Time Use and Cognitive Achievement

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2	format correction	Dean Liu	-4 word(s)	2413	2023-05-11 07:16:00	\|

This entry is adapted from the peer-reviewed paper 10.3390/jintelligence11050088

Everyone’s time is limited, and there is competition between different aspects of time use; this requires comprehensive consideration of the effects of different aspects of time use on cognitive achievement in adolescents.

cognitive achievement time use depression symptoms adolescents middle school students

1. Introduction

Adolescents’ cognitive achievement not only strengthens individual human capital and future competitiveness in the labor market, but also enhances social innovation capacity and promotes economic growth (Cameron and Heckman 1998; Hunter 1986; McLeod and Kaiser 2004; Singh et al. 2019). It is necessary to clarify the mechanisms that contribute to the improvement of adolescents’ cognitive achievement. A growing number of policymakers and parents worldwide are paying attention to the impact of time use on well-being and mental health among adolescents (Borga 2019; Hunt and McKay 2015; Wight et al. 2009). If adolescents allocate a significant proportion of their discretionary time to positive and purposeful constructive activities, this will be beneficial to their healthy growth (Zill 1995). Some studies have analyzed adolescents’ time use. For instance, 81% of schoolchildren aged 11–17 years worldwide do not meet the World Health Organization’s recommendation of one hour of moderate to vigorous physical activity per day, and in China, the figure is 84.3% (Bull et al. 2020; Guthold et al. 2020). In the United States, about 45% of adolescents spend excessive time in front of electronic screens (Onyeaka et al. 2022). However, everyone’s time is limited, and there is competition between different aspects of time use. Considering the impact of only one aspect of time use on cognitive development may not be comprehensive, and all other aspects of time use need to be considered to understand the role of each aspect of time use on adolescents’ cognitive achievement. Thus, clarifying the relationship between time use and cognitive achievement will facilitate the effective utilization of time for adolescent development, and can provide a reference for targeted public health interventions. Cognitive achievement is defined as a comprehensive measure of logical thinking and problem-solving abilities based on standardized cognition tests. Considering the fixed schedules of Chinese adolescents during school hours, researchers investigate time use outside of school, including time spent on homework, playing sports, surfing the Internet, watching TV, and sleeping.

It is worth analyzing the impact of time use on cognitive achievement mechanisms, as this may shed light on the frequent negative emotions experienced by adolescents in real life (X. Liu et al. 2019b; Pekrun et al. 2002; Pekrun 2006). Depression symptoms are associated with adolescents’ time use and cognitive achievement, and may serve as mediating factors in explaining the relationship between the two. Unfortunately, depression symptoms among adolescents are becoming increasingly prevalent (Cao and Liu 2022; Gao et al. 2022; X. Liu et al. 2019a), with incidence rates rising from 5% at the start of adolescence to as high as 20% at the end of adolescence (Thapar et al. 2012). According to the World Health Organization, one in seven 10- to 19-year-olds worldwide suffers from mental health problems (WHO 2021). The COVID-19 pandemic has exacerbated this trend, with negative time use, such as decreased physical exercise and increased screen time (Neville et al. 2022), leading to cognitive decline and intensified depression symptoms in adolescents (Y. Liu et al. 2021; Xin et al. 2020). Despite this, there is limited research examining the mediating effect of depression symptoms on the relationship between time use and cognitive achievement, particularly in a Chinese context.

2. The Relationship between Time Use and Cognitive Achievement

Studies have explored the relationship between different aspects of time use and cognitive achievement. Most of the findings suggest that there is a negative relationship between time spent on the Internet and watching television and cognition. This may be because prolonged exposure to the Internet and television can cause changes in the structure and function of the brain, with potentially detrimental effects on higher-order cognition. Additionally, the variety and transience of stimuli on the Internet and television can easily lead to emotional fluctuations and distraction, resulting in cognitive decline (Kuss and Griffiths 2012; Mills 2014). A large-scale survey of American adolescents has revealed a negative correlation between screen time spent on television and social media and cognitive achievement (Walsh et al. 2020). A national survey of 17,076 American adolescents concluded that excessive screen time was detrimental to cognition, increasing the likelihood of cognitive difficulties, such as attention problems and memory impairment, by almost 1.3 times compared to those who did not overuse screens (Onyeaka et al. 2022). Jürges and Khanam (2021) found that educational activities were beneficial to cognitive achievement, while screen time, including watching TV, playing computer games, and social media use, increased internalization problems in Australian adolescents. Islam et al. (2020) discovered that addictive tendencies toward the Internet and electronic games were negatively associated with academic performance in 1704 Australian children aged 11–17 years, and recommended reducing Internet and gaming time through parental supervision and self-discipline. In addition, Internet use and gaming can also significantly disrupt adolescents’ sleep time (King et al. 2013) and increase the risk of mental disorders and dangerous behaviors (Green et al. 2020; Kliestik et al. 2020; Lăzăroiu et al. 2020; Rikkers et al. 2016).

