Neurobehavioral approach for evaluation of office ...

Building and Environment 44 (2009) 1578–1588

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Neurobehavioral approach for evaluation of office workers’ productivity: The effects of room temperature Li Lan a, Zhiwei Lian a, *, Li Pan a, Qian Ye b a b

School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China Shanghai Research Institute of Building Science, Shanghai 200041, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 19 May 2008 Received in revised form 12 September 2008 Accepted 1 October 2008

Indoor environment quality has great influence on worker’s productivity, and how to assess the effect of indoor environment on productivity remains to be the major challenge. A neurobehavioral approach was proposed for evaluation of office workers’ productivity in this paper. The distinguishing characteristic of neurobehavioral approach is its emphasis on the identification and measurement of behavioral changes, for the influence of environment on brain functions manifests behaviorally. Therefore worker’s productivity can be comprehensively evaluated by testing the neurobehavioral functions. Four neurobehavioral functions, including perception, learning and memory, thinking, and executive functions were measured with nine representative psychometric tests. The effect of room temperature on performance of neurobehavioral tests was investigated in the laboratory. Four temperatures (19 C, 24 C, 27 C, and 32 C) were investigated based on the thermal sensation from cold to hot. Signal detection theory was utilized to analyze response bias. It was found that motivated people could maintain high performance for a short time under adverse (hot or cold) environmental conditions. Room temperature affected task performance differentially, depending on the type of tasks. The proposed neurobehavioral approach could be worked to quantitatively and systematically evaluate office workers’ productivity. Ó 2008 Elsevier Ltd. All rights reserved.

Keywords: Neurobehavioral approach Evaluation Office workers Productivity Signal detection theory

1. Introduction Researches indicated that the indoor environment was evaluated to have the biggest influence on productivity in relation to job dissatisfaction and job stress [1]. Since the cost of the people in an office is an order of magnitude higher than the cost of maintaining and operating the building, spending money on improving the work environment may be the most cost-effective way to improve productivity. Office work performance contributes substantially to productivity gain in today’s world, and recent research has focused on the impact of indoor environmental quality on office work. Air temperature was deemed to be one of the most important indoor environment factors that affected office productivity. However, determining a quantitative relationship between air temperature and productivity proved to be highly controversial. Investigations have been taken in field or laboratory to study the link between air temperature and productivity. Field studies used a work task as metrics of productivity, in call centers the talk time or the handling time per client was used as indication of the speed

* Corresponding author. Tel.: þ86 21 34204263; fax: þ86 21 34206814. E-mail address: [email protected] (Z. Lian). 0360-1323/$ – see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.buildenv.2008.10.004

of work. Niemela et al. [2] reported a decrement in productivity of call center workers when the temperature was above 25 C. Federspiel et al. [3] measured the productivity of call center workers in the US. They found temperature had no significant effect on productivity in the comfort zone. Laboratory studies in the past have focused mainly on simple and repetitive jobs, such as typing and simple calculation (addition, multiplication, etc.) task [4–8]. Office works cover a wide range of different tasks involving a complex set of component skills, so studies on simulated office work or one specific task cannot comprehensively reveal the effect on productivity of real office work. Also much more information was available on the effects of extremely low (or extremely high) temperatures not commonly experienced in office buildings. Less information was available on the degree to which productivity was affected by slightly low temperatures or cold thermal sensations. In addition, although it is felt that improving the quality of thermal environment can increase productivity, any quantitative proof of this statement is sparse and controversial. Therefore it is difficult to persuade clients to accept the concept of a relationship between indoor environment and economic productivity benefits. How to assess the effect of indoor environment on productivity remains to be the major challenge. In this paper a neurobehavioral approach was proposed aiming at measuring the effect of indoor environment quality on office workers’ productivity quantitatively and comprehensively.

L. Lan et al. / Building and Environment 44 (2009) 1578–1588

2. Methodologies 2.1. Neurobehavioral theory Neurobehavioral approach has been effectively used in environmental and occupational decision making, to determine safe exposure levels preventing the onset of early adverse effect on the nervous system. The development of the earliest neurobehavioral tests in toxicology took basically two fronts [9]. The first began with a clinical neuropsychological flavor. Tests from such classical batteries as the Wechsler Adult Intelligence Scale (WAIS) and the Halstead-Reitan Batteray were used in the mid 1970s to assess the effects of lead and some of the organic solvents. The second approach was to use tests from experimental psychology such as reaction time tests. The distinguishing characteristic of neurobehavioral approach is its emphasis on the identification and measurement of behavioral changes, for the influence of environment on brain functions manifests behaviorally. Neurobehavioral approach is neurobiologically justified since the central nervous system displays particular sensitivity to environmental disturbance, compared with peripheral physiological manifestations [10]. As a result, behavioral changes represent an avenue through which early and less obvious effects of environmental factors were evaluated. Behavior may be conceptualized in terms of three functional systems: (1) cognition, which is the information-handling aspect of behavior; (2) emotionality, which concerns feeling and motivation; and (3) executive functions, which have to do with how behavior is expressed [11]. The descriptive framework of these neurobehavioral functions is illustrated in Fig. 1. The four major classes of cognitive functions have the information-processing analogues in the computer operations of input, storage, processing and output. (1) Perception functions involve the ability to select, acquire, classify, and integrate information. There are visual perception and auditory perception, in which visual functions can be broadly divided along the lines of verbal/symbolic and configural stimuli. (2) Memory and learning refer to information storage and retrieval. The capacity for memory, learning, and intentional access to knowledge store is central to all cognitive functions and probably to all that is characteristically human in a person’s behavior [11]. As to the memory function, working memory is emphasized. The concept of working memory refers to a brain system that provides temporary storage and manipulation of the information necessary for such complex cognitive tasks as language comprehension, learning, and reasoning [12]. Working memory represents a modification and extension of an earlier

