Natural soundscapes enhance mood recovery amid anthropogenic noise pollution

Lia R V Gilmour; Isabelle Bray; Chris Alford; Paul R Lintott

doi:10.1371/journal.pone.0311487

. 2024 Nov 27;19(11):e0311487. doi: 10.1371/journal.pone.0311487

Natural soundscapes enhance mood recovery amid anthropogenic noise pollution

Lia R V Gilmour ¹, Isabelle Bray ², Chris Alford ^2,³, Paul R Lintott ^1,^*

Editor: Yuan Zhang⁴

PMCID: PMC11602051 PMID: 39602385

Abstract

In urbanised landscapes, the scarcity of green spaces and increased exposure to anthropogenic noise have adverse effects on health and wellbeing. While reduced speed limits have historically been implemented to address traffic safety, their potential impact on residents’ wellbeing, especially in relation to engagement with natural soundscapes, remains understudied. Our study investigates the influence of i) natural soundscapes, including bird song, and ii) the addition of traffic noise to natural soundscapes at two speeds (20 mi/h and 40 mi/h) on mood. We found that natural soundscapes were strongly linked with the lowest levels of anxiety and stress, with an increase in stress levels associated with mixed natural soundscapes with the addition of 20 mi/h traffic noise and the highest levels with 40 mi/h traffic noise. Higher levels of hedonic tone, indicative of positive mood, was noted with natural soundscapes, but diminished when combined with 40 mi/h traffic noise. Our results show that anthropogenic soundscapes including traffic sounds can mask the positive impact of natural soundscapes including birdsong on stress and anxiety. However, reducing traffic speeds in cities could be a positive intervention for enhancing access to nature. Technological solutions, such as the widespread adoption of hybrid and electric vehicles, and urban planning strategies like integrating green spaces into transit routes, offer potential opportunities to mitigate the impact of noise pollution and benefit humans in urban environments.

Introduction

Since the industrial revolution, many landscapes have become increasingly characterised by their anthropogenic footprint and this has profoundly affected both human health and wellbeing, as well as ecological communities [1]. Access to nature can lead to reduced risk of obesity and dementia, increase life satisfaction, aid stress recovery and provide restorative benefits (e.g. [2–5]. Furthermore, faced with global biodiversity and climate crises, increasing connection between people and nature is also important for improving engagement in environmental conservation actions [6]. Consequently, better understanding of the relationship between humans and nature in urban areas is vital.

Beneficial effects of nature may depend on an individual’s background, perception of biodiversity, its restorative potential and the senses used to perceive it [5,7]. Recently, various soundscape playback studies have examined the potential impacts of exposure to natural sounds (reviewed by [8]) and have shown that natural soundscapes, can aid health recovery and attention restoration in participants [9–14]. Studies have reported both physiological and psychological benefits to health from listening to natural sounds or soundscapes [8]. For example, natural sound exposure has been shown to lower blood pressure, heart and respiratory rates, as well as self-reported stress and anxiety [8,13,15]. Listening to natural sounds can also improve attention restoration and increase cognitive performance [8,13,14]. Responses to nature, including natural soundscapes, may also be dependent on factors such as age, sex and socio-cultural experience e.g. childhood connection to nature [11,16,17], though more research is needed to understand and tease apart the influence of these factors.

Conversely, anthropogenic soundscapes, such as those including traffic or aircraft noise, can have negative effects on human health and wellbeing with physiological and psychological effects recorded across the literature [18–22]. Exposure to sounds made by traffic infrastructure (including rail, road and air traffic noise) has been recorded to increase the risk of depression [21], severe anxiety [22] and physiological stress responses such as increase in cortisol levels [18]. Indeed, psychological effects of listening to traffic are likely to be caused by direct adverse impacts and changes in the central nervous system, causing for example changes to brain tissue and neuroinflammation [23]. Long-term effects of exposure to traffic noise also include increased instances of cardiovascular disease, risk of stroke, diabetes, hypertension and loss of hearing [19]. Higher traffic speeds are associated with higher noise pollution and perceived annoyance levels in people exposed to the sounds [24]. However, to our knowledge there has been no study to date that has examined the impact of lowering road traffic speeds on the sonic environment people are exposed to in urban environments and how this affects wellbeing.

Historically, reduced speed limits have been introduced to slow traffic and reduce the number and severity of road traffic collisions. International agencies including the World Health Organisation, World Bank and the Organisation for Economic Co-operation and Development have promoted the implementation of reduced speed limits across residential roads (e.g. reducing speed limits in the UK from 30 mi/h down to 20 mi/h, equating to a reduction of 50 to 30 km/h in equivalent traffic regimes). Although reduced traffic speeds are strongly associated with reductions in road traffic casualties (e.g. [25]), the current move towards lower speed limits is only in part powered by the injury prevention agenda. Reduced speed limits lessen noise pollution, as well as having proportionately larger positive impacts for poorer communities which suffer from higher levels of traffic pollution [26], thereby reducing inequalities in health. Also significant is the desire to reduce obesity though the promotion of physical activity in the form of walking, cycling and active play [26]. A reduction in background noise may also allow urban populations to hear wildlife more clearly, however the potential benefits of reducing speed limits on wellbeing amongst residents has not routinely been researched.

In this study, we aimed to test whether listening to natural soundscapes can aid stress recovery and reduce anxiety in student participants exposed to noise pollution and whether reducing traffic speeds affects psychological responses to these natural sounds. Specifically, we aimed to use two widely applied subjective scales commonly used to measure human mood to test to what extent self-reported anxiety, stress and pleasure are affected by i) natural soundscapes and ii) mixed natural and anthropogenic soundscapes, with the addition of traffic noise recorded on roads with two common speed limits in the UK, 20 mi/h and 40 mi/h (e.g. similar to 30 and 60 km/h). We also tested whether general mood state, age, gender and inherent preference for natural environments affected mood recovery in response to natural and mixed natural and anthropogenic soundscapes.

