Effectiveness Of Mindfulness Interventions in Reducing Perceived Stress Among Nurses and Nursing Students: A Systematic Review and Meta-Analysis

Effectiveness Of Mindfulness Interventions in Reducing Perceived Stress Among Nurses and Nursing Students: A Systematic Review and Meta-Analysis | 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 Systematic Review Effectiveness Of Mindfulness Interventions in Reducing Perceived Stress Among Nurses and Nursing Students: A Systematic Review and Meta-Analysis Ekta Ram, Rakesh Balachandar, Soundarya Soundararajan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7328822/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 While mindfulness-based interventions (MBIs) have demonstrated effectiveness in reducing anxiety and depression, their impact on perceived stress, a key driver of burnout and reduced well-being among clinical nurses and nursing students remains underexplored. This study synthesizes evidence on the effects of MBIs in mitigating perceived stress within this high-stress professional group, focusing on intervention delivery, settings, and methodological variations. Methods A systematic search was conducted in PubMed and Embase, identifying studies evaluating the effects of mindfulness on perceived stress. Standardized mean differences (SMDs) were calculated using random-effects models. Thirty-six studies involving 2,201 participants were included. Separate meta-analyses were conducted for (1) one-sample pre-post designs and (2) intervention-control designs. Subgroup analyses examined variables including control type (active vs. non-active), intervention mode (instructor-led vs. self-directed), intervention setting (workplace vs. non-workplace). Sensitivity analyses were performed to assess the robustness of findings. Results Mindfulness interventions significantly reduced perceived stress, with medium effects in one-sample pre-post studies (SMD = -0.54 [-0.77, -0.31]) and small effects in intervention-control studies (SMD = -0.21 [-0.37, -0.05]). Subgroup analyses revealed stronger effects for instructor-led interventions, workplace settings, and non-active controls. Sensitivity analyses confirmed the stability of findings, with no single study disproportionately influencing the pooled effect sizes. Conclusions This meta-analysis reaffirms the efficacy of MBIs in reducing perceived stress among clinical nurses and nursing students. Instructor-led and workplace-based interventions emerged as particularly effective. These findings highlight the potential of tailored MBIs to enhance stress management strategies, support mental health, and build resilience in clinical and educational nursing settings. Preregistration This systematic review/meta-analysis was preregistered in PROSPERO (Ref no: CRD42024509223) Mindfulness-Based Interventions Perceived Stress Nurses Nursing Students Systematic Review Meta-Analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Perceived stress, defined as an individual’s subjective evaluation of life demands exceeding one’s coping ability, has profound effects on mental health, behavioral choices, and even biological aging (Cohen et al. 1983, Cristóbal-Narváez et al., 2020; Fruehwirth et al. 2023; Hrairi et al. 2021; Khaled et al. 2020; Mathur et al. 2016; Schutte & Malouff, 2016). Among healthcare professionals, nurses and nursing students are particularly vulnerable due to high emotional labor (Vo et al. 2022). Shift works, demanding roles, long working hours, leading to elevated perceived stress levels that correlate strongly with burnout, absenteeism, and diminished work performance (Dash et al., 2021; Hrairi et al. 2021; Sahoo et al. 2021; Shruthi et al. 2023; Singh et al. 2013). Importantly, elevated perceived stress is not only a precursor to psychological distress but also linked with accelerated biological aging, including shortened telomeres (Mathur et al. 2016), and adverse physical health outcomes such as fatty liver disease (Luo et al. 2024). Given these consequences, addressing perceived stress is a critical mental health priority in nursing. Reducing perceived stress is a vital goal for high-stress groups like nurses, with profound implications for long-term well-being. Sustained reductions in perceived stress are linked to better psychological and physical health in later life (Johnson et al., 2023). Moreover, higher perceived stress assessed by Perceived Stress Scale (PSS) strongly correlates with depression, with a one-unit increase in PSS raising the odds of depression by 1.4 times, as demonstrated in a study across 45 low- and middle-income countries (Cristóbal-Narváez et al., 2020). These findings underscore the global need to address perceived stress, given its significant impact on mental and physical health. Mindfulness-Based Interventions (MBIs), which aim to cultivate present-moment awareness and emotional regulation, have shown promise in reducing stress and improving well-being in healthcare populations (Armstrong & Tume, 2022; Ghawadra et al., 2019; Green & Kinchen 2021; La Torre et al., 2020; Ramachandran et al. 2023; Selič-Zupančič et al. 2023). MBIs are theoretically grounded in Kabat-Zinn’s Stress Reduction Theory, which posits that mindfulness facilitates adaptive responses to stressors by enhancing awareness, decentering from automatic reactions, and improving emotional self-regulation (Kabat-Zinn, 2009). Neurobiological evidence suggests that mindfulness practice reduces amygdala hyperactivity (associated with fear and stress), strengthens hippocampal connectivity (important for memory and stress buffering), and promotes cortical thickening in prefrontal regions related to self-regulation (Hölzel et al., 2011; Treves et al., 2024; Caetano et al., 2022; Tang et al. 2015). Despite the growing literature, most meta-analyses on MBIs have focused on general stress, burnout, or anxiety, and often aggregate diverse outcome measures across heterogeneous healthcare populations. However, perceived stress, as measured consistently through the Perceived Stress Scale (PSS) offers a theoretically coherent and psychometrically validated outcome that aligns directly with the goals of mindfulness (Cristóbal-Narváez et al., 2020; Schutte & Malouff, 2016). Moreover, perceived stress reflects internal appraisal rather than symptomatology, making it especially suitable for evaluating interventions like mindfulness, which aim to shift subjective interpretations of stressors. To date, few reviews have isolated the effect of MBIs on perceived stress among nurses and nursing students, despite the unique occupational demands and stressors faced by this group. Even fewer have examined how delivery mode (instructor-led vs. self-directed), intervention setting (workplace vs. non-workplace), and control group type (active vs. passive) influence intervention outcomes. One recent meta-analysis (Wexler & Schellinger, 2023) focused narrowly on Mindfulness-Based Stress Reduction (MBSR), yet broader mindfulness practices remain understudied despite their prevalence in nursing interventions. The primary objective of this review is to pool existing evidence to determine the magnitude of the effects of mindfulness interventions on perceived stress reduction among nurses. By synthesizing the available data, this review aims to evaluate the effectiveness of mindfulness as an intervention for managing stress in this high-stress professional group. The findings will provide insights into the potential of mindfulness practices to alleviate perceived stress and support well-being in nursing populations. By addressing these gaps, our study contributes a focused and theory-driven synthesis of the literature, offering practical insights for designing more effective and context-sensitive MBIs in clinical and educational nursing settings (Braun 2022). Method This Systematic Review and Meta-Analysis followed the PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) (Page, Moher, et al., 2021 ; Page, McKenzie, et al., 2021 ). The review protocol was registered in PROSPERO (CRD42024509223). Search Strategy and Selection Criteria The search incorporated Medical Subject Headings (MeSH) and relevant keywords, including “Mindfulness-based interventions,” “Perceived Stress,” “Perceived Stress Scale (PSS),” “Nurses,” and “Nursing Students.” We also reviewed references from the retrieved studies. The search covered publications up to February 2024 and included two electronic databases: PubMed and Embase. The full search strategy is tabulated in Supplementary Table 1. Additionally, to ensure comprehensiveness beyond indexed sources, we also performed backward citation tracking using Research Rabbit, a machine-learning assisted discovery tool. This step allowed us to identify additional relevant studies that may have been missed in the database search. The same is listed under the “identification of new studies via other methods” in the PRISMA flowchart (Fig. 1 ). We included controlled and one-sample pre-post study designs if they met the following criteria: (a) participants were nurses or nursing students (b) studies employed mindfulness-based interventions comprising at least one of the core components of the following practices: Attention regulation, emotional regulation and self-awareness, (c) outcome was assessed using the Perceived Stress Scale (PSS), (d) studies published in English. (e). We included studies that reported perceived stress outcomes using the Perceived Stress Scale (PSS) only. The rationale for this restriction was twofold: (1) to maintain conceptual clarity by focusing on perceived stress as a psychological construct distinct from broader definitions of stress; and (2) to reduce outcome heterogeneity across studies. The PSS is the most widely validated tool for assessing perceived stress, enhancing the validity and interpretability of the pooled meta-analytic estimates (Yılmaz Koğar & Koğar 2024 ). Studies were excluded if they were published in languages other than English, if they were case reports, protocols, reviews, editorials, or other study designs not specified above, studies involving mixed populations (e.g., healthcare professionals) if they have not explicitly stated the outcomes for nurses or using outcome measures other than the Perceived Stress Scale (PSS) were excluded. Data Selection, Extraction and Coding The screening process was managed using the Rayyan application (Ouzzani et al., 2016 ) and was conducted independently by two authors (ER and SS) in two phases. First, the title and abstract screening identified eligible studies. Then, a full-text screening confirmed their inclusion. Results from both reviewers were compared at each stage, and any discrepancies were resolved through consensus with a third reviewer (RB). Data Extraction Two reviewers (S.S and E.R) independently extracted data, recording all relevant information in an Excel sheet, including, study characteristics (year of publication, country, study design), population characteristics (age, sample size, percentage of female participants, professional details), intervention characteristics (duration, mode of delivery, type of intervention, instructor-led components, informal practices), outcome characteristics (pre-post and follow-up means, standard deviations of perceived stress scores for control and intervention groups, perceived stress scale results). Any discrepancies during data extraction were discussed and resolved to ensure accuracy. Defining Controls Control conditions that involve structured, purposeful activities designed to engage participants in a manner similar to experimental intervention, without including the specific active component being tested (e.g., mindfulness). These activities require ongoing interaction, structured participation, or regular engagement over time. Examples include reflection seminars, listening to relaxing music, or structured multi-session discussions. Passive controls, on the other hand, include one-time activities or interventions without sustained engagement, such as single lectures or pamphlet distribution. These are not considered active controls due to their lack of comparable intensity or interaction. Study Classification for Subgroup Analyses Studies were classified according to several methodological and contextual features: Study Design: Studies were coded as RCTs if they explicitly reported random assignment of participants to study arms. Studies without randomization but with a comparator were categorized as non-RCT controlled trials Intervention Delivery: MBIs were categorized as instructor-led if sessions were delivered live by a facilitator, whether in person or via synchronous online platforms (e.g., Zoom). Interventions were classified as self-guided if participants accessed pre-recorded materials, mobile apps, or printed manuals without live facilitation. Intervention delivery modes were categorized as face-to-face (in-person), online (synchronous or asynchronous), or hybrid (combining both formats). Face-to-face referred strictly to in-person interactions. Intervention Setting: Interventions were coded as workplace-based if delivered within or closely tied to the participants' clinical job setting. Control Type: Active controls included any condition involving structured activities (e.g., relaxation, music therapy, stress education), while passive controls included waitlists, usual care, or no intervention. Population Type: Studies were additionally stratified based on participant type—nursing students and clinical nurses—to evaluate potential differences in intervention effectiveness across training stages and stressor contexts. Classification was made based on explicit mention in the study population description. Mixed populations were excluded from this subgroup analysis unless results were reported separately for each group. Classifications were made independently by two reviewers (SS and ER), with discrepancies resolved through consensus. Study Quality Assessment The risk of bias was evaluated by two independent reviewers using the Cochrane Risk of Bias Assessment Tool for Non-Randomized Controlled Trials (ROBINS-I) (Sterne et al., 2016 ). Discrepancies between the reviewers were resolved through