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Record W4399330961 · doi:10.32381/jpr.2024.19.01.10

Pet Attachment, Empathy and Mindful Self Care among Young Adults

2024· article· en· W4399330961 on OpenAlexaboutno aff
Sachika S Bharadwaj, Dr Archana Bhat Kallahalla

Bibliographic record

VenueJOURNAL OF PSYCHOSOCIAL RESEARCH · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEmpathyPsychologyContext (archaeology)Clinical psychologyPositive correlationNegative correlationDevelopmental psychologySocial psychologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

The study investigated the relationship between pet attachment, empathy and mindful self-care in young adult owners of pet dogs (n=226, 151 female) aged 18-45 years. The Lexington Attachment to Pets Scale (LAPS), Toronto Empathy Questionnaire (TEQ) and Mindful Self-Care Scale (MSCS-Brief) were used. Results showed that while women have significantly higher pet attachment and empathy, there were no gender differences in mindful self-care. In terms of magnitude of correlation, the correlation between pet attachment and empathy is higher in men than in women, and the correlation between empathy and mindful self-care was found to be significantly higher in women than in men. The relationship between pet attachment and mindful self-care is found to be similar in men and women. Further research is needed to study the potential of a causal relationship between pet attachment and the development of empathy and self-care practices, particularly in the Indian context.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.455
Teacher spread0.424 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2024
Admission routes1
Has abstractyes

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