Objective: This study explored the interaction between environment and behavior and analyzed the effect of physical environment stimuli and individual differences on environmental perception. Methods: We investigated the effects of two kinds of noise sensitivities (high sensitivity and low sensitivity) and three kinds of noise types (quiet, road traffic noise, and speech noise) on working memory and noise annoyance of college students through questionnaires and experiments. Results: (i) noise sensitivity was positively correlated with neuroticism and negatively correlated with conscientiousness. (ii) The interaction between noise sensitivity and noise type significantly affected the accuracy of working memory. (iii) Both noise sensitivity and the main effect of noise type significantly affected the response time of working memory. (iv) The interaction between noise sensitivity and noise type significantly affects noise annoyance. Conclusion: There were significant differences in working memory performance and subjective noise annoyance among individuals with different levels of noise sensitivity.
Keywords: Noise, noise annoyance, noise type, noise sensitivity, working memory
|How to cite this article:|
Song C, Li H, Ma H, Han T, Wu J. Effects of Noise Type and Noise Sensitivity on Working Memory and Noise Annoyance. Noise Health 2022;24:173-81
*These authors contribute equally to this paper and should be considered as co-first author. There is no symbolic annotation to illustrate this point.
| Introduction|| |
Noise has many negative effects on people’s physical and mental health. In terms of hearing, long-term exposure to strong noise can lead to tinnitus, auditory threshold shift, high-frequency hearing loss, and even irreversible hearing damage and deafness. In addition, noise increases the likelihood of ischemic heart disease and exacerbates adult asthma. It also increases the risk of hypertension and leads to the increase of (triglyceride and cholesterol in blood lipid and the abnormal rate of the electrocardiogram. Guo et al. showed that nonstandard steady-state noise was more likely to cause hostility, terror, psychotic symptoms, and interpersonal sensitivity. Using meta-analysis, the researchers found that compared with the control group, workers in the noise group experienced significantly higher levels of tension (anxiety), anger (hostility), depression (frustration), and fatigue (inertia). Noise can also trigger behavioral changes. Studies by Evans and Stecker show that noise is associated with learned helplessness behavior, as well as behavioral problems such as Attention Deficit and Hyperactivity Disorder (ADHD) in children.
The environment load theory holds that individuals act as an important variable between environment and behavior. When the total amount of information provided by the environment exceeds the individual’s effective processing capacity, the individual’s attention will be distracted and behavioral efficiency will decline. Studies have shown that with the increase in noise, the neurobehavioral adverse effects of workers increase significantly. Neurobehavioral dysfunction refers to the decline of the emotional state and behavioral function of the individual nervous system under the influence of latent and hidden occupational hazards caused by long-term and low-level exposure. Neurobehavioral Core Test Battery recommended by the World Health Organization is generally used to measure environmental load.
According to the environmental stress theory, whether an environmental event is a stress source depends on the individual’s cognitive evaluation. The factors that affect the evaluation include the characteristics of the uncertain situation (such as some kind of noise) and individual differences. Among individual variables related to noise, noise sensitivity is typical and innovative. Job believes that noise sensitivity is an internal state indicating general noise, which can increase the individual’s response to general noise and does not extend to other stimulus modes such as hearing. This internal state not only contains physiological and psychological conditions, but also has something to do with lifestyle and activities. Students who are sensitive to noise perform worse in academic ability, are more uneasy in interpersonal communication, and have a stronger desire for privacy. Individuals with high noise sensitivity have lower health levels and weaker environmental adaptability. As a personality variable, noise sensitivity is associated with neuroticism, extraversion, and other traits and may be affected by emotional motivation, noise meaning, and other variables, but it is relatively stable and continuous. Studies on the mechanism of noise sensitivity show that noise-sensitive individuals generally have an active orientation response and are more likely to produce obvious arousal due to noise. Thalamic-amygdala is the channel responsible for the “fear response” triggered by auditory stimuli. Non-noise sensitivities have a protective effect against noise.