discussion. Each study was assessed across seven methodological domains, confounding bias, selection bias, classification of intervention bias, bias due to deviations from intended interventions, bias due to missing outcome data, bias in the measurement of outcomes and selection of reported results. Each domain was rated as low, moderate, serious, critical, or no information, and the overall risk of bias was summarized. The criteria for overall judgments were: Low judgment in all domains: overall low risk, moderate or low judgments across all domains: moderate risk, a serious judgment in one domain without critical judgment: serious risk, critical judgment in at least one domain: critical risk. Statistical Analysis Meta-Analysis of Study Designs Meta-analysis was conducted using the metafor package in R. Standardized mean differences (SMDs) with 95% confidence intervals were calculated for both controlled and one-sample pre-post study designs. A random-effects model was used to evaluate the effectiveness of mindfulness-based interventions (MBIs) in reducing perceived stress among nurses. We conducted two separate meta-analyses. The first included pre-post data from all available intervention groups, including both uncontrolled studies and the intervention arms of controlled trials. This allowed for a pooled estimate of within-group change following MBIs. SMDs for these studies were directly computed using the rma() function in metafor based on reported means, SDs, and sample sizes. The effect size was calculated as the difference between post- and pre-intervention means, divided by the pooled standard deviation. The second analysis for controlled studies, we approximated difference-in-differences effect sizes using a simulation-based approach. Since participant-level data were not available, we generated synthetic individual-level scores based on reported means, standard deviations, and sample sizes for each group. For each study, we simulated pre- and post-intervention data for both the intervention and control arms using the rnorm() function in R, with fixed seeds for reproducibility. We then computed the mean and standard deviation of the within-group change scores and derived the between-group contrast. This approach allowed us to estimate the incremental effect of MBIs relative to a comparator. All simulations and meta-analyses files are made available in the associated GitHub repository. SMD values were classified as small (0.2 to 0.49), medium (0.5 to 0.79), and large (≥ 0.8). Heterogeneity was assessed using the I² test, with values of 25%, 50%, and 75% indicating low, intermediate, and high heterogeneity, respectively. Publication bias was assessed using a funnel plot and Egger’s test. If Egger’s test was significant, we followed it with the Duval & Tweedie’s trim-and-fill procedure (Schwarzer et al., 2015 ) to detect the actual effect size considering if the missing small effect size studies were published. Several subgroup analyses were conducted to explore the effect size of various factors, such as instructor-led interventions, active vs. non-active control groups, RCT vs. non-RCT studies, and workplace vs. non-workplace interventions. Additionally, a sensitivity analysis was conducted after removing one outlier study to assess its impact on overall outcomes. Results Study selection Our search yielded 2024 results, which were uploaded to Rayyan for downstream processing. After removing 474 duplicates, 1550 unique articles remained. These were screened based on title and abstract, leading to the exclusion of 1299 records due to irrelevance, leaving 251 articles for further consideration. During the full-text review, 62 articles were excluded for not meeting the inclusion criteria, resulting in 34 eligible studies. Additionally, 2 studies were included through citation searching, making a total of 36 studies. The stages of screening and the corresponding numbers of results are depicted in the PRISMA flowchart below (Fig. 1 ). Study characteristics Table 1 summarizes the characteristics of the studies included in the systematic review. A total of 36 studies were eligible and included for the synthesis of results, involving 2,201 participants. The studies were divided into two categories: one-sample pre-post studies (n = 18) and control-intervention pre-post studies (n = 18). Of the 18 control-intervention pre-post studies, 15 were randomized controlled trials (RCTs), and five of these used active control groups. For meta-analysis, 5 studies were excluded from the one-sample pre-post intervention designs and 2 from control-intervention pre-post studies as either the central tendencies or the dispersion values were not reported. ===Insert table 1 here== The interventions primarily focused on Mindfulness-Based Stress Reduction (MBSR) in 36% (n = 13) of the studies (Anderson, 2021 ; Bazarko et al., 2013 ; Cepeda-Lopez et al., 2023 ; Conelius et al., 2021; Janzarik et al., 2022 ; Kulka et al., 2018 ; Lin et al., 2019 ; Mahon et al., 2017 ; McNulty, 2021 ; Pan et al., 2019 ; Santos et al., 2016; Spadaro & Hunker, 2016 ; Wright et al., 2018), with follow-up periods ranging from 1 to 36 weeks. All follow-ups were at least 4 weeks, except for one study (Fong et al., 2022 ) where mindful coloring was the intervention, and the follow-up was conducted after 1 week. About 33% of the studies had 8 weeks study duration and nine studies had more than 8 weeks of intervention (Cepeda-Lopez et al., 2023 ; Chesak et al., 2015 ; Conelius et al., 2021; Coster et al., 2020 ; Drew et al., 2016 ; Dyess et al., 2018 ; Fadzil et al., 2021 ; McNulty, 2021 ; Plummer et al., 2018 ). The mean age of participants ranged from 18 to 65 years, although three studies did not report participant ages (Ficarra, 2023; Frögéli, et al., 2016 ; Kulka et al., 2018 ), and one study did not provide an upper age limit (Sawyer et al. 2023 ). Around 30% (n = 11) of the studies were conducted with nursing students (Alhawatmeh et al., 2022 ; Burger et al., 2017; Burner & Spadaro 2023 ; Conelius et al., 2021; Coster et al., 2020 ; Drew et al., 2016 ; Frögéli, Djordjevic, et al., 2016 ; Öztürk, 2023 ; Plummer et al., 2018 ; Ratanasiripong et al., 2015 ; Spadaro & Hunker, 2016 ). The majority (41%, n = 15) of interventions were face-to-face (in-person) interventions, were delivered online (synchronous or asynchronous) in 12 studies 8 followed a combined or hybrid modality. Around 58% (n = 21) were delivered at the workplace. Around 50% (n = 19) of studies were instructor-led. Regarding stress measurement, 52% (n = 19) of the studies used the PSS-10 scale, one study used the PSS-4 (Pratt et al., 2023 ), and the rest used the PSS-14 version of the Perceived Stress Scale. Most of the studies included predominantly female participants. Except for one study, which had a female population of 52–66% (Alhawatmeh et al., 2022 ), over 80% of the participants in all other studies were females. A vast majority of 67% (n = 25) of the studies were done in the USA. There were only two studies (Fadzil et al., 2021 ; Fong et al., 2022 ) from the Asian continent. Two studies were conducted in the UK (Anderson, 2021 ; Coster et al., 2020 ), one each from Mexico (Cepeda-Lopez et al., 2023 ), Canada (Silva Gherardi-Donato et al., 2023 ), Brazil (Dos Santos et al. 2016 ), Sweden (Frögéli, Djordjevic, et al., 2016 ), Germany (Janzarik et al., 2022 ), Jordan (Alhawatmeh et al., 2022 ) and Ireland (Mahon et al., 2017 ). The distribution of mindfulness intervention components (attention regulation, emotional regulation, and self-awareness) across the included studies is depicted in Supplementary Fig. 1. The majority of the studies incorporated components targeting attention regulation, with this element being present in most interventions. Four studies focused exclusively on emotional regulation (Bluth et al., 2021 ; Frögéli, Djordjevic, et al., 2016 ; Janzarik et al., 2022 ; Sawyer et al. 2023 ), while five studies included only attention regulation as a component (Burger et al., 2017; Drew et al., 2016 ; Dyess et al., 2018 ; Fong et al., 2022 ; Graham et al., 2022 ). Notably, no studies were identified that targeted only self-awareness without incorporating other components. Risk of bias within studies The risk of bias (RoB) assessment across the included studies was evaluated using the ROBINS-I tool, with judgments made for seven key bias domains (Fig. 2 , 3 ). Traffic-light plot showing domain-wise risk of bias assessments across all included studies using the ROBINS-I tool. Judgements are color-coded: low (yellow), moderate (orange), serious (dark orange), and critical (red). Domains assessed include confounding, participant selection, intervention classification, deviations from intended interventions, missing data, outcome measurement, and selective reporting. Overall risk of bias per study is shown in the final column. Overall, the studies demonstrated varying levels of bias across domains, with confounding (D1) being a particularly significant concern. All the studies were rated as having serious risk of bias in this domain, primarily due to the lack of control for potential confounding factors such as workplace environment including workplace conflict or violence, shift duty, duty hours, which could have influenced the observed outcomes. The selection of participants (D2) and classification of interventions (D3) were generally well-controlled, with most studies rated as having low or moderate risk of bias in these domains. However, three studies exhibited serious risk due to unclear participant selection criteria. The risk of bias due to deviations from intended interventions (D4) was also moderate in most cases, suggesting reasonable fidelity in intervention delivery. These included that the study participants either did not adhere to the assigned intervention regimen or failed to report an appropriate analysis method to estimate the initiation and adherence to the interventions. Seven studies showed serious and 2 showed critical risk for missing data (D5). For the measurement of outcomes (D6) majority were carrying serious risk of bias, thus incomplete outcome data and inconsistent measurement techniques being notable issues. This could potentially introduce bias in the interpretation of the intervention effects. Furthermore, a few (n = 3) exhibited moderate risk in the selection of reported results (D7), indicating possible selective reporting, which could further impact the overall reliability of findings. The aggregate results of the RoB assessment (Fig. 3 ) indicate that while certain methodological aspects, such as participant selection and intervention classification, were well-managed, the high risk of bias due to confounding, missing data, and measurement outcomes could limit the validity of the results. These methodological concerns need to be carefully considered when interpreting the pooled estimates in the meta-analysis. Meta-analysis The effect size obtained for perceived stress, the primary outcome, was statistically significant for the mindfulness intervention group, reaching a moderate magnitude based on Cohen’s d in the one-sample pre-post studies (0.54 [0.32, 0.76]), suggesting that mindfulness interventions had a meaningful impact on stress reduction in these studies. In the control intervention design, the reduction in perceived stress was also statistically significant but demonstrated a small effect size (0.21 [0.05, 0.37]), reflecting modest benefits of mindfulness interventions in controlled comparisons. Figure 4a, b displays two forest plots: one for one-sample pre-post studies and one for control-intervention pre-post studies. Heterogeneity was high in the one-sample pre-post studies (87.4%) and moderate in the control-intervention pre-post studies (49.5%). Publication bias Intervention only studies carried a significant asymmetry (z = -3.6260, p = 0.0003) suggesting a potential publication bias in the included studies. This is further corroborated in the funnel plot depicted in Fig. 5a. The plot appears asymmetrical, with one particular study lying on one side of the mean effect, in the negative effect region. Duval & Tweedie’s trim-and-fill procedure did not find any missing studies on the right side of the funnel plot, with a standard error (SE) of 3.1181, indicating that the observed asymmetry might not be due to a lack of studies. This trim-and-fill analysis implies that the observed effect size remains robust even after correcting for potential publication bias, with substantial heterogeneity across studies. Further publication bias for control-intervention pre-post studies was assessed using Egger’s test, yielding a non-significant result (z = -0.6662, p = 0.505). This indicates minimal evidence of publication bias, further supported by the symmetry observed in the funnel plot for these studies. Subgroup analysis Workplace and non-workplace interventions The subgroup analysis (Supplementary Fig. 2a) compared the effectiveness of mindfulness interventions in workplace and non-workplace settings. In the workplace subgroup, the effect was moderate (SMD = -0.61 [95% CI: -0.98 to -0.25]) and more compared to the non-workplace subgroup (SMD = -0.43 [95% CI: -0.65 to -0.21]) that showed a small-to-moderate effect. However, the test for subgroup differences was not statistically significant (Q M = 0.34, p = 0.56), suggesting similar intervention effectiveness across settings. High heterogeneity was observed in both subgroups (I² = 91.5% for workplace; I² = 65.3% for non-workplace), warranting further exploration of variability. Among control-intervention pre-post design (Supplementary Fig. 2b), in the workplace subgroup, the SMD was − 0.25 [95% CI: -0.46 to -0.04], showing a statistically significant reduction in stress with a small effect size. Moderate heterogeneity was observed (I² = 57.6%, p = 0.016). In the non-workplace subgroup, the SMD was much lower at -0.15 [95% CI: -0.40 to 0.11], with no statistically significant effect. Heterogeneity was lower (I² = 38.4%, p = 0.132). The test for subgroup differences was not statistically significant (Q M = 0.33, p = 0.57), suggesting comparable effects of mindfulness interventions in the workplace and non-workplace