Objective Subjective reports of patients with insomnia often show a discrepancy with their objective assessments of sleep. We aimed to assess subjective-objective sleep discrepancy in subjects with insomnia disorder as well as the psychological factors associated with the discrepancy. Methods This study is a secondary analysis of the baseline data of a randomized controlled study on 110 adults aged 18 years to 59 years with insomnia disorder. Subjective reports on sleep and the objective measures acquired by an overnight polysomnography were used to measure the sleep discrepancy. Smartphone Addiction Proneness Scale (SAPS), Center for Epidemiologic Studies Depression Scale (CES-D), beck anxiety inventory (BAI), and Global Assessment of Recent Stress (GARS) were used to evaluate the psychological factors associated with the sleep discrepancy. Results Mean total sleep time (TST) discrepancy of the participants was -81.65±97.41 minutes. Multivariable logistic regression analyses revealed that age (adjusted OR=1.07, 95% CI=1.01-1.13, p=0.027), years of education (adjusted OR=0.69, 95% CI=0.48-0.91, p=0.017), and smartphone addiction proneness (adjusted OR=1.14, 95% CI=1.04-1.27, p=0.008) were independent predictors of TST misperception. Mean sleep onset latency (SOL) discrepancy of the participants was 41.28±45.01 minutes. Only anxiety was an independent predictor of SOL misperception (adjusted OR=1.16, 95% CI=1.05-1.31, p=0.006). Conclusion The present study provides empirical evidence to increase our understanding of the various factors that are associated with subjective-objective sleep discrepancy. Screening insomnia patients with smartphone addiction proneness may help predict the potential discrepancy between the patients’ subjective reports and objective measures of sleep duration.
Objective Subjective reports of patients with insomnia often show a discrepancy with their objective assessments of sleep. We aimed to assess subjective-objective sleep discrepancy in subjects with insomnia disorder as well as the psychological factors associated with the discrepancy. Methods This study is a secondary analysis of the baseline data of a randomized controlled study on 110 adults aged 18 years to 59 years with insomnia disorder. Subjective reports on sleep and the objective measures acquired by an overnight polysomnography were used to measure the sleep discrepancy. Smartphone Addiction Proneness Scale (SAPS), Center for Epidemiologic Studies Depression Scale (CES-D), beck anxiety inventory (BAI), and Global Assessment of Recent Stress (GARS) were used to evaluate the psychological factors associated with the sleep discrepancy. Results Mean total sleep time (TST) discrepancy of the participants was -81.65±97.41 minutes. Multivariable logistic regression analyses revealed that age (adjusted OR=1.07, 95% CI=1.01-1.13, p=0.027), years of education (adjusted OR=0.69, 95% CI=0.48-0.91, p=0.017), and smartphone addiction proneness (adjusted OR=1.14, 95% CI=1.04-1.27, p=0.008) were independent predictors of TST misperception. Mean sleep onset latency (SOL) discrepancy of the participants was 41.28±45.01 minutes. Only anxiety was an independent predictor of SOL misperception (adjusted OR=1.16, 95% CI=1.05-1.31, p=0.006). Conclusion The present study provides empirical evidence to increase our understanding of the various factors that are associated with subjective-objective sleep discrepancy. Screening insomnia patients with smartphone addiction proneness may help predict the potential discrepancy between the patients’ subjective reports and objective measures of sleep duration.
INTRODUCTION METHODS RESULTS DISCUSSION