Noise can impair individual cognitive task performance, such as short-term or transient memory. Currently, there are few studies on working memory. Irrelevant sound effect (ISE) is beneficial to explore the effects of irrelevant sound stimulation such as noise on the individual cognitive process, job performance, and physical and mental health. This effect refers to the fact that participants’ performance on short-term memory for visual presentations is impaired when task-irrelevant noise is present, even when they are told not to attend to the auditory stimuli. Using the ISE paradigm, researchers found that verbal noise interferes with recall more strongly than nonverbal noise. Hygge showed that aircraft and road traffic noise impaired recall performance, while train and speech noise had no effect on recall and recognition.
This study was carried out on university campuses. The research on the sound environment of university campuses in China shows that road noise has the strongest negative impact among many noise sources. Road noise also affects the dormitory environment most, because it is usually built on the periphery of the university campus. Language noise is the main source of noise in dormitories, classrooms, dining rooms, and libraries. An investigation of indoor and outdoor noise conducted by Tongji University also shows that speech noise is the noise with the highest probability of occurrence indoors, while traffic noise is the most important noise source outdoors. To sum up, road noise and speech noise are the most closely related noise sources in the daily life of college students. In this study, these two kinds of noise were selected to compare with quiet conditions.
Behavioral constraint theory proposes that once the information provided by the environment is beyond the scope of the individual’s control, it will first trigger the individual’s emotional experience and then interfere with the cognitive task. The three basic processes are loss of sense of control, psychological resistance, and learned helplessness. According to previous studies, the impact of noise on individuals is mainly reflected in three aspects, namely, physiology, psychology, and work results. Noise will stimulate the secretion of adrenaline, leading to the imbalance of the balance process between excitement and inhibition, resulting in physiological changes such as heart rate and respiration, which will cause individuals to become agitated. The theory of the emotional center holds that the functional relationships among the four structures (frontal neocortex, amygdala, hippocampus, and hypothalamus) determine the characteristics of emotional activities, so the stimulation of the nervous system by noise will also indirectly affect emotions. The main psychological consequence of noise is annoyance. It refers to a series of feelings when noise interferes with an individual’s thoughts, feelings, and activities, including annoyance, discomfort, sadness, frustration, and feeling of being offended. Previous investigations have shown that there is a moderate and consistent relationship between noise sensitivity and noise annoyance under noise conditions, and the correlation coefficient is about 0.3. The emotional consequences caused by noise also have an impact on cognitive activities. In order to further verify this point, noise annoyance is considered a noise-induced emotional variable in this study.
In previous studies, the noise-related research was mainly carried out by questionnaire surveys or laboratory experiments. A questionnaire survey is mostly used in field research. Although it has certain practicality, it cannot reveal the causal relationship between variables more deeply. Laboratory experiments can reveal this causal relationship, but there is no unified conclusion due to variables and participant selection. So far, domestic environmental psychology is still in the development stage, and there are few empirical studies on noise and almost no studies on noise sensitivity. Previous studies mostly assumed that the perception and response of stimulus can be studied separately from the stimulus itself, while environmental psychology regards stimulus and perception of stimulus as a whole, and the perception of a stimulus is affected by individual differences, situations, and other factors. This study attempts to confirm the influence of different environmental conditions and the role of individual variables in environmental behavior. Therefore, this study combined questionnaires with experiments to explore the effects of noise types and noise sensitivity on working memory and noise annoyance. Based on this, the following hypotheses are proposed:
H1: Noise sensitivity is positively correlated with neuroticism and negatively correlated with extraversion, and both are positively correlated with accuracy and response time, which can be controlled as covariables.
H2: There was no difference in the accuracy of working memory between the high noise-sensitive group and the low noise-sensitive group under quiet conditions. Under road traffic and speech noise, the accuracy of the high sensitivity group was lower than that of the low sensitivity group. The working memory accuracy of the two groups was the lowest under the condition of speech noise.
