Development and Validation of Artificial Intelligence Addiction Scale for Researchers: A Methodological Study
Ahmed Abdelwahab Ibrahim El-Sayed, Samira Ahmed Alsenany, Maha Gamal Ramadan Asal, Ibrahim Alasqah, Lorena Gutiérrez-Puertas · 2025
Read Development and Validation of Artificial Intelligence Addiction Scale for Researchers: A Methodological Study by Ahmed Abdelwahab Ibrahim El-Sayed, Samira Ahmed Alsenany, Maha Gamal Ramadan Asal, Ibrahim Alasqah, Lorena Gutiérrez-Puertas (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12714078.txt.
Description
El-Sayed, Alsenany, Asal, and Alasqah build and test a scale for AI addiction among researchers in twenty twenty-five. Heavy use of AI tools boosts output but raises fears of over reliance. No validated measure existed for addictive use in research settings. The team drafted items from literature and interviews.
Data came from seven hundred eighteen nursing researchers. The final scale has twenty-two items across five dimensions. Those dimensions cover compulsive use, over dependency, harm to function, withdrawal, and tolerance. Factor analyses confirmed the five part structure, explaining most variance. Reliability scores were excellent across several measures. The authors say the tool can flag unhealthy dependence on AI in academia.
Catalog record
| CREATOR | Ahmed Abdelwahab Ibrahim El-Sayed, Samira Ahmed Alsenany, Maha Gamal Ramadan Asal, Ibrahim Alasqah, Lorena Gutiérrez-Puertas |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 57 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |