Applied Psychophysiology and Biofeedback (2023) 48:275–297 https://doi.org/10.1007/s10484-023-09582-6 Methods for Heart Rate Variability Biofeedback (HRVB): A Systematic Review and Guidelines Jaume F. Lalanza1,2 · Sonia Lorente3,4 · Raimon Bullich1 · Carlos García1 · Josep‑Maria Losilla3,5 · Lluis Capdevila1,5,6 Accepted: 15 February 2023 / Published online: 14 March 2023 © The Author(s) 2023 Abstract Heart Rate Variability Biofeedback (HRVB) has been widely used to improve cardiovascular health and well-being. HRVB is based on breathing at an individual’s resonance frequency, which stimulates respiratory sinus arrhythmia (RSA) and the baroreflex. There is, however, no methodological consensus on how to apply HRVB, while details about the protocol used are often not well reported. Thus, the objectives of this systematic review are to describe the different HRVB protocols and detect methodological concerns. PsycINFO, CINALH, Medline and Web of Science were searched between 2000 and April 2021. Data extraction and quality assessment were based on PRISMA guidelines. A total of 143 studies were finally included from any scientific field and any type of sample. Three protocols for HRVB were found: (i) “Optimal RF” (n = 37), each participant breathes at their previously detected RF; (ii) “Individual RF” (n = 48), each participant follows a biofeedback device that shows the optimal breathing rate based on cardiovascular data in real time, and (iii) “Preset-pace RF” (n = 51), all participants breathe at the same rate rate, usually 6 breaths/minute. In addition, we found several methodological differences for applying HRVB in terms of number of weeks, duration of breathing or combination of laboratory and home sessions. Remarkably, almost 2/3 of the studies did not report enough information to replicate the HRVB protocol in terms of breath- ing duration, inhalation/exhalation ratio, breathing control or body position. Methodological guidelines and a checklist are proposed to enhance the methodological quality of future HRVB studies and increase the information reported. Keywords Heart Rate Variability Biofeedback · RSA · Resonance frequency · Deep breathing · Guidelines · Checklist Introduction Based on yoga and meditation from ancient Asiatic cultures, slow, deep, and abdominal breathing has become a popular technique to regulate psychophysiological states (Brown & Gerbarg, 2005a, b) or, in other words, to control our mind- * Lluis Capdevila lluis.capdevila@uab.cat body relationship. Nowadays, slow breathing is considered an efficient technique to improve mental and physical well- 1 Department of Basic Psychology, Universitat Autònoma de being (Russo et al., 2017; Zaccaro et al., 2018). However, Barcelona, Bellaterra, Spain there is still a lack of consensus about how to regulate the 2 Department of Psychology, UiT The Arctic University breathing pace, its interventional protocol, and methodologi- of Norway, Tromsø, Norway cal factors. 3 Department of Psychobiology and Methodology of Health In 2000, based on previous cardiovascular research, Science, Universitat Autònoma de Barcelona, Bellaterra, Lehrer et al. (2000) proposed a standardized protocol for Spain increasing the cardiac variability, with the final aim of 4 Pediatric Area, Hospital de Terrassa, Consorci Sanitari de obtaining both physical and mental benefits: “resonant Terrassa, Terrassa, Spain frequency biofeedback” or “respiratory sinus arrhythmia 5 Sport Research Institute UAB, Universitat Autònoma de (RSA) biofeedback” (later called Heart Rate Variability Barcelona, Bellaterra, Spain Biofeedback, HRVB). The technique consisted of training 6 Departament of Basic Psychology, Universitat Autònoma de people to breathe at their resonant frequency (RF) with the Barcelona, 08193 Bellaterra, Barcelona, Spain 13 Vol.:(0123456789) 276 Applied Psychophysiology and Biofeedback (2023) 48:275–297 aim of producing maximal increases in amplitude of RSA, Rate Variability Biofeedback. For this review, we classified defined as the variation in heart rate due to the breath rhythm these protocols as “Optimal RF” (breathing at the previously (Lehrer, 2013). This synchrony between slow breathing and detected personal RF); “Individual” (a biofeedback device heart rate improves gas exchange and increases oxygenation displays the optimal breathing rate on a screen based on (Noble & Hochman, 2019; Yasuma & Hayano, 2004; Zac- real-time cardiovascular data); and “Preset-Pace” (breath- caro et al., 2018). ing at a standard breathing rate, usually 6 breaths/minute). When breathing at RF (or near to ~ 6b/m) some changes Thus, even though a standard protocol was published in may occur that may evolve slowly, such as increased activ- 2000 (Lehrer et al., 2000) and the same authors updated it a ity of the vagus nerve and the parasympathetic system, or few years later (Lehrer et al., 2013), there is still a lack of a increased body and brain oxygenation. All these physiologi- gold standard for HRVB interventions. In addition, most of cal benefits of breathing at RF could be responsible for the the published studies applying HRVB did not report enough mental benefits of HRVB. These psychophysiological