Sleep reactivity as a mediator in the relationship between trait mindfulness and insomnia: a correlational study

Sleep reactivity as a mediator in the relationship between trait mindfulness and insomnia: a correlational study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sleep reactivity as a mediator in the relationship between trait mindfulness and insomnia: a correlational study Ilde Pieroni, Antonino Raffone, Luca Simione This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7829160/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objectives: Previous research has established the beneficial effects of mindfulness practices on reducing insomnia, primarily through the alleviation of psychological stress. However, the specific role of sleep reactivity - a sleep-focused component of stress reactivity - has not been thoroughly explored. This study aims to investigate the mediating role of sleep reactivity in the relationship between dispositional mindfulness facets and insomnia symptoms. Methods: A total of 359 participants completed an online survey assessing mindfulness facets (namely, Observing, Describing, Acting with awareness, Non-judging of inner experiences, Non-reactivity to inner experiences), sleep reactivity, and insomnia severity. Structural equation modeling was used to assess direct and indirect paths from the five mindfulness facets to the outcome variable (insomnia severity) via the mediator variable (sleep reactivity). Results: The results indicate that while the Observing facet of mindfulness was associated with increased insomnia severity through heightened sleep reactivity, the Non-judging and Non-reactivity facets contributed to decreased insomnia symptoms by reducing sleep reactivity. Conclusions: These findings highlight the need for improved measurements to assess the monitoring aspect of mindfulness and highlight the protective role of dispositional mindfulness, particularly its acceptance-related component. Furthermore, they suggest that mindfulness training may serve as a preventive measure for individuals vulnerable to stress-induced insomnia. Figures Figure 1 INTRODUCTION Insomnia is a common chronic sleep disorder characterised by both nocturnal symptoms and daytime consequences. People with insomnia typically report difficulty falling asleep and/or staying asleep, dissatisfaction with sleep quantity and/or quality, as well as daytime fatigue, cognitive impairments and mood disturbances. Around one-third of the general population experience temporary insomnia symptoms, while up to 10% of the adult population is diagnosed with insomnia (Morin et al., 2006 ; Ohayon, 2002 ). Several psychobiological models of insomnia have been proposed to explain the mechanisms involved in the aetiology of this sleep disorder, as various factors have been identified as contributing to its onset and maintenance. However, it is well established in the literature that stress is a key factor in its development (Bastien et al., 2004 ; Healey et al., 1981 ). According to the 3P model of Spielman et al. ( 1987 ), stress is a precipitating factor that can interact with individual predispositions, such as temperamental and personality traits, increasing the likelihood of sleep problems. These problems can then be maintained and exacerbated by perpetuating factors, such as poor sleep hygiene and hyperarousal (Spielman et al., 1987 ). The first-line non-pharmacological treatment for insomnia is cognitive-behavioral therapy for insomnia (CBT-I; Edinger et al., 2021 ). However, in recent years, mindfulness approaches have also been proposed and studied as an alternative treatment for insomnia (Ong et al., 2012 ). Mindfulness is defined as “the awareness that emerges through paying attention on purpose, in the present moment, and nonjudgmentally to the unfolding of experience moment by moment” (Kabat- Zinn, 2003, p. 145). As such, mindfulness can be considered both a state that can be cultivated through formal meditation practices specifically designed to enhance this particular form of awareness (Bishop et al., 2004 ; Carmody & Baer, 2008 ), and a disposition or trait-like quality of attention that individuals naturally possess to varying degrees, regardless of mindfulness meditation practice (Brown & Ryan, 2004 ). Dispositional or trait mindfulness can be assessed using various self-report measures. One of the most widely used questionnaires in the literature is the Five Facet Mindfulness Questionnaire (FFMQ; Baer et al., 2006 ). This questionnaire conceptualizes mindfulness as a multidimensional construct characterized by five distinct components, namely Observing (i.e., noticing and attending to both internal and external experiences such as sensations, thoughts and feelings), Describing (i.e., being able to describe and label internal experiences with words), Acting with awareness (i.e, being present and attentive while doing things, as opposed to doing things on “automatic pilot”), Non-judging of inner experiences (i.e. taking a non-evaluative stance towards thoughts and feelings), and Non-reactivity to inner experiences (i.e. allowing all inner experiences to come and go without getting caught up or carried away by them). Alternative questionnaires relating to different operationalisations of the mindfulness construct have also been proposed (Bergomi et al., 2013 ), but for the purposes of this article we will adopt Baer's self-report instrument. A substantial body of research has shown that both dispositional mindfulness and practicing mindfulness meditation are associated with improvements in several indicators of mental health and well-being, including improved sleep quality and reduced insomnia severity (Garland et al., 2013 ; Rusch et al., 2019 ). Correlational studies using the FFMQ in both clinical and non-clinical samples have shown that the Acting with Awareness, Non-judging and Non-reactivity facets of the FFMQ are consistently associated with better sleep quality and lower insomnia severity (Curado et al., 2018 ; Fong & Ho, 2020 ; Garland et al., 2013 ; Park et al., 2019; Talley & Shelley-Tremblay, 2020 ; Xie et al., 2023 ). On the other hand, results for the Observe and Describe facets are more inconsistent. For example, while one study has reported a positive association between the Describe facet and improved sleep quality (Park et al., 2019), others have found no significant relationship between this facet and sleep outcomes (Garland et al., 2013 ; Talley & Shelley-Tremblay, 2020 ; Xie et al., 2023 ). Similarly, research on the Observe facet has yielded mixed results, with some studies linking higher levels of Observe to increased sleep disturbances (Curado et al., 2018 ; Talley & Shelley-Tremblay, 2020 ), while others have found no association at all (Fong & Ho, 2020 ; Garland et al., 2013 ; Park et al., 2019; Xie et al., 2023 ). In addition, studies investigating the effects of MBIs on improving sleep in populations with sleep difficulties or suffering of insomnia generally report some improvements in both subjective and objective sleep parameters (Rusch et al., 2019 9, further highlighting the potential of mindfulness practices as promising tools for improving sleep health (Ong et al., 2014 ). Despite the positive relationship between mindfulness and improved sleep, the mechanisms and factors through which mindfulness exerts its beneficial effects, particularly in relation to insomnia, remain understudied. Given the well-established role of mindfulness as a stress-reduction practice (Britton et al., 2012 ; Hoge et al., 2013 ), it is reasonable to hypothesize that its stress-reducing effects may contribute to improvements in sleep. Indeed, recent studies have demonstrated that the link between mindfulness and sleep quality may be mediated by reductions in psychological stress (Lau et al., 2018 ; Simione et al., 2020 ), emotional distress (Fong & Ho, 2020 ), and negative affect (Ding et al., 2020 ). All these studies underscore the well-established impact of mindfulness on stress as a crucial mechanism for alleviating sleep problems. As highlighted by Ong et al. ( 2012 ), mindfulness may alleviate insomnia primarily by altering one's relationship with stressors, thereby reducing their impact at bedtime. Dispositional reactivity to these stressors may thus mediate this effect, with mindfulness potentially attenuating a sleep-specific aspect of stress reactivity, known as sleep reactivity (Kalmbach et al., 2018 ). Sleep reactivity is defined as the susceptibility to experiencing disturbed sleep following exposure to situations that could be perceived as stressors (Kalmbach et al., 2018 ). Individuals with high sleep reactivity are more likely to experience acute sleep difficulties in response to stress, even from mild stressors like sleeping in a new environment - situations that typically do not affect those with lower levels of sleep reactivity (Drake et al., 2004 ). Sleep reactivity has been linked to increased pre-sleep cognitive and somatic hyperarousal, neuroticism, and rumination in healthy populations (Fernández-Mendoza et al., 2010 ). Additionally, it has been identified as a risk factor for the development of chronic insomnia (Drake et al., 2014 ; Jarrin et al., 2014 ; Kalmbach et al., 2016 ). Thus, the present correlational study aimed to examine the relationships between mindfulness facets, sleep reactivity, and insomnia symptoms. Based on the reviewed evidence, we hypothesized that sleep reactivity would positively correlate with insomnia severity. In addition, as the majority of correlational studies have primarily relied on global measures of mindfulness, the decision was taken to examine the individual effect of each mindfulness facet. Thus, we hypothesized that higher mindfulness scores would be associated with lower sleep reactivity and insomnia severity, in particular for the Acting with Awareness, Nonjudging, and Nonreactivity mindfulness facets, that have been already reported as effective in this context (Curado et al., 2018 ; Fong & Ho, 2020 ; Garland et al., 2013 ; Park et al., 2019; Talley & Shelley-Tremblay, 2020 ; Xie et al., 2023 ). We further hypothesized that sleep reactivity would mediate the relationship between these mindfulness facets and insomnia severity, given the established links between stress and both mindfulness (Britton et al., 2012 ; Hoge et al., 2013 ) and insomnia symptoms (Kalmbach et al., 2018 ; Morin et al., 2003 ). For the Observing and Describing facets, we did not formulate a specific hypothesis due to the conflicting evidence reported in the literature, especially for the Observing scale (see Lindsay & Creswell, 2007; Simione & Saldarini, 2023 ). METHODS Participants and procedure A Monte Carlo power analysis was conducted to estimate the appropriate sample size for this study, based on the indications outlined by Schoemann and colleagues ( 2017 ) for determining power and sample size in mediation models. To ensure adequate statistical power, we targeted a minimum power of 0.80. Using small-to-medium-sized correlation coefficients (ranging from 0.20 to 0.30), 1000 replications, 20,000 Monte Carlo draws per replication, and a 95% confidence interval, the analysis estimated that a sample size of approximately 200 participants would achieve 0.80 power. With 300 participants, the power would increase to 0.95. Consequently, we aimed to recruit about 300 participants. We enrolled 359 participants aged between 18 and 73 years (mean age = 34.82 ± 11.62; 77% females). The majority of our sample was composed of highly educated (64% with a tertiary degree) and employed (61%) individuals. One hundred and one (28%) participants reported a meditation practice (e.g., vipassana meditation, transcendental meditation) with an average of 321 ± 652 hours of practice over their lifetime. Twenty-five (7%) participants reported having or having been diagnosed with a mental health condition. Sixteen (4%) participants reported having or having been diagnosed with a sleep disorder. In terms of sleep hygiene habits, 16% of participants reported frequently consuming stimulating beverages in the evening (responding "Often" or "Always"), while 3% indicated they often engaged in physical activity during this time. Additionally, 23% reported often or always working in the evening, and 52% to engage in emotionally