Methods

Participants

Participants (n = 68) were recruited from the University of the West of England (UWE) Psychology participant pool, online on the UWE student’s union survey page and via email between 5^th March-14^th April 2021. Written informed consent was obtained from all participants prior to their participation and they were given the option to withdrawn from the experiment at any time. Psychology students that participated received an incentive of one course credit, but other students were not incentivised. All students that took part were either science, psychology or social science students. We excluded participants that had been diagnosed with or currently taking prescribed medication for psychiatric conditions such as anxiety and depression, as low mood and medication could influence subjective responses. We also wanted to avoid inducing increased stress response in those already suffering from anxiety and depression. Ethical approval was obtained from the university ethics committee prior to the experiment commencing (University of the West of England approval code: HAS.20.11.036).

Soundscapes

We created three 3-minute soundscape files for use in playback experiments using Audacity (v.2.4.2, Audacity Team, open-source software, https://www.audacityteam.org/). All three soundscapes included a base of a natural soundscape recording, made at sunrise in West Sussex, UK using a parabolic reflector microphone system (Talinga, Tobo, Sweden). The natural soundscape included a range of common UK bird species likely to be heard in a typical dawn chorus including those recorded on the RSPB’s top 25 Big Garden Birdwatch [27] and some rarer species such as the nightingale (Luscinia megarhynchos). We added anthropogenic soundscapes including traffic noise to the natural soundscape to create the other two mixed natural and anthropogenic soundscapes. Anthropogenic soundscapes including road traffic sounds were recorded on two roads (20 mi/h and 40 mi/h limits) in Bath, UK on the same morning at peak ‘rush hour’ between 8.30–9.00 am, using a Zoom H5 portable recorder (Zoom Inc. Tokyo, Japan) at 1 meter from each road. Traffic volume was consistently high between the two roads and contained rush hour traffic of mainly cars and buses. Soundscapes used in playback experiments therefore included i) a natural soundscape (‘natural’), ii) a mixed natural + anthropogenic soundscape with 20 mi/h traffic (‘mixed 20’) and iii) a mixed natural + anthropogenic soundscape with 40 mi/h traffic (‘mixed 40’).

Experimental design

Data were collected using a bespoke survey designed and administered online using Qualtrics XM software (Qualtrics International, Seattle, United States). Participants were given a basic background and information about the experiment, including that it contained a task to listen to soundscapes and watch videos, but not given any information about the hypotheses (see S1 Doc for exemplar experiment procedure). Participants took part in the experiment in one sitting online for 30 minutes to 1 hour (depending on the time taken to answer questions) (Fig 1). Each participant was exposed to three rounds of a stressor video for 1 minute and soundscape play back of 3 minutes and answered questions after each stressor and each soundscape (12 minutes of exposure to stressors and soundscape in total). At the end of the playback experiment, participants were asked demographics questions (age, gender, ethnicity) and some other questions to gain an understanding of any participant bias (see Demographics and other participant information).

Participants were asked to use noise cancelling (over the ear) headphones if available, or ear buds (in the ear) or laptop/computer speakers if they did not have access to headphones. Before starting the experiment, participants were asked about their mood in general (see Subjective Measures below), and then asked to do a sound test. During the sound test, participants were asked to put on their headphones, and click a test link that played some sounds of human talking. They were then asked to adjust their headphones to a level that was comfortable, but loud enough to immerse themselves in the sounds. Talking was chosen as the test sound as it was sufficiently different from the sounds used in the main experiment.

The experiment was comprised of three sections (Fig 1). In each section, each participant was exposed to a stressor video and then asked to rate their current mood (see Subjective Measures below). Participants were then exposed to one of the three soundscapes and again asked to rate their mood, allowing a measure of mood recovery. All participants were played all three stressor videos and all three soundscapes. The order of soundscapes was randomised between participants, but the stressor videos were not (Fig 1). Soundscapes were randomised to control for any order effects, with each participant exposed to all three soundscapes as part of the repeated measures design.

Stressors

Stressors are often used in psychological research as a way of standardising mood state, before subjecting a participant to a condition [11,15], which in this case was a soundscape playback. We created three multi-modal cognitive stressors including arithmetic, based on methods of similar studies [11,15]. All stressors were 1-minute long video comprised of a written maths question, which was obscured by flashing between different colours of text and background, along with stressful sounds (e.g. either a squeaky noise, annoying music or an alarm beeping). Each video contained a different maths question, sound, and colour pallet. Stressor order was the same for each participant, due to constraints within the survey program design architecture, but we included stressor as a fixed effect in statistical analysis to control for any effect on subjective measures (see Statistical Analysis below).

Subjective measures

In order assess participants mood before and during the experiment, we used two measures commonly used in psychological research and clinical settings to diagnose anxiety and measure acute shifts in mood. Two measures were used to ensure internal consistency in the experiment (i.e. if scores from the two measures mirrored each other, then they were both more likely a true representation of mood). We measured a participant’s general mood as subjective ‘trait’ anxiety (STAI-T) before the experiment, using a validated short form of the State-Trait Anxiety Inventory (STAI) scale (S1 Fig) [28,29]. We also measured a participant’s subjective mood changes (i.e. their current mood ‘state’) during the experiment, including after each of the three stressor videos and after each soundscape playback. We measured subjective mood as current ‘state’ anxiety, stress, and pleasure (hedonic tone). State anxiety is defined as a temporarily anxious emotional state influenced by the current situation, hedonic tone is a measure of pleasure in response to a situation, and subjective stress, the level of stress or tension currently felt. We measured current mood in terms of subjective stress and hedonic tone using a short form of the University of Wales Institute of Science and Technology Mood Adjective Checklist (UWIST MACL) [30]. Participants were asked to rate how they felt currently in terms of four mood items (relaxed, nervous, happy, sad) on a 4-point Likert scale (S2 Fig). Current stress was scored as nervous plus reverse relaxed scores and hedonic tone as happy plus reverse sad scores. Therefore, increased subjective stress and increased pleasure (hedonic tone) were represented by higher scores.

We also measured current mood in terms of anxiety (STAI-S) using a validated short form of the STAI scale (S3 Fig) [28,29]. Both STAI-S and STAI-T scales included three anxiety present and three anxiety absent items, rated on a 4-point Likert scale (S1 and S3 Figs). Both STAI-S and STAI-T scores were calculated as the sum of anxiety present items and reverse anxiety absent items scores, so that higher scores represented increased current and general anxiety.

