Abstract
Background
Nurses experience persistently high levels of occupational stress, which negatively impacts their health and the quality of patient care. Chronic psychological stress is closely linked to physiological dysregulation and cellular aging processes through stress-response pathways. However, limited evidence exists regarding whether stress management interventions targeting these mechanisms can influence cellular aging biomarkers in nurses. This study evaluated the effects of an Integrated Stress Response Reduction Intervention (iSRI) on cellular aging among middle-aged nurses.
Methods
A non-randomized controlled pilot study was conducted with 60 nurses aged 45–60 years recruited from two tertiary hospitals. Participants were allocated to either an intervention group (n = 31) or a control group (n = 29). The 12-week iSRI comprised biofeedback, cognitive–behavioral education, mindfulness, and exercise. Outcomes included perceived stress levels and biochemical markers (serum cortisol, IL-6, and SOD). Cellular aging was assessed via leukocyte telomere length (LTL) and mitochondrial DNA copy number (mtDNAcn) using qPCR.
Results
Following the intervention, the iSRI group showed a significant decrease in perceived stress levels, with a significant group ⋅ time interaction (p =.012). Regarding biochemical markers, serum cortisol showed a significant group ⋅ time interaction (p =.001), although no significant between-group difference was observed post-intervention. SOD levels increased significantly in the intervention group compared to the control group (p =.031), showing a robust interaction effect (p =.001). Regarding cellular aging markers, a significant between-group difference in LTL was observed post-intervention (p =.002), and this difference remained significant after controlling for covariates (p =.047). However, the longitudinal effect for LTL was not statistically significant (p =.263). No significant changes were observed in IL-6 and mtDNAcn.
Conclusions
The 12-week iSRI demonstrated an initial protective effect on preserving LTL, which was associated with reductions in perceived stress and subsequent improvements in cortisol and SOD. These findings suggest that mechanism-based stress management may help support telomere preservation, a hallmark of cellular aging. Given the exploratory nature of this pilot study, further larger-scale randomized controlled trials are warranted to confirm whether such interventions can induce sustained shifts in biological aging trajectories.
Trail registration
The study was registered in CRIS (KCT0011526; registration date: 23 January 2026; retrospectively registered).
Keywords: Biofeedback, Cellular senescence, Telomere, Mitochondria, Nurses, Psychological stress, Non-randomized controlled trial
Background
Nurses constitute a major workforce in healthcare systems worldwide. Although they deliver essential care across diverse clinical settings, nursing work environments are widely recognized as highly stressful and are associated with adverse health outcomes among nurses, ultimately threatening the quality of patient care [1, 2]. International reports consistently identify nursing as one of the most stressful occupations, characterized by high emotional demands and sustained workload pressure [3].
Primary sources of occupational stress for nurses include caring responsibilities for patients and their families, interpersonal conflicts with colleagues, and excessive workload demands [3, 4]. Additionally, organizational and environmental factors—such as long working hours, shift work, insufficient compensation for effort, and frequent exposure to emotionally charged patient interactions—further exacerbate stress in this profession [3]. Prolonged exposure to such stressors has been identified as a major determinant of both physical and psychological health deterioration.
Recent evidence indicates that psychological stress is closely associated with cellular and biological aging processes and age-related diseases [5–7]. In response to stressors, the autonomic nervous system (ANS) and the hypothalamic–pituitary–adrenal (HPA) axis serve as primary physiological pathways that regulate adaptive stress responses. However, chronic or repeated stress exposure can lead to cumulative physiological burden, commonly referred to as allostatic load, thereby increasing vulnerability to disease [8, 9].
Allostatic load represents a state of physiological dysregulation resulting from repeated or prolonged stress-induced “wear and tear” on regulatory systems [8, 10]. Persistent allostatic load is characterized by dysregulation of the ANS and HPA axis, leading to excessive secretion of catecholamines, glucocorticoids, pro-inflammatory cytokines, and reactive oxygen species (ROS), with insufficient termination of these responses [8, 11, 12]. These biological mediators contribute to tissue injury and cellular damage and form the mechanistic basis through which psychological stress influences the development of chronic diseases, including cardiovascular disorders [8].
Telomere length and mitochondrial function have emerged as key biomarkers reflecting cellular aging. Telomeres are protective nucleoprotein structures that maintain chromosomal stability, and their progressive shortening contributes to genomic instability and cellular senescence [13]. Shortened telomere length has been associated with inflammation, oxidative stress, impaired telomerase activity, and repeated cell division [14, 15]. Mitochondrial DNA copy number (mtDNAcn), an index of mitochondrial biogenesis and function, is considered a reliable biomarker of mitochondrial health [16].
The interaction between telomere dynamics and mitochondrial function plays a critical role in cellular aging. Telomere dysfunction impairs mitochondrial biogenesis and energy production and increases ROS generation, thereby accelerating cellular damage [16, 17]. Psychological stress has been shown to influence both telomeres and mitochondria through shared biological pathways involving inflammation and oxidative stress [18].
Based on the evidence, the overall scheme of the mechanism by which psychological stress can contribute to cellular aging is summarized as shown in Fig. 1.
Fig. 1.
