Do academic advising and levels of support affect nursing students' mental health? A cross‐sectional study
Bibliographic record
Abstract
AIM: The current study aimed to identify the association between social support, academic advising and mental health disorders among nursing students. BACKGROUND: Stress and workload can trigger multiple mental health disorders, especially for nursing students. Thus, academic advising and counselling help support students with academic and mental health problems. DESIGN: This cross-sectional study utilized online questionnaires in Egypt and Saudi Arabia. METHODS: Multidimensional Scale of Perceived Social Support (MSPSS), Patient Health Questionnaire (PHQ-4) and the Student Academic Advising and Counseling Survey (SAACS) were utilized to measure social support, depression and anxiety and evaluation of academic advising and counselling services, respectively. RESULTS: The study included 1134 nursing students (mean age of 20.3 years). Students with higher academic advising satisfaction were 37% less likely to experience depression (OR 0.63, 95% CI 0.46-0.85) and mental disorders (OR 0.68, 95% CI 0.50-0.94). Moderate family social support was associated with lower depression (OR 0.58, 95% CI 0.37-0.93) and mental disorders (OR 0.55, 95% CI 0.33-0.92). CONCLUSION: Academic advising and social support can mitigate mental health disorders among nursing students. These findings will help nurses and post-secondary providers develop strategies to support nursing students during difficult times.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".