Ⅰ. Introduction

Musculoskeletal pain is one of the most common problems encountered in physical therapy practice, yet its assessment still relies heavily on patients’ subjective reports. Because pain is a subjective experience that includes both sensory and emotional components, self-report remains the fundamental principle of pain assessment (Hjermstad et al., 2011;Hawker et al., 2011). In particular, the Numeric Rating Scale (NRS) is widely used in clinical practice and research because it is easy to administer and highly responsive, and it has been recognized as a valid indicator of pain intensity when compared with other pain scales (Hjermstad et al., 2011;Hawker et al., 2011;Ferreira-Valente et al., 2011). Moreover, when self-report is possible, the patient’s own pain report should remain the primary standard of assessment, and no objective pain measure has yet been established that can fully replace it (Herr et al., 2019;Gélinas, 2016).

However, in actual clinical settings, pain experience often cannot be fully explained by self-report alone. Tension related to the testing situation, anticipation of pain, task burden, and emotional arousal may simultaneously influence both reported pain intensity and physiological responses. For this reason, physiological responses such as heart rate have been explored as adjunctive indicators of pain. Nevertheless, studies conducted in emergency and intensive care settings have reported that associations between self-reported pain and vital signs are limited, and that HR is closer to a nonspecific arousal response than to a pain-specific index (Marco et al., 2006;Bossart et al., 2007;Arbour et al., 2014;Daoust et al., 2016). A reanalysis of a large emergency department dataset likewise suggested that the relationship between self-reported pain and HR is small and inconsistent (Dayoub & Jena, 2015).

Under experimental pain conditions, increases in HR may be observed as part of the physiological response to noxious stimulation, which has value for understanding autonomic reactions associated with pain (Tousignant-Laflamme et al., 2005;Loggia et al., 2011;Kyle & McNeil, 2014). Studies in healthy individuals exposed to experimentally induced pain have reported relationships between HR and pain perception and have suggested that cardiovascular responses may increase as stimulus intensity and pain ratings increase (Tousignant-Laflamme et al., 2005;Loggia et al., 2011). However, HR responses during experimental pain should be interpreted within a broader autonomic arousal context because they may be influenced not only by nociceptive stimulation itself but also by anticipation, perceived threat, uncertainty, anxiety sensitivity, and individual differences (Colloca et al., 2006;Dodo & Hashimoto, 2017;Kyle & McNeil, 2014). Thus, HR may be more appropriately interpreted as part of the physiological arousal that occurs during pain rather than as a substitute measure of pain itself.

In particular, state anxiety should be considered when interpreting the relationship between pain and HR responses. Among various psychological factors that may influence pain-related physiological responses, state anxiety was selected in this study because it reflects the participant’s immediate emotional state at the time of testing. Unlike trait anxiety, which represents a relatively stable individual characteristic, state anxiety captures momentary tension, worry, and situational arousal that may occur before or during an experimental pain procedure. Because HR is sensitive to autonomic arousal, state anxiety may directly influence HR responses and may confound the relationship between self-reported pain intensity and HR change. Psychological stress and anxiety have been reported to be significantly associated with cardiovascular and autonomic responses (Julian, 2011;Kim et al., 2018;Chalmers et al., 2014). Autonomic responses during pain anticipation may be distinguishable from actual pain perception while still showing repeatable patterns, and uncertainty about pain as well as anxiety sensitivity may also alter physiological responses in pain-inducing situations (Colloca et al., 2006;Dodo & Hashimoto, 2017). Therefore, state anxiety was included as a key psychological variable in this study to determine whether HR responses to experimentally evoked musculoskeletal pain reflect pain intensity itself or are influenced by anxiety-related autonomic arousal.

Meanwhile, pressure pain stimulation is a clinically relevant and easily standardized experimental pain model in the musculoskeletal field. Mechanical pressure stimulation using an algometer has been widely used to quantify pressure pain thresholds and pain responses, and studies in healthy adults have reported relatively favorable inter-rater and test–retest reliability (Antonaci et al., 1998;Nussbaum & Downes, 1998;Chesterton et al., 2007;Kinser et al., 2009;Liew et al., 2021). More recently, pressure pain data have also been reported in general adult populations, providing basic information on age- and sex-related differences in pressure pain thresholds (Vesal et al., 2024). Thus, pressure pain stimulation combined with HR measurement may provide an appropriate methodological foundation for investigating the relationship between subjective pain and physiological responses in experimentally evoked musculoskeletal pain.

