Digital Games and Mindfulness Apps: Comparison of Effects on Post Work Recovery
Bibliographic record
Abstract
Background Engagement in activities that promote the dissipation of work stress is essential for post work recovery and consequently for well-being. Previous research suggests that activities that are immersive, active, and engaging are especially effective at promoting recovery. Therefore, digital games may be able to promote recovery, but little is known about how they compare with other popular mobile activities, such as mindfulness apps that are specifically designed to support well-being. Objective The aim of this study was to investigate and compare the effectiveness of a digital game and mindfulness app in promoting post work recovery, first in a laboratory setting and then in a field study. Methods Study 1 was a laboratory experiment (n=45) in which participants’ need for recovery was induced by a work task, before undertaking 1 of 3 interventions: a digital game (Block! Hexa Puzzle), a mindfulness app (Headspace), or a nonmedia control with a fidget spinner (a physical toy). Recovery in the form of how energized participants felt (energetic arousal) was compared before and after the intervention and how recovered participants felt (recovery experience) was compared across the conditions. Study 2 was a field study with working professionals (n=20), for which participants either played the digital game or used the mindfulness app once they arrived home after work for a period of 5 working days. Measures of energetic arousal were taken before and after the intervention, and the recovery experience was measured after the intervention along with measures of enjoyment and job strain. Results A 3×2 mixed analysis of variance identified that, in study 1, the digital game condition increased energetic arousal (indicative of improved recovery) whereas the other 2 conditions decreased energetic arousal (F2,42=3.76; P=.03). However, there were no differences between the conditions in recovery experience (F2,42=.01; P=.99). In study 2, multilevel model comparisons identified that neither the intervention nor day of the week had a significant main effect on how energized participants felt. However, for those in the digital game condition, daily recovery experience increased during the course of the study, whereas for those in the mindfulness condition, it decreased (F1,18=9.97; P=.01). Follow-up interviews with participants identified 3 core themes: detachment and restoration, fluctuations and differences, and routine and scheduling. Conclusions This study suggests that digital games may be effective in promoting post work recovery in laboratory contexts (study 1) and in the real world, although the effect in this case may be cumulative rather than instant (study 2).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".