Schematic diagram of the mechanism summarizing the association of psychological stress and cellular aging. Prolonged-excessive psychological stress causes allostatic overload, including dysregulation of ANS and HPA axis. Changes in these two main systems contribute to the production of inflammatory cytokines and ROS accumulation. These allostatic overloads resulted in genetic instabilities and subsequently cellular aging. ANS, autonomic nervous system; HPA, hypothalamic pituitary adrenal; ROS, reactive oxygen species
Given these mechanisms, effective stress management interventions that target physiological stress-response pathways are essential for nurses. Numerous non-pharmacological interventions—such as relaxation therapy, mindfulness-based practices, and structured physical activity—aim to restore autonomic balance [19, 20]. However, many of these studies regarding nurses’ stress have relied primarily on self-reported measures of perceived stress, with limited assessment of physiological or cellular aging markers to validate the biological impact of such interventions [21–23].
Heart rate variability biofeedback training has demonstrated efficacy in improving both physiological and psychological outcomes by regulating ANS activity [24]. Also, a meta-analysis reported that cognitive behavioral therapy combined with relaxation therapy was more effective than cognitive behavioral therapy alone or relaxation therapy in reducing occupational stress among teachers [25]. On the basis of this evidence, the integrated stress response reduction intervention (iSRI) was developed to restore autonomic balance and potentially mitigate stress-induced cellular aging.
This study aimed to examine the effects of the 12-week iSRI intervention in middle-aged nurses. To our knowledge, few studies have investigated interventions targeting stress-related mechanisms at the cellular level, as well as associated biochemical markers.
Methods
Study design
This study employed a non-randomized controlled pilot study to examine the psychological and physiological effects of the iSRI among middle-aged nurses. Hospitals served as the unit of randomization to prevent treatment contamination, while data collection occurred at the individual level.
Study setting and participants
Among three tertiary hospitals of similar size and organizational characteristics located in a metropolitan city, two hospitals were randomly selected using a coin-toss method. After obtaining approval from the nursing department directors at both hospitals, a second independent coin toss conducted by a third party not involved in the study was used to allocate one hospital to the intervention group and the other to the control group.
Using a convenience sampling approach, nurses working at the participating hospitals were invited to enroll. Participants were recruited by posting notices and flyers at the hospital cafeteria entrance and the nursing department office. Among those who expressed interest, individuals meeting the eligibility criteria were provided with detailed information regarding the study’s purpose, methods, and duration. Those who voluntarily agreed to participate and signed the informed consent form were ultimately selected as the final subjects.
Inclusion criteria were nurses who (1) were aged 45–60 years, (2) had a Perceived Stress Scale (PSS) score greater than 16—based on evidence indicating a mean PSS score of 16.1 in the Korean general population [26, 27]—and (3) had not participated in any formal stress-relief intervention within the previous three months. Exclusion criteria included nurses (1) with central or peripheral nervous system disorders or neuropsychiatric conditions that could affect ANS, (2) who had been diagnosed with a psychiatric disorder or were receiving related pharmacological treatment, and (3) who were taking sleep medication for a diagnosed sleep disorder.
The age range was restricted because telomere length and mtDNAcn—both key biomarkers of cellular aging—are strongly associated with chronological age. These indicators typically decline with advancing age, and prior studies suggest that the rate of decline becomes more pronounced beginning in midlife [28, 29]. In addition, exposure to stressful life events during childhood has been associated with shorter telomere length; however, evidence suggests that the influence of early-life stress on telomere length is no longer detectable after approximately age 45 [30].
Sample size calculation
Sample size was calculated using the G*Power software version 3.1.9.6 [31]. Based on a two-tailed independent t-test with an effect size of 0.80, a significance level of 0.05, and statistical power of 0.80, a minimum of 26 participants per group was required. Allowing for a potential attrition rate of 15%, a total sample size of at least 60 participants was determined.
Intervention
The iSRI was developed following a comprehensive review of the literature on stress-reduction interventions and biofeedback training. The intervention was designed to mitigate physiological stress responses that underlie stress-related cellular aging mechanisms.
Content validity of the initial program was evaluated by an expert panel consisting of two nursing professors with expertise in autonomic balance–based interventions, two nursing professors specializing in intervention research, and one clinical public health nurse. Based on feedback from the expert panel, the intervention content and delivery methods were refined. The revised program was subsequently pilot-tested with six clinical nurses, leading to further simplification of weekly themes and clarification of intervention procedures.
The iSRI is a multicomponent, group-based intervention comprising cognitive–behavioral education, relaxation therapy, mindfulness practice, and individualized heart rate variability biofeedback training. Excluding one week each for pre- and post-intervention assessments, the intervention was delivered over a 12-week period. The iSRI intervention for the intervention group was conducted at designated locations at the designated hospital during outside working hours. The principal investigator conducted weekly 60-minute group education sessions focusing on stress mechanisms, ANS regulation, lifestyle modification, and coping strategies, including physical activity and relaxation techniques.
To enhance adherence, individual telephone counseling sessions lasting 5–10 min were conducted twice weekly. Participants recorded daily stress-management practices in logs provided at the beginning of the intervention. In the seventh week, participants’ logs were reviewed, and experiences were shared during the group session. A participant demonstrating the greatest improvement in stress management was identified and received a small monetary incentive.