H3: In the quiet condition, there was no difference in working memory response between high and low noise-sensitive groups. Under road traffic and language noise, the reaction time of highly sensitive participants was higher than that of low sensitive participants. The response time of the two groups was the highest in the speech noise.
H4: Under the condition of traffic noise and speech noise, the noise annoyance of the high sensitive group was significantly higher than that of the low sensitive group. The two groups had the highest noise annoyance under the condition of speech noise.
| Study|| |
The participants were all college students who took the same public elective course. A total of 150 Chinese versions of the Revised Weinstein Noise Sensitivity Scale and the Chinese version of the Simplified Big Five Personality Scale were distributed to college students, including 131 valid questionnaires. The scores of the noise sensitivity scale were arranged in descending order. According to the ranking, participants ranked in the top 27% of the scale were selected as the high noise-sensitive group, and participants ranked in the bottom 27% of the scale were selected as the low noise sensitivity group. One of them did not participate in the previous questionnaire survey, and one of them had serious hearing impairment, so both were removed. The final number of participants was 60, and 30 in each of the high noise sensitivity groups. The participants came from different majors and grades, including 27 freshmen, 6 sophomores, 20 juniors and 7 seniors, and 22 males and 38 females. The participants were in good health with normal hearing and participated in the experiment for the first time.
Materials and instruments
Three sound conditions (quiet/road traffic noise/speech noise) were selected as the subjects’ internal variables. In quiet conditions, the background noise is about 35 dB, and participants need to wear headphones.
Road traffic noise is recorded with a lenovo B620 recording pen from 12:00 to 12:20 at noon at the Wudaokou intersections. The loudness of the noise is 70 dB and the length is about 8 minutes. As there are many vehicles and few people in this period, the road traffic noise mainly consists of the roar, horn, and wheel friction of vehicles. The sound belongs to the irregular noise recorded in the natural situation, which is consistent with the definition of noise in this experiment.
The language noise is recorded by the software Goldwave, and the content is from a Chinese talk column, pure human voice dialogue, without background music. The noise is meaningful but not task-related. The loudness of the noise is 70 dB and the length is about 8 minutes. Similarly, the sound is unpredictable and uncontrollable and meets the definition of noise. Speech noise may interfere with cognitive tasks because it is meaningful, similar to stimuli in the task, or because changes in the rhythm of speech impede the performance of the participant.
A GM1357 sound level meter with accuracy up to 1.5 dB iis used to measure noise loudness. The sound level meter is used to measure the loudness of road traffic noise and speech noise. The specific operation is through an audio software to play two kinds of noise at the same time, adjust the volume, select a sound level (human ear), and slow speed to read the instant decibel value until a certain loudness under the sound level meter reading range is stable between 68 and72 dB and the average noise level is 70 dB.
Working memory tasks
The processing interference paradigm developed by eprime 2.0 was used to complete the cognitive task under the interference of a series of stimuli unrelated to the task. N-back paradigm was adopted in the working memory task because it was a continuous processing task and was less affected by gender and other factors. The 2-back paradigm in n-back is of moderate difficulty but requires some strategy to complete. In order to prevent ceiling or floor effects, the 1-back or 3-back paradigm is not used in this stud. A random number from one to nine appeared at the center of the screen, and participants were asked to determine whether the current number was the same as the number that appeared next to it (the first two numbers were not required to judge). The presentation time of each number is 500 ms, and the time between numbers is 1300 to 1500 ms. The experiment was divided into practice and formal stages. In the practice stage, participants were required to complete a 20-digit exercise and were given two kinds of feedback: correct and false. In the formal stage, participants were required to judge 90 numbers without providing feedback. The processing time of each experiment was 3 minutes, and the reaction ratio was 1:1.
(1) Noise sensitivity scale. The Chinese Version of the Weinstein Noise Sensitivity Scale was selected, with a total of 15 questions. The internal consistency reliability was 0.866, the retest reliability was 0.743, and the split reliability was 0.871, which were significantly correlated with the score of the noise annoyance scale (r = 0.499), showing good reliability and validity.
