A Narrative Review of the Effects of Mindfulness on Sleep and Hypertension.

PURPOSE OF REVIEW: The prevalence of both insomnia and hypertension in the general population is vast and the health implications to individuals and society are costly. The current pharmacological treatment options for insomnia and hypertension are limited and patients are becoming increasingly interested in non-pharmacological treatment options. Mindfulness, a disciplined mental training practice rooted in Eastern traditions, has become a widely popular treatment method for multiple chronic health problems. The aim of this paper was to review research on mindfulness-based intervention effects on sleep, insomnia, and hypertension from the past 3 years. Theoretical foundations of mindfulness are discussed. Empirical evidence and potential mechanisms of how mindfulness impacts sleep and hypertension are provided. RECENT FINDINGS: Our findings suggest that mindfulness-based interventions are safe and effective for people with insomnia and hypertension. We saw consistent, albeit small to moderate, effects of mindfulness-based interventions on reducing insomnia symptoms, improving sleep quality, and lowering systolic and diastolic blood pressure readings. While mindfulness interventions have shown to be effective for improving sleep and lowering hypertension, future research is needed to further evaluate their efficacy on larger samples of patient populations with long-term follow-up measures. These high-quality studies could help researchers and clinicians identify treatment response tendencies in patient populations which can lead to better tailoring of mindfulness-based interventions for specific health concerns.

Social Support Networks Among Black Caregivers of Persons With Memory Problems.

Positive social support can predict health outcomes in populations that experience significant burdens, such as minority caregivers. The purpose of the current study was to detail the social network (SN) of 36 Black family caregivers (FCGs) for persons with memory problems (PWMP) and examine differences in SN support depending on FCG gender and relationship to the care recipient. Participants were recruited from the Alzheimer's family program at the University of Alabama at Birmingham and the local community. FCGs were categorized into adult children (ACH), grandchildren and in-law children, and friends and other relatives. FCGs described the amount of adequate support they receive for different types of support from their SN. Female FCGs reported higher levels of support overall, with the largest effect sizes including social (d = 0.63), emotional (d = 0.64), and financial (d = 0.38) support. The largest effect size comparison of caregiver relationship type was in social support, with the ACH group reporting the lowest levels of adequate social support compared to the other two groups (d = 0.48). Findings suggest that different types of Black FCGs face unique challenges depending on their gender and familial relationship to the care recipient. [Journal of Gerontological Nursing, 50(1), 22-29.].

Quantitative assessment of structural image quality.

Data quality is increasingly recognized as one of the most important confounding factors in brain imaging research. It is particularly important for studies of brain development, where age is systematically related to in-scanner motion and data quality. Prior work has demonstrated that in-scanner head motion biases estimates of structural neuroimaging measures. However, objective measures of data quality are not available for most structural brain images. Here we sought to identify quantitative measures of data quality for T1-weighted volumes, describe how these measures relate to cortical thickness, and delineate how this in turn may bias inference regarding associations with age in youth. Three highly-trained raters provided manual ratings of 1840 raw T1-weighted volumes. These images included a training set of 1065 images from Philadelphia Neurodevelopmental Cohort (PNC), a test set of 533 images from the PNC, as well as an external test set of 242 adults acquired on a different scanner. Manual ratings were compared to automated quality measures provided by the Preprocessed Connectomes Project's Quality Assurance Protocol (QAP), as well as FreeSurfer's Euler number, which summarizes the topological complexity of the reconstructed cortical surface. Results revealed that the Euler number was consistently correlated with manual ratings across samples. Furthermore, the Euler number could be used to identify images scored "unusable" by human raters with a high degree of accuracy (AUC: 0.98-0.99), and out-performed proxy measures from functional timeseries acquired in the same scanning session. The Euler number also was significantly related to cortical thickness in a regionally heterogeneous pattern that was consistent across datasets and replicated prior results. Finally, data quality both inflated and obscured associations with age during adolescence. Taken together, these results indicate that reliable measures of data quality can be automatically derived from T1-weighted volumes, and that failing to control for data quality can systematically bias the results of studies of brain maturation.

Stroke Severity, Caregiver Feedback, and Cognition in the REGARDS-CARES Study.

Objective: Cognitive impairment after stroke is common, present up to 60% of survivors. Stroke severity, indicated by both volume and location, is the most consequential predictor of cognitive impairment, with severe strokes predicting higher chances of cognitive impairment. The current investigation examines the associations of two stroke severity ratings and a caregiver-report of post-stroke functioning with longitudinal cognitive outcomes. Methods: The analysis was conducted on 157 caregivers and stroke survivor dyads who participated in the Caring for Adults Recovering from the Effects of Stroke (CARES) project, an ancillary study of the REasons for Geographic and Racial Differences in Stroke (REGARDS) national cohort study. Glasgow Outcome Scale (GOS) and modified Rankin Scale (mRS) collected at hospitalization discharge were included as two primary predictors of cognitive impairment. The number of caregiver-reported problems and impairments at nine months following stroke were included as a third predictor. Cognition was assessed using a biennial telephone battery, incorporating multiple cognitive assessments to assess learning, memory, and executive functioning. Longitudinal cognitive scores were analyzed up to five years post-stroke, controlling for baseline (pre-stroke) cognitive scores and demographic variables of each stroke survivor collected at CARES baseline. Results: Separate mixed models showed significant main effects of GOS (b=0.3280, p=0.0009), mRS (b=-0.2119, p=0.0002), and caregiver-reported impairments (b=-0.0671, p<0.0001) on longitudinal cognitive scores. In a combined model including all three predictors, only caregiver-reported problems significantly predicted cognitive outcomes (b=-0.0480, p<0.0001). Impact: These findings underscore the importance of incorporating caregivers feedback in understanding cognitive consequences of stroke.