directed attention and the restorative potential of nature and positive affect

Running Head: ATTENTION, NATURE, AND AFFECT 1

Directed Attention and the Restorative Potential of Nature and Positive Affect

Sara Fechtelkotter

Submitted to the College of Liberal Arts

University of Minnesota

In partial fulfillment of the requirements

For the degree

Bachelor of Arts

summa cum laude


Abstract

In this experiment, we assess the effects of exposure to highly pleasant versus

comparatively unpleasant (boring or non-descript) nature, urban, and mixed scenes on

physiological responses and performance on a subsequent cognitive attention measure. The

objectives of this study are to: 1) determine the proportional restorative power of nature (i.e.,

how much nature is enough--are mixed scenes, containing an admixture of natural and urban

elements somewhat restorative?) and 2) ascertain the comparative restorative strength of setting

context versus emotional valence. We found no significant physiological or cognitive differences

among the six conditions (nature pleasant, nature unpleasant, mixed pleasant, mixed unpleasant,

urban pleasant, and urban unpleasant) and also no main effect of setting (nature, urban, and

mixed) or valence (pleasant and unpleasant). Nonetheless, this study provides several unique and

novel methods and considerations for future research, particularly underscoring the need for a

more modulated and ecologically valid approach to the classification of environmental settings

(because many commonly encountered settings are neither purely urban nor purely natural), and

pioneering the use of perceptual saliency maps to equate for bottom-up visual salience variations

between different settings. A more thorough understanding of the relationship among directed

attention, nature, and positive affect has both theoretical and practical significance. Insight into

the validity of the Attention Restoration Theory and the psycho-physiological theory regarding

the psychological effects of exposure to natural settings will improve our understanding of

human cognition and functioning as well as inform the decisions of municipalities and

individuals.


Directed Attention and the Restorative Potential of Nature and Positive Affect

According to the U.S. Census Bureau, 80 percent of the United States population lived in

urban areas in 2000 versus only 28 percent in 1910 (Hobbes & Stoops, 2002). The rise in

urbanization is not surprising considering the copious benefits available in cities, such as more

job opportunities, reduced transportation costs, a variety of entertainment, and better access to

important services (e.g., medical services). However, the benefits of urbanization are likely

accompanied by detriments.

Most people are aware of the environmental degradation associated with urbanization. To

take one illustrative example, urban planners now take into account the amount of impervious

surfaces, such as asphalt, that may prevent water from percolating into the ground, thereby also

reducing groundwater levels, and contributing to water quality degradation as storm-water runoff

accumulates chemicals, debris, sediments, and other pollutants (Rose & Peters, 2001; Booth &

Jackson, 1997). Yet, while these and other environmental issues that may be posed by the

concentration of large numbers of people (and vehicles) into cities are important considerations,

negative consequences may even extend to the cognitive abilities of those responsible for

urbanization, people. Simply living, viewing, and acting within urban environments may deplete

our directed attention capacity.

Intuitively, people escape the cognitive demands of urban life and typically seek refuge in

more natural areas during their vacation time. Twin Cities residents practically migrate in herds

“up north” or “to the lake” during the summer. These Twin Cities residents and other urban

dwellers may be onto something. Empirical studies indicate that spending time in natural areas

may restore directed attention capacity, but how much nature is enough? Is a four-hour drive up


to the Boundary Waters Canoe Area necessary, or can a stroll down a tree-lined residential street

suffice? Additionally, how much of apparent psychological benefit from such long or brief

excursions derives from the context itself––that is, natural versus urban settings, and how much,

instead, derives from the typical affective valence of those contexts—their relative pleasantness

versus unpleasantness?

To begin to answer these questions, in this experiment we assess the effects of exposure

to highly pleasant versus comparatively unpleasant (boring or non-descript) nature, urban, and

mixed scenes on physiological responses and performance on a subsequent cognitive attention

measure. Furthermore, in an effort to evade potential bottom-up perceptual saliency differences

for the different settings, the average perceptual saliency of the scenes was assessed and equated

across all six conditions (nature pleasant, nature unpleasant, mixed pleasant, mixed unpleasant,

urban pleasant, and urban unpleasant).

