Data sources and search

In consultation with a health sciences librarian, the research team developed an a-priori search strategy and scoped the literature across seven databases (PubMed, Embase, Cochrane Library, Web of Science, Scopus, PsychInfo, and CINAHL) from inception through 8/6/2024. In summary, search terms from the title, abstract, or keywords included “Mindfulness” OR up to 50 other synonyms AND “Healthcare Provider” OR any relevant synonyms and health care occupations AND “Physiological” OR any relevant synonymous metrics. An example of search terms used for the PubMed search are included in Table 3, while the complete search terms are available from authors upon request. The initial search yielded 19457 articles, which were uploaded to a systematic review software (Covidence, Melbourne, Australia) to manage and review the articles.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 3. Example of search terms used in PubMed for the current scoping review.

https://doi.org/10.1371/journal.pmen.0000332.t003

Study selection: inclusion criteria

Studies included in this scoping review were limited to English-language only, peer-reviewed original research and were assessing the effects of a mind-body program on physiological measures in healthcare workers. Specifically, we included experimental (randomized controlled trials (RCT), quasi-randomized controlled trials, non-randomized controlled clinical trials), quasi-experimental (within pre/post studies, interrupted time series), and observational (cohort, case control, cross-sectional) original research study designs. Eligible studies included healthcare workers, which were defined as employees or contractors, or clinical students that are currently regularly providing in-person services at a healthcare facility. The focus of the review was on healthcare workers; however, students of healthcare programs were included if they were described as senior or graduate levels with patient-care responsibilities in healthcare facilities. Eligible studies must have implemented some form of structured mind-body program with mindfulness or relaxation techniques that aim to alter healthcare workers’ physiological or perceptual levels of stress and relaxation. The studies generally sought long-term outcomes from mind-body programs (Table 2) but considering the healthcare worker environments we also included short-term outcomes to mind-body sessions. We included variations of the main physiological metrics found in Table 1. If multiple publications appeared to describe the same study design and data, we included the most recent.

Study selection: screening

All personnel were trained and provided with a checklist of eligibility criteria to help ensure consistency amongst reviewers. Additionally, all study titles and abstracts were independently screened by at least two individuals including at least one senior reviewer for full text screening. All conflicts were resolved by discussion until mutual agreement was reached within the group of senior reviewers. Studies that met all inclusion and exclusion criteria following full text screening were included in this analysis.

Data extraction and quality assessment

Two reviewers independently extracted data from each included study. Data were entered into a standardized data extraction form in Microsoft Excel (Microsoft Corp, Redmond, WA). Extracted information included: citation, year, country, study design, healthcare setting, healthcare worker population, sample size, mind-body intervention, comparison or control group, physiological metric methods and analysis, reported results, and limitations. All conflicts were resolved through discussion.

Data synthesis and analysis

Two researchers (JK and JJM) carried out the initial analysis of the extracted data to assess trends in study design, methodological processes, and overall physiological outcomes after a mind-body program. The interventions included herein were categorized based on their attributes as: 1) mindfulness-based interventions or Mindfulness-Based Stress Reduction, 2) yoga or meditation, 3) biofeedback or Attention-Based Training. The protocols were also compared within the themes of having investigated: 1) acute interventions and outcomes, 2) short term interventions and outcomes (≤ 6 weeks), 3) long term interventions and outcomes (~8–12 weeks). Discrepancies in coding were discussed amongst the research team to achieve consensus.

Literature search and selection

The initial search from the databases yielded 19457 articles, 8526 of which were removed as duplications. Of the 10931 articles screened, 165 were included for full text review. Forty-one studies that met the inclusion criteria were included in this scoping review for data extraction (Fig 1).

