Commentary: Video games and stress: how stress appraisals and game content affect cardiovascular and emotion outcomes
Bibliographic record
Abstract
In their study, Porter and Goolkasian (2019) explored whether physiological and psychological stress response to playing video games depends on how the participant appraises the stressful situation.Based on previous literature, the authors predicted that threat appraisals (which can induce feelings of anxiety) would lead to increased blood pressure and higher negative emotion ratings relative to challenge appraisals (which can induce feelings of excitement). To test this, Porter and Goolkasian compared the effects of threat and challenge appraisal when participants played the fighting-game Mortal Kombat (MK) and the puzzle-game Tetris. Threat appraisal was induced through difficult performance-based instructions during gameplay (e.g., time constraints), whereas challenge appraisal was induced through encouraging instructions (e.g., reminders that overcoming a challenge is done through continued effort). As predicted, the authors found that threat appraisal indeed led to more increased negative emotion ratings relative to challenge appraisal. However, contrary to the authors' predictions, blood pressure did not differ between the two appraisal conditions; the authors concluded this finding indicates that video games lack the evaluative stressors, such as public speaking, that are important for inducing stress.Although the authors' conclusion is a possibility, we suspect this discrepancy may be a result of the authors' study design, which did not carefully consider individual variability in skill level relative to the difficulty of the game. Previous literature suggests that one's appraisal of a stressor is dependent on the perceived demands of a task. Although the authors frame their study and much of their interpretations after the Biopsychosocial Model of Challenge and Threat, we propose that Flow Theory may provide further insight into their findings (Csikszentmihalyi, 1990;Blascovitch and Tomaka, 1996;). Thus, our aim in this commentary is to examine the findings of Porter and Goolkasian within the framework of Flow Theory.According to Flow Theory, different combinations of skill level and perceived demand can lead to various feelings, from boredom and anxiety to relaxation and flow (Csikszentmihalyi, 1990). Although Porter and Goolkasian (2019) made efforts to perform manipulation checks which indicated, for example, that the threat appraisal task was more demanding than the challenge appraisal task, they did not account for individual variability in skill level relative to the difficulty setting of each game. The authors predetermined the difficulty of each game based on the performance of only a subset of pre-test participants. Additionally, although the authors used selfreported measures to assess participants for general video game experience, they did not assess their experience specifically with fighting (e.g., Mortal Kombat) or puzzle games (e.g. Tetris). There is some suggestion in the literature that different genres and consequently different game mechanics may have differential effects on the brain and require different behavioral responses; thus, skill level in one videogame genre may not generalize to another (Mondéjar et al., 2016).Given the importance of skill level in stress appraisal and possible differences in video game genres, it would be important to adjust each game's difficulty based on each participant's individual performance before introducing threat and challenge appraisal instructions. In other words, by using a single difficulty level, the authors were averaging the responses of individuals who may have had very different perceptions and feelings towards playing the two games. For instance, those participants who felt appropriately challenged given their skill level might have been in a state of flow, while those who felt the task was too difficult given their skill level might have been in a state of anxiety. This could have minimized an otherwise larger difference between the two appraisal groups.Additionally, although the results of playing Mortal Kombat were generally consistent with the literature, i.e., playing fighting games increases stress, the results of playing Tetris were not. That is, contrary to the literature, the authors did not find that playing a casual video game such as Tetris reduced physiological and psychological stress among their participants (Russoniello et al., 2009;Porter and Goolkasian, 2019;Pine et al., 2020;Desai et al., 2021). While the authors attribute this discrepancy to self-determination theory, we offer a complementary explanation using Flow Theory.On average, participants rated the difficulty of playing Tetris as 3.73 and 4.51 on a 5-point Likert scale in the challenge and threat conditions, respectively. Therefore, the difficulty setting of Tetris used in the study by Porter and Goolkasian may have been too high relative to the participants' skill level and led participants to feelings of anxiety or worry. In contrast to Porter and Goolkasian's study, other studies investigating the effects of playing casual video games on stress did not set a difficulty level for their participants. Participants played the video game at their leisure for a set duration, which according to Flow Theory, could have led participants to feelings of relaxation or control (Russoniello et al., 2009;Pine et al., 2020;Desai et al., 2021).Given the intersection of skill level and perceived demand (or challenge), future studies would benefit from stratifying participants based on skill levels to minimize variability. This variability can be further minimized by implementing a repeated-measures design in which the same participants undergo both the threat and challenge appraisal conditions; a repeated-measures design may be especially important to consider given the individual nature of stress appraisal. Lastly, studies of this type may benefit from considering Flow Theory in their study design, as this Flow Theory provides a framework to understanding the intersection of skill and challenge (Csikszentmihalyi, 1990;Michailidis et al. 2018). Nevertheless, the findings of Porter and Goolkasian (2019) provide important insight into the individual nature of stress and the complexities related to stress research.
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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 | 0.005 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.039 | 0.032 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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".