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  4. Taking Mental Health & Well-Being to the Streets: An Exploratory Evaluation of In-Vehicle Interventions in the Wild
 
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Taking Mental Health & Well-Being to the Streets: An Exploratory Evaluation of In-Vehicle Interventions in the Wild

Series
CHI '21
Type
conference paper
Date Issued
2021
Author(s)
Koch, Kevin  
Tiefenbeck, Verena
Liu, Shu
Berger, Thomas
Fleisch, Elgar  
Wortmann, Felix  
Abstract
The increasing number of mental disorders worldwide calls for novel types of prevention measures. Given the number of commuters who spend a substantial amount of time on the road, the car offers an opportune environment. This paper presents the first in-vehicle intervention study affecting mental health and well-being on public roads. We designed and implemented two in-vehicle interventions based on proven psychotherapy interventions. Whereas the first intervention uses mindfulness exercises while driving, the second intervention induces positive emotions through music. Ten ordinary and healthy commuters completed 313 of these interventions on their daily drives over two months. We collected drivers’ immediate and post-driving feedback for each intervention and conducted interviews with the drivers after the end of the study. The results show that both interventions have improved drivers’ well-being. While the participants rated the music intervention very positively, the reception of the mindfulness intervention was more ambivalent.
Language
English
Keywords
Mindfulness
Field study
Well-being
Music
In-vehicle interventions
Natural driving
Psychology
HSG Classification
contribution to scientific community
HSG Profile Area
None
Publisher
Association for Computing Machinery
Publisher place
New York, NY, USA
Event Title
Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
Official URL
https://doi.org/10.1145/3411764.3446865
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/111118
Subject(s)

computer science

Division(s)

ITEM - Institute of T...

IWI - Institute of In...

Contact Email Address
kevin.koch@unisg.ch
Eprints ID
263222
File(s)
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Thumbnail Image

open.access

Name

3411764.3446865.pdf

Size

4.05 MB

Format

Adobe PDF

Checksum (MD5)

0a937d3f3266cea6a520ea97689ecb60

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