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Fig 1. PRISMA flow diagram for study selection.

https://doi.org/10.1371/journal.pmen.0000332.g001

Study and sample characteristics

All studies were published after 2011. Most studies included in this review were completed in Asia (n = 17) and North America (n = 14) with others completed in Europe (n = 6), Oceania (n = 2) and South America (n = 2). Twenty-one of the studies included were RCTs, 12 were cohort studies, 2 were cross-sectional studies and 6 were quasi-experimental. Most studies were conducted in hospital settings (n = 27), followed by emergency medicine (n = 4), assisted living/elderly care (n = 3), outpatient care (n = 2), intensive care (n = 2), psychiatric facility (n = 2), oncology (n = 1), and cardiac/respiratory care (n = 1) with some studies being conducted in multiple settings (n = 3) (i.e., public and private practices). Healthcare professions included physicians, surgeons, residents, nurses, respiratory therapists, physical therapists, social workers, mental health providers, nutritionists, dentists, professional caregivers, and healthcare office staff. Studies sample sizes ranged from 12 to 275 participants. A summary of participant characteristics is described in Table 4.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 4. Population characteristics.

https://doi.org/10.1371/journal.pmen.0000332.t004

Mind-body resiliency programs

Programs in this scoping review included yoga (n = 12), mindfulness-based stress reduction programs (n = 8), meditation (n = 6), breath work (n = 4), biofeedback (n = 4), and other mindfulness-based interventions (n = 7). Programs ranged from short-term immediate outcomes (n = 4), 6- or fewer week programs (n = 15), and 8- to 12-week programs (n = 22). See Table 5 for further details regarding each mind-body program type.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 5. Summary of study designs and outcomes for mind-body resiliency programs.

https://doi.org/10.1371/journal.pmen.0000332.t005

Physiological measures and technology

Studies included in this review investigated heart or pulse rate (n = 27), heart rate variability (n = 20), blood pressure (n = 18), respiration (n = 7) and sleep (n = 3). Several approaches were used to measure physiological outcomes with themes of clinical or research grade devices (n = 29), commercially available wearable or contactless technology (n = 10), and practical device free options (n = 8). Blood pressure was measured by a digital or manual sphygmomanometer (blood pressure cuff) (n = 11), which was presumed to also be the case in studies that didn’t specify a method for blood pressure (n = 4). Resting heart rate, also referred to as pulse rate, was also measured with a digital blood pressure cuff (n = 5 + 2 not specified), multi-lead electrocardiography (ECG, n = 5), single-lead or chest strap ECG (n = 4), manual measure (n = 2), photoplethysmography (PPG) wearable technology (n = 4), finger probe PPG (n = 3), and by other non-specified means (n = 4). Heart rate variability or pulse rate variability was measured by multi-lead ECG (n = 6), single-lead or chest strap ECG (n = 5), PPG wearable technology (n = 4), finger probe PPG (n = 4), and Ballistocardiography (n = 1). Specific software cited for HRV analysis included Heart Math System, ProComp Infiniti TM, Kubios, BrainTap HRV, OptimalHRV, EmWare Pro Plus and ARTiiFACT. Respiration rate was primarily collected using self-counting exhalations (n = 3), observer counting inhalations (n = 1), a stopwatch for breath hold time (n = 1), and respiratory inductance plethysmography (n = 2). Sleep was measured using a mixture of devices including polysomnography, electroencephalogram, electrooculogram, ballistocardiography and wearable technology (n = 5), as well as Pittsburgh Sleep Quality Index for subjective measures of sleep (n = 3).

Physiological outcomes

Several studies found significant decreases in SBP and DBP following mind-body programs (n = 7), while a few studies noted no change to BP within the treatment group or between the control group (n = 4). Other studies found a decrease in only DBP [40] or only SBP [47]. Several studies found mind-body practices to lower HR or PR (n = 12), of which two found the decreases in HR to be greater than the control group, while other studies did not find significant HR changes following mind-body programs (n = 4). Several studies found significant differences in SDNN [51,53,56,61,62], RMSSD [51,53,62,63], pNN50 [53,60], LF [53,56,60], HF [39,60], LF/HF [45,53,56,60–62] and general improvements in HRV [1,50,58,63,69]. Others found no change in HRV within treatment groups or between control groups [22,35,54,57]. Specifically, no significant differences were found in SDNN [37,42], RMSSD [37], pNN50 [37], LF [42,45], or HF [42,45]. Studies that assessed respiratory rate found significant decreases in respiratory rate [24,42,46,52,61,65]. Similarly, sleep quality was improved from mind-body programs [39,51], as well as increased total sleep, deep sleep, REM sleep and light sleep durations [51]. However, one study reported no effect of mind-body programs on sleep duration[59]. Only one study reported negative effects of mind-body programs on HRV, however authors cited lack of adjustment for potential influential and impactful covariates for HRV [64]. All study outcomes are summarized in Table 5.

