LONELINESS, CYNICAL HOSTILITY, AND COGNITIVE DECLINE IN AMERICANS ABOVE AGE 50

Background. Research identifies isolation (being alone) as a risk factor for cognitive decline— yet it is possible that subjective dimensions of isolation are more critical. Potential risk factors are loneliness (the distress stemming from feeling alone) and cynical hostility (an attitude of distrust and cynicism). The present study examined the relationship between these factors and cognitive functioning and decline. Methods. Data came from the Health and Retirement Study, a nationally representative longitudinal study of US adults over 50. Loneliness was measured using the Hughes Loneliness Scale; cynical hostility was measured using items from the Cook-Medley Hostility Inventory. Cognitive functioning was indexed by the Telephone Interview for Cognitive Status. Regressions were conducted to examine loneliness and cynical hostility as predictors of cognitive function at baseline as well as cognitive decline over four and six-year periods. Models were adjusted for demographic characteristics, health behaviors, and isolation. Results. Loneliness, [f2=.003, t(52)=-3.75; p\u3c.001] and cynical hostility, [f2=.002, t(52)=-2.98, p=.004] predicted cognitive function at baseline. Loneliness and cynical hostility each predicted cognitive decline over four [f2=.001, t(52)=-2.29; p=.026 f2=.003, t(52)=-3.98; p\u3c.001 respectively] but not six years [t(52)= -.78; p=.439; t(52)= -1.29; p=.203 respectively]. Discussion. Loneliness and cynical hostility are correlates of lower cognitive function and risk factors for cognitive decline over four years. The absence of significant effects of loneliness and cynical hostility over six years could be attributed to low statistical power in these analyses. The effect sizes in this study are small, yet meaningful in the context of the personal and social costs associated with cognitive decline

LONELINESS AND SLEEP DISTURBANCE IN OLDER AMERICANS

Loneliness is a risk factor for premature mortality but the mechanics of this relationship remain obscure. A potential mechanism is sleep disturbance. The present study aimed to examine the association between loneliness and sleep disturbance, evaluate loneliness as a risk factor for sleep disturbance and vice-versa, model effects between loneliness and sleep disturbance over time, and evaluate a mediation model of loneliness, sleep disturbance, and health. Data came from the 2006-2012 waves of the Health and Retirement Study, a nationally-representative study of older Americans; participants \u3e 65 were included (n=11,400). Analyses included (i) linear regressions accounting for complex sampling and (ii) path analysis (cross-lagged panel and mediation models). Loneliness and sleep disturbance were correlated and were risk factors for one another. Cross-lagged panel models showed reciprocal effects between loneliness and sleep disturbance. Cross-lagged mediation models showed that loneliness predicted subsequent sleep disturbance, which in turn predicted poor self-reported health. Moreover, there was evidence of a direct and indirect effect of loneliness on sleep disturbance. All associations were weakened— but remained—when accounting for demographics, isolation, and depression. Collectively, these findings are consistent with the theory that sleep disturbance is a mechanism through which loneliness damages health. However, effects between loneliness and sleep are reciprocal, rather than unidirectional. Moreover, longitudinal effects were very small. Further research is necessary to speak to causality, assess daily associations between loneliness and sleep, assess a comprehensive model of the mechanics of loneliness and health, and examine loneliness and sleep in the context of other factors

Influence of Visual Attention on the Likelihood of Choice Through Regression Analysis

Eye tracking technology allows for a relatively direct and continuous measurement of unconcealed visual attention. In the consumer goods market today, it is important for companies to make their brand or product stand out within a vast competitive array. Even though it is highly unlikely that a product would be purchased without having been noticed (unseen is unsold), it is important to investigate if products that garner high attention are in fact purchased in the marketplace, and if a correlation between the two metrics exists. Through the utilization of real consumers in an immersive consumer retail experience laboratory, an eye tracking study on seasoned breading mix was conducted to test the correlation between attention and sales data. Data captured from 37 study participants were used to create a regression model by utilizing the Fit Y by X function in the statistical program JMP Pro 12. Statistical analysis indicated that including attention metrics in the prediction model significantly improves the ability to predict average sales. Demographics such as gender, age, relationship status, education, employment, shopping habits were also investigated in order to understand the trends of individual participants to find ideal consumers. Overall, eye tracking is a viable option to foreshadow sales and attention performance within this category