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concept, short-term memory. Working memory also plays a crucial role in adding information to long-term memory. Baddeley’s concept of working memory mainly includes four components. The central executive is the controlling, decision-making mechanism of working memory that functions to recruit and perform operations required by the current task, as well as allocate capacity in the working memory subsystems. The three subsystems that have received some research effort are the phonological loop, visualspatial sketchpad and episodic buffer, each of which is a temporary storage system. Visual-spatial material is stored and manipulated by the visual-spatial sketchpad, whereas speech-based material is stored and manipulated by the phonological loop. These subsystems are essentially modality-specific storage/work space. The episodic buffer stores multidimensional representations, information that is integrated across modalities. (3) Thinking concerns the mental organization and reorganization of information. Thinking may be defined as any mental operation that relates two or more bit of information explicitly or implicitly [11]. The nature of the information being mentally manipulated (e.g., numbers, design concepts) and the operation (e.g., comparing, abstracting, ordering) define the category of thinking. (4) Expressive functions are the means through which information is communicated or acted upon, such as oral expression and written expression. Although each function constitutes a distinct class of behaviours, normally they work in close, interdependent concert, and they are inextricably bound together-different facets of the same activity. Generally speaking, within each class of cognitive functions, a division may be made between those functions that mediate verbal/symbolic information and those that deal with data that cannot be in words or symbols, such as complex visual or sound patterns. These cognitive functions are accomplished by different cortexes (mainly include frontal lobe, parietal lobe, temporal lobe and occipital lobe) of two hemispheres [11,13]. Two hemispheres are functional specialized. For most people the left hemisphere is the primary mediator of verbal functions, including reading and writing, understanding and speaking, verbal ideation, verbal memory, and even comprehension of verbal symbols traced on the skin. The left hemisphere also mediates the numerical symbol system. The right hemisphere dominates the processing of information that does not readily lend itself to verbalization. This includes the reception and storage of visual data, tactile and visual recognition of shapes and forms, perception of spatial orientation and perspective, and coping and drawing geometric and representational designs and pictures. The four cortexes are also functional specialized. Frontal lobe is concerned with reasoning, planning, parts of speech and movement, emotions, and

Fig. 1. A neurobehavioral framework for evaluation of productivity of office work.