Reported limitations by included studies

The most frequently cited limitation was a small or homogeneous sample size [1,21,34–41,43,45–50,52,53,56–58,61,63,69]. Conversely, sample heterogeneity increased difficulty of interpreting results [22]. Several studies lacked a control group [21,34,36,40,46,47,51,55,61,63,67] and identified differences between groups at baseline [37,44,52]. Research team and treatment group blinding was also cited as a limitation [40,48,52]. Several studies noted that follow up testing would have improved the strength of their findings [22,23,38–41,43,46,50,51,53,56]. Additionally, while some studies noted there was not enough structure to their intervention [42,52,58] or limits in scope [48,49], others reported overly high expectations of their participants during the intervention [35,39]. Logistical limitations included technological difficulties with physiological measurements [22,35,51], institutional support [24], space constraints [45], and disruption from COVID-19 [62,63,69].

Physiological considerations

Most health care workers in this review reported high levels of perceived stress [1,21,22,34,38,39,41,42,44,45,47,48,50,57] or depression [36] prior to beginning their mind-body resiliency program. Prior presence of reported stress may impact baseline physiology and response to mindfulness techniques. For example, rapid respiration and heart rates and low HRV are associated with stress and anxiety [6,11,16,70] but can be improved by mindfulness techniques to levels associated with relaxed mind-body states [71]. Thus, leveraging controlled rhythmic and attentive breathing during mind-body resiliency programs can offset the stress response with more RSA mediated PNS modulation [9,72–74]. Therefore, individuals with worse stress impaired physiological states may be more likely to experience positive detectable improvements in physiological metrics.

There was a great amount of variation in the tools used to assess physiological parameters in the current review, particularly for analyzing inter-beat intervals (R-R intervals) to capture HR and HRV. Several studies utilized multi-lead ECG [35,42,53,54,56], which is a widely accepted gold-standard tool for physiological measurement in research and clinical settings. Research-oriented criterion devices are often more difficult to utilize and wear in non-clinical settings as they include wired electrode sensors which are generally more expensive and burdensome to the participant and researcher [75]. Single-lead [69] chest strap form factor [1,43] ECG devices used in the current review may provide valid recordings with greater ease of use [76,77]. Yet, ECG recordings often require additional software, such as Kubios [40,53,56], ARTiiFACT [37], Elite HRV [57], Biotrace+[61], or Emwave Pro Plus [62], for data analysis and interpretation. Photoplethysmography (PPG) estimates heart rate from contraction-induced fluctuations in blood volume via light reflections in small devices worn on the wrist [37,39,58], finger [22,50,57], or arm [40] in the current review. Concerns with PPG devices often include their validity, but the error from PPG devices compared to ECG may be acceptable when considering their improved practicality and compliance [78].

Ultimately, many methods have been used to capture physiological states during mindfulness interventions which makes it difficult to decipher comparisons across previous findings. Practitioners and researchers must consider the balance of cost, simplicity, and validity of the methods being employed to increase compliance and confidence of acquired physiological recordings. Although multi-lead ECG were used in clinical studies herein, practitioners and researchers may consider the use of validated single-lead ECG devices that improve accessibility and ease of data collection in field settings. Some single-lead ECG, PPG, or self-monitoring methods also permit data collection remotely in real-world environments to potentially capture lasting effects of mind-body programs. Participants may also experience greater self-awareness by receiving biofeedback. Thus, data collection methods, such as single lead ECG, may help inform physiological responses to mind-body programs while also enhancing individuals’ self-awareness and reflective practices. Immediate physiological outcomes to mind-body program sessions