Previous literature has shown that homework time is an important factor in learning ability (Kumar and Choudhury 2021). Parents and teachers tend to believe that spending time of homework can benefit children’s cognitive development (Cooper et al. 2000). Some research has found a significant positive correlation between these two variables. A study based on 8–12-year-old adolescents in India showed that increasing homework time significantly improved the cognitive achievement of students who were lagging behind, suggesting that increasing homework time is one of the key ways to reduce the quality gap between private and public schools in India (Kumar and Choudhury 2021). Reinforcement theory proposes that continuous stimulation leads to changes in the brain’s cognitive and behavioral responses, increasing the likelihood of that behavior. Homework is an effective means of consolidating what students have learned, and spending time on homework helps to reinforce what they have learned in the classroom, thus having a positive effect on cognitive development (Skinner 1954). This has been demonstrated in studies of adolescents in Ethiopia, Vietnam, and India (Borga 2019). There is also evidence that the positive correlation between the two increases with grade level (Cooper and Valentine 2001; Cooper et al. 2006). However, there is currently no consensus on the effect of homework time on cognition, and some studies have found a negative correlation between the two. Chang et al. (2014) found that time spent on homework was negatively correlated with course outcomes based on a survey of 2342 students, possibly because smarter children require less time to complete their homework.

Most studies suggest that there is a significant positive correlation between sleep time and cognitive development. Adequate sleep time can significantly improve cognitive achievement in adolescents, including performance in tasks related to executive function and multiple cognitive domains (Jones and Harrison 2001; Lo et al. 2016). A meta-analysis of 61 studies based on 71 populations showed that sleep restriction has a significant negative effect on executive function, long-term memory, and attention in cognitive performance (Lowe et al. 2017). A survey of 55 adolescents in the Netherlands found that longer sleep time significantly ameliorated visual spatial processing skills (Dewald-Kaufmann et al. 2013). The results from 8323 American adolescents showed that insufficient sleep (less than 9 h) has lasting negative effects on cognition and brain function (Yang et al. 2022). There are also studies suggesting that the correlation between the two is very weak (Astill et al. 2012) or even negative. For example, some surveys of elderly people in Japan and the Bronx found that respondents with longer sleep time had worse cognitive achievement (Kondo et al. 2021; Schmutte et al. 2007).

Insufficient physical activity time presents a critical challenge for today’s adolescents worldwide. In total, 84.6% of Filipino adolescents do not meet the recommended daily minimum of one hour of physical exercise (Cagas et al. 2022). Only 27% of Thai adolescents achieve the daily threshold of 60 min for moderate-to-vigorous physical activity (Widyastari et al. 2022). Prior literature supports a significant positive association between physical activity time and cognitive achievement. Increasing physical activity time can enhance physical and mental functioning, leading to improved cognition (Hillman et al. 2008; Tomporowski et al. 2008). Children who participate in physical activity have larger basal ganglia and hippocampal brain volumes than inactive children, which is associated with superior cognitive control and memory performance (Chaddock-Heyman et al. 2014). A dearth of physical activity can lead to chronic diseases (such as diabetes and obesity) and mental health problems and impose a substantial economic burden on society (Colditz 1999; Hillman et al. 2008). Some studies have produced inconsistent conclusions, with a review of 58 intervention studies finding no conclusive evidence of the beneficial impact of physical activity time on cognitive achievement (Singh et al. 2019). This was also similar to the findings of a survey of Australian fifth–sixth grade primary school students (Dwyer et al. 1983).