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problem-solving; parietal lobe is concerned with perception of stimuli related to touch, pressure, temperature and pain; temporal lobe is concerned with perception and recognition of auditory stimuli and memory; occipital lobe is concerned with many aspects of vision. Academic psychology studies attention functions within the framework of cognitive psychology. However, attention functions differ from the above functions in that they underlie and, in a sense, maintain the activity of the cognitive functions. To carry computer analogy a step further, attention functions serve somewhat as command operation, calling into play one or more cognitive functions. For this reason, attention functions were not classified as cognitive functions here. The executive functions consist of those capacities that enable a person to engage successfully in independent, purposive, selfserving behavior. They include conceptualizing an intention, identifying and organizing the steps and elements needed to carry out an intention, motor skills, etc. Cognitive functions usually involve specific functions or functional area; executive functions tend to show up globally, affecting all aspects of behavior. 2.2. Neurobehavioral test battery The effect of indoor environment on productivity of office workers can be systematically and comprehensively assessed by testing these neurobehavioral functions, in which cognitive functions were the emphasis of testing since office works are characterized by more cognitive and information-processing components. These neurobehavioral functions can be accurately assessed by psychometric tests. In this research, nine representative tests were selected to test each neurobehavioral function, referring to some commonly used computerized neurobehavioral test batteries, experimental psychology, and cognitive researches. These representative tests were computerized with VB (Visual Basic) language. A short description of each test and scale was given below, and Table 1 lists the functions mainly tested by these tasks. Letter search was a visual search task, in which the participant had to detect the presence or the absence of a target letter in a string of 10 letters as quickly as possible. This task was relatively simple compared to the reasoning tasks, it required selective attention operations and an efficient identification of stimuli (match between target stimuli and perceived stimuli) [14]. A total of 50 stimuli was presented. The response time and number of hits, false alarm, correctly rejects and misses were recorded. Overlapping engaged strategic processes as well as many working memory resources in perceptive and spatial reasoning operations [15]. A sheet on which the outlines of 6 overlapping geometric figures were drawn was presented to the participant. The instructions were as follows: . Six trials were scheduled. The response time and number of corrects were recorded. Memory span was a traditional test of verbal working memory and attention adapted from the Wechsler Adult Intelligence Scale [14]. A string of random numbers was present on the screen for a period of time and then disappeared. The presentation time of each number string was based on the string length, one second for one number. Participants were required to reproduce the number string on the keyboard. The test started with a string of four numbers, with every length being present twice, and it was terminated when participants made two errors in succession. Correct number, error number and time were recorded. Picture recognition was a visual recognition memory and attention task [16]. Randomly ten nonsense pictures (called target stimuli) were successively presented on the screen one at a time with a 1-s presentation time. Then twenty nonsense pictures, mixing another ten target stimuli with other ten pictures (called obstructive stimuli) were successively presented on the screen. The task was to recognize among the twenty pictures which were target stimuli by pressing two different keyboards, therefore a response selection was also involved. Three measures were registered during the test: 1) the number of correctly recognized pictures, 2) the number of incorrectly recognized pictures, and 3) the response time. Symbol–digit modalities test was a learning memory test [17]. Ten symbols and digits were paired at the top of the screen and the participant was instructed to press the digit keys corresponding to a reordered test set of ten symbols displayed at the bottom of the screen. Digits at the top and bottom of the screen disappeared after participant finished the coding. Then participant was instructed to reproduce the symbol–digit pairs by pressing the digit keys corresponding to another reordered test set of the ten symbols. Three trials were scheduled. Three measures were registered during the test: 1) the number of correctly recalled symbol–digit pairs, 2) the number of incorrectly recalled symbol–digit pairs, and 3) the response time. Number calculation measured speed and accuracy of mental arithmetic operations [16]. Two three-digit numbers were presented on the screen to the participant. The task was to add the digits as quickly as possible and to indicate the sum on the keyboard. The test included a total of 20 items. The response time and the number of corrects were recorded. Conditional reasoning was a verbal deductive reasoning task. One premise and four conclusions (but only one conclusion can be deduced from the premise) were presented on the computer screen. Participant’s task was to choose the correct conclusion as quickly as possible. This task involved strategic processes and engaged many working memory resources. Three trials were scheduled. Response time and number of corrects and errors were recorded. Spatial image was a spatial reasoning and imagination task. Four cuboids and an outspread picture of one of the cuboids were presented on the screen. The instructions were as follows: . Totally 3 trials were scheduled. Response time and number of corrects were recorded. Visual choice reaction time (RT) was a sustained attention task measuring response speed and accuracy to visual signals [14]. Stimuli consisting of arrow and triangle were displayed one at a time on the screen. The arrows were left and right directional, and the triangles were left and right placed. The task was to indicate on


the left or right key the direction of arrows and position of triangles. A total of 50 stimuli was presented. Response time and correct numbers were recorded. Conditional reasoning and Spatial image tests were adopted from the Civil Service Examination of China. It should be noted that these neurobehavioral functions are inextricably bound togetherdifferent facets of the same activity, so the performance of any one test typically relied on more than one function. For example, virtually all tests involve some aspect of perception function, of working memory function and of motor function. 2.3. Experiment Experiment was designed to evaluate the effect of temperature on performance of the above neurobehavioral tests. The experiment was carried out in an ordinary but low-polluting office (L W H ¼ 6 4 5 m), in which participants sat at six workstations, each consisting of a table, a chair and a personal computer (Fig. 2). The room temperature was controlled by an air-conditioner, which was able to adjust temperature from 16 C to 32 C. The office was illuminated with eight fluorescent lamps. 2.3.1. Participants Twenty-four participants (12 females and 12 males) were recruited to participate in the present experiment. The participants were students aged 19–30 years (m ¼ 25, s ¼ 3). Also the 24 participants were familiar with computer, and impartial to the office in which the study was carried out. All protocols were approved by university’s ethics committee and conformed to the guidelines contained within the Declaration of Helsinki. Verbal and written informed consents were obtained from participants before they participated in the experiment. Participants were required to wear typical light clothes (shortsleeved shirt, long trousers) and their own underwear, socks and shoes (an estimated clothing insulation value of 0.6 Clo, including the insulation of the chair). They were also asked to have a good rest at the night before experiment.

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The participants were paid a salary for participation in the experiment at a fixed rate per hour. To increase their motivation and especially to encourage them to perform the tests seriously, they were told before experiment that a bonus will be paid depending on their performance. Participants all successfully completed experimental sessions. 2.3.2. Experimental design Four temperatures, 19 C, 24 C, 27 C and 32 C, were studied in this experiment. The indoor air velocity was kept under 0.1 m/s, and the relative humidity of air was not dependently controlled. 24 participants were separated into 4 groups with 6 participants (3 males and 3 females, respectively) in a group. Within-subject design was applied for this experiment [16]. In within-subject design, the same participants were tested in each condition. Therefore, individual differences could be offset more efficiently. However, there was also a fundamental disadvantage of the withinsubject design, that is, the participation in one condition might affect performance in other conditions, which could be referred to as ‘‘carryover effects’’, two basic types of which were practice and fatigue effect carryover effects. So the balanced Latin-square design was utilized to control the carryover effects. In this experiment, there was one independent variable of 4 levels – temperature, and 4 groups of participants. The experiment was performed during two successive weeks, each week on four days from Monday to Thursday, and each day for 80 min in the morning and afternoon, respectively, from 9:00 to 10:20 and from 15:00 to 16:20. Each temperature treatment lasted for 80 min. Therefore, each group received 4 treatments at 4 time periods. Also each group was exposed to the same weekday of two successive experimental weeks to avoid any influence of weekday on the within-subject difference between conditions. That is, one group received the four treatments in the morning and afternoon of the two successive Mondays, and other three groups at Tuesday, Wednesday and Thursday, respectively. A standardized four by four Latin-square design was shown in Table 2, in which Factor T was the experimental variable (T1 – 32 C, T2 – 27 C, T3 – 24 C, T4 – 19 C),