Generally, short-term effects of mind-body program sessions revealed positive impacts on physiological outcomes. Two studies found slower self-counted breath rates after mindfulness sessions compared to the start of each session [24,46,61,65]. These findings are expected for sessions that intentionally control breathing rates [65,79,80], which would theoretically yield lower HR and altered HRV according to the RSA [10]. One-hour of five restorative yoga poses and deep breathing non-significantly slowed HR (73 bpm to 64 bpm) [48], while Shavasana Yoga after a night of sleep deprivation slowed HR and improved HRV (SDNN, RMSSD, LF, HF, LF/HF) [53]. During healthcare simulations, a short mindful moment [1], general stress management training [58] improved HRV (e.g., higher SDNN) but did not affect HR or BP. Conversely, a short mindful activity (PITSTOP) resulted in slower HR but unchanged HRV (SDNN, RMSSD, pNN50) [37]. Yet, participants had improved PRV the nights following Mindfulness in Motion sessions compared to the remaining 6 nights of each week [64]. Others found simultaneous changes to BP, HR, and respiratory rate when nurses completed guided meditations [52]. More experience with virtual reality guided meditations and other forms of meditation was correlated with greater improvements in LF HRV and more relaxed states [50,61,62,68]. Thus, a variety of mind-body techniques seem efficacious for improving physiological states in the short-term, but changes to physiological metrics may not coincide and the current physiological state of participants and their mind-body experience may impact results.

Mindfulness programs of ≤ 6 weeks

Sleep quality generally improved after yoga programs lasting 4–6 weeks [38,41] while control groups noted worsened sleep quality in conjunction with increased stress, depression, and anxiety [38]. However, one study found no effect of a 4 week MBSR program on self-reported sleep [59]. Healthy healthcare workers had no change in BP after completing 6 weeks of one group yoga session and 3–5 home yoga sessions per week compared to the control group [41]. Moderately stressed medical professionals had reduced HR and BP following 4 weeks of Suryanamaskar Yoga (12 Asanas, ~ 30 min, every 5 days), but the changes were no different than aerobic exercise (30 min of treadmill walking at 40–60% of maximal heart rate) [43]. Four weeks of 60-minute integrated yoga sessions 6x per week in caregivers resulted in lower HR and BP, but the post intervention values were not different than the waitlist control group [38]. Unfortunately, the study mentioned did not directly examine an interaction effect of group and time, and the yoga group had an 11% greater decrease in HR compared to the control group [38]. For short yoga interventions, it appears that changes in HR and BP are less likely in healthcare workers currently experiencing little stress [41] compared to moderate or increasing stress [38,43].

Similarly, nurses with hypertension had lower BP and HR after 4 weeks of a neuroscience driven mindfulness training with sound therapy and guided meditations 2-3x per week compared to nurses with normotensive BP and control groups [40]. Heart rate, HRV, and sleep efficiency were also improved more than the control group [40]. Female nurses that completed daily Mahamantra chanting for at least 45 days experienced increased SDNN HRV and decreased LF/HF ratio, LF, and HR more than the control group [56]. Nurses who documented having negative mental health symptoms had slower respiratory rates, but unaltered HRV (SDNN, LF, HF), after completing 6 weeks of biofeedback training compared to controls [42]. Using a stress management tool three times per day for 28 days, which reinforced rhythmic breathing, positive emotions, and biofeedback, did not alter BP or HR in normotensive physicians [44]. Short breathing (21 powerful cycles of breath followed by 30 + second breath holds) and long duration breathing techniques administered morning and evening for 15 days did not alter HR or HRV (RMSSD, HF, LF) [54]. Therefore, short term meditation, biofeedback, or breathwork programs also seem more efficacious in improving physiological outcomes in healthcare workers currently experiencing unmanageable amounts of stress or impaired resting physiology.

Mindfulness programs of 8–12 weeks

Several studies investigated the MBSR intervention, which is a structured psycho-educational intervention that employs mindfulness and meditation practices aimed to improve the mind-body response to stressors [64,65,81–83]. Traditional MBSR protocols require an orientation session, eight weekly 2.5- to 3-hour classes, and a 7- to 8-hour retreat between week 6 and 7. Two studies followed typical MBSR protocols, including 45-minute daily practices, then provided a 10-week maintenance protocol which included one 2.5-hour session every month. Physicians in both studies had decreased HR and BP after the 8-week MBSR which was maintained throughout the 10-month maintenance period and associated with states of perceived relaxation [21,34]. Interestingly, a greater number of recorded hours of home practice was related with greater reductions in BP [21]. When comparing an 8-week Kripalu Yoga with MBSR-based psychoeducation program to cognitive behavioral stress management, the protocols were equally as effective at reducing HR and BP [55]. Therefore, these long-term stress management programs including mindfulness training seem to positively impact BP and HR.