In addition, the chest-strap HR sensor used in this study, the Polar H10, is highly portable and easy to apply, and recent validation studies have reported high agreement with ECG for short-term RR interval and HR measurements (Schaffarczyk et al., 2022). Because the present study focused on HR responses rather than heart rate variability, this choice of equipment was considered practical as long as a standardized placement and a consistent experimental environment were maintained.

Accordingly, the primary aim of this study was to examine differences in HR across baseline, pain stimulation, and recovery phases during experimentally evoked musculoskeletal pain in healthy adults. The secondary aim was to analyze the relationships among self-reported pain intensity, HR change, and state anxiety and to determine whether pain intensity independently predicted HR change after controlling for state anxiety. We hypothesized that HR would increase during experimentally evoked musculoskeletal pain, that HR change would show a positive correlation with pain intensity, but that this association would be attenuated after adjustment for state anxiety.

Ⅱ. Methods

1. Study design

This study was designed as a one-group repeated-measures experimental study involving healthy adults. All participants underwent the same sequence of baseline, pain stimulation, and recovery phases, and HR was repeatedly measured at each time point. This design was appropriate for reducing inter-individual variability in physiological responses and for comparing changes within the same participant.

2. Participants

This study was conducted with 30 healthy adults aged 20 to 40 years who resided in Y City, Gyeongsangbuk-do. Participants were recruited voluntarily through online and offline community advertisements. All participants were fully informed of the purpose and procedures of the study, as well as the expected discomfort and potential risks, and were included only after providing written informed consent. Inclusion criteria were as follows: (1) adults aged 20 to 40 years residing in Y City, Gyeongsangbuk-do; (2) no persistent musculoskeletal pain within the previous 3 months; (3) no history of cardiovascular, neurological, or psychiatric disorders; and (4) ability to communicate independently and understand the study procedures. Exclusion criteria were as follows: (1) history of arrhythmia or cardiac disease; (2) current treatment for an anxiety disorder or use of medication that could affect HR responses; (3) failure to comply with restrictions on caffeine, nicotine, alcohol, or vigorous exercise within the 24 hours preceding the experiment; and (4) inability to complete or need to terminate the pressure pain procedure. These criteria were established on the basis of reports that anxiety and stress may influence HR responses (Julian, 2011;Kim et al., 2018;Chalmers et al., 2014). Sample size was estimated using G*Power version 3.1.9.7. Because the primary outcome of this study was the difference in HR across the baseline, pain stimulation, and recovery phases, the sample size was primarily calculated based on a repeated-measures ANOVA. With a significance level of α=.05, statistical power of 1−β=.80, and a medium effect size, the minimum required sample size was calculated to be 24. Considering possible dropouts and missing data, a total of 30 participants were planned for recruitment. Correlation and multiple regression analyses were performed as secondary analyses to examine whether pain intensity independently predicted HR change after controlling for state anxiety.

3. Measurement and experimental instruments

1) Pain intensity assessment (Numeric Rating Scale, NRS)

Pain intensity was assessed using the Numeric Rating Scale (NRS). Participants were instructed that 0 indicated “no pain” and 10 indicated “the worst pain imaginable,” and they were asked to report their pain intensity as a number immediately after the pressure stimulation. The NRS is known to have high applicability and good validity for assessing pain intensity in adults (Hjermstad et al., 2011;Hawker et al., 2011;Ferreira-Valente et al., 2011). Previous research has also reported excellent test–retest reliability for the NRS, with an intraclass correlation coefficient of 0.95 in adults with knee osteoarthritis (Alghadir et al., 2018). In this study, the NRS was obtained only once immediately after stimulation in order to directly reflect the subjective intensity of experimentally evoked pressure pain while minimizing measurement interference caused by repeated questioning during the stimulus.

2) State anxiety assessment (State-Trait Anxiety Inventory-State, STAI-State)

State anxiety was assessed using the State form of the State-Trait Anxiety Inventory (STAI-State) developed by Spielberger. The STAI-State is a widely used self-report instrument designed to measure the tension, worry, and anxiety that a participant feels “at this moment.” It consists of 20 items, with total scores ranging from 20 to 80; higher scores indicate greater state anxiety. Previous validation research has reported excellent internal consistency and good test–retest reliability for the STAI-State, with Cronbach’s α = 0.93 and an intraclass correlation coefficient of 0.80 (Gustafson et al., 2020). In the present study, state anxiety was measured before pain stimulation to distinguish the influence of pain from that of anxiety in the interpretation of HR responses, and it was subsequently used as a covariate in the analyses.