settings for controlled designs. Instructor-Led vs. Non-Instructor-Led Mindfulness Interventions Among one-sample pre-post design studies (Supplemental Fig. 3a), there was a significant reduction in perceived stress in the instructor-led subgroup, with substantial heterogeneity (I² = 83.3%, p < 0.001). Non-instructor led group showed a large but imprecise effect − 0.86 [95% CI: -2.02 to 0.31] with wider confidence interval, suggesting possible variability or small study effects. The heterogeneity in this subgroup was very high (I² = 96.0%, p < 0.001). The test for subgroup differences was not statistically significant (Q M = 0.64, p = 0.42), indicating no clear evidence that instructor-led interventions are more effective than non-instructor-led ones. However, the heterogeneity within subgroups suggests variability in intervention implementation and outcomes. Subgroup Analysis for Instructor-Led vs. Non-Instructor-Led Mindfulness Interventions in Control-Intervention Design pre post designs (Supplementary Fig. 3b) revealed a smaller and non-significant reduction in perceived stress levels among the non-instructor led group. Heterogeneity was low (I² = 0%, p = 0.371), indicating consistency across studies. Instructor-led interventions showed a small and statistically significant reduction in stress, with moderate heterogeneity (I² = 55.8%, p = 0.008). The test for subgroup differences was not statistically significant (Q M = 0.16, p = 0.69), suggesting no strong evidence of differential effects between instructor-led and non-instructor-led interventions. Clinical Nurses vs. Nursing Students To explore differential effects based on population type, we conducted a subgroup analysis comparing clinical nurses and nursing students (Supplementary Figs. 4a, b). In the one-sample pre-post studies, MBIs showed a significant reduction in perceived stress for both groups. The pooled effect size was − 0.54 [–0.84, − 0.23] for nurses and − 0.55 [–0.75, − 0.36] for nursing students, both reflecting moderate effects. In controlled intervention studies, however, the effect was smaller and significant for nurses (–0.15 [–0.30, − 0.00]) but non-significant for students (–0.30 [–0.62, 0.03]), suggesting potential variability in how MBIs perform in more rigorously controlled settings across populations. Test for subgroup differences was non-significant in both designs (QM = 0.05, p = 0.83 for intervention-only; QM = 0.68, p = 0.41 for controlled), indicating no statistically reliable difference, though the patterns point to contextually nuanced effectiveness. Subgroup Analysis for RCT vs. Non-RCT Studies Supplementary Fig. 5 illustrates non-RCT studies demonstrated a small-to-moderate effect with statistically significant reduction in stress with low heterogeneity (I² = 8.4%, p = 0.358), suggesting consistent findings across studies. RCTs showed a smaller and non-significant reduction in stress. Moderate heterogeneity was observed (I² = 51.6%, p = 0.014). The test for subgroup differences was not statistically significant (QM = 1.30, p = 0.25), suggesting no strong evidence that the effect size varies significantly by study design. However, non-RCTs demonstrated a slightly larger and more consistent effect compared to RCTs. Subgroup Analysis for Active vs. No Active Controls Supplementary Fig. 6 depicts the effects of mindfulness interventions between studies with active control groups and those with no active controls in control-intervention designs. Studies with no active controls demonstrated a small but significant reduction in stress with no heterogeneity (I² = 0.0%, p = 0.302), indicating consistent results across studies. Studies with active controls had a very small and non-significant effect with high variability (I² = 85.1%, p < 0.001). The test for subgroup differences was not statistically significant (QM = 0.27, p = 0.60), suggesting no strong evidence that the effect size varies significantly between studies with active versus no active controls. However, interventions without active controls yielded more consistent and statistically significant results compared to those with active controls. Sensitivity analysis The leave-one-out sensitivity analysis for intervention-only designs (Supplementary Fig. 6a) revealed consistent results across studies, as the overall standardized mean difference (SMD) remained relatively stable upon the removal of individual studies. The effect sizes ranged between approximately − 0.40 and − 0.60, with no single study significantly altering the pooled effect size. The heterogeneity (I²) was similarly robust across iterations, fluctuating minimally from the overall I² of 87.8%, confirming that no single study disproportionately influenced the overall findings. The slight variability observed when certain studies (e.g., Mahon_2017 and Dyess_2018) were removed suggests that these studies may have contributed slightly to the heterogeneity but not to the magnitude of the overall effect. In addition, we conducted a formal sensitivity analysis excluding both Dyess_2018 and Mahon_2017, two studies with notably large effect sizes. The pooled standardized mean difference was attenuated from − 0.54 (95% CI: − 0.76 to − 0.32; I² = 87.4%) in the full model to − 0.41 (95% CI: − 0.58 to − 0.25; I² = 76.3%) when these studies were removed. The effect remained statistically significant and directionally consistent, supporting the robustness of our findings while acknowledging the influence of high-effect studies on magnitude (Supplementary Fig. 6b). Sensitivity analysis comparing the full pooled estimate with results excluding 2 studies (Dyess 2018 and Mahon 2016) is listed in Supplementary Table 2. The leave-one-out sensitivity analysis for controlled-intervention designs (Supplementary Fig. 6c) demonstrated consistent results across studies, with the overall standardized mean difference (SMD) remaining stable when individual studies were removed. The recalculated effect sizes ranged between approximately − 0.15 and − 0.35, with no single study significantly altering the pooled effect size. The heterogeneity (I²) fluctuated only slightly from the overall I² of 49.5%, confirming the robustness of the meta-analytic findings. Minor variability was noted when specific studies, such as Alhawatmeh et al (Alhawatmeh et al., 2022 ) and Chesak et al., 2015 , were excluded, indicating a marginal contribution to the heterogeneity without substantial impact on the overall effect. Discussion This systematic review and meta-analysis evaluated the effectiveness of mindfulness-based interventions (MBIs) in reducing perceived stress among nursing professionals. Synthesizing data from 36 studies with a combined sample of 2,201 participants, we found that MBIs had statistically significant reductions in perceived stress, with pooled effects in the small to medium range. Specifically, the effect size in one-sample pre-post studies was moderate (SMD = 0.54), and in control-intervention designs, it was small (SMD = 0.21), reflecting modest but meaningful improvements in stress reduction. These findings support the potential utility of MBIs for stress management in both nursing students and clinical nurses. Our observed effect sizes, a moderate effect (SMD = 0.54) in one-sample pre-post studies and a small effect (SMD = 0.21) in controlled designs align with, and in some cases exceed those reported in previous meta-analyses evaluating MBIs for perceived stress across different populations. For instance, Bartlett et al. ( 2019 ) reported a comparable effect size of Hedges’ g = 0.56 in general workplace settings, while Gál et al. ( 2021 ) found a moderate effect of g = 0.46 among general adult users of mindfulness mobile apps. Michaelsen et al. ( 2023 ) observed a higher effect (SMD = 0.72) across employee populations including healthcare workers, though nurses were not separately analyzed. Meanwhile, a review by Xu et al. ( 2020 ) focusing on emergency department personnel, including nurses, yielded a non-significant pooled effect (SMD = − 0.32), highlighting possible variability by occupational role or setting. Among student populations, Zuo et al. ( 2023 ) reported a smaller but significant pooled effect (SMD = − 0.39), consistent with our subgroup findings for nursing students (SMD = − 0.36). Taken together, our findings are consistent with a growing body of evidence supporting MBIs for stress reduction, while also underscoring the importance of contextual and methodological factors such as population type, setting, and intervention delivery mode. The effects were largely driven by intervention-only pre-post studies, though our analysis showed that these effects remained directionally consistent even when restricted to controlled trials using difference-in-differences estimators. A leave-one-out sensitivity analysis showed that the findings were robust to exclusion of any single study, and a targeted sensitivity analysis excluding outlier studies (Dyess_2018 and Mahon_2016) showed only a moderate reduction in effect size. This suggests that while some studies contributed disproportionately to effect magnitude, the direction and statistical significance of pooled results were preserved. Our findings extend previous meta-analyses by focusing specifically on perceived stress, rather than general stress or burnout, and by using a consistent and validated measure (the Perceived Stress Scale, PSS). This conceptual precision enhances interpretability. While many prior reviews have combined various stress constructs and outcome tools, our analysis isolates perceived stress as a psychological construct particularly aligned with the mechanisms of mindfulness, such as cognitive reappraisal and attention regulation and present-moment awareness. A notable finding is that no study focused solely on self-awareness as a mindfulness component, with most interventions emphasizing attention or emotional regulation. This points to a meaningful gap in literature and a future opportunity for developing targeted self-awareness interventions, particularly given its theoretical centrality to mindfulness practice. The subgroup analyses offer valuable insights into implementation. The study highlights potential differences in intervention effects between clinical nurses and nursing students. In one-sample pre-post designs, both groups benefited similarly, with moderate effect sizes. However, in controlled trials, the effect was weaker and non-significant for students, suggesting that contextual or developmental differences, such as academic vs. workplace stressors—may influence how MBIs are perceived or engaged with. This also raises the possibility that clinical nurses may respond more strongly to workplace-integrated interventions, while students may require pedagogical tailoring or different delivery structures. These insights underscore the importance of population-specific adaptation when designing mindfulness programs for nursing education versus professional practice. Stronger effects were observed in workplace-based interventions, suggesting that MBIs delivered in clinical settings may more directly address occupational stressors and benefit from environmental reinforcement. Similarly, instructor-led interventions showed greater effectiveness than self-guided formats. The presence of a facilitator may enhance therapeutic alliance, accountability, and engagement—key ingredients in mindfulness-based approaches. While our analysis did not examine facilitator background in detail, future research should explore whether facilitators with clinical or institutional familiarity (e.g., nurse educators or in-house staff vs. external mindfulness trainers) yield better outcomes, particularly through increased relevance and cultural alignment. The observed attenuation of effects in RCTs compared to. non-RCTs highlight the influence of study design, an expected but important methodological consideration. Effects were also smaller in studies with active controls (e.g., music therapy, stress education), suggesting that some components of MBIs (e.g., structured relaxation or emotional regulation) may overlap with those of other psychosocial interventions. This underscores the need for precise mechanism testing and dismantling studies. Taken together, these results emphasize the need for contextually tailored, well-facilitated MBIs, ideally delivered in the workplace, instructor-led, and evaluated through methodologically rigorous designs. Our study contributes to the growing literature on mindfulness as a scalable, flexible stress-reduction tool for nursing populations, while also clarifying the conditions and subgroups in which it is likely to be most effective. Limitations and Future Research This review has a few methodological and conceptual limitations. First, we restricted inclusion to studies using the Perceived Stress Scale (PSS), a validated instrument aligned with mindfulness mechanisms such as cognitive reappraisal and attention regulation. While this enhanced conceptual coherence, it may have excluded relevant studies using alternative stress measures. Similarly, most included studies were non-randomized and underpowered, underscoring the need for larger, well-designed RCTs. Our search was limited to PubMed and Embase due to project constraints, though we mitigated this by performing backward citation tracking. Finally, most studies relied on self-report outcomes, which could be complemented by physiological or behavioral markers to improve validity. In terms of intervention variability, studies differ widely in MBI duration, content, and delivery, limiting comparability. Fidelity reporting was often missing, and only a few studies examined sustained effects beyond immediate post-intervention. The predominance of female participants reflects the gender distribution in nursing but limits generalizability. Instructor backgrounds and modes of delivery were inconsistently reported, leaving open questions about the role of facilitator expertise and participant engagement. Future research should address these gaps by (1) investigating whether interventions led by internal facilitators (e.g., nurse educators or healthcare providers familiar with occupational stressors) are more