stimulating activities, such as watching TV, using social media, or playing video games. Finally, 13% of participants reported sleeping in an uncomfortable bed, while 16% indicated that their sleeping environment was uncomfortable. Participants were recruited through multiple channels, including social networking sites, online forums, and word of mouth. After reviewing the study's purpose and procedure and providing informed consent, participants were invited to complete a web-based survey hosted on Google Forms, which took approximately 20 minutes to complete. Participation was entirely voluntary, and all data were collected anonymously. If participants withdrew before completing the survey, their data were not retained. The study was conducted in accordance with the 1964 Declaration of Helsinki and its later amendments and approved by the Institutional Review Board of the [BLINDED]. Measures The survey included questions regarding demographic characteristics, medical history, sleep hygiene, and meditation experience, as well as self-administered scales assessing dispositional mindfulness, sleep reactivity, and insomnia symptoms severity. Demographic characteristics and medical history The following information was collected: age, gender, education, employment status, previous or current diagnosis of neurological or psychiatric conditions, and previous or current diagnosis of sleep disorders. Sleep hygiene Participants were asked four questions about their evening habits regarding the consumption of stimulating beverages, physical activity before bedtime, and cognitively or emotionally stimulating activities during the evening. They rated the frequency of each behavior on a scale from "Never" (0) to "Always" (4). Additionally, participants provided information about the comfort of their bed and sleeping environment, with responses recorded as "Yes" (1) or "No" (0). Meditation experience Participants were asked if they had ever engaged in any form of meditation. Those who answered affirmatively were then asked to specify the type of meditation practiced, the number of hours spent meditating each week, and the duration of their meditation practice in months. Dispositional Mindfulness The Five Facets Mindfulness Questionnaire – Short Form (FFMQ-SF; Bohlmeijer et al., 2011 ) was used to assess dispositional mindfulness. This self-report measure comprises 24 items, grouped into five subscales. The five subscales refers to the five mindfulness’s facets, namely Observing (e.g., “I notice the smells and aromas of things”), Describing (e.g., “I’m good at finding the words to describe my feelings”), Acting with awareness (e.g., “It seems I am “running on automatic” without much awareness of what I’m doing” [a reverse item]), Non-judging (e.g., “I make judgments about whether my thoughts are good or bad” [a reverse item]) and Non-reactivity (e.g., “When I have distressing thoughts or images, I just notice them and let them go”). Participants rated their agreement with each item on a 5-point Likert scale (1 = “Never or very rarely true”; 5 = “Very often or always true”). The scores for each subscale can range from 5 to 25, except for the Observing facet (range 5–20). Higher scores indicate higher levels of dispositional mindfulness. The Italian validated version (Iani et al., 2020 ) was submitted to the participants. In our sample, all subscales of the FFMQ-SF demonstrated good internal consistency, with Cronbach’s alpha values of 0.81, 0.80, 0.80, 0.81, and 0.71, and McDonald’s omega values of 0.82, 0.85, 0.86, 0.84, and 0.75, respectively. Sleep reactivity The Ford Insomnia Response to Stress Test (FIRST; Drake et al., 2004 ; italian adaptation by Palagini et al., 2016 ), a 9-item self-report scale, was used to assess sleep reactivity. Participants were asked to rate the likelihood of experiencing sleep difficulties in response to stressful life events, such as having a bad day at work or before having to speak in public, on a scale from 1 ("Not likely") to 4 ("Very likely"). The total score, calculated by summing the ratings for each item, can range from 9 to 36, with higher scores indicating greater levels of stress-related sleep reactivity. In our sample, the FIRST showed good internal consistency (Cronbach's alpha = 0.88 and McDonald's omega = 0.91). Insomnia The Insomnia Severity Index (ISI; Morin, C. M., 1993 ) was administered to assess the severity and impact of insomnia symptoms over a one-month period. This self-report questionnaire contains 7 items relating to the severity of nocturnal symptoms of insomnia (i.e. difficulties with sleep onset, sleep maintenance, and early morning awakenings), satisfaction with current sleep patterns, and severity of daytime consequences (i.e. interference of sleep problems with daily functioning, noticeability of sleep problems to others, and distress caused by these problems). Each item is rated on a 5-point Likert scale (e.g., 0 = no problem; 4 = very severe problem). The ISI total score ranges from 0 to 28, with higher scores indicating more severe insomnia symptoms. The Italian validation by Castronovo and colleagues ( 2016 ) was administered to the participants. In our sample, ISI total score revealed good internal consistency, with Cronbach's alpha = 0.85 and McDonald's omega = 0.91. Statistical analysis First, a bivariate Pearson’s correlation analysis was performed to examine the relationships between demographic, sleep-related, and psychological variables. Given the large number of correlations conducted, only those with r > 0.20 and p < 0.01 were considered significant. The purpose of this analysis was twofold: first, to verify the expected direction of the relationships between the variables, and second, to identify demographic variables that could be included as covariates in the subsequent mediation analysis. Then, we conducted a mediation model with the five subscales of the FFMQ-SF (Observing, Describing, Acting with Awareness, Non-judging and Non-reactivity) as individual predictors, the FIRST as the mediator, and the ISI as the dependent variable. Sex and sleep disorder diagnosis were included as covariates. The model was conducted through the statistical language R 4.4.1, using the “lavaan 0.6–19” package (Rosseel Y., 2012 ) for structured equation models (SEM) analysis, with bias-corrected 95% confidence intervals computed over 5000 bootstrap samples. RESULTS Initially, we calculated correlations between demographic, sleep-related, and psychological variables, as presented in Table 1 . The results revealed that age, meditation practice, and lifetime meditation hours were associated with higher scores on the Describing and Non-reactivity facets of mindfulness. Additionally, higher education levels were linked to increases in both the Describing and Non-judging facets. Moreover, being female was associated with higher sleep reactivity, while having a diagnosed sleep disorder was related to more severe insomnia symptoms. Given that only sex and the presence of a sleep disorder showed significant associations with stress and sleep-related variables, these two variables were included as covariates in the subsequent mediation analysis. Table 1 Correlation coefficients between demographic, sleep-related, and psychological variables. FFQM-SF Observing FFMQ-SF Describing FFMQ-SF Acting with awareness FFMQ-SF Non-judging FFMQ-SF Non-reacting FIRST ISI Age (in years) 0.05 0.20*** 0.05 0.18*** 0.20*** -0.05 -0.03 Sex 0.15** 0.03 0.01 -0.15** -0.11* 0.24*** 0.03 Education level (in years) 0.19*** 0.26*** 0.09 0.20*** 0.08 -0.06 -0.06 Presence of mental health condition -0.00 -0.02 -0.06 -0.12* -0.02 0.04 0.14** Sleep disorder diagnosis -0.01 -0.07 -0.04 -0.05 -0.07 0.12* 0.26*** Sleep hygiene: Stimulating substances -0.00 -0.03 -0.07 -0.04 0.03 -0.10 0.03 Sleep hygiene: Intense physical activity -0.05 -0.01 0.03 -0.05 0.02 -0.01 0.03 Sleep hygiene: Exciting activities -0.10 -0.13* -0.16** -0.14** -0.16** 0.05 0.08 Sleep hygiene: Studying or working 0.07 0.06 -0.01 -0.08 -0.07 0.04 0.07 Uncomfortable bed -0.01 -0.06 -0.06 -0.04 -0.07 0.01 0.09 Uncomfortable room -0.00 -0.09 -0.05 -0.03 -0.05 0.02 0.09 Meditation practice 0.19*** 0.24*** -0.01 0.13* 0.20*** -0.04 -0.06 Meditation expertise (in hours) 0.14** 0.23*** 0.04 0.19*** 0.26*** -0.07 -0.03 Note: Sex was coded as 0 = male, 1 = female. Education level was coded as years spent in education. Presence of mental health condition and sleep disorder diagnosis were coded as 0 = absent or not reported, 1 = present. Significance level is reported as *p < 0.05, **p < 0.01, ***p < 0.001. Next, correlations between the FFMQ-SF facets, the FIRST and the ISI were computed, with the results and corresponding descriptive statistics presented in Table 2 . As anticipated, the variables exhibited correlations in the expected directions. All subscales of the FFMQ-SF, except for Observing, showed significant negative correlations with both the FIRST and the ISI. Additionally, the FIRST was positively correlated with the ISI. Table 2 Descriptive statistics and correlation coefficients between psychological variables. M SD Observing Describing Acting with awareness Non-judging Non-reacting FIRST FFMQ-SF Observing 14.80 3.81 FFMQ-SF Describing 17.62 4.10 0.32*** FFMQ-SF Acting with awareness 18.11 4.35 0.05 0.34*** FFMQ-SF Non-judging 15.03 4.84 -0.07 0.27*** 0.40*** FFMQ-SF Non-reacting 14.01 3.77 0.27*** 0.36*** 0.08 0.25*** FIRST 21.01 6.45 0.09 -0.14** -0.17** -0.38*** -0.31*** ISI 7.11 5.29 0.05 -0.22*** -0.20*** -0.31*** -0.32*** 0.48*** Note: Significance level is reported as *p < 0.05, **p < 0.01, ***p < 0.001 Abbreviations: FFMQ-SF = Five Facets Mindfulness Questionnaire – Short Form; FIRST = Ford Insomnia Response to Stress Test; ISI = Insomnia Severity Index; M = Mean; SD = Standard Deviation We used SEM to assess direct and indirect paths from the five FFMQ-SF facets to the ISI through the FIRST (see Fig. 1 ). As the models were fully saturated, no fit statistics were reported. Path coefficients with their relative SE, upper and lower bootstrapped confidence intervals, and significance, are reported in Table 3 . To enhance clarity, we omitted the effects of covariates and nonsignificant paths from the main text. The full pattern of results, including these details, can be found in the Supplementary Materials (Supplementary Table 1). The model revealed that the FFMQ-SF Observing facet was related to a significant increase in the FIRST score, whereas the FFMQ-SF Non-judging and Non-reactivity facets were related to a significant decrease in the FIRST score. Additionally, both the FFMQ-SF Observing and Non-reactivity facets had significant direct effects on the ISI. Furthermore, the FIRST significantly increased the ISI. Regarding the indirect paths, a partially mediated effect was observed from the FFMQ-SF Observing and Non-reactivity facets to the ISI through the FIRST, while the relationship between the FFMQ-SF Non-judging facet and the ISI was fully mediated by the FIRST. The total effects of the FFMQ-SF Observing, Non-judging, and Non-reactivity facets on the ISI were all significant. In summary, these findings indicate that the Observing facet was associated with greater insomnia symptoms, partially mediated by heightened sleep reactivity. In contrast, the Non-judging and Non-reactivity facets reduced insomnia symptoms by decreasing sleep reactivity. Table 3 Path coefficients for mediation model with ISI as outcome. 