Stress, depression, and anxiety among undergraduate nursing students in the time of a pandemic
Bibliographic record
Abstract
INTRODUCTION: Emerging literature reports on the challenges faced by nursing students internationally during the pandemic as they continue their education. The aim of this mixed methods study was to examine stress, depression, and anxiety among undergraduate nursing students at a Canadian university during the pandemic. THEORETICAL FRAMEWORKS: Stress and coping and trauma theories informed this study. METHODS: Mixed methods included an online questionnaire composed of the Depression Anxiety Stress scales (DASS), sociodemographic data, and quality of life items with open-ended questions. RESULTS: Sample included 280 participants. Mean scores for depression and stress were in the mild level, for anxiety in the moderate level; 24 , 37 and 23 % of the sample had scores of severe or extremely severe for depression, anxiety, and stress respectively. Written comments reflected the impact on participants' relationships, motivation, struggles with remote learning, perceived heavy workloads, and impact on health and self-care, while some described positive experiences, including improved study habits. DISCUSSION: Uncertainty, isolation, sudden and ongoing changes with program delivery and a variety of psychosocial losses, helped to explain the distress many shared. The disconnect between reported levels of use of mental health services and the higher levels of mental distress raises the question of access to and use of these services. IMPLICATIONS FOR AN INTERNATIONAL AUDIENCE: The importance of developing and maintaining effective coping, including a support system, and committing to healthy self-care during challenging times was reinforced. CONCLUSIONS: This difficult time for nursing students emphasized the need to ensure attention to student well-being and mental health during their foundational educational experiences.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".