effective than those delivered by external mindfulness experts, (2) identifying which specific MBI components (e.g., attention regulation, emotional regulation, self-awareness) most contribute to stress reduction, and (3) examining how institutional and contextual factors, such as workplace culture, peer participation, and leadership support influence engagement and outcomes. Embedding MBIs into structured workplace wellness programs may enhance adherence, contextual relevance, and scalability. Additionally, long-term follow-ups, standardized intervention protocols, and greater inclusion of male and gender-diverse samples will be essential to strengthen the global applicability and methodological rigor of MBI research in nursing populations. Ethical Clearance The manuscript does not contain clinical studies or patient data and is a systematic review and meta-analysis with no primary data collection; hence, ethical clearance was not applicable. Declarations Ethical Clearance The manuscript does not contain clinical studies or patient data and is a systematic review and meta-analysis with no primary data collection; hence, ethical clearance was not applicable. Conflict of Interest We declare that we have no conflicts of interest. Funding Information This study was conducted without funding. Author Contribution The idea for this systematic review and meta-analysis was conceived by Dr. Ekta Ram and Dr. Soundarya Soundararajan; Dr. Ekta Ram prepared the study protocol, which was reviewed and approved by Dr. Soundarya Soundararajan and Dr. Rakesh Balachandar and subsequently registered in PROSPERO. The literature search and data extraction were performed by Dr. Ekta Ram and Dr. Soundarya Soundararajan. The initial analysis was conducted by Dr. Soundarya Soundararajan, with the interpretation of results collaboratively performed by Dr. Ekta Ram and Dr. Soundarya Soundararajan, with support from Dr. Rakesh Balachandar. Dr. Soundarya Soundararajan supervised the study. Dr. Ekta Ram and Dr. Soundarya Soundararajan drafted the manuscript, and all authors reviewed and revised it. All authors read and approved the final manuscript. Acknowledgement The authors thank the researchers and authors who generously provided full-text articles and additional materials upon request, which greatly supported the completion of this review. References Alhawatmeh, H. N., Rababa, M., Alfaqih, M., Albataineh, R., Hweidi, I., & Abu Awwad, A. (2022). The benefits of mindfulness meditation on trait mindfulness, perceived stress, cortisol, and c-reactive protein in nursing students: A randomized controlled trial. 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Worldviews on Evidence-Based Nursing, 14(6), 507–513. https://doi.org/10.1111/wvn.12250 Tang, Y.-Y., Hölzel, B. K., & Posner, M. I. (2015). The neuroscience of mindfulness meditation. Nature Reviews Neuroscience, 16(4), 213–225. https://doi.org/10.1038/nrn3916 Treves, I. N., Pichappan, K., Hammoud, J., Bauer, C. C. C., Ehmann, S., Sacchet, M. D., & Gabrieli, J. D. E. (2024). The mindful brain: A systematic review of the neural correlates of trait mindfulness. Journal of Cognitive Neuroscience, 1–38. https://doi.org/10.1162/jocn_a_02230 Vo, T. N., Chiu, H.-Y., Chuang, Y.-H., & Huang, H.-C. (2022). Prevalence of stress and anxiety among nursing students: A systematic review and meta-analysis. Nurse Educator. https://doi.org/10.1097/NNE.0000000000001343 Wexler, T. M., & Schellinger, J. (2023). Mindfulness-based stress reduction for nurses: An integrative review. Journal of Holistic Nursing, 41(1), 40–59. https://doi.org/10.1177/08980101221079472 Wright, E. M. (2018). Evaluation of a web-based holistic stress reduction pilot program among nurse-midwives. Journal of Holistic Nursing, 36(2), 159–169. https://doi.org/10.1177/0898010117704325 Xu, H. (Grace), Kynoch, K., Tuckett, A., & Eley, R. (2020). Effectiveness of interventions to reduce emergency department staff occupational stress and/or burnout: A systematic review. JBI Evidence Synthesis, 18(6), 1156–1188. https://doi.org/10.11124/JBISRIR-D-19-00252 Yilmaz Kogar, E., & Kogar, H. (2024). A systematic review and meta-analytic confirmatory factor analysis of the perceived stress scale (PSS-10 and PSS-14). Stress and Health, 40(1), e3285. https://doi.org/10.1002/smi.3285 Zuo, X., Tang, Y., Chen, Y., & Zhou, Z. (2023). The efficacy of mindfulness-based interventions on mental health among university students: A systematic review and meta-analysis. Frontiers in Public Health, 11, 1259250. https://doi.org/10.3389/fpubh.2023.1259250 Table 1 Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.docx 20250708supplementaryTables.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7328822","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":509486759,"identity":"36e4d717-80b7-4a34-b303-ee999c957946","order_by":0,"name":"Ekta Ram","email":"","orcid":"","institution":"National Institute of Occupational Health","correspondingAuthor":false,"prefix":"","firstName":"Ekta","middleName":"","lastName":"Ram","suffix":""},{"id":509486760,"identity":"2f6a8e3c-4c7e-4ca9-8b04-f751939dce87","order_by":1,"name":"Rakesh Balachandar","email":"","orcid":"","institution":"National Institute of Occupational Health","correspondingAuthor":false,"prefix":"","firstName":"Rakesh","middleName":"","lastName":"Balachandar","suffix":""},{"id":509486761,"identity":"120cc963-53b6-4c3a-b61a-0257a05b0939","order_by":2,"name":"Soundarya Soundararajan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYLACHhDB3pD4AMTmI14Lz4HHBiCKjXgtEonPJEA0QS3y7T1mD97U3Evsb0hOq/yaYyfDxsD88NENPFoMzpwxN5xzrDhxxoFjabdltyUDHcZmbJyDT4tEjpk0D1tCYsPBnrTbktuYgVp42KTxaZGfAdLyLyFx/mH+b8WS2+oJa2G4AdTC25aQuOEYQxrjx22HCWsxOHOsTHJuX4LxxjMMydKM247zsDET8It8e/M2iTffEmTn3X+Q+PHntmp7fvbmh4/xOgwKHBuABDM4gpiJUA4C9iCC8QeRqkfBKBgFo2BkAQBRw0kAnsL2agAAAABJRU5ErkJggg==","orcid":"","institution":"National Institute of Occupational Health","correspondingAuthor":true,"prefix":"","firstName":"Soundarya","middleName":"","lastName":"Soundararajan","suffix":""}],"badges":[],"createdAt":"2025-08-08 15:53:19","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7328822/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7328822/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90891487,"identity":"8b790a0d-a513-4c85-a4e8-3e7487fec79f","added_by":"auto","created_at":"2025-09-09 11:11:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":121598,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePRISMA flowchart\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThis PRISMA flowchart summarizes the study selection process for the systematic review and meta-analysis. Some studies were excluded as they did not report stress outcomes using the PSS, which was a pre-specified inclusion criterion to reduce outcome measure heterogeneity.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7328822/v1/7d7a720c855fa937376b1bf9.png"},{"id":90891489,"identity":"d045720f-dcc8-4a73-8002-3c63287d62d1","added_by":"auto","created_at":"2025-09-09 11:11:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1019756,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRisk of Bias Assessment Across Included Studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTraffic-light plot showing domain-wise risk of bias assessments across all included studies using the ROBINS-I tool. Judgements are color-coded: low (yellow), moderate (orange), serious (dark orange), and critical (red). Domains assessed include confounding, participant selection, intervention classification, deviations from intended interventions, missing data, outcome measurement, and selective reporting. Overall risk of bias per study is shown in the final column.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7328822/v1/8d28f855fb2cd1b5649be058.png"},{"id":90892344,"identity":"d0d8f661-3e26-4987-ad61-0324a7ce3fd2","added_by":"auto","created_at":"2025-09-09 11:19:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48117,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDistribution of Risk of Bias Judgements Across Domains\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStacked bar chart summarizing the proportion of studies with low, moderate, serious, and critical risk of bias across each of the seven ROBINS-I domains. The highest prevalence of serious to critical risk was noted for bias due to confounding and deviations from intended interventions, indicating common limitations in study design and delivery. Overall, a majority of studies showed moderate to serious risk of bias, warranting cautious interpretation of pooled estimates.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7328822/v1/1a443e7f56c2561c73b7af8a.png"},{"id":90891492,"identity":"97ad06a2-a0ab-4639-b6ef-c1949f0347a5","added_by":"auto","created_at":"2025-09-09 11:11:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":150412,"visible":true,"origin":"","legend":"\u003cp\u003ea: \u0026nbsp;\u0026nbsp;Forest plot of the meta-analysis of one-sample pre-post studies\u003c/p\u003e\n\u003cp\u003eb: \u0026nbsp;Forest plot of the meta-analysis \u0026nbsp;\u0026nbsp;of control-intervention pre-post studies\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7328822/v1/d863ac5e0d076d8df35765f3.png"},{"id":90891491,"identity":"5469f099-ebc2-4c9f-bbac-43a2d457b869","added_by":"auto","created_at":"2025-09-09 11:11:13","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":84036,"visible":true,"origin":"","legend":"\u003cp\u003ea: \u0026nbsp;\u0026nbsp;Funnel plot of the meta-analysis of one-sample pre-post studies\u003c/p\u003e\n\u003cp\u003eb: \u0026nbsp;Funnel plot of the meta-analysis of control-intervention studies pre-post studies\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7328822/v1/fd117569859378459a681a8d.png"},{"id":90893993,"identity":"30ba6ad2-33ab-4c84-a444-0cb96fc6e47d","added_by":"auto","created_at":"2025-09-09 11:27:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2188087,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7328822/v1/067cbc18-1f46-46ea-b946-d6b05c1acd2a.pdf"},{"id":90892345,"identity":"784cc310-5959-4218-a52b-56da519345bc","added_by":"auto","created_at":"2025-09-09 11:19:13","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":68917,"visible":true,"origin":"","legend":"","description":"","filename":"Table1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7328822/v1/5ebd56ed471a17a513a058a2.docx"},{"id":90891493,"identity":"9131cea3-6d0a-41c5-8072-4f69d094bbff","added_by":"auto","created_at":"2025-09-09 11:11:14","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":1182424,"visible":true,"origin":"","legend":"","description":"","filename":"20250708supplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-7328822/v1/c1a5756f84ae36a4bf74e111.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effectiveness Of Mindfulness Interventions in Reducing Perceived Stress Among Nurses and Nursing Students: A Systematic Review and Meta-Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePerceived stress, defined as an individual\u0026rsquo;s subjective evaluation of life demands exceeding one\u0026rsquo;s coping ability, has profound effects on mental health, behavioral choices, and even biological aging (Cohen et al. 1983, Crist\u0026oacute;bal-Narv\u0026aacute;ez et al., 2020; Fruehwirth et al. 2023; Hrairi et al. 2021; Khaled et al. 2020; Mathur et al. 2016; Schutte \u0026amp; Malouff, 2016). Among healthcare professionals, nurses and nursing students are particularly vulnerable due to high emotional labor (Vo et al. 2022). Shift works, demanding roles, long working hours, leading to elevated perceived stress levels that correlate strongly with burnout, absenteeism, and diminished work performance (Dash et al., 2021; Hrairi et al. 2021; Sahoo et al. 2021; Shruthi et al. 2023; Singh et al. 2013). Importantly, elevated perceived stress is not only a precursor to psychological distress but also linked with accelerated biological aging, including shortened telomeres (Mathur et al. 2016), and adverse physical health outcomes such as fatty liver disease (Luo et al. 2024). Given these consequences, addressing perceived stress is a critical mental health priority in nursing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eReducing perceived stress is a vital goal for high-stress groups like nurses, with profound implications for long-term well-being. Sustained reductions in perceived stress are linked to better psychological and physical health in later life (Johnson et al., 2023). Moreover, higher perceived stress assessed by Perceived Stress Scale (PSS) strongly correlates with depression, with a one-unit increase in PSS raising the odds of depression by 1.4 times, as demonstrated in a study across 45 low- and middle-income countries (Crist\u0026oacute;bal-Narv\u0026aacute;ez et al., 2020). These findings underscore the global need to address perceived stress, given its significant impact on mental and physical health.\u003c/p\u003e\n\u003cp\u003eMindfulness-Based Interventions (MBIs), which aim to cultivate present-moment awareness and emotional regulation, have shown promise in reducing stress and improving well-being in healthcare populations (Armstrong \u0026amp; Tume, 2022; Ghawadra et al., 2019; Green \u0026amp; Kinchen 2021; La Torre et al., 2020; Ramachandran et al. 2023; Selič-Zupančič et al. 2023). MBIs are theoretically grounded in Kabat-Zinn\u0026rsquo;s Stress Reduction Theory, which posits that mindfulness facilitates adaptive responses to stressors by enhancing awareness, decentering from automatic reactions, and improving emotional self-regulation (Kabat-Zinn, 2009). Neurobiological evidence suggests that mindfulness practice reduces amygdala hyperactivity (associated with fear and stress), strengthens hippocampal connectivity (important for memory and stress buffering), and promotes cortical thickening in prefrontal regions related to self-regulation (H\u0026ouml;lzel et al., 2011; Treves et al., 2024; Caetano et al., 2022; Tang et al. 2015).