ben- methodological information to allow replication, mostly efits are based on the neural connection between the car- related to breathing control like the inhalation and exhala- diorespiratory system and the limbic and prefrontal areas tion rate and control variables like body position during the through the brain stem. HRVB intervention. Last but not least, HRVB increases Heart Rate Vari- One of the fundamental pillars in science is replication, ability (HRV; Lehrer & Gevirtz, 2014), which is defined which consists in re-examining research findings indepen- as the fluctuations in the time interval between consecu- dently to increase their validity (Schmidt, 2009). Repli- tive beats, since a healthy heart is not a metronome (for a cation is important because it generates scientific knowl- review (Shaffer & Ginsberg, 2017)). HRV is considered an edge, allows unhelpful or even harmful interventions to be index of autonomic resilience, because it reflects the ability avoided, and provides robust evidence (Michie et al., 2009). to recover from exposure to both physical and psychologi- However, replication is still a major concern for science cal stressors (Hildebrandt et al., 2016; Lehrer, 2018; Walker (Fanelli, 2018). For example, around 1,400 researchers et al., 2017). In addition, HRV has been demonstrated as a (90%) responded to a survey in Nature that there is a repli- biomarker of psychophysiological and cardiovascular health, cation crisis in science (Baker & Peny, 2016). And, in psy- diet habits or well-being (Alvares et al., 2016; Appelhans chological science, replication is suggested to be between 36 & Luecken, 2006; Chalmers et al., 2014; Young & Benton, and 77% (depending on how you assess replication) (Open 2018). In fact, Mather and Thayer (2018) proposed that high Science, 2015; Patil et al., 2016). Whatever the percentage amplitude oscillations in heart rate have positive effects on is, these results show that science should improve its rep- the cerebral neural networks related to emotional regulation, lication levels. There are several threats to replication like because high levels of HRV are associated with higher func- publication bias, p-hacking, low statistical power and so on tional connectivity between the amygdala and the medial (Munafo et al., 2017), but also poorly detailed written pro- prefrontal cortex, which they called the neurovisceral inte- tocol information, inadequate methodological reporting, and gration model (Sakaki et al., 2016; Thayer et al., 2012). inadequate designs (Glasziou et al., 2014; Ioannidis et al., Lehrer et al. (2020) reviewed randomized controlled 2014) that, as we found in this review, are major concerns studies using HRVB as an intervention. They concluded for HRVB studies. that the efficacy of HRVB was mild to moderate for several Consequently, this deficit in methodological quality could emotional, physical and performance outcomes like anxi- explain the lack of robustness in the efficiency of HRVB ety, anger, or cardiovascular diseases. The authors suggest interventions as found in previous systematic reviews and that HRVB could be considered an excellent complementary meta-analyses (see above). Improving methodological qual- intervention for professionals that work in health, medicine, ity, study designs and intervention protocols is thus an urgent education, and sport fields. In addition, other reviews also need for future HRVB research studies and clinical interven- concluded that HRVB is a promising intervention for sport tions. Therefore, the aim of this review is to create a picture performance (Jimenez Morgan & Molina Mora, 2017), stress of the published HRVB protocols, critically evaluate the and anxiety reduction (Goessl et al., 2017), substance use quality of the application of HRVB and propose guidelines disorders (Leyro et al., 2019), pain management (Reneau, and a checklist for future HRVB studies as already proposed 2020), and some cardiovascular diseases (Gevirtz, 2013; for HRV (Catai et al., 2020; Laborde et al., 2017; Quin- Pinter et al., 2019) among others. HRVB is therefore a prom- tana et al., 2016). For example, in a methodological review, ising technique to improve psychophysiological health and Laborde et al. (2017) provided recommendations for the well-being. assessment of HRV in psychological research, from study However, as we are going to discuss in this review, there design and data analysis, like artifact corrections, to the are three main types of breathing intervention protocols structure of the experiment (what they called the three Rs: for HRVB, usually under the same terminology of Heart resting, reactivity and recovery) and confounding variables 13 Applied Psychophysiology and Biofeedback (2023) 48:275–297 277 such as age, medication, or sleeping routines. In detail, we considering the field of the intervention. The search was aim to describe the designs and methods of the published performed in April 2021 (Fig. 1). The following electronic HRVB interventions, evaluate the quality of the studies and bibliographic databases were checked from the following remark on the aspects that should be improved to increase portals: PsycINFO by PsycNET and OVID, CINAHL by both the scientific quality and the clinical applicability of EBSCOhost, MEDLINE by PubMed, and Core Collection future HRVB interventions. Finally, and based on the pre- of Web of Science by Web of Science. The search strategy vious findings, we aim to propose several methodological followed the Peer Review of Electronic Search Strategies items, in guideline and checklist format, to improve future (PRESS) guidelines recommendations (McGowan et al., HRVB studies and interventions at the methodological level. 