Skip to main content
NCBI home page
Health Science Reports logoLink to Health Science Reports
. 2025 Sep 14;8(9):e71226. doi: 10.1002/hsr2.71226

Recharging Healthcare Professionals: A Randomized Controlled Trial on the Impact of Automated Massage Chairs on Depression, Anxiety, Stress, Musculoskeletal Pain, and Biochemical Markers

Marilyn Li Yin Ong 1, Adam Abdul Malik 1, Norhasmah Mohd Zain 2, Nurulilyana Sansuddin 3, Norazliah Hj Samsudin 2, Rosminah Mohamed 4, Idris Long 5, Nor Haslina Mohd 3, Nurul Asma Abdullah 4, Hairul Anuar Hashim 1,6,✉
PMCID: PMC12434317  PMID: 40959182

ABSTRACT

Background/Objectives

Massage therapy has been shown to alleviate stress and improve well‐being, making it a promising intervention for healthcare professionals who often face high levels of job‐related stress. This study investigated the effects of automated massage chair therapy on negative emotional states, musculoskeletal pain, and biochemical markers in healthcare professionals.

Methods

Twenty‐four healthcare professionals with moderate levels of depression, anxiety, and stress were randomly assigned to either an automated massage chair group or a progressive muscle relaxation (PMR) group. Each group received 15‐min sessions, three times per week for 4 weeks, totaling 12 sessions. The depression, anxiety, and stress scale‐21 items (DASS‐21), the visual analog scale (VAS) for pain, and blood biomarkers [brain‐derived neurotrophic factor (BDNF), cortisol, beta‐endorphin, superoxide dismutase 1 (SOD1), endothelial nitric oxide synthase (eNOS), and myeloperoxidase (MPO)] were measured at baseline, after six sessions, and after 12 sessions.

Results

The massage chair group showed significant reductions in depression scores at 6 sessions (Z = −2.043, p = 0.041), and in stress scores at 6 (Z = −2.499, p = 0.012) and 12 sessions (Z = −2.326, p = 0.020). Calf pain scores improved significantly at 12 sessions (right calf: Z = −2.677, p = 0.007; left calf: Z = −2.253, p = 0.024), and lower back pain reduced at both 6 (Z = −2.275, p = 0.023) and 12 sessions (Z = −2.517, p = 0.012). MPO levels were significantly reduced in the massage group post‐intervention (F [1, 22] = 7.956, p = 0.01; t [11] = 2.959, p = 0.013), indicating anti‐inflammatory effects. A significant time effect was also observed for beta‐endorphin (F [1, 22] = 6.632, p = 0.017), with reduced levels after massage (t [11] = 3.321, p = 0.007). No significant changes were found in anxiety, blood pressure, heart rate, BDNF, cortisol, SOD1, or eNOS.

Conclusions

Automated massage chair therapy significantly alleviated depression, stress, and musculoskeletal pain, particularly in the calves and lower back, with modest biochemical changes such as reduced MPO and beta‐endorphin levels. These findings support massage chair use as a convenient, noncontact strategy to enhance psychological and physical well‐being in healthcare professionals.

Keywords: automated massage chair, BDNF, beta‐endorphin, cortisol, emotional distress, endothelial nitric oxide synthase, musculoskeletal pain, myeloperoxidase, superoxide dismutase

1. Introduction

Occupational stress among healthcare professionals has become a significant concern over the past decade, with profound implications for both physical and emotional health. Defined by the National Institute for Occupational Safety and Health [1], occupational stress occurs when job demands exceed the individual's capabilities, resources, or needs. Healthcare professionals, particularly physicians and nurses, are particularly vulnerable to stress due to factors such as inadequate staffing, long working hours, high public expectations, and exposure to infectious diseases and hazardous substances [2, 3]. This stress has been linked to a range of health problems, including cardiovascular disease, psychiatric disorders, psychosomatic symptoms, and, in extreme cases, suicide [4, 5, 6, 7, 8, 9]. Furthermore, the mental health of healthcare professionals remains a major post‐pandemic concern, with continued issues of burnout and stress [10, 11].

In Malaysia, the prevalence of occupational stress varies among healthcare occupations. Yahaya et al. [12] reported a 7.9% prevalence of stress among emergency department medical officers, while Rusli et al. [13] found a 24.6% prevalence among nurses. Lua and Imilia [14] identified radiographers as the most stressed group among support staff, followed by nurses and medical laboratory technologists. Occupational stress in the medical community is associated with numerous health issues, including burnout, sleep disturbances, anxiety, and an overall lack of well‐being [15, 16, 17].

Several interventions have been proposed to alleviate work‐related stress in healthcare workers, including physical activity [18, 19], relaxation technique [20, 21], massage therapy [22, 23, 24], and the use of automated massage chair [23, 25, 26]. Massage therapy, which stimulates sensory nerves in the skin, has been shown to reduce anxiety and depression [22, 24]. However, traditional massages require scheduling with a qualified therapist, and some individuals may not be comfortable with human contact. An alternative, noncontact therapy known as progressive muscle relaxation (PMR), has also demonstrated effectiveness in reducing stress by alternating muscle tension and relaxation, though it requires proper guidance and correct execution to be effective [27].

Automated massage chairs, which provide standardized, noncontact stimulation, offer a promising solution for stress reduction. These devices have been shown to alleviate musculoskeletal tension, improve blood circulation, and reduce stress hormones [26]. Automated back massages are particularly beneficial for individuals who prefer to avoid human touch. As these chairs become more sophisticated and accessible, they offer a convenient, contact‐free alternative to traditional massage therapy. However, empirical evidence on their efficacy remains limited, and the lack of standardization in intensity and modality may lead to inconsistent health outcomes [28].

Chronic occupational stress is known to affect multiple physiological systems, including neuroendocrine, immune, and vascular pathways [29]. To capture these multidimensional effects, selected serum biomarkers were included in this study as objective indicators of stress‐related biological alterations. Specifically, brain‐derived neurotrophic factors (BDNF) play a crucial role in neuronal plasticity, resilience, and mood regulation, and their levels are often diminished in individuals under chronic psychological stress or depressive states [30]. Cortisol, a key glucocorticoid hormone released via activation of the hypothalamic–pituitary–adrenal (HPA) axis, serves as a central marker of both acute and chronic stress responses [31]. Beta‐endorphins, as endogenous opioids, are involved in the modulation of pain and mood, and are typically elevated during stress‐induced analgesia [32]. To assess oxidative stress and vascular function, both of which are disrupted under chronic stress exposure, this study also measured superoxide dismutase 1 (SOD1), a key antioxidant enzyme [33]; endothelial nitric oxide synthase (eNOS), which regulates vascular tone and endothelial health [34]; and myeloperoxidase (MPO), a pro‐oxidant enzyme linked to inflammatory activation [35]. Together, these biomarkers provide a comprehensive physiological profile relevant to the emotional and somatic effects of occupational stress, as well as the potential therapeutic mechanisms of massage‐based interventions.