Background

Directed attention is an intentionally driven process engaging the brain’s top-down

control mechanisms in order to attend to specific stimuli and to inhibit distractions (Desimone &

Duncan, 1995; Kaplan, 1995). Due to the tremendous and varied amount of stimuli often present

within an urban environment, more attention is required and the demand for inhibition of

distracting stimuli is frequently greater. For example, imagine trying to cross a busy street. You

must attend to the stoplights and to approaching traffic while ignoring the airplane flying

overhead and the cell phone ringing in your pocket. The stoplights and approaching traffic may

not be the most captivating stimuli, yet you must attend to them in order to successfully cross the

street. Completing numerous and immediately successive goal-oriented tasks requiring directed

attention, such as crossing the street, and then negotiating through an unending stream of


pedestrians and cars, poses the potential for attentional fatigue (Cohen & Spacapan, 1978;

Kaplan & Kaplan, 1982).

Attentional fatigue, like many other detriments associated with urbanization, may be

assuaged with the appropriate reactions. Urban foresters plant trees along water bodies to

increase infiltration, which in turn improves water quality and reduces storm-water. Songbirds

modify their songs in response to increased anthropogenic noise in the city with nightingales

simply singing louder in the presence of traffic noise (Brumm, 2004) and robins shifting their

singing activity towards the night in areas that are noisier during the day (Fuller, Warren, &

Gaston, 2007). Like the songbirds, people may be able to restore their directed attention capacity

with a simple behavioral change. According to Attention Restoration Theory (ART), people may

be able to restore directed attention capacity by visiting or viewing natural environments.

ART is founded on the distinction between voluntary and involuntary attention first made

by William James in 1892. Voluntary attention, now referred to as directed attention, is an

effortful or “willful” process required for almost all goal-oriented tasks. Since directed attention

is effortful, the potential for fatigue exists. Conversely, involuntary attention, or fascination, is

stimulus-driven and requires no (or little) conscious effort. In involuntary attention, the innate

salience of the stimuli commands attention through a bottom-up process and is not typically

susceptible to fatigue.

Empirical evidence supports the distinction between involuntary and directed attention.

In one study, alcohol only affected directed attention as measured with a delayed ocular response

task, but did not affect involuntary attention as measured with a saccadic interference task

(Abroms, Gottlob, & Filmore, 2006). Considering the characteristics of involuntary and directed

attention, ART proposes that time spent in environments containing fascinating stimuli that


primarily employ bottom-up, stimulus-driven attention would allow the directed attention

mechanisms of the brain to relax and rejuvenate (Kaplan, 1995; Kaplan, 2001).

Natural areas with inherently interesting wildlife, rustic hiking paths, smooth lakes,

supple streams, and towering trees evoke involuntary attention and may provide the perfect

opportunity to conserve and possibly even restore directed attention. The restorative potential of

natural environments is demonstrated in numerous studies. In one naturalistic study, university

students living in dormitory rooms that had a window with a ‘natural’ view of trees, grass, and so

on performed better on a directed attention task than did students with a ‘built’ view comprised

of streets, sidewalks, etc. (Tennessen & Cimprich, 1995). Experimental studies have pointed to

similar benefits. Viewing pictures of natural scenes (e.g., ocean coves in Nova Scotia) versus

urban scenes (e.g., streets of Detroit and Chicago) for a period of 10 minutes significantly

improved performance on a controlled processing measure (backward digit span) as well as on a

component of an attention test (the Attention Network Test) that draws upon executive attention

(Berto, Baroni, Zainaghi, & Bettella, 2010).

While natural environments appear to be the most obvious place to relax and rejuvenate,

restorative attributes are not limited to natural environments. Even though natural environments

are often contrasted with urban environments in empirical studies, some studies have

demonstrated that well-designed, attractive urban environments can have an equally restorative

impact (e.g., Karmanov & Hamel, 2008). According to Attention Restoration Theory, restorative

environments, natural or urban, possess four properties, briefly designated as: fascination, being

away, extent, and compatibility (Kaplan, 1995).

Fascination, as mentioned earlier, evokes involuntary attention, but the intensity of

attention may still vary along a “soft-hard” dimension. Soft fascination is characterized by


moderate intensity, is typically focused on aesthetically pleasing stimuli, and allows for

reflection. Colorful sunsets and other natural environments are scenes that may provide soft

fascination (Herzog, Black, Fountaine, & Knotts, 1997). Hard fascination, on the other hand, is

intense, creating attentional capture, and generally prohibits reflection. Sporting events such as

basketball generally produce hard fascination.

