Hollandand Rathod

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Fatigue Effects on Simulator Driving in Older and Younger Adults: Comparing Complex with Monotonous Drives Carol Holland and Versha Rathod Psychology, Aston University, Birmingham, UK

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Fatigue effects on simulator driving in older and younger adults

Transcript of Hollandand Rathod

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Fatigue Effects on Simulator Driving in Older and Younger Adults: Comparing

Complex with Monotonous Drives

Carol Holland and Versha RathodPsychology, Aston University, Birmingham,

UK

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Maintaining safe mobility – a priority for an ageing society

A very significant part of maintaining independence is maintaining safe mobility, both as drivers and as pedestrians.

The percentage of adults aged over 70 in the UK with a valid driving licence has increased, from 39% (1998) to 59% (NTS 2011).

In the year 2000, Maycock (2000) projected that the age at which everyone had ceased driving would increase to 95 by 2020. This has been exceeded.

In 2010, there were 621 applications for licence renewals from people aged 95 to 101. However, numbers of drivers over 80 Killed or seriously injured did not increase between 2004 and 2010. (DfT Statistics)

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Older drivers’ habits have changed but they remain a relatively safe group of drivers.

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How do people stay as safe as they do?

The most important factors in older drivers staying as safe they largely do on the roads, even in the context of some impairments, are related to:

►ability to regulate their driving in accordance with any impairments (e.g. Nasvadi & Wister 2009), ►their awareness of their limitations, ►and their willingness to make adaptations to compensate for them (Holland & Rabbitt, 1992).

Providing guidance to older drivers on self-regulation is increasingly seen as a priority.

►internal (e.g. cognitive, vision, health, fatigue)►external (e.g., road categories, lighting)

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Self-regulation depends on good executive function

Attentional (executive) control :►ability to control or shift allocation of attention between tasks►Inhibition of processing of irrelevant information, ►updating ongoing tasks►flexibly planning solutions in the context of the changing environment or impairments.

Examples from health fields: Hall, et al., (2008) executive function contributes to relationships between intentions to perform healthy behaviours and actually doing so

Hall, et al., (2010) for those living with chronic illnesses that have heavy self-regulatory demands, survival time was longer for those with stronger executive function.

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Effects on Executive Function relevant to older drivers

► Executive function declines in older age (e.g. West, 1996)

► It is related to driving in older (Adrian et al, 2011; Parasuraman & Nestor, 1991) and younger drivers (Mantyla et al, 2009)

► Executive function, especially control of behaviour and ability to inhibit, is commonly impacted by complex prolonged demanding situations (van der Linden, et al., 2003)

► Effects are not necessarily on accuracy or speed of performance, but on factors such as planning or inhibition of inappropriate responses

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How do these factors work together? Looking at Fatigue.

This suggests that in the context of heavy driving demand, the impact of reduced executive function may be greater, therefore having a specific impact on older drivers, in a manner related to their executive function capabilities,

That is, fatigue effects may be different for older drivers.

this study sets out to examine this issue in older drivers.

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What might we expect to happen in fatigue situations?

► Chaparro et al. (2005): although older drivers may compensate by driving more slowly in a complex dual task condition, they did not make driving or secondary task errors.

► If such self-regulatory capacity becomes exhausted we would expect a reduction in the control exerted over driving speed with increasing duration of a complex drive.

Hancock and Desmond (2001) distinguish between ► active fatigue, resulting from demanding situations including overload of

attentional resources, and ► passive fatigue, resulting from low demand, or underload of attention.

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So…

This study compares the effects of passive versus active fatigue in older and younger drivers,

►monitoring the effects of perceived sleepiness,

►and examining the contribution of standardised measures of underlying executive function, in comparison with other cognitive and perceptual functions, to any fatigue effects in driving measures.

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AIMS

►The primary aim is to assess the relative and combined contributions of sleepiness, fatigue, and cognition on the ability to maintain safe driving in older adults, as follows:

►(i) Compare effects of monotonous versus complex demanding simulator driving on sleepiness for older and younger adults.

►(ii) Compare effects of monotonous versus complex demanding driving on change across the simulator drives in terms of driver performance measures (fatigue effect) for older and younger drivers,

►(iii) To examine the contribution of cognitive function indices to simulated driving performance indices and fatigue effects, contrasting control and adaptation performance measures (speed control) with errors and reaction time to hazards.

