| 1. |
- Thorslund, Birgitta, 1976-, et al.
(author)
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Cognitive workload and visual behavior in elderly drivers with hearing loss
- 2014
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In: European Transport Research Review. - : Springer Science and Business Media LLC. - 1867-0717 .- 1866-8887. ; 6:4, s. 377-385
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Journal article (peer-reviewed)abstract
- The purpose was to examine eye tracking data and compare visual behavior in individuals with normal hearing (NH) and with moderate hearing loss (HL) during two types of driving conditions: normal driving and driving while performing a secondary task.Methods24 participants with HL and 24 with NH were exposed to normal driving and to driving with a secondary task (observation and recall of 4 visually displayed letters). Eye movement behavior was assessed during normal driving by the following performance indicators: number of glances away from the road; mean duration of glances away from the road; maximum duration of glances away from the road; and percentage of time looking at the road. During driving with the secondary task, eye movement data were assessed in terms of number of glances to the secondary task display, mean duration of glances to the secondary task display, and maximum duration of glances to the secondary task display. The secondary task performance was assessed as well, counting the number of correct letters, the number of skipped letters, and the number of correct letters ignoring order.ResultsWhile driving with the secondary task, drivers with HL looked twice as often in the rear-view mirror than during normal driving and twice as often as drivers with NH regardless of condition. During secondary task, the HL group looked away from the road more frequently but for shorter durations than the NH group. Drivers with HL had fewer correct letters and more skipped letters than drivers with NH.
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| 2. |
- Lidestam, Björn, 1968-, et al.
(author)
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Speed perception affected by field of view : Energy-based versus rhythm-based processing
- 2019
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In: Transportation Research Part F. - : Elsevier. - 1369-8478 .- 1873-5517. ; 65, s. 227-241
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Journal article (peer-reviewed)abstract
- Two experiments were carried out to test speed perception dependency on field of view (FoV), virtual road markings (VRMs), and presentation orders. The primary purpose was to examine how the extent of the optic flow (foremost peripherally–vertically) informs the driver about egospeed. A second purpose was to examine different task demands and stimulus characteristics supporting rhythm-based versus energy-based processing. A third purpose was to examine speed changes indicative of changes in motion sensitivity. Participants were tested in a car simulator, with FoV resembling low front-door windows, and with VRMs inside the car. Three main results were found. Larger FoV, both horizontally and peripherally–vertically, significantly reduced participants' speed, as did VRMs. Delineator posts and road center lines were used for participants' rhythm-based processing, when the task was to drive at target speeds. Rich motion-flow cues presented initially resulted in lower egospeed in subsequent conditions with relatively less motion-flow cues. The practical implication is that non-iconic, naturalistic and intuitive interfaces can effectively instill spontaneous speed adaptation in drivers.
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| 3. |
- Timpka, Toomas, 1957-, et al.
(author)
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Intentions to perform non-pharmaceutical protective behaviors during influenza outbreaks in Sweden : A cross-sectional study following a mass vaccination campaign
- 2014
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In: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 9:3, s. e91060-
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Journal article (peer-reviewed)abstract
- Failure to incorporate the beliefs and attitudes of the public into theoretical models of preparedness has been identified as a weakness in strategies to mitigate infectious disease outbreaks. We administered a cross-sectional telephone survey to a representative sample (n = 443) of the Swedish adult population to examine whether self-reported intentions to improve personal hygiene and increase social distancing during influenza outbreaks could be explained by trust in official information, self-reported health (SF-8), sociodemographic factors, and determinants postulated in protection motivation theory, namely threat appraisal and coping appraisal. The interviewees were asked to make their appraisals for two scenarios: a) an influenza with low case fatality and mild lifestyle impact; b) severe influenza with high case fatality and serious disturbances of societal functions. Every second respondent (50.0%) reported high trust in official information about influenza. The proportion that reported intentions to take deliberate actions to improve personal hygiene during outbreaks ranged between 45–85%, while less than 25% said that they intended to increase social distancing. Multiple logistic regression models with coping appraisal as the explanatory factor most frequently contributing to the explanation of the variance in intentions showed strong discriminatory performance for staying home while not ill (mild outbreaks: Area under the curve [AUC] 0.85 (95% confidence interval 0.82;0.89), severe outbreaks AUC 0.82 (95% CI 0.77;0.85)) and acceptable performance with regard to avoiding public transportation (AUC 0.78 (0.74;0.82), AUC 0.77 (0.72;0.82)), using handwash products (AUC 0.70 (0.65;0.75), AUC 0.76 (0.71;0.80)), and frequently washing hands (AUC 0.71 (0.66;0.76), AUC 0.75 (0.71;0.80)). We conclude that coping appraisal was the explanatory factor most frequently included in statistical models explaining self-reported intentions to carry out non-pharmaceutical health actions in the Swedish outlined context, and that variations in threat appraisal played a smaller role in these models despite scientific uncertainties surrounding a recent mass vaccination campaign.
