Objective: Insomnia is associated with suicidality, although the mechanisms of this association are unclear. This study sought to replicate previous findings showing that insomnia symptoms but not sleep duration are associated with frequency of suicidal ideation in adults. We further investigated whether depression or sleep duration moderates the association between insomnia symptoms and frequency of suicidal ideation. Materials and Methods: We used the 2005-2006 cycle of the National Health and Nutrition Examination Survey to replicate previously reported findings from the 2007-2008 cycle. We used ordered logistic regression to determine whether insomnia symptoms were associated with frequency of suicidal ideation independently of depression and other potential confounds. To extend these findings, we tested whether depression or sleep duration moderated the association between insomnia symptoms and frequency of suicidal ideation. We further replicated these findings in parallel analyses using the combined data from the 2005-2006 and 2007-2008 cycles. Results: This study replicated previous results showing that insomnia symptoms are associated with frequency of suicidal ideation in the NHANES 2005-2006 cycle (OR = 1.09, p < 0.05), even after adjusting for potentially confounding variables, including depression. Neither depression nor sleep duration moderated this association. Difficulty with sleep maintenance insomnia symptoms were most robustly associated with frequency of suicidal ideation (OR ≥ 1.97, p < 0.05). Sleep duration was not robustly associated with suicidal ideation. Conclusions: In this study, we found that insomnia symptoms were uniquely associated with frequency of suicidal ideation. This association cannot be explained by the shared association with depression or sleep duration.

Study Objectives Insomnia is a risk factor for suicidal behavior including attempts and death by suicide. We investigated whether insomnia symptom severity was associated with suicidality and death by suicide in patients with psychiatric disorders. Methods The sample included 180 deceased patients with psychiatric disorders seen at Weber Human Services between 2008 and 2018 who completed the Outpatient Questionnaire-45.2 (OQ) prior to death. Insomnia symptom severity was assessed using item 41 from the OQ. Manner of death was determined by death records and autopsy reports. History of suicidality was determined through electronic medical records. Cases were grouped into 4 lifetime categories: non-suicidal (n=30), suicidal ideation (n=36), suicide attempt (n=95), and death by suicide (n=19). Demographic, medical, and psychiatric features of each group were compared using linear regression. Logistic regression was used to determine whether insomnia symptom severity was associated with lifetime suicidality severity grouping, adjusting for psychiatric disorders commonly linked to suicidality. Results Lifetime suicidality was associated with sleep problems, fatigue, headaches, and psychiatric disorders (i.e., depressive, personality, and trauma-related disorders). Referenced to the non-suicidal group, greater insomnia symptom severity was significantly associated with suicide attempts and death by suicide, with odds ratios (OR) of OR=2.67, p=0.011, and OR=5.53, p=0.002, respectively, even after adjusting important psychiatric diagnoses. Conclusions Results suggest that insomnia symptom severity endorsed during a clinical visit is associated with heightened suicidality, especially suicidal behavior. The presence of insomnia symptoms in patients with psychiatric disorders may indicate risk for suicide and is a target for suicide prevention.

Sleep valuation, the worth individuals place on sleep, is an understudied construct in the field of sleep medicine. This study introduced a Sleep Valuation Item Bank and explored how sleep valuation is related to sleep health and daytime functioning within a sample of college students. The participants in this study were 247 (85% white, 83% female) undergraduate students who completed an online survey that included questions from a Sleep Valuation Item Bank and questions about sleep and daytime functioning. Correlation and regression analyses were conducted to determine associations between sleep valuation, aspects of sleep health and daytime functioning. Mediation analyses were conducted to determine whether the sleep health variables explained the associations between sleep valuation and daytime functioning. In correlation analyses, sleep valuation was negatively associated with sleepiness and sleep quality. It was also associated with daytime functioning, including general mental and physical health, depression, and anxiety. In the regression analyses, daytime impairments including poorer physical and mental health, anxiety, and depression were associated with higher sleep valuation. Poorer sleep health, including greater sleepiness and lower sleep quality, explained these associations and were associated with higher sleep valuation. Thus, while daytime impairments, such as anxiety and depression, are related to sleep valuation, this relationship may be due in part to the sleep disturbance that often co-occurs with these impairments.

Introduction Sleep valuation is the relative worth individuals place on sleep. Our prior study using a Sleep Valuation Item Bank (SVIB) showed that sleep valuation relates to age, gender, and health status. In this study, the psychometric properties of the SVIB and its latent factor structure were explored. We also investigated how sleep valuation factors relate to demographic, psychological, and sleep features. Methods Participants (N = 854) were recruited through TurkPRIME and completed a survey consisting of demographic, psychological, and sleep-related questions. The distributional properties of the SVIB items were quantified. Cronbach’s alpha and correlation analyses were used to assess the internal consistency and test-retest reliability of SVIB items. Iterated principal factoring with a Promax rotation was used on the SVIB to explore its latent factor structure. Multiple regression analyses were used to investigate the variables associated with each factor. Results The factor analysis identified 29 items with factor loadings ≥0.4 on four major factors, tentatively called (1) sleep wanting, (2) sleep prioritizing, (3) sleep onset preference, and (4) sleep devaluation. While women had higher sleep wanting and lower sleep devaluation scores than men, they had lower sleep prioritizing. Older individuals tended to value sleep less but also devalued it less than younger participants. Finally, although both individuals with insomnia and depression devalued sleep, depressed individuals prioritized it more than those who were less depressed, while individuals with insomnia symptoms wanted sleep and preferred sleep onset more than those with less insomnia symptoms. Discussion The current SVIB captures broad dimensions of sleep valuation (wanting, prioritizing, preferring) and sleep devaluation. These broad dimensions had distinct patterns across person-level factors. Recognition of individual differences in sleep valuation may help target sleep health advocacy efforts and individualized treatment approaches, including for those with depression or insomnia.

Introduction Sleep valuation, the relative worth of one’s own sleep, is an under-explored construct that could have implications on sleep health. This study sought to validate the Sleep Valuation Questionnaire (SVQ) and to explore demographic differences in sleep valuation. Methods Participants (N = 946) recruited through TurkPrime were stratified across age (18-99), race (50% White, 17% Black, and 8.33% for each American Indian, Asian, Pacific Islander, and other), Hispanic ethnicity (20%), gender (50/50 female/male), employment status (50% employed full time and 8.33% for each part time, homemaker, retired, student, temp worker. unemployed, and disabled), Participants completed a demographic survey, followed by the original 43 item SVQ completed twice. Iterated principal factoring with a Promax solution was used to identify the factor structure of the SVQ. Cronbach’s alpha and correlation analyses were also used to help identify items with poor reliability. Total sleep valuation, the sum of valid items on the SVQ, was used as the dependent variable in a multiple regression analysis. Age, gender, race, work status, socioeconomic status, educational level, marital status, and general health and mental health estimates served as independent variables. Results After removing items with weak factor loadings (&lt;0.6), poor reliability, and weak face validity, the number of items were reduced to 10, which loaded on to 2 factors: Sleep Desire and Sleep Need. Those who cohabitate had lower SVQ scores than married individuals (p=0.04), full-time workers had higher SVQ scores than non-full-time workers (p=0.001), higher age was associated with lower SVQ scores (p&lt;0.001), and higher general mental health was associated with lower SVQ scores (p&lt;0.001). Conclusion This is the first study to explore how demographic variables relate to sleep valuation. The SVQ may help identify factors that contribute to sleep valuation and sleep valuation relates to sleep behavior, sleep health, and sleep treatment utilization. Support None