Previous literature also suggests possible gender and grade differences in time use (Lloyd et al. 2008). For instance, a survey of American adolescents showed that 8th graders spent more time watching TV and playing video games than 10th graders, and girls spent less time playing video games than boys (Tang and Patrick 2018). Twenge and Martin (2020) found significant gender differences in digital media use among American and British youth, with females spending more time on the Internet and social media, while males allocated more time to gaming and electronic devices. A study of 237 college students found that younger college students had shorter sleep time, while female college students had poorer sleep quality than males (Tsai and Li 2004). A study in Canada found that there were significant gender differences in weekend time use and that adolescents had less leisure time as their grade level increased (Hilbrecht et al. 2008).

In conclusion, existing research lacks a comprehensive analysis of adolescents’ time use across different aspects. Time is a finite resource, and different aspects of time use compete with each other. A narrow focus on a solitary aspect of time use is not effective, and it is crucial to analyze the impact of multiple aspects on adolescents’ cognitive achievement. According to the characteristics and life trajectories of adolescents, their time use typically includes activities such as homework, sports, surfing the Internet, watching TV, and sleeping. It is therefore imperative to investigate the impacts of these common aspects of time use on cognitive achievement among adolescents and give full consideration to gender and grade differences. This will help parents and teachers to improve their parenting and teaching methods effectively.

3. The Mediating Role of Depression Symptoms

Previous literature has demonstrated a correlation between time use and cognitive achievement, yet little is known about the underlying mechanism. School achievement and psychological well-being are both crucial for adolescents, and a range of factors affect these outcomes, such as parental support (Moè et al. 2020), teacher enthusiasm (Moe et al. 2021), and also depression symptoms (Moè 2015). The present study focuses mostly on the latter variable by examining time use on the one hand, and cognitive achievement on the other. Depression symptoms may serve as the mediating factor that helps to explain this relationship. Control-value theory recognizes that emotions play a crucial role in cognitive processing and behavior. Positive emotions are often seen as a driving force for learning and development, resulting in improved learning efficiency and academic performance. Conversely, negative emotions have a detrimental effect, hindering behavior, learning outcomes, and personal growth (Pekrun et al. 2002; Pekrun 2006). Depression symptoms are the most common negative emotional expression among adolescents worldwide. The World Health Organization estimates that the burden of depression will exceed all other diseases by 2030 (Thapar et al. 2012). The negative impact of depression symptoms on adolescents is becoming increasingly apparent (Gao et al. 2020; X. Liu et al. 2022b), with the incidence among Chinese adolescents rising significantly to 57% following the outbreak of the COVID-19 pandemic (Chen et al. 2021). Unfortunately, few studies have focused on the mediating role of depression symptoms (Lim and Jeong 2022). A study of 562 Puerto Ricans over the age of 60 found that depression symptoms played a complete mediating role in the relationship between perceived daily discrimination and cognitive function (K. Wang et al. 2022). Relevant conclusions drawn from previous studies in other populations cannot be directly applied to the adolescent population, so it is of significance to examine the mediating effect of depression symptoms while taking into account the unique characteristics of adolescence.

Research into the relationship between depression symptoms and cognition has accumulated a substantial body of literature, with the preponderance of evidence indicating that depression symptoms are significant predictors of cognitive decline (Conradi et al. 2011; Lee et al. 2012; Wagner et al. 2012), with 90% of depression patients experiencing impaired cognition (Hollon et al. 2006). A minority of studies have found little association between the two (Goulabchand et al. 2022; Grant et al. 2001). Studies investigating the impact of time allocation for tasks, such as homework and extracurricular activities, on the relationship between depression symptoms and cognition are relatively limited. A survey of Australian adolescents revealed that those with emotional issues or high levels of psychological distress spent the most time on the Internet or playing games (Rikkers et al. 2016). Neuroscientific evidence suggests that chronic sleep deprivation is a risk factor for the onset and progression of depression (Y.-Q. Wang et al. 2015). A study of 82 young adults found that Facebook use was associated with a decrease in subjective well-being. The more frequently people used Facebook, the lower their moment-to-moment experiences of happiness and life satisfaction tended to be (Kross et al. 2013). A review of adolescent mental health during the COVID-19 pandemic found that spending too much time on the Internet and social media can lead to increased symptoms of depression. This highlights how excessive screen time can be detrimental to the mental health of vulnerable adolescents (Oliveira et al. 2022). Although not all studies have confirmed this finding, a synthesis of 25 reviews reveals that the majority of research interprets the association between social media and mental health as weak or inconsistent (Valkenburg et al. 2022). A study of 79 suburban Florida high school students found that those with depression symptoms spent less time on homework and achieved lower average grades (Field et al. 2001). A significant positive association was observed between homework time and depression symptoms among Chinese primary school students in grades 2–6 (Xiao et al. 2022). However, the above literature only examined the relationship between individual time use and depression symptoms separately. Meanwhile, some individual studies have also explored the relationship between time use, cognition, and depression symptoms in specific domains. A survey of 3724 adolescents found that cognitive function moderated the effect of sleep time on depression symptoms (Zhou et al. 2022). A study of 280 retired individuals showed that self-reported depression symptoms were associated with slow stepping reaction time, a connection that could be explained by underlying cognitive impairment (Kvelde et al. 2010).