95% CI Path Estimate SE LL UL p Observing → FIRST (a1) 0.202 0.098 0.007 0.358 0.040 Non-judging → FIRST (a4) -0.355 0.078 -0.510 -0.204 < 0.001 Non-reacting → FIRST (a5) -0.424 0.092 -0.607 -0.238 < 0.001 Direct effects Observing → ISI (c1) 0.156 0.072 0.016 0.299 0.031 Non-judging → ISI (c4) -0.076 0.065 -0.204 0.055 0.245 Non-reacting → ISI (c5) -0.265 0.076 -0.409 -0.108 0.001 FIRST → ISI (b) 0.302 0.044 0.219 0.38 < 0.001 Indirect effects Observing → FIRST → ISI 0.061 0.031 0.002 0.124 Non-judging → FIRST → ISI (a4 x b) -0.107 0.029 -0.169 -0.055 Non-reacting → FIRST → ISI (a5 x b) -0.128 0.03 -0.198 -0.066 Total effects Observing → ISI (c1 + a1 x b) 0.217 0.077 0.070 0.367 Non-judging → ISI (c4 + a4 x b) -0.183 0.066 -0.312 -0.050 Non-reacting → ISI (c5 + a5 x b) -0.393 0.078 -0.545 -0.235 Note. 95% CI = bootstrapped confidence intervals; LL and UL = lower and upper limits of CI. Abbreviations. FIRST = Ford Insomnia Response to Stress Test; ISI = Insomnia Severity Index. DISCUSSION The current study investigated the relationships between mindfulness facets, sleep reactivity, and insomnia symptoms, with the hypotheses that (i) mindfulness facets, in particular Acting with awareness, Non-judging and Non-reactivity, would be associated with lower sleep reactivity and decreased insomnia symptoms, and (ii) the relationship between mindfulness facets and insomnia symptoms would be mediated by a reduction in sleep reactivity. Overall, the results support these hypotheses, though not completely. Our first hypothesis was supported, consistently with the existing trends reported in the literature. In the correlation analyses, we confirmed the positive relationship between sleep reactivity and insomnia symptoms, aligning with previous findings (Kalmbach et al., 2018 ). Sleep reactivity has consistently been associated with increased insomnia severity, not only in clinical samples but also in studies involving general and healthy populations (Fernandez-Mendoza et al., 2010; Palagini et al., 2016 ). Furthermore, all FFMQ-SF subscales, except for Observing, were significantly negatively correlated with both the FIRST and ISI. Previous studies have shown that Acting with awareness, Non-judging and Non-reactivity facets are associated to lower levels of insomnia symptoms and reduced distress (Curado et al., 2018 ; Fong & Ho, 2020 ; Garland et al., 2013 ; Park et al., 2019; Talley & Shelley-Tremblay, 2020 ; Xie et al., 2023 ). We found that the strongest correlations with stress and sleep-related variables were associated with the Non-judging and Non-reactivity facets, whereas the Acting with awareness facet demonstrated a weaker relationship. In addition, we found a negative correlation between the Describing facet and stress- and sleep-related variables. Instead, no significant correlation was observed between the Observing facet and any of the outcome variables. Previous studies have reported contrasting findings regarding the Describing and Observing facets of mindfulness. These inconsistencies may stem from differences in sample characteristics and the instrument used to assess the constructs under study, other than to intrinsic problems with the construct actually assessed by the scale (Redkin et al., 2018; Simione & Saldarini, 2023 ). To address this variability, future research should undertake a systematic review of studies employing the FFMQ, aiming to identify methodological and contextual factors that may have contributed to the divergent findings observed in the literature. Regarding our second hypothesis, we found that sleep reactivity was a significant mediator in the relationship between three mindfulness facets and insomnia. Some studies have explored the mediating role of variables associated with emotional distress and stress reactivity (e.g., hyperarousal, negative affect, psychological stress) in the relationship between mindfulness and sleep quality (Simione et al., 2020 ; Fong et al., 2020; Ding et al., 2020 ; Talley, 2020 ). However, to our knowledge, no previous study has investigated the mediating role of sleep reactivity in the relationship between mindfulness facets and insomnia symptoms. Importantly, sleep reactivity, as a sleep-specific dimension of stress reactivity, is closely related to hyperarousal (Fernandez-Mendoza et al., 2010; Kalmbach et al., 2018 ). In insomnia models, hyperarousal appears to be a central phenomenon in the development and maintenance of this sleep disturbance. In fact, individuals with insomnia exhibit heightened physiological, cortical, and cognitive/emotional arousal (Dressle & Riemann, 2023 ; Riemann et al., 2010 ). Specifically, in the cognitive/emotional domain, individuals with insomnia often exhibit difficulties coping with stressful situations and in regulating emotions. For instance, individuals with insomnia tend to perceive life events as more stressful (Morin et al., 2003 ) and experience greater difficulties in resolving emotional distress related to both past and novel emotional experiences (Wassing et al., 2019 ). Importantly, these difficulties are not limited to individuals with chronic insomnia but are also observed in those predisposed to insomnia and with high sleep reactivity (Fernandez-Mendoza et al., 2010). Therefore, future studies should further investigate aspects of emotion regulation in healthy populations with varying levels of sleep reactivity, given its role as a risk factor for both acute and chronic insomnia (Jarrin et al., 2014 ; Walker et al., 2022 ). Additionally, preventive mindfulness-based interventions targeting improved coping strategies for stress and enhanced emotional regulation could potentially serve as protective measures against sleep difficulties in individuals with higher levels of this characteristic. Not only did our study aim to assess the mediating role of sleep reactivity, but it also sought to investigate the individual contributions of mindfulness facets within this mediation model. In our study, the facets of Non-Judging and Non-Reacting were found to decrease sleep reactivity, which in turn led to a reduction in the severity of insomnia symptoms. The Monitoring and Acceptance Theory (MAT; Lindsay & Creswell, 2017 ) frames these two facets within the broader construct of acceptance. Rather than viewing acceptance as passive resignation to (negative) life events, the MAT conceptualises it as an attitude of openness and curiosity towards all life experiences that, in combination with attention monitoring, i.e., awareness, leads to a better mental state. This involves acknowledging them and allowing them to arise and pass without judgement or reactivity. As an emotion regulation strategy, acceptance involves approaching emotional experiences with openness, rather than avoiding them, actively trying to change them, or hyperfixating on them (Lindsay & Creswell, 2019 ). This approach potentially explains the observed benefits of mindfulness training in altering affective responses, reducing stress reactivity, and improving stress-related health outcomes (Lindsay & Creswell, 2017 ; Lindsay et al., 2018 ), beyond its interaction with awareness (Simione et al., 2021 ; Simione & Saldarini, 2024). Research supports the idea that higher levels of acceptance are linked to better sleep outcomes (Black et al., 2015 ; Fong & Ho, 2020 ; Mirolli et al., 2021 ; Tzioridou et al., 2022 ). In addition, several authors have suggested over the years that cultivating acceptance through mindfulness practices—both toward the mental and physical processes that precede sleep and toward beliefs and attitudes about sleep—may promote the cognitive and physiological deactivation necessary for falling asleep (Lundh, 2005 ; Ong et al., 2012 ; Shallcross et al., 2019 ). This acceptance-based approach may also facilitate a shift in perspective that interrupts the cycle of negative emotions and maladaptive behaviors that contribute to the maintenance of chronic insomnia (Ong et al., 2012 ; Shallcross et al., 2019 ). In these views, the way individuals approach stressors is critical because it regulates their physiological and psychological responses to stress. Adopting an acceptance-based attitude toward thoughts, emotions, and sensations related to sleep can reduce arousal and stress reactivity, thereby improving sleep quality. While the path from Non-judging and Non-reacting through sleep reactivity led to a decrease in insomnia severity, we observed that the path from the FFMQ-SF Observing subscale was associated with increased insomnia severity through heightened sleep reactivity. This finding, despite anomalous, is in line with previous literature, which have shown a positive association between this subscale of the FFMQ and variables linked to psychological distress and emotional reactivity (Baer et al., 2006 ). Interestingly, the association between the Observing facet of mindfulness and psychological symptoms is found in studies involving samples of non-meditators, while in samples of long-term meditators, it is not usually reported (Baer et al., 2008 ). In our study, which used a convenience sample of the adult general population, even though nearly 30% of participants reported being involved in a meditation practice, the majority were not. Therefore, the characteristics of our sample may have influenced this particular finding. Several authors have attempted to explain the odd behavior of this specific FFMQ subscale. One possible explanation could be the way participants interpret the items in the subscale, which may differ between non-meditators and meditators (Baer et al., 2008 ). Furthermore, the Observing subscale includes items targeting mainly body awareness and awareness of external perceptions, while completely lacking items related to emotional awareness - a construct negatively related to psychological symptoms (Rudkin et al., 2018 ). As a result, the Observing facet might capture a form of maladaptive monitoring, rather than genuine mindful monitoring. In this regard, a recent review (Simione & Pieroni, 2023 ) suggested that the positive relationship between the FFMQ Observing and psychological symptoms may be influenced by a third variable, namely sensory-processing sensitivity (SPS; Aron & Aron, 1997 ), which could act as a confounder in this relationship. SPS is characterized by heightened awareness of environmental stimuli and increased reactivity to them (Aron & Aron, 1997 ; Greven et al., 2019 ). The authors of the review argue that, in dispositional studies involving non-meditators, the assessment of mindful awareness using the Observing subscale of the FFMQ may be confounded by SPS, as this trait reflects an inherent, involuntary attention to stimuli - unlike mindful awareness, which involves a deliberate and intentional focus on present-moment experiences (Simione & Pieroni, 2023 ). Notably, a recent study found evidence linking SPS with sleep reactivity and insomnia (Pieroni et al., 2023 ). To address this potential confound, future research employing the FFMQ would benefit from incorporating a scale to assess SPS. This addition could help disentangle the extent to which the Observing facet of mindfulness overlaps with the construct of SPS. Finally, another potential explanation for our finding stems from the MAT (Lindsay & Creswell, 2017 ). According to MAT, the capacity to monitor ongoing experiences—whether naturally heightened or enhanced through training—can increase awareness of both positive and negative affective information. For individuals who lack training in monitoring present-moment experiences with an accepting attitude or who have dispositionally low acceptance skills, this heightened awareness, particularly of unpleasant or negative experiences, may amplify stress reactivity. Such increased reactivity could, in turn, exacerbate psychological symptoms. Building on this reasoning, it is plausible that heightened awareness of present-moment experiences could amplify the perception of and attention to sleep-interfering stimuli, such as somatic sensations of arousal, ruminative thoughts, or environmental distractions. This increased focus on such stimuli may, in turn, heighten the susceptibility of the sleep system to respond reactively to these stressors, resulting in sleep disruptions. This perspective is supported by two recent studies that found that the nonreactivity facet act as a moderator in the relationship between the observing facet and sleep outcomes (Lau et al., 2018 ; Xie et al., 2023 ). These findings suggest that the presence of acceptance-related skills, such as nonreactivity, may play a critical role in mitigating the potentially negative impact of heightened awareness on sleep outcomes. In the present study, we primarily focused on investigating whether sleep reactivity serves as a mediator between mindfulness and insomnia and aimed to explore the individual contributions of the five mindfulness facets to this relationship. However, we did not specifically examine whether variations in acceptance-related facets, such as nonjudging and nonreactivity, might alter the relationship between the observing facet and sleep-related outcomes. Future studies should address this gap by systematically exploring