Effects of Acupressure on Nurses' Psychological Distress, Anxiety, Depression, Job Stress, Occupational Burnout, and Resilience
Phase: NA
Conditions: Psychological Distress, Anxiety, Depression, Nurses, Acupressure
Sponsor: Kaohsiung Veterans General Hospital.

Effects of acupressure on psychological distress, 
depression among nurses in a medical center: a single-
blind randomized controlled trial 
 
 
 
 
NCT Number: NCT06946888 
 
Date: December 31, 2024 
 
 
 
 
 
 
 
 
 
 
 
 

Study Title 
Effects of Acupressure on Psychological Distress and Depression Among Nurses in a 
Medical Center: A Single-Blind Randomized Controlled Trial 
NCT Number: NCT06946888 
Date: May 21, 2024-December 31, 2024 
Background 
Clinical nurses are routinely exposed to occupational stressors such as shift rotations, 
emotional labor, and high patient acuity, placing them at elevated risk of psychological 
distress and burnout (Zeiher et al., 2022; Katsiroumpa et al., 2025). Compared with other 
healthcare professionals, nurses report higher rates of emotional exhaustion and post-
traumatic stress symptoms, particularly in the aftermath of the COVID-19 pandemic. 
Acupressure is a complementary therapy that involves applying manual pressure to 
specific acupoints along the body9s meridians to promote physiological and emotional 
regulation. Among the most studied acupoints for psychological symptoms are Shenmen 
(HT7) and Neiguan (PC6). HT7 is traditionally used to calm the spirit and regulate mood, 
and is commonly applied in treating insomnia and anxiety (Lee et al., 2019; WHO, 2008). 
PC6 is associated with regulating heart rhythm, relieving palpitations, and reducing stress 
(WHO, 2008; Lee et al., 2023). Prior studies have demonstrated that stimulation at HT7 
and PC6 can reduce anxiety and depressive symptoms in patients recovering from 
COVID-19 (Liang et al., 2024) and improve mood stability in cardiac populations (Bal & 
Gun, 2024). Systematic reviews further confirm the potential of these acupoints in 
alleviating depression and anxiety (Lin et al., 2022). 
Despite this evidence, research applying acupressure as a self-care intervention for 
healthcare workers4especially nurses4remains scarce. Given the high psychological 
demands of nursing work, evaluating accessible, low-cost interventions that nurses can 
self-administer without disrupting workflow is critically important. This trial addresses 
that gap by assessing the effects of self-administered acupressure on depressive 
symptoms, psychological distress, emotional distress, anxiety, job stress, occupational 
burnout, and resilience in clinical nurses. 
Objective 
This study aimed to examine the effects of self-administered acupressure at the Shenmen 
(HT7) and Neiguan (PC6) points on emotional distress, anxiety, depression, stress, work-
related fatigue, and resilience among clinical nurses. 

Methods 
 
This study adopted a single-blind randomized controlled trial (RCT) design. It was 
approved by the Institutional Review Board of a medical center (IRB No. 24-CT6-13) 
and registered at ClinicalTrials.gov (NCT06946888). The study was conducted from June 
13, 2024, to September 22, 2024. Participants included nurses aged 20 and above 
working in clinical departments. Exclusion criteria included: (1) refusal or inability to 
comply with the study; (2) non-clinical roles (e.g., administrative units, supply 
departments); and (3) pregnancy. Out of 463 screened nurses, 160 were eligible based on 
the Brief Symptom Rating Scale (BSRS-5 g 4) or Distress Thermometer score g 3 and 
agreed to participate. They were randomly assigned via computer to the intervention 
group (n=80) or control group (n=80). 
 

Interventions 
Participants in the intervention group received in-person instruction from a trained 
research assistant on how to self-administer acupressure targeting two specific acupoints 
on each hand4Shenmen (HT7) and Neiguan (PC6)4resulting in a total of four 
acupoints (two on each hand). Participants were guided to apply approximately 3/kg of 
thumb pressure to each acupoint until a sensation of soreness or tingling was perceived. 
Each acupoint was stimulated with 15 rhythmic presses (approximately 30/seconds per 
point), totaling about 2/minutes per session for all four acupoints. The intervention was 
performed twice daily for two consecutive weeks, and participants were provided with 
illustrated instructions (Figure/1) and a daily acupressure log to record adherence. The 
control group received no intervention. Although the intervention lasted 2/weeks, all 
participants in both groups were followed for 8/weeks and completed weekly 
questionnaires throughout the follow-up period. 
 