References

Cameron, Stephen V., and James J. Heckman. 1998. Life cycle schooling and dynamic selection bias: Models and evidence for five cohorts of American males. Journal of Political Economy 106: 262–333.
Hunter, John E. 1986. Cognitive ability, cognitive aptitudes, job knowledge, and job performance. Journal of Vocational Behavior 29: 340–62.
McLeod, Jane D., and Karen Kaiser. 2004. Childhood emotional and behavioral problems and educational attainment. American Sociological Review 69: 636–58.
Singh, Amika S., Emi Saliasi, Vera Van Den Berg, Léonie Uijtdewilligen, Renate H. M. De Groot, Jelle Jolles, Lars B. Andersen, Richard Bailey, Yu-Kai Chang, and Adele Diamond. 2019. Effects of physical activity interventions on cognitive and academic performance in children and adolescents: A novel combination of a systematic review and recommendations from an expert panel. British Journal of Sports Medicine 53: 640–47.
Borga, Liyousew Gebremedhin. 2019. Children’s own time use and its effect on skill formation. The Journal of Development Studies 55: 876–93.
Hunt, Eithne, and Elizabeth Anne McKay. 2015. What can be learned from adolescent time diary research. Journal of Adolescent Health 56: 259–66.
Wight, Vanessa R., Joseph Price, Suzanne M. Bianchi, and Bijou R. Hunt. 2009. The time use of teenagers. Social Science Research 38: 792–809.
Zill, Nicholas. 1995. Adolescent time use, risky behavior, and outcomes: An analysis of national data. Adolescents 11: 138.
Bull, Fiona C., Salih S. Al-Ansari, Stuart Biddle, Katja Borodulin, Matthew P. Buman, Greet Cardon, Catherine Carty, Jean-Philippe Chaput, Sebastien Chastin, and Roger Chou. 2020. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. British Journal of Sports Medicine 54: 1451–62.
Guthold, Regina, Gretchen A. Stevens, Leanne M. Riley, and Fiona C. Bull. 2020. Global trends in insufficient physical activity among adolescents: A pooled analysis of 298 population-based surveys with 1· 6 million participants. The Lancet Child & Adolescent Health 4: 23–35.
Onyeaka, Henry K., Chioma Muoghalu, Philip Baiden, Lucinda Okine, Hannah S. Szlyk, JaNiene E. Peoples, Erin Kasson, MSW Patricia Cavazos-Rehg, Joseph Firth, and John Torous. 2022. Excessive screen time behaviors and cognitive difficulties among adolescents in the United States: Results from the 2017 and 2019 national youth risk behavior survey. Psychiatry Research 316: 114740.
Liu, Xinqiao, Xueheng Gao, and Siqing Ping. 2019b. Post-1990s college students academic sustainability: The role of negative emotions, achievement goals, and self-efficacy on academic performance. Sustainability 11: 775.
Pekrun, Reinhard, Thomas Goetz, Wolfram Titz, and Raymond P. Perry. 2002. Academic emotions in students’ self-regulated learning and achievement: A program of qualitative and quantitative research. Educational Psychologist 37: 91–105.
Pekrun, Reinhard. 2006. The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review 18: 315–41.
Cao, Xiaojie, and Xin-Qiao Liu. 2022. Artificial intelligence-assisted psychosis risk screening in adolescents: Practices and challenges. World Journal of Psychiatry 12: 1287.
Gao, Wenjuan, Yunfeng Luo, Xiaojie Cao, and Xinqiao Liu. 2022. Gender differences in the relationship between self-esteem and depression among college students: A cross-lagged study from China. Journal of Research in Personality 97: 104202.
Liu, Xinqiao, Siqing Ping, and Wenjuan Gao. 2019a. Changes in undergraduate students’ psychological well-being as they experience university life. International Journal of Environmental Research and Public Health 16: 2864.
Thapar, Anita, Stephan Collishaw, Daniel S. Pine, and Ajay K. Thapar. 2012. Depression in adolescence. The Lancet 379: 1056–67.
