Monitoring beliefs and physiological measures in students at risk for COVID-19 using wearable sensors and smartphone technology: Protocol for a mobile health study (Preprint)

BACKGROUND The COVID-19 pandemic has impacted lives significantly and greatly affected an already vulnerable population, college students, in relation to mental health and public safety. Social distancing and isolation have brought about challenges to student’s mental health. Mobile health apps and wearable sensors may help to monitor students at risk for COVID-19 and support their mental well-being. OBJECTIVE Through the use of a wearable sensor and smartphone-based survey completion, this study aimed to monitor students at risk for COVID-19. METHODS We conducted a prospective study of students, undergraduate and graduate, at a public university in the Midwest. Students were instructed to download the Fitbit, Social Rhythms, and Roadmap 2.0 apps onto their personal mobile devices (Android or iOS). Subjects consented to provide up to 10 saliva samples during the study period. Surveys were administered through the Roadmap 2.0 app at five timepoints - at baseline, 1-month later, 2-months later, 3-months later, and at study completion. The surveys gathered information regarding demographics, COVID-19 diagnoses and symptoms, and mental health resilience, with the aim of documenting the impact of COVID-19 on the college student population. RESULTS This study enrolled 2158 college students between September 2020 and January 2021. Subjects are currently being followed on-study for one academic year. Data collection and analysis are ongoing. CONCLUSIONS This study examined student health and well-being during the COVID-19 pandemic. While data collection and analyses are ongoing, the study will assess the feasibility of wearable sensor use and survey completion in a college student population, which may inform the role of our mobile health tools on student health and well-being. Finally, using wearable sensor data, biospecimen collection, and self-reported COVID-19 diagnosis, our results may provide key data towards the development of a model for the early prediction and detection of COVID-19. CLINICALTRIAL ClinicalTrials.gov NCT04766788

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Wearable sensors and Mobile Health (mHealth) technologies to assess and promote physical activity in stroke: a narrative review

Brain Impairment ◽

10.1017/brimp.2016.1 ◽

2016 ◽

Vol 17 (1) ◽

pp. 34-42 ◽

Cited By ~ 12

Author(s):

Shamala Thilarajah ◽

Ross A Clark ◽

Gavin Williams

Keyword(s):

Physical Activity ◽

Behaviour Change ◽

Mobile Health ◽

Wearable Sensors ◽

Chronic Illnesses ◽

Behaviour Change Techniques ◽

Health Issues ◽

Activity Trackers ◽

Wearable Activity Trackers ◽

Smartphone Technology

Stroke is a leading cause of disability worldwide, with approximately one third of people left with permanent deficits impacting on their function. This may contribute to a physically inactive lifestyle and further associated health issues. Current research suggests that people after stroke are not meeting the recommended levels of physical activity, and are less active than people with other chronic illnesses. Thus, it is important to understand how to support people after stroke to uptake and maintain physical activity. Wearable sensors and mobile health (mHealth) technologies are a potential platform to measure and promote physical activity. Some of these technologies may incorporate behaviour change techniques such as real-time feedback. Although wearable activity trackers and smartphone technology are widely available, the feasibility and applicability of these technologies for people after stroke is unclear. This article reviews the devices available for assessment of physical activity in stroke and discusses the potential for advances in technology to promote physical activity in this population.

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Discriminant Validation of the Test of Reading Performance (TORP) for Identifying Children at Risk of Reading Difficulties

European Journal of Psychological Assessment ◽

10.1027//1015-5759.16.2.139 ◽

2000 ◽

Vol 16 (2) ◽

pp. 139-146 ◽

Cited By ~ 17

Author(s):

Padeliadu Susana ◽

Georgios D. Sideridis

Keyword(s):

At Risk ◽

Elementary School Students ◽

Reading Difficulties ◽

Reading Performance ◽

Low Achievers ◽

Children At Risk ◽

School Students ◽

Students At Risk ◽

Group A ◽

The Mean

Abstract This study investigated the discriminant validation of the Test of Reading Performance (TORP), a new scale designed to evaluate the reading performance of elementary-school students. The sample consisted of 181 elementary-school students drawn from public elementary schools in northern Greece using stratified random procedures. The TORP was hypothesized to measure six constructs, namely: “letter knowledge,” “phoneme blending,” “word identification,” “syntax,” “morphology,” and “passage comprehension.” Using standard deviations (SD) from the mean, three groups of students were formed as follows: A group of low achievers in reading (N = 9) including students who scored between -1 and -1.5 SD from the mean of the group. A group of students at risk of reading difficulties (N = 6) including students who scored between -1.5 and -2 SDs below the mean of the group. A group of students at risk of serious reading difficulties (N = 6) including students who scored -2 or more SDs below the mean of the group. The rest of the students (no risk, N = 122) comprised the fourth group. Using discriminant analyses it was evaluated how well the linear combination of the 15 variables that comprised the TORP could discriminate students of different reading ability. Results indicated that correct classification rates for low achievers, those at risk for reading problems, those at risk of serious reading problems, and the no-risk group were 89%, 100%, 83%, and 97%, respectively. Evidence for partial validation of the TORP was provided through the use of confirmatory factor analysis and indices of sensitivity and specificity. It is concluded that the TORP can be ut ilized for the identification of children at risk for low achievement in reading. Analysis of the misclassified cases indicated that increased variability might have been responsible for the existing misclassification. More research is needed to determine the discriminant validation of TORP with samples of children with specific reading disabilities.

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