Figure 1. Anatomical locations of Shenmen (HT7) and Neiguan (PC6) acupoints. 
HT7 (Shenmen) is located at the wrist crease on the radial side of the flexor carpi ulnaris 
tendon. 
PC6 (Neiguan) is found approximately two cun (about three finger-widths) proximal to 
the wrist crease, between the palmaris longus and flexor carpi radialis tendons. 
Instruments 
Data were collected using self-administered questionnaires, which included measures of 
emotional distress, distress thermometer, Taiwanese Depression Scale, State Anxiety 

Inventory, Nurse Stress Checklist, Occupational Fatigue Inventory, Resilience Scale, and 
basic demographic information. All instruments were used with permission from the 
original authors. 
(1) Demographic Data: 
Information collected included age, date of birth, gender, education level, current 
academic enrollment, marital status, number of children, living arrangements, religious 
beliefs, medical history, medication use, hospitalization experience, physical activity, 
stress-relief methods, work unit and department, experience with COVID-19 patient care, 
employment start date, external hospital experience, total years in nursing, self-reported 
sleep quality (1310), and presence of sleep disorders. 
 
(2) Emotional distress: 
Emotional distress was measured using the Distress Thermometer (DT), a single-item 
self-report screening tool rated from 0 (no distress) to 10 (extreme distress). Higher 
scores indicate greater emotional distress, and participants were asked to report their 
overall distress during the past week, including the current day. The DT has demonstrated 
adequate psychometric properties across validation studies, with sensitivity ranging from 
0.50 to 1.00 (median = 0.83) and specificity ranging from 0.36 to 0.98 (median = 0.68) 
(Donovan et al., 2014). 
For the purpose of this study, a DT cut-off score of g3 was adopted as an inclusion 
criterion. This threshold has been recommended in a large-scale validation study as an 
efficient marker of clinically elevated distress (Cutillo et al., 2017). Other studies have 
shown that optimal DT cut-offs vary across settings, typically ranging from 3 to 5 
(Donovan et al., 2014), while clinical practice often applies a threshold of g4 or g5 
(Ownby, 2019). Using g3 in this study was intended to maximize sensitivity and 
minimize the risk of under-identification in a nursing population considered at high risk 
for psychological distress. 
 
(3) Psychological distress: 
Psychological distress was measured using the 5-item Brief Symptom Rating Scale 
(BSRS-5; Lee et al., 2010), a validated screening tool for general psychological distress. 
The BSRS-5 assesses the subjective severity of (1) anxiety (feeling tense or keyed up), (2) 
depression (feeling blue), (3) hostility (feeling easily annoyed or irritated), (4) inferiority 
(feeling inferior to others), and (5) insomnia (difficulty falling asleep). Each item is rated 
on a 5-point Likert scale ranging from 0 (5not at all6) to 4 (5extremely severe6), with 

higher scores indicating greater psychological distress. Total scores range from 0 to 20, 
and the BSRS-5 demonstrated good internal consistency in the present study (Cronbach9s 
³ = .86). 
Validation studies have suggested that total scores of 334 represent an optimal threshold 
for identifying clinically relevant distress, based on receiver operating characteristic 
(ROC) curve analysis (Lee et al., 2010). At these cut-offs, the BSRS-5 showed high 
accuracy (AUC = 0.92), with good sensitivity (0.83) and specificity (0.86). Based on this 
evidence, the present study adopted a BSRS-5 total score of g4 as one of the inclusion 
criteria, ensuring that participants with at least mild psychological distress were captured. 
 
(4) Depressive symptoms: 
Depressive symptoms were assessed using the Taiwanese Depression Scale (TDS; Lee 
et al., 2000), which has demonstrated strong psychometric properties in Taiwanese 
populations. The TDS consists of 18 items rated on a 4-point Likert scale: 0 = none or 
seldom (less than one day per week), 1 = sometimes (one to two days per week), 2 = 
often (three to four days per week), and 3 = almost always (five to seven days per week). 
Total scores range from 0 to 54, with higher scores indicating greater severity of 
depressive symptoms. 
The results from Lee et al. (2000) demonstrated that the TDS had excellent reliability and 
validity. The Cronbach9s alpha coefficient was 0.90, and the area under the receiver 
operating characteristic (ROC) curve was 0.92. The TDS also showed good concurrent 
validity, with a sensitivity of 0.89 and specificity of 0.92 at a cutoff score of 19. 
In the present study, the TDS demonstrated excellent internal consistency, with a 
Cronbach9s alpha of .94. 
 
(5) Anxiety: 
Anxiety was assessed using the State subscale of the State3Trait Anxiety Inventory 
(STAI-S; Spielberger, Gorsuch, & Lushene, 1970), a widely used and psychometrically 
validated instrument. The STAI-S consists of 20 items that assess anxiety-related feelings, 
thoughts, and behaviors at the time of assessment. Each item is rated on a 4-point Likert 
scale ranging from 1 (5not at all6) to 4 (5very much so6). Items 1, 2, 5, 8, 10, 11, 15, 16, 
19, and 20 are reverse-scored. Total scores range from 20 to 80, with higher scores 
indicating greater levels of state anxiety. Scores between 20339 indicate mild anxiety, 
40359 moderate anxiety, and 60380 severe anxiety. 

