HOW STABLE IS BREATHING AT RESONANCE FREQUENCY? A TEST-RETEST STUDY ON INDIVIDUAL VARIABILITY AND ITS ASSOCIATIONS WITH EMOTION REGULATION AND LIFESTYLE

HOW STABLE IS BREATHING AT RESONANCE FREQUENCY? A TEST-RETEST STUDY ON INDIVIDUAL VARIABILITY AND ITS ASSOCIATIONS WITH EMOTION REGULATION AND LIFESTYLE | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 14 December 2025 V1 Latest version Share on HOW STABLE IS BREATHING AT RESONANCE FREQUENCY? A TEST-RETEST STUDY ON INDIVIDUAL VARIABILITY AND ITS ASSOCIATIONS WITH EMOTION REGULATION AND LIFESTYLE Authors : Jente Depoorter 0000-0003-2296-2625 [email protected] , Kristof Hoorelbeke , Marie-Anne Vanderhasselt , and Rudi De Raedt Authors Info & Affiliations https://doi.org/10.22541/au.176571010.03910095/v1 418 views 202 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Introduction. An individual’s resonance frequency (RF) is considered the optimal breathing rate for eliciting cardiovascular and autonomic benefits and is often used to guide home breathing practice. However, evidence on the stability of RF over time is scarce. Capdevila et al. (2021) reported poor one-week test-retest reliability in a small sample. The present study aimed to replicate and extend these findings in a larger community sample while adhering to a RF determination protocol [(Fisher & Lehrer, 2022)](#ref-0013). Methods. Fifty-one participants completed a one-week test-retest assessment of RF. Results. Group-level RF remained stable, but individual-level stability was low (ICC = 0.18), with approximately 25% of participants showing differences larger than 0.5 breaths per minute. Trend-level associations indicated that higher physical activity and more use of acceptance and self-support emotion regulation skills were linked to smaller RF differences. Conclusions. These findings suggest that RF is not uniformly stable across individuals, raising questions about the necessity and clinical relevance of repeated or individualized RF assessment. Future research should examine for whom RF remains stable and whether tailoring breathing rates provide measurable physiological or clinical benefits. HOW STABLE IS BREATHING AT RESONANCE FREQUENCY? A TEST-RETEST STUDY ON INDIVIDUAL VARIABILITY AND ITS ASSOCIATIONS WITH EMOTION REGULATION AND LIFESTYLE Jente Depoorter a* , Kristof Hoorelbeke a , Marie-Anne Vanderhasselt b , Rudi De Raedt a a Department of Experimental, Clinical and Health Psychology, Ghent University, Belgium b Department of Head and Skin, Ghent University, Belgium ORCID authors: Jente Depoorter: https://orcid.org/0000-0003-2296-2625 Kristof Hoorelbeke: https://orcid.org/0000-0002-8269-0441 Marie-Anne Vanderhasselt: https://orcid.org/0000-0002-4045-1055 Rudi De Raedt: https://orcid.org/0000-0001-6781-4808 Contact information authors: *Corresponding author: Jente Depoorter: [email protected] Kristof Hoorelbeke: [email protected] Marie-Anne Vanderhasselt: [email protected] Rudi De Raedt: [email protected] ABSTRACT Introduction. An individual’s resonance frequency (RF) is considered the optimal breathing rate for eliciting cardiovascular and autonomic benefits and is often used to guide home breathing practice. However, evidence on the stability of RF over time is scarce. Capdevila et al. (2021) reported poor one-week test-retest reliability in a small sample. The present study aimed to replicate and extend these findings in a larger community sample while adhering to a RF determination protocol (Fisher & Lehrer, 2022). Methods. Fifty-one participants completed a one-week test-retest assessment of RF. Results. Group-level RF remained stable, but individual-level stability was low (ICC = 0.18), with approximately 25% of participants showing differences larger than 0.5 breaths per minute. Trend-level associations indicated that higher physical activity and more use of acceptance and self-support emotion regulation skills were linked to smaller RF differences. Conclusions. These findings suggest that RF is not uniformly stable across individuals, raising questions about the necessity and clinical relevance of repeated or individualized RF assessment. Future research should examine for whom RF remains stable and whether tailoring breathing rates provide measurable physiological or clinical benefits. KEYWORDS Resonance frequency, breathing, heart rate variability, emotion regulation, lifestyle factors INTRODUCTION Heart Rate Variability (HRV) refers to the natural fluctuations in the time intervals between consecutive heartbeats, reflecting the dynamic balance of the autonomic