Weekly individualized biofeedback training commenced in the second intervention week. Initial respiration rate was set at 10 breaths per minute, after which individualized respiration rates producing optimal autonomic responses were determined and maintained throughout the intervention period. Each biofeedback session lasted 20 min and was administered once weekly using a biofeedback device (ProComp Infiniti; Thought Technology Ltd., Quebec, Canada) in a controlled environment with minimal visual and auditory stimulation.
Intervention fidelity was ensured through standardized training of research personnel, use of a detailed intervention manual, and monitoring adherence using session checklists. Participant adherence was also evaluated through regular review of daily practice logs.
Control group
Participants in the control group received a single 30-minute group education session on general stress management following completion of baseline assessments. In addition, participants were provided with a wearable activity-tracking device to encourage and monitor daily physical activity.
Data collection procedure
Pre-intervention assessments were initiated after the principal investigator obtained participants’ signed and dated informed consent forms. Upon arrival at the data collection site, participants rested for 30 min before a registered nurse, who was a member of the research team, administered self-report questionnaires and collected venous blood samples for biochemical analyses and DNA extraction.
Post-intervention assessments were conducted 12 weeks after baseline, following the same procedures used for pre-intervention data collection.
Blinding
The principal investigator delivered the intervention but did not participate in data collection. To minimize potential bias that could influence study outcomes, research team members responsible for data collection and outcome assessment were strictly blinded to group allocation.
Measures
Perceived psychological stress
Perceived psychological stress was measured using the Korean version of the PSS, which was originally developed by Cohen et al. [26] and later validated in Korean populations [27]. The PSS consists of 10 items rated on a Likert scale, with total scores ranging from 0 to 40, where higher scores indicate higher levels of perceived stress. In the original development study, Cronbach’s α ranged from 0.84 to 0.86, and a reliability coefficient of 0.81 was reported in a previous study involving Korean adults [32].
Biochemical markers
For biochemical analysis, 5 mL of venous blood was collected from the antecubital vein using a disposable syringe after a minimum of 12 h of fasting. To account for diurnal variation, all samples were collected between 8:00 and 10:00 a.m. Following the standardized laboratory’s protocol, samples were collected in serum-separating tube, inverted eight times immediately after collection, and maintained at room temperature for 30 min to ensure proper clotting. The serum was then separated by centrifugation at 3,000 rpm for 10 min.
For serum cortisol analysis, 1.0 mL of aliquoted serum was stored at 4 °C and analyzed on the day of collection. For IL-6 and SOD, serum samples were stored in separate tubes at -20 °C and analyzed in a single batch after the completion of data collection. During transport from the collection site to the laboratory, samples were placed in specialized temperature-controlled blood transport bags to maintain optimal condition. All biochemical analyses were performed by Seoul Clinical Laboratories (SCL, Yongin, South Korea), a CAP-accredited (College of American Pathologists) and ISO-certified reference laboratory recognized for its stringent quality control standards. Serum cortisol levels were determined using chemiluminescent microparticle immunoassay (CMIA), with a reference range of 3.7–19.4 µg/dL. IL-6 and SOD were measured using enzyme-linked immunosorbent assay (ELISA) with a SpectraMax 190 ELISA Reader (Molecular Devices, China). The reference value for IL-6 was < 8 pg/mL, and SOD was analyzed using a Superoxide Dismutase kit (Cayman, USA).
Cellular aging markers
Leukocyte telomere length (LTL) and mtDNAcn are commonly used as biomarkers for assessing biological or cellular aging. Because white blood cells (leukocytes) are easily obtained from peripheral blood, sufficient amounts of DNA for such measurements can be extracted from them. Thus, genomic DNA was extracted from the buffy coat of 1 mL of whole blood collected on the same day using a DNA isolation kit (QIAamp DNA Blood Midi Kit; Qiagen, Hilden, Germany). The extracted DNA was aliquoted into 1.5-mL microcentrifuge tubes and stored at − 24 °C until analysis.
To measure LTL and mtDNAcn, quantitative real-time polymerase chain reaction (qPCR) was performed using a commercial assay kit (Absolute Human Telomere Length Quantification qPCR Assay Kit; ScienCell Research Laboratories, Carlsbad, CA, USA) as previously described. Each 20-µL reaction contained 2× TaqGreen master mix, telomere, mitochondrial, and single-copy reference primer sets, participant DNA (1 ng/µL), and nuclease-free water; all samples and reference genomic DNA were run in triplicate on 96-well plates using a Thermal Cycler Dice Real-Time System (Takara Bio Inc., Otsu, Japan) with an initial denaturation at 95 °C for 10 min, followed by 32 cycles of 95 °C for 20 s, 52 °C for 20 s, and 75 °C for 45 s. Baseline and 12-week samples from the same participant were assayed on the same plate whenever possible, and each plate included a reference DNA to generate a standard curve and monitor inter-plate variability. The specificity of qPCR amplification was verified by melt-curve analysis. Relative LTL was calculated as the ratio of telomere repeat copy number to single-copy reference (T/S ratio), and mtDNAcn was expressed as the ratio of mitochondrial to nuclear DNA. All measurements, including the use of mean quantification cycle (Cq) values after quality checks, were performed in triplicate as previously described [33]. In the present study, the intra-assay coefficient of variation (CV) was < 2% for all qPCR measurements, including LTL (0.80%) and mtDNAcn (0.50%), indicating high reproducibility of the assays.
