ArticleAnimal cognition2021
Using a new video rating tool to crowd-source analysis of behavioural reaction to stimuli.
Article in Animal cognition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Investigating the capabilities of large vision language models in dog emotion recognition.Scientific reports · 2025Article
- Exploring the impact of a brief positive experience on dogs' performance and stress resilience during a learning task.PloS one · 2025Article
- Using a cognitive model to understand crowdsourced data from citizen scientists.Behavior research methods · 2024Article
- The Power Is in the Word-Do Laypeople Interpret Descriptors of Dog Emotional States Correctly?Animals : an open access journal from MDPI · 2023Article
- Uncertainty in experts' judgments exposes the vulnerability of research reporting anecdotes on animals' cognitive abilities.Scientific reports · 2021Article
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 3 countries.
Funding
Abstract
Quantifying the intensity of animals' reaction to stimuli is notoriously difficult as classic unidimensional measures of responses such as latency or duration of looking can fail to capture the overall strength of behavioural responses. More holistic rating can be useful but have the inherent risks of subjective bias and lack of repeatability. Here, we explored whether crowdsourcing could be used to efficiently and reliably overcome these potential flaws. A total of 396 participants watched online videos of dogs reacting to auditory stimuli and provided 23,248 ratings of the strength of the dogs' responses from zero (default) to 100 using an online survey form. We found that raters achieved very high inter-rater reliability across multiple datasets (although their responses were affected by their sex, age, and attitude towards animals) and that as few as 10 raters could be used to achieve a reliable result. A linear mixed model applied to PCA components of behaviours discovered that the dogs' facial expressions and head orientation influenced the strength of behaviour ratings the most. Further linear mixed models showed that that strength of behaviour ratings was moderately correlated to the duration of dogs' reactions but not to dogs' reaction latency (from the stimulus onset). This suggests that observers' ratings captured consistent dimensions of animals' responses that are not fully represented by more classic unidimensional metrics. Finally, we report that overall participants strongly enjoyed the experience. Thus, we suggest that using crowdsourcing can offer a useful, repeatable tool to assess behavioural intensity in experimental or observational studies where unidimensional coding may miss nuance, or where coding multiple dimensions may be too time-consuming.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.