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| 4. |
- Timpka, Toomas, et al.
(author)
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Performance of eHealth data sources in local influenza surveillance : a 5-year open cohort study
- 2014
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In: Journal of Medical Internet Research. - : JMIR Publications Inc.. - 1438-8871. ; 16:4, s. 216-225
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Journal article (peer-reviewed)abstract
- BACKGROUND: There is abundant global interest in using syndromic data from population-wide health information systems-referred to as eHealth resources-to improve infectious disease surveillance. Recently, the necessity for these systems to achieve two potentially conflicting requirements has been emphasized. First, they must be evidence-based; second, they must be adjusted for the diversity of populations, lifestyles, and environments.OBJECTIVE: The primary objective was to examine correlations between data from Google Flu Trends (GFT), computer-supported telenursing centers, health service websites, and influenza case rates during seasonal and pandemic influenza outbreaks. The secondary objective was to investigate associations between eHealth data, media coverage, and the interaction between circulating influenza strain(s) and the age-related population immunity.METHODS: An open cohort design was used for a five-year study in a Swedish county (population 427,000). Syndromic eHealth data were collected from GFT, telenursing call centers, and local health service website visits at page level. Data on mass media coverage of influenza was collected from the major regional newspaper. The performance of eHealth data in surveillance was measured by correlation effect size and time lag to clinically diagnosed influenza cases.RESULTS: Local media coverage data and influenza case rates showed correlations with large effect sizes only for the influenza A (A) pH1N1 outbreak in 2009 (r=.74, 95% CI .42-.90; P<.001) and the severe seasonal A H3N2 outbreak in 2011-2012 (r=.79, 95% CI .42-.93; P=.001), with media coverage preceding case rates with one week. Correlations between GFT and influenza case data showed large effect sizes for all outbreaks, the largest being the seasonal A H3N2 outbreak in 2008-2009 (r=.96, 95% CI .88-.99; P<.001). The preceding time lag decreased from two weeks during the first outbreaks to one week from the 2009 A pH1N1 pandemic. Telenursing data and influenza case data showed correlations with large effect sizes for all outbreaks after the seasonal B and A H1 outbreak in 2007-2008, with a time lag decreasing from two weeks for the seasonal A H3N2 outbreak in 2008-2009 (r=.95, 95% CI .82-.98; P<.001) to none for the A p H1N1 outbreak in 2009 (r=.84, 95% CI .62-.94; P<.001). Large effect sizes were also observed between website visits and influenza case data.CONCLUSIONS: Correlations between the eHealth data and influenza case rates in a Swedish county showed large effect sizes throughout a five-year period, while the time lag between signals in eHealth data and influenza rates changed. Further research is needed on analytic methods for adjusting eHealth surveillance systems to shifts in media coverage and to variations in age-group related immunity between virus strains. The results can be used to inform the development of alert-generating eHealth surveillance systems that can be subject for prospective evaluations in routine public health practice.
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| 5. |
- Blissing, Björn, 1978-, et al.
(author)
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Driver behavior in mixed and virtual reality : A comparative study
- 2017
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In: Transportation Research Part F. - : Elsevier Ltd. - 1369-8478 .- 1873-5517.
