Abstract
Objectives
Hikikomori, a severe and prolonged form of social withdrawal, is attracting growing global interest, and well-validated tools to support the clinical assessment of hikikomori are needed. This study aimed to examine the Italian version of the Hikikomori Questionnaire–25 (HQ-25) and the ERRESSEGI questionnaire to differentiate between adolescents with and without hikikomori providing evidence on their optimal cut-offs and filling in the gap in existing literature.
Methods
Adolescents attending Italian secondary schools and adolescents referred to neuropsychiatric centers from the Public National Health Service participated in this study. Data from 381 participants aged between 13 and 18 years were used for the present analysis: non-clinical sample n = 274, clinical sample without hikikomori n = 70, and clinical sample with hikikomori n = 37. The metric of maximizing the sum of sensitivity and specificity was used to determine the optimal cutoff scores, with bootstrapping procedures to examine the variability of the estimates. The diagnosis of hikikomori, based on research criteria previously proposed, was used as a criterion or gold standard measurement.
Results
An HQ-25 cut-off score ≥ 52 correctly identified 73% of hikikomori cases and 88% of non-hikikomori cases, while an ERRESSEGI cut-off score ≥ 30 correctly identified 81% of hikikomori cases and 87% of non-cases. Satisfactory classification accuracy was also found (area under the curve [AUC] value of 0.86 for the HQ-25 and. 90 for the ERRESSEGI). The receiver-operating characteristic curve comparison demonstrated no significant difference in AUC values. Bootstrap analysis showed good stability of classification accuracy estimates.
Conclusions
Both the HQ-25 and ERRESSEGI demonstrate criterion validity among adolescents and may be useful in the assessment of hikikomori.
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright
Copyright (c) 2023 Journal of Psychopathology
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