![187682-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2023-06/187682-Thumbnail%20Image.png?versionId=ljsnW40Y8AJkS5ByD8s3ZYXtgUH5DR65&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240617/us-west-2/s3/aws4_request&X-Amz-Date=20240617T101404Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=9aaead826c025bfc3116bb2c94fa206e8606aaeab8d6cd17430a3553db175e33&itok=vix_rbda)
![162295-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-12/162295-Thumbnail%20Image.png?versionId=Dyq7stw.Jt1t03vqFu58GK6QjNdg0npi&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240617/us-west-2/s3/aws4_request&X-Amz-Date=20240617T101404Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=4771981f3914011589c4fdd2b1d6d44e822c965815b0c1fedbdd06303d58f2b5&itok=mLsdEfIe)
A dynamical approach is used to avoid isolating systems and instead view systems as interacting together. The current study applied a dynamical approach to heart rate variability and personality. There were two main research questions that this study sought to answer with a dynamical analysis of heart rate variability and personality: “Can we listen to a heartbeat and draw connections to behavior and personality?” and “Is dynamical analysis more effective than traditional analysis at finding correlations between heart rate variability and personality?” To answer these questions a dynamical analysis of heart rate variability was conducted (detrended fluctuation analysis; DFA) along with traditional analysis (standard deviations of NN intervals, SDNN, and root mean squared of successive deviations, RMSSD) and then correlations between heart rate variability measures and personality traits from the Big Five Inventory, Positive and Negative Affect schedule, and State-Trait Anxiety Inventory were examined. Data for this study came from the Rapid Automatic & Adaptive Model for Performance Prediction (RAAMP2) Dataset that was part of The Multimodal Objective Sensing to Assess Individuals with Context (MOSAIC) project. There were no statistically significant correlations between heart rate variability and personality. However, there were notable correlations between extraversion and SDNN and RMSSD and between positive affect and SDNN and RMSSD. We found that SDNN and RMSSD were more closely correlated to each other compared to DFA to either measure. This suggests that DFA can provide information that SDNN and RMSSD do not. Future research can explore dynamic analysis of heart rate variability and other nested systems.
![162308-Thumbnail Image.png](https://d1rbsgppyrdqq4.cloudfront.net/s3fs-public/styles/width_400/public/2021-12/162308-Thumbnail%20Image.png?versionId=pRjBj7ui4Uk_mYXGhjyVm0fUe348rfmv&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIASBVQ3ZQ42ZLA5CUJ/20240617/us-west-2/s3/aws4_request&X-Amz-Date=20240617T101404Z&X-Amz-SignedHeaders=host&X-Amz-Expires=120&X-Amz-Signature=ff5f16e67ba279df76305098c14a8d73438d575f485306b0419fcbb1a6a6bd47&itok=QNPQ3g29)
This study sought to determine if perceived neighborhood danger impacted children's sleep. The current study asks: how does perceived neighborhood danger impact children’s sleep both quantity and quality (duration and efficiency), could children’s physical activity mediate these associations, and how do genetic and environmental factors play into these relationships? Questionnaires, biological measurements, and actigraphy watch data were collected from 709 8-year-old Arizonan twins and their parents in order to calculate neighborhood safety, sedentary physical activity, moderate to vigorous physical activity, sleep duration, and sleep efficiency as well as covariates. It was concluded that perceived neighborhood danger does not directly impact children’s sleep duration and efficiency, children’s physical activity does not mediate the relation of perceived neighborhood danger and children’s sleep, but rather, perceived neighborhood danger indirectly impacts children’s sleep duration and efficiency through moderate to vigorous activity, and finally, that both sedentary and moderate to vigorous activity are heavily influenced by genetics.