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Journal article (peer-reviewed)abstract
- This paper presents a comparative study of driving behavior when using different virtual reality modes. Test subjects were exposed to mixed, virtual, and real reality using a head mounted display capable of video see-through, while performing a simple driving task. The driving behavior was quantified in steering and acceleration/deceleration activities, divided into local and global components. There was a distinct effect of wearing a head mounted display, which affected all measured variables. Results show that average speed was the most significant difference between mixed and virtual reality, while the steering behavior was consistent between modes. All subjects but one were able to successfully complete the driving task, suggesting that virtual driving could be a potential complement to driving simulators.
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| 6. |
- Kircher, Katja, 1973-, et al.
(author)
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Design and analysis of semi-controlled studies
- 2016
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In: Transportation Research Part F. - : Elsevier. - 1369-8478 .- 1873-5517.
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Journal article (peer-reviewed)abstract
- Semi-controlled studies provide a hybrid approach in between controlled experiments and naturalistic driving studies. As in controlled experiments, the researcher can assign participants to groups, select the route and define the tasks, but the participants are given more freedom when it comes to if, when, where and how to perform the tasks. Increased flexibility makes it possible to investigate how drivers use tactical behaviour to accommodate task execution. The disadvantage is decreased control and more complicated analyses.The main objective of this paper is to discuss how to analyse data obtained in semi-controlled studies.The analysis of data from a semi-controlled study include three types of variables:variables that describe the experimental designvariables that describe the tactical choices of the participantsoperational variables such as speed, lateral position or glance behaviourTo analyse the three types of variables a two-step procedure is suggested. First, the tactical indicators are analysed with regard to the experimental design. Second, the operational indicators are analysed and the tactical indicators are used to divide participants into sub-populations.The semi-controlled design does not need any new statistical procedures to be developed. It is more important that the analysis conditions on the initial properties and not on structures that happen to occur during the experiment, like where the participant chose to do a certain task.We recommend to use the semi-controlled study method when investigating questions involving adaptive and compensatory behaviour on the tactical level. It is especially useful if causal relationships are of interest, if the data collection should be accelerated in comparison to naturalistic studies, and if certain geographical locations definitely should be included.
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| 7. |
- Timpka, Toomas, et al.
(author)
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Age as a determinant for dissemination of seasonal and pandemic influenza : An open cohort study of influenza outbreaks in Östergötland County, Sweden
- 2012
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In: PLOS ONE. - San Francisco : Public Library of Science. - 1932-6203. ; 7:2, s. e31746-
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Journal article (peer-reviewed)abstract
- An understanding of the occurrence and comparative timing of influenza infections in different age groups is important for developing community response and disease control measures. This study uses data from a Scandinavian county (population 427,000) to investigate whether age was a determinant for being diagnosed with influenza 2005–2010 and to examine if age was associated with case timing during outbreaks. Aggregated demographic data were collected from Statistics Sweden, while influenza case data were collected from a county-wide electronic health record system. A logistic regression analysis was used to explore whether case risk was associated with age and outbreak. An analysis of variance was used to explore whether day for diagnosis was also associated to age and outbreak. The clinical case data were validated against case data from microbiological laboratories during one control year. The proportion of cases from the age groups 10–19 (p<0.001) and 20–29 years old (p<0.01) were found to be larger during the A pH1N1 outbreak in 2009 than during the seasonal outbreaks. An interaction between age and outbreak was observed (p<0.001) indicating a difference in age effects between circulating virus types; this interaction persisted for seasonal outbreaks only (p<0.001). The outbreaks also differed regarding when the age groups received their diagnosis (p<0.001). A post-hoc analysis showed a tendency for the young age groups, in particular the group 10–19 year olds, led outbreaks with influenza type A H1 circulating, while A H3N2 outbreaks displayed little variations in timing. The validation analysis showed a strong correlation (r = 0.625; p<0.001) between the recorded numbers of clinically and microbiologically defined influenza cases. Our findings demonstrate the complexity of age effects underlying the emergence of local influenza outbreaks. Disentangling these effects on the causal pathways will require an integrated information infrastructure for data collection and repeated studies of well-defined communities.
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