\u003c/p\u003e\n\u003cp\u003eDespite the growing literature, most meta-analyses on MBIs have focused on general stress, burnout, or anxiety, and often aggregate diverse outcome measures across heterogeneous healthcare populations. However, perceived stress, as measured consistently through the Perceived Stress Scale (PSS) offers a theoretically coherent and psychometrically validated outcome that aligns directly with the goals of mindfulness (Crist\u0026oacute;bal-Narv\u0026aacute;ez et al., 2020; Schutte \u0026amp; Malouff, 2016). Moreover, perceived stress reflects internal appraisal rather than symptomatology, making it especially suitable for evaluating interventions like mindfulness, which aim to shift subjective interpretations of stressors.\u003c/p\u003e\n\u003cp\u003eTo date, few reviews have isolated the effect of MBIs on perceived stress among nurses and nursing students, despite the unique occupational demands and stressors faced by this group. Even fewer have examined how delivery mode (instructor-led vs. self-directed), intervention setting (workplace vs. non-workplace), and control group type (active vs. passive) influence intervention outcomes. One recent meta-analysis (Wexler \u0026amp; Schellinger, 2023) focused narrowly on Mindfulness-Based Stress Reduction (MBSR), yet broader mindfulness practices remain understudied despite their prevalence in nursing interventions.\u003c/p\u003e\n\u003cp\u003eThe primary objective of this review is to pool existing evidence to determine the magnitude of the effects of mindfulness interventions on perceived stress reduction among nurses. By synthesizing the available data, this review aims to evaluate the effectiveness of mindfulness as an intervention for managing stress in this high-stress professional group. The findings will provide insights into the potential of mindfulness practices to alleviate perceived stress and support well-being in nursing populations. By addressing these gaps, our study contributes a focused and theory-driven synthesis of the literature, offering practical insights for designing more effective and context-sensitive MBIs in clinical and educational nursing settings (Braun 2022).\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003eThis Systematic Review and Meta-Analysis followed the PRISMA guidelines (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) (Page, Moher, et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Page, McKenzie, et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The review protocol was registered in PROSPERO (CRD42024509223).\u003c/p\u003e\n\u003ch3\u003eSearch Strategy and Selection Criteria\u003c/h3\u003e\n\u003cp\u003eThe search incorporated Medical Subject Headings (MeSH) and relevant keywords, including \u0026ldquo;Mindfulness-based interventions,\u0026rdquo; \u0026ldquo;Perceived Stress,\u0026rdquo; \u0026ldquo;Perceived Stress Scale (PSS),\u0026rdquo; \u0026ldquo;Nurses,\u0026rdquo; and \u0026ldquo;Nursing Students.\u0026rdquo; We also reviewed references from the retrieved studies. The search covered publications up to February 2024 and included two electronic databases: PubMed and Embase. The full search strategy is tabulated in Supplementary Table\u0026nbsp;1. Additionally, to ensure comprehensiveness beyond indexed sources, we also performed backward citation tracking using Research Rabbit, a machine-learning assisted discovery tool. This step allowed us to identify additional relevant studies that may have been missed in the database search. The same is listed under the \u0026ldquo;identification of new studies via other methods\u0026rdquo; in the PRISMA flowchart (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWe included controlled and one-sample pre-post study designs if they met the following criteria: (a) participants were nurses or nursing students (b) studies employed mindfulness-based interventions comprising at least one of the core components of the following practices: Attention regulation, emotional regulation and self-awareness, (c) outcome was assessed using the Perceived Stress Scale (PSS), (d) studies published in English. (e). We included studies that reported perceived stress outcomes using the Perceived Stress Scale (PSS) only. The rationale for this restriction was twofold: (1) to maintain conceptual clarity by focusing on perceived stress as a psychological construct distinct from broader definitions of stress; and (2) to reduce outcome heterogeneity across studies. The PSS is the most widely validated tool for assessing perceived stress, enhancing the validity and interpretability of the pooled meta-analytic estimates (Yılmaz Koğar \u0026amp; Koğar \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eStudies were excluded if they were published in languages other than English, if they were case reports, protocols, reviews, editorials, or other study designs not specified above, studies involving mixed populations (e.g., healthcare professionals) if they have not explicitly stated the outcomes for nurses or using outcome measures other than the Perceived Stress Scale (PSS) were excluded.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eData Selection, Extraction and Coding\u003c/h2\u003e\u003cp\u003eThe screening process was managed using the Rayyan application (Ouzzani et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and was conducted independently by two authors (ER and SS) in two phases. First, the title and abstract screening identified eligible studies. Then, a full-text screening confirmed their inclusion. Results from both reviewers were compared at each stage, and any discrepancies were resolved through consensus with a third reviewer (RB).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData Extraction\u003c/h3\u003e\n\u003cp\u003eTwo reviewers (S.S and E.R) independently extracted data, recording all relevant information in an Excel sheet, including, study characteristics (year of publication, country, study design), population characteristics (age, sample size, percentage of female participants, professional details), intervention characteristics (duration, mode of delivery, type of intervention, instructor-led components, informal practices), outcome characteristics (pre-post and follow-up means, standard deviations of perceived stress scores for control and intervention groups, perceived stress scale results). Any discrepancies during data extraction were discussed and resolved to ensure accuracy.\u003c/p\u003e\n\u003ch3\u003eDefining Controls\u003c/h3\u003e\n\u003cp\u003eControl conditions that involve structured, purposeful activities designed to engage participants in a manner similar to experimental intervention, without including the specific active component being tested (e.g., mindfulness). These activities require ongoing interaction, structured participation, or regular engagement over time. Examples include reflection seminars, listening to relaxing music, or structured multi-session discussions.\u003c/p\u003e\u003cp\u003ePassive controls, on the other hand, include one-time activities or interventions without sustained engagement, such as single lectures or pamphlet distribution. These are not considered active controls due to their lack of comparable intensity or interaction.\u003c/p\u003e\n\u003ch3\u003eStudy Classification for Subgroup Analyses\u003c/h3\u003e\n\u003cp\u003eStudies were classified according to several methodological and contextual features:\u003c/p\u003e\u003cp\u003eStudy Design: Studies were coded as RCTs if they explicitly reported random assignment of participants to study arms. Studies without randomization but with a comparator were categorized as non-RCT controlled trials\u003c/p\u003e\u003cp\u003eIntervention Delivery: MBIs were categorized as instructor-led if sessions were delivered live by a facilitator, whether in person or via synchronous online platforms (e.g., Zoom). Interventions were classified as self-guided if participants accessed pre-recorded materials, mobile apps, or printed manuals without live facilitation. Intervention delivery modes were categorized as face-to-face (in-person), online (synchronous or asynchronous), or hybrid (combining both formats). Face-to-face referred strictly to in-person interactions.\u003c/p\u003e\u003cp\u003eIntervention Setting: Interventions were coded as workplace-based if delivered within or closely tied to the participants' clinical job setting.\u003c/p\u003e\u003cp\u003eControl Type: Active controls included any condition involving structured activities (e.g., relaxation, music therapy, stress education), while passive controls included waitlists, usual care, or no intervention.\u003c/p\u003e\u003cp\u003ePopulation Type: Studies were additionally stratified based on participant type\u0026mdash;nursing students and clinical nurses\u0026mdash;to evaluate potential differences in intervention effectiveness across training stages and stressor contexts. Classification was made based on explicit mention in the study population description. Mixed populations were excluded from this subgroup analysis unless results were reported separately for each group.\u003c/p\u003e\u003cp\u003eClassifications were made independently by two reviewers (SS and ER), with discrepancies resolved through consensus.\u003c/p\u003e\n\u003ch3\u003eStudy Quality Assessment\u003c/h3\u003e\n\u003cp\u003eThe risk of bias was evaluated by two independent reviewers using the Cochrane Risk of Bias Assessment Tool for Non-Randomized Controlled Trials (ROBINS-I) (Sterne et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Discrepancies between the reviewers were resolved through discussion. Each study was assessed across seven methodological domains, confounding bias, selection bias, classification of intervention bias, bias due to deviations from intended interventions, bias due to missing outcome data, bias in the measurement of outcomes and selection of reported results. Each domain was rated as low, moderate, serious, critical, or no information, and the overall risk of bias was summarized. The criteria for overall judgments were: Low judgment in all domains: overall low risk, moderate or low judgments across all domains: moderate risk, a serious judgment in one domain without critical judgment: serious risk, critical judgment in at least one domain: critical risk.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eMeta-Analysis of Study Designs\u003c/p\u003e\u003cp\u003eMeta-analysis was conducted using the metafor package in R. Standardized mean differences (SMDs) with 95% confidence intervals were calculated for both controlled and one-sample pre-post study designs. A random-effects model was used to evaluate the effectiveness of mindfulness-based interventions (MBIs) in reducing perceived stress among nurses.\u003c/p\u003e\u003cp\u003eWe conducted two separate meta-analyses. The first included pre-post data from all available intervention groups, including both uncontrolled studies and the intervention arms of controlled trials. This allowed for a pooled estimate of within-group change following MBIs. SMDs for these studies were directly computed using the rma() function in metafor based on reported means, SDs, and sample sizes. The effect size was calculated as the difference between post- and pre-intervention means, divided by the pooled standard deviation.\u003c/p\u003e\u003cp\u003eThe second analysis for controlled studies, we approximated difference-in-differences effect sizes using a simulation-based approach. Since participant-level data were not available, we generated synthetic individual-level scores based on reported means, standard deviations, and sample sizes for each group. For each study, we simulated pre- and post-intervention data for both the intervention and control arms using the rnorm() function in R, with fixed seeds for reproducibility. We then computed the mean and standard deviation of the within-group change scores and derived the between-group contrast.\u003c/p\u003e\u003cp\u003eThis approach allowed us to estimate the incremental effect of MBIs relative to a comparator. All simulations and meta-analyses files are made available in the associated GitHub repository.\u003c/p\u003e\u003cp\u003eSMD values were classified as small (0.2 to 0.49), medium (0.5 to 0.79), and large (\u0026ge;\u0026thinsp;0.8). Heterogeneity was assessed using the I\u0026sup2; test, with values of 25%, 50%, and 75% indicating low, intermediate, and high heterogeneity, respectively. Publication bias was assessed using a funnel plot and Egger\u0026rsquo;s test. If Egger\u0026rsquo;s test was significant, we followed it with the Duval \u0026amp; Tweedie\u0026rsquo;s trim-and-fill procedure (Schwarzer et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) to detect the actual effect size considering if the missing small effect size studies were published.\u003c/p\u003e\u003cp\u003eSeveral subgroup analyses were conducted to explore the effect size of various factors, such as instructor-led interventions, active vs. non-active control groups, RCT vs. non-RCT studies, and workplace vs. non-workplace interventions. Additionally, a sensitivity analysis was conducted after removing one outlier study to assess its impact on overall outcomes.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eStudy selection\u003c/h2\u003e\u003cp\u003eOur search yielded 2024 results, which were uploaded to Rayyan for downstream processing. After removing 474 duplicates, 1550 unique articles remained. These were screened based on title and abstract, leading to the exclusion of 1299 records due to irrelevance, leaving 251 articles for further consideration. During the full-text review, 62 articles were excluded for not meeting the inclusion criteria, resulting in 34 eligible studies. Additionally, 2 studies were included through citation searching, making a total of 36 studies. The stages of screening and the corresponding numbers of results are depicted in the PRISMA flowchart below (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eStudy characteristics\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;1 summarizes the characteristics of the studies included in the systematic review. A total of 36 studies were eligible and included for the synthesis of results, involving 2,201 participants. The studies were divided into two categories: one-sample pre-post studies (n\u0026thinsp;=\u0026thinsp;18) and control-intervention pre-post studies (n\u0026thinsp;=\u0026thinsp;18). Of the 18 control-intervention pre-post studies, 15 were randomized controlled trials (RCTs), and five of these used active control groups. For meta-analysis, 5 studies were excluded from the one-sample pre-post intervention designs and 2 from control-intervention pre-post studies as either the central tendencies or the dispersion values were not reported.