Fig. 2. Experimental set-up in the lab. (a) Sketch map (1 – air conditioner, 2 – personal computer); (b, c) field picture.

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Table 2 Balanced Latin-square design of this experiment.

A1 A2 A3 A4

B1

B2

B3

B4

T1 T2 T3 T4

T2 T4 T1 T3

T3 T1 T4 T2

T4 T3 T2 T1

factor A referred to the four participant groups, and factor B referred to the four successive time periods of each group. 2.3.3. Measurements Physical measurements. The temperature, relativity humidity and velocity of the air were measured. The mean radiant temperature was estimated from the globe temperature, which was measured using a 150 mm diameter black globe thermometer. The illuminant was measured with a digital luxmeter near each participant at the height of working face. Physiological measurements. The finger temperature of the right 3rd finger was measured with portable infrared Thermometers (Raytek ST). The temperature of the planar surface of the terminal phalanx was measured. Subjective measurements. The questionnaire used to obtain subjective sensations included questions regarding perceived air quality, general perceptions of the environment and thermal comfort. Thermal sensation votes (TSV) were cast on the ASHRAE/ ISO seven-point thermal sensation scale, which was defined as hot (þ3), warm (þ2), slightly warm (þ1), neutral (0), slightly cool (1), cool (2) and cold (3). Thermal comfort (TC) was cast on 9-point numerical scales – comfortable (0), slightly uncomfortable (1), uncomfortable (2), very uncomfortable (3), and limited tolerance (4), recognizing the same positive/negative convention for warm/ cold discomfort. Objective measurements. The sequence of nine neurobehavioral tests was: Overlapping – Conditional reasoning – Spatial image – Memory span – Picture recognition – Visual choice RT – Letter search – Number calculation – Symbol–digit modalities test. Participants were encouraged to do their best and perform tests as accurately and quickly as possible by supporting extra bonus. Memory capacity was used to measure the accuracy of memory tests [16]. Digit span, which was a common measure of working memory, i.e. the maximum number of digit the participant could correctly absorb and recall, was used to measure the memory capacity of Memory span. The memory capacity of Picture recognition and Symbol–digit modalities test was evaluated, respectively, as following: Picture recognition

MCP ¼

NC NINC NT

(1)

where NC – the number of correctly recognized pictures; NINC – the number of incorrectly recognized pictures; NT – the number of total recognized pictures. Symbol–digit modalities test

MCP ¼

NC NT

For each test used in the present study, except Memory span, two efficiency indices were considered: speed of execution and accuracy expressed in percentage (number of correct responses/total number of responses 100) or in memory capacity. 2.3.4. Experimental procedure The experiment was carried out according to balanced Latinsquare design (as shown in Table 2). For each treatment, the schedule was as follows: after participants were exposed to the office, they were allowed to read books or play games for 40 min to adapt to the indoor environment. During this period, physical parameters were measured. 40 min later, participants’ finger temperatures were measured just before they assessed indoor environment by filling in questionnaires, and then they performed the neurobehavioral test battery. Each experimental section lasted for about 80 min. The participants could leave the room once they had completed their assigned tasks. A week before the experiment, participants received training of the test battery. They were also instructed on how to fill out the questionnaires used to obtain subjective responses. 2.3.5. Statistical analysis The results of performance tasks were first tested for normality using Shapiro–Wilk’s W test; the significance level was set to be 0.05 (P < 0.05). Normally distributed data were subjected to analysis of variance in a repeated measures design and PairedSamples T test with each subject as her own control, thus excluding any differences in experience, training, intellectual skills, etc. which can influence the performance [18]. Not normally distributed data were analyzed using Friedman’s analysis of variance and Wilcoxon Signed-Ranks test [19]. For repeated measures analysis of variance, Huynh–Feldt statistics were used to adjust the violation of sphericity. Huynh–Feldt’s P values were based on corrected degrees of freedom, though the original degrees of freedom were reported.

3. Results 3.1. Results of thermal condition and finger temperature The measured physical parameters describing the indoor climate of the office and the finger temperatures are shown in Table 3. Relationship between thermal sensation votes and air temperature is shown in Fig. 3. Relationship between thermal comfort votes and air temperature is shown in Fig. 4. The size of the plot in Figs. 3 and 4 represented the number of replies. Linear fit and polynomial fit lines showed that most participants felt neutral and thermal comfort around 25.0 C. According to subjective questionnaires, about 80 percent participants voted comfortable cool and comfortable warm when indoor air temperature was 24 C and 27 C, respectively.

