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This study tests whether different types of sounds can help reduce emotional distress in people with fibromyalgia. Fibromyalgia is a condition that causes widespread muscle and joint pain and makes people extra sensitive to sounds and other sensations. Many people with fibromyalgia also struggle with emotional distress symptoms. About half of people with fibromyalgia (54 out of 100) have depression symptoms, while 55 out of 100 also have anxiety symptoms.
Researchers want to know if listening to environmental sounds can help people with fibromyalgia feel less distressed. The study will include four different types of sounds:
People with fibromyalgia who are between 18 and 64 years old may be able to join. The study takes 4 weeks total. Each person will visit the research center 4 times over these weeks. Each visit takes about 1 hour. Visits are scheduled 1 week apart. During each visit, participants will:
Each person will try all 4 types of sounds in a random order. This helps researchers compare how each sound affects the same person.
Before and after each sound session, participants will fill out questionnaires about:
These questionnaires have been tested in many studies and work well for people with chronic pain conditions.
Participants' mood, stress, and anxiety levels might change after listening to certain sounds. If the study shows that sounds help, this could lead to new treatment options and preventive measures that are easy to use and would be safe and cost much less than medications.
Full description
This study investigates whether distinct soundscapes can alleviate emotional distress symptoms in individuals with fibromyalgia syndrome. The study's theoretical foundation is grounded in converging evidence from environmental neuroscience and psychology research demonstrating that auditory stimuli can significantly influence emotional processing through neural pathways connecting the auditory cortex with brain areas involved in emotional regulation. By investigating how different soundscapes influence emotional distress, this research may contribute to the field of environmental psychology, as well as inform environmental health policies and acoustic design strategies for healthcare settings.
Soundscapes represent acoustic environments that are perceived, experienced, and interpreted within specific contexts. For research purposes, soundscapes are categorized based on their sources: natural soundscapes comprise biophonies (sounds produced by non-human living organisms) and geophonies (sounds generated by non-biological natural processes), while urban soundscapes feature anthropophonies (human-generated sounds) and technophonies (sounds produced by mechanical and technological sources).
Emerging neuroscientific research has identified direct neural pathways between the auditory cortex and emotion-processing brain areas, including the limbic and paralimbic regions. These auditory-emotion connections may provide a neurobiological foundation for investigating how environmental soundscapes might modulate emotional states in populations with altered sensory processing. Moreover, numerous studies conducted in healthy populations suggest that soundscapes can influence mood states and stress levels. Natural soundscapes have been shown to elicit distinct neural signatures compared to urban soundscapes, with differential effects on emotional distress symptoms.
Fibromyalgia syndrome affects approximately 2 to 3% of the global population and is commonly associated with emotional distress, with clinical symptoms of depression and anxiety occurring in 54% and 55% of affected individuals, respectively. This high prevalence of emotional comorbidity significantly impacts various aspects of life in this population. The hypothalamic-pituitary-adrenal axis dysfunction observed in fibromyalgia may contribute to altered stress responsivity and emotional regulation difficulties. Furthermore, the chronic pain experience itself can precipitate and maintain emotional distress through various psychological mechanisms. The substantial emotional burden associated with fibromyalgia necessitates efficacious strategies that can address emotional distress symptoms characteristic of this condition.
The use of environmental acoustic stimuli to influence emotional distress symptoms may offer a promising management strategy in individuals with fibromyalgia. This proposition is supported by two core characteristics of the condition. First, fibromyalgia is associated with increased sensory sensitivity, which may heighten responsiveness to acoustic features of the environment. Second, emotion regulation difficulties have been identified as a key factor mediating the relationship between fibromyalgia symptoms and emotional distress. In particular, individuals with fibromyalgia often demonstrate reduced efficacy in employing adaptive emotion regulation strategies, such as cognitive reappraisal and emotional acceptance. These limitations may contribute to the persistence and intensification of affective symptoms. Together, these factors indicate that environmental sounds capable of modulating emotional distress symptoms through non-cognitive mechanisms represent a theoretically grounded and clinically relevant intervention approach for this population.
The general objective (GO) of this study is to:
GO1. Investigate whether exposure to distinct soundscapes differentially modulates emotional distress variables in individuals with fibromyalgia syndrome.
The specific objectives (SO) are to:
SO1. Compare the effects of natural and urban soundscapes with those of broadband sound (active comparator) and silence (attention-placebo control) on mood states, perceived stress, and state anxiety.