\u003c/p\u003e\u003cp\u003e===Insert table 1 here==\u003c/p\u003e\u003cp\u003eThe interventions primarily focused on Mindfulness-Based Stress Reduction (MBSR) in 36% (n\u0026thinsp;=\u0026thinsp;13) of the studies (Anderson, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Bazarko et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Cepeda-Lopez et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Conelius et al., 2021; Janzarik et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Kulka et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Lin et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Mahon et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; McNulty, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Pan et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Santos et al., 2016; Spadaro \u0026amp; Hunker, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Wright et al., 2018), with follow-up periods ranging from 1 to 36 weeks. All follow-ups were at least 4 weeks, except for one study (Fong et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) where mindful coloring was the intervention, and the follow-up was conducted after 1 week. About 33% of the studies had 8 weeks study duration and nine studies had more than 8 weeks of intervention (Cepeda-Lopez et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Chesak et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Conelius et al., 2021; Coster et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Drew et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Dyess et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fadzil et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; McNulty, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Plummer et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The mean age of participants ranged from 18 to 65 years, although three studies did not report participant ages (Ficarra, 2023; Fr\u0026ouml;g\u0026eacute;li, et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Kulka et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and one study did not provide an upper age limit (Sawyer et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Around 30% (n\u0026thinsp;=\u0026thinsp;11) of the studies were conducted with nursing students (Alhawatmeh et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Burger et al., 2017; Burner \u0026amp; Spadaro \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Conelius et al., 2021; Coster et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Drew et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Fr\u0026ouml;g\u0026eacute;li, Djordjevic, et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; \u0026Ouml;zt\u0026uuml;rk, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Plummer et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ratanasiripong et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Spadaro \u0026amp; Hunker, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe majority (41%, n\u0026thinsp;=\u0026thinsp;15) of interventions were face-to-face (in-person) interventions, were delivered online (synchronous or asynchronous) in 12 studies 8 followed a combined or hybrid modality. Around 58% (n\u0026thinsp;=\u0026thinsp;21) were delivered at the workplace. Around 50% (n\u0026thinsp;=\u0026thinsp;19) of studies were instructor-led.\u003c/p\u003e\u003cp\u003eRegarding stress measurement, 52% (n\u0026thinsp;=\u0026thinsp;19) of the studies used the PSS-10 scale, one study used the PSS-4 (Pratt et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and the rest used the PSS-14 version of the Perceived Stress Scale. Most of the studies included predominantly female participants. Except for one study, which had a female population of 52\u0026ndash;66% (Alhawatmeh et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), over 80% of the participants in all other studies were females.\u003c/p\u003e\u003cp\u003eA vast majority of 67% (n\u0026thinsp;=\u0026thinsp;25) of the studies were done in the USA. There were only two studies (Fadzil et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Fong et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) from the Asian continent. Two studies were conducted in the UK (Anderson, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Coster et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), one each from Mexico (Cepeda-Lopez et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Canada (Silva Gherardi-Donato et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), Brazil (Dos Santos et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), Sweden (Fr\u0026ouml;g\u0026eacute;li, Djordjevic, et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), Germany (Janzarik et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Jordan (Alhawatmeh et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and Ireland (Mahon et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe distribution of mindfulness intervention components (attention regulation, emotional regulation, and self-awareness) across the included studies is depicted in Supplementary Fig.\u0026nbsp;1. The majority of the studies incorporated components targeting attention regulation, with this element being present in most interventions. Four studies focused exclusively on emotional regulation (Bluth et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Fr\u0026ouml;g\u0026eacute;li, Djordjevic, et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Janzarik et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sawyer et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), while five studies included only attention regulation as a component (Burger et al., 2017; Drew et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Dyess et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fong et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Graham et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Notably, no studies were identified that targeted only self-awareness without incorporating other components.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eRisk of bias within studies\u003c/h2\u003e\u003cp\u003eThe risk of bias (RoB) assessment across the included studies was evaluated using the ROBINS-I tool, with judgments made for seven key bias domains (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTraffic-light plot showing domain-wise risk of bias assessments across all included studies using the ROBINS-I tool. Judgements are color-coded: low (yellow), moderate (orange), serious (dark orange), and critical (red). Domains assessed include confounding, participant selection, intervention classification, deviations from intended interventions, missing data, outcome measurement, and selective reporting. Overall risk of bias per study is shown in the final column.\u003c/p\u003e\u003cp\u003eOverall, the studies demonstrated varying levels of bias across domains, with confounding (D1) being a particularly significant concern. All the studies were rated as having serious risk of bias in this domain, primarily due to the lack of control for potential confounding factors such as workplace environment including workplace conflict or violence, shift duty, duty hours, which could have influenced the observed outcomes. The selection of participants (D2) and classification of interventions (D3) were generally well-controlled, with most studies rated as having low or moderate risk of bias in these domains. However, three studies exhibited serious risk due to unclear participant selection criteria. The risk of bias due to deviations from intended interventions (D4) was also moderate in most cases, suggesting reasonable fidelity in intervention delivery. These included that the study participants either did not adhere to the assigned intervention regimen or failed to report an appropriate analysis method to estimate the initiation and adherence to the interventions. Seven studies showed serious and 2 showed critical risk for missing data (D5). For the measurement of outcomes (D6) majority were carrying serious risk of bias, thus incomplete outcome data and inconsistent measurement techniques being notable issues. This could potentially introduce bias in the interpretation of the intervention effects. Furthermore, a few (n\u0026thinsp;=\u0026thinsp;3) exhibited moderate risk in the selection of reported results (D7), indicating possible selective reporting, which could further impact the overall reliability of findings. The aggregate results of the RoB assessment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) indicate that while certain methodological aspects, such as participant selection and intervention classification, were well-managed, the high risk of bias due to confounding, missing data, and measurement outcomes could limit the validity of the results. These methodological concerns need to be carefully considered when interpreting the pooled estimates in the meta-analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eMeta-analysis\u003c/h2\u003e\u003cp\u003eThe effect size obtained for perceived stress, the primary outcome, was statistically significant for the mindfulness intervention group, reaching a moderate magnitude based on Cohen\u0026rsquo;s d in the one-sample pre-post studies (0.54 [0.32, 0.76]), suggesting that mindfulness interventions had a meaningful impact on stress reduction in these studies. In the control intervention design, the reduction in perceived stress was also statistically significant but demonstrated a small effect size (0.21 [0.05, 0.37]), reflecting modest benefits of mindfulness interventions in controlled comparisons.\u003c/p\u003e\u003cp\u003eFigure 4a, b displays two forest plots: one for one-sample pre-post studies and one for control-intervention pre-post studies.\u003c/p\u003e\u003cp\u003eHeterogeneity was high in the one-sample pre-post studies (87.4%) and moderate in the control-intervention pre-post studies (49.5%).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003ePublication bias\u003c/h2\u003e\u003cp\u003eIntervention only studies carried a significant asymmetry (z = -3.6260, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0003) suggesting a potential publication bias in the included studies. This is further corroborated in the funnel plot depicted in Fig.\u0026nbsp;5a. The plot appears asymmetrical, with one particular study lying on one side of the mean effect, in the negative effect region. Duval \u0026amp; Tweedie\u0026rsquo;s trim-and-fill procedure did not find any missing studies on the right side of the funnel plot, with a standard error (SE) of 3.1181, indicating that the observed asymmetry might not be due to a lack of studies. This trim-and-fill analysis implies that the observed effect size remains robust even after correcting for potential publication bias, with substantial heterogeneity across studies.\u003c/p\u003e\u003cp\u003eFurther publication bias for control-intervention pre-post studies was assessed using Egger\u0026rsquo;s test, yielding a non-significant result (z = -0.6662, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.505). This indicates minimal evidence of publication bias, further supported by the symmetry observed in the funnel plot for these studies.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eSubgroup analysis\u003c/h2\u003e\u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\u003ch2\u003eWorkplace and non-workplace interventions\u003c/h2\u003e\u003cp\u003eThe subgroup analysis (Supplementary Fig.\u0026nbsp;2a) compared the effectiveness of mindfulness interventions in workplace and non-workplace settings. In the workplace subgroup, the effect was moderate (SMD = -0.61 [95% CI: -0.98 to -0.25]) and more compared to the non-workplace subgroup (SMD = -0.43 [95% CI: -0.65 to -0.21]) that showed a small-to-moderate effect. However, the test for subgroup differences was not statistically significant (Q\u003csub\u003eM\u003c/sub\u003e = 0.34, p\u0026thinsp;=\u0026thinsp;0.56), suggesting similar intervention effectiveness across settings. High heterogeneity was observed in both subgroups (I\u0026sup2; = 91.5% for workplace; I\u0026sup2; = 65.3% for non-workplace), warranting further exploration of variability. Among control-intervention pre-post design (Supplementary Fig.\u0026nbsp;2b), in the workplace subgroup, the SMD was \u0026minus;\u0026thinsp;0.25 [95% CI: -0.46 to -0.04], showing a statistically significant reduction in stress with a small effect size. Moderate heterogeneity was observed (I\u0026sup2; = 57.6%, p\u0026thinsp;=\u0026thinsp;0.016). In the non-workplace subgroup, the SMD was much lower at -0.15 [95% CI: -0.40 to 0.11], with no statistically significant effect. Heterogeneity was lower (I\u0026sup2; = 38.4%, p\u0026thinsp;=\u0026thinsp;0.132). The test for subgroup differences was not statistically significant (Q\u003csub\u003eM\u003c/sub\u003e = 0.33, p\u0026thinsp;=\u0026thinsp;0.57), suggesting comparable effects of mindfulness interventions in the workplace and non-workplace settings for controlled designs.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eInstructor-Led vs. Non-Instructor-Led Mindfulness Interventions\u003c/h2\u003e\u003cp\u003eAmong one-sample pre-post design studies (Supplemental Fig.