how the interplay between the observing and acceptance facets influences sleep outcomes. Such research could help clarify the mechanisms through which mindfulness-based interventions impact sleep and identify specific components of mindfulness that may be most beneficial for individuals with heightened sleep reactivity or insomnia. Finally, it is noteworthy that the Acting with Awareness facet did not play a role in our mediation model, despite correlational analyses suggesting its association with reductions in both sleep reactivity and insomnia severity. Moreover, a previous longitudinal study conducted with colorectal cancer survivors found that Acting with Awareness, alongside Non-Judging and Non-Reacting, significantly predicted better sleep quality indirectly through reductions in emotional distress (Fong et al., 2020). However, that study differs from ours in several key methodological aspects, including the research design, the population under investigation, and the type of self-report measures employed. Future research should aim to address these discrepancies by examining the role of Acting with Awareness in relation to stress and sleep outcomes across varied populations and study designs, offering greater clarity on its potential contribution to improving sleep health. LIMITATIONS The findings of the present study should be interpreted in light of several limitations. First, the cross-sectional design of the study precludes any definitive conclusions about the directionality or causality of the relationships observed between mindfulness facets, stress, and sleep-related variables. Longitudinal and experimental studies are needed to better understand these relationships over time. For instance, exploring whether mindfulness training, particularly among individuals at risk for insomnia, offers sustained protection for sleep health could yield valuable insights. Another significant limitation is the exclusive reliance on self-report measures, which may have introduced biases related to participants' perceptions and retrospective recall. Future research should incorporate objective assessments of sleep, such as actigraphy, polysomnography (PSG), or physiological measures of stress (e.g., heart rate variability), to provide a more robust and nuanced understanding of the relationships between mindfulness, stress, and sleep outcomes. The sampling method also poses challenges to the generalizability of the findings. The use of a convenience sample may not adequately represent broader populations. Moreover, the sample was predominantly composed of women (70%) and included a significant proportion of meditators (30%), which could have influenced the observed relationships between mindfulness and sleep. Future studies should aim for more diverse and representative samples, employing stratified or random sampling methods to improve generalizability and provide insights into specific subgroups, such as individuals with chronic insomnia. Additionally, while meditation practice was included as a variable in the study, its operationalization as cumulative lifetime hours of practice may have limited its explanatory power. This approach does not account for important contextual factors, such as the frequency or recency of practice. For example, a recent study (Tzioridou et al., 2023) demonstrated that while cumulative mindfulness practice was associated with nightmare frequency, it did not predict nightmare distress. Furthermore, the time elapsed since the last meditation session was found to correlate with sleep variables, with longer intervals associated with increased nightmare occurrence (Tzioridou et al., 2023). These findings highlight the need for more precise and comprehensive measures of meditation practice in future studies, including the timing, intensity, and type of meditation practice. Declarations Author Contribution All the authors contributed to the design and implementation of the research, to the analysis of the results and to the writing of the manuscript. Data Availability The data that support the findings of this study are available from the corresponding author upon request. References Aron, E. N., & Aron, A. (1997). 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04:18:36","extension":"html","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":183833,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7829160/v1/37c8d63596aecedc450b4b76.html"},{"id":94622646,"identity":"1b0b7151-2705-4368-8de9-2a756a087521","added_by":"auto","created_at":"2025-10-29 04:18:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":74030,"visible":true,"origin":"","legend":"\u003cp\u003eThe mediation model tested, from the FFMQ-SF facets to the ISI through the FIRST. For clarity, covariates and their relative paths are not represented\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7829160/v1/52929095198d4c6b8553ffb6.png"},{"id":96252856,"identity":"f5e3fd24-8418-44c6-9469-8c2d3429f6f2","added_by":"auto","created_at":"2025-11-19 07:41:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1147349,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7829160/v1/6acadb67-a8ed-407e-a33c-7f9db7f6c449.pdf"},{"id":94622696,"identity":"a220393b-a39e-4063-9534-524c3d53568a","added_by":"auto","created_at":"2025-10-29 04:18:28","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":10320,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable1Mindfulnesssleepreactivityandinsomnia.docx","url":"https://assets-eu.researchsquare.com/files/rs-7829160/v1/f0b46e0dcf745a1c5a4f46ae.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Sleep reactivity as a mediator in the relationship between trait mindfulness and insomnia: a correlational study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eInsomnia is a common chronic sleep disorder characterised by both nocturnal symptoms and daytime consequences. People with insomnia typically report difficulty falling asleep and/or staying asleep, dissatisfaction with sleep quantity and/or quality, as well as daytime fatigue, cognitive impairments and mood disturbances. Around one-third of the general population experience temporary insomnia symptoms, while up to 10% of the adult population is diagnosed with insomnia (Morin et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Ohayon, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Several psychobiological models of insomnia have been proposed to explain the mechanisms involved in the aetiology of this sleep disorder, as various factors have been identified as contributing to its onset and maintenance. However, it is well established in the literature that stress is a key factor in its development (Bastien et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Healey et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1981\u003c/span\u003e). According to the 3P model of Spielman et al. (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1987\u003c/span\u003e), stress is a precipitating factor that can interact with individual predispositions, such as temperamental and personality traits, increasing the likelihood of sleep problems. These problems can then be maintained and exacerbated by perpetuating factors, such as poor sleep hygiene and hyperarousal (Spielman et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). The first-line non-pharmacological treatment for insomnia is cognitive-behavioral therapy for insomnia (CBT-I; Edinger et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, in recent years, mindfulness approaches have also been proposed and studied as an alternative treatment for insomnia (Ong et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eMindfulness is defined as \u0026ldquo;the awareness that emerges through paying attention on purpose, in the present moment, and nonjudgmentally to the unfolding of experience moment by moment\u0026rdquo; (Kabat- Zinn, 2003, p. 145). As such, mindfulness can be considered both a \u003cem\u003estate\u003c/em\u003e that can be cultivated through formal meditation practices specifically designed to enhance this particular form of awareness (Bishop et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Carmody \u0026amp; Baer, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), and a \u003cem\u003edisposition\u003c/em\u003e or trait-like quality of attention that individuals naturally possess to varying degrees, regardless of mindfulness meditation practice (Brown \u0026amp; Ryan, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Dispositional or trait mindfulness can be assessed using various self-report measures. One of the most widely used questionnaires in the literature is the Five Facet Mindfulness Questionnaire (FFMQ; Baer et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). This questionnaire conceptualizes mindfulness as a multidimensional construct characterized by five distinct components, namely Observing (i.e., noticing and attending to both internal and external experiences such as sensations, thoughts and feelings), Describing (i.e., being able to describe and label internal experiences with words), Acting with awareness (i.e, being present and attentive while doing things, as opposed to doing things on \u0026ldquo;automatic pilot\u0026rdquo;), Non-judging of inner experiences (i.e. taking a non-evaluative stance towards thoughts and feelings), and Non-reactivity to inner experiences (i.e. allowing all inner experiences to come and go without getting caught up or carried away by them). Alternative questionnaires relating to different operationalisations of the mindfulness construct have also been proposed (Bergomi et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), but for the purposes of this article we will adopt Baer's self-report instrument.\u003c/p\u003e\u003cp\u003eA substantial body of research has shown that both dispositional mindfulness and practicing mindfulness meditation are associated with improvements in several indicators of mental health and well-being, including improved sleep quality and reduced insomnia severity (Garland et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Rusch et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Correlational studies using the FFMQ in both clinical and non-clinical samples have shown that the Acting with Awareness, Non-judging and Non-reactivity facets of the FFMQ are consistently associated with better sleep quality and lower insomnia severity (Curado et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fong \u0026amp; Ho, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Garland et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Park et al., 2019; Talley \u0026amp; Shelley-Tremblay, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Xie et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). On the other hand, results for the Observe and Describe facets are more inconsistent. For example, while one study has reported a positive association between the Describe facet and improved sleep quality (Park et al., 2019), others have found no significant relationship between this facet and sleep outcomes (Garland et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Talley \u0026amp; Shelley-Tremblay, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Xie et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Similarly, research on the Observe facet has yielded mixed results, with some studies linking higher levels of Observe to increased sleep disturbances (Curado et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Talley \u0026amp; Shelley-Tremblay, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), while others have found no association at all (Fong \u0026amp; Ho, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Garland et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Park et al., 2019; Xie et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In addition, studies investigating the effects of MBIs on improving sleep in populations with sleep difficulties or suffering of insomnia generally report some improvements in both subjective and objective sleep parameters (Rusch et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2019\u003c/span\u003e9, further highlighting the potential of mindfulness practices as promising tools for improving sleep health (Ong et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Despite the positive relationship between mindfulness and improved sleep, the mechanisms and factors through which mindfulness exerts its beneficial effects, particularly in relation to insomnia, remain understudied.