A network approach to understanding distance learners’ experience of stress and mental distress whilst studying

• Published in: International Journal of Educational Technology in Higher Education Vol. 20; no. 1; pp. 27 - 19
• Main Authors: Samra, Rajvinder, França, Alex Bacadini, Lucassen, Mathijs F. G., Waterhouse, Philippa
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.12.2023; BioMed Central, Ltd; Springer Nature B.V; SpringerOpen
• Subjects: Academic Achievement; Anxiety; Anxiety Disorders; College Students; Colleges & universities; Computer Appl. in Social and Behavioral Sciences; Computer Science; Computers and Education; Depression (Psychology); Distance Education; Distance learning; Dropout Prevention; Dropout Rate; Educational Practices; Educational Researchers; Educational Technology; Grade Point Average; Graduate Students; Health Needs; Health Services; Higher Education; Humanities; Information Systems Applications (incl.Internet); Law; Mental depression; Mental Disorders; Mental distress; Mental Health; Mental Health Programs; Meta Analysis; National Surveys; Network analysis; Outcomes of Education; Research Article; Statistics for Social Sciences; Stress; Student Surveys; Students; Study Habits; Study skills; Undergraduate Students; Undergraduate study; University students; Well Being; World Problems; Distance education; Students; Mental distress; Network analysis; Stress
• ISSN: 2365-9440; 2365-9440
• DOI: 10.1186/s41239-023-00397-3

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.