Table 3 Mean values and STD of physical parameters and finger temperature inside the office. Parameter

(2)

where NC – the number of correctly recalled symbol–digit pairs; NT – the number of total recalled symbol–digit pairs.

Air temperature ( C) Relative humidity (%) Air velocity (m/s) Mean radiant temperature ( C) Illuminant (lx) Finger temperature ( C)

32

27

24

19

32.2 0.2 76.0 2.0 0.04 0.01 32.4 0.2

27.2 0.5 54.3 2.9 0.07 0.03 27.8 0.6

25.4 0.5 54.3 4.3 0.06 0.02 26.0 0.5

19.5 0.5 63.2 3.9 0.06 0.01 20.2 0.5

562.1 54.1 32.8 1.8

561.8 54.0 32.5 2.4

563.6 54.8 31.3 2.2

563.0 54.5 27.4 2.4


Fig. 3. Correlation of thermal sensation votes versus air temperature.

3.2. Results of neurobehavioral tests Mean values, standard deviations and P values for all of the collected indices (response time and correct percentage or memory capacity) of neurobehavioral tests are shown in Appendix A. Peaks of maximum accuracy or minimum response time are indicated in bold face. The difficulties of each test (P0 ), which were estimated by the averaged ratio of the number of correct responses to the total number of responses on each test [20], are also shown in Appendix A. The higher the P0 value, the easier the test. It can be seen that the two reasoning tests – Conditioning reasoning and Spatial image, had medium difficulty, and the other tests were comparatively easy. Non-parametric Friedman’s ANOVA indicated that room temperature did not significantly affect the accuracy of all neurobehavioral tests. Repeated measures ANOVA also showed that room temperature had no significant effect on response time of most tests, except that temperature had a significant (P < 0.05) effect on response time of Number Calculation test. Paired-Samples T test revealed that participants performed Number Calculation test

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significantly slower at 19 C (P < 0.01) than at 32 C, and also slower (P < 0.05) than 24 C and 27 C. The variation of accuracy and speed versus air temperature is shown in Figs. 5 and 6. The accuracy and speed data had been transformed into z scores for each participant. It could be seen from Figs. 5 and 6 that room temperature affected the performance of neurobehavioral tests differentially, depending on the type of tasks. The accuracy of most tests increased from 19 C, and peaked at 24 C or at 27 C, then decreased. Interestingly, the accuracy of some tests, such as Conditional reasoning, Number calculation and Picture recognition, rebound somewhat at 32 C when compared with those at 27 C. With regard to Overlapping and Memory span, their accuracy almost remained constant among the four temperatures. As to response time, Fig. 6 showed a consistency among the tests. It can be seen that generally participants performed tasks most quickly at 32 C and slowest at 19 C. The variation of response time between 24 C and 27 C was smallest compared with other temperature pairs, and the response time of 27 C was longer than that of 24 C. The large variance of accuracy and speed indicated that there were large individual differences on the performance of neurobehavioral tests. 3.2.1. Circadian effects The difference of accuracy and speed between morning and afternoon sessions is illustrated in Table 4. It can be seen from Table 4 that the accuracy of most tests at the afternoon session was better than that at the morning session, and the speed of all tests at the afternoon session was faster than that at the morning. Although there is no significant difference in accuracy, significant differences were found in speed of several tests. So generally speaking, participants performed better at the afternoon session than at the morning session. However, it is arbitrary to attribute this difference only to the am/pm circadian effects. It can be seen from Table 2 that, for each group of participants, the afternoon sessions were all the second session of the same day. It also should be noted that the significant differences in speed were found for those easy tests, but not for some tests that should have little learning effect, such as Conditional reasoning and Spatial image. So it is possible that the circadian effect was masked by the learning effects. The circadian effect could not be analyzed independently according to this experimental design, as the aim of which was to investigate temperature effect only. The balanced Latin-square design helped to partially balance circadian effects, for each temperature condition had the same chance to be in the morning session and afternoon session. 3.3. Result analysis

Fig. 4. Correlation of thermal comfort votes versus air temperature.

Signal detection theory (SDT) was utilized to analyze the sensitivity and response bias of participants when they performed Letter search at different temperature environments. SDT was a method of modeling the decision-making process treating detection of stimulus, part of which was determined by the nature of stimulus, by how sensitive a subject was to the stimulus, and by cognitive factors, and their bias to favor a particular type of response [16,21]. Investigation had found that a summary score of accuracy or response time would just indicate impaired or improved performance, but analysis of variables or subfunctions that contribute to performance might be more important for tests such as Letter search. There were four possible outcomes for Letter search: hit (target present and participant responded ‘‘yes’’), miss (target present and participant responded ‘‘no’’), false alarm (target absent and participant responded ‘‘yes’’), and correct rejection (target absent and participant responded ‘‘no’’). Although no significant temperature effect was observed on accuracy (correct

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Fig. 5. The effect of room temperature on accuracy.

ratio including hit and correct rejection) of Letter search, approaching significant temperature effect on correct rejection was observed (P ¼ 0.06 by Friedman ANOVA). A Wilcoxon MatchedPairs Signed-Ranks test further showed that the percentage of correct reject was significantly higher at 24 C than that at 32 C (P < 0.05).