2016). The general searching syntax was: (“resonance This review thus complements the previous ones, which frequency” and breathing) or (“resonant frequency” and analyzed the efficiency of HRVB (see above), by evaluating breathing) or (“resonance frequency” and biofeedback) or the quality of the HRVB interventions and proposing meth- (“resonant frequency” and biofeedback) or (“resonance odological guidelines to enhance future HRVB interventions frequency” and training) or (“resonant frequency” and and, by extension, the replication of HRVB protocols by training) or (“heart rate variability” and biofeedback) or proposing a reporting checklist. (HRV and Biofeedback) or “heart rhythm coherence” or HRVB. In addition, the following filters were applied, if pos- sible: (i) from 2000 (when the first guidelines of HRVB were Methods published) to 2021; (ii) human participants; (iii) empiri- cal, experimental and clinical studies, (iv) scientific fields This systematic review was carried out according to the related to psychology, medicine, neuroscience, etc., and (v) “Preferred Reporting Items for Systematic Reviews and language: English, Catalan and Spanish. The specific search Meta-Analyses Guidelines” (PRISMA) (Moher et al., 2009), syntaxes are provided in supplementary Tables 1–4. When and its protocol was registered previously in PROSPERO: the paper’s full text was not available, the authors of the CRD42018086748 (Lalanza et al., 2018). study were contacted to request the full text. Studies were stored, and duplicates were deleted by Men- Search Procedure deley. Then, one review author (JFL) selected the studies based on the eligibility criteria of its title and abstract. After As the aim of this systematic review was about the differ- that, the same author checked and included, if necessary, ent methodologies applied in HRVB interventions, a search those studies being cited in the reference list of previously was made for all peer reviewed HRVB studies without published reviews of HRVB. Finally, the selected papers (in Fig. 1  Flowchart of the different phases of the searching and selection of studies, following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). RF resonance fre- quency. See table for details on the exclusion criteria 13 278 Applied Psychophysiology and Biofeedback (2023) 48:275–297 full text) were checked and included by two pairs of review Interventions” (ROBINS-I; (Sterne et al., 2016)). Domains authors independently (JFL/SL/RB/CG) (Fig. 1). Discrepan- regarding the outcomes or reports of the studies were not cies were resolved through discussion (with a third author, applied due to the methodological nature of this systematic LC, when necessary) until reaching consensus. review. The 5-Score system of the ROBINS-I was reformu- lated using the terminology of Cochrane, and reduced to 3 Eligibility Criteria categories, merging Moderate and Serious Risk of Bias into a “Medium Risk” category, to simplify its interpretation and Experimental and quasi-experimental studies were selected assessment. if they applied an active HRVB intervention without another simultaneous experimental intervention (Table 1). Thus, Statistical Analysis studies indicating only deep breathing, combining different techniques at the same time, and other types of methodolo- Descriptive analyses of the findings from the included gies (single-cases, reviews, meeting abstracts, book reviews, studies were structured around the research design, type of protocols, etc.) were discarded. Selected papers had to be breathing intervention, relevant variables measured in the written in English, Catalan, or Spanish. HRVB protocols, number of sessions, minutes of breathing, type of control group, biological sex and so on. Agreement Data Extraction between reviewers during the study selection process was analyzed by Cohen’s Kappa (Cohen, 1960). Data were extracted by an ad hoc checklist, which included data about sample, study design, HRVB protocol and envi- ronmental conditions, and risk of bias. Similarly to the pro- tocol for search procedures, two independent pairs of review Results and Discussion authors (JFL/SL/RB/CG) extracted the data of each final selected study and discrepancies were resolved through Identified Studies discussion. From the 920 non-duplicate studies found and screened by Quality Assessment title and abstract, 262 were selected after excluding for topic (n = 524) and methodology (n = 134) (Fig. 1). Of these, 19 The risk of bias of the included experimental (random) stud- were excluded owing to non-availability of full text (n = 8) ies was assessed (by JFL/SL/RB/CG) with