\u0026nbsp;3a), there was a significant reduction in perceived stress in the instructor-led subgroup, with substantial heterogeneity (I\u0026sup2; = 83.3%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Non-instructor led group showed a large but imprecise effect \u0026minus;\u0026thinsp;0.86 [95% CI: -2.02 to 0.31] with wider confidence interval, suggesting possible variability or small study effects. The heterogeneity in this subgroup was very high (I\u0026sup2; = 96.0%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The test for subgroup differences was not statistically significant (Q\u003csub\u003eM\u003c/sub\u003e = 0.64, p\u0026thinsp;=\u0026thinsp;0.42), indicating no clear evidence that instructor-led interventions are more effective than non-instructor-led ones. However, the heterogeneity within subgroups suggests variability in intervention implementation and outcomes. Subgroup Analysis for Instructor-Led vs. Non-Instructor-Led Mindfulness Interventions in Control-Intervention Design pre post designs (Supplementary Fig.\u0026nbsp;3b) revealed a smaller and non-significant reduction in perceived stress levels among the non-instructor led group. Heterogeneity was low (I\u0026sup2; = 0%, p\u0026thinsp;=\u0026thinsp;0.371), indicating consistency across studies. Instructor-led interventions showed a small and statistically significant reduction in stress, with moderate heterogeneity (I\u0026sup2; = 55.8%, p\u0026thinsp;=\u0026thinsp;0.008). The test for subgroup differences was not statistically significant (Q\u003csub\u003eM\u003c/sub\u003e = 0.16, p\u0026thinsp;=\u0026thinsp;0.69), suggesting no strong evidence of differential effects between instructor-led and non-instructor-led interventions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eClinical Nurses vs. Nursing Students\u003c/h2\u003e\u003cp\u003eTo explore differential effects based on population type, we conducted a subgroup analysis comparing clinical nurses and nursing students (Supplementary Figs.\u0026nbsp;4a, b). In the one-sample pre-post studies, MBIs showed a significant reduction in perceived stress for both groups. The pooled effect size was \u0026minus;\u0026thinsp;0.54 [\u0026ndash;0.84, \u0026minus;\u0026thinsp;0.23] for nurses and \u0026minus;\u0026thinsp;0.55 [\u0026ndash;0.75, \u0026minus;\u0026thinsp;0.36] for nursing students, both reflecting moderate effects. In controlled intervention studies, however, the effect was smaller and significant for nurses (\u0026ndash;0.15 [\u0026ndash;0.30, \u0026minus;\u0026thinsp;0.00]) but non-significant for students (\u0026ndash;0.30 [\u0026ndash;0.62, 0.03]), suggesting potential variability in how MBIs perform in more rigorously controlled settings across populations. Test for subgroup differences was non-significant in both designs (QM\u0026thinsp;=\u0026thinsp;0.05, p\u0026thinsp;=\u0026thinsp;0.83 for intervention-only; QM\u0026thinsp;=\u0026thinsp;0.68, p\u0026thinsp;=\u0026thinsp;0.41 for controlled), indicating no statistically reliable difference, though the patterns point to contextually nuanced effectiveness.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eSubgroup Analysis for RCT vs. Non-RCT Studies\u003c/h2\u003e\u003cp\u003eSupplementary Fig.\u0026nbsp;5 illustrates non-RCT studies demonstrated a small-to-moderate effect with statistically significant reduction in stress with low heterogeneity (I\u0026sup2; = 8.4%, p\u0026thinsp;=\u0026thinsp;0.358), suggesting consistent findings across studies. RCTs showed a smaller and non-significant reduction in stress. Moderate heterogeneity was observed (I\u0026sup2; = 51.6%, p\u0026thinsp;=\u0026thinsp;0.014). The test for subgroup differences was not statistically significant (QM\u0026thinsp;=\u0026thinsp;1.30, p\u0026thinsp;=\u0026thinsp;0.25), suggesting no strong evidence that the effect size varies significantly by study design. However, non-RCTs demonstrated a slightly larger and more consistent effect compared to RCTs.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eSubgroup Analysis for Active vs. No Active Controls\u003c/h2\u003e\u003cp\u003eSupplementary Fig.\u0026nbsp;6 depicts the effects of mindfulness interventions between studies with active control groups and those with no active controls in control-intervention designs. Studies with no active controls demonstrated a small but significant reduction in stress with no heterogeneity (I\u0026sup2; = 0.0%, p\u0026thinsp;=\u0026thinsp;0.302), indicating consistent results across studies. Studies with active controls had a very small and non-significant effect with high variability (I\u0026sup2; = 85.1%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The test for subgroup differences was not statistically significant (QM\u0026thinsp;=\u0026thinsp;0.27, p\u0026thinsp;=\u0026thinsp;0.60), suggesting no strong evidence that the effect size varies significantly between studies with active versus no active controls. However, interventions without active controls yielded more consistent and statistically significant results compared to those with active controls.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eSensitivity analysis\u003c/h2\u003e\u003cp\u003eThe leave-one-out sensitivity analysis for intervention-only designs (Supplementary Fig.\u0026nbsp;6a) revealed consistent results across studies, as the overall standardized mean difference (SMD) remained relatively stable upon the removal of individual studies. The effect sizes ranged between approximately \u0026minus;\u0026thinsp;0.40 and \u0026minus;\u0026thinsp;0.60, with no single study significantly altering the pooled effect size. The heterogeneity (I\u0026sup2;) was similarly robust across iterations, fluctuating minimally from the overall I\u0026sup2; of 87.8%, confirming that no single study disproportionately influenced the overall findings. The slight variability observed when certain studies (e.g., Mahon_2017 and Dyess_2018) were removed suggests that these studies may have contributed slightly to the heterogeneity but not to the magnitude of the overall effect. In addition, we conducted a formal sensitivity analysis excluding both Dyess_2018 and Mahon_2017, two studies with notably large effect sizes. The pooled standardized mean difference was attenuated from \u0026minus;\u0026thinsp;0.54 (95% CI: \u0026minus;\u0026thinsp;0.76 to \u0026minus;\u0026thinsp;0.32; I\u0026sup2; = 87.4%) in the full model to \u0026minus;\u0026thinsp;0.41 (95% CI: \u0026minus;\u0026thinsp;0.58 to \u0026minus;\u0026thinsp;0.25; I\u0026sup2; = 76.3%) when these studies were removed. The effect remained statistically significant and directionally consistent, supporting the robustness of our findings while acknowledging the influence of high-effect studies on magnitude (Supplementary Fig.\u0026nbsp;6b). Sensitivity analysis comparing the full pooled estimate with results excluding 2 studies (Dyess 2018 and Mahon 2016) is listed in Supplementary Table\u0026nbsp;2.\u003c/p\u003e\u003cp\u003eThe leave-one-out sensitivity analysis for controlled-intervention designs (Supplementary Fig.\u0026nbsp;6c) demonstrated consistent results across studies, with the overall standardized mean difference (SMD) remaining stable when individual studies were removed. The recalculated effect sizes ranged between approximately \u0026minus;\u0026thinsp;0.15 and \u0026minus;\u0026thinsp;0.35, with no single study significantly altering the pooled effect size. The heterogeneity (I\u0026sup2;) fluctuated only slightly from the overall I\u0026sup2; of 49.5%, confirming the robustness of the meta-analytic findings. Minor variability was noted when specific studies, such as Alhawatmeh et al (Alhawatmeh et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and Chesak et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2015\u003c/span\u003e, were excluded, indicating a marginal contribution to the heterogeneity without substantial impact on the overall effect.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis systematic review and meta-analysis evaluated the effectiveness of mindfulness-based interventions (MBIs) in reducing perceived stress among nursing professionals. Synthesizing data from 36 studies with a combined sample of 2,201 participants, we found that MBIs had statistically significant reductions in perceived stress, with pooled effects in the small to medium range. Specifically, the effect size in one-sample pre-post studies was moderate (SMD\u0026thinsp;=\u0026thinsp;0.54), and in control-intervention designs, it was small (SMD\u0026thinsp;=\u0026thinsp;0.21), reflecting modest but meaningful improvements in stress reduction. These findings support the potential utility of MBIs for stress management in both nursing students and clinical nurses.\u003c/p\u003e\u003cp\u003eOur observed effect sizes, a moderate effect (SMD\u0026thinsp;=\u0026thinsp;0.54) in one-sample pre-post studies and a small effect (SMD\u0026thinsp;=\u0026thinsp;0.21) in controlled designs align with, and in some cases exceed those reported in previous meta-analyses evaluating MBIs for perceived stress across different populations. For instance, Bartlett et al. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) reported a comparable effect size of Hedges\u0026rsquo; g\u0026thinsp;=\u0026thinsp;0.56 in general workplace settings, while G\u0026aacute;l et al. (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found a moderate effect of g\u0026thinsp;=\u0026thinsp;0.46 among general adult users of mindfulness mobile apps. Michaelsen et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) observed a higher effect (SMD\u0026thinsp;=\u0026thinsp;0.72) across employee populations including healthcare workers, though nurses were not separately analyzed. Meanwhile, a review by Xu et al. (\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) focusing on emergency department personnel, including nurses, yielded a non-significant pooled effect (SMD = \u0026minus;\u0026thinsp;0.32), highlighting possible variability by occupational role or setting. Among student populations, Zuo et al. (\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) reported a smaller but significant pooled effect (SMD = \u0026minus;\u0026thinsp;0.39), consistent with our subgroup findings for nursing students (SMD = \u0026minus;\u0026thinsp;0.36). Taken together, our findings are consistent with a growing body of evidence supporting MBIs for stress reduction, while also underscoring the importance of contextual and methodological factors such as population type, setting, and intervention delivery mode.\u003c/p\u003e\u003cp\u003eThe effects were largely driven by intervention-only pre-post studies, though our analysis showed that these effects remained directionally consistent even when restricted to controlled trials using difference-in-differences estimators. A leave-one-out sensitivity analysis showed that the findings were robust to exclusion of any single study, and a targeted sensitivity analysis excluding outlier studies (Dyess_2018 and Mahon_2016) showed only a moderate reduction in effect size. This suggests that while some studies contributed disproportionately to effect magnitude, the direction and statistical significance of pooled results were preserved.\u003c/p\u003e\u003cp\u003eOur findings extend previous meta-analyses by focusing specifically on perceived stress, rather than general stress or burnout, and by using a consistent and validated measure (the Perceived Stress Scale, PSS). This conceptual precision enhances interpretability. While many prior reviews have combined various stress constructs and outcome tools, our analysis isolates perceived stress as a psychological construct particularly aligned with the mechanisms of mindfulness, such as cognitive reappraisal and attention regulation and present-moment awareness.\u003c/p\u003e\u003cp\u003eA notable finding is that no study focused solely on self-awareness as a mindfulness component, with most interventions emphasizing attention or emotional regulation. This points to a meaningful gap in literature and a future opportunity for developing targeted self-awareness interventions, particularly given its theoretical centrality to mindfulness practice.\u003c/p\u003e\u003cp\u003eThe subgroup analyses offer valuable insights into implementation. The study highlights potential differences in intervention effects between clinical nurses and nursing students. In one-sample pre-post designs, both groups benefited similarly, with moderate effect sizes. However, in controlled trials, the effect was weaker and non-significant for students, suggesting that contextual or developmental differences, such as academic vs. workplace stressors\u0026mdash;may influence how MBIs are perceived or engaged with. This also raises the possibility that clinical nurses may respond more strongly to workplace-integrated interventions, while students may require pedagogical tailoring or different delivery structures. These insights underscore the importance of population-specific adaptation when designing mindfulness programs for nursing education versus professional practice.\u003c/p\u003e\u003cp\u003eStronger effects were observed in workplace-based interventions, suggesting that MBIs delivered in clinical settings may more directly address occupational stressors and benefit from environmental reinforcement. Similarly, instructor-led interventions showed greater effectiveness than self-guided formats. The presence of a facilitator may enhance therapeutic alliance, accountability, and engagement\u0026mdash;key ingredients in mindfulness-based approaches. While our analysis did not examine facilitator background in detail, future research should explore whether facilitators with clinical or institutional familiarity (e.g., nurse educators or in-house staff vs. external mindfulness trainers) yield better outcomes, particularly through increased relevance and cultural alignment.\u003c/p\u003e\u003cp\u003eThe observed attenuation of effects in RCTs compared to. non-RCTs highlight the influence of study design, an expected but important methodological consideration. Effects were also smaller in studies with active controls (e.g., music therapy, stress education), suggesting that some components of MBIs (e.g., structured relaxation or emotional regulation) may overlap with those of other psychosocial interventions. This underscores the need for precise mechanism testing and dismantling studies.\u003c/p\u003e\u003cp\u003eTaken together, these results emphasize the need for contextually tailored, well-facilitated MBIs, ideally delivered in the workplace, instructor-led, and evaluated through methodologically rigorous designs. Our study contributes to the growing literature on mindfulness as a scalable, flexible stress-reduction tool for nursing populations, while also clarifying the conditions and subgroups in which it is likely to be most effective.