Digital Self-Regulation in Attention-Driven Online Environments: A Person-Centered Analysis of Clickbait Engagement


Eren H. İ., Takım U.

International Journal of Human-Computer Interaction, 2026 (SCI-Expanded, SSCI, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1080/10447318.2026.2678533
  • Dergi Adı: International Journal of Human-Computer Interaction
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, ABI/INFORM, Aerospace Database, Applied Science & Technology Source, Compendex, INSPEC, Psycinfo, Academic Search Ultimate (EBSCO), Business Source Ultimate (EBSCO), Engineering Source (EBSCO), Psychology & Behavioral Sciences Collection (EBSCO), Technology Collection (ProQuest)
  • Anahtar Kelimeler: Individual differences, digital self-regulation, person-centered analysis, online engagement, clickbait
  • Sağlık Bilimleri Üniversitesi Adresli: Evet

Özet

Individual differences in digital self-regulation may shape how users respond to attention-capturing features such as clickbait in algorithmically mediated environments. This study adopted a person-centered approach to identify distinct self-regulation profiles and examine whether clickbait engagement predicts profile membership. An international online sample of 610 adults completed the Clickbait Consumption Scale, Pure Procrastination Scale, Regret Scale, and Digital Well-Being Scale. K-means clustering yielded three profiles: Well-Regulated (34.4%), Moderately Dysregulated (42.0%), and Highly Dysregulated (23.6%). Clickbait engagement significantly distinguished the well-regulated group from both dysregulated profiles (OR ≈ 1.08, p < 0.001) but did not differentiate between severity levels, suggesting a threshold-based shift rather than a linear dose-response effect. The highly dysregulated profile showed elevated mental and emotional engagement alongside reduced physical well-being, indicating domain-specific disruption. Younger age independently predicted highly dysregulated profile membership. These findings highlight the value of person-centered frameworks for understanding behavioral heterogeneity in digitally mediated attention environments.