Given the increasing need for evidence‐based interventions to prevent and manage stress‐related health issues in healthcare professionals, it is essential to explore the effects of automated massage chairs on depression, anxiety, stress, musculoskeletal pain and biochemical markers. Therefore, the aim of this study was to assess the efficacy of automated massage chair therapy on psychological distress (depression, anxiety, and stress), musculoskeletal pain, and selected biochemical markers among healthcare professionals. It is hypothesized that massage chair therapy would lead to greater improvements in psychological distress, musculoskeletal pain, and selected biochemical markers compared to PMR.

2. Materials and Methods

2.1. Participants

The study involved 24 healthcare professionals (11 males, 13 females; mean age of 37.7 ± 8.1 years) recruited from Hospital Universiti Sains Malaysia (HUSM), Kubang Kerian, Kelantan, a tertiary teaching hospital affiliated with Universiti Sains Malaysia. All participants were full‐time staff, including nurses, assistant medical officers, medical laboratory technologists, and radiographers. Recruitment was conducted through internal announcements and emails distributed via the hospital's internal communication system. Individuals who expressed interest were selected based on their highest scores from the self‐reported Depression, Anxiety, and Stress Scale‐21 items (DASS‐21) during the initial screening assessment [36]. Before the study, participants were briefed on the research procedures, and informed written consent was obtained if they agree to participate. The consent forms and study procedures were approved by the Human Research Ethics Committee of Universiti Sains Malaysia (USM/JEPeM/19120958). A familiarization session was conducted during Visit 1 to ensure participants were comfortable with the study setup and protocol. This study was conducted at the Exercise and Sports Science laboratory, School of Health Sciences, Health Campus, Kubang Kerian, Kelantan, Malaysia.

2.2. Study Design

In Visit 2, participants were randomly assigned to either the massage chair or PMR group using a computer‐generated random sequence with a 1:1 allocation ratio. The randomization sequence was stored in a secure, password‐protected database accessible only to an independent staff not involved in enrollment or assessment. The sample size was determined a priori using G*Power software with the following parameters: 80% power, 95% confidence interval, 0.05 alpha level, an effect size (ES) of 0.25, and an estimated 20% dropout rate. Based on these parameters and the previous method used [37], a total of 24 participants were required, with 12 participants per group. The aim was to evaluate the efficacy of massage chair therapy compared to PMR in improving psychological, musculoskeletal, and biochemical health parameters in healthcare professionals. It is hypothesized that massage chair therapy would lead to greater improvements across these outcomes compared to PMR.

Both groups participated in their respective interventions three times per week for 4 weeks, with a total of 12 sessions. Body weight, body height, physio‐psychological measures such as systolic blood pressure (SBP), diastolic blood pressures (DBP), average heart rate (HR), psychological distress, musculoskeletal pain and biochemical markers were assessed at baseline (0‐), 6‐, and 12‐sessions post‐intervention by a trained researcher, with assistance from a medical laboratory technologist from sports science department.

2.3. Massage Chair Intervention

The automated massage chair (Master's Choice, Ogawa Masters Drive AI 2.0) was used according to the manufacturer's recommendation, with a 15‐min duration per session to promote relaxation. Sessions occurred three times per week for 4 weeks. The massage chair was controlled via a Bluetooth‐enabled app (Ogawa Wellness, Ogawa International Holdings Limited). Participants wore normal work clothing, with shoes and personal items removed. The room was set to temperature of 20°C with low lighting ambience to create a relaxing environment.

2.4. Progressive Muscle Relaxation Intervention

Participants practiced PMR while sitting in a semi‐reclining position, with eyes closed and arms and legs placed comfortably on the massage chair's leg and footrest. The massage chair program was not activated during this intervention. Participants assigned to the PMR group underwent 15‐min sessions, three times per week for 4 weeks (totaling 12 sessions). This duration was based on previous studies indicating that a minimum of five sessions is sufficient to reduce somatic and psychological stress symptoms [36, 38]. The PMR protocol was standardized using an audio‐guided recording with consistent narration and instrumental music played at a low volume.

2.5. Psychological Distress Assessments

The Malay version of the Depression, Anxiety, and Stress Scale‐21 items (DASS‐21) scale was used to determine the psychological distress [39]. Each item was rated on a 4‐point scale, from 0 (not at all) to 3 (most of the time). The DASS‐21 is a validated self‐report instrument comprising three subscales (depression, anxiety, and stress) each consisting of 7 items. Participants rated the extent to which they experienced each symptom over the past week on a 4‐point Likert scale ranging from 0 (“Did not apply to me at all”) to 3 (“Applied to me very much or most of the time”). Scores for each subscale are summed and then multiplied by two to match the original 42‐item DASS scale, producing final scores ranging from 0 to 42 for each subscale. Higher scores indicate greater levels of distress. The Malay version of the DASS‐21 has demonstrated good internal consistency, with Cronbach's alpha coefficients reported as 0.84 for depression, 0.74 for anxiety, and 0.79 for stress [40]. It has also shown satisfactory construct validity and is widely used in clinical and nonclinical Malaysian populations.

2.6. Musculoskeletal Complaints

A body chart was used to assess musculoskeletal complaints. Participants marked areas of pain or discomfort experienced in the last 12 months, targeting the area of the neck, back and calves. Pain perception was measured using the VAS, with a range from 0 (no pain) to 10 (worst possible pain) [41, 42].

2.7. Blood Sampling and Biochemical Marker Analysis

Blood samples were collected via venipuncture into 5‐mL tubes, processed immediately, and stored at −20°C until analysis. Serum was obtained through centrifugation (4°C, 10 min, 1500g) and analyzed for biomarkers using enzyme‐linked immunosorbent assay (ELISA) (Raybiotech, Norcross, GA, USA). Serum biomarkers analyzed included BDNF, Superoxide Dismutase 1 (SOD1), Endothelial Nitric Oxide Synthase (eNOS), Beta‐Endorphin, Cortisol, and MPO. To preserve sample integrity, all samples were aliquoted immediately after centrifugation to avoid repeated freeze/thaw cycles. Each aliquot was thawed only once before analysis. Samples were analyzed in duplicate using a microplate reader (Tecan Infinite 200 PRO, Switzerland), with absorbance read at 450 nm. Results with a coefficient of variation (CV) greater than 15% between duplicates were excluded from the analysis.

