Impact of osteopathic tests on heart rate and heart rate variability: an observational study on osteopathic students

Population

A total of 51 participants, recruited on a voluntary basis, were selected from osteopathy students (first to fifth year). An intervention was carried out before a class to introduce the study. The project was explained to them as an HR study, without mentioning the listening tests so that they would not know the different groups. The noninclusion criteria were also presented during this intervention. Several factors can influence HR and HRV, potentially affecting the results:

1. Consumption of coffee or energy drinks in the past 24 h [18], [28], [29], [30].

2. Participation in sports within the last 24 h [18], 31], 32].

3. Smoking any type of cigarette, including e-cigarettes, in the last 20 min [31], [33], [34], [35].

4. Presence of known cardiac pathology, because treatment may influence HRV measurements [36].

5. Having an acute illness (e.g., cold, fever), which contraindicates osteopathy [37].

6. Cardiac and noncardiac comorbidities, because their treatment may affect HR [38].

7. The use of antihypertensive, antidepressant, antipsychotic, or beta-blocker medications within the last 48 h, which can impact HR and HRV [18], 39], 40].

Volunteers were contacted by email or phone, and an appointment was scheduled. Students were asked to complete an informed consent form, according to French regulation. They also completed a document to affirm that they did not present a noninclusion criterion.

If the participant did not provide informed consent or had a noninclusion criterion, he was not selected for the study. For those selected, tests were carried out in a single session. Participants with artifacts rates that were too high during the software analysis were excluded. The percentage of ectopic beats considered too high for HRV measurements was greater than 1 %, and greater than 0.1 % for rMSSD [41], 42].

Randomization

The repartition between the osteopathic test group (OTG), LPG, and CG were done by blocks of six in Microsoft Excel. Participants remained unaware of the existence of other groups to reduce bias. Demographic information for each group is presented in Table 1.

Each test session involved three investigators: one performed the tests, another reproduced the protocol, and a third conducted the measurements. Investigators rotated roles randomly between the participants to further minimize bias.

Protocol

The protocol was conducted in a room with controlled ambient temperature to prevent environmental variations that could influence HRV [41].

The protocol for each group, with the number of participants at each stage, is summarized in a flow chart, shown in Figure 1. The details of each test session are then explained in Figure 2 for all of the different groups. Each test session is described for the first practitioner, and the second one reproduces the same protocol. The test procedures for each group are summarized below:

Figure 1:

Flow chart for the observational study. CG, control group; HRV, heart rate variability; LPG, light pressure group; OTG, osteopathic test group.

Figure 2:

Test protocols for the different groups. (A) Protocol for the osteopathic test group session. (B) Protocol for the LPG session. (C) Protocol for the CG session. CG, control group; HR, heart rate; LPG, light pressure group.

Heart rate and heart rate variability measures

Participants were asked to remain still and silent throughout the measurements, because movement and speech can distort HRV analysis [43]. They lay on their back and rested for 1 min before the measurements began. HR and HRV measurements were then taken over a 5-min period. The tests and light pressures applied to the participants were always conducted with them in the supine position. It has been shown that body inclination increases HR [17], which is why no standing or sitting tests were performed.

For each group, a POLAR H10 chest strap was fitted by the first practitioner over the participant’s xiphoid process. The size of the strap was adjusted for each participant so that the sensor made contact with the skin. This strap enables noninvasive HR and HRV data collection for the student. The suitability of the strap for use was evaluated against electrocardiogram recordings, and it was recommended for practitioners [42]. Simultaneously, data were collected utilizing the Elite HRV mobile application, software designed for the chest strap [44]. The collected data were then analyzed utilizing the Kubios HRV software, which allows the study of HR, rMSSD, and the LF/HF ratio [45]. The validity and reliability of the three tools utilized were confirmed [19], 44], 46].

Statistical analysis

The first stage of the statistical analysis was to define if the values follow a normal distribution. The Shapiro–Wilk test was utilized to study the normality of the values of each measurement criterion. The results show that the HR values follow a normal distribution, although the rMSSD and LF/HF ratio values do not follow a normal distribution.

To begin the statistical analysis, it was necessary to compare the first 30 s of each group, for the three selected criteria, to make sure that there is no difference between the three groups at the beginning of the test session. A Student’s t-test allowed a comparison of the FC values between the three groups. Because the data are independent, a Mann–Whitney U test was utilized to compare the rMSSD and LF/HF ratio of the different groups.

To compare the different averages calculated before and after the protocol, a comparison of the means tests were carried out. The following tests were utilized for paired data. A Student’s t-test was utilized to compare the HR averages. The Wilcoxon signed-rank test was chosen to compare the means of the rMSSD and the LF/HF ratio. The significance threshold of the tests chosen is 5 %, or α=0.05.

Population

Fifty-one participants were selected for the study. They were equally and randomly allocated to the osteopathic test, LPG, or CG. Each group was thus composed of 17 students, from the first to the fifth year of study (1Y to 5Y). After data analysis with the Kubios software, three participants in the LPG group were removed from the study because their values showed a percentage of artifacts greater than 5 %.

Main results

After comparing the first 30 s between each group, no significant difference was found. The p values between OTG and CG are p=0.293 for HR, p=0.158 for rMSSD, and p=0.811 for the LF/HF ratio. Between the OTG and LPG, they are p=0.315 for HR, p=0.861 for rMSSD, and p=0.799 for the LF/HF ratio. Concerning the last two groups, LPG and CG, the p values are p=0.968 for HR, p=0.063 for rMSSD, and p=0.591 for LF/HF ratio. Because there were no difference between the groups from the start, the rest of the statistical analysis could be carried out.