Being away occurs when one is able to withdraw from the routine activities contributing

to attentional fatigue either physically or mentally. Extent refers to the level of content and

structure. The environment must provide adequate detail and a logical structure so as to allow

one to think and perceive the environment as a “whole other world” and fully engage the mind

(Kaplan, 1995). Lastly, compatibility is achieved when the environment and the individual’s

goals align. Compatible environments are able to provide the information necessary and

opportunities needed to realize those goals.

City skylines after dark are one type of urban environment that may contain all four of

these restorative characteristics. In one study, participants rated Natural Scenes as more pleasant

than the Day Skylines; however the Night skylines and Natural Scenes were rated equally

pleasant (Nasar & Terzano, 2010). A follow-up study involved a more active task asking

participants to choose the most desirable scene and participants actually chose the Night Skylines

more frequently than the Natural Scenes. The reasons provided by participants for their choice of

Night Skylines differed from those given for choosing Natural Scenes. Participants chose night

skylines for their excitement and Natural Scenes for their calming quality (Nasar & Terzano,

2010).

Night Skylines fulfill the four criteria for restorative environments. City nightlife

associated with the Night Skylines may be more compatible with participants’ desire for


entertainment and excitement. Well-known skylines (e.g., New York, Washington D.C., etc)

were not used in order to avoid familiarity effects, but the novel city views may have also led to

a sense of extent, seeming like a “whole new world.” Additionally, it might be speculated that

commutes to work in the city likely occur during the day-time, so viewing the skyline at night

may provide a sufficient sense of being away. The complexity of lights randomly left on within

different rooms throughout buildings likely produce soft fascination.

While ART and the four characteristics of restorative environments provide a compelling

argument, Ulrich (1983) proposes an alternative psycho-physiological theory. Ulrich suggests

that environments have the capacity to influence affective states with positive emotions resulting

in stress-reduction and negative emotions activating a process of stress mobilization. Stress

mobilization prepares the cardiovascular, musculoskeletal, and neuroendocrine systems to cope

with the current stressful situation. While stress mobilization is a valuable tool, the process is

strenuous and can lead to fatigue. Conversely, low-stress environments can improve emotional

states (e.g., reducing fear or anger) and physiological states (e.g., reducing heart rate and blood

pressure).

Empirical evidence suggests that natural environments’ stress-reductive capacity is

superior to urban environments. In one study, participants’ cardiac inter-beat interval (IBI) was

measured before, during, and after the viewing of a video depicting either an urban or natural

environment (Laumann, Garling, & Stormark, 2003). The nature group had longer mean IBI (i.e.,

lower heart rate) measured as the difference from baseline than the urban group while watching

the video. Interestingly, before the video, both the nature and urban groups reacted faster to

validly versus invalidly cued targets in the Posner’s attention-orienting task, whereas after

viewing the video, the difference in reaction disappeared for the nature group while the urban


group continued to respond faster to the validly versus invalidly cued targets. Reductions in

automatic arousal (i.e., IBI) experienced during the viewing of the video induced less spatially

selective attention in the nature group than the urban group.

The reduction in spatially selective attention exhibited corresponds with the hypothesis

that increases in arousal narrow attention and elicits increased spatially selective attention

(Easterbrook, 1959). While empirical evidence suggests that natural areas have superior stress-

reductive capacity and restorative qualities (Ulrich, Simons, Losito, Fiorito, Miles, & Zelson,

1991; Van den Berg, Koole, & van der Wulp, 2003), an intermediate factor or confounding

variable may be operating, such as emotional valence. Considering that a number of studies show

that people prefer natural areas to urban areas (Palmer, 1978; Bernaldez & Parra, 1979), it is no

surprise that natural areas are likely more restorative when applying the psycho-physiological

theory, but as Karmanov and Hamel (2008) point out, well-designed, attractive urban

environments can be equally restorative.