WHO. 2021. Adolescent Mental Health. Available online: https://www.who.int/news-room/fact-sheets/detail/adolescent-mental-health (accessed on 20 January 2023).
Neville, Ross D., Kimberley D. Lakes, Will G. Hopkins, Giampiero Tarantino, Catherine E. Draper, Rosemary Beck, and Sheri Madigan. 2022. Global changes in child and adolescent physical activity during the COVID-19 pandemic: A systematic review and meta-analysis. JAMA Pediatrics 9: 886–94.
Liu, Yan, Song Yue, Xiaoran Hu, Jin Zhu, Zifan Wu, JianLi Wang, and Yili Wu. 2021. Associations between feelings/behaviors during COVID-19 pandemic lockdown and depression/anxiety after lockdown in a sample of Chinese children and adolescents. Journal of Affective Disorders 284: 98–103.
Xin, Meiqi, Sitong Luo, Rui She, Yanqiu Yu, Lijuan Li, Suhua Wang, Le Ma, Fangbiao Tao, Jianxin Zhang, and Junfeng Zhao. 2020. Negative cognitive and psychological correlates of mandatory quarantine during the initial COVID-19 outbreak in China. American Psychologist 75: 607.
Kuss, Daria J., and Mark D. Griffiths. 2012. Internet and gaming addiction: A systematic literature review of neuroimaging studies. Brain Sciences 2: 347–74.
Mills, Kathryn L. 2014. Effects of Internet use on the adolescent brain: Despite popular claims, experimental evidence remains scarce. Trends in Cognitive Sciences 18: 385–87.
Walsh, Jeremy J., Joel D. Barnes, Mark S. Tremblay, and Jean-Philippe Chaput. 2020. Associations between duration and type of electronic screen use and cognition in US children. Computers in Human Behavior 108: 106312.
Jürges, Hendrik, and Rasheda Khanam. 2021. Adolescents’ time allocation and skill production. Economics of Education Review 85: 102178.
Islam, Md Irteja, Raaj Kishore Biswas, and Rasheda Khanam. 2020. Effect of internet use and electronic game-play on academic performance of Australian children. Scientific Reports 10: 1–10.
King, Daniel L., Michael Gradisar, Aaron Drummond, Nicole Lovato, Jason Wessel, Gorica Micic, Paul Douglas, and Paul Delfabbro. 2013. The impact of prolonged violent video-gaming on adolescent sleep: An experimental study. Journal of Sleep Research 22: 137–43.
Green, Matthew, Maria Kovacova, and Katarina Valaskova. 2020. Smartphone addiction risk, depression psychopathology, and social anxiety. Analysis and Metaphysics 19: 52–58.
Kliestik, Tomas, Joan Scott, Hussam Musa, and Petr Suler. 2020. Addictive smartphone behavior, anxiety symptom severity, and depressive stress. Analysis and Metaphysics 19: 45–51.
Lăzăroiu, George, Maria Kovacova, Anna Siekelova, and Jaromir Vrbka. 2020. Addictive behavior of problematic smartphone users: The relationship between depression, anxiety, and stress. Review of Contemporary Philosophy 19: 50–56.
Rikkers, Wavne, David Lawrence, Jennifer Hafekost, and Stephen R. Zubrick. 2016. Internet use and electronic gaming by children and adolescents with emotional and behavioural problems in Australia–results from the second Child and Adolescent Survey of Mental Health and Wellbeing. BMC Public Health 16: 399.
Kumar, Deepak, and Pradeep Kumar Choudhury. 2021. Do private schools really produce more learning than public schools in India? Accounting for student’s school absenteeism and the time spent on homework. International Journal of Educational Development 83: 102395.
Cooper, Harris, James J. Lindsay, and Barbara Nye. 2000. Homework in the home: How student, family, and parenting-style differences relate to the homework process. Contemporary Educational Psychology 25: 464–87.
Skinner, Burrhus Frederic. 1954. The science of learning and the art of teaching. Harvard Educational Review 24: 86–97.