(2) NEO Five-Factor Inventory (NEO-FFI). A brief version of the Big Five-factor Personality Scale was selected,NEO-FFI) with a total of 60 questions, including five dimensions: neuroticism, extraversion, agreeableness, openness, and conscientiousness.
(3) Noise annoyance scale. The noise annoyance level was measured according to ISO/TS 15666 standard. The scale is a 10-point self-rating scale with one item, with a scale of 1 to 10 representing “not upset” to “extremely upset.” To fit the experiment, the statement was slightly changed to “How much did the noise in the task bother you?”
Instruments and experimental sites
A 15.4-inch laptop equipped with eprime2.0, Windows audio player software, and headset was selected. The experiment was conducted in the Cognitive Psychology Laboratory of the Psychology Department of Beijing Forestry University from 7 a.m. to 12 a.m.
Experimental design and procedure
A mixed experimental design of 2 (noise sensitivity: high and low) × 3 (noise type: quiet, road traffic noise, and speech noise) was adopted. The intergroup variable was noise sensitivity, and the intragroup variable was noise type. The dependent variables were working memory performance, accuracy, and response time. In addition, noise annoyance was considered the emotion variable caused by noise.
Since each participant was required to accept three experimental treatments, the presentation of experimental materials was in Latin square balance. After the correct rate reached 80%, the participants entered the formal test. In the formal experiment, the experimental processing was carried out simultaneously with the noise introduction and the task (3 minutes). After both kinds of noise treatment, the participants were asked to fill in the noise annoyance scale. The specific situation is shown in [Figure 1]. At the end of one treatment, participants were allowed to rest for 1 minute until all treatments were completed.
SPSS22.0 was used for descriptive statistics of experimental data, followed by 2 (noise sensitivity: high and low) × 3 (noise type: quiet, road traffic noise, and speech noise) analysis of variance and simple effect test.
| Results|| |
Noise sensitivity and personal traits
The average score and standard deviation of the noise sensitivity scale were 61.65 and 11.2, respectively. And the dataset of the score of noise sensitivity scale was generally a normal distribution. An independent sample t test was conducted on the scores of the high and low sensitivity groups. The results revealed that there was an extremely significant difference in noise sensitivity between the two groups (t = 11.790, P < 0.01). Correlation analysis found that noise sensitivity was positively correlated with neuroticism in the Big Five, negatively correlated with conscientiousness and extraversion, and not significantly correlated with other personality factors [Table 1].
Previous studies have found that individuals with high neuroticism or low extraversion may perform worse on cognitive tasks. [Table 1] showed that noise sensitivity is positively correlated with neuroticism and negatively correlated with conscientiousness and extraversion. Since neuroticism is also highly correlated with extraversion and conscientiousness, the results were inaccurate, so a partial correlation analysis between the three personality dimensions and noise sensitivity was needed. The results indicated that noise sensitivity was positively correlated with neuroticism (r = 0.267, P < 0.01), negatively correlated with conscientiousness (r = –0.190, P < 0.05), and did not reach a significant level with extraversion (r = –0.039, P = 0.787). Thus, neuroticism and conscientiousness may be controlled as covariates.
According to the analysis process of covariates, the correlation analysis was carried out between neuroticism and conscientiousness and the accuracy and reaction time of the participants under the three processing conditions. The results showed that there was no significant correlation between the two personality factors and the accuracy and reaction time of the three noise types (P > 0.05), so there was no need to control neuroticism and conscientiousness as covariates.
Working memory under different noise types and noise sensitivity conditions
Accuracy of working memory under different noise types and noise sensitivity
The accuracy of the participants’ working memory task performance was used as a dependent variable for statistical analysis, and repeated measures analysis of variance was used to test whether the accuracy was significantly different between the two noise sensitivity levels and the three noise types and whether there’s any interaction between the two. [Table 2] showed that the accuracy rate of participants is the highest under quiet conditions, followed by road traffic noise and language noise. Under the conditions of quiet, road noise, and language noise, the accuracy of the low sensitive group was higher than that of the highly sensitive group.