Statistical analysis
The data were analyzed using SPSS Statistics version 26 (Armonk, NY: IBM Corp., 2019). Baseline characteristics and homogeneity between the intervention and control groups were assessed using the chi-square test or Fisher’s exact test for categorical variables, and independent sample t-tests or Mann–Whitney U tests for continuous variables, as appropriate. The normality of continuous variables was evaluated using the Shapiro–Wilk test. Independent sample t-tests were used for normally distributed data, while Mann–Whitney U tests were applied to non-normally distributed variables. Due to its skewed distribution, IL-6 levels underwent log-transformation prior to analysis to meet normality assumptions. To examine the intervention effects, a two-step analytical approach was employed. First, within-group pre-post comparisons were performed using paired t-tests, and between-group differences in change scores were compared using independent t-tests or Mann-Whitney U tests. Second, to account for significant baseline imbalances, analysis of covariance (ANCOVA) was performed. In this model, baseline values for each outcome variable were included as covariates to adjust for initial group differences. To control for Type I error across multiple outcomes, Bonferroni corrections were applied where appropriate. Bonferroni-adjusted pairwise comparisons of estimated marginal means were used for between-group comparisons in the ANCOVA analyses, and the resulting adjusted p-values are reported in the text and table. Adjusted means (estimated marginal means), standard errors, and effect sizes (partial eta squared, η²) are reported. Furthermore, a linear mixed-effects model (LMM) was conducted with fixed effects for group, time, and the group × time interaction, including a random intercept for each participant to account for within-subject correlations. The models were additionally adjusted for baseline covariates that differed between groups, including age, duration of clinical experience, alcohol consumption, and current stress status. Statistical significance was defined as p <.05.
Ethical considerations
This study was approved by the Institutional Review Board of K University prior to data collection (IRB No. 40525-202212-BR-085-06). All potential participants received detailed information regarding the study’s purpose, procedures, duration, eligibility criteria, potential benefits, confidentiality measures, and incentives. Written informed consent was obtained from all participants who voluntarily agreed to participate.
Participants were informed that they could withdraw from the study at any time without penalty and that their anonymity would be strictly protected. Access to personal information was restricted to the principal investigator and authorized research personnel only, and all collected data were securely disposed of upon completion of the study.
Results
Participant characteristics and homogeneity testing
A total of 129 nurses were assessed for eligibility, of whom 66 were excluded based on the inclusion and exclusion criteria. During the 12-week intervention period, three participants withdrew from the study (one due to nonattendance and two due to refusal to complete post-intervention assessments). Data from 60 participants were included in the final analysis, with 31 nurses in the intervention group and 29 in the control group (Fig. 2).
Fig. 2.
Flow diagram depicting selection process for study participants
All participants in both the intervention and control groups were women. The mean age of participants was 50.2 years in the intervention group and 53.0 years in the control group. More than half of the participants held a master’s degree or higher. Mean duration of clinical experience was 340.3 months for the intervention group and 375.9 months for the control group. The participants were relatively evenly distributed across inpatient units, outpatient settings, and administrative roles and there were no significant differences between groups. Of the total participants, 32.3% in the intervention group and 31.0% in the control group were engaged in rotating shift work. Statistical testing showed no significant differences between groups regarding general characteristics, except for age (p =.003), duration of clinical experience (p =.007), alcohol consumption (p =.032) and current stress status (p =.015) (Table 1).
Table 1.