nervous system (Malik et al., 1996). Since a healthy heart should not work as a metronome (Shaffer et al., 2014), greater variability between beats indicates adaptive responses to situational demands (Balzarotti et al. 2017). Higher HRV is generally associated with greater physiological flexibility, better stress adaptation and enhanced emotion regulation, whereas lower HRV has been linked to stress, cardiovascular risk and difficulties in managing emotional responses (Beauchaine & Thayer, 2015; Mather & Thayer, 2018). Furthermore, HRV is modulated by lifestyle factors, including sleep quality and duration, Body Mass Index (BMI), and physical activity (Damoun et al., 2024; Sammito et al., 2024). A simple and non-invasive way to increase HRV is through slow-paced breathing (Laborde et al., 2022; Vanderhasselt & Ottaviani; 2022). Heart Rate Variability Biofeedback (HRVB) builds on this technique by using real-time visual or auditory feedback to help individuals breathe at their resonance frequency (RF), an individual’s breathing rate to optimally increase HRV by synchronizing with the heart’s natural rhythm, producing large-amplitude blood pressure oscillations and, over time, can enhance baroreflex sensitivity (Lehrer et al., 2000). As a result, HRVB has been shown to enhance effective regulation of physiological responses (Lehrer et al., 2013). Moreover, meta-analytic evidence indicates that HRVB reduces stress and anxiety, while also improving emotional and physical health (Goessl et al., 2017; Lehrer et al., 2020). A commonly used protocol to identify RF is the stepped protocol from Lehrer et al. (2000). In this method, individuals breathe at several fixed frequencies for two minutes each. After every two minutes, the breathing rate is adjusted to a slower pace. As such, the participants breathe for 12 minutes at six different paces (respectively 6.75, 6.25, 5.75, 5.25, 4.75 and 4.25 breaths per minute (bpm)). RF is then determined based on multiple criteria, such as Low Frequency HRV, amplitude of the HRV and average peak-to-trough amplitude. More recently, Fisher and Lehrer (2022) updated the protocol. In the sliding window method, the breathing rate is consistently slowed down over 15 minutes, using a visual breathing pacer, from 6.75 bpm to 4.25 bpm. In this protocol, RF is determined using a single criterion (i.e. peak-trough amplitude). This new sliding protocol has shown to be equally accurate as the older stepped protocol, while providing greater consistency in the determination of RF as it avoids ambiguity in selecting the final RF. Moreover, the sliding window protocol was also preferred by participants, who reported it as more comfortable than the stepped protocol (Fisher & Lehrer, 2022). To our knowledge, only one study examined the stability of RF. Capdevila et al. (2021) found RF to be unstable in a one-week test-retest reliability study. Although the mean RF remained stable at the group level, 14 of the 21 participants showed a different RF at retest compared to the initial assessment. However, their sample size was relatively small, and they did not fully adhere to the RF-determination protocols as defined by Lehrer et al. (2000) or Fisher and Lehrer (2022). As such, the main aim of the current study was to replicate the findings of Capdevila et al. (2021) regarding the stability of RF over a one-week test-retest interval. To extend the original study, we recruited a larger, community sample and adhered strictly to the RF determination protocol as proposed by Fisher and Lehrer (2022). Based on Capdevila et al. (2021), we expected that RF would not remain entirely stable over time. In addition, the current study aimed to explore the association between RF (in)stability, emotion regulation and lifestyle factors to identify potential determinants of RF instability. METHOD 2.1 Ethics and participants The study was approved by the Ethics Committee of the Faculty of Psychology and Educational Sciences of Ghent University (2023-110) and conducted in accordance with the Declaration of Helsinki. All participants gave their informed consent. The study was preregistered on the Open Science framework (OSF; https://osf.io/dbe3n). Participants received €20, a psychoeducation video on stress and breathing (see Supplementary Materials), and their individual RFs. Recruitment occurred via social media. Following Laborde et al. (2017), participants with cardiovascular diseases or asthma, smokers and pregnant women were excluded. Furthermore, only participants aged between 18 and 65 years old could