Evidence map›Paper›PMID 37644577›Full record

ArticleBMC psychology2023

'Pawing' uncertainty! how dogs attenuate the impact of daily hassles at work on uncertainty.

Ana Junça-Silva

Abstract read
In one paragraph

Article in BMC psychology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
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  3. 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

1 author.

Ana Junça-SilvaInstituto Universitário de Lisboa (ISCTE-IUL), Lisboa, Portugal. analjsilva@gmail.com.

Funding

Fundação para a Ciência e a Tecnologia UIDB/00315/2020
6 · The paper itself

Abstract

purposeThis study relied on the integrative model of uncertainty tolerance to delineate an argument proposing that daily hassles trigger uncertainty, and this influences adaptive performance. Furthermore, relying on the "furr-recovery method" -where interactions with dogs allow dog owners to recover from negative situations or job demands - this study tested whether having a dog would moderate the relationship between daily hassles and uncertainty. METHODOLOGY: To test this proposed model, daily data during ten working days was gathered with a sample of white-collar workers who were teleworking (N = 233 × 10 = 2,330).

findingsMultilevel results showed that daily hassles influenced adaptive performance via perceived uncertainty. However, the relationship between daily hassles and uncertainty was conditional on the ownership of a dog, in such a way that the relationship became weaker for those who had dogs. That is, those who did not have dogs had increased levels of uncertainty after daily hassles when compared to those who had dogs. PRACTICAL IMPLICATIONS: Managers may consider the adoption of pet-friendly work practices (for instance, telework - working from home allow employees to work nearby and interact with their dogs during worktime) as dogs appear to have a beneficial effect to help employees effectively cope with daily hassles and reduce their uncertain reactions. ORIGINALITY: This study advances knowledge regarding the pawing-effect (the reduced uncertainty to daily hassles on dog owners) on employees' uncertainty to daily hassles and opens new venues for research regarding their role in work-related outcomes. Further, future research could examine how human-dog interactions or the quality of their relationship may benefit owners and explore the benefits of bringing dogs to work periodically.

Indexed as

Human-Animal InteractionTeleworkingUncertaintyAnimalsDogsHumansAdaptive performanceDaily hasslesDogs at workHuman-animal interactionsThe health benefits of dogsUncertainty

Identifiers

PMID37644577
PMCPMC10466751

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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.