When considering ART and the psycho-physiological theory, it is important to note that

the two theories are not necessarily mutually exclusive. According to Hartig, Mang, and Evans

(1991), both theories can “run simultaneously and to some degree independently of one another,

with different outcomes emerging at different times” as demonstrated by the “large degree of

congruency between the psychological measures of restorativeness and the three physiological

responses [electromyography (EMG), electrocephalography (EEG), and blood volume pulse

(BVP)]” (Chang, Hammitt, Chen, Machnik, & Su, 2008).

A clear consensus is struck when discussing the restorative value of natural

environments. Both ART and the psycho-physiological theory suggest that natural environments

contain restorative attributes. But how much nature is needed, and how “purely natural” does a


natural setting need to be? In a study comparing nature scenes without built structures, urban

scenes with green spaces, and urban scenes without green spaces, students rated the natural

scenes as the most restorative and urban scenes without green spaces as the least restorative;

notably, the urban scenes with green spaces fell in between (Herzog, Maguire, & Nebel, 2003).

The restorative potential of setting context (nature, urban with green spaces, and urban

without green spaces) as demonstrated in the latter study is important to understand, not least

because a very large number of settings in contemporary cities and urban areas entail admixtures

of natural and urban elements rather than exclusively one or the other. Equally important, setting

context must not be considered alone, as it may not necessarily be the most influential or only

restorative attribute. As mentioned earlier, the emotional valence of an environment and the

resultant affective state may indicate the restorativeness as well. The purpose of this study is to

provide a novel analytical test of the relative strength of setting context (nature, urban, and

mixed) versus emotional valence (pleasantness and unpleasantness) for directed attention

restoration.

Being a novel analytical test, we had to create our own stimulus set for each of the six

conditions, requiring two separate phases. Phase 1 involved collecting normative data used to

select the stimulus set for Phase 2, the experimental phase. The normative data collected during

Phase 1 obviously included setting context, emotional valence, and arousal, but there is one other

variable of interest: saliency.

Saliency, or stimulus conspicuity, is similar to fascination in that some stimuli

automatically draw attention in a bottom-up manner (Itti & Koch, 2001). Computational models

based on properties of the human visual system can create a “saliency map,” a topographical map

that codes for local conspicuity over an entire visual scene. Differences in elementary features


such as the orientation of edges, color, disparity, and direction of movement at a given location

lead to saliency (Koch & Ullman, 1985; Itti & Koch, 2000; Itti, Koch, & Niebur, 1998).

In order to create saliency maps and control for stimulus conspicuity, the stimuli used

needed to be photographs. While actual natural environments yielded more energy and higher

ratings of degree of altered states of consciousness (ASC) than did simulated natural

environments (slideshows of pictures from the same environment), simulated natural

environments still result in stress reduction (Kjellgren & Buhrkall, 2010).

The viewing of photographs in other laboratory experiments resulted in attention

restoration as well. In one study (Berto, 2005), photographs of natural environments significantly

improved participants’ performance on a Sustained Attention to Response Task (SART).

Viewing photos of natural compared with urban settings also improved participants’ scores on a

backwards digit span task (Berman, Jonides, & Kaplan, 2008). Photographs clearly have a

restorative potential and this potential may even be increased if participants are able to imagine

themselves within the scene depicted. Kort, Meijinders, Sponselee, and IJsselsteiujn (2006) posit

that immersion enhances the restorative potential of a natural environment.

Purpose

The objectives of this study are to: 1) determine the proportional restorative power of

nature (i.e., how much nature is enough?) and 2) ascertain the comparative restorative strength of

setting context versus emotional valence. Two phases were needed to meet these objectives. In

Phase 1, normative data on valence (happy/pleasant and unhappy/unpleasant), arousal (calm and

excited), and setting (nature, urban, and mixed) as well as saliency data was collected to create a

stimulus set. After generating a suitable stimulus set, Phase 2 involved comparing the

physiological and cognitive responses across two levels of valence (pleasant and unpleasant),


three types of setting (nature, urban, and mixed), and each independent condition (nature

pleasant, nature unpleasant, mixed pleasant, mixed unpleasant, urban pleasant, and urban

unpleasant).

Methods

Phase 1

Participants. Thirty-six University of Minnesota undergraduate students (14 male, 22

female, mean age = 20.14) participated in exchange for Research Experience Program (REP)

points. All of the participants were native English speakers and had normal or corrected-to-

normal vision. Participants were randomly assigned to one of three rating groups: valence,

arousal, and setting.