\u003c/p\u003e\u003cdiv id=\"Sec23\" class=\"Section2\"\u003e\u003ch2\u003eLimitations and Future Research\u003c/h2\u003e\u003cp\u003eThis review has a few methodological and conceptual limitations. First, we restricted inclusion to studies using the Perceived Stress Scale (PSS), a validated instrument aligned with mindfulness mechanisms such as cognitive reappraisal and attention regulation. While this enhanced conceptual coherence, it may have excluded relevant studies using alternative stress measures. Similarly, most included studies were non-randomized and underpowered, underscoring the need for larger, well-designed RCTs. Our search was limited to PubMed and Embase due to project constraints, though we mitigated this by performing backward citation tracking. Finally, most studies relied on self-report outcomes, which could be complemented by physiological or behavioral markers to improve validity.\u003c/p\u003e\u003cp\u003eIn terms of intervention variability, studies differ widely in MBI duration, content, and delivery, limiting comparability. Fidelity reporting was often missing, and only a few studies examined sustained effects beyond immediate post-intervention. The predominance of female participants reflects the gender distribution in nursing but limits generalizability. Instructor backgrounds and modes of delivery were inconsistently reported, leaving open questions about the role of facilitator expertise and participant engagement.\u003c/p\u003e\u003cp\u003eFuture research should address these gaps by (1) investigating whether interventions led by internal facilitators (e.g., nurse educators or healthcare providers familiar with occupational stressors) are more effective than those delivered by external mindfulness experts, (2) identifying which specific MBI components (e.g., attention regulation, emotional regulation, self-awareness) most contribute to stress reduction, and (3) examining how institutional and contextual factors, such as workplace culture, peer participation, and leadership support influence engagement and outcomes. Embedding MBIs into structured workplace wellness programs may enhance adherence, contextual relevance, and scalability. Additionally, long-term follow-ups, standardized intervention protocols, and greater inclusion of male and gender-diverse samples will be essential to strengthen the global applicability and methodological rigor of MBI research in nursing populations.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eEthical Clearance\u003c/h2\u003e\u003cp\u003eThe manuscript does not contain clinical studies or patient data and is a systematic review and meta-analysis with no primary data collection; hence, ethical clearance was not applicable.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthical Clearance\u003c/h2\u003e\n\u003cp\u003eThe manuscript does not contain clinical studies or patient data and is a systematic review and meta-analysis with no primary data collection; hence, ethical clearance was not applicable.\u003c/p\u003e\n\u003ch2\u003eConflict of Interest\u003c/h2\u003e\u003cp\u003eWe declare that we have no conflicts of interest.\u003c/p\u003e\u003ch2\u003eFunding Information\u003c/h2\u003e\u003cp\u003eThis study was conducted without funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eThe idea for this systematic review and meta-analysis was conceived by Dr. Ekta Ram and Dr. Soundarya Soundararajan; Dr. Ekta Ram prepared the study protocol, which was reviewed and approved by Dr. Soundarya Soundararajan and Dr. Rakesh Balachandar and subsequently registered in PROSPERO. The literature search and data extraction were performed by Dr. Ekta Ram and Dr. Soundarya Soundararajan. The initial analysis was conducted by Dr. Soundarya Soundararajan, with the interpretation of results collaboratively performed by Dr. Ekta Ram and Dr. Soundarya Soundararajan, with support from Dr. Rakesh Balachandar. Dr. Soundarya Soundararajan supervised the study. Dr. Ekta Ram and Dr. Soundarya Soundararajan drafted the manuscript, and all authors reviewed and revised it. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors thank the researchers and authors who generously provided full-text articles and additional materials upon request, which greatly supported the completion of this review.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlhawatmeh, H. N., Rababa, M., Alfaqih, M., Albataineh, R., Hweidi, I., \u0026amp; Abu Awwad, A. (2022). 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M., Hr\u0026oacute;bjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., \u0026hellip; McKenzie, J. E. (2021). PRISMA 2020 explanation and elaboration: Updated guidance and exemplars for reporting systematic reviews. BMJ, n160. https://doi.org/10.1136/bmj.n160\u003c/li\u003e\n\u003cli\u003ePan, C., Wang, H., Chen, M., Cai, Y., Xiao, C., Tang, Q., \u0026amp; Koniak-Griffin, D. (2019). Mindfulness-based intervention for nurses in AIDS care in China: A pilot study. Neuropsychiatric Disease and Treatment, 3131-3141. https://doi.org/10.2147/ndt.s223036 \u003c/li\u003e\n\u003cli\u003ePlummer, C., Cloyd, E., Doersam, J. K., Dietrich, M. S., \u0026amp; Hande, K. A. (2018). Mindfulness in a graduate nursing curriculum: A randomized controlled study. Holistic Nursing Practice, 32(4), 189\u0026ndash;195. https://doi.org/10.1097/HNP.0000000000000277 \u003c/li\u003e\n\u003cli\u003ePratt, E. H., Hall, L., Jennings, C., Olsen, M. K., Jan, A., Parish, A., Porter, L. S., \u0026amp; Cox, C. E. (2023). Mobile mindfulness for psychological distress and burnout among frontline covid-19 nurses: A pilot randomized trial. Annals of the American Thoracic Society, 20(10), 1475\u0026ndash;1482. https://doi.org/10.1513/AnnalsATS.202301-025OC \u003c/li\u003e\n\u003cli\u003eRamachandran, H. J., Bin Mahmud, M. S., Rajendran, P., Jiang, Y., Cheng, L., \u0026amp; Wang, W. (2023). Effectiveness of mindfulness-based interventions on psychological well-being, burnout and post-traumatic stress disorder among nurses: A systematic review and meta-analysis. Journal of Clinical Nursing, 32(11\u0026ndash;12), 2323\u0026ndash;2338. https://doi.org/10.1111/jocn.16265 \u003c/li\u003e\n\u003cli\u003eRatanasiripong, P., Park, J. F., Ratanasiripong, N., \u0026amp; Kathalae, D. (2015). Stress and anxiety management in nursing students: Biofeedback and mindfulness meditation. 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The impact of a psychoeducational group program on the mental well-being of unit-based nurse leaders: A randomized controlled trial. International Journal of Environmental Research and Public Health, 20(11), 6035. https://doi.org/10.3390/ijerph20116035 \u003c/li\u003e\n\u003cli\u003eSchutte, N. S., \u0026amp; Malouff, J. M. (2016). The relationship between perceived stress and telomere length: A meta-analysis. Stress and Health, 32(4), 313\u0026ndash;319. https://doi.org/10.1002/smi.2607\u003c/li\u003e\n\u003cli\u003eSchwarzer, G., Carpenter, J. R., \u0026amp; R\u0026uuml;cker, G. (2015). Meta-analysis with r. Springer International Publishing. https://doi.org/10.1007/978-3-319-21416-0 \u003c/li\u003e\n\u003cli\u003eSelic-Zupancic, P., Klemenc-Keti\u0026scaron;, Z., \u0026amp; Onuk Tement, S. (2023). The impact of psychological interventions with elements of mindfulness on burnout and well-being in healthcare professionals: a systematic review. Journal of multidisciplinary healthcare, 1821-1831. https://doi.org/10.2147/JMDH.S398552 \u003c/li\u003e\n\u003cli\u003eShruthi, M. N., Veena, V., \u0026amp; Seeri, J. S. (2023). Prevalence of psychological distress and perceived stress among nursing staff in a tertiary care center, Bengaluru. MRIMS Journal of Health Sciences, 11(1), 41-47. https://doi.org/10.4103/mjhs.mjhs_28_22 \u003c/li\u003e\n\u003cli\u003eSingh, A., Chopra, M., Adiba, S., Mithra, P., Bhardwaj, A., Arya, R., Chikkara, P., Duraisamy Rathinam, R., \u0026amp; Panesar, S. (2013). A descriptive study of perceived stress among the North Indian nursing undergraduate students. Iranian Journal Of Nursing And Midwifery Research, 18(4). Retrieved from http://ijnmr.mui.ac.ir/index.php/ijnmr/article/view/917/693\u003c/li\u003e\n\u003cli\u003eSpadaro, K. C., \u0026amp; Hunker, D. F. (2016). Exploring The effects Of An online asynchronous mindfulness meditation intervention with nursing students On Stress, mood, And Cognition: A descriptive study. Nurse Education Today, 39, 163\u0026ndash;169. https://doi.org/10.1016/j.nedt.2016.02.006 \u003c/li\u003e\n\u003cli\u003eSterne, J. A., Hern\u0026aacute;n, M. A., Reeves, B. C., Savovic, J., Berkman, N. D., Viswanathan, M., Henry, D., Altman, D. G., Ansari, M. T., Boutron, I., Carpenter, J. R., Chan, A.-W., Churchill, R., Deeks, J. J., Hr\u0026oacute;bjartsson, A., Kirkham, J., J\u0026uuml;ni, P., Loke, Y. K., Pigott, T. D., \u0026hellip; Higgins, J. P. (2016). ROBINS-I: A tool for assessing risk of bias in non-randomised studies of interventions. BMJ, i4919. https://doi.org/10.1136/bmj.i4919 \u003c/li\u003e\n\u003cli\u003eStillwell, S. B., Vermeesch, A. L., \u0026amp; Scott, J. G. (2017). Interventions to reduce perceived stress among graduate students: A systematic review with implications for evidence-based practice. 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(2023). Mindfulness-based stress reduction for nurses: An integrative review. Journal of Holistic Nursing, 41(1), 40\u0026ndash;59. https://doi.org/10.1177/08980101221079472 \u003c/li\u003e\n\u003cli\u003eWright, E. M. (2018). Evaluation of a web-based holistic stress reduction pilot program among nurse-midwives. Journal of Holistic Nursing, 36(2), 159\u0026ndash;169. https://doi.org/10.1177/0898010117704325 \u003c/li\u003e\n\u003cli\u003eXu, H. (Grace), Kynoch, K., Tuckett, A., \u0026amp; Eley, R. (2020). Effectiveness of interventions to reduce emergency department staff occupational stress and/or burnout: A systematic review. JBI Evidence Synthesis, 18(6), 1156\u0026ndash;1188. https://doi.org/10.11124/JBISRIR-D-19-00252 \u003c/li\u003e\n\u003cli\u003eYilmaz Kogar, E., \u0026amp; Kogar, H. (2024). A systematic review and meta-analytic confirmatory factor analysis of the perceived stress scale (PSS-10 and PSS-14). Stress and Health, 40(1), e3285. https://doi.org/10.1002/smi.3285 \u003c/li\u003e\n\u003cli\u003eZuo, X., Tang, Y., Chen, Y., \u0026amp; Zhou, Z. (2023). The efficacy of mindfulness-based interventions on mental health among university students: A systematic review and meta-analysis. Frontiers in Public Health, 11, 1259250. https://doi.org/10.3389/fpubh.2023.1259250 \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 1","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"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":"Mindfulness-Based Interventions, Perceived Stress, Nurses, Nursing Students, Systematic Review, Meta-Analysis","lastPublishedDoi":"10.21203/rs.3.rs-7328822/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7328822/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjectives\u003c/h2\u003e\u003cp\u003eWhile mindfulness-based interventions (MBIs) have demonstrated effectiveness in reducing anxiety and depression, their impact on perceived stress, a key driver of burnout and reduced well-being among clinical nurses and nursing students remains underexplored. This study synthesizes evidence on the effects of MBIs in mitigating perceived stress within this high-stress professional group, focusing on intervention delivery, settings, and methodological variations.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA systematic search was conducted in PubMed and Embase, identifying studies evaluating the effects of mindfulness on perceived stress. Standardized mean differences (SMDs) were calculated using random-effects models. Thirty-six studies involving 2,201 participants were included. Separate meta-analyses were conducted for (1) one-sample pre-post designs and (2) intervention-control designs. Subgroup analyses examined variables including control type (active vs. non-active), intervention mode (instructor-led vs. self-directed), intervention setting (workplace vs. non-workplace). Sensitivity analyses were performed to assess the robustness of findings.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eMindfulness interventions significantly reduced perceived stress, with medium effects in one-sample pre-post studies (SMD = -0.54 [-0.77, -0.31]) and small effects in intervention-control studies (SMD = -0.21 [-0.37, -0.05]). Subgroup analyses revealed stronger effects for instructor-led interventions, workplace settings, and non-active controls. Sensitivity analyses confirmed the stability of findings, with no single study disproportionately influencing the pooled effect sizes.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis meta-analysis reaffirms the efficacy of MBIs in reducing perceived stress among clinical nurses and nursing students. Instructor-led and workplace-based interventions emerged as particularly effective. These findings highlight the potential of tailored MBIs to enhance stress management strategies, support mental health, and build resilience in clinical and educational nursing settings.\u003c/p\u003e\u003ch2\u003ePreregistration\u003c/h2\u003e\u003cp\u003eThis systematic review/meta-analysis was preregistered in PROSPERO (Ref no: CRD42024509223)\u003c/p\u003e","manuscriptTitle":"Effectiveness Of Mindfulness Interventions in Reducing Perceived Stress Among Nurses and Nursing Students: A Systematic Review and Meta-Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-09 11:11:09","doi":"10.21203/rs.3.rs-7328822/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":"1fce20f6-e362-41fc-a041-7837ac2af8af","owner":[],"postedDate":"September 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-09T11:11:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-09 11:11:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7328822","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7328822","identity":"rs-7328822","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}