\u003c/p\u003e\u003cp\u003eGiven the well-established role of mindfulness as a stress-reduction practice (Britton et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Hoge et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), it is reasonable to hypothesize that its stress-reducing effects may contribute to improvements in sleep. Indeed, recent studies have demonstrated that the link between mindfulness and sleep quality may be mediated by reductions in psychological stress (Lau et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Simione et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), emotional distress (Fong \u0026amp; Ho, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and negative affect (Ding et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). All these studies underscore the well-established impact of mindfulness on stress as a crucial mechanism for alleviating sleep problems. As highlighted by Ong et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), mindfulness may alleviate insomnia primarily by altering one's relationship with stressors, thereby reducing their impact at bedtime. Dispositional reactivity to these stressors may thus mediate this effect, with mindfulness potentially attenuating a sleep-specific aspect of stress reactivity, known as sleep reactivity (Kalmbach et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSleep reactivity is defined as the susceptibility to experiencing disturbed sleep following exposure to situations that could be perceived as stressors (Kalmbach et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Individuals with high sleep reactivity are more likely to experience acute sleep difficulties in response to stress, even from mild stressors like sleeping in a new environment - situations that typically do not affect those with lower levels of sleep reactivity (Drake et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Sleep reactivity has been linked to increased pre-sleep cognitive and somatic hyperarousal, neuroticism, and rumination in healthy populations (Fern\u0026aacute;ndez-Mendoza et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Additionally, it has been identified as a risk factor for the development of chronic insomnia (Drake et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Jarrin et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Kalmbach et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThus, the present correlational study aimed to examine the relationships between mindfulness facets, sleep reactivity, and insomnia symptoms. Based on the reviewed evidence, we hypothesized that sleep reactivity would positively correlate with insomnia severity. In addition, as the majority of correlational studies have primarily relied on global measures of mindfulness, the decision was taken to examine the individual effect of each mindfulness facet. Thus, we hypothesized that higher mindfulness scores would be associated with lower sleep reactivity and insomnia severity, in particular for the Acting with Awareness, Nonjudging, and Nonreactivity mindfulness facets, that have been already reported as effective in this context (Curado et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fong \u0026amp; Ho, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Garland et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Park et al., 2019; Talley \u0026amp; Shelley-Tremblay, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Xie et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). We further hypothesized that sleep reactivity would mediate the relationship between these mindfulness facets and insomnia severity, given the established links between stress and both mindfulness (Britton et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Hoge et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and insomnia symptoms (Kalmbach et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Morin et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). For the Observing and Describing facets, we did not formulate a specific hypothesis due to the conflicting evidence reported in the literature, especially for the Observing scale (see Lindsay \u0026amp; Creswell, 2007; Simione \u0026amp; Saldarini, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eParticipants and procedure\u003c/h2\u003e\u003cp\u003eA Monte Carlo power analysis was conducted to estimate the appropriate sample size for this study, based on the indications outlined by Schoemann and colleagues (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) for determining power and sample size in mediation models. To ensure adequate statistical power, we targeted a minimum power of 0.80. Using small-to-medium-sized correlation coefficients (ranging from 0.20 to 0.30), 1000 replications, 20,000 Monte Carlo draws per replication, and a 95% confidence interval, the analysis estimated that a sample size of approximately 200 participants would achieve 0.80 power. With 300 participants, the power would increase to 0.95. Consequently, we aimed to recruit about 300 participants.\u003c/p\u003e\u003cp\u003eWe enrolled 359 participants aged between 18 and 73 years (mean age\u0026thinsp;=\u0026thinsp;34.82\u0026thinsp;\u0026plusmn;\u0026thinsp;11.62; 77% females). The majority of our sample was composed of highly educated (64% with a tertiary degree) and employed (61%) individuals. One hundred and one (28%) participants reported a meditation practice (e.g., vipassana meditation, transcendental meditation) with an average of 321\u0026thinsp;\u0026plusmn;\u0026thinsp;652 hours of practice over their lifetime. Twenty-five (7%) participants reported having or having been diagnosed with a mental health condition. Sixteen (4%) participants reported having or having been diagnosed with a sleep disorder. In terms of sleep hygiene habits, 16% of participants reported frequently consuming stimulating beverages in the evening (responding \"Often\" or \"Always\"), while 3% indicated they often engaged in physical activity during this time. Additionally, 23% reported often or always working in the evening, and 52% to engage in emotionally stimulating activities, such as watching TV, using social media, or playing video games. Finally, 13% of participants reported sleeping in an uncomfortable bed, while 16% indicated that their sleeping environment was uncomfortable.\u003c/p\u003e\u003cp\u003eParticipants were recruited through multiple channels, including social networking sites, online forums, and word of mouth. After reviewing the study's purpose and procedure and providing informed consent, participants were invited to complete a web-based survey hosted on Google Forms, which took approximately 20 minutes to complete. Participation was entirely voluntary, and all data were collected anonymously. If participants withdrew before completing the survey, their data were not retained.\u003c/p\u003e\u003cp\u003eThe study was conducted in accordance with the 1964 Declaration of Helsinki and its later amendments and approved by the Institutional Review Board of the [BLINDED].\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cp\u003eThe survey included questions regarding demographic characteristics, medical history, sleep hygiene, and meditation experience, as well as self-administered scales assessing dispositional mindfulness, sleep reactivity, and insomnia symptoms severity.\u003c/p\u003e\n\u003ch3\u003eDemographic characteristics and medical history\u003c/h3\u003e\n\u003cp\u003eThe following information was collected: age, gender, education, employment status, previous or current diagnosis of neurological or psychiatric conditions, and previous or current diagnosis of sleep disorders.\u003c/p\u003e\n\u003ch3\u003eSleep hygiene\u003c/h3\u003e\n\u003cp\u003eParticipants were asked four questions about their evening habits regarding the consumption of stimulating beverages, physical activity before bedtime, and cognitively or emotionally stimulating activities during the evening. They rated the frequency of each behavior on a scale from \"Never\" (0) to \"Always\" (4). Additionally, participants provided information about the comfort of their bed and sleeping environment, with responses recorded as \"Yes\" (1) or \"No\" (0).\u003c/p\u003e\n\u003ch3\u003eMeditation experience\u003c/h3\u003e\n\u003cp\u003eParticipants were asked if they had ever engaged in any form of meditation. Those who answered affirmatively were then asked to specify the type of meditation practiced, the number of hours spent meditating each week, and the duration of their meditation practice in months.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eDispositional Mindfulness\u003c/h2\u003e\u003cp\u003eThe Five Facets Mindfulness Questionnaire \u0026ndash; Short Form (FFMQ-SF; Bohlmeijer et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) was used to assess dispositional mindfulness. This self-report measure comprises 24 items, grouped into five subscales. The five subscales refers to the five mindfulness\u0026rsquo;s facets, namely Observing (e.g., \u0026ldquo;I notice the smells and aromas of things\u0026rdquo;), Describing (e.g., \u0026ldquo;I\u0026rsquo;m good at finding the words to describe my feelings\u0026rdquo;), Acting with awareness (e.g., \u0026ldquo;It seems I am \u0026ldquo;running on automatic\u0026rdquo; without much awareness of what I\u0026rsquo;m doing\u0026rdquo; [a reverse item]), Non-judging (e.g., \u0026ldquo;I make judgments about whether my thoughts are good or bad\u0026rdquo; [a reverse item]) and Non-reactivity (e.g., \u0026ldquo;When I have distressing thoughts or images, I just notice them and let them go\u0026rdquo;). Participants rated their agreement with each item on a 5-point Likert scale (1 = \u0026ldquo;Never or very rarely true\u0026rdquo;; 5 = \u0026ldquo;Very often or always true\u0026rdquo;). The scores for each subscale can range from 5 to 25, except for the Observing facet (range 5\u0026ndash;20). Higher scores indicate higher levels of dispositional mindfulness. The Italian validated version (Iani et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) was submitted to the participants. In our sample, all subscales of the FFMQ-SF demonstrated good internal consistency, with Cronbach\u0026rsquo;s alpha values of 0.81, 0.80, 0.80, 0.81, and 0.71, and McDonald\u0026rsquo;s omega values of 0.82, 0.85, 0.86, 0.84, and 0.75, respectively.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSleep reactivity\u003c/h3\u003e\n\u003cp\u003eThe Ford Insomnia Response to Stress Test (FIRST; Drake et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; italian adaptation by Palagini et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), a 9-item self-report scale, was used to assess sleep reactivity. Participants were asked to rate the likelihood of experiencing sleep difficulties in response to stressful life events, such as having a bad day at work or before having to speak in public, on a scale from 1 (\"Not likely\") to 4 (\"Very likely\"). The total score, calculated by summing the ratings for each item, can range from 9 to 36, with higher scores indicating greater levels of stress-related sleep reactivity. In our sample, the FIRST showed good internal consistency (Cronbach's alpha\u0026thinsp;=\u0026thinsp;0.88 and McDonald's omega\u0026thinsp;=\u0026thinsp;0.91).\u003c/p\u003e\n\u003ch3\u003eInsomnia\u003c/h3\u003e\n\u003cp\u003eThe Insomnia Severity Index (ISI; Morin, C. M., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) was administered to assess the severity and impact of insomnia symptoms over a one-month period. This self-report questionnaire contains 7 items relating to the severity of nocturnal symptoms of insomnia (i.e. difficulties with sleep onset, sleep maintenance, and early morning awakenings), satisfaction with current sleep patterns, and severity of daytime consequences (i.e. interference of sleep problems with daily functioning, noticeability of sleep problems to others, and distress caused by these problems). Each item is rated on a 5-point Likert scale (e.g., 0\u0026thinsp;=\u0026thinsp;no problem; 4\u0026thinsp;=\u0026thinsp;very severe problem). The ISI total score ranges from 0 to 28, with higher scores indicating more severe insomnia symptoms. The Italian validation by Castronovo and colleagues (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) was administered to the participants. In our sample, ISI total score revealed good internal consistency, with Cronbach's alpha\u0026thinsp;=\u0026thinsp;0.85 and McDonald's omega\u0026thinsp;=\u0026thinsp;0.91.