Cooper, Harris, and Jeffrey C. Valentine. 2001. Using research to answer practical questions about homework. Educational Psychologist 36: 143–53.
Cooper, Harris, Jorgianne Civey Robinson, and Erika A. Patall. 2006. Does homework improve academic achievement? A synthesis of research, 1987–2003. Review of Educational Research 76: 1–62.
Chang, Charles B., Daniel Wall, Medha Tare, Ewa Golonka, and Karen Vatz. 2014. Relationships of attitudes toward homework and time spent on homework to course outcomes: The case of foreign language learning. Journal of Educational Psychology 106: 1049.
Jones, Kay, and Yvonne Harrison. 2001. Frontal lobe function, sleep loss and fragmented sleep. Sleep Medicine Reviews 5: 463–75.
Lo, June C., Ju Lynn Ong, Ruth L. F. Leong, Joshua J. Gooley, and Michael W. L. Chee. 2016. Cognitive performance, sleepiness, and mood in partially sleep deprived adolescents: The need for sleep study. Sleep 39: 687–98.
Lowe, Cassandra J., Adrian Safati, and Peter A. Hall. 2017. The neurocognitive consequences of sleep restriction: A meta-analytic review. Neuroscience & Biobehavioral Reviews 80: 586–604.
Dewald-Kaufmann, Julia, Frans Jeroen Oort, and Anne Marie Meijer. 2013. The effects of sleep extension on sleep and cognitive performance in adolescents with chronic sleep reduction: An experimental study. Sleep Medicine 14: 510–17.
Yang, Fan Nils, Weizhen Xie, and Ze Wang. 2022. Effects of sleep duration on neurocognitive development in early adolescents in the USA: A propensity score matched, longitudinal, observational study. The Lancet Child & Adolescent Health 6: 705–12.
Astill, Rebecca G., Kristiaan B. Van der Heijden, Marinus H. Van Ijzendoorn, and Eus J. W. Van Someren. 2012. Sleep, cognition, and behavioral problems in school-age children: A century of research meta-analyzed. Psychological Bulletin 138: 1109.
Kondo, Risa, Ichiro Miyano, Sangyoon Lee, Hiroyuki Shimada, and Hiroaki Kitaoka. 2021. Association between self-reported night sleep duration and cognitive function among older adults with intact global cognition. International Journal of Geriatric Psychiatry 36: 766–74.
Schmutte, Timothy, Shelby Harris, Ross Levin, Richard Zweig, Mindy Katz, and Richard Lipton. 2007. The relation between cognitive functioning and self-reported sleep complaints in nondemented older adults: Results from the Bronx aging study. Behavioral Sleep Medicine 5: 39–56.
Cagas, Jonathan Y., Marla Frances T. Mallari, Beatriz A. Torre, Mary-Grace D. P. Kang, Yves Y. Palad, Roselle M. Guisihan, Maria Isabela Aurellado, Chessa Sanchez-Pituk, John Guiller P. Realin, and Marvin Luis C. Sabado. 2022. Results from the Philippines’ 2022 report card on physical activity for children and adolescents. Journal of Exercise Science & Fitness 20: 382–90.
Widyastari, Dyah Anantalia, Pairoj Saonuam, Kornkanok Pongpradit, Narakorn Wongsingha, Panya Choolers, Sarocha Kesaro, Wittika Thangchan, Pott Pongpaopattanakul, Khwansupanat Phankasem, and Muhammadrorfee-E Musor. 2022. Results from the Thailand 2022 report card on physical activity for children and youth. Journal of Exercise Science & Fitness 20: 276–82.
Hillman, Charles H., Kirk I. Erickson, and Arthur F. Kramer. 2008. Be smart, exercise your heart: Exercise effects on brain and cognition. Nature Reviews Neuroscience 9: 58–65.
Tomporowski, Phillip D., Catherine L. Davis, Patricia H. Miller, and Jack A. Naglieri. 2008. Exercise and children’s intelligence, cognition, and academic achievement. Educational Psychology Review 20: 111–31.
Chaddock-Heyman, Laura, Charles H. Hillman, Neal J. Cohen, and Arthur F. Kramer. 2014. III. The importance of physical activity and aerobic fitness for cognitive control and memory in children. Monographs of the Society for Research in Child Development 79: 25–50.