Baseline characteristics of participants (N = 60)
| Variable | Category | Intervention (n = 31) |
Control (n = 29) |
z/t/χ2 | p |
|---|---|---|---|---|---|
| Mean (SD) or n (%) | |||||
| Age (year) | 50.23 (3.63) | 53.00 (0.76) | -2.93* | 0.003 | |
| Education | College | 7 (22.6) | 11 (37.9) | 1.68 | 0.195 |
| ≥ Graduate school | 24 (77.4) | 18 (62.1) | |||
| Spouse | No | 5 (16.1) | 2 (6.9) | 1.24 | 0.426† |
| Yes | 26 (83.9) | 27 (93.1) | |||
| Religion | No | 6 (19.4) | 12 (41.4) | 3.46 | 0.063 |
| Yes | 25 (80.6) | 17 (58.6) | |||
| Working department | Ward | 12 (38.7) | 9 (31.0) | 1.62 | 0.445 |
| Operation room/Outpatient | 9 (29.0) | 13 (44.8) | |||
| Administration | 10 (32.3) | 7 (24.2) | |||
| Duration of clinical experience (month) | 340.32 (47.04) | 375.97 (51.98) | -2.78 | 0.007 | |
| Shift work | No | 21 (67.7) | 20 (69.0) | 0.01 | 0.919 |
| Yes | 10 (32.3) | 9 (31.0) | |||
| Alcohol drinking | No | 14 (45.2) | 21 (72.4) | 4.58 | 0.032 |
| Yes | 17 (54.8) | 8 (27.6) | |||
| Chronic disease | No | 17 (54.8) | 18 (62.1) | 0.32 | 0.570 |
| Yes | 14 (45.2) | 11 (37.9) | |||
| Menopause | No | 14 (45.2) | 20 (69.0) | 3.46 | 0.063 |
| Yes | 17 (54.8) | 9 (31.0) | |||
| Current stress status | No | 5 (16.1) | 13 (44.8) | 5.87 | 0.015 |
| Yes | 26 (83.9) | 16 (55.2) | |||
| PSS | 20.48 (3.53) | 18.86 (3.85) | 1.70 | 0.094 | |
|
Serum cortisol (µg/dL) |
7.77 (2.77) | 8.66 (2.83) | -1.22 | 0.226 | |
|
Ln_IL-6 (pg/mL) |
0.22(0.74) | 0.12(0.57) | 0.57 | 0.572 | |
|
SOD (U/mL) |
1.11 (0.36) | 1.32 (0.63) | -2.26* | 0.024 | |
|
LTL (T/S ratio) |
1.78 (0.59) | 2.04 (0.37) | -2.04 | 0.047 | |
| mtDNAcn (copies per diploid cell) | 468.26 (154.57) | 461.10 (143.81) | 0.19 | 0.854 | |
Note. *Mann-Whitney U test; †Fisher exact test
SD = standard deviation; PSS = Perceived Stress Scale; *Mann-Whitney U test; Ln IL-6 = Natural Logarithm Interleukin-6; SOD = Superoxide Dismutase; LTL= Leukocyte Telomere Length; T/S ration = Telomere-to-Single-copy gene ratio; mtDNAcn = Mitochondrial DNA Copy Number
Homogeneity testing of outcome variables at baseline revealed significant between-group differences in SOD levels (p =.024) and LTL (p =.047), whereas no significant differences were observed for other outcome measures (Table 1).
Effects of the intervention on psychological stress and biochemical markers
Table 2 shows changes in PSS scores and biochemical markers from baseline to 12 weeks. Following the 12-week iSRI intervention, PSS levels decreased significantly in the intervention group, whereas no significant change was observed in the control group.
Table 2.
Changes in psychological stress, biochemical markers, cellular aging markers (N = 60)
| Variable | Intervention (n = 31) | Control (n = 29) | Difference between groups z/t (p) |
||||
|---|---|---|---|---|---|---|---|
| Baseline | 12 weeks | t (p) | Baseline | 12 weeks | t (p) | ||
| Mean (SD) | Mean (SD) | ||||||
| PSS | 20.48 (3.53) | 17.06 (4.19) |
3.65 (0.001) |
18.86 (3.85) |
17.97 (3.75) |
1.13 (0.269) |
-2.04 (0.046) |
|
Serum cortisol (µg/dL) |
7.77 (2.77) |
8.55 (2.27) |
-1.73 (0.094) |
8.66 (2.83) |
10.28 (3.75) |
-2.65 (0.013) |
-1.68* (0.093) |
|
Ln_IL-6 (pg/mL) |
0.29 (0.70) |
0.35 (0.61) |
-0.45 (0.656) |
0.12 (0.57) |
0.11 (0.55) |
0.07 (0.944) |
0.41 (0.687) |
|
SOD (U/mL) |
1.06 (0.23) |
1.66 (0.35) |
-10.43 (< 0.001) |
1.21 (0.22) |
1.60 (0.18) |
-8.37 (< 0.001) |
2.96 (0.005) |
|
LTL (T/S ratio) |
1.78 (0.59) |
1.81 (0.39) |
-0.22 (0.831) |
2.04 (0.37) |
1.66 (0.35) |
5.58 (< 0.001) |
3.20 (0.002) |
|
mtDNAcn (copies per diploid cell) |
468.26 (154.57) | 448.68 (89.25) |
0.76 (0.452) |
461.10 (143.81) | 426.97 (103.56) |
0.94 (0.355) |
0.33 (0.745) |
Note. *Mann-Whitney U test
SD = Standard deviation; PSS = Perceived Stress Scale; *Mann-Whitney U test; Ln_IL-6 = Natural Logarithm Interleukin-6; SOD = Superoxide Dismutase; LTL= Leukocyte Telomere Length; T/S ration = Telomere-to-Single copy gene ratio; mtDNAcn = Mitochondrial DNA Copy Number
Regarding biochemical outcomes, serum cortisol levels remained stable in the intervention group, whereas they increased significantly over time in the control group (p =.094 vs. p =.013, respectively). However, no significant between-group differences were observed for serum cortisol levels following the intervention (p =.093). For IL-6 levels, no significant between group differences were identified. Regarding antioxidant status, SOD levels increased in both groups, but the intervention group exhibited a significantly greater increase compared to the control group (p =.005), indicating a favorable effect of the intervention on antioxidant status.
Effects of the intervention on cellular aging markers
With respect to cellular aging indicators, LTL showed a slight, non-significant increase in the intervention group, whereas a significant decrease was observed in the control group (Fig. 3A and B). The between-group difference in LTL change was statistically significant (p =.002).