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eFirst, a bivariate Pearson\u0026rsquo;s correlation analysis was performed to examine the relationships between demographic, sleep-related, and psychological variables. Given the large number of correlations conducted, only those with r\u0026thinsp;\u0026gt;\u0026thinsp;0.20 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 were considered significant. The purpose of this analysis was twofold: first, to verify the expected direction of the relationships between the variables, and second, to identify demographic variables that could be included as covariates in the subsequent mediation analysis.\u003c/p\u003e\u003cp\u003eThen, we conducted a mediation model with the five subscales of the FFMQ-SF (Observing, Describing, Acting with Awareness, Non-judging and Non-reactivity) as individual predictors, the FIRST as the mediator, and the ISI as the dependent variable. Sex and sleep disorder diagnosis were included as covariates. The model was conducted through the statistical language R 4.4.1, using the \u0026ldquo;lavaan 0.6\u0026ndash;19\u0026rdquo; package (Rosseel Y., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) for structured equation models (SEM) analysis, with bias-corrected 95% confidence intervals computed over 5000 bootstrap samples.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eInitially, we calculated correlations between demographic, sleep-related, and psychological variables, as presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The results revealed that age, meditation practice, and lifetime meditation hours were associated with higher scores on the Describing and Non-reactivity facets of mindfulness. Additionally, higher education levels were linked to increases in both the Describing and Non-judging facets. Moreover, being female was associated with higher sleep reactivity, while having a diagnosed sleep disorder was related to more severe insomnia symptoms. Given that only sex and the presence of a sleep disorder showed significant associations with stress and sleep-related variables, these two variables were included as covariates in the subsequent mediation analysis.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelation coefficients between demographic, sleep-related, and psychological variables.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFFQM-SF Observing\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFFMQ-SF\u003c/p\u003e\u003cp\u003eDescribing\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFFMQ-SF Acting with awareness\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFFMQ-SF Non-judging\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eFFMQ-SF Non-reacting\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFIRST\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eISI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge (in years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.20***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.18***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.20***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.15**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.15**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.11*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.24***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducation level (in years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.19***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.26***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.20***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePresence of mental health condition\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.12*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.14**\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSleep disorder diagnosis\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.12*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.26***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSleep hygiene: Stimulating substances\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSleep hygiene: Intense physical activity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSleep hygiene: Exciting activities\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.13*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.16**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.14**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.16**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSleep hygiene: Studying or working\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eUncomfortable bed\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eUncomfortable room\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e-0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMeditation practice\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.19***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.24***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.13*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.20***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMeditation expertise (in hours)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.14**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.23***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.19***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.26***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003eNote: Sex was coded as 0\u0026thinsp;=\u0026thinsp;male, 1\u0026thinsp;=\u0026thinsp;female. Education level was coded as years spent in education. Presence of mental health condition and sleep disorder diagnosis were coded as 0\u0026thinsp;=\u0026thinsp;absent or not reported, 1\u0026thinsp;=\u0026thinsp;present. Significance level is reported as *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eNext, correlations between the FFMQ-SF facets, the FIRST and the ISI were computed, with the results and corresponding descriptive statistics presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. As anticipated, the variables exhibited correlations in the expected directions. All subscales of the FFMQ-SF, except for Observing, showed significant negative correlations with both the FIRST and the ISI. Additionally, the FIRST was positively correlated with the ISI.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescriptive statistics and correlation coefficients between psychological variables.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eM\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eObserving\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eDescribing\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eActing with awareness\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNon-judging\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eNon-reacting\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eFIRST\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFFMQ-SF Observing\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFFMQ-SF Describing\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e17.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.32***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFFMQ-SF Acting with awareness\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e18.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.34***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFFMQ-SF Non-judging\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e15.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.27***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.40***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFFMQ-SF Non-reacting\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.27***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.36***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.25***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFIRST\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e21.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.14**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.17**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.38***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.31***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eISI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.22***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.20***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-0.31***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e-0.32***\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.48***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cem\u003eNote: Significance level is reported as *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01, ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cem\u003eAbbreviations: FFMQ-SF\u0026thinsp;=\u0026thinsp;Five Facets Mindfulness Questionnaire \u0026ndash; Short Form; FIRST\u0026thinsp;=\u0026thinsp;Ford Insomnia Response to Stress Test; ISI\u0026thinsp;=\u0026thinsp;Insomnia Severity Index; M\u0026thinsp;=\u0026thinsp;Mean; SD\u0026thinsp;=\u0026thinsp;Standard Deviation\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWe used SEM to assess direct and indirect paths from the five FFMQ-SF facets to the ISI through the FIRST (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). As the models were fully saturated, no fit statistics were reported. Path coefficients with their relative SE, upper and lower bootstrapped confidence intervals, and significance, are reported in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. To enhance clarity, we omitted the effects of covariates and nonsignificant paths from the main text. The full pattern of results, including these details, can be found in the Supplementary Materials (Supplementary Table\u0026nbsp;1). The model revealed that the FFMQ-SF Observing facet was related to a significant increase in the FIRST score, whereas the FFMQ-SF Non-judging and Non-reactivity facets were related to a significant decrease in the FIRST score. Additionally, both the FFMQ-SF Observing and Non-reactivity facets had significant direct effects on the ISI. Furthermore, the FIRST significantly increased the ISI. Regarding the indirect paths, a partially mediated effect was observed from the FFMQ-SF Observing and Non-reactivity facets to the ISI through the FIRST, while the relationship between the FFMQ-SF Non-judging facet and the ISI was fully mediated by the FIRST. The total effects of the FFMQ-SF Observing, Non-judging, and Non-reactivity facets on the ISI were all significant. In summary, these findings indicate that the Observing facet was associated with greater insomnia symptoms, partially mediated by heightened sleep reactivity. In contrast, the Non-judging and Non-reactivity facets reduced insomnia symptoms by decreasing sleep reactivity.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePath coefficients for mediation model with ISI as outcome.