the “Cochrane and language (n = 11), and 20 studies were added from the Risk of Bias Tool for Randomised Trials” (Higgins et al., reference list of other reviews related to HRVB. Thus, 282 2011), and for the quasi-experiments (non-randomised stud- studies were assessed for the full text and 143 were finally ies) with the “Risk Of Bias In Non-randomised Studies - of included in the review (Fig. 1). Percentage of agreement Table 1  Exclusion criteria of articles after obtaining the full text Type of Exclusion Exclusion definition No breath control Breathing was not considered either a factor or a treatment. No RF RF was not detected individually before treatment for each participant. and RF was not pre-set for all participants. and RF was not detected individually during each treatment session. In this case, RF, Coherence or RSA had to be indicated as the main feature of the breathing treatment in order to be considered HRVB and be included in this systematic review. No RF alone HRVB had to be carried out alone, without any other simultaneous treatment; except for clinical samples with a clinical treatment, for example, patients after a cardiac surgery. Intervention with different treatments, including HRVB, administered sequentially has been included. Follow-up a previous included Follow-up studies of a previously included study have not been included in this systematic review. Studies study or the same method/ that unquestionably applied a secondary analysis of a previous published method and/or sample were also sample excluded. No intervention HRVB had not been applied to obtain a benefit to the participants; for example, creating a computerized model of RSA was not an included study. Methodology Methodologies that were not: experiments or quasi-experiments; for example, reviews not excluded by title and abstract in the first screening phase. HRVB Heart Rate Variability Biofeedback, RF, Resonance (or Resonant) Frequency 13 Applied Psychophysiology and Biofeedback (2023) 48:275–297 279 between the reviewers during the study selection at first versions (short and long) were based on the same theoretical round was 85.8% (Kappa = 0.72; CI95%: 0.63 to 0.80). principle, in which the best breathing rhythm is unique for Two of the included studies performed two types of each person, the RF. HRVB interventions separately (Chalaye et al., 2009; Chen To find the RF, participants/patients breathe at different et al., 2016), and one study (Kennedy & Pretorius, 2008) rates, usually from 6.5 to 4.5 b/m for 2 min each. Then, the applied the same type of HRVB in two experimental designs. HRVB device calculates the RF and determines which of Therefore, depending on the variable analyzed, the sample the breathing rates is optimal for each participant/patient. (n) will range from 143 to 145 interventions from a total of Finally, participants/patients usually breathe for 5 to 20 min 143 studies. daily (or twice a day) at their individual RF. A second type of intervention, named “Individual” for A Summary of the HRVB Interventions this review, was applied in 33% of the studies (e.g., Narita et al., 2018; Stern et al., 2014). In these studies, the par- As the first objective of this review was to summarize the ticipants/patients receive a special device that monitors and different protocols and methodologies in HRVB, we sum- displays their heart rate on a screen. They are instructed marized the designs, methods and protocols of the stud- to make the heart rate go up as much as possible during ies applying an HRVB intervention. For each intervention inhalation and down as much as possible during exhalation. (n = 145), the sample and experimental design are shown in Instructions may also include relaxed breathing to amplify supplementary Tables 5, the protocol of each HRVB inter- the magnitude of the heart rate. One of the advantages of this vention in supplementary Tables 6 and the general labora- intervention is that it skips the initial procedure of finding tory or clinical conditions in supplementary Table 7. the RF, which the participant/patients could eventually find by matching the heart rate curve during training. However, Types of HRVB Intervention its major disadvantage is that the users may not know how to optimally pace their breathing without the device. As Based on the type of breathing intervention, we classified the happens with “Optimal RF”, the “Individual” intervention HRVB interventions found in the included studies into four requires specialized software and hardware. Today, mHealth different categories that we named: Optimal RF (n = 37), has democratized this technology, making it accessible to Individual (n = 48), Preset-Pace (n = 51) and Referenced different types of users, from medical personnel to sports (n = 9) (Fig. 2). We have already commented on the first trainers. For instance, the increasing popularity of apps and three categories in the Introduction of this review, but in wearables has made it possible for a wide range of users addition, we have added the special category “Referenced” to access their cardiovascular data at a relatively low cost. when the studies did not provide enough information to