Evidence map›Paper›PMID 36361139›Full record

ArticleInternational journal of environmental research and public health2022

The Novelty Appraisal of the Feeling of Risk in Vehicles.

Meng Zhang, Meike Jipp, Klas Ihme

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. 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

3 authors.

Meng ZhangInstitute of Transportation Systems, German Aerospace Center (DLR), 12489 Berlin, Germany.ORCID 0000-0003-1655-764X
Meike JippInstitute of Transport Research, German Aerospace Center (DLR), 12489 Berlin, Germany.
Klas IhmeInstitute of Transportation Systems, German Aerospace Center (DLR), 38108 Braunschweig, Germany.ORCID 0000-0002-7911-3512

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nowadays, vehicle assistance systems may assess the risks of the traffic situation with the help of advanced sensor technology and optimized algorithms. However, the passengers' feelings of risk in the vehicle have been mostly neglected. According to the Component Process Model of emotions, during the feeling of risk, novelty is one of the relevant event appraisals leading to particular physiological and facial responses. In order to identify whether or not indicators for novelty appraisal may be used for detecting the feeling of risk of vehicle occupants, we investigated physiological responses and facial expressions of individuals experiencing the feeling of risk with different levels of novelty. This secondary analysis of an earlier simulator study revealed that pupil diameter amplitude, skin conductance level changes, and changes in and amplitude of activity in facial expressions (the inner and outer brow raiser, brow lowerer, upper lid raiser and lid tightener) were correlated with the reduction in the novelty, suggesting that they could indicate the novelty of the feeling of risk of vehicle occupants. Hence, this research provides evidence for the novelty appraisal of the feeling of risk. Furthermore, it informs research on affect-aware systems to identify and reduce the feeling of risk of vehicle occupants in order to help to keep trust in automated vehicles high.

Indexed as

EmotionsFacial ExpressionAccidents, TrafficAlgorithmsFaceHumansComponent Process Modelfacial expressionfeeling of riskin vehiclesnoveltyphysiological responses

Identifiers

PMID36361139
PMCPMC9658280

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.