Demographics and other participant information

Self-selected student participants are often used in studies of this type [15,31,32] However, despite students being generally regarded as appropriate subjects for this type of study [33], we wanted to understand any inherent biases that existed in the participant pool. We therefore collected a range of participant information before the main playback experiment to gain an understanding of the biases that may exists in our sample. We then chose a subset of that participant information for use in analysis (see Statistical Analysis), chosen as they were the most likely to influence a person to being more or less sensitive to natural soundscapes, which could in turn bias the results. We collected demographic data (age, ethnicity, gender), all commonly measured in similar studies examining wellbeing in response to soundscape playbacks (e.g. [10,13]). We also included several questions related to participants’ relationship with their environment. We asked whether participants live, work and grew up in urban, semi-rural or rural environments and whether they had a preference for natural or urban environments (scale: none, slight, strong preference for either urban/rural), whether participants noticed sounds in their environment (4-point scale: not sure, sometimes, often, very often). We also included the type of listening device used to take part in the experiment (in ear or over ear headphones or speakers), as this might influence the ability of the participant to fully engage in the experiment. As bird sound was prominent in all three soundscapes, to rule out any effect of bird phobia, we also included a question asking about phobias in general and included birds in a list of other common phobias (e.g. bats, spiders).

Statistical analysis

We analysed all data using the R package lme4 (v.1.1–26 [34]) in R Studio (R version 4.0.5) using generalized linear mixed models (GLMMs). We analysed three subjective mood measures datasets, collected as part of the main soundscape playback experiment. Subjective mood measures included stress and hedonic tone (UWIST MACL) and anxiety (STAI-S). We included participant information data included in the analysis a general (trait) anxiety measure (STAI-T), demographic variables (age, gender), inherent preferences for nature scores (preference for natural environments).

Analysis of subjective mood measures

Response variables included stress, hedonic tone and anxiety scores calculated from scores recorded after each soundscape. Fixed effects included in the full model were soundscape (factor variable with levels: ‘natural’, ‘mixed 20’, ‘mixed 40’), STAI-T (continuous variable), age (continuous variables), gender (factor coded as binary: 1 = male, 0 = female, NA = non-binary), preference for natural environments (factor coded as a binary score: 1 = slight and strong preference for natural environments, 0 = slight and strong preference for urban environments or no preference). Each participant was exposed to all stressors and all soundscapes. However, soundscape order was randomised within the Qualtrics software, whereas stressor order was not. We therefore included stressor identifier (factor variable with levels: A, B, C) as a fixed effect in the full model to control for any effect of stressor type or order on the outcome measures. We also chose to use mixed effect models due to their ability to include random effects (as well as fixed effects) and included the random effect of participant number. Using this mixed modelling method allowed us to control for order of the fixed factor effects soundscape and stressor as well as any inherent variation in stress, hedonic tone and anxiety amongst participants.

Modelling procedure

Final models were selected using a backwards step-wise model selection procedure to find the most parsimonious yet best fitting model. Fixed effect variable terms were removed sequentially, and likelihood ratio tests (LRTs) (ANOVA) were performed between models with and without that term. Variables that were significant in LRTs were retained in the final model and non-significant terms were removed. Models were also compared based on their second order Akaike Information Criterion (AICc) and the model with the lowest AICc that contained all significant terms was chosen as the final model. Relevant interaction effects were also tested in the same way. Tukey contrast tests were also performed on final models to test for differences between soundscape levels. Statistics are presented in tables, including model summary statistics (estimates and s.d. for fixed effects and variance and s.d for random effects), likelihood ratio tests (χ², d.f. and p value) and Tukey contrast statistics (estimate, SE, z and p values). We tested whether residuals were normal for LMMs and validated all models using a simulation method in the Dharma package in R [35], which tested for homogeneity of variance, zero inflation and overdispersion (v0.4.5).

Results

Participant information and demographics

Participants (n = 68) were mainly white British female undergraduate in their first- or second year studying science and psychology/social science students, living and working in an urban environment (S1 Table). Participants had an age range of 18–42. Most participants (66.18%) either had a slight or strong preference for natural environments and 22.06% and 38.24% reported noticing sounds sometimes and very often in their environment. Most participants grew up in semi-rural (39.71%) or urban (44.12%) environments. Only 1.4% of participants had a bird phobia. Most participants used headphones (in ear 41.18%, over ear 36.76%) to listen to the soundscapes and 22% listened on laptop speakers.

Subjective measures

Current stress and anxiety were lower and pleasure (hedonic tone) scores higher in participants after experiencing all three soundscapes when compared to the three stressors (Table 1, Fig 2). There was a significant effect of soundscape treatment on all three subjective measures (Table 2, see S3 Table for model selection statistics). Current stress and anxiety scores increased across soundscape treatments (Fig 2; S2 Table). We recorded significant differences between the ‘natural’ and ‘mixed 40’ treatments for current stress (UWIST MACL) and ‘natural’ vs ‘mixed 20’ and ‘natural’ vs ‘mixed 40’ treatments for current anxiety (STAI-S) (Table 3). Pleasure scores (hedonic tone) were lower after exposure to the ‘mixed 40’ when compared to both ‘natural’ and ‘mixed 20’, however this was marginally non-significant when analysed with post-hoc Tukey contrasts (Table 3), despite soundscape treatment being a significant fixed effect when analysed with a GLMM (S2 Table).

Table 1. Descriptive statistics (mean and s.d.) for subjective measures including UWIST MACL stress and hedonic tone (hedtone) and STAI state anxiety scores for 3 stressors and 3 soundscape treatments, including a natural soundscape and mixed natural and urban soundscapes with 20 and 40mi/h traffic noise (‘natural’, ‘mixed 20’, ‘mixed 40’).

	Stress		Hedtone		Anxiety
Stressor/soundscape	Mean	s.d.	Mean	s.d.	Mean	s.d.
Stressor A	5.87	1.68	5.16	1.30	15.66	3.87
Stressor B	5.12	1.44	5.35	1.29	14.94	4.00
Stressor C	4.82	1.41	5.62	1.39	14.63	3.93
Natural	3.03	1.06	6.26	1.46	9.57	2.86
Mixed 20	3.28	1.05	6.32	1.10	10.87	3.24
Mixed 40	3.54	1.25	6.01	1.17	11.32	3.27

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Higher UWIST MACL stress and hedtone scores represent higher levels of subjective stress and pleasure respectively, and higher STAI state scores represent increased anxiety.