Colditz, Graham A. 1999. Economic costs of obesity and inactivity. Medicine and Science in Sports and Exercise 31: S663–67.
Dwyer, Terry, Wayne E. Coonan, Donald R. Leitch, Basil S. Hetzel, and R. A. Baghurst. 1983. An investigation of the effects of daily physical activity on the health of primary school students in South Australia. International Journal of Epidemiology 12: 308–13.
Lloyd, Cynthia B., Monica Grant, and Amanda Ritchie. 2008. Gender differences in time use among adolescents in developing countries: Implications of rising school enrollment rates. Journal of Research on Adolescence 18: 99–120.
Tang, Sandra, and Megan E. Patrick. 2018. Technology and interactive social media use among 8th and 10th graders in the US and associations with homework and school grades. Computers in Human Behavior 86: 34–44.
Twenge, Jean M., and Gabrielle N. Martin. 2020. Gender differences in associations between digital media use and psychological well-being: Evidence from three large datasets. Journal of Adolescence 79: 91–102.
Tsai, Ling-Ling, and Sheng-Ping Li. 2004. Sleep patterns in college students: Gender and grade differences. Journal of Psychosomatic Research 56: 231–37.
Hilbrecht, Margo, Jiri Zuzanek, and Roger C. Mannell. 2008. Time use, time pressure and gendered behavior in early and late adolescence. Sex Roles 58: 342–57.
Moè, Angelica, Idit Katz, Rinat Cohen, and Marianna Alesi. 2020. Reducing homework stress by increasing adoption of need-supportive practices: Effects of an intervention with parents. Learning and Individual Differences 82: 101921.
Moe, Angelica, Anne C. Frenzel, Lik Au, and Jamie L. Taxer. 2021. Displayed enthusiasm attracts attention and improves recall. British Journal of Educational Psychology 91: 911–27.
Moè, Angelica. 2015. Perceived control mediates the relations between depressive symptoms and academic achievement in adolescence. The Spanish Journal of Psychology 18: E70.
Gao, Wenjuan, Siqing Ping, and Xinqiao Liu. 2020. Gender differences in depression, anxiety, and stress among college students: A longitudinal study from China. Journal of Affective Disorders 263: 292–300.
Liu, Xinqiao, Yu-Xin Guo, Wen-Jie Zhang, and Wen-Juan Gao. 2022b. Influencing factors, prediction and prevention of depression in college students: A literature review. World Journal of Psychiatry 12: 860.
Chen, Xu, Han Qi, Rui Liu, Yuan Feng, Wen Li, Mi Xiang, Teris Cheung, Todd Jackson, Gang Wang, and Yu-Tao Xiang. 2021. Depression, anxiety and associated factors among Chinese adolescents during the COVID-19 outbreak: A comparison of two cross-sectional studies. Translational Psychiatry 11: 148.
Lim, Shin-Il, and Sookyung Jeong. 2022. The Relationship between Korean Parents’ Smartphone Addiction and That of Their Children: The Mediating Effects of Children’s Depression and Social Withdrawal. International Journal of Environmental Research and Public Health 19: 5593.
Wang, Kaipeng, Dale Dagar Maglalang, Bongki Woo, Carson M. De Fries, Leslie K. Hasche, and Luis M. Falcón. 2022. Perceived discrimination and cognitive function among older Puerto Ricans in Boston: The mediating role of depression. International Journal of Geriatric Psychiatry 37.
Conradi, Henk Jan, Johan Ormel, and Peter De Jonge. 2011. Presence of individual (residual) symptoms during depressive episodes and periods of remission: A 3-year prospective study. Psychological Medicine 41: 1165–74.
Lee, Rico S. C., Daniel F. Hermens, Melanie A. Porter, and M. Antoinette Redoblado-Hodge. 2012. A meta-analysis of cognitive deficits in first-episode major depressive disorder. Journal of Affective Disorders 140: 113–24.