clas- However, further research is needed to confirm the reliability sify them in one of the three previous categories of HRVB. of these mobile apps in certain conditions, such as abnormal A standardized version of HRVB was proposed in 2000 sinus arrhythmia or atrial fibrillation (Li et al., 2019). for clinical and professional applications (Lehrer et al., The faster, easier and more economical alternative for 2000) and an updated and shorter version was published by applying HRVB is establishing a preset breathing rate for the same authors thirteen years later (Lehrer et al., 2013). all the participants that is usually set at 6b/m or 5.5b/m The studies that followed these two protocols were assigned (Lehrer & Gevirtz, 2014; Lin et al., 2014). We named this to the “Optimal RF” category, which included almost 1/4 of type of HRVB intervention “Preset-Pace” and it was applied the studies (e.g., Caldwell & Steffen, 2018; Hallman et al., in approximately 1/3 of the included studies (e.g., Bartur 2011). The typical “Optimal RF” protocol starts with breath- et al., 2014; Nolan et al., 2005). Although a preset breath ing practice following a pacer or a metronome and then ratio is not individually calculated in the same way as RF, detection of the RF. In the “Optimal RF” protocol a range we included this type of intervention because it is based on of breathing rates is applied before each HRVB session or the theoretical principle of HRVB. before the total HRVB intervention to detect the optimal Finally, 4.4% of the studies (e.g., Meyer et al., 2018; resonance frequency (RF) for each participant. During the Ozier & Linden, 2018) did not provide enough information second session the participant/patient continues to practice to classify them into one of the three previous categories of the RF and learns the abdominal and pursed lips breathing to HRVB. Thus, we created a special category named “Refer- achieve the RF without hyperventilating. In the third session, enced”, because in these studies the authors just mentioned the therapist must continue with the breathing technique the previous scientific work on which the HRVB was based training and introduce the home training device. And, finally, (in all cases, the work of Lehrer and colleagues was cited). sessions 4 to 10 proceed with breathing at the individual We strongly recommend providing the basic information RF. The proposed short version kept the original training about the HRVB protocol and avoiding just citing a previ- structure and just reduced the “intervention” sessions. Both ous study. For example, as an alternative to just citing a 13 280 Applied Psychophysiology and Biofeedback (2023) 48:275–297 previous study, we recommend adding the methodological breathing session (e.g., Francis et al., 2016; MacKinnon details of the HRVB intervention in the “supplementary et al., 2013). Again, a significant number of studies did not information” section in order to keep the study short, direct report enough information to know the amount of labora- and easily readable without losing relevant methodological tory sessions per week with certainty, because 16 out of information. 145 interventions did not explain it in the published paper. The minutes of laboratory and home breathing are shown Characteristics of HRVB Interventions in the third and fourth rows of Fig. 3. In general, participants/ patients breathed for 10–20 min in each HRVB session. In Once we had ascertained that most of the HRVB studies detail, for “Optimal RF” and “Preset-Pace”, laboratory ses- applied “Optimal RF”, “Individual” or “Preset-Pace” inter- sions usually lasted ten to 20 min (e.g., Eddie et al., 2018; ventions, the next step for a current and accurate picture of Schmidt et al., 2012). For “Individual” interventions how- HRVB applicability was to detect protocol differences like ever there was not a clear pattern. Among the interventions differences in the number of sessions. These variables are that applied laboratory sessions (n = 138), 19 of them did shown in Fig. 3 and commented below. not report the minutes of breathing, and 21 only reported the The total number of weeks of HRVB intervention is duration of the entire laboratory session but not the detailed shown in the first row of Fig. 3. Surprisingly, whereas most minutes of breathing. Regarding the minutes of home ses- “Optimal RF” and “Individual” interventions lasted from sions, ten to 20 min of breathing were again the preferred two to eight weeks (e.g., Hasuo et al., 2018; Yucha et al., option (e.g., Reiner, 2008; van der Zwan et al., 2015), even 2005), most of the “Preset-Pace” interventions lasted only though for “Optimal RF,” 1/3 of interventions applied more one week (e.g., Stromberg et al., 2015; Wells et al., 2012). than 20 min (e.g., Lehrer et al., 2003; Sutarto et al., 2013). This is an unexpected result, because the advantage of not For “Preset-Pace”, it is confirmed that most of the studies relying on technology provided by the “Preset-Pace” is not only applied laboratory sessions, because only twelve inter- applied in long interventions combined with home sessions. ventions applied home sessions from ten to 20 min or more On the other