Acknowledgement Entity Recognition in CORD-19 Papers

Acknowledgements are ubiquitous in scholarly papers. Existing acknowledgement entity recognition methods assume all named entities are acknowledged. Here, we examine the nuances between acknowledged and named entities by analyzing sentence structure. We develop an acknowledgement extraction system, AckExtract based on open-source text mining software and evaluate our method using manually labeled data. AckExtract uses the PDF of a scholarly paper as input and outputs acknowledgement entities. Results show an overall performance of F1=0.92. We built a supplementary database by linking CORD-19 papers with acknowledgement entities extracted by AckExtract including persons and organizations and find that only up to 50–60% of named entities are actually acknowledged. We further analyze chronological trends of acknowledgement entities in CORD-19 papers. All codes and labeled data are publicly available at https://github.com/lamps-lab/ackextract

Loneliness and sleep: A systematic review and meta-analysis

Despite the mounting evidence linking loneliness with health, the mechanisms underlying this relationship remain obscure. This systematic review and meta-analysis on the association between loneliness and one potential mechanism—sleep—identified 27 relevant articles. Loneliness correlated with self-reported sleep disturbance (r = .28, 95% confidence interval (.24, .33)) but not duration, across a diverse set of samples and measures. There was no evidence supporting age or gender as moderators or suggesting publication bias. The longitudinal relationship between loneliness and sleep remains unclear. Loneliness is related to sleep disturbance, but research is necessary to determine directionality, examine the influence of other factors, and speak to causality

Using process evaluation for program improvement in dose, fidelity and reach: the ACT trial experience

<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to demonstrate how formative program process evaluation was used to improve dose and fidelity of implementation, as well as reach of the intervention into the target population, in the "Active by Choice Today" (ACT) randomized school-based trial from years 1 to 3 of implementation.</p> <p>Methods</p> <p>The intervention integrated constructs from Self-Determination Theory and Social Cognitive Theory to enhance intrinsic motivation and behavioral skills for increasing long-term physical activity (PA) behavior in underserved adolescents (low income, minorities). ACT formative process data were examined at the end of each year to provide timely, corrective feedback to keep the intervention "on track".</p> <p>Results</p> <p>Between years 1 and 2 and years 2 and 3, three significant changes were made to attempt to increase dose and fidelity rates in the program delivery and participant attendance (reach). These changes included expanding the staff training, reformatting the intervention manual, and developing a tracking system for contacting parents of students who were not attending the after-school programs regularly. Process outcomes suggest that these efforts resulted in notable improvements in attendance, dose, and fidelity of intervention implementation from years 1 to 2 and 2 to 3 of the ACT trial.</p> <p>Conclusion</p> <p>Process evaluation methods, particularly implementation monitoring, are useful tools to ensure fidelity in intervention trials and for identifying key best practices for intervention delivery.</p

EM-mosaic detects mosaic point mutations that contribute to congenital heart disease.

BackgroundThe contribution of somatic mosaicism, or genetic mutations arising after oocyte fertilization, to congenital heart disease (CHD) is not well understood. Further, the relationship between mosaicism in blood and cardiovascular tissue has not been determined.MethodsWe developed a new computational method, EM-mosaic (Expectation-Maximization-based detection of mosaicism), to analyze mosaicism in exome sequences derived primarily from blood DNA of 2530 CHD proband-parent trios. To optimize this method, we measured mosaic detection power as a function of sequencing depth. In parallel, we analyzed our cohort using MosaicHunter, a Bayesian genotyping algorithm-based mosaic detection tool, and compared the two methods. The accuracy of these mosaic variant detection algorithms was assessed using an independent resequencing method. We then applied both methods to detect mosaicism in cardiac tissue-derived exome sequences of 66 participants for which matched blood and heart tissue was available.ResultsEM-mosaic detected 326 mosaic mutations in blood and/or cardiac tissue DNA. Of the 309 detected in blood DNA, 85/97 (88%) tested were independently confirmed, while 7/17 (41%) candidates of 17 detected in cardiac tissue were confirmed. MosaicHunter detected an additional 64 mosaics, of which 23/46 (50%) among 58 candidates from blood and 4/6 (67%) of 6 candidates from cardiac tissue confirmed. Twenty-five mosaic variants altered CHD-risk genes, affecting 1% of our cohort. Of these 25, 22/22 candidates tested were confirmed. Variants predicted as damaging had higher variant allele fraction than benign variants, suggesting a role in CHD. The estimated true frequency of mosaic variants above 10% mosaicism was 0.14/person in blood and 0.21/person in cardiac tissue. Analysis of 66 individuals with matched cardiac tissue available revealed both tissue-specific and shared mosaicism, with shared mosaics generally having higher allele fraction.ConclusionsWe estimate that ~ 1% of CHD probands have a mosaic variant detectable in blood that could contribute to cardiac malformations, particularly those damaging variants with relatively higher allele fraction. Although blood is a readily available DNA source, cardiac tissues analyzed contributed ~ 5% of somatic mosaic variants identified, indicating the value of tissue mosaicism analyses