3) Heart rate measurement

HR was measured using a chest-strap HR sensor, the Polar H10 (Polar Electro Oy, Kempele, Finland) (Figure 1). The sensor was worn horizontally around the thorax just below the chest and adjusted so that the sensor unit was centered anteriorly. This positioning was intended to ensure stable skin contact and consistent signal collection. Data were collected using the Polar Flow app (Polar Electro Oy, Kempele, Finland). Participants remained in this setup while continuous HR data were recorded during the baseline, pain stimulation, and recovery phases. HR data recorded during each phase were summarized as mean values and used for analysis. Mean HR was used to represent the overall cardiovascular response during each phase and to allow consistent comparison among the baseline, pain stimulation, and recovery phases. Maximum HR was not used as the primary HR variable because it may be more sensitive to transient peaks, movement-related fluctuations, or signal artifacts during short-term stimulation. In addition, posture, time of measurement, and laboratory environment were kept as constant as possible in order to minimize external factors that could affect HR responses. Selection of the device was based on recent evidence showing the validity of the Polar H10 for HR and RR interval measurements compared with ECG (Schaffarczyk et al., 2022).

Figure 1

Experimental devices used in this study.

• (A): Digital pressure algometer used for experimentally evoked musculoskeletal pain.

• (B): Chest-strap heart rate sensor used for heart rate measurement.

4) Pressure pain induction device (Digital Pressure Algometer)

Experimentally evoked musculoskeletal pain was induced using a digital pressure algometer, the FPX 25 Algometer (Wagner Instruments, Greenwich, CT, USA) (Figure 1). The stimulation site was standardized to the dominant forearm flexor muscle belly. This site was selected because mechanical pressure can be applied relatively consistently there and because, compared with bony prominences or tendinous regions, it is more likely to reflect pain responses of muscle tissue directly. The algometer was applied perpendicularly to the skin by the same trained examiner. Pressure was increased manually at a target rate of approximately 30 kPa/s, as consistently as possible (Suzuki et al., 2023;Deodato et al., 2022). To account for individual differences in pain sensitivity while maintaining a standardized procedure, compression was terminated when the participant first reported a clear but tolerable pain sensation. Therefore, the duration of pressure stimulation was not fixed. The pressure pain stimulation was standardized procedurally by keeping the stimulation site, examiner, direction of force application, target rate of pressure increase, and predefined verbal stopping criterion consistent across participants, rather than by applying the same absolute pressure or identical stimulation duration to all participants. Digital pressure algometry is regarded as an appropriate tool for musculoskeletal experimental pain research because it can provide standardized mechanical pain stimulation (Antonaci et al., 1998;Chesterton et al., 2007;Kinser et al., 2009;Liew et al., 2021).

Figure 2

Experimental measurement setup used in this study.

• (A): Application of the digital pressure algometer to the dominant forearm flexor muscle belly for experimentally evoked musculoskeletal pain.

• (B): Placement of the chest-strap heart rate sensor for heart rate measurement.

4. Experimental procedure

All measurements were performed in a fixed chronological order. Upon arrival at the laboratory, participants were first informed of the study purpose, experimental procedures, expected discomfort, and potential risks, and written informed consent was obtained. Participants then rested quietly in a seated position for 10 minutes to stabilize physiological responses. After the resting period, general characteristics were recorded, and the STAI-State questionnaire was completed before pain stimulation. Next, the Polar H10 chest-strap HR sensor (Polar Electro Oy, Kempele, Finland) was attached horizontally around the thorax just below the chest, and baseline HR was recorded continuously for 5 minutes. After baseline measurement, experimentally evoked pressure pain was induced by applying the FPX 25 Algometer (Wagner Instruments, Greenwich, CT, USA) perpendicularly to the dominant forearm flexor muscle belly. HR was recorded continuously during the pressure stimulation phase. The stimulation was terminated when the participant reported a clear but tolerable pain sensation, and pain intensity was assessed immediately after stimulation using the NRS. After pain assessment, HR was recorded continuously for an additional 3 minutes during the recovery phase. Thus, HR was measured repeatedly across three phases: baseline, pain stimulation, and recovery. The recorded HR data were extracted and organized, and the mean HR for each phase was calculated for analysis. HR change was calculated as the mean HR during pain stimulation minus the mean HR during baseline. Before the experiment, caffeine, nicotine, alcohol, and vigorous exercise were restricted for a specified period, and all measurements were conducted at a similar time of day and under similar environmental conditions to minimize nonspecific external factors that could influence HR responses.