Fig 2 — Stress (UWIST MACL) was scored as nervous plus reverse relaxed scores and hedonic tone as happy plus reverse sad scores. Therefore, increased subjective stress and increased (positive) hedonic tone were represented by higher scores. Anxiety scores were calculated from the STAI-S scale as the sum of anxiety present items and reverse anxiety absent items scores, so that higher scores represented increased anxiety. Significance stars are presented for Tukey contrasts (. = *p < 0*.1, * = p < 0.05, ** = p < 0.01, *** = p < 0.001).

Table 2. Likelihood ratio test statistics for GLMMs for three subjective measures: UWIST MACL stress and hedonic tone (hedtone) and STAI-S (state) anxiety, including fixed effects soundscape treatment, STAI trait score (STAI-T), preference for natural environments, gender, age and stressor.

Model	Fixed effects	χ²	df	p	Significance
Stress (UWIST)	Soundscape	11.20	2	p < 0.01	^**
	STAI-T	4.03	1	0.04	^*
	Pref natural	0.25	1	0.62	NS
	Gender	0.16	2	0.92	NS
	Age	0.11	1	0.74	NS
	Stressor	1.81	1	0.18	NS
Hedtone (UWIST)	Soundscape	6.81	2	p < 0.05	^*
	STAI-T	4.01	1	p < 0.05	^*
	Stressor	5.24	1	p < 0.05	^*
	Pref natural	0.43	1	0.51	NS
	Gender	1.46	2	0.48	NS
	Age	0.10	1	0.75	NS
Anxiety (STAI-S)	Soundscape	22.34	2	p < 0.001	^***
	STAI-T	6.14	1	p < 0.05	^*
	Pref natural	0.25	1	0.62	NS
	Gender	1.32	2	0.52	NS
	Age	1.22	1	0.27	NS
	Stressor	2.44	1	0.12	NS

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Higher UWIST MACL stress and hedtone scores represent higher levels of subjective stress and pleasure respectively, and higher STAI state scores represent increased anxiety. Significance stars include

* p < 0.05, ** p < 0.01, ** p > 0.001, NS = non significant).

Table 3. Tukey contrast statistics for three subjective measures, including UWIST MACL stress and hedonic tone (pleasure) and STAI-S (state) anxiety, for three soundscape treatments, including a natural soundscape (‘natural’) and mixed natural and urban soundscapes with 20 and 40mi/h traffic noise (‘mixed 20’, ‘mixed 40’).

Model	Contrast	Estimate	SE	z	p	significance
Stress	Natural vs mixed 20	0.25	0.15	1.65	0.23	NS
	Natural vs mixed 40	0.51	0.15	3.39	p < 0.01	^**
	Mixed 20 vs mixed 40	0.26	0.15	1.74	0.19	NS
Hedtone	Natural vs mixed 20	0.02	0.14	0.18	0.98	NS
	Natural vs mixed 40	-0.29	0.14	-2.10	0.09	.
	Mixed 20 vs mixed 40	-0.31	0.14	-2.29	0.06	.
Anxiety	Natural vs mixed 20	1.29	0.37	3.49	p < 0.01	^**
	Natural vs mixed 40	1.75	0.37	4.71	p < 0.001	^***
	Mixed 20 vs mixed 40	0.00	0.46	0.37	0.44	NS

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Significance stars include * p < 0.05, ** p < 0.01, ** p > 0.001 and NS = non-significant).

There was a significant positive trend between general ‘trait’ anxiety (STAI-T) and current stress (UWIST MACL) and anxiety (STAI-S) scores (Fig 3). However, pleasure (hedonic tone) decreased with increased general ‘trait’ anxiety (STAI-T) scores (Fig 3). General ‘trait’ anxiety (STAI-T) score was also significant when included as a fixed effect in GLMMs for all three measures (Tables 2 and S2).

Stressor had no effect on current stress (UWIST MACL) or anxiety STAI-S scores, but pleasure (hedonic tone) scores were significantly different between stressors and so this variable was controlled for and retained in the final model for hedonic tone (S2 Table).

Discussion

This online study set out to assess the effect on participants mood of listening to a natural soundscape including birdsong, following exposure to a multi-modal cognitive stressor, and whether the addition of anthropogenic soundscapes including road traffic of different speeds also affected mood recovery. We show that listening to a natural soundscape (including bird song) can reduce self-reported current stress and anxiety levels, and that mood recovery (after a stressor) is lessened on addition of road traffic soundscapes. Positive mood (pleasure/hedonic tone) was also enhanced by the natural soundscape, but this was limited by traffic sounds. Results indicated that the natural soundscape alone was associated with the lowest levels of self-reported current anxiety and stress levels which then increased on listening to the mixed soundscape with 20 mi/hr road traffic, with the highest levels reported after the mixed soundscape with 40mi/h road traffic. Higher levels of pleasure (hedonic tone), reflecting positive mood, were reported after listening to the natural soundscape, but reduced in comparison after listening to the mixed natural and 40mi/h traffic soundscape.

Do natural soundscapes improve mood?

When participants were exposed to the natural soundscape they had the lowest levels of subjective stress and anxiety relative to soundscapes including anthropogenic noise. This supports previous findings highlighting the positive impact that natural soundscapes can have on stress recovery and mental fatigue [8,14,36,37]. Our result therefore highlights the importance of the retention of suitable sized urban greenspace that are accessible to the public and large enough to support wildlife populations beyond the reach of anthropogenic pollutants such as traffic noise. This supports [38] who call for the urban populace to experience more robust, healthy and even wilder forms of nature, away from human disturbances. Access to greenspace rapidly reduces as cities grow, which reduces opportunities for people to experience nature [39], it is therefore essential that future urban development and expansion occurs with the provision of greenspace included to maximise the health and wellbeing benefits from these spaces.

What are the benefits of reducing traffic speeds on mood?