participate. A priori power analysis based on the results of Capdevila et al. (2021) indicated that 50 participants were required to estimate an ICC of 0.5 with a 95% confidence interval. A total of 62 participants were recruited. Two withdrew before the second session due to illness, and nine were excluded (three unusable physiological data, one protocol non-compliance, five breathing protocol non-adherence), resulting in a final sample of 51 participants. For an overview of sample characteristics, we refer to Table 1. Table 1 Sample Characteristics (N = 51) Age (M ( SD )) 35.20 years ( 12.03 ) Gender (N, %) Men (11, 21.57%), Women (39, 76.47%), Other (1, 1.96%) BMI (M ( SD )) 23.57 ( 3.49 ) Ethnicity (N, %) Caucasian (51, 100%) Employment (N, %) Student (14, 27.45%), Employed full-time (26, 50,98%), Employed part-time (8, 15.69%), Unemployed (2, 3.92%), Occupationally disabled (1, 1.96%) Sleep (M ( SD ))) 7.69 hours per day ( 0.91 ) Physical activity (M ( SD )) 3.77 hours per week ( 2.89 ) Prior experience with breathing exercises (N, %) No (22, 43.14%), Yes (29, 56.86%; e.g. yoga, box breathing) Amount of exercise (M( SD )) a 3.67 times per week ( 5.07 ) Exercise time (M ( SD )) a 39.21 minutes per week ( 46.56 ) Breathing exercises between both sessions (N, %) No (26, 43.14%), Yes (26, 56.86%) Amount of exercise between sessions (M( SD )) b 3.35 times ( 2.86 ) Exercise time between sessions (M( SD )) b inutes ( 23.91 ) Note. a These values are based on the subgroup that indicated having experience with breathing, b These values are based on the subgroup that indicated having exercised with abdominal breathing between sessions. 2.2 Procedure Participants were invited to the lab twice and provided written informed consent at the start of the first session, after which participants’ eligibility was confirmed. Eligible participants then filled in demographic questions, after which they were asked to remain seated in the same posture for seven minutes, of which the last five minutes served as a baseline measurement for all psychophysiological variables. Subsequently, participants filled in Visual Analogue Scales (VAS) about their current mood. Next, abdominal breathing was explained to all participants. Once comfortable with abdominal breathing, participants slowed their pace to a personally relaxing pace and continued for 10 minutes (data on this will be reported in another paper). Afterwards, they reported any use of alternative techniques and completed questionnaires on emotion regulation and resilience. This period served as a wash-out to minimize carry-over effects of the breathing exercise on the subsequent RF determination. After filling out the questionnaires, the RF determination started. Participants were shown how the exercise would be and were told that it would last 15 minutes. Participants were instructed to closely follow the pacer, as this was essential for accurate RF determination. Finally, participants were asked about possible negative effects and how difficult they found it to follow the breathing pace and if they had any comments on the session. The second session took place exactly one week later and followed the same procedure as the first, except that demographic questions were replaced by questions about participants’ practice with abdominal breathing between sessions. To avoid time-of-day effects, participants were scheduled at the same hour on both sessions. Materials Questionnaires Demographic information was collected to provide an accurate sample description: age, gender, self-reported height and weight (used to calculate BMI), ethnicity, and employment status. Furthermore, average sleep (hours per day) and physical activity (hours per week) were assessed. Lastly, data was collected on participants’ experience with breathing exercises (type and frequency). Self-reported mood states were assessed at the beginning of each session. Participants were asked to rate how tense, happy, anxious and angry they were at that time on a Visual Analogue Scale (VAS) from 0 (not at all) to 100 (very much). At the end of every session, participants reported perceived difficulty in following the breathing pacer during RF determination on a VAS from 0 (not at all) to 100 (very much). Participants were also asked to report any adverse effects during the 15-minute breathing period. Emotion regulation was measured using the short version of the Cognitive Emotion Regulation Questionnaire (CERQ-short; Garnefski & Kraaij, 2006) and the EMO-CHECK (ERSQ; Berking, 2017). The CERQ-short is an 18 