5. Data analysis

All data were analyzed using SPSS Statistics (version 25.0; IBM Corp., Armonk, NY, USA). General characteristics were presented as means and standard deviations or as frequencies and percentages. The Shapiro–Wilk test was used to assess the normality of each variable. Changes in HR across baseline, pain stimulation, and recovery were analyzed using repeated-measures analysis of variance (ANOVA), and Bonferroni post hoc tests were applied. HR change was calculated as the mean HR during pain stimulation minus the mean HR during baseline. The mean HR during the pain stimulation phase was selected as the primary stimulation-related HR variable to reflect the average physiological response across the stimulation period rather than a transient peak response. The relationships among pain intensity, state anxiety, and HR change were examined using Pearson correlation analysis. Finally, multiple regression analysis was performed to determine whether pain intensity independently predicted HR change after controlling for state anxiety. The significance level was set at α=.05.

Ⅲ. Results

1. General characteristics of the participants

The mean age of the 30 participants was 27.43±4.62 years, mean height was 169.18±8.11 cm, and mean body weight was 66.51±11.64 kg. Mean body mass index was 23.11±2.94 kg/m², and 15 participants were male and 15 were female. Resting HR was 71.87±7.54 bpm, the STAI-State score was 39.63±8.21 points, and the NRS pain intensity immediately after pressure stimulation was 5.97±1.31 points (Table 1).

2. Changes in heart rate following pain stimulation

Changes in HR following pain stimulation are presented in Table 2. Baseline HR was 71.87±7.54 bpm, which increased to 80.43±8.92 bpm during pain stimulation and decreased to 74.96±7.88 bpm during recovery. Repeated-measures ANOVA showed a significant difference in HR across time points (F=51.375, p<.001, η_p²=.639) (Table 2). Bonferroni post hoc tests showed that HR during pain stimulation was significantly higher than HR during baseline and recovery, and that HR during recovery remained significantly higher than HR during baseline. These findings indicate that pain stimulation induced an increase in HR and that a certain level of physiological response persisted even after the stimulus had ended.

3. Relationships among pain intensity, state anxiety, and heart rate change

Correlation analysis showed that NRS pain intensity was positively correlated with HR change (r=.422, p<.05), and that STAI-State score was also positively correlated with HR change (r=.536, p<.01). A positive trend was observed between NRS pain intensity and STAI-State score (r=.348) (Table 3). Multiple regression analysis was then conducted to determine whether pain intensity independently predicted HR change after adjusting for state anxiety. The regression model was statistically significant (F=7.274, p=.003), with an overall explanatory power of 35.0% (Adjusted R²=.302). STAI-State score was a significant predictor of HR change (B=0.259, β=.443, p=.012), whereas NRS pain intensity was not significant (B=0.979, β=.267, p=.118) (Table 4). Thus, although HR change showed a simple correlation with pain intensity, that association was no longer significant when state anxiety was considered simultaneously.

Ⅳ. Discussion

The main finding of this study was that HR increased significantly during experimentally evoked musculoskeletal pain, but the relationship between pain intensity and HR change was no longer significant after accounting for state anxiety. Specifically, HR during pain stimulation was significantly higher than HR at baseline and during recovery, indicating that pressure pain stimulation elicited a measurable cardiovascular response. Although NRS pain intensity was positively correlated with HR change in the simple correlation analysis, multiple regression analysis showed that state anxiety, rather than pain intensity, remained a significant explanatory variable for HR change. These findings suggest that HR response during experimentally evoked musculoskeletal pain reflects not only pain-related physiological arousal but also anxiety-related autonomic arousal.

The significant increase in HR during pain stimulation observed in this study is generally consistent with previous experimental pain research. Studies inducing heat pain or pressure pain in healthy individuals have reported increases in HR accompanying pain perception, and relationships between stimulus intensity and physiological arousal have also been suggested (Tousignant-Laflamme et al., 2005;Loggia et al., 2011). A critical review of autonomic responses to experimental pain further noted that painful stimulation can evoke arousal responses such as increases in HR and skin conductance, although the magnitude and direction of these responses may vary depending on stimulus modality, timing of measurement, and individual differences (Kyle & McNeil, 2014). In the present study, HR during pain stimulation was significantly higher than HR during baseline, and HR during recovery did not fully return to baseline, indicating a pattern consistent with previous findings that experimental pain induces transient physiological arousal.

However, an increase in HR does not necessarily indicate a direct measure of pain intensity. Studies in emergency departments and intensive care units have reported that the association between self-reported pain and vital signs is weak or clinically insufficient, and repeated measurements have suggested that changes in HR do not correspond well to changes in pain (Marco et al., 2006;Bossart et al., 2007;Arbour et al., 2014;Daoust et al., 2016). A large emergency department study similarly reported that the relationship between self-reported pain and HR was small and limited (Dayoub & Jena, 2015). In the present study, NRS pain intensity and HR change were significantly correlated in the simple correlation analysis, but the association became nonsignificant after adjustment for state anxiety. This finding supports the interpretation that although HR may be sensitive to pain, it should not be regarded as an index that independently represents pain intensity.