2.8. Statistical Analysis

All data analyzes were conducted using IBM SPSS Statistics version 27. Descriptive statistics are presented as mean ± standard deviation (SD). Before inferential analysis, normality of all data was assessed using the Shapiro‐Wilk test.

For normally distributed variables (BP, DBP, HR, BDNF, cortisol, beta‐endorphin, SOD1, eNOS, and MPO), General Linear Model (GLM) repeated measures ANOVA was applied to examine within‐subject effects of TIME (baseline, 6 sessions, 12 sessions), between‐subject effects of GROUP (massage chair vs. PMR), and TIME × GROUP interaction effects. Where assumptions of sphericity were violated, Greenhouse‐Geisser correction was applied.

For non‐normally distributed variables [DASS‐21 subscale scores (depression, anxiety, stress) and VAS pain scores for neck, back, and calves], non‐parametric methods were used. The Friedman test was employed to assess differences across timepoints (baseline, 6 sessions, 12 sessions), while the Wilcoxon Signed‐Rank Test was used for pairwise comparisons within groups. Statistical significance was set at a two‐tailed alpha of 0.05.

3. Results

3.1. BP and HR

Resting systolic (SBP) and diastolic blood pressures (DBP) measured at all timepoints were not significantly different between massage chair and PMR [SBP: F(3, 66) = 0.912, p = 0.44; DBP: F(3, 66) = 0.987, p = 0.404]. Participants recruited were normotensive during both massage chair and PMR interventions, showing unchanged responses across pre, 0‐, 6‐ and 12‐ sessions. SBP and DBP were not different across time points for massage chair intervention (no main TIME effect [SBP: F[3, 66] = 1.387, p = 0.255; DBP: F[3, 66] = 1.207, p = 0.314] [See Figure 1A,B]).

Figure 1.

Figure 1

Open in a new tab

Systolic (A) and diastolic (B) resting blood pressures and average heart rate (C) measured at pre, 0‐, 6‐, 12‐ sessions in participants in both massage chair and progressive muscle relaxation (PMR) interventions. Data in mean ± standard deviation.

Average resting heart rates (HR) were not significantly different between massage chair and PMR interventions across 0‐, 6‐, and 12‐sessions (F[2, 44] = 1.388, p = 0.26) (See Figure 2). Resting HR were normal in all participants during both intervention sessions. Within‐subject analysis showed massage chair intervention showed a main TIME effect (F[2, 44] = 3.459, p = 0.04)at 6‐ and 12‐sessions. (See Figure 1C).

Figure 2.

Figure 2

Open in a new tab

Depression (A), anxiety (B) and stress (C) scores measured at 0‐, 6‐, 12‐ sessions in participants for both massage chair and progressive muscle relaxation (PMR) interventions. *Significantly different from 0‐session for massage chair intervention.

3.2. DASS‐21

3.2.1. Depression, Anxiety and Stress Scores

There was significant difference in depression scores [X 2(2, N = 24) = 16.037, p = 0.0001] between massage chair and PMR interventions. For massage intervention, depression scores were lower at 6‐sessions compared to 0‐session (Z = −2.043, p = 0.041) (see Figure 2A).

Anxiety scores were not significantly different [X 2(2, N = 24) = 4.083, p = 0.130] between massage chair and PMR interventions. For massage intervention, anxiety scores were not significantly different at 6‐ (Z = −0.997, p = 0.319) and 12‐session (Z = −1.476, p = 0.140) compared to 0‐session (see Figure 2B).

Stress scores were not significantly different [X 2(2, N = 24) = 12.487, p = 0.002] between massage chair and PMR interventions. For massage intervention, stress scores were significantly different at 6‐ (Z = −2.499, p= 0.012) and 12‐sessions (Z = −2.326, p = 0.020) compared to 0‐session (see Figure 2C).

3.3. Musculoskeletal Pain Scores

3.3.1. Neck Pain

There was no significant difference in neck pain score [X 2(2, N = 24) = 14.852, p = 0.001] between massage chair and PMR interventions. Wilcoxon Signed Ranks Test showed that neck pain was significantly lower in massage chair intervention at 6‐ (Z = −2.222, p = 0.026) and 12‐sessions (Z = −2.958, p= 0.003) compared to 0‐session, respectively (see Figure 3).

Figure 3.

Figure 3

Open in a new tab

Neck pain scores measured at 0‐, 6‐, 12‐ sessions in participants for massage chair and progressive muscle relaxation (PMR) intervention group. *Significantly different from 0‐session for massage chair intervention.

3.3.2. Upper and Lower Back Pain

There was no significant difference in upper back pain score [X 2(2, N = 24) = 5.429, p = 0.066] between massage chair and PMR interventions. However, lower back pain score was significantly different [X 2(2, N = 24) = 10.586, p = 0.005] between massage chair and PMR interventions. Wilcoxon Signed Ranks Test showed that lower body pain score was lower at 6‐ (Z = −2.275, p = 0.023) and 12‐sessions (Z = −2.517, p = 0.012) compared to 0‐week for massage chair intervention (See Figure 4).

Figure 4.

Figure 4

Open in a new tab

Upper (A) and lower (B) back pain scores measured at 0‐, 6‐, 12‐ sessions in participants in both massage chair and progressive muscle relaxation (PMR) interventions. *Significantly different from 0‐session for massage chair intervention.

3.3.3. Right and Left Calf Pain

There was significant difference in right calf pain score [X 2(2, N = 24) = 10.571, p = 0.005] between massage chair and PMR interventions. For massage intervention, right calf pain scores were lower at 12‐sessions compared to 0‐session (Z = −2.677, p = 0.007) and at 12‐sessions compared to 6‐sessions (Z = −1.973, p = 0.049) (see Figure 5A).

Figure 5.

Figure 5

Open in a new tab

Right (A) and left (B) calves scores measured at 0‐, 6‐, 12‐ sessions in participants for both massage chair and progressive muscle relaxation (PMR) interventions. *Significantly different from 0‐session for massage chair intervention; + Significantly different from 6‐session for massage chair intervention.

