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COVID 19 and the perceived impacts on adolescents’ and young adults’ mental health: A quantitative survey

Kumar et al. | Jul 31, 2023

COVID 19 and the perceived impacts on adolescents’ and young adults’ mental health: A quantitative survey
Image credit: Nick Fewings

Here, recognizing the effects of the COVID-19 pandemic on young peoples' mental health and wellbeing the authors used an online survey which included the short General Health Questionnaire (GHQ-12) to probe 102 young adults. Overall they found that young adults perceived the pandemic to be detrimental to many areas of their wellbeing, with females and those aged 18-19 and 22-23 reporting to be the most significantly impacted.

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Does technology help or hurt learning? Evidence from middle school and high school students

Lu et al. | Oct 02, 2022

Does technology help or hurt learning? Evidence from middle school and high school students

Here, recognizing the vastly different opinion held regarding device usage, the authors considered the effects of technology use on middle and high school students' learning effectiveness. Using an anonymous online survey they found partial support that device use at school increases learning effectiveness, but found strong support for a negative effect of technology use at home on learning effectiveness. Based on their findings they suggest that the efficacy of technology depends on environmental context along with other important factors that need consideration.

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Sex differences in confidence and memory

Primack et al. | Oct 25, 2021

Sex differences in confidence and memory

In this work, the authors sought to provide an original experiment to investigate the conflict over whether males or females tend to exhibit greater accuracy or confidence in their memories. By using an online portal to obtain a convenience sample, the authors found that their results suggest that though males tend to be more confident regarding their memories, they may in fact remember fewer details. The authors suggest that these findings merit further research before making systematic changes regarding crime scene recall settings.

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Depression detection in social media text: leveraging machine learning for effective screening

Shin et al. | Mar 25, 2025

Depression detection in social media text: leveraging machine learning for effective screening

Depression affects millions globally, yet identifying symptoms remains challenging. This study explored detecting depression-related patterns in social media texts using natural language processing and machine learning algorithms, including decision trees and random forests. Our findings suggest that analyzing online text activity can serve as a viable method for screening mental disorders, potentially improving diagnosis accuracy by incorporating both physical and psychological indicators.

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Attitudes towards mental health in Indians who practice yoga regularly and those who do not

Komar et al. | Jul 13, 2022

Attitudes towards mental health in Indians who practice yoga regularly and those who do not

Whether it is through implicit association or intentional practice, yoga has been known to help individuals maintain good mental health. However, many communities, such as South Asian communities, often project the stereotype that embodies neglecting topics such as mental health and considering them taboo. In this online survey-based study, the authors focused on examining whether yoga would alter individuals’ attitudes toward mental health. They hypothesized that 1) participants who regularly practiced yoga would be more familiar with the term mental health, 2) participants who practiced yoga would value their mental health more, and 3) participants who practiced yoga regularly would be more open about their mental health and be more likely to reach out for professional help if needed. They did not find a statistical significance for any of our hypotheses which suggests that yoga may not have an effect on perceptions of mental health in yoga-practicing Indian adults.

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A five-year retrospective analysis of Tuberculosis risk factors and their variability in the United States

Kini et al. | Mar 14, 2026

A five-year retrospective analysis of Tuberculosis risk factors and their variability in the United States
Image credit: Kini, Diaz Gaviria, Diaz, and Kini

The main goal of this study is to determine what demographics are related to tuberculosis incidence in the United States populations, particularly if changing demographics are related to differences in tuberculosis risk over two discrete time periods. The major finding is that in the two studied time periods, tuberculosis risk factors were somewhat consistent and may be influenced by things such as immigration, healthcare access, and race or ethnicity, although the top predictor did change.

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An evaluation of the trends in U.S. maternal deaths based on abortion policies from 2018 to 2021

Haq et al. | Feb 18, 2026

An evaluation of the trends in U.S. maternal deaths based on abortion policies from 2018 to 2021

Here the authors evaluate the relationship between state-level abortion policies and maternal mortality across the United States from 2018 to 2021. Their findings reveal that states with restrictive abortion laws consistently experienced higher maternal mortality ratios than those with protective policies, culminating in a 72% increase in deaths within restrictive states by the end of the study period.

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