The Endemic Stage of COVID-19: Mental Health and Wellbeing Among University Students
Bibliographic record
Abstract
This study was intended to examine a range of independent/predictor variables that may impact the independent/outcome variables of stress, anxiety, depression, and wellbeing. The predictor variables examined in this study are workload, loneliness, social support, physical health, compassion, financial stress, sense of meaning in life, and substance use. This study employed a correlational design and was conducted at Mount Royal University during Fall 2022 and Winter 2023. Survey ratings were collected from 384 students from the participant pool of students taking an introductory psychology course. Participants completed a range of surveys measuring stress, anxiety, depression, and wellbeing, as well as being examined in this study are workload, loneliness, social support, physical health, compassion, financial stress, sense of meaning in life, and substance use. Two correlation analyses were conducted between the variables. The study revealed several significant correlations between psychological constructs and well-being indicators. This study contributes valuable insights into the factors influencing mental health and well-being in a post-pandemic/endemic world. Future research could explore these relationships and develop targeted interventions to improve mental health outcomes in vulnerable populations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".