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePath\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEstimate\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUL\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eObserving \u0026rarr; FIRST (a1)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.202\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.358\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.040\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNon-judging \u0026rarr; FIRST (a4)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.355\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.510\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.204\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNon-reacting \u0026rarr; FIRST (a5)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.424\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.092\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.607\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.238\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eDirect effects\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eObserving \u0026rarr; ISI (c1)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.156\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.072\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.299\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.031\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNon-judging \u0026rarr; ISI (c4)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.076\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.065\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.204\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.245\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNon-reacting \u0026rarr; ISI (c5)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.076\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.409\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.108\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFIRST \u0026rarr; ISI (b)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.302\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.219\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eIndirect effects\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eObserving \u0026rarr; FIRST \u0026rarr; ISI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.031\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.124\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNon-judging \u0026rarr; FIRST \u0026rarr; ISI (a4 x b)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.107\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.029\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.169\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNon-reacting \u0026rarr; FIRST \u0026rarr; ISI (a5 x b)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.198\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eTotal effects\u003c/span\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eObserving \u0026rarr; ISI (c1\u0026thinsp;+\u0026thinsp;a1 x b)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.217\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.077\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.070\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.367\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNon-judging \u0026rarr; ISI (c4\u0026thinsp;+\u0026thinsp;a4 x b)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.312\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNon-reacting \u0026rarr; ISI (c5\u0026thinsp;+\u0026thinsp;a5 x b)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.393\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.545\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e-0.235\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eNote. 95% CI\u0026thinsp;=\u0026thinsp;bootstrapped confidence intervals; LL and UL\u0026thinsp;=\u0026thinsp;lower and upper limits of CI.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eAbbreviations. FIRST\u0026thinsp;=\u0026thinsp;Ford Insomnia Response to Stress Test; ISI\u0026thinsp;=\u0026thinsp;Insomnia Severity Index.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe current study investigated the relationships between mindfulness facets, sleep reactivity, and insomnia symptoms, with the hypotheses that (i) mindfulness facets, in particular Acting with awareness, Non-judging and Non-reactivity, would be associated with lower sleep reactivity and decreased insomnia symptoms, and (ii) the relationship between mindfulness facets and insomnia symptoms would be mediated by a reduction in sleep reactivity. Overall, the results support these hypotheses, though not completely.\u003c/p\u003e\u003cp\u003eOur first hypothesis was supported, consistently with the existing trends reported in the literature. In the correlation analyses, we confirmed the positive relationship between sleep reactivity and insomnia symptoms, aligning with previous findings (Kalmbach et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Sleep reactivity has consistently been associated with increased insomnia severity, not only in clinical samples but also in studies involving general and healthy populations (Fernandez-Mendoza et al., 2010; Palagini et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Furthermore, all FFMQ-SF subscales, except for Observing, were significantly negatively correlated with both the FIRST and ISI. Previous studies have shown that Acting with awareness, Non-judging and Non-reactivity facets are associated to lower levels of insomnia symptoms and reduced distress (Curado et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fong \u0026amp; Ho, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Garland et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Park et al., 2019; Talley \u0026amp; Shelley-Tremblay, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Xie et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). We found that the strongest correlations with stress and sleep-related variables were associated with the Non-judging and Non-reactivity facets, whereas the Acting with awareness facet demonstrated a weaker relationship. In addition, we found a negative correlation between the Describing facet and stress- and sleep-related variables. Instead, no significant correlation was observed between the Observing facet and any of the outcome variables. Previous studies have reported contrasting findings regarding the Describing and Observing facets of mindfulness. These inconsistencies may stem from differences in sample characteristics and the instrument used to assess the constructs under study, other than to intrinsic problems with the construct actually assessed by the scale (Redkin et al., 2018; Simione \u0026amp; Saldarini, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). To address this variability, future research should undertake a systematic review of studies employing the FFMQ, aiming to identify methodological and contextual factors that may have contributed to the divergent findings observed in the literature.\u003c/p\u003e\u003cp\u003eRegarding our second hypothesis, we found that sleep reactivity was a significant mediator in the relationship between three mindfulness facets and insomnia. Some studies have explored the mediating role of variables associated with emotional distress and stress reactivity (e.g., hyperarousal, negative affect, psychological stress) in the relationship between mindfulness and sleep quality (Simione et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Fong et al., 2020; Ding et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Talley, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, to our knowledge, no previous study has investigated the mediating role of sleep reactivity in the relationship between mindfulness facets and insomnia symptoms. Importantly, sleep reactivity, as a sleep-specific dimension of stress reactivity, is closely related to hyperarousal (Fernandez-Mendoza et al., 2010; Kalmbach et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In insomnia models, hyperarousal appears to be a central phenomenon in the development and maintenance of this sleep disturbance. In fact, individuals with insomnia exhibit heightened physiological, cortical, and cognitive/emotional arousal (Dressle \u0026amp; Riemann, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Riemann et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Specifically, in the cognitive/emotional domain, individuals with insomnia often exhibit difficulties coping with stressful situations and in regulating emotions. For instance, individuals with insomnia tend to perceive life events as more stressful (Morin et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) and experience greater difficulties in resolving emotional distress related to both past and novel emotional experiences (Wassing et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Importantly, these difficulties are not limited to individuals with chronic insomnia but are also observed in those predisposed to insomnia and with high sleep reactivity (Fernandez-Mendoza et al., 2010). Therefore, future studies should further investigate aspects of emotion regulation in healthy populations with varying levels of sleep reactivity, given its role as a risk factor for both acute and chronic insomnia (Jarrin et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Walker et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, preventive mindfulness-based interventions targeting improved coping strategies for stress and enhanced emotional regulation could potentially serve as protective measures against sleep difficulties in individuals with higher levels of this characteristic.\u003c/p\u003e\u003cp\u003eNot only did our study aim to assess the mediating role of sleep reactivity, but it also sought to investigate the individual contributions of mindfulness facets within this mediation model. In our study, the facets of Non-Judging and Non-Reacting were found to decrease sleep reactivity, which in turn led to a reduction in the severity of insomnia symptoms. The Monitoring and Acceptance Theory (MAT; Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) frames these two facets within the broader construct of acceptance. Rather than viewing acceptance as passive resignation to (negative) life events, the MAT conceptualises it as an attitude of openness and curiosity towards all life experiences that, in combination with attention monitoring, i.e., awareness, leads to a better mental state. This involves acknowledging them and allowing them to arise and pass without judgement or reactivity. As an emotion regulation strategy, acceptance involves approaching emotional experiences with openness, rather than avoiding them, actively trying to change them, or hyperfixating on them (Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This approach potentially explains the observed benefits of mindfulness training in altering affective responses, reducing stress reactivity, and improving stress-related health outcomes (Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Lindsay et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), beyond its interaction with awareness (Simione et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Simione \u0026amp; Saldarini, 2024). Research supports the idea that higher levels of acceptance are linked to better sleep outcomes (Black et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Fong \u0026amp; Ho, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Mirolli et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Tzioridou et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In addition, several authors have suggested over the years that cultivating acceptance through mindfulness practices\u0026mdash;both toward the mental and physical processes that precede sleep and toward beliefs and attitudes about sleep\u0026mdash;may promote the cognitive and physiological deactivation necessary for falling asleep (Lundh, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Ong et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Shallcross et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This acceptance-based approach may also facilitate a shift in perspective that interrupts the cycle of negative emotions and maladaptive behaviors that contribute to the maintenance of chronic insomnia (Ong et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Shallcross et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In these views, the way individuals approach stressors is critical because it regulates their physiological and psychological responses to stress. Adopting an acceptance-based attitude toward thoughts, emotions, and sensations related to sleep can reduce arousal and stress reactivity, thereby improving sleep quality.