However, left calf score was not significantly different [X 2(2, N = 24) = 5.059, p = 0.08] between massage chair and PMR interventions. However, Wilcoxon Signed Ranks Test showed that left calf pain score was lower at 12‐sessions (Z = −2.253, p = 0.024) compared to 0‐session for massage chair intervention (see Figure 5B).

3.4. Blood Biomarkers

3.4.1. BDNF, Cortisol, and Beta‐Endorphin

There was no significant difference in BDNF (F[1, 22] = 0.008, p = 0.928) between massage chair and PMR interventions. The BDNF concentrations were not significantly different across time points for both massage chair and PMR interventions (Main TIME effect: F[1, 22] = 1.764, p = 0.198) (See Figure 6A). Similarly, cortisol concentrations were not significantly different (F[1, 20] = 0.188, p = 0.669] between massage chair and PMR interventions. The cortisol concentrations were not significantly different across time points for both massage chair and PMR interventions (Main TIME effect: F[1, 20] = 1.556, p = 0.072) (See Figure 6B). There was no significant difference in beta‐endorphins (F[1, 22] = 1.377, p = 0.253) between massage chair and PMR interventions. However, there was a main TIME effect (F[1, 22] = 6.632, p = 0.017), with the beta‐endorphins concentrations significantly reduced at post massage chair intervention (t[11] = 3.321, p = 0.007] (See Figure 6C).

Figure 6.

Figure 6

Open in a new tab

Concentration of serum brain‐derived neurotrophic factor (BDNF) (A), cortisol (B) and beta‐endorphin (C) measured at 0‐, 6, 12‐ sessions in participants for both massage chair and progressive muscle relaxation (PMR) interventions. Data in mean ± SD. *Significantly different from pre for massage chair intervention.

3.4.2. SOD1, eNOS, and MPO

There was no significant difference in SOD1 (F[1, 22] = 0.942, p = 0.342) between massage chair and PMR interventions. The SOD1 concentrations were not significantly different across time points for both massage chair and PMR interventions (Main TIME effect: F[1, 22] = 1.018, p = 0.324) (See Figure 7A).

Figure 7.

Figure 7

Open in a new tab

Serum concentrations of superoxide dismutase 1 (SOD1) (A), endothelial nitric oxide synthase (eNOS) (B) and myeloperoxidase (MPO) (C) measured at 0‐, 6‐, 12‐ sessions in participants for both massage chair and progressive muscle relaxation (PMR) interventions. Data in mean ± standard deviation. *Significantly different between massage chair and PMR interventions.

Similarly, there was no significant difference in eNOS (F[1, 22] = 0.550, p = 0.466) between massage chair and PMR interventions. The eNOS concentrations were not significantly different at post intervention for both massage chair and PMR (Main TIME effect: F[1, 22] = 1.108, p = 0.304) (See Figure 7B).

There was a significant difference in MPO concentrations (F[1, 22] = 7.956, p = 0.01) between massage chair and PMR interventions. There was a main TIME effect (F[1, 22] = 4.548, p = 0.044], with MPO concentrations significantly reduced at post massage chair intervention (t[11] = 2.959, p= 0.013) (See Figure 7C).

4. Discussion

The findings from this study offer important insights into the effectiveness of automated massage chair therapy, particularly in comparison to PMR for managing musculoskeletal pain, psychological distress, and inflammatory biochemical markers. The massage chair intervention was found to significantly reduce musculoskeletal pain in the neck, lower back, and calf regions, demonstrating its potential as an effective nonpharmacological treatment for pain management. These results are aligned with recent research indicating that massage chair therapy can provide substantial relief for musculoskeletal pain [43, 44]. Our study found that massage chair therapy significantly alleviated pain in the neck, lower back, and calves after 6 and 12 sessions. Massage devices, including automated systems, have been shown to have similar efficacy to manual massage, with advantages such as convenience and accessibility [44]. The improvement in lower body pain, particularly in the calves, highlights the potential of massage chair therapy for addressing localized discomfort. Interestingly, no significant differences were found in upper back pain reduction between massage chair and PMR interventions, suggesting that the therapeutic effects of automated massage may be more effective in certain anatomical regions. The efficacy of massage may vary by muscle group, with certain areas benefiting more from massage due to work‐related muscle discomfort. One such example of a healthcare job is the cardiac sonographer, who showed improved musculoskeletal conditions following massage chair therapy [45].

The massage chair intervention was also effective in reducing both stress and depression scores, reflecting its impact on psychological well‐being. These findings corroborate recent studies showing that massage therapy can lead to significant reductions in stress and depressive symptoms by promoting relaxation and modulating the autonomic nervous system [46, 47]. Moreover, the observed improvement in stress scores after both 6 and 12 sessions emphasizes the potential of massage chair therapy in stress and fatigue management [48], especially in the healthcare settings where managing stress is critical. Frequent and long‐term use of a massage chair can significantly reduce stress in healthcare professionals experiencing high levels of work‐related stress [25]. In Malaysia, the healthcare industries have been reported to have high prevalence of occupational stress [12, 14, 49, 50].

The anxiety scores did not show significant improvement, which may suggest that while massage can alleviate stress and depression levels, its effects on anxiety may be less pronounced. Massage's ability to reduce anxiety may depend on factors such as the intensity of the massage and the individual's baseline anxiety levels [51, 52]. For example, Swedish massage has been found to reduce anxiety of generalized anxiety disorder compared to light massage [53] while effleurage type of massage reduces anxiety in multiple sclerosis patients who experienced much more pronounced anxiety [54]. Thus, while massage therapy shows promise in addressing stress and depression, further exploration is needed to understand its effects on anxiety more thoroughly.

In terms of physiological parameters, the massage chair intervention did not produce significant changes in BP or HR. These results are consistent with studies suggesting that massage therapy has minimal effects on cardiovascular parameters in normotensive individuals [55]. The lack of significant change in these measures supports the safety aspects of massage chair therapy, indicating that it does not negatively affect cardiovascular function in healthy individuals [56].

