ArticleInternational journal of educational technology in higher education2023
A network approach to understanding distance learners' experience of stress and mental distress whilst studying.
Article in International journal of educational technology in higher education, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Network analysis of depression, anxiety, and stress symptoms in Brazilian nursing workers.Revista brasileira de enfermagem · 2026Article
- Stress, Anxiety, and Depression as Psychological Distress Among College and Undergraduate Students: A Scoping Review of Reviews Guided by the Socio-Ecological Model.Healthcare (Basel, Switzerland) · 2025Review
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4 authors.
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Abstract
Research has shown that learners' stress and mental distress are linked to poorer academic outcomes. A better understanding of stress and mental distress experiences during study could foster more nuanced course and intervention design which additionally teaches learners how to navigate through to protect their academic performance. The current study draws on data collected via validated self-reported questionnaires completed by final year undergraduate students (n = 318) at a large distance education university. We examined how common features of stress, depression and anxiety link to each other using a network analysis of reported symptoms. The results included findings demonstrating the symptoms with the greatest relative importance to the network. Specifically, these included the stress symptom 'I found it difficult to relax' and the depression symptom 'I was unable to become enthusiastic about anything'. The findings could help institutions design interventions that directly correspond to common features of students' stress and distress experiences.
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