scholarly journals Collection of human reaction times and supporting health related data for analysis of cognitive and physical performance

Data in Brief ◽  
2018 ◽  
Vol 17 ◽  
pp. 469-511 ◽  
Author(s):  
Petr Brůha ◽  
Roman Mouček ◽  
Vítězslav Vacek ◽  
Pavel Šnejdar ◽  
Kateřina Černá ◽  
...  
Keyword(s):  
Physical Performance ◽  
Reaction Times ◽  
Related Data ◽  
Human Reaction ◽  
Health Related

Novel Visualization of Large Health Related Data Sets

2015 ◽  
Author(s):  
William E. Hammond ◽  
Vivian L. West ◽  
David Borland ◽  
Igor Akushevich ◽  
Eugenia M. Heinz
Keyword(s):  
Data Sets ◽  
Related Data ◽  
Health Related

scholarly journals Assessment of Dietary Habits, Physical Activity and Lifestyle in Medical University Students

2021 ◽  
Vol 13 (6) ◽  
pp. 3572
Author(s):  
Lavinia-Maria Pop ◽  
Magdalena Iorga ◽  
Iulia-Diana Muraru ◽  
Florin-Dumitru Petrariu
Keyword(s):  
Physical Activity ◽  
Medical Students ◽  
Fast Food ◽  
Dietary Habits ◽  
Healthy Life ◽  
Related Data ◽  
The Third ◽  
Health Related ◽  
Medical University ◽  
Busy Schedule

A busy schedule and demanding tasks challenge medical students to adjust their lifestyle and dietary habits. The aim of this study was to identify dietary habits and health-related behaviours among students. A number of 403 students (80.40% female, aged M = 21.21 ± 4.56) enrolled in a medical university provided answers to a questionnaire constructed especially for this research, which was divided into three parts: the first part collected socio-demographic, anthropometric, and medical data; the second part inquired about dietary habits, lifestyle, sleep, physical activity, water intake, and use of alcohol and cigarettes; and the third part collected information about nutrition-related data and the consumption of fruit, vegetables, meat, eggs, fish, and sweets. Data were analysed using SPSS v24. Students usually slept M = 6.71 ± 1.52 h/day, and one-third had self-imposed diet restrictions to control their weight. For both genders, the most important meal was lunch, and one-third of students had breakfast each morning. On average, the students consumed 1.64 ± 0.88 l of water per day and had 220 min of physical activity per week. Data about the consumption of fruit, vegetables, meat, eggs, fish, sweets, fast food, coffee, tea, alcohol, or carbohydrate drinks were presented. The results of our study proved that medical students have knowledge about how to maintain a healthy life and they practice it, which is important for their subsequent professional life.

510 A Profile of Physical Performance Variables in an Out-Patient Adult Population with Narcolepsy

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A201-A201
Author(s):  
Ragy Tadrous ◽  
Julie Broderick ◽  
Niamh Murphy ◽  
Lisa Slattery ◽  
Gillian Quinn ◽  
...  
Keyword(s):  
Quality Of Life ◽  
Physical Activity ◽  
Physical Performance ◽  
Symptom Severity ◽  
Health Related Quality ◽  
Cardiopulmonary Fitness ◽  
Performance Variables ◽  
Related Quality ◽  
Health Related

Abstract Introduction Narcolepsy can significantly impact the physical and mental wellbeing of people with narcolepsy, and has been associated with significant reductions in quality of life and physical performance. People with narcolepsy demonstrate many barriers to being physically fit and active, such as sleepiness and social isolation. Despite physical functioning and vitality being the most affected domains of health-related quality of life in this cohort, little is known about how physical performance variables are affected in people with narcolepsy. Methods This cross-sectional study profiled the physical performance of adults with narcolepsy attending the Narcolepsy Centre located in St. James’s Hospital. Participants underwent a physical performance test battery that investigated cardiopulmonary fitness, physical activity, muscle strength and endurance. Furthermore, health-related quality of life (HRQoL), symptom severity and sedentary behaviour was ascertained through self-report questionnaires. Results A total of 23 participants were recruited in this study. The majority of participants were female (n=13, 56.52%) and the mean age was 31.53 (± 13.17) years. Physical performance was generally found to be lower than age-and-gender matched normative values for cardiopulmonary fitness, physical activity and muscle strength and endurance. Participants’ completed 42.20 ± 21.41 minutes of moderate-vigorous physical activity daily as measured by actigraphy. Considerable sedentary behaviour was objectively measured in this sample (10.21 hours). Symptom severity was high as measured by the Epworth Sleepiness Scale and the Narcolepsy Severity Scale, and participants reported reduced quality of life when compared to general population norms (US, UK, France and Norway). Conclusion Markedly reduced physical performance was identified in this sample of people with narcolepsy, irrespective of participant age, gender and BMI. Future research should explore the role of exercise in improving the physical fitness in people with narcolepsy, and the influence of exercise on HRQoL and symptom severity in this cohort. Support (if any) This study was completed as part of Mr Ragy Tadrous’ Master of Science (MSc) degree in Trinity College Dublin. This degree was co-sponsored by the Physiotherapy Department in St. James’s Hospital, Dublin.

