Preliminary feasibility of mindfulness in motion to improve physiological biomarkers of wellbeing in healthcare providers during dayshift hours
Justin J Merrigan, Maryanna Klatt, Catherine Quatman-Yates, Angela Emerson, Jamie Kronenberg, Morgan Orr, Jacqueline Caputo, Kayla Daniel, Anne-Marie Duchemin, Beth Steinberg, Joshua A Hagen
Discover Public Health May 25, 2025 DOI: 10.1186/s12982-025-00690-8 (opens in new tab) via DOAJ
Summary
AI-generated from the abstractA program called Mindfulness in Motion (MIM) improved physiological markers of stress in healthcare providers. Nineteen participants wore heart monitors before and after eight weekly MIM sessions. After sessions, heart rate variability (SDNN) increased from 38.2 to 47.8 ms, low-frequency power rose from 906 to 2375 ms², and respiration rate slowed from 13.9 to 11.9 breaths per minute. Resilience scores also increased from 27.7 to 31.5 over the eight weeks. Some improvements were seen at the start of later sessions, suggesting cumulative benefits. However, changes in frequency-domain heart rate variability metrics suggested slight physiological arousal immediately after sessions, so results should be interpreted cautiously.
Study at a glance
| Characteristics | Observational cohort Peer reviewed |
|---|---|
| Sample size | 19 |
| Population | Healthcare providers |
| Intervention | Mindfulness in Motion (MIM) |
| Duration | 8-week intervention |
| Topics | Breathwork Meditation |
| Keywords | Parasympathetic Autonomic nervous system Mental health |
| Key finding | Mindfulness in Motion improved heart rate variability, slowed respiration rate, and increased resilience in healthcare providers over eight weekly sessions. |
Abstract
Abstract Mindfulness in Motion (MIM) can improve stress, resiliency, and burnout in healthcare providers but physiological outcomes are unknown. Thus, this study evaluated the effects of MIM on respiration rate (RR), heart rate (HR), and heart rate variability (HRV). Nineteen healthcare providers wore chest strap electrocardiography (ECG) devices and remained still and seated while data were recorded for 5 min prior to (MIM-Start) and after completing (MIM-End) each of the 8 weekly MIM sessions. Metrics included: HR, RR, root-mean square of successive differences between R–R intervals (RMSSD), standard deviation of R–R intervals (SDNN), absolute low frequency power (LF), and absolute high frequency power (HF). At MIM-End, average SDNN (47.8 ± 26.6 vs. 38.2 ± 16.7 ms) and LF Power (2375 ± 3306 vs. 906 ± 1272 ms2) were greater and RR was slower (11.9 ± 3.0 v. 13.9 ± 3.0 bpm) than MIM-Start (p < 0.05). The Connor-Davidson Resilience Scale increased from Week-1 (27.7 ± 4.8) to Week-8 (31.5 ± 4.8, p < 0.001). Compared to Week-1, HR was slower and RMSSD was greater during weeks 2, 3, and 4. There were increases in SDNN and LF, as well as decreases in RR, HF Power, and LF/HF Ratio at MIM-Start for some later weeks compared to MIM-Start at Week-1 (p < 0.05). For healthcare workers in normal work hours, respiration rates were slower and HRV improved but HRV frequency metrics could suggest slight physiological arousal at the end of MIM sessions. These results should be taken with caution, but MIM improved physiological biomarkers of stress at the start of some of the 8 weekly sessions.