The normality test and homogeneity of variance indicated that the data conformed to the normality hypothesis and homogeneity of variance hypothesis (P ＞ 0.05) and had the condition of repeated measures analysis of variance. The results showed that noise type had a significant effect on the accuracy of the dependent variable working memory task, F (1.420,82.379) = 261.422, P ＜ 0.01, η2 = 0.818. Noise sensitivity had a significant effect on the accuracy, F (1,56) = 32.743, P ＜ 0.01, η2 = 0.361. The effect of noise type and noise sensitivity on the accuracy was very significant, F (1.420,82.379) = 71.508, P ＜ 0.01, η2 = 0.552.
Because the interaction between noise sensitivity and noise type was very significant, a simple effect analysis is needed. The results revealed that noise sensitivity had a significant effect on the accuracy of different noise types, P ＜ 0.01. Under the quiet condition, there was no significant difference in the accuracy rate between the high-sensitivity participants and the low-sensitivity participants. Under the road traffic noise condition, the accuracy rate of the high-sensitivity participants was lower than that of the low-sensitivity participants, P ＜ 0.01. Under the language noise condition, the result was the same as above, and the difference in accuracy was larger, P ＜ 0.01. The accuracy of the highly sensitive participants was the highest in the quiet condition, followed by traffic noise, and the lowest in language noise, P ＜ 0.01. The results of low noise sensitivity participants were the same, but the difference was reduced, as shown in [Figure 2].
|Figure 2 Interaction between noise type and noise sensitivity on the accuracy of working memory|
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The reaction time of working memory under different noise types and noise sensitivity
The reaction time of the working memory task was used as the dependent variable for statistical analysis. The reaction time of highly sensitive participants was lower than that of low sensitive participants under the three conditions of silence, road noise, and language noise. From quiet conditions to road traffic noise, then to language noise, the reaction time of the participants gradually decreased [Table 3].
The normality test and homogeneity of variance indicated that the data conformed to the normality hypothesis and homogeneity of variance hypothesis (P ＞ 0.05) and had the condition of repeated measures analysis of variance. The results showed that the main effect of noise type on working memory task was significant, F (2,116) = 4.784, P ＜ 0.05, η2 = 0.076. The main effect of noise sensitivity on reaction time was significant, F (1,58) = 6.154, P ＜ 0.05, η2 = 0.09. The effect of noise type and noise sensitivity on reaction time was not significant, which means there was no interaction between them. The accuracy of working memory tasks under different noise types and noise sensitivity conditions was tested after the experiment. The results revealed that there was no significant difference in the reaction time of participants under quiet and road traffic noise conditions. Under the condition of language noise, the reaction of the participants was significantly different from that of the other two kinds of noise. The reaction time under language noise was the lowest (P ＜ 0.05). There was a significant difference in reaction time between high and low sensitive groups (P ＜ 0.05), and the reaction time of the high sensitivity group was shorter than that of the low sensitivity group.
Effects of different noise types and noise sensitivity on noise annoyance
Noise annoyance was used as the emotion-dependent variable in the experiment. Repeated measures analysis of variance was used to test whether noise annoyance had a significant difference between the two noise sensitivity levels and the three noise types and whether there was an interaction between them. [Table 4] indicated that the subjective noise annoyance of highly sensitive participants is higher than that of low sensitive participants under road traffic noise and language noise. From the road traffic noise to the language noise, the noise annoyance of the participants increased gradually.
