Dataset Information

Does rush hour see a rush of emotions? Driver mood in conditions likely to exhibit congestion.

ABSTRACT: Polls show that a large portion of the public considers traffic congestion to be a problem and believes a number of policy interventions would ameliorate it. However, most of the public rejects new taxes and fees to fund these improvements. This may be because of a disconnect between the public's stated antipathy towards congestion and the recalled emotional costs congestion imposes. To explore this, we use a large and representative sample drawn from the American Time Use Survey to examine how drivers experience four emotions (happiness, sadness, stress, and fatigue), plus a constructed composite mood variable, when they travel in peak periods, in large cities, in city centers, and in combinations of these. We also explore the interactions between these indicators and trip duration. We find evidence that drivers in the largest cities at the very peak of rush hour (5:00pm-6:00pm) are in a less positive mood, presumably because of congestion. However, this effect, though significant, is small, and we find no significant results using broader definitions of the peak period. In all, our findings suggest that congestion's impact on drivers as a group is quite limited. This may help explain why the public's attitude toward painful financial trade-offs to address congestion is lukewarm.

SUBMITTER: Morris EA

PROVIDER: S-EPMC4876728 | biostudies-other | 2016 Sep

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Does rush hour see a rush of emotions? Driver mood in conditions likely to exhibit congestion.

Morris Eric A EA Hirsch Jana A JA

Travel behaviour & society 20160901

Polls show that a large portion of the public considers traffic congestion to be a problem and believes a number of policy interventions would ameliorate it. However, most of the public rejects new taxes and fees to fund these improvements. This may be because of a disconnect between the public's stated antipathy towards congestion and the recalled emotional costs congestion imposes. To explore this, we use a large and representative sample drawn from the American Time Use Survey to examine how ...[more]

PMID: 27231669

Similar Datasets

Project description:BackgroundMood and anxiety are widely associated with physical conditions, but research and treatment are complicated by their overlap, clinical heterogeneity, and manifestation on a spectrum rather than as discrete disorders. In contrast to previous work relying on threshold-level disorders, we examined the association between empirically-derived profiles of mood and anxiety syndromes with physical conditions in a nationally-representative sample of US adolescents.MethodsParticipants were 2,911 adolescents (aged 13-18) from the National Comorbidity Survey-Adolescent Supplement who provided information on physical conditions and reported at least one lifetime mood-anxiety 'syndrome' based on direct interviews with the Composite International Diagnostic Interview Version 3.0. Mood-anxiety syndromes reflected 3-level ratings from subthreshold to severe distress/impairment, and subtyped mood episodes. Stepwise latent profile analysis identified mood-anxiety profiles and tested associations with physical conditions.ResultsThree mood-anxiety profiles were identified: "Mood-GAD" (25.6%)-non-atypical depression, mania, generalized anxiety; "Atypical-Panic" (11.3%)-atypical depression, panic; and "Reference" (63.1%)-lower mood and anxiety except specific phobia. Headaches were more prevalent in Mood-GAD and Atypical-Panic than Reference (47.9%, 50.1%, and 37.7%, respectively; p=0.011). Heart problems were more common in Mood-GAD than Atypical-Panic (7.4% v 2.2%, p=0.004) and Reference, with back/neck pain more prevalent in Mood-GAD than Reference (22.5% v 15.3%, p=0.016).LimitationsBroad categories of physical conditions without information on specific diagnoses; replication regarding specificity is recommended.ConclusionsHeart problems and pain-related conditions were differentially associated with specific mood-anxiety profiles. Subtyping depression and anxiety-inclusive of subthreshold syndromes-and their patterns of clustering may facilitate etiologic and intervention work in multimorbidity.

Dataset Information

Does rush hour see a rush of emotions? Driver mood in conditions likely to exhibit congestion.

Publications

Does rush hour see a rush of emotions? Driver mood in conditions likely to exhibit congestion.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets