Evidence map›Paper›PMID 42614682›Full record

ArticleFrontiers in psychiatry2026

Cross-species conversations: the development of the AURAL-Pet coding system to capture how people talk to pets in daily life.

Dara S Jonkoski, Nicole M Lorig, Molly C Delzio, Alyssa Klensin, Abigail Marsters, Huashi Li, Amanda M Bernal, Matthias R Mehl, Kerri E Rodriguez, Emily E Bray

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Dara S JonkoskiUniversity of Arizona, College of Veterinary Medicine, Tucson, AZ, United States.
Nicole M LorigUniversity of Arizona, College of Veterinary Medicine, Tucson, AZ, United States.
Molly C DelzioUniversity of Arizona, College of Veterinary Medicine, Tucson, AZ, United States.
Alyssa KlensinUniversity of Arizona, Department of Psychology, College of Science, Tucson, AZ, United States.
Abigail MarstersUniversity of Arizona, Department of Psychology, College of Science, Tucson, AZ, United States.
Huashi LiUniversity of Arizona, Center for Biomedical Informatics and Biostatistics, Statistics Consulting Laboratory, Tucson, AZ, United States.
Amanda M BernalUniversity of Arizona, Department of Psychology, College of Science, Tucson, AZ, United States.
Matthias R MehlUniversity of Arizona, Department of Psychology, College of Science, Tucson, AZ, United States.
Kerri E RodriguezUniversity of Arizona, College of Veterinary Medicine, Tucson, AZ, United States.
Emily E BrayUniversity of Arizona, College of Veterinary Medicine, Tucson, AZ, United States.

Funding

Atlanta Clinical and Translational Science Institute (ACTSI) RenewalUL1TR000454 · NCATS · EMORY UNIVERSITY · PI STEPHENS, DAVID S · 2012 to 2016
$25.8M
Mechanisms of MeditationR01AT004698 · NCCIH · UNIVERSITY OF ARIZONA · PI RAISON, CHARLES · 2009 to 2013
$3.1M
Sleep and Divorce: Identifying Bidirectional Vulnerability and ResilienceR01HD069498 · NICHD · UNIVERSITY OF ARIZONA · PI SBARRA, DAVID A · 2011 to 2014
$1.3M
NCATS NIH HHS UL1 TR000454NCCIH NIH HHS R01 AT004698NICHD NIH HHS R01 HD069498
6 · The paper itself

Abstract

While pets are a well-established fixture in many households, how owners perceive their pets' roles can range from distant housemates to casual companions to trusted confidantes. At the same time, findings relating to the impact pets have on human health and wellbeing are mixed. A potential explanation for these disparate effects is the naturally occurring variation in daily human-pet interactions and relationship quality. However, there is a lack of methodological approaches that can accurately quantify naturalistic interactions between people and their pets with limited bias. To address this gap, we developed the Auditory-based Understanding of Relational Animal-directed Language (AURAL-Pet) coding system to apply to ambient sound clips of human-pet interactions as captured by the Electronically Activated Recorder (EAR). By consulting existing literature, subject matter experts, and an archival database of EAR audio clips, we used an iterative process to develop and refine the coding system. In the final version, we retained 30 variables, 27 binary and 3 qualitative, which extract aspects of pet-focused activities, as well as the quality and content of human speech directed towards pets. We found that 22 out of 23 original AURAL-Pet binary variables had acceptable inter-coder agreement (ICC ≥.70). We then applied AURAL-Pet to four archival EAR studies, totaling N = 5,072 ambient audio clips containing evidence of pet presence across N = 240 participants, to better understand how frequently participants demonstrated different human-pet interactions across gender- and age-diverse samples. We found that individual participants' interactions with pets varied extensively across all variables, and that certain variables were more heterogeneous across genders and ages than others. In summary, this coding tool provides a novel, reliable method for quantifying daily human-pet interactions across diverse populations. Future work applying AURAL-Pet to naturalistic audio clips would be well-positioned to explore how differences in human-animal interactions may impact both human and animal health and wellbeing.

Indexed as

coding systemecological momentary assessmentethogramhuman-animal interactioninter-rater reliabilitypet-directed speech

Identifiers

PMID42614682
PMCPMC13482966

What OpenQuestion holds

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Registered trials

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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.