Machine learning-based analytics of the impact of the Covid-19 pandemic on alcohol consumption habit changes among United States healthcare workers DOI Creative Commons
Mostafa Rezapour, Muhammad Khalid Khan Niazi, Metin N. Gürcan

et al.

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: April 12, 2023

The COVID-19 pandemic is a global health concern that has spread around the globe. Machine Learning promising in fight against pandemic. learning and artificial intelligence have been employed by various healthcare providers, scientists, clinicians medical industries disease. In this paper, we discuss impact of Covid-19 on alcohol consumption habit changes among workers United States during first wave We utilize multiple supervised unsupervised machine methods models such as decision trees, logistic regression, support vector machines, multilayer perceptron, XGBoost, CatBoost, LightGBM, AdaBoost, Chi-Squared Test, mutual information, KModes clustering synthetic minority oversampling technique mental survey data obtained from University Michigan Inter-University Consortium for Political Social Research to investigate links between COVID-19-related deleterious effects habits workers. Through interpretation methods, concluded whose children stayed home US consumed more alcohol. also found work schedule due led change use habits. Changes food consumption, age, gender, geographical characteristics, sleep habits, amount news screen time are important predictors an increase States.

Language: Английский

A longitudinal study of the impact of COVID-19 restrictions on students’ health behavior, mental health and emotional well-being DOI Creative Commons
Peter Reuter,

Bridget L. Forster,

Bethany J. Kruger

et al.

PeerJ, Journal Year: 2021, Volume and Issue: 9, P. e12528 - e12528

Published: Dec. 14, 2021

Background COVID-related restrictions impacted the lives of students on and off campus during Academic Year 2020/2021. Methods Our study collected data student health behavior habits as well their mental emotional using anonymous surveys. We compared these with prior to COVID in longitudinal part our ( n = 721) analyzed them for cross-sectional 506). Results The show a significant difference some behaviors habits, such sleeping physical activity, breakfast consumption, time spent online or playing video games, vaping, marijuana use, pandemic pre-COVID data. Respondents also reported increase difficulty concentrating, remembering, making decisions, being by feelings sadness hopelessness. Yet, there was no proportion respondents considering, planning attempting suicide COVID. illuminate negative effect overall situation students’ well-being. Three-quarters having craved human interaction past six months, more than half felt that mental/emotional had been lack social events switch virtual (online) teaching. Two-thirds expressed they less connected peers motivated studies previous semesters. Fifty percent selected anxious, stressed, overwhelmed, disconnected, tired, fatigued words best described state pandemic. Conclusions impact severe one would have expected based early stage While changed period, changes were not substantial overall. did find an COVID, although from survey make well-being evident. will unquestionably be long-lasting necessitate further future investigations.

Language: Английский

Citations

23

Limited negative effects of the COVID-19 pandemic on mental health measures of Ghanaian university students DOI Creative Commons
Mary Adjepong,

Felicity Amoah-Agyei,

Chen Du

et al.

Journal of Affective Disorders Reports, Journal Year: 2022, Volume and Issue: 7, P. 100306 - 100306

Published: Jan. 1, 2022

Stress and mental health outcomes are negatively correlated among university students throughout the world. Reports of differences in stress perception by gender exist, but there is limited data on from sub-Saharan African countries. This study describes burden perceived financial stress; characterizes mood degree anxiety symptoms; examines coping mechanisms, including resilience repetitive negative thinking (RNT); explores how at a Ghanaian believed COVID-19 pandemic affected these measures.Students (n = 129) were recruited Kwame Nkrumah University Science Technology, Kumasi, Ghana October 2020 - January 2021. Validated surveys used. Participants asked "Are your answers to questions pandemic?"No mean scores observed between genders. For female students, was positively associated with RNT (p 0.009), 0.002), < 0.001). Males more likely report decreased during no difference (PS) change category males. Effects mixed, substantial proportions reported improvements or stress, mood, anxiety, RNT.Students one particiapted this cross-sectional survey.This adds understanding higher education experiencing uncertainties Ghana.

Language: Английский

Citations

16

Understanding the mental health impacts of biological disasters: Lessons from Taiwan's experience with COVID-19 DOI Creative Commons
Chih-Chieh Chang,

Kuan-Ying Hsieh,

Su‐Ting Hsu

et al.

Journal of the Formosan Medical Association, Journal Year: 2024, Volume and Issue: 124(1), P. 6 - 14

Published: March 22, 2024

Biological disasters pose a growing challenge in the 21st century, significantly impacting global society. Taiwan has experienced such disasters, resulting long-term consequences like loss of life, trauma, economic decline, and societal disruptions. Post-disaster, mental health issues as fear, anxiety, depression, post-traumatic stress disorder (PTSD), surge, accompanied by increased suicide rates. The Coronavirus disease 2019 (COVID-19) (also called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)) pandemic, recognized biological disaster, triggered lockdowns quarantines Taiwan, causing lifestyle changes, recession, so on. These shifts may elevate uncertainty about future, intensifying leading to rise various illnesses. This article reviews studies conducted during emphasizing need integrate this research for future preparedness interventions regarding impacts including COVID-19. Further is essential explore effects, interventions, generalizability.

Language: Английский

Citations

3

Adolescents’ Digital Nightlife: The Comparative Effects of Day- and Nighttime Smartphone Use on Sleep Quality DOI Creative Commons
Teun Siebers, Ine Beyens, Susanne E. Baumgartner

et al.

Communication Research, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 30, 2024

The smartphone occupies a substantial part of adolescents’ daily life, from the moment they wake up to, for some, well beyond their bedtime. current study compared impact daytime, pre-bedtime, and post-bedtime use on sleep quality. In addition, it explored differential effects lean-back lean-forward apps. We collected data 155 adolescents across 21 days using tracking (745,706 app activities) in combination with experience sampling (1,950 quality assessments). found no significant daytime pre-bedtime quality, but negative association (β = −.09). between varied categories: Time spent apps around bedtime, such as social media right before −.08) game after bedtime −.23), was associated lower (i.e., video players) not neither nor

Language: Английский

Citations

3

Machine learning-based analytics of the impact of the Covid-19 pandemic on alcohol consumption habit changes among United States healthcare workers DOI Creative Commons
Mostafa Rezapour, Muhammad Khalid Khan Niazi, Metin N. Gürcan

et al.

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: April 12, 2023

The COVID-19 pandemic is a global health concern that has spread around the globe. Machine Learning promising in fight against pandemic. learning and artificial intelligence have been employed by various healthcare providers, scientists, clinicians medical industries disease. In this paper, we discuss impact of Covid-19 on alcohol consumption habit changes among workers United States during first wave We utilize multiple supervised unsupervised machine methods models such as decision trees, logistic regression, support vector machines, multilayer perceptron, XGBoost, CatBoost, LightGBM, AdaBoost, Chi-Squared Test, mutual information, KModes clustering synthetic minority oversampling technique mental survey data obtained from University Michigan Inter-University Consortium for Political Social Research to investigate links between COVID-19-related deleterious effects habits workers. Through interpretation methods, concluded whose children stayed home US consumed more alcohol. also found work schedule due led change use habits. Changes food consumption, age, gender, geographical characteristics, sleep habits, amount news screen time are important predictors an increase States.

Language: Английский

Citations

8