To compare the ANS markers before and after the test sequence, measurements were taken in the first 30 and last 30 s of each test session. Each criterion mean with their standard deviation (SD) are represented on Figure 3.

Figure 3:

A histogram of the means of the different metrics before and after the protocol. (A) Heart rate before and after the protocol for each group. (B) rMSSD before and after the protocol for each group. (C) LF/HF ratio before and after the protocol for each group. CG, control group; LF/HF, low-frequency/high-frequency; LPG, light pressure group; OTG, osteopathic test group; rMSSD, root mean square of successive differences; SD, standard deviation.

Figure 3A shows the HR mean before and after the protocol for each group. Figure 3B represents the rMSSD means before and after protocol in the three groups. The same goes for Figure 3C, but with the LF/HF ratio mean. The values shown on this figure are represented below for each group.

Interpretation

The results indicate that there were no significant changes in HR or HRV metrics (rMSSD and LF/HF ratio) following the osteopathic listening tests or light pressure application. Therefore, the hypothesis that these tests could influence ANS markers is not supported by the data. The findings suggest that the selected osteopathic listening tests do not have a measurable therapeutic effect on HR or HRV. The results suggest that these tests remain diagnostic tools utilized by osteopaths to detect somatic dysfunctions rather than interventions that produce therapeutic effects on the ANS. They do not induce significant changes in HR and HRV, and thus do not have a measurable physiological impact on the markers we selected.

Previous studies have shown that OMT can influence the ANS, especially by modulating the sympathovagal balance through HRV metrics like the LF/HF ratio [23]. Another study proposes the HRV as a useful method for developing simulated controls during studies on osteopathic manipulations [17]. While OMT has been associated with changes in HR and HRV, the results of our study suggest that listening tests themselves do not elicit similar physiological effects. It would be worthwhile to investigate whether comparing listening tests to actual OMTs would yield different results. Future studies could focus on treatment techniques rather than just diagnostic tests to explore their potential effects on the ANS. Regarding the LPG, our data show that a simple application of light pressure (utilizing a rice bag without therapeutic intent) did not lead to any significant changes in HR, rMSSD, or LF/HF ratio. This suggests that touch alone, when not combined with a therapeutic intent, does not appear to influence the ANS.

The lack of therapeutic effect observed in the osteopathic listening tests can be attributed to their primary diagnostic purpose. These tests are designed to detect somatic dysfunctions through palpation and are not intended to provide therapeutic interventions or stimulate physiological changes. Unlike OMT, which involves intentional and targeted interventions to influence physiological processes, the listening tests employ light touch primarily for assessment purposes. Furthermore, the light pressure applied during the listening tests may not constitute a sufficient stimulus to elicit a measurable autonomic response. Studies that have observed changes in HRV following osteopathic treatments often involve more dynamic manipulations that engage the musculoskeletal and nervous systems to a greater extent. In contrast, the listening tests do not involve sustained or intentional therapeutic interventions, which could explain their lack of impact on ANS markers such as HR and HRV. Another factor is the role of intentionality in therapeutic touch. Previous research suggests that the therapeutic intent behind an intervention can influence its physiological effects. In this study, the tests were explicitly diagnostic, and the absence of therapeutic intent may have contributed to the lack of observable changes in HR and HRV. This finding is supported by the results of the LPG, in which nontherapeutic touch also failed to produce significant effects on ANS markers.

These findings emphasize the need for future studies to distinguish between diagnostic and therapeutic interventions in osteopathy. Investigating the physiological effects of treatment techniques, rather than the diagnostic tests, may provide more insight into the mechanisms by which osteopathic interventions influence the ANS.

Limitations

This study has several limitations. The participants were osteopathy students, who were familiar with listening tests and were aware of their own group’s procedures, but not those of the other groups. Their prior experience with these tests may have influenced their perception of touch compared to the general population. As a result, our sample may yield different results from those that could be expected in the general population. Furthermore, because the participants were not seeking treatment, their readiness to receive touch in a therapeutic context could have been affected [47].

Another limitation is that the practitioners were students. As the quality of palpation improves with training [47], [48], [49], it is expected that the quality of touch would differ between practitioners and, moreover, between students and experienced osteopaths. Investigating whether practitioners of different experience levels, such as newly graduated osteopaths or students from various years, produce different physiological effects could provide useful insights.

The testing protocol followed a fixed sequence (knee, digestive area, and skull), which may have influenced the outcomes. Testing these sequences in different orders could potentially yield different results and insights.

Generalizability

This study is repeatable and reproducible, because the protocol and hand positions for the listening tests are easily replicable by those trained in osteopathy. However, this study could be expanded by exploring other markers of the ANS to provide a more comprehensive understanding of the potential effects of listening tests.

HRV is a simple, non-invasive method for measuring sympathovagal balance [50]. By exploring additional HRV metrics, valuable insights could be gained, because HRV is easily measurable and carries minimal risk for participants. Furthermore, a more thorough investigation of osteopathic listening tests is warranted. This could include assessing other physiological markers beyond the ANS to ensure that there are no unintended physiological effects that could be attributed to these tests as treatments. Such examinations could serve as important reference points for clinical trials. It would also be interesting to generalize this study to other osteopathic tests. Different physiological markers may yield different results, and perhaps other osteopathic tests would demonstrate modifications in these markers. The statistical analysis part could also be modified by adding other data as confidence intervals (CIs), or other statistical tests that could bring more information.

Finally, the small sample size (17 participants in each of the three groups) may limit the generalizability of the findings. Because this is an observational study presenting preliminary results, further investigation with a larger sample size would be an important next step to confirm or challenge these conclusions.