Understanding Data Collection Mechanisms Used by Health and Wellness Applications (Preprint)

2021 ◽  
Author(s):  
Ben Philip ◽  
Mohamed Abdelrazek ◽  
Alessio Bonti ◽  
Scott Barnett ◽  
John Grundy
Keyword(s):  
Data Collection ◽  
User Experience ◽  
Health Data ◽  
Domain Model ◽  
Health And Wellness ◽  
Related Services ◽  
Related Data ◽  
Medical Apps ◽  
App Development ◽  
Health Related

UNSTRUCTURED Our objective is to better understand health-related data collection across different mHealth app categories. This would help in developing a health domain model for mHealth apps to facilitate app development and data sharing between these apps to improve user experience and reduce redundancy in data collection. We identified app categories listed in a curated library which was then used to explore the Google Play Store for health/medical apps that were then filtered using our inclusion criteria. We downloaded and analysed these apps using a script we developed around the popular AndroGuard tool. We analysed the use of Bluetooth peripherals and built-in sensors to understand how a given app collects/generates health data. We retrieved 3,251 applications meeting our criteria, and our analysis showed that only 10.7% of these apps requested permission for Bluetooth access. We found 50.9% of the Bluetooth Service UUIDs to be known in these apps, with the remainder being vendor specific. The most common health-related services using the known UUIDs were Heart Rate, Glucose and Body Composition. App permissions show the most used device module/sensor to be the camera (20.57%), closely followed by GPS (18.39%). Our findings are consistent with previous studies in that not many health apps were found to use built-in sensors or peripherals for collecting health data. The use of more peripherals and automated data collection along with integration with other apps could increase usability and convenience which would eventually also improve user experience and data reliability.

Secure Cross-Border Exchange of Health Related Data: The KONFIDO Approach

2019 ◽  
pp. 318-327
Author(s):  
Sotiris Diamantopoulos ◽  
Dimitris Karamitros ◽  
Luigi Romano ◽  
Luigi Coppolino ◽  
Vassilis Koutkias ◽  
...  
Keyword(s):  
Related Data ◽  
Cross Border ◽  
Health Related

scholarly journals Data safe havens to combine health and genomic data: benefits and challenges

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Kerina H Jones ◽  
Arron S Lacey ◽  
Brian L Perkins ◽  
Mark I Rees
Keyword(s):  
Association Studies ◽  
Genomic Data ◽  
Population Level ◽  
Data Availability ◽  
Genome Wide Association Studies ◽  
Related Data ◽  
Research Areas ◽  
Individual Privacy ◽  
Access Controls ◽  
Health Related

ABSTRACTObjectivesData safe havens can bring together and combine a rich array of anonymised person-based data for research and policy evaluation within a secure setting. To date, the majority of available datasets have been structured micro-data derived from routine health-related records. Possibilities are opening up for the greater reuse of genomic data such as Genome Wide Association studies (GWAS) and Whole Exome/Genome Sequencing (WES or WGS). However, there are considerable challenges to be addressed if the benefits of using these data in combination with health-related data are to be realized safely. ApproachWe explore the benefits and challenges of using genomic datasets with health-related data, and using the Secure Anonymised Information Linkage (SAIL) system as a case study, the implications and way forward for Data Safe Havens in seeking to incorporate genomic data for use with health-related data. ResultsThe benefits of using GWAS, WES and WGS data in conjunction with health-related data include the potential to explore genetics at a population level and open up novel research areas. These include the ability to increasingly stratify and personalize how medical indications are detected and treated through precision medicine by understanding rare conditions and adding socioeconomic and environmental context to genomic data. Among the challenges are: data availability, computing capacity, technical solutions, legal and regulatory frameworks, public perceptions, individual privacy and organizational risk. Many of the challenges within these areas are common to person-based data in general, and often Data Safe Havens have been designed to address these. But there are also aspects of these challenges, and other challenges, specific to genomic data. These include issues due to the unknown clinical significance of genomic information now or in the future, with corresponding risks for privacy and impact on individuals. ConclusionGenomic data sets contain vast amounts of valuable information, some of which is currently undefined, but which may have direct bearing on individual health at some point. The use of these data in combination with health-related data has the potential to bring great benefits, better clinical trial stratification, epidemiology project design and clinical improvements. It is, therefore, essential that such data are surrounded by a properly-designed, robust governance framework including technical and procedural access controls that enable the data to be used safely.

scholarly journals The Implications of Using Stereotypes

2020 ◽  
Vol 25 (4) ◽  
pp. 331-336
Author(s):  
Gabriela-Maria Man
Keyword(s):  
Stereotype Threat ◽  
Human Resource ◽  
Physical Performance ◽  
Negative Consequences ◽  
Relevant Today ◽  
Health Related ◽  
Group Members ◽  
Group Diversity

AbstractThe term stereotype was first used around a century ago, but its meaning and implications are relevant today due to an increase in group diversity and interactions. Stereotypes are simplistic and generalized beliefs about group members that can have negative consequences. This article reviews some of the evidence relating to two of the most common implications of stereotypes; discrimination and changes in cognitive and physical performance related with stereotype threat. The findings from this article may be helpful for human resource (HR) specialists, professors, health related specialists and those engaged in evaluation activities.

Sign in / Sign up

Export Citation Format

Share Document