Diagnostic Performance and Subcategorization of Hikikomori Cases in Oman: A Cross-Sectional Study and Comparative...

Hikikomori, a severe form of social withdrawal, has been predominantly studied in East Asia but remains underexplored in Middle Eastern contexts. As societal and cultural factors influence its manifestation, developing reliable diagnostic tools is critical for accurate identification and intervention. The Hikikomori Questionnaire-25 (HQ-25) serves as a self-reported screening measure, while the Hikikomori Diagnostic Evaluation Interview (HiDE-I) is used for clinical confirmation.

This study aims to assess the diagnostic classification and predictive performance of the HQ-25 compared to the HiDE-I in an Omani sample, with a specific focus on refining cutoff thresholds for better classification accuracy.

A cross-sectional study was conducted in Oman in 2024, enrolling 454 participants from clinical and community settings. Participants were classified as either patients (psychiatric service users) or attendees (nonclinical individuals). The HQ-25 was administered at four cutoff thresholds (≥ 42, ≥ 50, ≥ 62, ≥ 75). The HiDE-I was used as the clinical criterion standard, classifying cases as pathological, at-risk, or resembling hikikomori. Diagnostic metrics-including sensitivity, specificity, predictive values, and receiver operating characteristic (ROC) curves-were calculated.

Table-based analyses demonstrated that at the ≥ 42 cutoff, the HQ-25 yielded 62.9% sensitivity and 57.6% specificity under the strict HiDE-I definition, and 80.0% sensitivity with 53.4% specificity under the confirmed HiDE-I definition. ROC analyses across all thresholds showed area under the curve (AUC) values ranging from 0.58 to 0.66 (strict HiDE-I) and 0.55 to 0.85 (confirmed HiDE-I), with the highest classification accuracy observed among psychiatric patients.

The HQ-25 is a useful screening tool but insufficient on its own for diagnosing hikikomori. Incorporating both diagnostic tiers revealed its limitations and reinforced the need for structured clinical assessments to improve accuracy, especially in nonclinical settings.