The Influence of Chronotype and Grit on Lifestyle and Physical Activity

Background:  The chronotype of a person refers to an individual's natural sleep-wake cycle and whether that individual prefers morning or evening activities, and grit is an individual's perseverance and passion for long-term goals.Aim: The purpose of this study was to investigate the relationship between grit, chronotype, physical activity, and leading a healthy lifestyle in college-age students.Methods:  Health and fitness data (i.e., chronotype, grit, lifestyle assessment score, and daily steps) from 431 first-semester university students at a private college were collected and analyzed. Results: This study found that grit and chronotype both have significant correlations with living a healthy lifestyle and with physical activity. Grit more accurately predicts a person's lifestyle (β = -13.712, r = 0.39, p < 0.0001) while chronotype more accurately predicts the physical activity, or steps, of a person (β = 66.48, r = .19, p = .0001). Chronotype can also accurately predict the grit of a person (r = .25, p < .0001), and it was found that morning people tend to have more grit.Conclusions:  This study concluded that grit, chronotype, steps, and a healthy lifestyle are all significantly correlated with each other. Knowing the relationship between endogenous chronotype, grit, and living a physically active and healthy lifestyle can help inform policy decisions related to the goal of strengthening an institution's inclusive and healthy academic community

The Impact of the COVID-19 Pandemic on College Student’s Stress and Physical Activity Levels

Background: The coronavirus disease 2019 (COVID-19) pandemic adversely disrupted university student educational experiences worldwide, with consequences that included increased stress levels and unhealthy sedentary behavior. Aim: This study aimed to quantify the degree of impact that COVID-19 had on the levels of physical activity and stress of university students by utilizing wearable fitness tracker data and standard stress survey instrument scores before and during the pandemic. Methods: We collected Fitbit heart rate and physical activity data, and the results of a modified Social Readjustment Rating Scale (SRRS) stress survey from 2,987 university students during the Fall 2019 (residential instruction; before COVID-19) and Fall 2020 (hybrid instruction; during COVID-19) semesters. Results: We found indicators of increased sedentary behavior during the pandemic. There was a significant decrease in both the levels of physical activity as measured by mean daily step count (↓636 steps/day; p = 1.04 · 10-9) and minutes spent in various heart rate zones (↓58 minutes/week; p = 2.20 · 10-16). We also found an increase in stressors during the pandemic, primarily from an increase in the number of students who experienced the “death of a close family member” (38.8%), with the number even higher for the population of students who opted to stay home and attend classes virtually (41.4%). Conclusions: This study quantifies the decrease in levels of physical activity and notes an increase in the number of students who experienced the death of a close family member, a known stressor, during the first year of the COVID-19 pandemic. These findings allow for more informed student-health-focused interventions related to the COVID-19 pandemic disruptions experienced by academic communities worldwide

Using Amazon Mechanical Turk to Transcribe Historical Handwritten Documents

The developing “information age” is continually unraveling new ways of discovering, presenting and sharing information. Most new academic material is digitally formatted upon its creation and is thus easy to find and query. However, there remains a good deal of material from times prior to the “information age” that has yet to be converted to digital form. Much of this material can be found in library collections—whether academic, public or private—and thus remains available only to a limited number of locals or willing-and-able sojourners. Using OCR technology, most typeset documents can be digitized and made available online; and there are several projects underway to do exactly this. However, there remains little to be done for handwritten materials. Those who own collections of handwritten documents are increasingly wanting to make the content thereof available to the general public. Unfortunately, traditional transcription models typically prove to be expensive or inefficient and pdf snapshots are not searchable. We have developed a model for digital transcription using Google Docs and Amazon's Mechanical Turk. Using this model, one can use an online workforce to efficiently transcribe handwritten texts and perform quality control at a cost much lower than professional transcription services. To illustrate the model we used Amazon’s Mechanical Turk to transcribe and then proofread the Frederick Douglass Diary which we have made available on a public searchable wiki. The total cost of transcription and proofreading for the 72 page diary was less than $25.00 with some pages being transcribed and proofread for as little as$0.04. Our results show that using Amazon’s Mechanical Turk holds great promise for providing an affordable transcription method for hand-written historical documents making them easily sharable and fully searchable