item self-report questionnaire that assesses cognitive emotion regulation strategies and is divided into nine subscales: self-blame, other-blame, rumination, catastrophizing, positive refocusing, planning, positive reappraisal, putting into perspective and acceptance. All items must be rated on a 5-point scale from 1 (almost never) to 5 (almost always). Cronbach’s alpha values for all subscales and both sessions can be found in Table 2. The EMO-CHECK is the Dutch version of the Emotion Regulation Skills Questionnaire (Grant et al., 2018). This 27-itemself-report questionnaire assesses perceived emotion regulation skills over the past two weeks on a 5-point scale from 0 (not at all) to 4 (almost always). There are 9 subscales: awareness, sensations, clarity, understanding, acceptance, tolerance, confrontation, self-support, and modification. Table 2 presents Cronbach’s alpha values for all subscales across both sessions. The 25 items Dutch version of the Connor-Davidson Resilience Scale (CD-RISC; Connor & Davidson, 2003) was used to assess self-reported resilience. Scores are summed, yielding a total score ranging from 0 to 100, with higher scores reflecting greater resilience. Each item has to be rated on a scale from 0 (not true at all) to 4 (true nearly all of the time). Internal consistency (Cronbach α ) for all subscales in both sessions is reported in Table 2. Table 2 Descriptive statistics and Internal Consistency of questionnaires. M ( SD ) Cronbach’s alpha M (SD) Cronbach’s alpha CERQ Self-blame 2.47 ( 0.86 ) .84 2.50 ( 0.72 ) .67 Other-blame 1.77 ( 0.67 ) .83 1.90 ( 0.67 ) .87 Rumination 3.14 ( 1.04 ) .74 3.09 ( 0.96 ) .82 Catastrophizing 1.81 ( 0.84 ) .81 1.81 ( 0.68 ) .77 Positive refocusing 2.11 ( 0.90 ) .80 2.34 ( 0.90 ) .85 Planning 3.43 ( 0.92 ) .73 3.45 ( 0.95 ) .86 Positive reappraisal 3.22 ( 0.98 ) .66 3.40 ( 0.75 ) .57 Putting into perspective 3.18 ( 1.07 ) .82 3.21 ( 0.96 ) .87 Acceptance 3.20 ( 0.96 ) .83 3.10 ( 0.88 ) .75 EMO-CHECK Awareness 2.46 ( 0.86 ) .90 2.28 ( 0.83 ) .89 Sensations 2.86 ( 0.75 ) .77 2.85 ( 0.73 ) .86 Clarity 2.92 ( 0.75 ) .87 2.82 ( 0.81 ) .87 Understanding 2.98 ( 0.72 ) .85 2.88 ( 0.72 ) .83 Acceptance 2.71 ( 0.67 ) .79 2.80 ( 0.58 ) .78 Tolerance 2.52 ( 0.72 ) .76 2.73 ( 0.66 ) .82 Confrontation 2.75 ( 0.64 ) .75 2.82 ( 0.57 ) .72 Self-support 2.65 ( 0.58 ) .61 2.63 ( 0.50 ) .46 Modification 2.27 ( 0.65 ) .80 2.35 ( 0.56 ) .71 CD-RISC 67.84 ( 10.24 ) .86 68.06 ( 10.63 ) .89 Psychophysiological measurements Autonomic nervous system activity was measured using the Vrije Universiteit Ambulatory Monitoring System device (VU-AMS; De Geus et al., 1995). This device can record both an electrocardiogram (ECG) and impedance cardiography (ICG), allowing retrieval of parasympathetic measures such as HRV indices, as well as respiratory parameters. Three electrodes were placed on participants’ chest for ECG and four electrodes (two on the chest and two on the back) for ICG. Electrode placement is illustrated in Supplemental Figure 1. Resonance Frequency determination An open-source breathing pacer (https://breath.cafe/) was used, which employs a triangular waveform, but remains in the midline of the display. This allows participants to observe their recent breaths and anticipate the upcoming pace. The pacer was configured following Fisher and Lehrer (2022) guidelines: a 15-minute session beginning at 6.75 bpm and ending at 4.25 bpm with the rate adjusted after every two half-breaths (i.e. one complete breath cycle). This produces a constant deceleration of 67.04 ms per breath over 78 breaths. Data analysis VU-AMS recordings were visually inspected, corrected and analyzed with the corresponding Data Analysis and Management Software (VU-DAMS) program version 5.4.13. Subsequently, physiological data were exported in .txt files, after which they were uploaded to the HRVisualizer program (open source, Fisher & Lehrer, 2022). The obtained individual frequency was compared with the breathing rate that the participant was instructed to follow at that time. Participants for whom the detected RF did not match the instructed breathing rate at that time point were excluded from further analyses, since this meant they were not following the breathing pacer accurately. Subsequent statistical analyses were conducted in R (version 4.5.1; R Core Team, 2025). Categorical data were described as counts, while numerical data were presented as mean values and standard deviations. To visualize RF variation over sessions, a difference score (IF1-IF2) was computed. Stability of RF over time