Stimuli. Five hundred and ninety-five pictures were collected from the internet. The

pictures generally fell into six categories: nature pleasant, nature unpleasant, mixed urban-natural

pleasant, mixed urban-natural unpleasant, urban pleasant, and urban unpleasant. Pleasant nature

scenes (N=99) included landscapes and objects such as trees, rivers, oceans, mountain ranges,

beaches, and sunsets. Unpleasant nature scenes (N=99) contained swamps, termite nests, grasses,

moss, roots, leaves, and mushrooms. Pleasant mixed scenes (N=100) included trees lining a

street, city skylines together with trees or mountain ranges, lighthouses, and parks. Unpleasant

mixed scenes showed landscapes or objects such as leafless trees, fenced in gardens, and

mosses/trees/flowers next to dilapidated buildings. Pleasant urban scenes contained daytime

skylines, night skylines, city streets, highways, buildings, buses, and cars. Unpleasant urban

scenes (N=99) included streets, dilapidated cars, dumpsters, lampposts, and buildings.

Procedure. Before the experiment, participants were informed that they would be

viewing and rating pictures of real world scenes. Twelve participants were instructed to rate the


emotional valence of the photograph on a 9-point scale (1=very happy, 9=very unhappy). Twelve

other participants rated how arousing the photographs were on a 9-point scale (1=calm,

9=excited). Another twelve participants rated the setting of the photographs on a 9-point scale

(1=purely urban, 9=purely nature, 5=equally urban and nature). There was no time limit for

rating the photographs, but participants were instructed to give their initial response rather than

extensively considering or “overthinking” their judgments.

Phase 2

Experimental Design. The experiment was a mixed design, including 6 between-subject

conditions, formed by crossing the three types of settings (nature, urban, and mixed) with two

levels of valence (pleasant versus unpleasant); directed attention was assessed within subjects,

pre- and post-intervention. There were sixteen participants in each of the six conditions. The

main dependent measures were hits and correct rejections on the Sustained Attention to

Response Task (SART), heart rate, systolic blood pressure, and diastolic blood pressure.

Participants. Ninety-six people (42 males, 54 females, mean age = 21.05) participated in

this experiment in return for Research Experience Program (REP) points or $10 per hour. All of

the participants were native English speakers and had normal to corrected-to-normal vision. The

participants were assigned to the 6 between-subject conditions using a block-randomization

procedure.

Procedure. After obtaining participants’ informed consent, participants completed a

demographic information worksheet and had their heart rate and blood pressure measured. Then

participants were instructed to complete the Letter SART (this task is discussed in detail below)

to induce attentional fatigue. Participants’ heart rate and blood pressure was measured again

before receiving instructions and beginning the intervention. Upon the completion of the


intervention, participants’ heart rate and blood pressure were assessed again. Attention

restoration was then measured as participants completed another attention task (Number SART).

Then, the participants’ heart rate and blood pressure was collected one last time before

completing the post-experimental questionnaire. The experiment concluded with the debriefing

of the participant.

Directed Attention Assessments. Two different Sustained Attention to Response Tasks

(SART; Manly, Robertson, Galloway, & Hawkins, 1999; Robertson, Manly, Andrade, Baddeley,

& Yiend, 1997) were used to induce attentional fatigue before the intervention and to measure

attention restoration after the intervention. The SART is a modified go/no-go task in which

participants view repetitive stimuli (numbers or letters) and are instructed to respond by pushing

the ‘b’ key to all briefly presented stimuli with the exception of a specific stimulus or target.

To induce attentional fatigue (before the intervention), participants performed a Letter

SART. Before the task, participants had eighteen practice trials. Afterwards, 225 letters,

including the consonants “B” through “L”, were presented. In this task, the exception target was

the letter “D”; this stimulus appeared twenty-five times and required inhibitory control. The

stimuli remained on the screen for 250ms and were subsequently followed by a 900ms mask.

To measure attention restoration (after the intervention), participants performed a

Number SART. This version of the SART is exactly the same except numbers “1” through “9”

were presented 225 times and twenty-five of those times required inhibitory control as the target,

“3,” appeared on the screen for 250ms before the mask appeared for 900ms.

