AI Summary of Peer-Reviewed Research

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Indonesian Doomscrolling Scale shows one-factor structure

A person with dark skin tone wearing a smartwatch and bracelets holds a smartphone displaying a keyboard interface in both hands against a blurred background.
Research area:Social SciencesSociology and Political ScienceScale (ratio)

What the study found

The Indonesian version of the Doomscrolling Scale showed a 15-item, unidimensional structure and high internal consistency. The authors report that it has acceptable foundational reliability and structure for future use.

Why the authors say this matters

The authors say this matters because no validated instrument was previously available to assess doomscrolling in Indonesia. They suggest the scale may be useful for future research and digital literacy initiatives.

What the researchers tested

The researchers examined the structural validity and internal reliability of the Indonesian version of the Doomscrolling Scale. They surveyed 502 social media users aged 18–40 years in 2025 using an online questionnaire distributed via Google Forms and analyzed the data with confirmatory factor analysis in JASP.

What worked and what didn't

The analysis supported a single-factor, 15-item scale. Internal consistency was excellent, with Cronbach’s alpha reported as 0.939.

What to keep in mind

The abstract does not describe additional limitations beyond the sample and the fact that this is a foundational validation study. The findings are limited to the participants and methods described in the abstract.

Key points

  • The Indonesian Doomscrolling Scale was supported as a 15-item unidimensional measure.
  • Internal consistency was reported as excellent (Cronbach’s alpha = 0.939).
  • The study surveyed 502 social media users aged 18–40 years in 2025.
  • The data were analyzed with confirmatory factor analysis using JASP.
  • The authors say the scale may support future research and digital literacy initiatives.

Disclosure

Research title:
Indonesian Doomscrolling Scale shows one-factor structure
Authors:
Indri Oktavia Rospita, Lusy Asa Akhrani, Cleoputri Al Yusainy
Institutions:
University of Brawijaya
Publication date:
2026-04-06
OpenAlex record:
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AI provenance: This post was generated by OpenAI. The original authors did not write or review this post.