Fig. 3B.
Between group pre-post changes of leukocyte telomere length (*p<.05)
Fig. 3 A.
Within group pre-post changes of leukocyte telomere length (**p<.01)
In contrast, no significant within-group or between-group differences were identified in mtDNAcn following the intervention period (p =.745).
Between-group differences in outcomes after adjusting for baseline
To account for baseline imbalance, ANCOVA was performed by entering post-intervention values as dependent variables and corresponding baseline values as covariates (Table 3). After adjusting for baseline values, the intervention group demonstrated significantly lower serum cortisol levels (p =.047) and significantly higher SOD levels (p =.031) compared with the control group. Regarding cellular aging markers, the adjusted mean for LTL was significantly higher in the intervention group than in the control group (p =.047). As LTL significantly decreased in the control group while remaining relatively stable in the intervention group, these finding suggest that the iSRI may have contributed to the relative preservation of telomere length. However, no significant between-group differences were observed for PSS, IL-6, or mtDNAcn in the ANCOVA model.
Table 3.
Between group differences in outcomes after adjusting for baseline (N = 60)
| Variable | Intervention (n = 31) | Control (n = 29) | Mean Difference (95% CI) |
F | p-value | Partial η² |
|---|---|---|---|---|---|---|
| Adjusted Mean ± SE |
Adjusted Mean ± SE |
|||||
| PSS | 16.85 ± 0.69 | 18.26 ± 0.74 |
-1.41 (-3.44, 0.62) |
1.93 | 0.170 | 0.033 |
|
Serum cortisol (µg/dL) |
8.71 ± 0.48 | 10.03 ± 0.47 |
-1.33 (-2.63, -0.02) |
4.13 | 0.047 | 0.068 |
|
Ln_IL-6 (pg/mL) |
0.23 ± 0.07 | 0.25 ± 0.08 |
-0.02 (-0.11, 0.07) |
0.23 | 0.635 | 0.004 |
|
SOD (U/mL) |
1.71 ± 0.05 | 1.55 ± 0.05 |
0.16 (0.02, 0.30) |
4.93 | 0.031 | 0.084 |
|
LTL (T/S ratio) |
1.83 ± 0.07 | 1.65 ± 0.06 |
0.18 (0.00, 0.36) |
4.11 | 0.047 | 0.067 |
|
mtDNAcn (copies per diploid cell) |
455.62 ± 16.73 | 419.26 ± 17.39 |
36.36 (-10.84, 83.55) |
2.38 | 0.128 | 0.040 |
Note. SD = Standard deviation; PSS = Perceived Stress Scale; *Mann-Whitney U test; Ln_IL-6 = Natural Logarithm Interleukin-6; SOD = Superoxide Dismutase; LTL= Leukocyte Telomere Length; T/S ration = Telomere-to-Single-copy gene ratio; mtDNAcn = Mitochondrial DNA Copy Number
p-values for pairwise comparisons were Bonferroni-adjusted
Intervention effects over time by Linear mixed-effects models
LMMs were utilized to evaluate longitudinal changes, adjusting for baseline covariates that differed between groups, including age, duration of clinical experience, alcohol consumption, and current stress status (Table 4). The LMM analysis revealed significant group ⋅ time interactions for PSS (p =.012), serum cortisol (p =.001), and SOD (p =.001), indicating that the trajectories of change for these variables differed significantly between the intervention and control groups over the 12-week period (Table 4). In contrast, no significant group ⋅ time interactions were identified for IL-6, LTL, or mtDNAcn, suggesting that the rate of change in these parameters did not differ significantly between the two groups over time.
Table 4.
Intervention effects over time (N = 60)
| Variable | Group × Time (β) |
SE | 95% CI | p-value |
|---|---|---|---|---|
| PSS | 2.52 | 0.99 | 0.55 ~ 4.48 | 0.012 |
|
Serum cortisol (µg/dL) |
-2.51 | 0.76 | -4.01~-1.00 | 0.001 |
|
Ln_IL-6 (pg/mL) |
0.10 | 0.18 | -0.24 ~ 0.45 | 0.554 |
|
SOD (U/mL) |
-1.07 | 0.33 | -1.72~-0.42 | 0.001 |
|
LTL (T/S ratio) |
0.13 | 0.11 | -0.10 ~ 0.35 | 0.263 |
| mtDNAcn (copies per diploid cell) | 41.29 | 32.49 | -23.07 ~ 105.65 | 0.206 |
Note: SD = Standard deviation; PSS = Perceived Stress Scale; *Mann-Whitney U test; Ln_IL-6 = Natural Logarithm Interleukin-6; SOD = Superoxide Dismutase; LTL= Leukocyte Telomere Length; T/S ration = Telomere-to-Single-copy gene ratio; mtDNAcn = Mitochondrial DNA Copy Number
Discussion
This study examined the effects of a 12-week iSRI on psychological stress, physiological responses, and cellular aging biomarkers among middle-aged nurses. The findings indicate that the iSRI was effective in reducing perceived stress levels and improving specific biochemical markers linked to cellular aging. Notably, these effects remained statistically significant even after adjusting for baseline imbalances through ANCOVA. While the group ⋅ time interaction analysis did not reach statistical significance for certain markers, especially LTL, the significant between-group differences observed post-intervention should be interpreted cautiously as exploratory evidence of relative LTL preservation, suggesting an initial protective effect rather than a definitive mitigation of cellular aging.