d0 ¼ zðHRÞ zðFARÞ

(3)

where z(HR) and z(FAR) were the z-score transforms of the HR and FAR probabilities, based on the Gaussian normal distribution. Larger absolute values of d0 meant that a person was more sensitive to stimulus. Response bias b reflected the response strategy of participant (e.g., saying easily YES rather than NO). It corresponded to the ratio of the height of the signal distribution to the noise distribution for the value of the threshold. It could be computed as:

b¼

NðHRÞ NðFARÞ

where meant often) meant

(4)

pffiffiffiffiffiffiffi NðxÞ ¼ 1= 2p expfð1=2Þx2 g. When b was less than 1, it that the participant was liberal (i.e., responded YES more to respond stimulus, while when b was larger than 1, it that the participant was conservative (i.e., responded NO

more often). Larger b indicated that the participant was more conservative. The value of d0 and b of Letter search of four temperatures is shown in Table 5. The highest d0 value indicated that participants were most sensitive to stimulus at temperature of 24 C, whereas the lowest d0 value indicated that they were least sensitive to stimulus at temperature of 32 C. It also could be seen that all values of b were larger than 1, which indicated that participants responded NO more often. Comparatively participants were more conservative at 24 C, and less conservative at 27 C and 32 C, and particularly participants were even more liberal at 27 C than at 32 C.

4. Discussion No significant effect of temperature on the performance of almost of all tests was observed within the short duration of experimental session in this research. It revealed that most people could maintain high performance for a short time under adverse (hot or cold) environmental conditions when they were trying to do their best. Tanabe and Nishihara [22] also found no significant effect of moderately high temperature on the performance of several tasks. This result could be explained by the following reasons. First, several studies supported the hypothesis that there


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Fig. 6. The effect of room temperature on speed.

was a temperature range within which task performance was not significantly affected. Witterseh [6], who investigated the effect of temperature on mental work by performing simulated office work (including multiplication, typing and addition tests), found that there was no significant effect of temperature on the performance from thermal neutral temperature (22 C) to slightly warm discomfort temperature (25 C). Seppa¨nen et al. [8] summarized relevant studies and assumed a conservative temperature range (21–25 C) in which productivity was not affected by temperature.

Hancock presented maximal adaptability model and suggested that ‘‘minor levels of input stress are readily absorbed by adaptive capability; they do not disturb steady-state functioning and so are not reflected as output stress, manifest in change of behaviour’’. Lorsch and Ossama [23] stated that there was a critical temperature zone (between 32.2 C and 35 C) above which accuracy of performance of mental tasks declined. Razmjou [24] argued that deficit of mental performance in the heat could be offset by an increase in arousal, particularly when task demand was low. Based

Table 4 Mean and STD of accuracy and speed between morning and afternoon sessions. Item

Correct ratio

Session

Morning

Afternoon

P

Morning

Afternoon

P

Letter search Overlapping Number calculation Conditional reasoning Spatial image Memory span Picture recognition Symbol–digit modalities test Visual choice RT

97.3 0.5 94.0 0.7 94.2 0.8 72.2 4.1 65.6 3.9 10.3 0.2 85.6 1.8 86.7 2.4 98.2 0.3

98.1 0.4 94.9 0.7 95.0 0.8 69.6 3.8 68.8 4.1 10.9 0.2 79.2 2.4 87.5 2.4 98.8 0.2

0.23 0.36 0.38 0.44 0.62 0.06 0.06 0.70 0.12

72.0 1.6 227.3 6.8 173.8 5.7 290.2 12.7 164.6 12.6

68.1 1.7 203.6 6.0 157.1 5.1 290.1 12.4 144.8 8.0

0.06 0.01** 0.03* 0.99 0.44

20.3 0.5 144.2 7.8 48.6 1.3

18.7 0.5 139.4 6.6 44.2 1.0

0.01** 0.91 0.02*

*

P < 0.05, **P < 0.01.

Response time (s)

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Table 5 Mean d0 and b of participants at different temperatures. Temperature ( C)