was assessed at both the group and individual levels. Group-level differences were examined using a two-sided paired t-test, while individual-level stability was evaluated with an intra-class correlation coefficient (ICC) computed from a two-way mixed-effects model for absolute agreement. For exploratory analyses, a linear regression model was constructed to predict the second resonance frequency measurement (IF2) from the first measurement (IF1). Age and gender were included as covariates since these are stable factors that influence HRV (Aschbacher et al., 2024; Koenig & Thayer, 2016). Residuals from this model were used to compute a Spearman correlation matrix in order to examine the associations of the residuals with lifestyle and emotion regulation variables, while controlling for age and gender. A list of the used R packages, and relevant version information can be found in the supplementary material. RESULTS 3.1 Descriptive statistics Descriptive statistics are presented in Tables 1 and 2. During the first session, 23 participants reported at least one adverse effect (e.g., tiredness, yawning, lightheadedness), compared to 17 in the second session. A detailed overview is provided in Supplemental Table 1. Importantly, the interpretation of such effects is context-dependent; for example, tiredness may be desirable before sleep but less so before an exam. Participants’ mood state at the start of each session did not differ significantly, nor did perceived difficulty in following the breathing pacer. Details are presented in Table 3. Table 3 Self-reported mood states at the beginning of each session and self-reported difficulty to follow the breathing pacer during RF determination. VAS Tensed 21.90 ( 22.62 ) 21.10 ( 22.57 ) .75 [.56,.86], F (50,50.1) = 3.93 < .001 VAS Happy 59.84 ( 18.74 ) 63.14 ( 19.79 ) .81 [.67,.89], F (50,49.8) = 5.46 < .001 VAS Anxious 4.78 ( 9.63 ) 4.06 ( 10.88 ) .78 [.62,.88], F (50,50.5) = 4.54 < .001 VAS Sad 8.55 ( 15.68 ) 6.94 ( 13.27 ) .73 [.52,.84], F (50,50.8) = 3.66 < .001 Difficulty 64.10 ( 23.58 ) 62.37 ( 26.30 ) .73 [.52,.84], F (50,50.4) = 3.61 <.001 3.2 Stability of RF The mean RF was 5.01 bpm ( SD = 0.73) in the first session and 4.95 bpm ( SD = 0.71) in the second. Figure 1 represents the distribution of all obtained RF values across both sessions. Figure 1 Distribution of all obtained RF values across both sessions. Note. The left panel represents the obtained RF values during the first session, whereas the right panel represents the obtained RF values during the second session. Results of the paired t-test indicated no significant differences at group level ( t (50) = 0.45, p = .66, 95% CI [-0.21, 0.33]). In contrast, the intra-class correlation coefficient (ICC) indicated poor stability of RF at the individual level ( ICC (A,2) = 0.18, F (50,50.1) = 1.22, p = .24, 95% CI [-0.44, 0.54]). Although examination of the distribution of individual RF differences revealed substantial variability (Figure 2), for 76.47% of the sample, the difference in RF between sessions was less than 0.5 bpm. Figure 2 Distribution of RF differences between session 1 and 2. 3.3 Exploratory analysis Next, we explored to what extent individual differences in RF (in)stability were related to emotion regulation and lifestyle factors. For this purpose, we first predicted RF values for session 2 by RF values of session 1, controlling for age and gender. The obtained residuals of this model were used to explore associations between RF (in)stability, emotion regulation and lifestyle factors. The overall regression model was not significant ( F (4, 46) = 0.43, p = .79, adjusted \(R^{2}\) = -.05). None of the predictors contributed significantly to the model (all p s > .48). The residuals of the model were significantly negatively associated with only two ERSQ subscales: acceptance ( r = -.31, p = .03) and self-support ( r = -.30, p = .03). Thus, higher acceptance and higher self-support were both related to smaller differences in RF across sessions. In addition, residuals were trend significant negatively correlated with physical activity ( r = -.27, p = .05), indicating greater physical activity being related to smaller RF differences. No other significant associations were observed with emotion regulation or lifestyle measures (all other p s > 07). A detailed overview of all correlations can be found in Table 4. Table 4 Correlation of residuals with emotion regulation and lifestyle Phyiscal activity -0.27 Awareness 0.08 Self-blame 0.23 Total -0.11 Sleep 0.13 Sensations -0.2 Other-blame 