Following the intervention, perceived stress levels in the intervention group decreased significantly. However, post-intervention stress levels remained higher than those reported in the Korean general population [27]. This aligns with prior research indicating that while stress reduction interventions are effective for nurses, their absolute stress levels often remain elevated due to the persistent demands of the clinical environment [34]. These results suggest that while the iSRI successfully mitigated individual stress responses, the high baseline stress inherent in this professional group necessitates sustained or periodic intervention to maintain long-term psychological and physiological benefits.
Unlike studies reporting significant cortisol reductions following relaxation interventions [35], our first-step analysis showed no significant between-group differences. This discrepancy likely reflects the inherent complexity of cortisol dynamics, which are influenced by sex, stress duration, and circadian rhythms [36, 37]. However, the longitudinal interaction analysis revealed a significant group ⋅ time effect, indicating a meaningful difference in the trajectory of change between the groups. While these preliminary findings suggest a positive intervention effect, the female-only sample and limited sample size necessitate caution in their interpretation.
While IL-6 levels showed no significant changes, SOD levels increased significantly in the intervention group compared with the control group. Psychological stress activates the sympathetic nervous system and the HPA axis, increasing allostatic load and the production of ROS [8, 12, 38], which are key drivers of cellular aging [39]. Notably, the increase in SOD remained significant after adjusting for covariates and was further supported by a robust group ⋅ time interaction. This indicates a clear shift in the trajectory of antioxidant activity. These findings suggest that the iSRI may attenuate oxidative stress by restoring autonomic balance and moderating excessive physiological stress responses.
A primary objective of this study was to determine whether the iSRI could influence cellular aging markers. While LTL significantly decreased in the control group over 12 weeks, it remained stable in the intervention group. This divergence resulted in a significant between-group difference, which was further confirmed after rigorously adjusting for baseline values. These findings align with evidence that stress-reduction interventions can mitigate accelerated telomere attrition [40–43]. Although the lack of a significant group ⋅ time interaction requires a cautious interpretation, this relative stabilization of LTL provides exploratory evidence suggesting that targeting physiological stress pathways could be further investigated as a potential approach for supporting relative telomere preservation. Mechanistically, this effect appears linked more closely to the modulation of oxidative stress pathways [44, 45] than to systemic inflammation, given the lack of significant change in IL-6. Instead, the robust increase in SOD suggests that the iSRI enhances antioxidant capacity, potentially mitigating the ROS that accelerate telomere shortening.
However, it is important to note that while a significant between-group difference in LTL was observed post-intervention after adjustment, this effect did not reach statistical significance in the longitudinal interaction analysis. This discrepancy may be attributed to the intervention duration. Although 8 to 12 weeks of interventions can induce detectable changes in telomere length [46–48], 12 weeks may have been insufficient for these cellular aging mechanisms to fully manifest as stable, longitudinal shifts in telomere dynamics. Thus, the observed LTL differences should be interpreted as preliminary evidence of an ‘initial protective effect’—where the iSRI initiated a defense against telomere attrition—rather than definitive evidence of long-term cellular aging reversal. These findings provide cautious support for the conceptual framework that nursing interventions targeting antioxidant defenses can exert measurable, exploratory protective effects at the cellular level.
Regarding mitochondrial function, no significant changes were observed in mtDNAcn across the statistical models, despite the reciprocal influences between stress, telomeres, and mitochondria [18, 49]. This absence of change may reflect the different biological sensitivities of these biomarkers. Evidence suggests that telomere dynamics may respond more sensitively to psychological shifts, whereas mitochondrial markers often exhibit a slower rate of change or may require more sustained intervention to demonstrate measurable adaptation [17, 50]. This suggests a temporal lag where improvements in telomere maintenance precede mitochondrial adaptation, highlighting the need for longer follow-up periods to capture the full spectrum of cellular recovery.
Strengths and limitations
This study represents a pioneering investigation exploring whether a stress management intervention grounded in physiological stress mechanisms can influence cellular aging biomarkers in nurses. A notable strength of this study is its multidimensional assessment, which integrates objective biochemical (cortisol, IL-6, and SOD) and cellular aging indicators (LTL, mtDNAcn) with subjective stress measures. These preliminary findings offer a mechanistic basis for understanding how targeted nursing interventions may potentially mitigate the biological impact of stress, providing a foundation for future large-scale confirmatory trials.
Nevertheless, methodological limitations warrant careful consideration. First, the use of convenience sampling may introduce selection bias, potentially favoring highly motivated participants. Second, due to the behavioral nature of the intervention and unequal intensity between groups, participant blinding was unfeasible, which may risk performance or expectation bias. Conversely, while the active control condition may have produced conservative effect estimates, the unequal session intensity might still have introduced expectation-related bias. To mitigate these limitations, data collection personnel and outcome assessors were completely blinded. Furthermore, since the most primary outcomes relied on objective physiological measures, the potential impact of both selection and expectation biases is likely minimized. Additionally, while including diverse clinical settings enhanced the intervention’s versatility, excluding those with psychiatric conditions or sleep medications likely introduced a healthy worker bias, meaning the results may not fully represent younger or shift-working nurses who face more severe sleep disturbances.