32

27

24

19

HR (%) FAR (%) z(HR) z(FAR) N(HR) N(FAR) d0

95.329 1.131 1.678 2.280 0.0976 0.0297 3.958 3.292

97.272 0.9175 1.922 2.358 0.0629 0.0247 4.28 2.542

97.341 0 1.933 3.09 0.0616 0.0034 5.023 18.280

95.420 0.495 1.687 2.58 0.0961 0.0143 4.267 6.721

b

on the results of subjective assessment, participants were thermally neutral at temperature around 25.0 C (Fig. 3). So the four temperatures investigated in this research were not deviated too much from neutral, and even the highest temperature did not exceed the critical zone. Second, heat stress together with exposure time affected participant’s performance. Studies showed that increased temperatures only tend to increase errors in the performance of sustained mental tasks that continued for 60 min or longer [23]. Another important reason was the existence of a ‘cognitive reserve’, whereby participants have at their disposal a certain amount of neural resources that could be allocated to the performance of tasks and activities. Performance of these tasks and activities would deteriorate when the amount of resources was insufficient to deal with both the task demands and the thermal stress, such that participants would be able to maintain their performance level until the resources were overloaded [25]. Several studies had found that when individuals were encouraged to do their best, they did it as well under optimum as under stagnant, hot, and humid conditions for a short time [23]. In our experiment, the neurobehavioral tests occupied participants, who were encouraged to perform trying their best, only about 30 min to complete, which was relatively very short time. In addition, the nine neurobehavioral tests were not very difficult. It was therefore reasonable that the performance of many tasks might be affected, but not significantly over a short period within the temperature range we investigated. While this conclusion may be valid for relatively short periods of experimental duration, it is questionable whether this holds true for sustained periods of actual work. Ramsey and Kwon [26] noted that the core temperature had a tendency to elevate slightly with continued exposure which would suggest a continual deterioration in cognitive performance with prolonged exposure. Motivated participants may sustain the performance by exerting more effort. Short-lasting effort investment is probably without health consequences and is one of the advantages of human flexibility to deal with in demands. However, prolonged, continuous effort compensation will cause fatigue and less motivation, and even can be a threat to good health, as it has been suggested that repetitive activation of the cardiovascular defense response may lead to hypertension [27]. Therefore subjective assessment that reports participants’ feeling is necessary to be included in the research took in laboratory. Figs. 5 and 6 indicated that temperature affected the task performance differentially, depending on the type of tasks. This result had also been approved by the review of Hancock and Vasmatzidis [10]. This discrepancy might result from the fact that different tasks were accomplished by different dominant hemispheres and different brain cortexes [11,13]. Accuracy of many tests was slightly impaired under high and low temperatures. The accuracy of tests such as Letter search, Conditional reasoning, and Number calculation that were dominated by left hemisphere peaked at 24 C, while the accuracy of tests such as Overlapping, Spatial image, and Visual choice RT that were dominated by right hemisphere peaked at 27 C. With regard to memory tests, the memory

capacity of Memory span and Symbol–digit modalities test varied differently with temperature from that of Picture recognition. Although the Memory span, Picture recognition and Symbol–digit modalities test were presented in the visual domain, verbal strategies usually were applied to solve the Memory span and Symbol– digit substitution tasks. So Memory span and Symbol–digit modalities test were verbal memory tests, which were dominated by left hemisphere, while Picture recognition had a substantially visualspatial processing component, which was a significant right hemisphere component. Phonological loop and visual-spatial sketchpad were involved, respectively, in these two kinds of memory tests. Neuroimaging research has also provided support for the claim that the neural areas responsible for the storage and manipulation of visual-spatial information are distinct from those dedicated to the storage and manipulation of verbal information [28]. Furthermore, Picture recognition was a pure recognition task, whereas Memory span and Symbol–digit modalities test relied on recollection memory. Recognition memory tasks are easier than recollection tasks and thus differ in terms of cognitive load, and are most likely carried out in different brain areas. Peripheral cortex provides a simple recognition signal, while recollection involves sensory cortices and larger parts of the media-temporal lobe. It could be seen from Fig. 6 that participants performed tasks more quickly at 32 C, while more slowly at 19 C. When the room temperature was 32 C, participants felt uncomfortable hot, so they hoped to complete tasks as soon as possible and escaped from the environment. Another potential explanation for high speed was a rise in internal body temperature, which resulted in an increase in the rate of neural activity and a decrease in perceived time [29]. A study by Hocking et al. [25] supported the theory of increased neural activity. In their study, brain imaging showed changes in electrical activity in response to thermal stress during cognitive performance. On the other hand, the slowing speed at low temperature can be attributed to the deterioration of dexterity of hands, due to stiffening of joints and slow muscular reaction, numbness, and a loss in strength. Studies indicated that the dexterity of hands was deteriorated already with indoor air temperatures between 20 and 22 C [8]. Meese et al. reported significant decrement in finger strength and speed in pencil rolling task with different levels of retardation, and pegboard, screwplate, block treading and knot-tying tests. The performance in all tests was 5–15% lower with an ambient temperature of 18 C than with the reference temperature of 24 C. It also can be found in Table 3 that the finger temperature decreased sharply when the air temperature was 19 C. So the significantly lower speed of Number calculation test at 19 C than at other three temperatures may be attributed to the dexterity of hands. Number calculation test was completed by typing the calculation results on the number keyboard, and the response time largely depended on the speed of number typing, therefore correlated highly with the motor flexibility of hands. Figs. 5 and 6 indicated that participants performed worse at 27 C (when they feel comfortable warm) than at 24 C (when they feel comfortable cool). The correct ratios of some tests such as Conditional reasoning, Number calculation and Picture recognition at 27 C were even lower than those at 32 C. It indicated that mild warmth was harmful to task performance. This was linked to the common experience that warmth made one feel drowsy and relaxed, and therefore worked less efficiently. Several other studies have shown that very moderate stress can negatively affect mental performance [4]. In the case of a warm thermal environment, the blood vessels would normally vasodilate, increasing the blood flow through the skin and at higher thermal load one begins to perspire. In the absence of conscious effort, the human body might tend to adapt through lowering of internal heat production and this reduces or even avoids perspiration. This subconscious behavioral adjustment could mean a lower arousal and results in a slower