Our results also indicated a significant reduction in MPO levels following the massage chair intervention, which points to potential anti‐inflammatory effects. MPO is a marker of neutrophil activation, known as inflammatory and oxidative markers of stress [57]. Our findings on MPO are in line with studies suggesting that massage therapy can modulate immune function and reduce inflammation, possibly through mechanisms such as improved circulation and reduced muscle tension [58, 59]. In contrast, no significant changes were observed in other biomarkers, such as BDNF, SOD1, eNOS, or cortisol levels in the current study. BDNF is an important neuroprotective growth factor, and its secretion is said to be dependent on the event of damage to the neuron cells [60]. The SOD1 and eNOS are both secreted in oxidative‐stressed neuro and endothelial cells respectively. Thus, it is believed that the unchanged levels in these biomarkers showed massage chair sessions may be utilized safely without contraindications up to 12 sessions (3 x weekly for 20 min). Cortisol, a measure of stress hormone, is more extensively studied in stress studies and is shown to be reduced in another study on a large cohort of 82 hospital bedside nurses, a 10‐min massage chair session reduced the perception of stress compared to a regular “coffee break” session of similar duration [61]. The reduction in cortisol levels in individuals receiving massage chair therapy may be attributed to the specific job responsibilities of these healthcare professionals [62]. Therefore, it is plausible to suggest that the impact of massage on reducing stress levels in healthcare professionals remains inconclusive [63]. Taken together, the lack of significant response in these blood biomarkers may indicate that the therapeutic effects of massage chair therapy in the current study may be more localized or that the systemic effects are not more pronounced than in a much more demanding job environment (i.e. intensive care nurses) [24].

The decrease in beta‐endorphins seen after the intervention implies that, like manual massage and other therapeutic touch, the analgesic effects of massage chair therapy may be mediated by the activation of endogenous opioid systems [64, 65]. Our current study found a decrease in beta‐endorphin; however, this finding does not negate the pain‐relieving benefits of massage. The effect of pain is not always directly correlated with beta‐endorphin levels [66]. Nevertheless, we believe that with long‐term usage of a massage chair, overall well‐being of the healthcare professionals can be maintained. In Engen et al.'s study [23], 38 nurses (78.95%) who received 15‐min weekly massage chair therapy for 10 weeks during work hours reported improved job satisfaction, and 23 (60.53%) expressed willingness to pay USD $10–25 for a 15‐min massage at work. Thus, long‐term use of massage chair therapy may reduce job dissatisfaction, potentially increasing job retention among healthcare professionals.

While the current study provides promising results, several limitations should be considered. Our participants' biomarker values at both baseline and post‐intervention were largely within the expected physiological reference ranges. participants' biomarker values at both baseline and post‐intervention were largely within accepted physiological reference ranges. Serum BDNF levels ranged within the expected 15–30 ng/mL range reported in healthy adults [67, 68]. Likewise, morning cortisol concentrations fell within the typical reference interval of 140–690 ng/mL [69]. The absence of biomarker dysregulation at baseline may have constrained the potential for significant pre–post changes in this relatively healthy population. Based on the results of the present study, although the massage chair group reported slightly higher baseline pain scores in the upper back, lower back, and calves compared to the PMR group, these differences were not statistically significant. As group allocation was randomized and no systematic recruitment bias was identified, the observed baseline variations are likely attributable to random variation inherent in the group assignment process, particularly given the modest sample size. The present study investigates a diverse group of healthcare professionals, who have different job‐related tasks which may produce different localized symptoms (i.e. musculoskeletal pain). Future studies are needed to confirm these results and assess by job scope and work duration to understand the broader applicability of massage chair therapy in certain healthcare jobs. Additionally, a longer follow‐up period would help clarify the long‐term benefits of the massage intervention.

Future research should also explore the underlying mechanisms of action, particularly the neurobiological pathways involved in the therapeutic effects of massage, to gain a deeper understanding of its impact on inflammation, pain, and psychological health.

5. Conclusions

The massage chair intervention demonstrated several beneficial effects, particularly in reducing musculoskeletal pain and stress. While it did not significantly affect blood pressure, heart rate, or anxiety levels, it significantly alleviated pain in the neck, lower back, and calves, with reductions observed after 6‐ and 12‐session interventions. Additionally, depression and stress scores improved after the massage chair sessions. Notably, the intervention also reduced MPO concentrations, indicating a potential anti‐inflammatory effect. However, no significant changes were observed in biomarkers such as BDNF, SOD1, eNOS, and cortisol. These findings suggest that massage chair therapy may be a promising nonpharmacological approach for managing musculoskeletal pain and stress in healthcare professionals, with a favorable relaxation profile state similar to PMR intervention. Therefore, healthcare professionals may benefit from using automated massage chair therapy should it be available in the healthcare settings. Further research is needed to fully elucidate its mechanisms and to explore its long‐term benefits.

Author Contributions

Marilyn Li Yin Ong: conceptualization, methodology, formal analysis, data curation, visualization, writing — original draft, writing — review and editing. Adam Abdul Malik: conceptualization, methodology, investigation, writing — review and editing. Norhasmah Mohd Zain: conceptualization, methodology, investigation, writing — review and editing. Nurulilyana Sansuddin: conceptualization, methodology, investigation, writing — review and editing. Norazliah Hj Samsudin: conceptualization, methodology, investigation, writing — review and editing. Rosminah Mohamed: conceptualization, methodology, investigation, writing — review and editing. Idris Long: conceptualization, methodology, investigation, writing — review and editing. Nor Haslina Mohd: conceptualization, methodology, investigation, writing — review and editing. Nurul Asma Abdullah: conceptualization, methodology, investigation, resources, writing — review and editing. Hairul Anuar Hashim: conceptualization, methodology, formal analysis, supervision, funding acquisition, visualization, project administration, writing — review and editing, data curation, resources.

Ethics Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by Human Research Ethics Committee of Universiti Sains Malaysia (protocol code USM/JEPeM/19120958 and date of approval May 4th, 2020).

Consent

Written informed consent was obtained from all participants before agreeing to be involved in this study (printed and signed). Written informed consent has been obtained from the participants to publish this article.

Conflicts of Interest

The funder had no role in the design of the study; in the collection, analyzes, or interpretation of data; in the writing of the article; or in the decision to publish the results. There is no other conflict of interest to declare.

Transparency Statement

The lead author Hairul Anuar Hashim affirms that this article is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned (and, if relevant, registered) have been explained.

Acknowledgments

The authors would like to thank Madam Norlida Azalan@ZED and Madam Nur Fadhilah Ain Md Adanan for their assistance in the biochemical analysis. All participants were thanked for volunteering in the research project. This study and APC were funded by Healthy World Lifestyle Sdn. Bhd. (OGAWA), grant number OGW‐USM‐AO2663‐04.