Physiological Measures. Heart rate as well as systolic and diastolic blood pressure was

measured using an Omron digital wrist blood pressure monitor (model: HEM-670ITO).


Intervention. Each condition (nature pleasant, nature unpleasant, mixed pleasant, mixed

unpleasant, urban pleasant, and urban unpleasant) consisted of twenty-four photographs selected

from the stimuli set used in Phase 1. Photographs were selected based upon the valence, arousal,

and setting ratings previously provided (see Table 1). The selected photographs were also

balanced on a computationally-derived measure of average levels of low-level visual salience

from generated saliency maps (topographical maps that code for local conspicuity over an entire

visual scene) across all conditions. Examples of the photographs can be seen in Figure 1.

Condition Valence Setting Arousal Mean Visual Salience

Mean SD Mean SD Mean SD Mean SDNature Pleasant

6.514 .502 8.295 .276 4.674 .316 .044 .116

Mixed Pleasant

6.851 .709 5.420 1.149 4.813 .724 .040 .102

Urban Pleasant

6.378 .378 1.757 .469 5.097 .505 .045 .112

Nature Unpleasant

3.736 .662 8.229 .224 4.663 .474 .041 .106

Mixed Unpleasant

3.757 .547 4.635 .746 4.698 .377 .045 .114

Urban Unpleasant

3.635 .753 1.819 .253 4.608 .225 .040 .103

Table 1. Valence, Setting, Arousal, and Mean Visual Salience means and standard deviations for all six conditions. Analyses for the control Visual Salience measure showed no effect of setting, F < 1, no effect of valence, F < 1, and no setting x valence interaction, F = 2.27. As expected, there was a significant effect of Valence, F(1, 138) = 808.95, p < .001; this did not interact with setting, F = 1.22. There was no main effect of setting on Arousal, F = 1.89. On the Arousal measure, there was also an effect of valence, F(1, 138) = 7.00, p = .009, and a modest interaction of valence x setting, F(2, 138) = 3.53, p = .032; notably, however, these findings reflected slightly lower arousal for negative (4.66) than for positive (4.86) scenes and slightly higher arousal for the positive urban than for the negative urban scenes.

Participants viewed each photograph for 12,000ms and were instructed to imagine

themselves fully and vividly within the scene shown, thinking about the sounds, smells, feelings,

and thoughts they would experience when actually in that place. After viewing and imagining


themselves within each scene, they rated how well they were able to imagine being in the scene

on a 9-point scale (1=not at all able to imagine, 9=able to imagine very vividly).

Nature Pleasant

Mixed Pleasant

Urban Pleasant

Nature Unpleasant

Mixed Unpleasant

Urban Unpleasant

Figure 1. Examples of photographs for each of the six conditions.


Results

Directed Attention Assessments

We first examined directed attention performance on the pre-intervention Letter SART,

separately considering hits (i.e., correct go responses) and correct rejections (i.e., correct no-go

or inhibited responses). Mean hits and correct rejections appear to be fairly consistent across all

six conditions. Table 2 presents the average number of correct go responses and correct no-go

responses separately for the pre-intervention SART task and the post-intervention SART task for

each of the six intervention conditions as well as for the more general valence (pleasant and

unpleasant) or setting (nature, urban, and mixed) conditions.

Condition Mean Hits (Correct Go Responses)

Mean Correct Rejections (Correct No-Go Responses)

Valence Setting Letter SART (pre-intervention)

Number SART (post-intervention)

Letter SART (pre-intervention)

Number SART (post-intervention)

Pleasant Nature 0.951 0.989 0.846 0.691Mixed 0.946 0.998 0.912 0.749Urban 0.952 0.996 0.888 0.690Total 0.950 0.994 0.882 0.710

Unpleasant Nature 0.950 0.991 0.817 0.696Mixed 0.948 0.995 0.805 0.705Urban 0.954 0.989 0.880 0.793Total 0.950 0.992 0.834 0.731

Total Nature 0.950 0.990 0.831 0.694Mixed 0.948 0.996 0.858 0.727Urban 0.953 0.993 0.884 0.741Total 0.950 0.993 0.858 0.721

Table 2. Average correct go responses (hits) and correct no-go responses (correct rejections).