hand, those studies that applied a more com- (e.g., Chen et al., 2016; Wang et al., 2010). Finally, twelve plex biofeedback technology like “Optimal RF” and “Indi- out of 75 interventions (that applied home sessions) did not vidual” designed longer interventions that included home report this information appropriately. sessions (see below). For “Referenced” studies, most of them Therefore, the general protocol for HRVB interventions designed interventions from five to eight weeks. As most of (“Optimal RF” and “Individual”) lasts from two to eight the “Referenced” studies cited the standardized HRVB pro- weeks, has one laboratory session per week while partici- tocols, this is an expected result. Finally, ten out of 145 inter- pants practice HRVB daily at home for 20 min. On the other ventions did not provide enough information in the paper to hand, “Preset-Pace” studies were mostly planned as acute know the duration of the HRVB intervention, which makes interventions of only one session in the laboratory. it impossible to replicate them. The amount of laboratory sessions per week is shown Design in the second row of the Fig. 3. This variable is relevant, because laboratory sessions are the only type of session that For studies and interventions applying HRVB, the category allows scientists/therapists to control the breathing perfor- of breathing technique is the central methodological aspect. mance of the participants directly. Nevertheless, as shown However, the study design, the sample and the control group in the next sections, the control of laboratory variables was are other relevant methodological information that cannot be also inadequate in several studies. Among “Optimal RF” neglected. In this section, the information is not divided by studies, most applied only one laboratory session per week the category of breathing, because the study design is not (e.g., Hassett et al., 2007; Sutarto et al., 2012) and among a determinant factor for core HRVB variables such the cal- “Individual,” most applied one or less than one laboratory culation of the RF. The purpose of this section is therefore session (e.g., Wu et al., 2012; Zucker et al., 2009). There- aimed to achieve the first objective of this review, describe fore, these studies were usually designed with one laboratory the methodological characteristics of the HRVB studies. session per week to teach and control the adequate breathing technique and most of them included daily home sessions Study Design (data do not shown) using the same breathing rate detected during the laboratory session (e.g., Brinkmann et al., 2020; A basic classification of interventional studies is based Tan et al., 2011). “Preset-Pace” studies mainly applied one on the type of study design or experimental approach laboratory session per week. The majority of “Preset-Pace” (Fig. 4A). Among the included studies and interventions studies lasted one week which means that most of the “Pre- (n = 145), randomized experiments were most common set-Pace” studies were acute interventions with only one (75%). They were divided into between-subjects designs 13 Applied Psychophysiology and Biofeedback (2023) 48:275–297 281 (84%), where each participant was randomly assigned to Sample and Allocation each experimental condition, and within-subjects designs (16%), where each participant was randomly assigned to The type of sample is also a relevant factor, not only for each order of presentation of the experimental conditions. interpretation and extrapolation but also for replication of The second-most-common type of study design found in scientific studies. The use of university student participants this review was the quasi-experimental design (25%), is a common research practice, but could hamper the gener- which was defined as a study aimed to demonstrate causal- alization of the results to the general public (Hanel & Vione, ity between the intervention and the final outcome, but that 2016). Considering the translational character of HRVB, we did not use randomization or did not include an equivalent wanted to assess the number of studies using university stu- control group. dents. Fortunately, we did not find that most studies used university students, rather the contrary (Fig. 5A). In fact, samples composed by university students were found in only Type of Control Group 26% of the studies (e.g., Tavares et al., 2017; Zunhammer et al., 2013), whereas non-student samples were used in 70% The type of study design was partially determined by the (n = 100) (e.g., Narita et al., 2018; Yu et al., 2018). Unfor- type of control group. Control groups are a key element of tunately, six studies did not adequately report the type of science, because they allow researchers to adequately com- sample, which is a major methodological concern. pare and evaluate the experimental intervention or treat- “Age” is another factor that interacts with cardiovascu- ment and obtain valid conclusions. Ideally, an experimen- lar parameters, being inversely related to HRV (Voss et al., tal study that uses HRVB as a treatment should include 2012). However, most of the studies applying an HRVB two control groups. The first