Data Availability Statement

All data related to this study has been included in the results section of this article. The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  • 1. National Institute for Occupational Safety and Health (NIOSH) . Stress at Work. Cincinnati, OHIO, U.S.: Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, DHHS (NIOSH); 1999. 99–101.
  • 2. Chen S.‐Y., Yan S.‐R., Zhao W.‐W., et al., “The Mediating and Moderating Role of Psychological Resilience Between Occupational Stress and Mental Health of Psychiatric Nurses: A Multicenter Cross‐Sectional Study,” BMC Psychiatry 22, no. 1 (2022): 823. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3. Nassehi A., Jafari J., Jafari‐Oori M., and Jafari M., “Moral Distress, Burnout, and Job Satisfaction in Emergency Medical Technicians During the COVID‐19 Pandemic,” Nursing and Midwifery Studies 12, no. 1 (2023): 48–54. [Google Scholar]
  • 4. Li X., Jiang T., Sun J., Shi L., and Liu J., “The Relationship Between Occupational Stress, Job Burnout and Quality of Life Among Surgical Nurses in Xinjiang, China,” BMC Nursing 20 (2021): 181. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Copertaro A., Bracci M., Barbaresi M., and Santarelli L., “Assessment of Cardiovascular Risk in Shift Healthcare Workers,” European Journal of Cardiovascular Prevention and Rehabilitation 15, no. 2 (2008): 224–229. [DOI] [PubMed] [Google Scholar]
  • 6. Kivimaki M., “Work Stress and Risk of Cardiovascular Mortality: Prospective Cohort Study of Industrial Employees,” BMJ 325, no. 7369 (2002): 857. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. Yi J., Kang L., Li J., and Gu J., “A Key Factor for Psychosomatic Burden of Frontline Medical Staff: Occupational Pressure During the COVID‐19 Pandemic in China,” Frontiers in Psychiatry 11 (2021): 590101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8. Jiang C., Jiang W., Yue Y., et al., “The Trends of Psychosomatic Symptoms and Perceived Stress Among Healthcare Workers During the COVID‐19 Pandemic in China: Four Cross‐Sectional Nationwide Surveys, 2020–2023,” Psychiatry Research 326 (2023): 115301. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Liu G., Tong Y., Li J., et al., “Burnout, Moral Injury, and Suicidal/Self‐Harm Ideation Among Healthcare Professionals in Mainland China: Insights From an Online Survey During the COVID‐19 Pandemic,” International Journal of Psychiatry in Medicine 59, no. 4 (2024): 487–502. [DOI] [PubMed] [Google Scholar]
  • 10. Hui‐Ren Z., Li‐Li M., Qin L., Wei‐Ying Z., Hai‐Ping Y., and Wei Z., “Evaluation of the Correlation Between Sleep Quality and Work Engagement Among Nurses in Shanghai During the Post‐Epidemic Era,” Nursing Open 10, no. 7 (2023): 4838–4848. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11. de Vroege L. and van den Broek A., “Post‐Pandemic Self‐Reported Mental Health of Mental Healthcare Professionals in the Netherlands Compared to During the Pandemic–An Online Longitudinal Follow‐Up Study,” Frontiers in Public Health 11 (2023): 1221427. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12. Yahaya S. N., Wahab S. F. A., Yusoff M. S. B., Yasin M. A. M., and Rahman M. A. A., “Prevalence and Associated Factors of Stress, Anxiety and Depression Among Emergency Medical Officers in Malaysian Hospitals,” World Journal of Emergency Medicine 9, no. 3 (2018): 178. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13. Rusli B. N., Edimansyah B. A., and Naing L., “Prevalence and Associated Factors of Stress in Dental Healthcare Workers of a Higher Institution of Learning in Kelantan,” Archives of Orofacial Sciences 1 (2006): 51–56. [Google Scholar]
  • 14. Lua P. L. and Imilia I., “Work‐Related Stress Among Healthcare Providers of Various Sectors in Peninsular Malaysia,” Malaysian Journal of Psychiatry 20, no. 2 (2011): 30–44. [Google Scholar]
  • 15. Khoo E. M., Abdullah A., Liew S. M., et al., “Psychological Health and Wellbeing of Primary Healthcare Workers During COVID‐19 Pandemic in Malaysia: A Longitudinal Qualitative Study,” BMC Primary Care 23, no. 1 (2022): 261. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Dadar Singh N. K., Loo J. L., Ko A. M. N., Husain S. S., Dony J. F., and Syed Abdul Rahim S. S., “Obesity and Mental Health Issues Among Healthcare Workers: A Cross‐Sectional Study in Sabah, Malaysia,” Journal of Health Research 36, no. 5 (2022): 939–945. [Google Scholar]
  • 17. Woon L. S.‐C. and Tiong C. P., “Burnout, Mental Health, and Quality of Life Among Employees of a Malaysian Hospital: A Cross‐Sectional Study,” Annals of Work Exposures and Health 64, no. 9 (2020): 1007–1019. [DOI] [PubMed] [Google Scholar]
  • 18. Jakobsen M. D., Sundstrup E., Brandt M., Jay K., Aagaard P., and Andersen L. L., “Physical Exercise at the Workplace Prevents Deterioration of Work Ability Among Healthcare Workers: Cluster Randomized Controlled Trial,” BMC Public Health 15 (2015): 1174. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19. Andersen L. N., Juul‐Kristensen B., Roessler K. K., Herborg L. G., Sørensen T. L., and Søgaard K., “Efficacy of ‘Tailored Physical Activity' on Reducing Sickness Absence Among Health Care Workers: A 3‐months Randomised Controlled Trial,” Manual Therapy 20, no. 5 (2015): 666–671. [DOI] [PubMed] [Google Scholar]
  • 20. Wood K. and Carini C., “A Moment of Peace: Utilizing Practical on the Job Relaxation and Meditation Techniques to Improve Feelings of Stress and Burnout Among Healthcare Professionals,” Journal of Interprofessional Education and Practice 31 (2023): 100613. [Google Scholar]
  • 21. Veiga G., Dias Rodrigues A., Lamy E., Guiose M., Pereira C., and Marmeleira J., “The Effects of a Relaxation Intervention on Nurses' Psychological and Physiological Stress Indicators: A Pilot Study,” Complementary Therapies in Clinical Practice 35 (2019): 265–271. [DOI] [PubMed] [Google Scholar]
  • 22. Bost N. and Wallis M., “The Effectiveness of a 15 Minute Weekly Massage in Reducing Physical and Psychological Stress in Nurses,” Australian Journal of Advanced Nursing 23, no. 4 (2006): 28–33. [PubMed] [Google Scholar]