Anthropogenic noise reduces the human ability to hear natural sounds, for example the ability of ornithologists to detect birds (e.g. [40]). Our results show that the presence of traffic noise does mask the positive impact of a natural soundscape on stress and anxiety in participants and that this was irrespective of age, gender or a pre-disposed preference for natural environments. We found a trend of decreasing stress and anxiety scores, with a decrease in traffic speed across the conditions, despite not all treatment comparisons being significant during multiple comparison tests. For example, there was no significant difference in levels of subjective stress between hearing a natural soundscape and natural soundscape alongside 20mi/h road noise, in contrast to 40mi/h traffic where both stress and anxiety were heightened. Pleasure was also reduced during the higher traffic speed condition, but we recorded no difference between the natural soundscape and the mixed 20mi/hr traffic condition and only small differences recorded in the other treatment comparisons. The reason for these results is likely the differing sensitivity of the two subjective measures in their ability to pick up the differences in mood caused by the treatments, which is why we chose to include two measures (e.g. UWIST MACL has less mood items to score than the STAI-state measure, which may make it comparatively more sensitive) (S1–S3 Figs). Despite some between treatment comparisons being non-significant, soundscape was a significant predictor of all three mood item scores and the trend was for higher traffic speeds to reduce mood recovery in comparison to when natural soundscapes were heard alone. Reduced traffic speeds can therefore be a positive intervention in improving accessibility to nature as well as reducing road injuries [41] and encouraging active play [26].

How can reducing traffic speed influence health and wellbeing?

Anthropogenic noise pollution is associated with hypertension, cardiovascular disease risk [19,20], and an increased risk of mental health conditions, including depression and anxiety symptoms [21–23]. Our results show that for those with high baseline anxiety levels (so-called ‘trait’ anxiety STAI-T), exposure to anthropogenic soundscapes will lead to heightened levels of anxiety and stress, highlighting the pressures that many people will be exposed to on city streets on a daily basis. Trait anxiety (STAI-T) is a relatively stable characteristic reflecting the general background levels of anxiety experienced by individuals and is likely to be associated with other personality characteristics as well as mood states. Our results show that those participants with higher trait anxiety levels also reported higher current ‘state’ anxiety–how anxious they felt at the point of assessment, and similarly higher stress scores when compared to those with lower levels of trait anxiety who reported correspondingly lower state anxiety and stress. In addition, a significant proportion of people suffering from clinical levels of depression will also have anxiety [42]. A recent review of the mechanisms of anthropogenic noise impacts on mental health has pointed to a direct impact on the central nervous system, including adverse changes in brain tissue when people are exposed to traffic noise in their immediate environment every day [23]. Our study shows that exposure to natural soundscapes may alleviate some of the adverse effects on health and wellbeing caused by anthropogenic noise pollution. Therefore, the inclusion of wildlife and associated green environments within urban areas where over 80% of the UK population lives [43] may then benefit those suffering from these conditions, and possibly help prevent the transition of negative mood to a clinical level requiring treatment.

Study limitations, research directions and recommendations

Like other studies of this kind, we used a student participant pool [15,31,32]. Although there is president for doing so among the literature [33], participants may have been predisposed to favour natural soundscapes, due to their age, sex or backgrounds. However, neither age, sex nor preference for the natural environment influenced mood response to the soundscapes, despite inherent biases existing in the participant pool. This study included playbacks including a number of different bird sounds making up a dawn chorus soundscape but did not change the level of biodiversity represented in the soundscape. Future studies could therefore include participants from a range of backgrounds and ages, with both sexes represented equally, to examine how participant socio-cultural background may influence responses to different elements of soundscapes, and whether prior knowledge of bird song influences response. Understanding how biodiversity impacts wellbeing via the sonic environment is an important avenue for future research, including the question of whether more biodiverse soundscapes are better at enhancing mood recovery. It is also important to understand the interaction between anthropogenic sounds and biodiversity in the sonic environment in relation to urban planning and effects on human health and wellbeing. From our study, it is clear that a reduction in urban speed limits would have benefits to human wellbeing in urban environments. Further research is also needed to understand how technological adaptations to the urban soundscape, such as the widespread transition to hybrid and electric vehicles, could reduce the impact of noise pollution on both human and wildlife in cityscapes. We recommend work that explores the redesign of major urban transit routes, both for potentially polluting motor vehicles and for pedestrian walkways or cycle paths, to include green spaces and significant vegetation that encourages wildlife. Greening in this way will in turn will dampen traffic noise, help absorb air born pollutants as well as benefitting mental health supporting a healthier travelling public [3,5,44].

Conclusion

There is increasing pressure to implement reduced speed limits within cities, however speed reduction initiatives are still met with considerable resistance amongst policymakers and local communities. Here, we demonstrate that a reduction in traffic speed and therefore noise pollution can aid stress recovery and reduce anxiety highlighting the importance of exposing urban populations to wildlife. The reduced level of stress, anxiety and higher level of pleasure (hedonic tone) experienced by participants when exposed to a natural soundscape compared to a stressor event, even in the presence of masking anthropogenic sounds, highlight the importance of being able to hear natural sounds in our cities. City-wide strategies such as reducing road traffic speeds and conserving urban greenspace are therefore necessary steps to aid stress recovery and reduce anxiety.

Supporting information

S1 Doc. Survey example experienced by participants.

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S1 Fig. Example of scale presented to participants to rate their general mood (trait anxiety).

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S2 Fig. Example of scale presented to participants to rate their current mood in terms of stress and hedonic tone (pleasure).

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S3 Fig. Example of 4-point Likert scale presented to participants after each stressor video and soundscape file.

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S1 Table. Demographic data for all participants.

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S2 Table. GLMM statistics for subjective measures UWIST MACL stress and hedonic tone (pleasure) and STAI-S current state anxiety scores.

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S3 Table. Model selection statistics for GLMM for three subjective measures, UWIST MACL stress and hedtone and STAI state anxiety.

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S1 Data. Current state anxiety (STAI-S) dataset.

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S2 Data. UWIST MACL dataset (stress and hedonic tone).

(XLSX)

pone.0311487.s009.xlsx^{(26.6KB, xlsx)}

Acknowledgments

We would like to thank Gary Moore for the use of his bird song soundscape and for recording traffic noise for us.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

The author(s) received no specific funding for this work.

