Examining the Effects of Nature and Animal Videos on Stress
Bibliographic record
Abstract
Animals are often prohibited in public areas, which limit opportunities for people to experience improvements in well-being from their presence. Visual representations of animals, such as videos, may serve as an alternative intervention to the physical presence of live animals. University students, in particular, may benefit from virtual animal-assisted interventions, given that they report high rates of stress, and opportunities to interact with live animals at tertiary institutions are generally limited. This study recruited 200 participants from introductory psychology courses through a research participant pool at Toronto Metropolitan University in Canada. Following exposure to a mental arithmetic stressor that was 3 minutes in length, participants were randomly assigned to watch a 3-minute video that featured either a dog, puppy, nature, or blank screen. In light of previous research that found that infantile facial features elicit greater attention and positive affect among viewers compared with mature facial features, this study hypothesized that the video of the puppy would be the most effective at enhancing wellbeing. Data were collected through the Depression Anxiety Stress Scales (DASS-21), Social Phobia Inventory (SPIN), Positive and Negative Affect Schedule (PANAS), Visual Analog Scale (VAS), and the Subjective Appraisal of Video Affects (SAVA). The results revealed that the puppy video produced significantly higher scores of happiness relative to the nature and control videos (F(8.54,557.94) = 3.29, p < 0.001, ηp2 = 0.05). Additionally, participants reported that the puppy video was significantly more effective at inducing relaxation compared with the control video (F(3,199) = 7.58, p < 0.001, ηp2 = 0.10). These results suggest that watching a video of a puppy can be useful to improve wellbeing among university students. This study offers novel contributions to the limited literature examining the impact of visual representations of infant animals on stress.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".