: AI Posture Evaluation uygulaması kullanılarak gerçekleştirilmiştir. Ekran süresi ile postür parametreleri arasında istatistiksel olarak anlamlı bir ilişki saptanmamıştır (p>0.05). Buna karşın cinsiyet değişkenine göre yapılan analizde, erkek öğrencilerin teknoloji bağımlılığı puanlarının kadın öğrencilere kıyasla istatistiksel olarak anlamlı düzeyde daha yüksek olduğu bulunmuştur (p=0.038). Ayrıca, teknoloji bağımlılığı puanı ile ayak bileği rotasyonunu değerlendiren postür parametresi arasında anlamlı ve pozitif yönlü bir ilişki belirlenmiştir (p=0.001). Çalışma yapay zekâ tabanlı postür analiz yöntemlerinin üniversite öğrencilerinde uygulanabilirliğini ortaya koymaktadır. Kullanılan bu yöntem, geleneksel gözlemsel analizlere göre daha objektif, hızlı ve tekrarlanabilir sonuçlar sunmuştur. Elde edilen sonuçlar, genç bireylerde teknoloji kullanımına bağlı oluşabilecek postüral değişikliklerin erken dönemde belirlenmesi ve önleyici eğitim programlarının geliştirilmesi açısından önem arz etmektedir.

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Cite This Article

Keleş, C., Arslan, S. N., Turak, E. G., Kondak, M. (2026). THE RELATIONSHIP BETWEEN AI-BASED POSTURE ANALYSIS AND TECHNOLOGY ADDICTION IN UNIVERSITY STUDENTS. Kırşehir Ahi Evran Üniversitesi Sağlık Bilimleri Dergisi, Cilt: 10 Sayı: 1, 81–103. https://ajindex.com/articles/1520390

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