References

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PLoS One. doi: 10.1371/journal.pone.0311487.r001

Decision Letter 0

Yuan Zhang

24 May 2024

PONE-D-24-08824Natural Soundscapes Enhance Mood Recovery Amid Anthropogenic Noise PollutionPLOS ONE

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Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

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5. Review Comments to the Author

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Reviewer #1: It is an interesting paper that creatively included the investigations of the effect of traffic speeds on psychological responses to natural sounds. The study objectives are explicit, and the following works align well with such goals. The expression of this manuscript is logically clear and well-written, making the readers understand easily. However, I personally think the results of this study have not been exhibited, analyzed, and explained thoroughly. Also, the current contents are more narrative-like, lacking deep discussions of the phenomena found in the results. These aspects are really suggested for further improvement. Please see the detailed comments as follows.

Line 73-74

Due to the change in the subject of the description, the logical relationship before and after this sentence does not seem obvious. The link could be strengthened by modifying the formulation.

Line 81

Is it necessary to use the term “natural sounds” if the study only included and examined birdsongs?

Line 114

More details of the experiment are suggested to indicate clearly. For instance, how did the authors control the device condition, like sound volumes, of the participants’ sides? Is it possible that the conditions are different from person to person? Because it seems to be an online experiment conducted in this study, and the objects did not have to be somewhere (e.g., a room or lab) to participate in the experiment in person.

Line 171

The authors should indicate in this section why they preferred to use these models for data analysis.

Line 231

Some phenomena found in the results can be discussed more instead of simply describing them in this section. For instance, in Line 260, what is the possible reason for the lack of significant difference in stress levels between birdsong and birdsong with 20mi/h noise hearing?

Furthermore, the authors included some demographic factors in the analysis, but why were such factors not mentioned in this section? Even though they were insignificant in the models, the potential reasons or mechanisms can still be analyzed or speculated reasonably.

Line 235

The wording should be more concrete here. The present study does indicate the effect of birdsongs, a part/type of natural sounds/soundscapes, on stress and anxiety. However, the other types of natural sounds or soundscapes were not examined in this work, so this general term is not suggested here. Please check the whole manuscript to see whether there are similar cases.

Line282

The limitations of this study should also be stated.

Reviewer #2: The manuscript presents an interesting study assessing to what extend self-reported anxiety, stress and pleasure are affected by natural soundscapes (bird song) and traffic noise at different speed limits. The paper is well written and might be a relevant contribution to the field because the effect of speed limit has been largely understudied. The provided evidence is also very useful for urban planning. Overall, this paper is of high quality. There are some minor points to be considered before its publication:

Introduction is well-written and concise. However, the first paragraph is very broad. I would suggest to reduce or even omit it, and expand on the actual focus of the study, so to broaden on the soundscape part (paragraph two) on how soundscapes have been used in health and well-being studies before, while strengthening on what contributions and novelty the presented approach brings.

Lines 83-87: You also test for the effect of different background characteristics such as nature preference, pleas add here. I think adding a short paragraph on how socio-cultural characteristics have been studied before in soundscape-well-being studies will also justify more clearly the chose of variables in the questionnaire

Line 114: In the experimental design section, please state if randomization was used and in what ways. This information can be found only in the Supplementary, but I think it is important to clarify in the methods main text as well. In fact, figure S1 of the experimental procedure is really informative and clear and I would suggest including it in the main body of the article, not as part of the Supplementary, if possible

Stressors: if this is an established and validated stressor method, please add the reference

Line 165, Why did you ask about where participants grew up, please justify and add reference? In general, related to my previous comment, it would be better to connect the questions you have used with previous literature to justify the choice of your socio-demographic variables. Please add references and relate previous research studying such associations wherever possible

In the statistical analysis, did you somehow account for the order of the sound interventions (bird, bird + 20mi/h, bird + 40mi/h)? although they were randomized, accounting for the order effect in the model is important

Line 182: What do you mean by “non-experimental data” isn’t all data used in the experiment? Also, it is unclear in the methods description why you chose some of the demographic characteristics to be included in the models and others are omitted. In general, the difference in the aim/research question/hypothesis between the LMM and GLMM model is not very clear, especially the GLMM needs better explanation.

Line 184 -185 Why do you treat listening device (especially the latter) as a response variable? Please clarify

The results and discussion are well-written and concise. However, please add a short paragraph discussing study limitations. Please also add future directions for research, currently future recommendations are related only to planning

Reviewer #3: The study examines the impact of natural soundscapes, such as bird song, and the addition of traffic noise at different speeds (20 mi/h and 40 mi/h) on mood in urbanized environments where green spaces are scarce and exposure to anthropogenic noise is high.

Reviewer Comments:

1.The current review lacks sufficient depth regarding conclusions drawn from previous studies that combine traffic noise with natural sounds. Please expand the review to include a more comprehensive analysis of existing literature on this topic.

2.The manuscript does not provide a clear rationale for selecting 68 participants. Please elaborate on the selection criteria and the methods used to determine and verify the adequacy of this sample size.

3.There is a lack of detail regarding the duration of rest periods for subjects under different conditions. Please specify how long the subjects rested in each condition.

4.It would be beneficial to include Figure S1 in the main text and to add photos of the experimental scenes to provide clearer context and enhance the reader's understanding.、

5.The manuscript should clarify the relationships between the various scales used. Specifically, provide details on the relationship between STAI-T and STAI, and how these scales are interrelated in the context of the study.

6.The horizontal axis of Figure 2 is not clearly labeled. Please provide a clear and descriptive label for the horizontal axis.

7.The study mentions audio collection on two speed-limited roads but does not detail the traffic volume and vehicle type ratio on these roads. Please include this information and discuss whether it was considered during audio collection.

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

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PLoS One. 2024 Nov 27;19(11):e0311487. doi: 10.1371/journal.pone.0311487.r002

Author response to Decision Letter 0

12 Aug 2024

Response to Reviewers' comments

We have provided a response in bold underneath each reviewer’s comment and indicated the line number of any changes in the revised manuscript. Excepts are provided for ease of reference to changes in the manuscript.

Reviewer #1 (R1)

It is an interesting paper that creatively included the investigations of the effect of traffic speeds on psychological responses to natural sounds. The study objectives are explicit, and the following works align well with such goals. The expression of this manuscript is logically clear and well-written, making the readers understand easily. However, I personally think the results of this study have not been exhibited, analyzed, and explained thoroughly. Also, the current contents are more narrative-like, lacking deep discussions of the phenomena found in the results. These aspects are really suggested for further improvement. Please see the detailed comments as follows.