\u003c/p\u003e\u003cp\u003eWhile the path from Non-judging and Non-reacting through sleep reactivity led to a decrease in insomnia severity, we observed that the path from the FFMQ-SF Observing subscale was associated with increased insomnia severity through heightened sleep reactivity. This finding, despite anomalous, is in line with previous literature, which have shown a positive association between this subscale of the FFMQ and variables linked to psychological distress and emotional reactivity (Baer et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Interestingly, the association between the Observing facet of mindfulness and psychological symptoms is found in studies involving samples of non-meditators, while in samples of long-term meditators, it is not usually reported (Baer et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In our study, which used a convenience sample of the adult general population, even though nearly 30% of participants reported being involved in a meditation practice, the majority were not. Therefore, the characteristics of our sample may have influenced this particular finding.\u003c/p\u003e\u003cp\u003eSeveral authors have attempted to explain the odd behavior of this specific FFMQ subscale. One possible explanation could be the way participants interpret the items in the subscale, which may differ between non-meditators and meditators (Baer et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Furthermore, the Observing subscale includes items targeting mainly body awareness and awareness of external perceptions, while completely lacking items related to emotional awareness - a construct negatively related to psychological symptoms (Rudkin et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). As a result, the Observing facet might capture a form of maladaptive monitoring, rather than genuine mindful monitoring. In this regard, a recent review (Simione \u0026amp; Pieroni, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) suggested that the positive relationship between the FFMQ Observing and psychological symptoms may be influenced by a third variable, namely sensory-processing sensitivity (SPS; Aron \u0026amp; Aron, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1997\u003c/span\u003e), which could act as a confounder in this relationship. SPS is characterized by heightened awareness of environmental stimuli and increased reactivity to them (Aron \u0026amp; Aron, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Greven et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The authors of the review argue that, in dispositional studies involving non-meditators, the assessment of mindful awareness using the Observing subscale of the FFMQ may be confounded by SPS, as this trait reflects an inherent, involuntary attention to stimuli - unlike mindful awareness, which involves a deliberate and intentional focus on present-moment experiences (Simione \u0026amp; Pieroni, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Notably, a recent study found evidence linking SPS with sleep reactivity and insomnia (Pieroni et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). To address this potential confound, future research employing the FFMQ would benefit from incorporating a scale to assess SPS. This addition could help disentangle the extent to which the Observing facet of mindfulness overlaps with the construct of SPS.\u003c/p\u003e\u003cp\u003eFinally, another potential explanation for our finding stems from the MAT (Lindsay \u0026amp; Creswell, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). According to MAT, the capacity to monitor ongoing experiences\u0026mdash;whether naturally heightened or enhanced through training\u0026mdash;can increase awareness of both positive and negative affective information. For individuals who lack training in monitoring present-moment experiences with an accepting attitude or who have dispositionally low acceptance skills, this heightened awareness, particularly of unpleasant or negative experiences, may amplify stress reactivity. Such increased reactivity could, in turn, exacerbate psychological symptoms. Building on this reasoning, it is plausible that heightened awareness of present-moment experiences could amplify the perception of and attention to sleep-interfering stimuli, such as somatic sensations of arousal, ruminative thoughts, or environmental distractions. This increased focus on such stimuli may, in turn, heighten the susceptibility of the sleep system to respond reactively to these stressors, resulting in sleep disruptions. This perspective is supported by two recent studies that found that the nonreactivity facet act as a moderator in the relationship between the observing facet and sleep outcomes (Lau et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Xie et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These findings suggest that the presence of acceptance-related skills, such as nonreactivity, may play a critical role in mitigating the potentially negative impact of heightened awareness on sleep outcomes.\u003c/p\u003e\u003cp\u003eIn the present study, we primarily focused on investigating whether sleep reactivity serves as a mediator between mindfulness and insomnia and aimed to explore the individual contributions of the five mindfulness facets to this relationship. However, we did not specifically examine whether variations in acceptance-related facets, such as nonjudging and nonreactivity, might alter the relationship between the observing facet and sleep-related outcomes. Future studies should address this gap by systematically exploring how the interplay between the observing and acceptance facets influences sleep outcomes. Such research could help clarify the mechanisms through which mindfulness-based interventions impact sleep and identify specific components of mindfulness that may be most beneficial for individuals with heightened sleep reactivity or insomnia.\u003c/p\u003e\u003cp\u003eFinally, it is noteworthy that the Acting with Awareness facet did not play a role in our mediation model, despite correlational analyses suggesting its association with reductions in both sleep reactivity and insomnia severity. Moreover, a previous longitudinal study conducted with colorectal cancer survivors found that Acting with Awareness, alongside Non-Judging and Non-Reacting, significantly predicted better sleep quality indirectly through reductions in emotional distress (Fong et al., 2020). However, that study differs from ours in several key methodological aspects, including the research design, the population under investigation, and the type of self-report measures employed. Future research should aim to address these discrepancies by examining the role of Acting with Awareness in relation to stress and sleep outcomes across varied populations and study designs, offering greater clarity on its potential contribution to improving sleep health.\u003c/p\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eLIMITATIONS\u003c/h2\u003e\u003cp\u003eThe findings of the present study should be interpreted in light of several limitations. First, the cross-sectional design of the study precludes any definitive conclusions about the directionality or causality of the relationships observed between mindfulness facets, stress, and sleep-related variables. Longitudinal and experimental studies are needed to better understand these relationships over time. For instance, exploring whether mindfulness training, particularly among individuals at risk for insomnia, offers sustained protection for sleep health could yield valuable insights. Another significant limitation is the exclusive reliance on self-report measures, which may have introduced biases related to participants' perceptions and retrospective recall. Future research should incorporate objective assessments of sleep, such as actigraphy, polysomnography (PSG), or physiological measures of stress (e.g., heart rate variability), to provide a more robust and nuanced understanding of the relationships between mindfulness, stress, and sleep outcomes. The sampling method also poses challenges to the generalizability of the findings. The use of a convenience sample may not adequately represent broader populations. Moreover, the sample was predominantly composed of women (70%) and included a significant proportion of meditators (30%), which could have influenced the observed relationships between mindfulness and sleep. Future studies should aim for more diverse and representative samples, employing stratified or random sampling methods to improve generalizability and provide insights into specific subgroups, such as individuals with chronic insomnia. Additionally, while meditation practice was included as a variable in the study, its operationalization as cumulative lifetime hours of practice may have limited its explanatory power. This approach does not account for important contextual factors, such as the frequency or recency of practice. For example, a recent study (Tzioridou et al., 2023) demonstrated that while cumulative mindfulness practice was associated with nightmare frequency, it did not predict nightmare distress. Furthermore, the time elapsed since the last meditation session was found to correlate with sleep variables, with longer intervals associated with increased nightmare occurrence (Tzioridou et al., 2023). These findings highlight the need for more precise and comprehensive measures of meditation practice in future studies, including the timing, intensity, and type of meditation practice.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll the authors contributed to the design and implementation of the research, to the analysis of the results and to the writing of the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAron, E. N., \u0026amp; Aron, A. (1997). 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Trait mindfulness and sleep: Interactions between observing and nonreactivity in the association with sleep health. \u003cem\u003eHealth Psychology Open\u003c/em\u003e, 10(1). https://doi.org/10.1177/20551029221149282\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7829160/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7829160/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eObjectives: Previous research has established the beneficial effects of mindfulness practices on reducing insomnia, primarily through the alleviation of psychological stress. However, the specific role of sleep reactivity - a sleep-focused component of stress reactivity - has not been thoroughly explored. This study aims to investigate the mediating role of sleep reactivity in the relationship between dispositional mindfulness facets and insomnia symptoms.\u003c/p\u003e\n\u003cp\u003eMethods: A total of 359 participants completed an online survey assessing mindfulness facets (namely, Observing, Describing, Acting with awareness, Non-judging of inner experiences, Non-reactivity to inner experiences), sleep reactivity, and insomnia severity. Structural equation modeling was used to assess direct and indirect paths from the five mindfulness facets to the outcome variable (insomnia severity) via the mediator variable (sleep reactivity).\u003c/p\u003e\n\u003cp\u003eResults: The results indicate that while the Observing facet of mindfulness was associated with increased insomnia severity through heightened sleep reactivity, the Non-judging and Non-reactivity facets contributed to decreased insomnia symptoms by reducing sleep reactivity.\u003c/p\u003e\n\u003cp\u003eConclusions: These findings highlight the need for improved measurements to assess the monitoring aspect of mindfulness and highlight the protective role of dispositional mindfulness, particularly its acceptance-related component. Furthermore, they suggest that mindfulness training may serve as a preventive measure for individuals vulnerable to stress-induced insomnia.\u003c/p\u003e","manuscriptTitle":"Sleep reactivity as a mediator in the relationship between trait mindfulness and insomnia: a correlational study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-29 03:58:24","doi":"10.21203/rs.3.rs-7829160/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b001fbe9-836d-4d15-8fc8-f6ab068c718c","owner":[],"postedDate":"October 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-11-18T17:23:48+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-29 03:58:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7829160","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7829160","identity":"rs-7829160","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}