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Record W4411857176 · doi:10.1038/s41598-025-00872-z

An experimental study focusing on mindfulness to capture how our contacts with dogs can promote human well-being

2025· article· en· W4411857176 on OpenAlexafffund
Catherine E. Amiot, Mylène Quervel-Chaumette, Christophe Gagné, Brock Bastian

Bibliographic record

VenueScientific Reports · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversité du Québec à Montréal
FundersSocial Sciences and Humanities Research Council of CanadaInstituto de Física de Cantabria
KeywordsMindfulnessComputer scienceMedicinePsychologyPsychotherapist

Abstract

fetched live from OpenAlex

Pet ownership per se has not been reliably associated with increased human well-being and health. Furthermore, the specific psychological mechanisms and behavioral dynamics through which the presence of pets could yield higher human wellness remain under-investigated. Conducted among dog owners and their dogs, the current experiment investigates if a specific psychological factor - i.e., mindfulness - activated in the presence of one's dog increases dog owners' psychological well-being. The study also explores which affiliative and synchronization behaviors manifested within the human-dog dyad are associated with higher human well-being. A within-participants design was employed among 52 dog owners and their dogs. The mindfulness condition was found to have a positive impact on dog owners' well-being. This condition also generated more affiliative and synchronization behaviors among both owners and their dogs on a majority of behaviors, with some of these behaviors (i.e., frequency the dog initiated contact with their owner; duration the owner communicated with their dog) mediating the associations between the mindfulness induction and the well-being outcomes. These findings confirm the importance of investigating the psychological and behavioral factors which, when activated and manifested within human-dog relationships, promote human wellness as well as interspecies interactivity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.723

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.342
Teacher spread0.327 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2025
Admission routes2
Has abstractyes

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