The Relationship Between Gaming Behaviours, Emotional Vulnerability, And Coping During The Covid-19 Pandemic
Bibliographic record
Abstract
The onset of the COVID-19 pandemic led to significant changes in the way people interacted, functioned, and coped with life stressors (Restubog et al., 2020; Rettie & Daniels, 2021). With government guidelines, uncertainty, and isolation, individuals sought new coping methods, including video games (Entertainment Software Association, 2020; King et al., 2020; López-Cabarcos et al., 2020). This coping strategy may have been particularly prevalent among individuals with emotional vulnerabilities (i.e., symptoms of depression and anxiety), or personality traits such as anxiety sensitivity or hopelessness. As such, there is a need to better understand how emotional vulnerability relates to coping-motivated gaming during the pandemic. This dissertation presents two longitudinal studies exploring emotional vulnerability, gaming behaviours, and coping motivations for gaming during the COVID-19 pandemic. The first study involved 332 Canadian gamers (Mage= 33.79, SDage=8.92; 60.8% male, 39.2% female) and examined the influence of emotional vulnerability on coping-motivated gaming and gaming-related problems during the first six months of the pandemic (April – October 2020). The results supported the hypotheses, that higher levels of emotional vulnerability predicted excessive time spent gaming and gaming-related problems, with coping motives playing a mediating role. The second study, conducted between July 2021 and January 2022, involved 1001 American gamers (Mage= 38.43, SDage= 12.11; 46.8% male, 53.2% female) and aimed to understand how internalizing personality traits, namely anxiety sensitivity and hopelessness influenced video gaming engagement. There was an observed predictive relationship between anxiety sensitivity and subsequent time spent gaming, through coping motives. Overall, these studies provide valuable insights into emotional vulnerability, gaming behaviours, and coping motives during the pandemic. They emphasize the importance of coping motives in these relationships and offer an opportunity to explore how symptoms of depression or anxiety and related personality traits, may influence the use of gaming during the pandemic.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".