Evidence map›Paper›PMID 37525269›Full record

ReviewTropical diseases, travel medicine and vaccines2023

Robots in travel clinics: building on tourism's use of technology and robots for infection control during a pandemic.

Irmgard L Bauer

Abstract readReview
In one paragraph

Review in Tropical diseases, travel medicine and vaccines, 2023. 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

1 author.

Irmgard L BauerCollege of Healthcare Sciences, Academy - Tropical Health and Medicine, James Cook University, Townsville, QLD, 4811, Australia. Irmgard.Bauer@jcu.edu.au.ORCID http://orcid.org/0000-0002-8305-3700

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The arrival of COVID-19 impacted every aspect of life around the world. The virus, whose spread was facilitated overwhelmingly by people's close contact at home and by travelling, devastated the tourism, hospitality, and transportation industry. Economic survival depended largely on demonstrating to authorities and potential travellers the strict adherence to infection control measures. Fortunately, long before the pandemic, the industry had already employed digital technology, artificial intelligence, and service robots, not to keep the world safe, but to either bridge staff shortages or save costs, reduce waiting times, streamline administration, complete unattractive, tedious, or physical tasks, or use technology as marketing gimmicks. With COVID-19, offering social distancing and touchless service was an easy step by extending quickly what was already there. The question arose: could travellers' acceptance of technology and robots for infection control be useful in travel medicine? COVID-19 fostered the rapid and increased acceptance of touchless technology relating to all things travel. The public's expectations regarding hygiene, health and safety, and risk of infection have changed and may stay with us long after the pandemic is 'the new normal', or a new one approaches. This insight, combined with the current experience with robots in health and medicine, is useful in exploring how robots could assist travel medicine practice. However, several aspects need to be considered in terms of type of robot, tasks required, and the public's positive or negative attitudes towards robots to avoid known pitfalls. To meet the crucial infection control measures of social distancing and touch avoidance, the use of robots in travel medicine may not only be readily accepted but expected, and implications for management, practice, and research need to be considered.

Indexed as

Artificial intelligenceAutomationCOVID-19Human-robot interactionMedical technologyRoboticsTravel medicine

Identifiers

PMID37525269
PMCPMC10391865

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.