SO2. Determine the relative efficacy of natural versus urban soundscapes in modulating mood states, perceived stress, and state anxiety.
SO3. Quantify and characterize the magnitude and direction of within-group pre-post changes in mood states, perceived stress, and state anxiety following exposure to natural and urban soundscapes.
The primary hypothesis (PH) is:
PH1. Exposures to distinct soundscape categories will differentially modulate total mood disturbance in individuals with fibromyalgia syndrome, with the following specific contrasts:
PH1.1. Natural soundscape exposure will result in lower total mood disturbance compared to the attention-placebo control (silence).
PH1.2. Natural soundscape exposure will result in lower total mood disturbance compared to broadband sound active control.
PH1.3. Urban soundscape exposure will result in higher total mood disturbance compared to the attention-placebo control.
PH1.4. Urban soundscape exposure will result in higher total mood disturbance compared to broadband sound active control.
PH1.5. Natural soundscape exposure will result in lower total mood disturbance compared to urban soundscape exposure.
The secondary hypotheses (SH) are:
SH1. Exposures to distinct soundscape categories will differentially modulate perceived stress and state anxiety in individuals with fibromyalgia syndrome, with the following specific contrasts:
SH1.1. Natural soundscape exposure will result in lower perceived stress and state anxiety compared to the attention-placebo control.
SH1.2. Natural soundscape exposure will result in lower perceived stress and state anxiety compared to broadband sound active control.
SH1.3. Urban soundscape exposure will result in higher perceived stress and state anxiety compared to the attention-placebo control.
SH1.4. Urban soundscape exposure will result in higher perceived stress and state anxiety compared to broadband sound active control.
SH1.5. Natural soundscape exposure will result in lower perceived stress and state anxiety compared to urban soundscape exposure.
SH2. Exposure to natural soundscapes will produce a significant pre-post reduction in total mood disturbance, perceived stress, and state anxiety.
SH3. Exposure to urban soundscapes will produce a significant pre-post increase in total mood disturbance, perceived stress, and state anxiety.
The study design optimizes statistical efficiency by allowing within-subject comparisons while controlling period effects. The auditory exposure sessions are conducted in a controlled laboratory environment, maintaining a consistent room temperature and relative humidity.
An a priori power analysis was conducted using Monte Carlo simulations in R with the simr package. The sample size estimation was based on a linear mixed-effects model, with power evaluated via a likelihood ratio test. Model parameters were defined to detect a partial eta-squared of 0.075 with a two-tailed alpha level of 0.05, derived from literature on the impact of environmental sounds on total mood disturbance. The simulation assumed a total standard deviation of 25 for the primary outcome and an intra-class correlation of 0.5. To test the overall main effect of "treatment," a total of 56 participants provides 83.48% power (95% CI [82.42%, 84.50%]) based on 5000 simulations. To account for a potential attrition rate of 20%-including potential dropout, loss to follow-up, clinical reasons, and operational challenges-a total of 70 participants is required. To ensure balanced allocation across the four experimental sequences using a multiple of four, a final sample of 72 participants will be recruited.
The assessment protocol incorporates validated instruments specifically selected for their psychometric properties in chronic pain populations. It follows International Association for the Study of Pain consensus guidelines and incorporates core outcome domains recommended for chronic pain trials.
The primary and secondary analyses will employ linear mixed-effects models. The dependent variable will be defined as post-intervention outcome adjusted for baseline. Fixed effects will include treatment, sequence, period, and the treatment × period interaction term to assess potential carryover effects. Participants will be modeled as a random effect. If no statistically significant carry-over effect is detected at the 25% significance level, the interaction term will be excluded, and a reduced model will subsequently be re-estimated. The inferences will be based on the main effects from the final model. Following a significant omnibus F-test for the treatment effect, pairwise comparisons between interventions will be conducted using estimated marginal means with Bonferroni adjustment. As a sensitivity analysis, the prespecified covariate will be incorporated into the final model to assess its potential influence on the estimated treatment effects. Post-hoc analyses will include within-group changes from baseline, conducted using paired t-tests or Wilcoxon signed-rank tests, depending on the data's distributional properties. All hypothesis testing will be two-sided with an overall Type I error rate of 5%, and all analyses will adhere to the intention-to-treat (ITT) principle.
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72 participants in 4 patient groups
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José Manuel Pérez Mármol, PhD
Data sourced from clinicaltrials.gov
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