An investigation of the relationship between subjective sleep quality, loneliness and mood in an Australian sample: Can daily routine explain the links?

Background: Loneliness and low mood are associated with significant negative health outcomes including poor sleep, but the strength of the evidence underlying these associations varies. There is strong evidence that poor sleep quality and low mood are linked, but only emerging evidence that loneliness and poor sleep are associated. Aims: To independently replicate the finding that loneliness and poor subjective sleep quality are associated and to extend past research by investigating lifestyle regularity as a possible mediator of relationships, since lifestyle regularity has been linked to loneliness and poor sleep. Methods: Using a cross-sectional design, 97 adults completed standardized measures of loneliness, lifestyle regularity, subjective sleep quality and mood. Results: Loneliness was a significant predictor of sleep quality. Lifestyle regularity was not a predictor of, nor associated with, mood, sleep quality or loneliness. Conclusions: This study provides an important independent replication of the association between poor sleep and loneliness. However, the mechanism underlying this link remains unclear. A theoretically plausible mechanism for this link, lifestyle regularity, does not explain the relationship between loneliness and poor sleep. The nexus between loneliness and poor sleep is unlikely to be broken by altering the social rhythm of patients who present with poor sleep and loneliness

Demographic Factors, Fatigue, and Driving Accidents : an Examination of the Published Literature

This article reviews the literature pertaining to the association between demographic variables (e.g., age, sex, race, socio-economic status) with fatigue, and when feasible, accident risk. It also explores their potential influence and interaction with some working arrangements, commute time, personality characteristics, and circadian chronotype. Fatigue has been implicated in a range of impairments that can have detrimental effects on individuals, and it is differentially associated with conventional demographic variables. However, several major methodological limitations prevent clear conclusions. First, there is absence of a shared definition both within and across disciplines. Second, although fatigue has been investigated using a variety of diverse designs, they have either been too weak to substantiate causality or lacked ecological validity. Third, while both subjective and objective measures have been used as dependent variables, fatigue has been more often found to be more strongly linked with the former. Fourth, with the exception of age and sex, the influence of other demographic variables is unknown, since they have not yet been concomitantly assessed. In instances when they have been assessed and included in statistical analyses, they are considered as covariates or confounders; thus, their contribution to the outcome variable is controlled for, rather than being a planned aspect of investigation. Because the interaction of demographic factors with fatigue is largely a neglected area of study, we recommend greater interdisciplinary collaborations, incorporation of multiple demographic variables as independent factors, and use of within-participant analyses. These recommendations would provide meaningful results that may be used to inform public policy and preventive strategies

In vivo detection of cortical plaques by MR imaging in patients with multiple sclerosis

BACKGROUND AND PURPOSE: In vivo detection of cortical lesions in patients with multiple sclerosis (MS) by MR imaging is hampered by several factors. Among them is the low contrast between small cortical lesions and surrounding cortical gray matter offered by present techniques, METHODS: T1-weighted 3D spoiled gradient-recalled-echo (SPGR) volumes and 2D fluid-attenuated inversion recovery (FLAIR) sequences of 22 patients with MS who had 12 monthly brain MR imaging examinations at 1.5T, using a quadrature head coil, were retrospectively analyzed. These serial studies were coregistered and averaged to generate a single high signal-to-noise ratio (SNR) mean image, which was used to identify cortical lesions. The means of 12 FLAIRs and SPGRs from 14 age- and sex-matched healthy volunteers were analyzed as well. RESULTS: No cortical lesions were found on images of healthy subjects. Eighty-six cortical lesions were identified in 13 (59.1%) patients, predominantly in the frontal lobe (73.3%); 23.3% of cortical lesions lay entirely in the cortex, whereas the remaining lesions invaded the white matter underneath. CONCLUSION: Averaging multiple SPGRs created a single high SNR volume, allowing identification of cortical lesions. Because data were obtained monthly for 1 year, the average image does not account for transient lesion activity. However, for cortical lesions that remained stable during this time, the findings are valid in demonstrating the importance of high SNR images for detecting cortical brain abnormalities in MS