In the present study, the validated Chinese version of the STAI-S, adapted by Wang and 
Chung (2016), was used. Their study confirmed the multidimensional factorial structure 
of the Chinese version and demonstrated good psychometric properties, including 
adequate convergent and discriminant validity. In the present sample, the STAI-S showed 
excellent internal consistency (Cronbach9s ³ = .95). 
 
(6) Job Stress: 
Perceived job stress was measured using the 14-item Work Pressure Inventory 
developed by Huang et al. (2017), which has demonstrated good internal consistency. 
The scale comprises three dimensions: low self-development, workload, and job 
characteristics. Each item is rated on a 5-point Likert scale ranging from 1 (5strongly 
disagree6) to 5 (5strongly agree6), with total scores ranging from 14 to 70. Higher scores 
indicate greater perceived occupational stress. In the original validation study, the 
Cronbach9s ³ coefficients for the three subscales were 0.81, 0.73, and 0.77, respectively. 
In the present study, the Work Pressure Inventory showed good overall internal 
consistency (Cronbach9s ³ = .84). 
 
(7) Occupational burnout: 
Occupational burnout was assessed using the Chinese version of the Copenhagen 
Burnout Inventory (CBI; Yeh et al., 2008), which has demonstrated good psychometric 
properties in Taiwanese populations. The scale consists of four subscales: personal 
burnout, work-related burnout, client-related burnout, and overcommitment to work. 
Each item is rated on a five-point frequency scale: 5always6 (100), 5often6 (75), 
5sometimes6 (50), 5rarely6 (25), and 5never6 (0). Subscale scores are calculated as the 
average of the items within each domain, ranging from 0 to 100, with higher scores 
indicating more severe occupational burnout. The original validation study reported 
Cronbach9s ³ values above 0.84 across all subscales (Yeh et al., 2008). In the present 
study, the scale demonstrated excellent internal consistency (Cronbach9s ³ = .95). 
 
(8) Resilience: 
Resilience was measured using the 10-item Resilience Scale developed and validated by 
Hsiao et al. (2019) for use among hospital staff in Taiwan. The scale assesses individuals9 
psychological capacity to adapt to and recover from stress and adversity. Each item is 
rated on a 5-point Likert scale ranging from 1 (5strongly disagree6) to 5 (5strongly 

agree6), with total scores ranging from 10 to 50. Higher scores indicate greater levels of 
psychological resilience. 
The original validation study demonstrated strong psychometric properties, including 
good model fit from confirmatory factor analysis (GFI = 0.973) and excellent internal 
consistency (Cronbach9s ³ = .91). The authors also found that resilience levels varied by 
gender and years of service, highlighting the tool9s sensitivity in occupational contexts. 
In the present study, the scale showed excellent internal consistency (Cronbach9s ³ = .92). 
 
All instruments used in this study were authorized by the original developers and have 
been psychometrically validated in previous research. In the present study, all scales 
demonstrated good to excellent internal consistency, with Cronbach9s ³ values ranging 
from .84 to .95. 
 
Statistical Analysis 
All statistical analyses were conducted using IBM SPSS Statistics version 30.0. 
Continuous variables were summarized as mean ± standard deviation (SD), and 
categorical variables as n (%). Baseline group comparability was assessed using 
independent-samples t tests (continuous variables) and Ç² tests (categorical variables). 
Variables that differed significantly at baseline (p < .05) were considered potential 
confounders; because age differed significantly between groups, it was included as a 
covariate in all longitudinal models. 
Within-group changes from baseline (weeks 038) were examined using paired t tests. 
Between-group comparisons at each follow-up time point were performed using 
independent-samples t tests. For significant between-group differences, effect sizes were 
calculated using Cohen9s d with 95% confidence intervals (CI), where 0.2, 0.5, and 0.8 
indicated small, medium, and large effects, respectively. 
To assess the longitudinal effects of the intervention, generalized estimating equations 
(GEE) were applied with a normal distribution, identity link, and an exchangeable 
correlation structure. The model included group (intervention vs. control), week 
(categorical: 038), the group × week interaction, and age as a covariate. Robust 
(sandwich) standard errors were used. Regression coefficients (B), standard errors, Wald 
Ç² statistics, 95% CIs, and p values for group × week contrasts are reported. GEE was 
chosen over repeated-measures ANOVA or generalized linear mixed models because it 
provides population-averaged estimates, is robust to correlation misspecification, 
accommodates missing data under MAR/MCAR assumptions, and does not require 
sphericity. All tests were two-tailed with ³ = .05.