Healthcare professionals work under sustained cognitive, emotional and physical demands, including high patient loads, emergency decision-making, irregular schedules and night duty. These exposures contribute to occupational stress and may adversely affect well-being and clinical performance. Conventional stress instruments are useful but remain subjective and retrospective. Wearable technologies permit continuous physiological assessment in real-world settings and have therefore attracted increasing interest in healthcare-worker stress research.1–4 Heart rate variability reflects beat-to-beat variation in cardiac intervals and is influenced by autonomic regulation. Time-domain indices such as SDNN and RMSSD and frequency-domain measures such as HF power are commonly used to characterize autonomic modulation. Reduced vagally mediated HRV has been associated with psychological and occupational stress.5–8 Wearable ECG- or PPG-based devices can facilitate ambulatory HRV assessment, although motion artifact and device characteristics require careful interpretation.9,12 The present study aimed to compare baseline and clinical-duty HRV among healthcare professionals and to determine the relationship between wearable-derived HRV parameters and perceived stress measured by PSS-10.

A prospective observational study was conducted among healthcare professionals working in a tertiary care teaching hospital from 1 April 2024 to 31 December 2025. The study included 100 doctors, resident doctors, nurses, interns and other eligible personnel aged 21–60 years who were directly involved in patient care and consented to wearable monitoring. Participants with major arrhythmias, implanted cardiac devices, acute febrile illness, major conditions substantially affecting autonomic function, or inadequate wearable recordings were excluded. Baseline demographic, occupational and lifestyle information was recorded. After 5–10 minutes of seated rest, a baseline heart-rate/HRV recording of approximately five minutes was obtained where technically feasible. Participants then wore a validated ECG- or PPG-capable device during routine clinical duty for approximately 6–12 hours according to duty schedule. Interbeat data were screened for missing beats, ectopy, noise, motion artifact and signal loss. HRV analysis included mean NN interval, SDNN, RMSSD, pNN50, LF power, HF power and LF/HF ratio. RMSSD was treated as a principal vagally mediated HRV parameter.6,7,10 Perceived stress was assessed with PSS-10 (score 0–40): low 0–13, moderate 14–26 and high 27–40. Continuous variables were summarized as mean±SD and categorical variables as frequency and percentage. Baseline and duty values were compared using paired tests as appropriate; stress categories were compared using ANOVA/Kruskal-Wallis testing; and correlations used Pearson or Spearman coefficients according to distribution. A p value <0.05 was considered significant. The source thesis states that Institutional Ethics Committee approval and written informed consent were required; the final manuscript should insert the actual ethics approval number before submission.

Among 100 participants, 58% had moderate perceived stress and 23% had high perceived stress; the mean PSS-10 score was 21.8±6.7. Clinical duty produced a consistent autonomic stress pattern, with increased heart rate and reduced vagally mediated HRV. Table 1. Comparison of baseline and duty-period heart rate and HRV Parameter Baseline/resting During clinical duty Mean change p value Heart rate (beats/min) 74.2 ± 8.6 88.7 ± 10.9 +14.5 <0.001 Mean NN interval (ms) 812.5 ± 96.4 684.7 ± 88.5 −127.8 <0.001 SDNN (ms) 52.8 ± 15.4 38.6 ± 13.2 −14.2 <0.001 RMSSD (ms) 46.7 ± 16.8 31.5 ± 13.7 −15.2 <0.001 pNN50 (%) 21.4 ± 10.5 13.1 ± 8.6 −8.3 <0.001 LF power (ms²) 621 ± 248 748 ± 286 +127 0.002 HF power (ms²) 544 ± 221 361 ± 174 −183 <0.001 LF/HF ratio 1.32 ± 0.61 2.18 ± 0.92 +0.86 <0.001 Paired Student’s t-test/Wilcoxon signed-rank test as appropriate. Heart rate rose by 14.5 beats/min during duty, while SDNN and RMSSD fell by 14.2 ms and 15.2 ms, respectively. HF power decreased and LF/HF ratio increased, indicating marked alteration in autonomic regulation during clinical work. Table 2. HRV parameters according to perceived stress category Parameter Low stress (n=19) Moderate stress (n=58) High stress (n=23) p value Heart rate (beats/min) 80.1 ± 8.4 88.0 ± 9.1 97.2 ± 10.5 <0.001 SDNN (ms) 49.8 ± 12.7 38.9 ± 11.4 28.5 ± 9.8 <0.001 RMSSD (ms) 43.6 ± 12.9 31.7 ± 10.8 21.0 ± 8.7 <0.001 HF power (ms²) 493 ± 181 362 ± 154 248 ± 121 <0.001 LF/HF ratio 1.46 ± 0.58 2.11 ± 0.71 2.94 ± 0.88 <0.001 One-way ANOVA/Kruskal-Wallis test. A graded relationship was observed across PSS-10 categories. Participants with high stress had the highest heart rate and LF/HF ratio and the lowest SDNN, RMSSD and HF power. Table 3. Correlation between PSS-10 score and wearable-derived HRV parameters Variable Correlation coefficient (r) p value Interpretation Mean heart rate +0.52 <0.001 Moderate positive SDNN −0.49 <0.001 Moderate negative RMSSD −0.58 <0.001 Moderate-to-strong negative pNN50 −0.44 <0.001 Moderate negative HF power −0.46 <0.001 Moderate negative LF/HF ratio +0.41 <0.001 Moderate positive RMSSD showed the strongest inverse relationship with PSS-10 (r=−0.58), while mean heart rate showed a moderate positive relationship (r=+0.52).

This study demonstrates concordance between subjective occupational stress and wearable-derived autonomic changes. Clinical duty was associated with higher heart rate and significant reductions in SDNN, RMSSD, pNN50 and HF power. These findings are consistent with systematic evidence showing that stressful clinical contexts are accompanied by reduced HRV and impaired parasympathetic modulation.1,4,5 The graded reduction in RMSSD from low- to high-stress groups is particularly relevant because RMSSD is widely used as a short-term marker of vagally mediated HRV and is relatively practical for ambulatory recordings.6,7 The observed inverse correlation between PSS-10 and RMSSD supports the use of wearable HRV as a physiological complement rather than a replacement for validated psychological assessment. Barac et al. similarly concluded that wearable measures can capture acute stress-related physiology, while cautioning against treating them as standalone diagnostic markers of burnout.3 The increase in LF/HF ratio should be interpreted cautiously. Although it changed consistently with stress severity in this dataset, the ratio does not represent a simple or pure measure of sympathovagal balance.11 In real clinical environments, physical movement, posture, respiration, caffeine, sleep and circadian factors may also influence HRV.5,7 Therefore, contextual and behavioral information remains important when interpreting wearable data. Strengths include real-world monitoring during clinical duties, simultaneous PSS-10 assessment and evaluation of multiple HRV indices. Limitations include the observational single-center design, potential motion artifact, confounding by physical activity and other physiological factors, and the inability of short-term monitoring to establish chronic burnout. Larger longitudinal multicenter studies are needed.

Clinical duty among healthcare professionals was associated with significant autonomic alteration, and increasing perceived stress was accompanied by progressively reduced HRV. RMSSD demonstrated the strongest inverse association with PSS-10 and may be a useful objective marker for short-term occupational stress monitoring. Wearable-derived HRV should be interpreted alongside validated stress scales and relevant clinical, sleep and activity context

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