Research interest concerning associations between sleep characteristics and suicidality in psychopathology has been growing. However, possible linkages of suicidality to sleep characteristics in terms of sleep quality and chronotypes among depressive patients have not been well documented. In the current study, the authors investigated the possible effects of sleep quality and chronotype on the severity of depressive symptoms and suicide risk in patients with depressive disorder and healthy controls. The study was conducted on 80 patients clinically diagnosed with major depression and 80 healthy subjects who were demographically matched with the patient group. All participants completed a questionnaire package containing self-report measures, including the Beck Depression Inventory (BDI), Pittsburgh Sleep Quality Index (PSQI), Morningness-Eveningness Questionnaire (MEQ), and Suicide Ideation Scale (SIS), and subjects were interviewed with the suicidality section of the Mini-International Neuropsychiatric Interview (MINI). Results are as follows: (a) logistic regression analyses revealed that poor sleep quality and depression symptom severity significantly predicted onset of major depression; (b) morningness-type circadian rhythm may play as a significant relief factor after onset of major depression; (c) sleep variables of chronotype and sleep quality did not significantly predict suicide ideation after controlling for depressive symptoms in the major depression group; and (d) suicide ideation and poor sleep quality were antecedents of depression symptom severity in patients with major depression, and in healthy controls. Findings are discussed under the theoretical assumptions concerning possible relations between chronotype, sleep quality, depression, and suicidality.

Objective: Even though the internet is a valuable resource for medical information, it has the potential to increase anxiety, fear or obsessive-compulsive behaviours, particularly among individuals more prone to health related anxiety. Researchers have found that health anxiety, hypochondria, and online health searches are associated with increased anxious symptomatology. The aim of this study is to investigate the psychometric properties of the Turkish version of the Cyberchondria Severity Scale, a measure of online health anxiety. Method: Three hundred thirty-seven university students with an age range of 16-55 were included in the study. The Cyberchondria Severity Scale (CSS), Internet Addiction Test (IAT), Anxiety Sensitivity Inventory-3 (ASI-3), and Health Anxiety Inventory (HAI) were administered to participants. Results: Confirmatory factor analysis revealed that five-factor solution best fit to the data. The overall and subscales of the CSS had excellent internal consistency (Cronbach α = 0.91, for the overall measure, and Cronbach α values ranged from 0.78 to 0.87), with an exception of 'mistruct of medical professional' subscale (Cronbach α = 0.64). The total and subscales of the CSS had generally good convergent validity. Conclusion: The CSS is a newly developed screening tool to assess online health anxiety, and present study demonstrated that the Turkish version of the scale had promising psychometric properties.

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