  • 23. Engen D. J., Wahner‐Roedler D. L., Vincent A., et al., “Feasibility and Effect of Chair Massage Offered to Nurses During Work Hours on Stress‐Related Symptoms: A Pilot Study,” Complementary Therapies in Clinical Practice 18, no. 4 (2012): 212–215. [DOI] [PubMed] [Google Scholar]
  • 24. Nazari F., Mirzamohamadi M., and Yousefi H., “The Effect of Massage Therapy on Occupational Stress of Intensive Care Unit Nurses,” Iranian Journal of Nursing and Midwifery Research 20, no. 4 (2015): 508–515. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Hand M., Margolis J., and Staffileno B., “Massage Chair Sessions: Favorable Effects on Ambulatory Cancer Center Nurses' Perceived Level of Stress, Blood Pressure, and Heart Rate,” Clinical Journal of Oncology Nursing 23, no. 4 (2019): 375–381. [DOI] [PubMed] [Google Scholar]
  • 26. Baek J. Y., Lee E., Gil B., Jung H.‐W., and Jang I.‐Y., “Clinical Effects of Using a Massage Chair on Stress Measures in Adults: A Pilot Randomized Controlled Trial,” Complementary Therapies in Medicine 66 (2022): 102825. [DOI] [PubMed] [Google Scholar]
  • 27. Ganjeali S., Farsi Z., Sajadi S. A., and Zarea K., “The Effect of the Demonstration‐Based Progressive Muscle Relaxation Technique on Stress and Anxiety in Nurses Caring for COVID‐19 Patients: A Randomized Clinical Trial,” BMC Psychiatry 22, no. 1 (2022): 791. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28. Stewart‐Richardson J. L., Hopf S. C., Crockett J., and Southwell P., “What is Effective in Massage Therapy? Well, ‘It Depends’: A Qualitative Study of Experienced Orthopaedic Massage Therapists,” International Journal of Therapeutic Massage and Bodywork 17, no. 1 (2024): 4–18. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. McEwen B. S., “Central Effects of Stress Hormones in Health and Disease: Understanding the Protective and Damaging Effects of Stress and Stress Mediators,” European Journal of Pharmacology 583, no. 2 (2008): 174–185. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Molendijk M. L., Spinhoven P., Polak M., Bus B. A. A., Penninx B. W. J. H., and Elzinga B. M., “Serum BDNF Concentrations as Peripheral Manifestations of Depression: Evidence From a Systematic Review and Meta‐Analyses on 179 Associations (N=9484),” Molecular Psychiatry 19, no. 7 (2014): 791–800. [DOI] [PubMed] [Google Scholar]
  • 31. Chrousos G. P., “Stress and Disorders of the Stress System,” Nature Reviews Endocrinology 5, no. 7 (2009): 374–381. [DOI] [PubMed] [Google Scholar]
  • 32. Drolet G., Dumont É. C., Gosselin I., Kinkead R., Laforest S., and Trottier J.‐F., “Role of Endogenous Opioid System in the Regulation of the Stress Response,” Progress in Neuro‐Psychopharmacology and Biological Psychiatry 25, no. 4 (2001): 729–741. [DOI] [PubMed] [Google Scholar]
  • 33. Bhatt S., Nagappa A. N., and Patil C. R., “Role of Oxidative Stress in Depression,” Drug Discovery Today 25, no. 7 (2020): 1270–1276. [DOI] [PubMed] [Google Scholar]
  • 34. Landmesser U., Hornig B., and Drexler H., “Endothelial Function,” Circulation 109, no. 21_suppl_1 (2004): II‐27‐II‐33. [DOI] [PubMed] [Google Scholar]
  • 35. Ndrepepa G., “Myeloperoxidase – A Bridge Linking Inflammation and Oxidative Stress With Cardiovascular Disease,” Clinica Chimica Acta 493 (2019): 36–51. [DOI] [PubMed] [Google Scholar]
  • 36. Lovibond P. F. and Lovibond S. H., “The Structure of Negative Emotional States: Comparison of the Depression Anxiety Stress Scales (DASS) With the Beck Depression and Anxiety Inventories,” Behaviour Research and Therapy 33, no. 3 (1995): 335–343. [DOI] [PubMed] [Google Scholar]
  • 37. Sharifah Maimunah S. M. P. and Hashim H. A., “Differential Effects of 7 and 16 Groups of Muscle Relaxation Training Following Repeated Submaximal Intensity Exercise in Young Football Players,” Perceptual and Motor Skills 122, no. 1 (2016): 227–237. [DOI] [PubMed] [Google Scholar]
  • 38. Lohaus A. and Klein‐Hessling J., “Relaxation in Children: Effects of Extended and Intensified Training,” Psychology and Health 18, no. 2 (2003): 237–249. [Google Scholar]
  • 39. Hashim H. A. and Hanafi@Ahmad Yusof H., “The Effects of Progressive Muscle Relaxation and Autogenic Relaxation on Young Soccer Players' Mood States,” Asian Journal of Sports Medicine 2, no. 2 (2011): 99. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Musa R., Fadzil M. A., and Zain Z. A., “Translation, Validation and Psychometric Properties of Bahasa Malaysia Version of the Depression Anxiety and Stress Scales (DASS),” ASEAN Journal of Psychiatry 8, no. 2 (2007): 82–89. [Google Scholar]
  • 41. Huskisson E. C., “Measurement of the effects of treatment by the patient,” Spontanverlauf und Therapiebeurteilung rheumatischer Erkrankungen (Springer, 1983), 99–102. [Google Scholar]
  • 42. Scott J. and Huskisson E. C., “Graphic Representation of Pain,” Pain 2, no. 2 (1976): 175–184. [PubMed] [Google Scholar]
  • 43. Cygańska A., Truszczyńska‐Baszak A., and Tomaszewski P., “Impact of Exercises and Chair Massage on Musculoskeletal Pain of Young Musicians,” International Journal of Environmental Research and Public Health 17, no. 14 (2020): 5128. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. Kim S.‐K., Min A., Jeon C., et al., “Clinical Outcomes and Cost‐Effectiveness of Massage Chair Therapy Versus Basic Physiotherapy in Lower Back Pain Patients: A Randomized Controlled Trial,” Medicine 99, no. 12 (2020): e19514. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45. Engen D. J., Wahner‐Roedler D. L., Nadolny A. M., et al., “The Effect of Chair Massage on Muscular Discomfort in Cardiac Sonographers: A Pilot Study,” BMC Complementary and Alternative Medicine 10 (2010): 50. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Lindgren L., Rundgren S., Winsö O., et al., “Physiological Responses to Touch Massage in Healthy Volunteers,” Autonomic Neuroscience 158, no. 1–2 (2010): 105–110. [DOI] [PubMed] [Google Scholar]
