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Abstract Background Sleep quality is closely linked to mental health, with growing evidence showing that poor or disrupted sleep significantly increases the risk of suicidal ideation. Existing tools, however, assess sleep and suicidality separately, failing to capture the contribution of sleep problems to suicidal ideation. This study aimed to develop and validate the Sleep and Suicidal Ideation Risk Assessment Scale (S-SIRAS) to systematically measure the perceived relationship between sleep quality and suicidal ideation. Methods S-SIRAS was developed through a comprehensive literature review, content validity assessment (CVI), face validity testing, and a pilot study. Psychometric evaluation was conducted among 150 young adults (aged 18–30 years). Analyses included descriptive statistics, internal consistency (Cronbach’s α), split-half reliability (Spearman–Brown coefficient), item–total correlations, two-week test–retest reliability (ICC), and diagnostic accuracy (sensitivity, specificity, predictive values, and area under the ROC curve AUC). Results The S-SIRAS demonstrated acceptable internal consistency (α = 0.748) and good split-half reliability (Spearman–Brown coefficient = 0.793). Item analysis indicated generally satisfactory discrimination, with Items S and T showing excellent item–total correlations (r > 0.80), while Item I showed negligible correlation (r = 0.017). The scale exhibited excellent temporal stability over a two-week period (ICC = 0.981). Diagnostic accuracy analysis showed high specificity (87.7%) but low sensitivity (35.1%) for identifying high suicide risk, with modest discriminatory power (AUC = 0.610) and a strong positive predictive value (75.0%). It assesses two related domains, sleep disturbance and sleep-attributed suicidal reactivity, rather than a single unified construct. Conclusion S-SIRAS demonstrates acceptable psychometric properties, supporting its reliability for assessing sleep-related suicidal ideation in young adults. However, low sensitivity indicates it should not be used as a standalone screening tool. The scale facilitates early identification of sleep-related risk factors, enabling timely interventions in research and clinical settings.
Imran et al. (Thu,) studied this question.