ArticleInternational journal of environmental research and public health2021
Associations between Depression, Anxiety, Fatigue, and Learning Motivating Factors in e-Learning-Based Computer Programming Education.
Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 36 citations in OpenAlex.
- The Impact of Coursework Demand and Learning Engagement on Mental Fatigue in Online College Students.International journal of environmental research and public health · 2025Article
- Cross-sectional and longitudinal network analyses depict variations of symptom networks in depression patients across the lifespan: insight from a large-scale sample.BMC psychiatry · 2025Article
- Depressive symptoms and Learning Motivation among Chinese freshmen: a longitudinal study using random intercept cross-lagged panel model and the subgroup analysis of parental educational background.Frontiers in psychiatry · 2025Article
- COVID-19-Related Stressors and Psychophysical Health Conditions among Italian University Students: A Post Pandemic Insight.Healthcare (Basel, Switzerland) · 2024Article
- A cross-sectional study on the role of computer anxiety in students' online learning.Journal of advances in medical education & professionalism · 2024Article
- COVID-19 Pandemic: What We Have Learned on Stress, Technology Use, and Psychological Health Among University Students.Advances in experimental medicine and biology · 2024Review
- Evaluating the psychometric properties of the fatigue severity scale using item response theory.BMC psychology · 2023Article
- Undergraduates' Negative Emotion and Academic Procrastination During COVID-19: Life Autonomy as a Mediator and Sense of School Belonging as a Moderator.Psychology research and behavior management · 2023Article
- Student's perspectives, satisfaction and experiences with online and classroom learning during the COVID-19 pandemic: Findings and implications on blended learning.SAGE open medicine · 2023Article
- How growth mindset influences mathematics achievements: A study of Chinese middle school students.Frontiers in psychology · 2023Article
- Technostress and academic motivation: direct and indirect effects on university students' psychological health.Frontiers in psychology · 2023Article
- Key Predictive Factors in the Mental Health of Chinese University Students at Home and Abroad.International journal of environmental research and public health · 2022Article
- Perceived Past and Current COVID-19-Stressors, Coping Strategies and Psychological Health among University Students: A Mediated-Moderated Model.International journal of environmental research and public health · 2022Article
- Online or Blended Learning: the COVID-19 Pandemic and First-Year Medical Students' Academic Motivation.Medical science educator · 2022Article
- Article
- Depression in Final-Year Medical Students in Ho Chi Minh City, Vietnam: The Role of Career-Choice Motivation.Journal of medical education and curricular developmentArticle
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Quarantines imposed due to COVID-19 have forced the rapid implementation of e-learning, but also increased the rates of anxiety, depression, and fatigue, which relate to dramatically diminished e-learning motivation. Thus, it was deemed significant to identify e-learning motivating factors related to mental health. Furthermore, because computer programming skills are among the core competencies that professionals are expected to possess in the era of rapid technology development, it was also considered important to identify the factors relating to computer programming learning. Thus, this study applied the Learning Motivating Factors Questionnaire, the Patient Health Questionnaire-9 (PHQ-9), the Generalized Anxiety Disorder Scale-7 (GAD-7), and the Multidimensional Fatigue Inventory-20 (MFI-20) instruments. The sample consisted of 444 e-learners, including 189 computer programming e-learners. The results revealed that higher scores of individual attitude and expectation, challenging goals, clear direction, social pressure, and competition significantly varied across depression categories. The scores of challenging goals, and social pressure and competition, significantly varied across anxiety categories. The scores of individual attitude and expectation, challenging goals, and social pressure and competition significantly varied across general fatigue categories. In the group of computer programming e-learners: challenging goals predicted decreased anxiety; clear direction and challenging goals predicted decreased depression; individual attitude and expectation predicted diminished general fatigue; and challenging goals and punishment predicted diminished mental fatigue. Challenging goals statistically significantly predicted lower mental fatigue, and mental fatigue statistically significantly predicted depression and anxiety in both sample groups.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.