The normality test and homogeneity of variance manifested that the data conformed to the normality hypothesis and homogeneity of variance hypothesis (P ＞ 0.05) and had the condition of repeated measurement analysis of variance. The subjective noise annoyance scores of two noise-sensitive participants under two noise conditions were analyzed by repeated measurement of variance. The results showed that noise type had a significant effect on noise annoyance, F (1,58) = 48.531, P ＜ 0.01, η2 = 0.456. Noise sensitivity had a significant effect on noise annoyance, F (1,58) = 23.999, P ＜ 0.01, η2 = 0.293. Noise type and noise sensitivity had significant effect on noise annoyance, F (1,58) = 9.943, P ＜ 0.01, η2 = 0.146.
Because the interaction between noise sensitivity and noise type was very significant, a simple effect analysis was required. The results indicated that noise sensitivity had a significant effect on noise annoyance scores of different noise types, P ＜ 0.01. Under the condition of road traffic noise, the noise annoyance score of high sensitive participants was significantly higher than that of low sensitive participants, P ＜ 0.01; under the condition of language noise, the result was the same as above, and the score of highly sensitive participants was higher. The results of low sensitivity participants were the same as above, but the difference was reduced, as shown in [Figure 3].
|Figure 3 Interaction of noise type and noise sensitivity on noise annoyance|
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| Discussion|| |
Noise sensitivity and five-factor personality
There have been many studies on the relationship between noise sensitivity and personality. Some researchers believe that sensitivity to noise or other stimuli involves an individual’s internal state and is physiologically related to the continuous arousal of the hippocampus, amygdala and hypothalamus, and other areas of the brain. As a personality trait that is less involved, the physiological structure of noise sensitivity cannot be entirely understood and confirmed. However, with the help of the Big Five Inventory (BFI), it can be comprehensible and reflected. The study indicated that noise sensitivity was related to neuroticism, introversion, and extraversion. Belojevic and Jakovljevic view neuroticism as the best predictor of subjective noise sensitivity. Tsai et al. argue that neurotic individuals performed worse on learning tasks. It can be inferred that personality is associated with noise sensitivity, cognitive performance, and even emotional changes. To verify the noise sensitivity, the BFI was selected in this study for its practicality and a higher degree of coincidence with the Eysenck Personality Questionnaire. The results demonstrated that noise sensitivity was positively correlated with neuroticism and conscientiousness, which were not controlled as covariates. This may be because individuals with high neuroticism tend to be anxious and distracted, while conscientiousness was associated with impulse control. Individuals with low conscientiousness were prone to be less self-disciplined and more susceptible to noise. In the absence of control over conscientiousness and neuroticism, extraversion was also negatively correlated with noise sensitivity. But there was no statistically significant correlation, which needs to be further studied. Inconsistent with the hypothesis, conscientiousness and neuroticism were not associated with working memory accuracy or reaction time. It may be because the personality factors are overall complex, and the noise sensitivity contained more personality components, which jointly affected the results of the experiment.
Effects of noise sensitivity and noise type on working memory accuracy and reaction time
The results manifested that the interaction between noise sensitivity and noise type affected the accuracy. Research by Enmarker shows that language noise mainly damages the memory of meaningful content and has little interference with meaningless statements. Sandrock et al. verify that highly sensitive participants performed worse on cognitive tasks under traffic noise. In this study, under the quiet condition, the accuracy of participants with high and low sensitivity was high and the difference was not significant, indicating that after practice, the two groups of participants had roughly the same understanding of the task, and the impact of other variables was excluded. Under the condition of road traffic noise, the accuracy of the two groups decreased, indicating that noise played a role in distraction and inhibition of the performance of the participants. The scores of the highly sensitive participants dropped more, manifesting that their anti-interference ability was worse, leading to more negative emotional experiences. Compared with the traffic noise, the participants were also guided by the implied meaning under the condition of language noise, resulting in a further decrease in inaccuracy.