work rate. This is the responsiveness of human thermoregulatory system towards external variation in climate, work condition and perceived sensations [30]. The significantly higher percentage of correct reject at 24 C than that at 32 C could be explained by response bias b, i.e. participants preferred to perform Letter search conservatively (b [ 1). The smallest b indicated that participants performed tasks most liberally at 27 C. In addition, lowest hit accuracy and lower correct rejection accuracy revealed that participants were less sensitive to stimuli and responded more liberally at 32 C than at 24 C. Different from a summary score that would just suggest impaired accuracy, analysis of these variables could reflect the response bias of participants and their sensitivity to stimulus, both of which determined their performance. So it was important to analyze the variables or subfunctions that contribute to performance besides summary score. 5. Conclusions A neurobehavioral approach was proposed with an attempt to evaluate office worker’s productivity. Effect of room temperature on performance of office workers was investigated by the neurobehavioral test battery. Conclusions can be obtained as follows: The neurobehavioral approach can be worked to quantitatively and comprehensively evaluate office workers’ productivity. Motivated people can maintain high productivity for a short time under adverse (hot or cold) environmental conditions when they are trying to do their best. Room temperature affects task performance differentially, depending on the type of tasks. This discrepancy may result from the fact that different tasks are accomplished by different dominant hemispheres and different brain cortexes. Very moderate warmth can negatively affect mental performance. It is important to analyze the variables or subfunctions that contribute to productivity besides summary score. However, there are many future works need to be done for the development of neurobehavioral test battery. Some other abilities required in offices (such as oral comprehension, fluency of ideas, writing, etc.) have not been tested by the present neurobehavioral test battery yet, so more tests should be included further in order to evaluate office workers’ productivity better. For individuals the task should be neither very easy nor very difficult. Maybe one solution is to employ versions of a given task with different degrees of difficulty. Also the accuracy should be evaluated in more detail, for example, not only record the correct number, but also score differently according to how close the answer to correct answer. Moreover, to estimate Beta and Delta more accurately using Signal Detection Theory (SDT), participants should be asked not only respond yes/no but also sure/unsure. In addition, subjective assessment which is useful in tapping participants’ internal feelings should be included in the evaluation. Longer exposure experiments, such as 5 h, will also be carried out in our future research. Acknowledgement The project was financially supported by the National Natural Science Foundation of China (No. 50878125) and the 11th Five Plan National Science and Technology Support Project of China, Key technology research on the improvement and protection of urban living environment (No. 2006BAJ02A06). The authors would like to acknowledge Professor XiuYan Guo for her help on experimental design and the participants who volunteered for this study. The authors also would like to thank the anonymous reviewers for their useful and valuable comments on this research.

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Appendix A. Means and standard deviations of each neurobehavioral test

Temperature Letter search Response time (s) Accuracy (%) Overlapping Response time (s) Accuracy (%) Number calculation Response time (s) Accuracy (%) Conditional reasoning Response time (s) Accuracy (%) Spatial image Response time (s)

Accuracy (%) Memory span Memory capacity Picture recognition Response time (s) Memory capacity (%) Symbol–digit modalities test Response time (s) Memory capacity (%) Visual choice RT Response time (s) Accuracy (%)

32

27

24

19

P

68.55 (10.40) 97.08 (3.48)

65.83 (12.98) 98.23 (2.94)

64.83 (11.02) 98.73 (2.15)

71.31 (12.32) 97.48 (2.89)

0.361

204.13 (36.75) 95.01 (3.81)

211.29 (42.66) 95.03 (3.90)

220.23 (49.98) 94.81 (4.84)

222.38 (55.08) 94.97 (4.02)

156.24 (39.00) 94.92 (5.56)

166.66 (40.61) 92.75 (5.70)

163.11 (39.02) 96.96 (2.95)

178.21 (31.37) 94.25 (5.63)

0.027*

142.75 (40.66) 72.78 (26.50)

147.10 (43.34) 64.72 (29.95)

141.13 (39.23) 77.78 (25.99)

149.23 (49.71) 58.33 (25.05)

0.610

146.45 (71.18)

147.35 (59.34)

143.05 (59.05)

161.29

0.607

61.39 (33.00)

66.11 (27.22)

61.67 (28.43)

(97.47) 55.83 (26.00)

0.274

9.81 (1.43)

9.91 (1.18)

9.96 (1.51)

9.78 (1.60)

0.973

19.13 (3.11) 80.75 (11.92)

18.83 (19.84) 79.75 (16.04)

19.55 (4.09) 84.42 (16.54)

19.93 (3.03) 83.75 (15.01)

0.735

P0 0.98

0.248 0.95 0.195 0.987 0.95

0.161 0.69

0.250 0.61

–

0.82

0.284 0.87

136.10 (43.11) 84.17 (17.09)

146.01 (57.33) 87.17 (14.86)

142.3 (48.19) 89.42 (11.33)

145.75 (59.80) 87.67 (22.02)

46.53 (9.77) 98.22 (1.89)

46.55 (9.88) 98.94 (1.41)

46.91 (9.33) 98.69 (1.54)

47.13 (7.58) 98.5 (1.45)

0.590 0.439 0.99 0.887 0.447

*

P < 0.05.

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