  • 47. Sherman K. J., Ludman E. J., Cook A. J., et al., “Effectiveness of Therapeutic Massage for Generalized Anxiety Disorder: A Randomized Controlled Trial,” Depression and Anxiety 27, no. 5 (2010): 441–450. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48. Fu M., Sun C., Liu T., and Li S., “Effect of Massotherapy on the Fatigue Recovery Using the Smart Massage Chair: A Randomized Controlled Trial,” Journal of Mechanics in Medicine and Biology 22, no. 9 (2022): 1–14. [Google Scholar]
  • 49. Beh L.‐S. and Loo L.‐H., “Job Stress and Coping Mechanisms Among Nursing Staff in Public Health Services,” IJ‐ARBSS 2, no. 7 (2012): 131. [Google Scholar]
  • 50. Sukadarin E. H., Pim N. U., Zakaria J., Deros B. M., and Syazwani N., “The Prevalence of Work‐Related Musculoskeletal Disorders and Stress Level Among Hospital Nurses,” HFEIJ 1, no. 1 (2016): 40–44. [Google Scholar]
  • 51. Field T., “Massage Therapy Research Review,” Complementary Therapies in Clinical Practice 20, no. 4 (2014): 224–229. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52. Kaye A. D., Kaye A. J., Swinford J., et al., “The Effect of Deep‐Tissue Massage Therapy on Blood Pressure and Heart Rate,” Journal of Alternative and Complementary Medicine 14, no. 2 (2008): 125–128. [DOI] [PubMed] [Google Scholar]
  • 53. Rapaport M. H., Schettler P. J., Larson E. R., et al., “A Preliminary Descriptive Report of the Longevity of the Effects of Swedish Massage Therapy for Subjects With Generalized Anxiety Disorder,” Journal of Bodywork and Movement Therapies 33 (2023): 176–181. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54. Gaballah S., El‐Deen D. S., and Hebeshy M. I., “Effect of Effleurage Massage Therapy on Sleep Disturbance, Fatigue, Pain, and Anxiety in Patients With Multiple Sclerosis: A Quasi‐Experimental Study,” Applied Nursing Research 73 (2023): 151719. [DOI] [PubMed] [Google Scholar]
  • 55. Craig T. A., Effects of Automated Electronic Massage Chairs on Autonomic Control in Non‐hypertensive Adults (San Francisco State University, 2017), https://scholarworks.calstate.edu/downloads/b8515q30g. [Google Scholar]
  • 56. Kraft K., Kanter S., and Janik H., “Safety and Effectiveness of Vibration Massage by Deep Oscillations: A Prospective Observational Study,” Evidence‐Based Complementary and Alternative Medicine 2013, no. 1 (2013): 679248. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57. Khan A. A., Alsahli M. A., and Rahmani A. H., “Myeloperoxidase as an Active Disease Biomarker: Recent Biochemical and Pathological Perspectives,” Medical Sciences 6, no. 2 (2018): 33. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58. Rapaport M. H., Schettler P., and Bresee C., “A Preliminary Study of the Effects of a Single Session of Swedish Massage on Hypothalamic–Pituitary–Adrenal and Immune Function in Normal Individuals,” The Journal of Alternative and Complementary Medicine 16, no. 10 (2010): 1079–1088. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59. Rapaport M. H., Schettler P., and Bresee C., “A Preliminary Study of the Effects of Repeated Massage on Hypothalamic–Pituitary–Adrenal and Immune Function in Healthy Individuals: A Study of Mechanisms of Action and Dosage,” Journal of Alternative and Complementary Medicine 18, no. 8 (2012): 789–797. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60. Maiworm M., “The Relevance of BDNF for Neuroprotection and Neuroplasticity in Multiple Sclerosis,” Frontiers in Neurology 15 (2024): 1385042. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61. Youn B.‐Y., Cho H., Joo S., Kim H.‐J., and Kim J.‐Y., “Utilization of Massage Chairs for Promoting Overall Health and Wellness: A Rapid Scoping Review,” Explore 20, no. 3 (2024): 285–297. [DOI] [PubMed] [Google Scholar]
  • 62. Van Dijk W., Huizink A. C., Müller J., Uvnäs‐Moberg K., Ekström‐Bergström A., and Handlin L., “The Effect of Mechanical Massage and Mental Training on Heart Rate Variability and Cortisol in Swedish Employees—A Randomized Explorative Pilot Study,” Frontiers in Public Health 8 (2020): 82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63. Li H., Zhao M., Shi Y., et al., “The Effectiveness of Aromatherapy and Massage on Stress Management in Nurses: A Systematic Review,” Journal of Clinical Nursing 28, no. 3–4 (2019): 372–385. [DOI] [PubMed] [Google Scholar]
  • 64. Day J. A., Mason R. R., and Chesrown S. E., “Effect of Massage on Serum Level of β‐endorphin and β‐lipotropin in Healthy Adults,” Physical Therapy 67, no. 6 (1987): 926–930. [DOI] [PubMed] [Google Scholar]
  • 65. Kaada B. and Torsteinbø O., “Increase of Plasma β‐endorphins in Connective Tissue Massage,” General Pharmacology: The Vascular System 20, no. 4 (1989): 487–489. [DOI] [PubMed] [Google Scholar]
  • 66. Bender T., Nagy G., Barna I., Tefner I., Kádas É., and Géher P., “The Effect of Physical Therapy on Beta‐Endorphin Levels,” European Journal of Applied Physiology 100 (2007): 371–382. [DOI] [PubMed] [Google Scholar]
  • 67. Naegelin Y., Dingsdale H., Säuberli K., Schädelin S., Kappos L., and Barde Y. A., “Measuring and Validating the Levels of Brain‐Derived Neurotrophic Factor in Human Serum,” eNeuro 5, no. 2 (2018): ENEURO.0419‐17.2018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68. Puhlmann L. M. C., Linz R., Valk S. L., et al., “Association Between Hippocampal Structure and Serum Brain‐Derived Neurotrophic Factor (BDNF) in Healthy Adults: A Registered Report,” NeuroImage 236 (2021): 118011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69. Melmed S., Auchus R. J., Goldfine A. B., Koenig R. J., and Rosen C. J., ed., Williams Textbook of Endocrinology (Elsevier, 2020). 14th ed. [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

All data related to this study has been included in the results section of this article. The data that support the findings of this study are available from the corresponding author upon reasonable request.

Articles from Health Science Reports are provided here courtesy of Wiley

RESOURCES