악몽장애 선별을 위한 반구조화된 임상면담도구 개발 및 타당화
Development and Validation of a Semi-Structured Clinical Interview for Nightmare Disorder
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Objectives: Nightmare disorder is highly prevalent in clinical settings and is highly comorbid with posttraumatic stress disorder (PTSD). In the current study, we aimed to develop and validate a semi-structured interview based on the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders-fifth edition for diagnosing nightmare disorder. Methods: We developed a Semi-Structured Clinical Interview for Nightmare Disorder (SCIN) in five steps: we interviewed 100 females (mean age, 24.6±5.88 years) using the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5); Structured Clinical Interview for DSM-IV Axis 1 Disorders, Research Version (SCID-I); and self-report questionnaires for nightmares (Disturbing Dream and Nightmare Severity Index, DDNSI), depression, state anxiety, trait anxiety, suicidal ideation, and insomnia. Two independent raters assessed the responses of the interviewees. The interrater reliability for the SCIN was calculated. Pearson’s correlation coefficient was used to assess convergent validity between SCIN and the DDNSI. Chi-square analyses were conducted to compare prevalence of PTSD based on nightmare disorder diagnosis. Results: Among the participants, 42% were diagnosed with nightmare disorder, 15% had subthreshold nightmare disorder, and 43% did not have nightmare disorder. Interrater reliability was moderate (Kappa=0.707, p<0.001). The semi-structured clinical interview showed good convergent validity with the DDNSI (r=0.639, p<0.001). Additionally, individuals who were identified as having nightmare disorder had higher levels of depression, state anxiety, trait anxiety, suicidal ideation, and insomnia (p<0.001). Based on the PTSD diagnosis using CAPS-5, the nightmare group had a higher proportion of PTSD diagnoses than the no-nightmare group (26.2% vs. 8.6%, respectively; χ2=38.41, p<0.001). Conclusions: The semi-structured clinical interview for nightmare disorder appears to have good reliability and validity and can be used in clinical settings.
Abstract
Objectives: Nightmare disorder is highly prevalent in clinical settings and is highly comorbid with posttraumatic stress disorder (PTSD). In the current study, we aimed to develop and validate a semi-structured interview based on the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders-fifth edition for diagnosing nightmare disorder. Methods: We developed a Semi-Structured Clinical Interview for Nightmare Disorder (SCIN) in five steps: we interviewed 100 females (mean age, 24.6±5.88 years) using the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5); Structured Clinical Interview for DSM-IV Axis 1 Disorders, Research Version (SCID-I); and self-report questionnaires for nightmares (Disturbing Dream and Nightmare Severity Index, DDNSI), depression, state anxiety, trait anxiety, suicidal ideation, and insomnia. Two independent raters assessed the responses of the interviewees. The interrater reliability for the SCIN was calculated. Pearson’s correlation coefficient was used to assess convergent validity between SCIN and the DDNSI. Chi-square analyses were conducted to compare prevalence of PTSD based on nightmare disorder diagnosis. Results: Among the participants, 42% were diagnosed with nightmare disorder, 15% had subthreshold nightmare disorder, and 43% did not have nightmare disorder. Interrater reliability was moderate (Kappa=0.707, p<0.001). The semi-structured clinical interview showed good convergent validity with the DDNSI (r=0.639, p<0.001). Additionally, individuals who were identified as having nightmare disorder had higher levels of depression, state anxiety, trait anxiety, suicidal ideation, and insomnia (p<0.001). Based on the PTSD diagnosis using CAPS-5, the nightmare group had a higher proportion of PTSD diagnoses than the no-nightmare group (26.2% vs. 8.6%, respectively; χ2=38.41, p<0.001). Conclusions: The semi-structured clinical interview for nightmare disorder appears to have good reliability and validity and can be used in clinical settings.
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