A 2 (valence) x 3 (setting) analysis of variance (ANOVA) showed that there were no

significant differences for hits as a function of valence, F < 1, or of setting, F < 1, and no


interaction between valence and setting, F < 1. A similar analysis on correct rejections showed

that, on this pre-intervention measure, inhibitory control also did not differ across the valence

conditions F(1, 90) = 1.38, or the setting conditions, F < 1, and no interaction was found, F < 1.

We next examined directed attention performance on the post-intervention Number

SART. The mean number of hits appear quite similar across conditions, and show a high level

of accuracy (~.99; see Table 2). A 2 x 3 ANOVA on hits showed no effect of valence, F < 1.2,

no effect of setting, F(2, 90) = 1.89, p > 0.15, and no interaction, F < 1.2. The mean number of

correctly rejected responses (i.e., correct no-go responses) seemed to be a bit more variable, with

participants in the Urban Unpleasant condition performing better. Despite the variation in means

amongst the conditions, inhibitory control (correct rejections) did not differ across valence, F <1,

or setting, F <1, and there was no interaction, F(2, 90) = 1.26, p > 0.25.

Based upon the pattern of means, participants in the urban unpleasant condition (M =

0.79, SD = 0.14) appeared to perform better on the post-intervention Number SART, particularly

in more effectively inhibiting responses to the no-go (exception) target stimuli, than the other

five conditions (M = 0.71, SD = 0.19). A post-hoc analysis revealed a trend for better inhibitory

control during the Number SART in the urban unpleasant group than for the other five groups,

F(1, 94) = 2.90, p<0.10.

Photo Ratings

According to the self-reported ratings, there were no significant differences in

participants’ ability to imagine themselves within the scenes depicted in the photographs. Table 3

presents the average ratings for immersion/engagement in each of the six conditions

independently as well as across the more general valence (pleasant and unpleasant) or setting

(nature, urban, and mixed) conditions. Participants in the unpleasant conditions were just as


capable of imagining themselves within their scenes as participants in the pleasant conditions, F

<1. There was no significant difference amongst the nature, mixed, or pleasant settings, F <1. No

interaction between valence or setting occurred, F <1.

Valence Setting Photo Rating (1=not at all able to imagine to 9=able to imagine very vividly)Pleasant Nature 5.586

Mixed 6.021Urban 5.445Total 5.684

Unpleasant Nature 6.052Mixed 5.600Urban 5.531Total 5.727

Total Nature 5.819Mixed 5.810Urban 5.488Total 5.706

Table 3. Mean ratings of immersion/engagement for each of the six conditions independently as well as across the more general valence (pleasant and unpleasant) or setting (nature, urban, and mixed) conditions.

Physiological Measures

Figures 2 and 3 present the average heart rate, diastolic blood pressure, and systolic blood

pressure measures for pleasant and unpleasant scenes in each of the setting conditions separately

for the multiple time points.


Figure 2. Mean heart rate (beats per minute) for each condition.


Physiological measures at time-points two and three are of particular interest given that

time-point two is pre-intervention and time-point three is post-intervention. Participants in both

the pleasant and unpleasant nature conditions experienced an increase in heart rate (See Figure

2). Participants in the Pleasant Mixed condition also exhibited an increase in heart rate, whereas

Unpleasant Mixed condition participants demonstrated a decrease in heart rate. The Urban

conditions displayed the opposite pattern as the Mixed conditions with participants in the

Unpleasant Urban condition experiencing an increase in heart rate while Pleasant Urban

condition showed a decrease in heart rate. Nonetheless, despite these small numerical condition

differences, there were no significant differences in participant heart rate across the setting

conditions, F < 1, or the valence conditions F(1, 90) = 1.58, p>0.20, and no interaction, F < 1.

Participants in all Unpleasant conditions as well as those in the Urban Pleasant condition

displayed decreased systolic blood pressure from time-point two (pre-intervention) to time-point

three (post-intervention), yet all participants in all conditions demonstrated decreased diastolic

blood pressure (See Figure 3).


Figure 3. Graphs on the left show the mean systolic blood pressure over the course of the experiment for each condition. Graphs on the right show the mean diastolic blood pressure over the same time period.