0.02 BMI -0.05 Clarity 0.01 Rumination 0.16 Experience with breathing (yes/no) -0.25 Understanding -0.16 Catastrophizing 0.07 Experience with breathing (Amount) -0.11 Acceptance -0.31* Positive refocusing -0.23 Experience with breathing (Time) -0.08 Tolerance -0.11 Refocus on planning 0.08 Exercise between sessions (yes/no) 0.14 Confrontation -0.18 Positive reappraisal 0.07 Exercise between sessions (Amount) 0.19 Self-support -0.30* Putting into perspective -0.14 Exercise between sessions (Time) 0.13 Modification -0.19 Acceptance 0.10 Note. * = p < .05 DISCUSSION In clinical practice, individuals are often instructed to practice breathing exercises at their RF following an initial assessment. RF is considered the most optimal breathing rate for eliciting cardiovascular and autonomic benefits (Lehrer et al., 2013). However, it is important to investigate whether measuring an individual’s RF once is sufficient for home practice (Shaffer et al., 2014). Capdevila et al. (2021) were the first to investigate this question and found that RF was not stable over a short period (i.e. one week). However, their study had a relatively small sample size and did not fully adhere to well-established RF determination protocols (e.g. Lehrer et al., 2000 or Fisher & Lehrer, 2022). Thus, the present study aimed to replicate the findings and extend the study in a larger sample, while adhering to the protocol outlined by Fisher and Lehrer (2022). An individual’s RF is influenced by HRV parameters and may therefore also be affected by several psychological and physical variables. For instance, research has shown that higher HRV is associated with better emotion regulation (Mather & Thayer, 2018). Furthermore, lifestyle factors, such as sleep quality and duration, BMI and physical activity may also modulate HRV. The current study therefore aimed to additionally explore associations between variations in RF and both emotion regulation and lifestyle factors. Fifty-one participants took part in a one-week test-retest examination of RF. Although no significant group-level differences emerged, the ICC indicated poor individual stability (0.18). This suggests that using an RF that is not determined immediately before practice may be suboptimal. However, for 76.47 % of the participants, the difference in RF between sessions was less than 0.5 bpm. When considering that most biofeedback systems are not able to adjust the breathing pace by less than 0.5 bpm, the RF differences may be clinically negligible (Pereira et al., 2025). It is nevertheless important to note that for approximately one-quarter of participants, RF changed by more than 0.5 bpm and in some cases by up to two bpm. Thus, RF does not remain stable for all individuals. These findings raise an important clinical question: does tailoring to an individual’s RF add benefit over a fixed rate (e.g. 6 bpm)? Although breathing exactly at RF may produce slightly greater increases in HRV or baroreflex function than general slow-paced breathing, effects are often small and not consistently significant (Pagaduan et al., 2019). Given the limited stability observed in the present study, the clinical relevance of repeated RF assessment (or even individualized RF determination altogether) remains questionable. Future studies directly comparing individualized and standardized breathing rates are therefore warranted. Until further research identifies for whom RF is stable, pre-setting the rate at for example 6 bpm may offer a practical alternative (Capdevila et al., 2021). The impact of breathing slightly above or below RF on physiological and clinical outcomes remains an open question. These findings can also be considered in the broader context of HRVB training. Typically, RF is determined before the first HRVB session, after which participants practice paced breathing at this frequency at home (Lehrer et al., 2013). This assumes RF remains stable during HRVB, though evidence is mixed. A review by Lalanza et al. (2023) showed that RF was assessed only once in over half of HRVB protocols, with few studies reassessing it before each session. Findings are inconsistent: some studies report stability across sessions (Hallman et al., 2011), while others observe significant session-to-session changes (Lin et al., 2012). Notably, these studies examined RF during active HRVB training, which may differ from individuals without regular practice, as in the present study. Although significant associations between variations in RF and lifestyle or emotion regulation factors were generally scarce, higher