Development and initial validation of DESCAQ: A Rasch-based computer-adaptive questionnaire for assessing digital eye...

Area of Science:

• Ophthalmology
• Digital Health
• Psychometrics

Background:

• Digital eye strain is a prevalent issue among digital device users.
• Existing measurement tools may lack efficiency or ease of use.
• A need exists for a rapid and accurate assessment of digital eye strain.

Purpose of the Study:

• To develop and validate the Digital Eye Strain Computer Adaptive Questionnaire (DESCAQ).
• To create a tool for measuring digital eye strain in individuals aged 8-65.
• To provide a Spanish and English version for broader accessibility.

Main Methods:

• Cross-cultural adaptation of the Spanish DESCAQ to English.
• Online administration to UK and US digital device users.
• Analysis using the partial credit model and Rasch model.
• Test-retest reliability and convergent validity assessment against CVSS17.

Main Results:

• The final English DESCAQ includes 36 items, with a reliability index of 0.95.
• The questionnaire is completed quickly (approx. 120 seconds) using an average of 12 items.
• High test-retest reliability (ICC=0.884) and strong convergent validity (r=0.87) were demonstrated.
• The tool can distinguish up to eight severity levels of digital eye strain.

Conclusions:

• The DESCAQ is a validated, precise, and reliable web-based tool for assessing digital eye strain.
• It offers a quick and easy-to-interpret score for researchers and clinicians.
• The DESCAQ categorizes digital eye strain severity across eight distinct levels.