Evidence map›Paper›PMID 33805308›Full record

ArticleAnimals : an open access journal from MDPI2021

Human-Animal Interactions: Expressions of Wellbeing through a "Nature Language".

Rachel M Yerbury, Samantha J Lukey

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Classic Psychedelics and Human-Animal Relations.International journal of environmental research and public health · 2022
    Article
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

2 authors.

Rachel M Yerburyllawarra Health and Medical Research Institute, University of Wollongong, Wollongong, NSW 2522, Australia.ORCID 0000-0001-9498-5047
Samantha J LukeySchool of Health & Society, Faculty of the Arts, Social Sciences and the Humanities, University of Wollongong, Wollongong, NSW 2522, Australia.ORCID 0000-0001-7844-3539

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Human-animal interactions (HAIs) can be beneficial for humans in a number of ways, and interactions with wild animals may contribute to human mental wellbeing, partly through nature connectedness. This study applies the "Nature Interaction Pattern" approach (proposed by Kahn and colleagues) to characterize the structure of meaningful human engagement with nature and animals, and to consider the wellbeing outcomes. This qualitative, retrospective study uses open responses from 359 participants who describe how their wild animal encounters affected their nature connectedness. Thematic analysis explores five nature Interaction Patterns and four resulting Psychological Descriptions that occur in the portrayals of the marine animal encounters and these are described using representative quotes. Feelings of love, belonging, positive feelings, fulfillment and the gaining of perspective, were linked with the human-animal experience and the Interaction Patterns. These findings suggest that when people encounter and interact with animals in their natural environment, their mental health and wellbeing may be enhanced. Further, through connecting with nature and animals, reciprocity may occur, that is, when people connect with nature and animals, they can also give back. Within this interaction there becomes an entanglement of experiences thereby encouraging caring for nature and animals.

Indexed as

human–animal interactionshuman wellbeingnature interactionsreciprocitywildlife

Identifiers

PMID33805308
PMCPMC8067212

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.