one must be an “active” con- intervention recruited young adults (Fig. 5B). In addition, trol group that for example breathes freely, reads a book we found several ways to report the age of the participants, about stress management or practices sport. Thereby, one from a mean per each experimental group to a simple range. can compare the HRVB directly to another treatment. The We recommend reporting the mean and standard deviation second control group must be a “passive” one that for of the age for each experimental condition and for the total example goes to the laboratory room and sits quietly or sample as it is the most complete option. In this review, is part of a waiting list. One can then control the effects for studies indicating a range, we took the middle value, of going to the laboratory and contextual events such as and for studies indicating the mean of age per group, we meteorological changes that could affect the mood of the calculated the mean of the groups (as usually the number participants. We only found 19 studies that included both of participants is very similar among experimental and passive and active control groups (e.g., Lee et al., 2015; control groups, even though it should be considered as an Vagedes et al., 2019) (Fig. 4B). Thus, we recommend approximate value). After that, due to the high variability of including both types of control groups in future HRVB reporting formats and dispersion, we classified participants studies, even though the passive group was just a “waiting into five age categories: childhood and adolescence (< 18 list”. Among those studies that only included one control years), early adulthood (18–39 years), middle adulthood group, 48 included an active control (e.g., Li et al., 2015; (40–55 years), late adulthood (56–65 years) and seniors Munafo et al., 2016), whereas 38 included a passive con- (> 65 years). As shown in Fig. 5B, most of the studies (60%) trol (e.g., Cullins et al., 2013; Meyer et al., 2018). We did included participants in early adulthood (e.g., Lehrer et al., not include the within-subjects studies in this category, 2018; Russell et al., 2017). In the second position, we found because the same participants received the experimental middle adulthood (20%) (e.g., Deschodt-Arsac et al., 2020; and control conditions. Finally, 21 studies did not include Windthorst et al., 2017) and with less than 10% of the stud- a control group. Due to the nature of these studies, it can ies for each category, we found participants in late adulthood be difficult to include a control group. All 21 studies were (e.g., Weeks et al., 2015; Zauszniewski et al., 2013), children quasi-experimental designs, of which 19 included clinical and adolescents (e.g., Sierra Murguía et al., 2017; Sowder patients or participants related to elite sport (e.g., Ozier & et al., 2010) and seniors (e.g., Del Pozo et al., 2004; Jester Linden, 2018; Reneau, 2020; Shaw et al., 2012). Including et al., 2019). Therefore, and always depending on the aim a non-treated condition, an equivalent healthy group or a of the study, we encourage researchers to include other age within-factor design could be impractical or even unethical groups rather than young adults. Sadly, six studies did not in these sorts of studies. On the other hand, we encour- report the age of the participants, which should be avoided age the inclusion of a control group and the design of a in future studies. randomized experiment if the characteristics of the sam- Finally, biological sex is still a major issue in science, ple allow it, for example in studies with students or with mainly in basic and human or animal studies (Beery & healthy adults. Zucker, 2011; Mamlouk et al., 2020). Based on the false 13 282 Applied Psychophysiology and Biofeedback (2023) 48:275–297 myth that the oestrus cycle adds too much variability, most rate variability (GRAPH). Although the GRAPH is geared human or animal studies include only males (Becker et al., towards HRV and psychiatric disorders, these authors also 2016). Luckily, this sex bias is disappearing in biological focus on the relevance of increasing methodological details. science and there is a significant increase in the last 10 years They elegantly argue that the lack of methodological details: in the inclusion of both sexes (Woitowich et al., 2020), but (i) delays the peer-review process, (ii) hinders replication, women are still a minority in randomized controlled trials and (iii) blocks future meta-analysis. We totally agree with (Geller et al., 2018). Regarding HRVB, we found that the them and also defend the need for increasing methodologi- total sample of the included studies was almost 50% women cal details, as is shown in the guidelines and checklist we and 50% men (Fig. 5C). Unfortunately, four studies did not proposed for HRVB. report the biological sex of the participants. Breathing Information Lack of Methodological Information The first six rows of Fig. 6 include methodological infor- The second aim of the review is to critically evaluate the mation related to the HRVB intervention. Unlike the previ- quality of the studies and highlight methodological aspects ous section, herein