We thank R1 for their positive comments regarding the study objectives and we welcome their feedback on the way the results have been presented, analysed and discussed. We believe the changes made in line with the feedback from R1 has made the manuscript a stronger contribution to the field and more widely applicable.

Line 73-74

Due to the change in the subject of the description, the logical relationship before and after this sentence does not seem obvious. The link could be strengthened by modifying the formulation.

We agree, and have moved the line lower down the paragraph to L81-83

Line 81

Is it necessary to use the term “natural sounds” if the study only included and examined birdsongs?

We thank the reviewer for picking this up. We have reviewed the whole manuscript and made our wording consistent throughout.

Our study included soundscapes created from a natural soundscape recorded at a rewilded site during dawn chorus, including bird song and an urban soundscape including traffic noise recorded on two roads, one with 20mi/h traffic and one with 40 mi/hr traffic. A soundscape is different from sounds e.g. bird song or car noises recorded in isolation, as it represents the multi-layered soundscape you get with birds singing at different distances and the echoes from objects in the environment, all contributing to the experience of the soundscape.

However, we agree the use of the term “natural sounds” was misleading. We have removed the reference to natural sounds throughout the manuscript and made sure we refer to natural soundscapes throughout. We have also included ‘including bird song’, or ‘including 20/40 mi/hr traffic noise’ where appropriate, to make it clear that the natural soundscapes included bird song and the anthropogenic/urban soundscape included traffic noise.

We have also changed the names of the treatments throughout the manuscript, for clarity. The conditions are now Natural soundscape (previously bird only) and mixed 20 and mixed 40 treatments for the mixed soundscapes with natural soundscapes with 20 and 40 mi/h traffic noise added (previously bird + 20 and bird + 40 mi/hr).

Line 114

We thank R1 for raising this. We did indeed attempt to control the sound volume as much as possible given that participants were doing the experiment at home at their computers or laptops. We asked that participants use ear cancelling headphones if available, or in ear headphones at the least. We also did a sound test before starting the experiment. We have added these details into the methods.

L138-144: “Before starting the experiment, participants were asked about their mood in general (see Subjective Measures below), and then asked to do a sound test. During the sound test, participants were asked to put on their headphones, and click a test link that played some sounds of human talking. They were then asked to adjust their headphones to a level that was comfortable, but loud enough to immerse themselves in the sounds. Talking was chosen as the test sound as it was sufficiently different from the sounds used in the main experiment.”

Line 171

The authors should indicate in this section why they preferred to use these models for data analysis.

We used mixed models in both cases as it allowed us to include random effects in our models. This allowed us to control for any inherent mood differences among participants via the random effect of participant number. For clarity we have included the following on L228-230:

“Using this mixed modelling method allowed us to control for order of the fixed factor effects soundscape and stressor as well as any inherent variation in stress, hedonic tone and anxiety amongst participants.”

Line 231

We agree that more detail examining the results would be helpful in determining the wider narrative. We used two subjective mood state measures in this experiment, and state the reasoning for this in the methods L166-167:

“Two measures were used to ensure internal consistency in the experiment (i.e. if scores from the two measures mirrored each other, then they were both more likely a true representation of mood).”

All three measures of mood- subjective anxiety, stress and hedonic tone (pleasure) were significantly different between soundscape treatments. However, on closer comparison, STAI anxiety scores show a significant difference between treatments, e.g. natural soundscape and mixed 20mi/hr, whereas UWIST MACL stress scores do not. There may be some power loss due to accounting for multiple comparisons. More likely is a difference in sensitivity between the tests. We have included this explanation and included reference to the supplementary figures showing the mood items in each Likert scale. Both measures show the same trend however, but one is perhaps more sensitive in picking up the nuances of mood differences felt by participants between the treatments. We have added an explanation to L305-320.

We thank R1 for the suggestion and have added in reference to the demographic factors in the aims section of the introduction and into the discussion. We have also added a discussion of the limitations of the study and included reference to demographics and other participant information.

Line 235

We thank R1 for their comment and refer them back to our earlier response regarding use of the term natural soundscapes vs natural sounds. We acknowledge that we did not test other types of natural soundscapes, and have made this clear throughout the manuscript.

Line282

The limitations of this study should also be stated.

We have added a section at the end of the discussion that includes limitations of the current study, future research directions and recommendations based on this study. L343-366

Reviewer #2 (R2)

The manuscript presents an interesting study assessing to what extend self-reported anxiety, stress and pleasure are affected by natural soundscapes (bird song) and traffic noise at different speed limits. The paper is well written and might be a relevant contribution to the field because the effect of speed limit has been largely understudied. The provided evidence is also very useful for urban planning. Overall, this paper is of high quality. There are some minor points to be considered before its publication:

We thank R2 for their positive comments about the manuscript, especially that it is of high quality and will have use in urban planning.

We thank R2 for this suggestion and have reduce paragraph one in the introduction accordingly. We have also expanded on paragraph two, including examples of studies including exposure to natural sounds and anthropogenic sounds. We have also made it clearer how our study is novel in comparison to what has been done before.

Lines 83-87: You also test for the effect of different background characteristics such as nature preference, pleas add here.

I think adding a short paragraph on how socio-cultural characteristics have been studied before in soundscape-well-being studies will also justify more clearly the chose of variables in the questionnaire

We have added the line:

“We also tested whether general mood state, age, gender and inherent preference for natural environments affected mood recovery in response to natural and mixed natural and anthropogenic soundscapes.” L92-94

We have also added in a line introducing the influence of demographic and other factors in determining response to nature and natural soundscapes:

“Responses to nature, including natural soundscapes, may also be dependent on factors such as age, sex and socio-cultural experience e.g. childhood connection to nature (Hughes et al. 2018, Shu and Ma, 2020, Ge et al. 2023), though more research is needed to understand and tease apart the influence of these factors.” L53-56

We agree and have included Figure S1 as a figure in the main text (now Figure 1). We have also included the following line for clarity on randomisation:

“The order of soundscapes was randomised between participants, but the stressor videos were not (Figure 1). Soundscapes were randomised to control for any order effects, with each participant exposed to all three soundscapes as part of the repeated measures design.” L149-151

Stressors: if this is an established and validated stressor method, please add the reference

We based our stressor method on similar previous studies. Reference to these studies has been added to the methods section. L154

We included this question to understand the bias that may exist in the participant pool we were sampling from, i.e. students that were at university in an urban environment. Many similar studies in fields related to this research use student participants, however, we wanted to be able to discuss the limitations of our participant sample. We have now added a section discussing limitations and referenced these factors. We have also clarified the collection of participant information in the methods.

