Exploring factors associated with individual differences in the mental health of university students during the COVID-19 pandemic
Bibliographic record
Abstract
Rates of anxiety and depression are known to be high in university students, and the COVID-19 pandemic appears to have exacerbated this situation slightly, especially in females. Research has consistently identified alexithymia, sensory processing sensitivity (SPS), anxiety sensitivity (AS), and childhood emotional abuse as risk factors for poor mental health outcomes. Given that linkages have also been reported between these variables, it is difficult to ascertain the unique weight of each factor in the overall prediction of mental health. The current dissertation sought to fill this gap in the literature by investigating how these and other potentially relevant variables relate to depression and anxiety in young adults engaged in widely differing levels of physical activity. In Study 1, 410 university students completed an online survey assessing current mood, alexithymia, SPS, AS, childhood emotional abuse, physical activity, and pandemic-related impacts. Over half of the participants reported moderate to extremely severe symptoms of anxiety and depression. Alexithymia, SPS, AS, and childhood emotional abuse each accounted for unique variance in prediction of both anxiety and depression. Males scored significantly lower than females on SPS and AS, but male sex emerged as an additional risk factor for depression when these variables were controlled for. Several secondary analyses were carried out using the data from the 309 female participants to gain further insights into their risk profile. The results suggested that risk for exercise dependence negatively predicted depression, and that being an athlete positively predicted anxiety, when effects related to the aforementioned personality and experiential variables were controlled. Finally, two follow-up studies were conducted involving a subgroup of the females who took part in the original investigation. The results of these studies suggested that, in females, problems exercising self control when demands of emotion and attentional processing overlap accounted for unique variance in prediction of anxiety and that body uneasiness accounted for unique variance in prediction of both anxiety and depression, when holding variance accounted for by personality and experiential variables constant. The results from this basic research provide a more nuanced understanding of the influence of co-occurring alexithymia, SPS, AS, and childhood emotional abuse on emotional processing during the COVID-19 pandemic. They also have important implications for the development and implementation of individualized treatments for common mental disorders, particularly in females.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".