Both noise sensitivity and noise type had significant effects on reaction time. Usually, the n-back task only considers the accuracy, but the research supports that reaction time is one of the indicators of a personality test. The reaction time of participants who are impulsive and anxious is faster. This study confirmed that neuroticism and conscientiousness were correlated with noise sensitivity. So it is speculated that noise sensitivity, as a personality trait, might affect the relationship between noise type and working memory reaction time. A study on the reaction time of coal mine noise and miners reveals that the average reaction time increased with the increase of noise level, with a significant impact of more than 75 dB. However, some researchers have come to the opposite conclusion that participants respond faster under the influence of noise. This study hypothesized that the participants’ cognitive load increased and their attention was diverted under noise conditions, while the highly sensitive participants had a lower tolerance to noise and a longer reaction time. But this study found that there was no difference in reaction time under quiet and road traffic noise, and the reaction time was shorter under language noise, which was not consistent with the hypothesis. According to the negative-impact-avoidance model, negative emotion is a mediator between unpleasant events and aggressivity, with the relationship between unpleasant events and aggressivity forming an inverted U-shaped curve. Before a certain point, the more negative feelings you have, the more aggressive you will be. And once you get past that point, it becomes even more important to avoid stress and pain. Similarly, language noise may cause more cognitive load than quiet and road traffic noise, and the negative effects are more likely to reach a certain threshold. Compared with the effect of noise on attention, which interfered with the completion of the experimental task, verbal noise may make participants more anxious to avoid the noise source. Highly sensitive participants had more active directional reflexes and were more eager to get rid of noise, resulting in faster responses and shorter response time.
Effects of noise sensitivity and noise type on noise annoyance
The results indicated that the interaction between noise type and noise sensitivity affects noise annoyance. The highly sensitive participants had higher scores of noise annoyance under both noise conditions, possibly because the uncontrolled noise made them feel “violated”. Weinstein argues that noise-sensitive individuals would be more agitated in generally annoying situations. Compared with road traffic noise, language noise will increase the cognitive load. And the original acquisition of memory strategy will be interfered, so the feeling of annoyance will be heavier.
Lan’s research manifests that indoor environmental stimuli affect subjective evaluation, information processing, and neurophysiology (in which subjective assessment involves an individual’s perception of environmental stimuli and the resulting emotions). These three aspects are connected and constitute an organic whole that determines the efficiency of individual work. Therefore, environmental stimuli and individual differences can affect working memory through emotion. In this study, we confirmed that different types of noise environmental stimuli had negative effects on emotion and working memory, but no further evidence had been taken on the pathways of the two effects. This is an area where future research can improve.
According to the environment-behavior theory, factors such as physical environment stimulus and individual differences influence each other and jointly determine the perception of the environment. Once the stimulation is excessive or the control is lost, the individual will perceive beyond the optimal range of stimulation, resulting in stress. If the coping is not successful, it can lead to cumulative effects (reduced performance, negative emotions, etc.). In general, the different excitability of different noise itself, the best range of stimulus perceived by the individual (the highly sensitive participants are smaller), and the coping ability are different, which result in different emotions and work results.
Despite the major strengths of our analysis, there are several limitations to this study. First, these measures were exclusively self-reported, which may lead to reporting bias. Second, the data were obtained from college students, which requires that caution be taken when generalizing the findings to other populations. Third, the experimental setup was artificial, which should be further verified in real-life conditions.
| Conclusions|| |
(1) Noise sensitivity was positively correlated with neuroticism and negatively correlated with conscientiousness. (2) The interaction between noise sensitivity and noise type significantly affected the accuracy of working memory. (3) Both the noise sensitivity and the main effect of the noise type significantly affected the reaction time of working memory. (4) The interaction between noise sensitivity and noise type significantly influenced noise annoyance.
This research was funded by the National Forestry and Grassland Administration, Forestry Soft Science Research: Technical Support Research on Forestry Restorative Functions in National Forests (fund no.: 2018-R17).
Conflicts of interest
Whether or not this heading level is incorrect, it does not belong in the conclusion section.
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Department of Psychology, School of Humanities and Social Sciences, Beijing Forestry University, Beijing 100083
Source of Support: None, Conflict of Interest: None
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3], [Table 4]