The finding that state anxiety remained a significant explanatory variable for HR change is particularly important. State anxiety reflects momentary tension and worry, and evidence that anxiety and stress influence cardiovascular and autonomic responses has been reported relatively consistently (Julian, 2011;Kim et al., 2018;Chalmers et al., 2014). Colloca et al. (2006) reported that autonomic responses during pain anticipation and pain stimulation may show repeatable patterns, suggesting that HR responses in pain-inducing situations may be shaped by both anticipatory anxiety and the actual stimulus. In addition, individuals with high anxiety sensitivity have shown more pronounced psychological and biological responses during the cold pressor test, and systematic reviews addressing experimental pain, musculoskeletal pain, and HRV have concluded that autonomic responses should be understood within the interaction between pain itself and emotional state (Dodo & Hashimoto, 2017;Koenig et al., 2014;Forte et al., 2022;Rampazo et al., 2024). Taken together, it is reasonable that state anxiety emerged as a stronger explanatory variable than pain intensity in the present study.

The use of pressure algometry allowed experimentally evoked musculoskeletal pain to be induced under a procedurally standardized condition, and previous studies have supported the reliability and usefulness of pressure algometry in healthy adults (Chesterton et al., 2007;Kinser et al., 2009;Liew et al., 2021). However, because the pressure stimulation was individualized according to a predefined verbal stopping criterion rather than by applying identical absolute pressure to all participants, the NRS values should be interpreted as subjective pain intensity under a standardized procedure rather than as responses to the same physical stimulus.

The clinical implication of this study is that HR should be interpreted as an adjunctive rather than a substitute indicator for musculoskeletal pain assessment. HR may increase in response to painful stimulation and therefore provide clinicians with additional information regarding the patient’s level of physiological arousal. However, because that response reflects not only pain intensity but also the influence of state anxiety, it is not appropriate to judge the intensity or authenticity of pain on the basis of HR alone. Thus, when self-report is possible, the patient’s pain report should remain the primary criterion for assessment, and HR should be used only as a supplementary source of information (Hjermstad et al., 2011;Hawker et al., 2011;Herr et al., 2019).

This study has several limitations. First, because it was a one-group repeated-measures study conducted in healthy young adults, its findings cannot be directly generalized to patients with actual musculoskeletal pain. Second, because stimulation was limited to a single site—the dominant forearm flexor muscle belly—interpretation should not be extended uncritically to other muscle regions or to clinical chronic pain conditions. Third, because only HR was used as a physiological variable, more detailed autonomic response characteristics could not be identified. Fourth, because the design did not include a control condition, the relative contributions of pain itself, situational tension, expectation, and emotional arousal could not be more rigorously separated. Future studies should include non-pain control conditions, recruit individuals with actual musculoskeletal pain, and measure additional physiological indicators beyond HR. Fifth, this study used mean HR rather than maximum HR during the pain stimulation phase. Although mean HR was selected to represent the overall cardiovascular response during each phase and to reduce the influence of transient artifacts, it may have attenuated short-lasting peak HR responses to pain stimulation. Therefore, future studies should consider analyzing both mean HR and maximum HR to more fully characterize cardiovascular responses to experimentally evoked pain. Sixth, the pressure stimulation duration was not identical across participants because stimulation was terminated when each participant reported a clear but tolerable pain sensation. Although this procedure was used to account for individual differences in pain sensitivity, differences in stimulation duration may have influenced the mean HR during the pain stimulation phase. Future studies should record and analyze stimulation duration or use a fixed-duration stimulation protocol to better control its potential influence on HR responses. It would also be valuable to incorporate variables such as anticipation, uncertainty, and sex differences into study designs to allow more refined interpretations of experimental pain and autonomic responses (Tousignant-Laflamme & Marchand, 2006;Koenig et al., 2014;Forte et al., 2022).

In summary, this study confirmed that HR response can increase during experimentally evoked musculoskeletal pain, but also demonstrated that the response is influenced by state anxiety. Therefore, HR is better interpreted as an adjunctive physiological indicator that reflects emotional state as well as pain-related arousal rather than as a direct indicator of pain.

Ⅴ. Conclusion

Experimentally evoked musculoskeletal pain induced an increase in HR, and HR change was significantly correlated with pain intensity. However, when state anxiety was considered simultaneously, the independent explanatory value of pain intensity was no longer significant. Therefore, HR should be interpreted not as a direct indicator of pain but as an adjunctive physiological indicator that also reflects state anxiety.