We have added a section discussing limitations, future research and recommendations from the study. L343

The order of soundscapes was randomised between participants, but the stressor videos were not (Figure 1). Soundscapes were randomised to control for any order effects, with each participant exposed to all three soundscapes as part of the repeated measures design.” L149-151

“Each participant was exposed to all stressors and all soundscapes. However, soundscape order was randomised within the Qualtrics software, whereas stressor order was not. We therefore included stressor identifier (factor variable with levels: A, B, C) as a fixed effect in the full model to control for any effect of stressor type or order on the outcome measures. We also chose to use mixed effect models due to their ability to include random effects (as well as fixed effects) and included the random effect of participant number. Using this mixed modelling method allowed us to control for order of the fixed factor effects soundscape and stressor as well as any inherent variation in stress, hedonic tone and anxiety amongst participants.” L222-230

Line 182: What do you mean by “non-experimental data” isn’t all data used in the experiment?

By this we mean any data collected before the experimental playback. We have made this clearer throughout the methods and results sections.

Also, it is unclear in the methods description why you chose some of the demographic characteristics to be included in the models and others are omitted.

In general, the difference in the aim/research question/hypothesis between the LMM and GLMM model is not very clear, especially the GLMM needs better explanation.

We have rewritten the methods for the statistical analysis to make the whole section clearer and included an explanation of why the chosen variables were used in the analysis. We have also added some info that was missing into the Participant info and demographics section in the results.

Line 184 -185 Why do you treat listening device (especially the latter) as a response variable? Please clarify

We have removed this section as it was confusing. The main analysis includes a subset of “participant information” including demographic data, trait anxiety scores and preference for natural environments (see previous points).

We have added a section discussing limitations, future research and recommendations from the study. L343

Reviewer #3 (R3)

The study examines the impact of natural soundscapes, such as bird song, and the addition of traffic noise at different speeds (20 mi/h and 40 mi/h) on mood in urbanized environments where green spaces are scarce and exposure to anthropogenic noise is high.

We thank R3 for their comments and recommendations to improve the manuscript.

Reviewer Comments:

We have expanded the introduction to include a more thorough examination of previous studies.

Similar studies had between 40 and around 180 participants (see examples below), so w

Attachment

Submitted filename: PONE_response_to_reviewers.docx

pone.0311487.s010.docx^{(29.4KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0311487.r003

Decision Letter 1

Yuan Zhang

20 Sep 2024

Natural Soundscapes Enhance Mood Recovery Amid Anthropogenic Noise Pollution

PONE-D-24-08824R1

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PLoS One. doi: 10.1371/journal.pone.0311487.r004

Acceptance letter

Yuan Zhang

25 Oct 2024

PONE-D-24-08824R1

PLOS ONE

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Doc. Survey example experienced by participants.

(DOCX)

pone.0311487.s001.docx^{(35.9KB, docx)}

S1 Fig. Example of scale presented to participants to rate their general mood (trait anxiety).

(DOCX)

pone.0311487.s002.docx^{(51.4KB, docx)}

S2 Fig. Example of scale presented to participants to rate their current mood in terms of stress and hedonic tone (pleasure).

(DOCX)

pone.0311487.s003.docx^{(34.5KB, docx)}

S3 Fig. Example of 4-point Likert scale presented to participants after each stressor video and soundscape file.

(DOCX)

pone.0311487.s004.docx^{(42.4KB, docx)}

S1 Table. Demographic data for all participants.

(DOCX)

pone.0311487.s005.docx^{(18.6KB, docx)}

S2 Table. GLMM statistics for subjective measures UWIST MACL stress and hedonic tone (pleasure) and STAI-S current state anxiety scores.

(DOCX)

pone.0311487.s006.docx^{(19.6KB, docx)}

S3 Table. Model selection statistics for GLMM for three subjective measures, UWIST MACL stress and hedtone and STAI state anxiety.

(DOCX)

pone.0311487.s007.docx^{(20.3KB, docx)}

S1 Data. Current state anxiety (STAI-S) dataset.

(XLSX)

pone.0311487.s008.xlsx^{(25.2KB, xlsx)}

S2 Data. UWIST MACL dataset (stress and hedonic tone).

(XLSX)

pone.0311487.s009.xlsx^{(26.6KB, xlsx)}

Attachment

Submitted filename: PONE_response_to_reviewers.docx

pone.0311487.s010.docx^{(29.4KB, docx)}

Data Availability Statement

All relevant data are within the paper and its Supporting Information files.

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PERMALINK

Natural soundscapes enhance mood recovery amid anthropogenic noise pollution

Lia R V Gilmour

Isabelle Bray

Chris Alford

Paul R Lintott

Roles

Abstract

Introduction

Methods

Participants

Soundscapes

Experimental design

Stressors

Subjective measures

Demographics and other participant information

Statistical analysis

Analysis of subjective mood measures

Modelling procedure

Results

Participant information and demographics

Subjective measures

Table 2. Likelihood ratio test statistics for GLMMs for three subjective measures: UWIST MACL stress and hedonic tone (hedtone) and STAI-S (state) anxiety, including fixed effects soundscape treatment, STAI trait score (STAI-T), preference for natural environments, gender, age and stressor.

Fig 3. Scatterplots of three subjective measures, including UWIST MACL stress and hedonic tone (hedtone) scores and STAI-S (state) anxiety score against STAI-T (trait) anxiety scores.

Discussion

Do natural soundscapes improve mood?

What are the benefits of reducing traffic speeds on mood?

How can reducing traffic speed influence health and wellbeing?

Study limitations, research directions and recommendations

Conclusion

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Decision Letter 0

Yuan Zhang

Roles

Author response to Decision Letter 0

Decision Letter 1

Yuan Zhang

Roles

Acceptance letter

Yuan Zhang

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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