Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 3, 2024
BMC Medical Education, Journal Year: 2024, Volume and Issue: 24(1)
Published: Dec. 18, 2024
Abstract Background Prior studies found that dental students are affected by various stressors during their studies. Those can exert adverse effects on (mental) health. Our study addresses the lack of qualitative data students’ perspectives exploring perceived and resources among interventions suggested them. The results our contribute to development better preventive measures interventions. Methods In total, 57 enrolled at a school in Germany participated seven focus groups summer semester 2019 (May July). Discussions were facilitated using topic guide, collection was conducted until thematic saturation. All discussions audio-recorded, transcribed content-analyzed MAXQDA. Results Key emerging related organization program, digitalization, practical tasks, examination system, work/study environment social interactions. Resources encompassed, e.g., good organization, courses, patient work valued feedback. Interventions included regular meetings enhance collaboration, improved communication between staff students, central coordination unit, fixed evaluation criteria integration physical exercises physiotherapy program prevent neck back pain. Conclusions Known for new aspects (e.g., concurring exams or obligatory brands) emerged from data. use digital learning platforms, training improvement processes. Additional research, explore teaching other stakeholders is necessary gain more insights into conditions ways reduce stress students.
Language: Английский
Citations
2
Journal of Public Health, Journal Year: 2024, Volume and Issue: 46(3), P. e430 - e438
Published: June 23, 2024
This study was designed to assess stress levels and related factors during the coronavirus disease 2019 (COVID-19) epidemic among individuals in centralized quarantine camps Wenzhou, China.
Language: Английский
Citations
1
Published: June 27, 2024
Qualitative data is invaluable, yet its analysis very time-consuming. To prevent the loss of valuable information and to streamline coding process for developing assigning inductive categories, we introduce LLM-Assisted Inductive Categorization (LAIC), a novel method categorizing text responses using Large Language Model (LLM). In two pre-registered studies, tested Generative Pre-trained Transformer (GPT) models that are commonly used in ChatGPT (GPT-3.5 Turbo GPT-4o) across three temperature settings (0, 0.5, 1) with 10 repetitions each (120 runs total). Outputs were evaluated based on established qualitative research criteria (credibility, dependability, confirmability, transferability, transparency). Two human coders also generated categories assigned accordingly comparison. Our findings demonstrate both GPT highly effective even outperforming agreement rates. Overall, GPT-4o achieved best results (e.g., better explanations higher agreement) recommended category formation assignment setting 0 repetitions. This approach saves significant time resources while enhancing quality. Instructions Python scripts applying our new technique freely available under CC-BY 4.0 International license: https://osf.io/h4dux/
Language: Английский
Citations
1
BMC Public Health, Journal Year: 2024, Volume and Issue: 24(1)
Published: Aug. 10, 2024
Healthcare professionals are at increased risk of experiencing occupational stress and its detrimental stress-sequalae. Relevant theories that contribute to the subjective experience have been identified, such as model effort-reward imbalance (ERI) concept leader-member exchange (LMX). The aim this study was examine how perceived importance social relationships work moderates relationship between LMX ERI.
Language: Английский
Citations
1
Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 3, 2024
Citations
0