levels of physical activity were trend significant (i.e. p = .05) associated with smaller RF differences, suggesting that individuals may exert some control over the stability of their RF and could potentially enhance RF consistency through lifestyle choices such as engaging in regular physical activity. This aligns with prior research showing that regular physical activity is associated with improved cardiovascular and mental health (Amekran & El Hangouche, 2024; Duncan et al., 2023). Furthermore, significant negative correlations were observed between RF differences and the emotion regulation skills of acceptance and self-support. More use of these skills was related to higher RF stability RF. Strengthening these skills may therefore help individuals obtaining a greater RF stability, consistent with findings that effective emotion regulation is linked to better psychological and physiological functioning (Aldao et al., 2010; Appleton & Kubzansky, 2014). The main limitation of the current study is that participants had limited experience with breathing exercises. Although no significant effect of breathing experience on RF variations was observed, participants on average practiced breathing fewer than four times a week, with an average of 39.21 minutes per week. This is considerably less than advised in the guidelines of Lehrer et al (2013). Future studies should try to include participants who regularly perform breathing exercises to examine whether RF stability improves with greater training. Nonetheless, taken together our findings have clinical importance. Assessing RF only once may not be sufficient for individuals who are unexperienced or infrequent practitioners of breathing techniques. CONCLUSION Although the current study suggests that RF remained highly stable at group level, we observed strong interindividual differences in RF stability. Lifestyle and emotion regulation factors, such as physical activity, acceptance, and self-support, were associated with higher RF stability, although these associations were small in magnitude. Further research is necessary to understand for whom RF is stable and what the (clinical) impact of breathing slightly above or below one’s individual RF is. AUTHOR CONTRIBUTIONS JD, KH, MAV and RDR developed the study concept and contributed to the study design. JD collected the data required for this study, performed the data analysis and interpretation, and drafted the paper. KH, MAV and RDR provided critical revisions. All authors approved the final version of the manuscript for submission. FUNDING RDR and MAV are supported by a grant for a Concerted Research Action of the Special Research Fund of Ghent University (01G00623) and received funding from FWO-Flanders for research projects for fundamental research (Grant Numbers: G044222N; G044019N). KH received funding from FWO-Flanders (G0A2425N) and a research grant of Ghent University (Bijzonder OnderzoeksFonds Ugent; BOF/STA/202109/049). REFERENCES Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010). Emotion-regulation strategies across psychopathology: A meta-analytic review. Clinical psychology review , 30 (2), 217–237. https://doi.org/10.1016/j.cpr.2009.11.004 Amekran, Y., & El Hangouche, A. J. (2024). Effects of Exercise Training on Heart Rate Variability in Healthy Adults: A Systematic Review and Meta-analysis of Randomized Controlled Trials. Cureus , 16 (6), e62465. https://doi.org/10.7759/cureus.62465 Appleton, A. A., & Kubzansky, L. D. (2014). Emotion regulation and cardiovascular disease risk. In J. J. 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Authors Affiliations Jente Depoorter 0000-0003-2296-2625 [email protected] Universiteit Gent Vakgroep Experimenteel-Klinische en Gezondheidspsychologie View all articles by this author Kristof Hoorelbeke Universiteit Gent Vakgroep Experimenteel-Klinische en Gezondheidspsychologie View all articles by this author Marie-Anne Vanderhasselt Universiteit Gent Vakgroep Hoofd en Huid View all articles by this author Rudi De Raedt Universiteit Gent Vakgroep Experimenteel-Klinische en Gezondheidspsychologie View all articles by this author Metrics & Citations Metrics Article Usage 418 views 202 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Jente Depoorter, Kristof Hoorelbeke, Marie-Anne Vanderhasselt, et al. HOW STABLE IS BREATHING AT RESONANCE FREQUENCY? A TEST-RETEST STUDY ON INDIVIDUAL VARIABILITY AND ITS ASSOCIATIONS WITH EMOTION REGULATION AND LIFESTYLE. Authorea . 14 December 2025. 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