Discussion

While a number of empirical studies have investigated the restorativeness of natural

environments, the level or intensity of naturalness needed to produce restorative effects is not

known. And while Karmanov and Hamel (2008) challenge the conclusion that urban areas

inherently lack restorative qualities, they only begin to suggest potential restorative attributes

available in urban areas. In this study, we investigated the level of naturalness needed to provide

attention restoration by including a mixed urban-nature type of setting. In addition, we compared

the relative restorative power of setting context (nature, urban, and mixed) and emotional

valence (pleasant versus unpleasant or comparatively boring and nondescript).

We found no significant physiological or cognitive differences among the six conditions

(nature pleasant, nature unpleasant, mixed pleasant, mixed unpleasant, urban pleasant, and urban

unpleasant) nor the types of setting (nature, urban, and mixed) and levels of valence (pleasant

and unpleasant). Collecting useful physiological data proved to be difficult. Being on a larger

college campus, some students walk or bike to the study while others catch the campus shuttle/

city bus. Some students even chose to climb the five flights of stairs to reach the lab room.

Considering the wide variety of physical activity prior to the study and other moderating factors,

participants did not start out with comparatively equal heart rate or blood pressure. Without some

sort of baseline, making sense of the physiological data and analyzing the effects proved to be

quite difficult. Future experiments dependent upon baseline physiological measures may need to

be coordinated with another experiment in order to achieve the needed baseline. Participants

could partake in a different experiment that provides sufficient time for physiological measures

to return to normal after traveling to the testing site prior to participation in the physiological

baseline dependent experiment.


No significant differences were found among the six different conditions, types of

settings, or levels of valence for attention restoration measured with the Number SART (a

directed attention task); however a post hoc analysis did reveal a trend towards better

performance for those in the Urban Unpleasant condition. Given that we predicted participants

in the Nature Pleasant condition would perform the best on the SART, this trend is particularly

interesting. One possible explanation is the somewhat lower, albeit non-significant, mean arousal

for photographs in the Urban Unpleasant condition. Lower levels of arousal may provide the

opportunity to relax and restore directed attention, leading to improved performance on the

SART.

Despite the lack of significant results, this study provides several unique and novel

methods and considerations for future research. Including the mixed urban-nature setting can be

incredibly useful when trying to identify the amount of nature needed to provide a satisfying

restorative environment. Municipalities are becoming increasingly aware and interested in Green

Infrastructure and the associated benefits. Urban foresters are stressing the psychological risks

associated with tree loss, citing environmental psychology research in their management plans,

as invasive species such as Emerald Ash Borer and the Asian Longhorned Beetle threaten the

health of the urban forest canopy (Touzlas, Korpela, Venn, Ylipelkonen, Kazmierczak, Niemela,

& James, 2007). Understanding the level of nature needed for attention restoration can greatly

inform urban planning and natural resource management.

Crossing the setting context (nature, urban, and mixed) with the further important factor

of emotional valence (pleasant/unpleasant) provides a unique way to compare the relative

strength of context versus valence with regards to attention restoration. The 3 X 2 design of this


experiment permits a variety of analyses and allows one to see how different factors may interact

or maybe even counteract one another.

Equating on saliency and eliminating potential bottom-up differences, as done in this

experiment, can greatly improve future attention restoration research. Creating and using

saliency maps does not require much time and easily removes another possible confound.

Investigating potential innate saliency difference in natural versus urban areas could provide

interesting insight into the restorative character of different types of environments.

Just as the benefits of urbanization are accompanied by detriments, the strengths of this

study are accompanied by weaknesses. One limitation of this study is the length of the

intervention. The intervention only lasted about fifteen minutes and participants only viewed

twenty-four photographs depicting a variety of locations. Even though participants reported that

they were able to imagine themselves within the scene depicted in the photograph fairly well (M

= 5.71), participants might have been able to immerse themselves better if the pictures were

presented longer and depicted one location.

There are many questions that remain unanswered and new questions are constantly

posed. “As a place that houses more and more of the world’s population every day, it [the city] is

a place that needs to be studied and discussed. It influences people for better and for worse; and

its influence, whether subtle or explicit, is always there” (Krupat, 1985). A more thorough

understanding of the relationship among directed attention, nature, and positive affect has both

theoretical and practical application, providing insight into the validity of the Attention

Restoration Theory and the psycho-physiological theory regarding the psychological effects of

exposure to natural settings on human cognition and functioning and informing the decisions of

municipalities and individuals.


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