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Methods

Participants10 older (>60 years) mean age 65.38 years, SD 4.97) and 19 younger drivers (19-22 years) (21.74 years, SD=5.08). Cognitive assessmentsThe CANTAB battery:►processing speed (CRT) ►executive function (IED (task switching and inhibition) and Stockings of Cambridge (strategic planning), affective go/no go (inhibition) and rapid visual information processing ►Verbal recognition memory was also assessed. The Addenbrookes Cognitive examination, revised. (ACE-R)

Sleep questionnairesStanford Sleepiness scale (SSs) alertness, Karolinska Sleepiness scale (KSs)

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Driving simulator

The Aston Research Centre for Healthy Ageing (ARCHA) STISIM Drive simulator (Systems Technology Inc) was used to measure driving data and associated driving related paradigms:

(i)Hazard response (ii)speed limit exceedances(iii)Collisions (pedestrian, vehicle, off road)

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Copyright C.Holland, Aston University

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The scenarios - monotonous

Long monotonous drives (40mins),

14 hazards (0.35 per minute on average)

long periods of very little complexity (straight roads with plain “countryside”) and short periods of urban environment or traffic features in order to present comparable hazards.

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The scenarios - complex

► attentionally demanding complex drives (10 minutes),

► 11 hazards (1.1 per minute on average)

► through an all urban environment

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Procedure

Participants completed cognitive measures first, and then had a break.

They completed the sleepiness and alertness (Karolinska and Stanford scales) before and after each drive. Drive orders were counterbalanced

Participants were given a break between the drives in which they were given non-caffeine beverages and a light snack.

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Results

(i) Comparison of the effects of monotonous versus complex demanding simulator driving on sleepiness for older and younger adults.

KarolinskaBefore-after F(1,33) = 51.48, p<0.001, drive x before-after F(1,33) = 44.10, p<0.001, monotonous drive was more tiring than the complex drive overall. No age group effect, and no 3 way interaction between the type of drive and the before after effect with age.

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Results

Stanfordbefore-after the drives F(1,33) = 17.90, p<0.001; drive x before-after F(1,33) 14.45, p<0.001. Again, monotonous was more fatiguing

age group F(1,33) = 4.95, p<0.05.No 3 way interaction,

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Aim 2: Compare the effects of monotonous versus complex drives on driver performance measures.

Each drive was subdivided into two halves. Data were analysed by type of errors across the two drives. Errors were relatively rare except for speed exceedances

(i) speed controlYounger drivers made marginally more excursions over the speed limit than older drivers (F(1,28)=3.45, p<0.07).

Older drivers’ exceedances increased with duration in the complex drive (age group x drive interaction F(1,28)=5.11, p<0.05), but the three way interaction was not significant.

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Aim 2: Compare the effects of monotonous versus complex drives on driver performance measures

Reaction Times to matched Hazards

Significant effect for complex drive for old, but not for monotonous t(13) = 2.37 p<0.05.

For young, similar significant effect for both drives t (18) = 2.26, p<0.05 0

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Aim 3: Contribution of cognitive function to fatigue effects (in RTs,speed control, collisions)

Calculated fatigue effects (performance at end of the runs minus performance at the beginning).

Complex driveRT – no relationshipsSpeed control - RVP (hits) –sustained updating task,

- Go/no go task latency (inhibition processing)

Collisions - CRT

Monotonous driveRT – no relationshipsSpeed control - RVP false alarms (failure to inhibit)

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Conclusions

►Although RT to hazards was faster amongst older drivers than younger drivers overall, older adults showed more slowing in the complex scenario.

►The fatigue effect (difference between RTs at start and end of the drives) was greatest in the monotonous drive for the younger drivers.

►These findings together suggest that younger, less experienced drivers were more affected by a long monotonous drive and older drivers more affected by the complex drive.

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Conclusions cont…

►The fatigue effects (as opposed to actual performance) were predicted by inhibition and updating components of executive function, but not task switching or planning.

►This mainly affected control of driving such as speed control, rather than response to hazards

►Increase in collisions in the complex drive with fatigue was predicted by underlying processing speed (but there weren’t many collisions!)

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Take home point and limitations

We need to increase the numbers of older drivers in our sample.

simulator sickness in the longer drives a real issue.

Response to Hazards assessment needs fine tuning

But - Within high functioning experienced older drivers, complex, demanding drives are more fatiguing in terms of performance than long monotonous drives,

Variations in cognition, specifically inhibition and updating, are important predictors in complex conditions.

High demand may be exhausting self-regulation because of its effect on already potentially depleted EF, on which SR depends.

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Thank you!