Third, group allocation was conducted at the hospital level rather than through individual randomization. Because only two institutions participated, intervention effects cannot be fully separated from inherent hospital-level differences, and the shared institutional characteristics may compromise causal inferences. This limited number of clusters also restricts the generalizability of the findings to other healthcare settings. Furthermore, the perfect collinearity between the treatment group and the hospital prevented full control of clustering effects in the LMM analysis. Fourth, the relatively small sample size and limited cluster count may have reduced statistical power, particularly for cellular aging biomarkers with high inter-individual variability like LTL. Given the pilot nature of this study, the sample size might have been insufficient to detect subtle longitudinal interactions. Although Bonferroni corrections were applied to address the risk of Type I error from multiple outcomes, the findings—particularly regarding telomere dynamics—should still be interpreted as exploratory. Fifth, as the iSRI is a multicomponent intervention integrating biofeedback, mindfulness, cognitive-behavioral education, and exercise, we could not isolate the specific effects of each component. While the program was designed to maximize synergistic benefits, it remains unclear which components were most potent. Future studies employing a dismantling design are warranted to identify the most effective components for mitigating cellular aging. Lastly, the 12-week intervention period limits the interpretation of changes in long-term biological markers like LTL. The observed findings reflect short-term physiological responses rather than definitive evidence of sustained effects on the cellular aging. Given these methodological constraints, the findings should be interpreted with caution, and future large-scale randomized controlled trials are warranted to validate these preliminary results.
Implications for future research and practice
Future studies employing longitudinal and randomized controlled trial is warranted to clarify the causal relationship between stress reduction interventions and cellular aging trajectories. Given that significant between-group differences in LTL were observed without a corresponding longitudinal interaction, extending the intervention duration or incorporating booster sessions is essential to achieve stable, long-term cellular shifts beyond initial protective trends. Such extended designs would also help determine if improvements in mitochondrial function (mtDNAcn) can be realized beyond the observed temporal lag. Additionally, examining the effectiveness of the iSRI in younger nurses, shift workers, or individuals with chronic stress-related conditions would further enhance its applicability.
From a practice perspective, the observed benefits of the iSRI suggest that healthcare organizations should consider integrating structured, evidence-based stress management into occupational health strategies. Although biofeedback-based interventions require initial investment in equipment and training, their potential to mitigate the biological impact of stress-related health deterioration may justify institutional support. Flexible, technology-assisted delivery models could further enhance accessibility within demanding clinical environments.
Conclusions
The 12-week iSRI demonstrated an initial protective effect on LTL preservation, which remained significant even after adjusting for baseline imbalance. This effect was associated with a reduction in perceived stress, along with subsequent changes in physiological stress responses and improved serum cortisol and SOD levels. These findings suggest that mechanism-based stress management may help support telomere preservation by restoring biological balance. While the longitudinal interaction was not statistically significant, this study provides exploratory evidence for supporting relative LTL preservation in high-stress professionals. Given the preliminary and hypothesis-generating nature of these findings, further large-scale, multi-center randomized trials are warranted to confirm whether these initial shifts can lead to sustained changes in biological aging trajectories at the individual level.
Acknowledgements
English language editing was assisted by an AI-based tool (ChatGPT, OpenAI). The final manuscript was carefully reviewed and approved by the authors.
Abbreviations
- ANCOVA
Analysis of Covariance
- ANS
Autonomic Nervous System
- HPA
Hypothalamic-Pituitary-Adrenal
- IL-6
Interleukin-6
- iSRI
Integrated Stress Response Reduction Intervention
- LMM
Linear Mixed-effects Model
- LTL
Leukocyte Telomere Length
- mtDNAcn
Mitochondrial DNA Copy Number
- PSS
Perceived Stress Scale
- qPCR
Quantitative real-time polymerase chain reaction
- ROS
Reactive Oxygen Species
- SOD
Superoxide Dismutase
Author contributions
Conceptualization; NK, Data curation; HC, NK, Formal analysis; HC, MS, Investigation; NK, HC, HK Methodology; HC, NK, Project administration; HC, NK, Resources; HK, NK, Supervision; NK, Validation; HK, MS, NK, Visualization; HK, MS, Roles/Writing - original draft; HC, HK, Writing - review & editing: HK, NK.
Funding
This work was supported by the National Research Foundation of Korea (grant number: 2020R1A2C1006590). The funding body had no role in the study design, data collection, analysis, interpretation, manuscript writing, or decision to submit the paper for publication.
Data availability
The datasets generated and analysed during the current study are not publicly available due to the protection of participants’ privacy but are available from the corresponding author on reasonable request.
Declarations
Ethics approval and consent to participate
This study was conducted in accordance with the principles of the Declaration of Helsinki.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and analysed during the current study are not publicly available due to the protection of participants’ privacy but are available from the corresponding author on reasonable request.