Conversely, PRV did not change and was not correlated with reductions in perceived stress after Newborn Nursery and Neonatal Intensive Care Unit (NICU) healthcare workers completed MBSR [22]. These results may have been due to using the Heart Math finger probe system, the length of measurement (5-minute measure after a 5-minute rest), or a relative insensitivity of PRV for detecting biologic implications for reduced stress [22]. Similarly, the Mindfulness in Motion intervention has shown reductions in self-reported respiration rates [65] but no change in nocturnal resting PRV via the OURA ring throughout the 8 week program [64]. Yet, variations of 8-week web- or application-based stress management interventions with and without biofeedback were not effective at improving HRV (SDNN, RMSSD, LF/HF ratio) measured by clinical ECG [35] or OptimalHRV [63]. The lack of findings in the aforementioned study could have been impacted by the 74% dropout rate due to COVID-19 and technological difficulties [35] as well as lack of adjustment for factors that would negatively impact HRV [64]. Blood pressure, HR, and HRV (RMSSD) remained unchanged following Yoga interventions or compared to control groups [57,66], while other structured Yoga programs demonstrated significant improvement to BP and HRV metrics compared to control conditions [69]. Thus, there seems to be a lack of evidence that HRV can improve or be capable of detecting physiological improvements from 8-week mindfulness programs.

An 8-week yogic meditation program, including one weekly class and one at-home practice, resulted in improved sleep quality, as well as decreased HR compared to the control group [23]. Only SBP was improved more than the control group after 12 weeks of two structured yoga (Asana, Pranayama, relaxation techniques) sessions per week [47]. Implementing short (20 min) daily progressive muscle relaxation techniques (Jacobson’s protocol) decreased HR and BP and increased breath hold times after 3 months [36]. One hour weekly yoga sessions (warm up, breathing, meditation, stretching) for 12 weeks did not alter LF or HF HRV but did reduce the LF/HF ratio compared to the control group [45]. However, other 1-hour weekly yoga sessions (5 min Meditation, 40 min Yoga/ Breath, 15 min Mindfulness) did not alter HR after 12 weeks despite HR being lower after each session [49]. Interestingly, the participants had an affinity for yoga and mindfulness, which may have impacted their results [49]. A 2 month chair yoga program did have positive effects on heart rate (decrease), HRV (increased RR interval, increased SDNN, increased PNN50, decreased LF, increased HF, decreased LF/HF ratio) compared to individuals who did not complete chair yoga [60]. Lastly, completing 4-hour sessions of attention-based training (focused attention to transcendental or other mantra-based meditations) 4 times and 20 minute practices (attention to Maranatha phrases) twice per day over 7 weeks decreased HR and increased HRV and sleep durations [39].

Overall, mind-body programs lasting 8–12 weeks may require large variations in commitments. According to the studies in the current scoping review, all intervention types included herein seem efficacious for improving physiological parameters despite difficulty in extrapolating precise comparisons due to variations in programs and outcome methodologies. This is especially problematic for HRV measures, which generally remained unchanged from the 8- to 12-week mind-body programs. These findings bring to question whether HRV parameters are capable of detecting physiological changes from mind-body programs, but also whether the methods being used thus far are appropriate. Since HRV is susceptive to many external and internal factors, more frequent testing throughout the mind-body program (such as seen in [39]) may be more appropriate than simple pre- and post-program timepoints. Considering the busy schedules of healthcare professionals and the challenges of coordinating a mind-body program, the time commitments of mind-body programs must be thought about carefully. To induce physiological changes, there may be a necessary requirement of total density or daily time allotment for mind-body practices throughout the intervention length.