Wagner, Stefanie, Bettina Doering, Isabella Helmreich, Klaus Lieb, and André Tadić. 2012. A meta-analysis of executive dysfunctions in unipolar major depressive disorder without psychotic symptoms and their changes during antidepressant treatment. Acta Psychiatrica Scandinavica 125: 281–92.
Hollon, Steven D., Richard C. Shelton, Stephen Wisniewski, Diane Warden, Melanie M. Biggs, Edward S. Friedman, Mustafa Husain, David J. Kupfer, Andrew A. Nierenberg, and Timothy J. Petersen. 2006. Presenting characteristics of depressed outpatients as a function of recurrence: Preliminary findings from the STAR* D clinical trial. Journal of Psychiatric Research 40: 59–69.
Goulabchand, Radjiv, Elodie Castille, Sophie Navucet, Damien Etchecopar-Etchart, Aurélie Matos, Alexandre Maria, Laure Anne Gutierrez, Alain Le Quellec, Nicolas Menjot de Champfleur, and Audrey Gabelle. 2022. The interplay between cognition, depression, anxiety, and sleep in primary Sjogren’s Syndrome patients. Scientific Reports 12: 13176.
Grant, Merida M., Michael E. Thase, and John A. Sweeney. 2001. Cognitive disturbance in outpatient depressed younger adults: Evidence of modest impairment. Biological Psychiatry 50: 35–43.
Wang, Yi-Qun, Rui Li, Meng-Qi Zhang, Ze Zhang, Wei-Min Qu, and Zhi-Li Huang. 2015. The neurobiological mechanisms and treatments of REM sleep disturbances in depression. Current Neuropharmacology 13: 543–53.
Kross, Ethan, Philippe Verduyn, Emre Demiralp, Jiyoung Park, David Seungjae Lee, Natalie Lin, Holly Shablack, John Jonides, and Oscar Ybarra. 2013. Facebook use predicts declines in subjective well-being in young adults. PLoS ONE 8: e69841.
Oliveira, Júlia Meller Dias de, Luciana Butini, Patrícia Pauletto, Karyn Munyk Lehmkuhl, Cristine Miron Stefani, Michele Bolan, Eliete Guerra, Bruce Dick, Graziela De Luca Canto, and Carla Massignan. 2022. Mental health effects prevalence in children and adolescents during the COVID-19 pandemic: A systematic review. Worldviews on Evidence-Based Nursing 19: 130–37.
Valkenburg, Patti M., Adrian Meier, and Ine Beyens. 2022. Social media use and its impact on adolescent mental health: An umbrella review of the evidence. Current Opinion in Psychology 44: 58–68.
Field, Tiffany Diego, and Christopher Sanders. 2001. Adolescent depression and risk factors. Adolescence 36: 491–98.
Xiao, Pei, Kaiheng Zhu, Qi Liu, Xinyan Xie, Qi Jiang, Yanan Feng, Xiaoqian Wu, Jun Tang, and Ranran Song. 2022. Association between developmental dyslexia and anxiety/depressive symptoms among children in China: The chain mediating of time spent on homework and stress. Journal of Affective Disorders 297: 495–501.
Zhou, Tong, Rui Li, Yan Shi, Gang Tian, and Yan Yan. 2022. The associations between sleep duration, cognitive function, and depressive symptoms: An analysis of Chinese adolescents from China Family Panel Studies. Journal of Affective Disorders 319: 252–59.
Kvelde, Tasha, Mirjam Pijnappels, Kim Delbaere, Jacqueline C. T. Close, and Stephen R. Lord. 2010. Physiological and cognitive mediators for the association between self-reported depressed mood and impaired choice stepping reaction time in older people. Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences 65: 538–44.

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Subjects: Education & Educational Research

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Xiaojie Cao

Xinqiao Liu

View Times: 438

Update Date: 11 May 2023

Table of Contents

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1. Introduction

2. The Relationship between Time Use and Cognitive Achievement

3. The Mediating Role of Depression Symptoms

References