Mental disorders are highly prevalent among university students. Distance-learning students are particularly burdened and have limited access to conventional university health services. Interventions for stress are sought after in distance learners and may help increase treatment coverage. Internet-based interventions have been shown to be effective in preventing and treating depression, but it remains unclear if interventions directed at academic stress also have this potential. The trial presented here investigates the effectiveness of an Internet- and App-based stress intervention in distance-learning students with elevated levels of depression. A sample of = 200 students of a large German distance university with elevated levels of depression [Center for Epidemiological Studies' Depression Scale (CES-D) ≥ 16] will be randomly assigned to either an Internet- and App-based stress management intervention group (IG) or a control group (CG) receiving an Internet-based psychoeducational program for academic stress. The IG consists of eight Internet-based sessions promoting stress management skills using cognitive-behavioral and problem-solving techniques. A mobile App will be employed to facilitate training transfer. Self-report data will be assessed at baseline (T0), post-treatment (T1; 7 weeks), and 3-month follow-up (T2). Potential moderators will be assessed at baseline. The primary outcome is depression (CES-D) post-treatment. Secondary outcomes include mental health outcomes, modifiable risk and protective factors, and academic outcomes. Data will be analyzed on an intention-to-treat principle along with sensitivity analyses to assess the robustness of findings. Additional health economic analyses will be conducted. Results will provide the basis to assess the acceptance and effectiveness of Internet-delivered stress interventions in distance-learning students with symptoms of depression. The study has been reviewed and approved by the University of Erlangen-Nuremberg ethics committee (Erlangen, Germany; 33_17 Bc). Results of the study will be disseminated through peer-reviewed publications. German Clinical Trial Registration (DRKS), identifier DRKS00011800.
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http://dx.doi.org/10.3389/fpsyt.2019.00361 | DOI Listing |
Nurs Health Sci
March 2025
School of Health, University of the Sunshine Coast, Petrie, Queensland, Australia.
The COVID-19 pandemic had immediate impact on nursing students enrolled in postgraduate and post-registration nursing courses. Some students were required to undertake additional clinical hours and place their studies on hold, while others had clinical experiences and face-to-face classes suspended, with online learning modes quickly mobilized. While there have been many reports on the impact and experience of these changes on undergraduate students, limited reports have focused on challenges for nursing students who were registered for practice following completion of their undergraduate studies, and were enrolled in higher degree, postgraduate education programs.
View Article and Find Full Text PDFBMJ Open
January 2025
Rockhampton Regional Clinical Unit, Medical School, Faculty of Medicine, The University of Queensland, Rockhampton, Queensland, Australia.
Objective: Community-engaged immersive rural experiences were limited during the COVID-19 pandemic when online learning was instigated across medical institutions globally. This study aimed to explore the impact of online learning on medical students' satisfaction levels and intentions to practice in a rural area after graduation.
Design, Setting And Participants: We conducted a natural quasi-experimental longitudinal retrospective cross-sectional study during 2011-2022 for all Australian domestic medical students who undertook a Rural and Remote Medicine (RRM) placement at the University of Queensland.
PLoS One
January 2025
Nanjing University of Science and Technology, Jiangsu, China.
Student performance is crucial for addressing learning process problems and is also an important factor in measuring learning outcomes. The ability to improve educational systems using data knowledge has driven the development of the field of educational data mining research. Here, this paper proposes a machine learning method for the prediction of student performance based on online learning.
View Article and Find Full Text PDFJ Educ Eval Health Prof
January 2025
School of Pharmacy, Monash University Malaysia, Bandar Sunway, Malaysia.
Purpose: This study aimed to explore pharmacy students' perceptions of remote flipped classrooms in Malaysia, focusing on their learning experiences and identifying areas for potential improvement to inform future educational strategies.
Methods: A qualitative approach was employed, utilizing inductive thematic analysis. Twenty Bachelor of Pharmacy students (18 women, 2 men; age range, 19-24 years) from Monash University participated in 8 focus group discussions over 2 rounds during the coronavirus disease 2019 pandemic (2020-2021).
Med Biol Eng Comput
January 2025
Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.
Performing automatic and standardized 4D TEE segmentation and mitral valve analysis is challenging due to the limitations of echocardiography and the scarcity of manually annotated 4D images. This work proposes a semi-supervised training strategy using pseudo labelling for MV segmentation in 4D TEE; it employs a Teacher-Student framework to ensure reliable pseudo-label generation. 120 4D TEE recordings from 60 candidates for MV repair are used.
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