we are going deep into the breathing that could be improved in future HRVB studies. Hence, process with detailed information about each of the HRVB Fig. 6 shows the number of studies that reported essential interventions. information about the HRVB intervention and the contextual Beginning with “Optimal RF” interventions, a large factors. majority of studies (84%) (e.g., Hallman et al., 2011; Schu- In general, we found that many central variables and man & Killian, 2019) reported the range of breathing rates methodological factors were not adequately reported in the (RF range) applied before starting the main HRVB. This included studies, therefore one should be careful interpret- initial battery of breathing rates allows detection of the opti- ing and comparing some results. A previous systematic mal RF for each individual and consequently attainment of review and meta-analysis, for example, also found that it is the maximal benefits of the HRVB intervention. This initial important to consider methodological quality when inter- battery of breathing rates is the key aspect of “Optimal RF” preting HRV results (Alvares et al., 2016). It could indeed HRVB, so it is surprising that 16% (n = 6) did not report this be hypothesized that this lack of methodological information information. could exemplify the low levels of replication in psychology To go into more detail with the RF range, the standard (Open Science, 2015) and biomedical disciplines (Begley & duration of each breathing rate trial period is two minutes Ellis, 2012; Ioannidis et al., 2009). These authors (Open Sci- (according to Lehrer et al., 2000). As this review did not aim ence, 2015) did not conclude that the original evidence was to evaluate the efficacy of each HRVB protocol, but rather its a false positive but suggested that a confluence of factors quality, we are not going to assess the number of minutes of like poor research designs or publication bias could explain each study, only whether this information is reported. Most the difficulty in replicating the results. In fact, the National studies reported the minutes of RF range (70%) (e.g., Hasuo Institutions of Health (NIH) together with the Nature Pub- et al., 2019; Steffen et al., 2017). However, 1/3 of the “Opti- lishing Group emphasized the need to increase transparent mal RF” studies did not contain information about the num- reporting of key methodological information (among other ber of minutes of each breathing rate during the RF range. principles), like clearly stating the inclusion/exclusion cri- Finally, one can apply the detection of the optimal RF (RF teria, in order to improve rigor and replication (NIH, 2017). range) before each HRVB session, once per week or only Munafò et al. (2017) also recently published a manifesto that once at the beginning of the HRVB intervention. Whereas encourages scientists to improve the transparency, replica- more than half of the “Optimal RF” studies only applied the tion and efficiency of scientific research. One of the propos- RF range during the first HRVB session (n = 21) (e.g., Rus- als is indeed improving the quality of the reporting by, for ciano et al., 2017), only six studies checked the optimal RF example, reporting experimental conditions and following before each HRVB session or more than once (e.g., Gross guidelines (e.g., the Consolidated Standards of Reporting et al., 2016; Perez-Gaido et al., 2021). Lin et al. (2012) found Trials –CONSORT–) may increase the quality of reports of that the optimal RF (assessed by the RF mean of partici- randomized controlled trials, (Plint et al., 2006). Another pants) changed from session to session (from 6 to 5 b/m) in review also reported the need to improve the reporting of students (~ 22 year) with prehypertension, whereas Hallman protocols and documentation about research, suggesting et al. (2011) found that the optimal RF was stable during ten that making the full protocols available or even publishing HRVB sessions in older participants (~ 40 year) without car- them in advance, e.g. pre-registration, was necessary (Ioan- diovascular disorders. In an experimental laboratory study, nidis et al., 2014). Finally, Quintana et al. (2016) proposed Capdevila et al. (2021) have also found that the optimal RF guidelines for reporting articles on psychiatry and heart showed some variation in a test-retest protocol. In addition, 13 Applied Psychophysiology and Biofeedback (2023) 48:275–297 283 cardiovascular improvement was also detected during the Chalaye et al., 2009; Reyes del Paso et al., 2006). However, optimal RF. Similarly, an included study also compared the some studies reported breathing rates that differed from the optimal RF with the optimal RF + 1 breathing rate and cor- established protocols (e.g., Bartur et al., 2014; Francis et al., roborated that the non-optimal RF had less cardiovascular 2016), which highlights the need to ensure that the HRVB and psychological benefits (Steffen et al., 2017). However, intervention is adequately implemented. the differences in breathing protocols, experimental designs For all four categories of HRVB protocols, the inhalation/ and contextual variables among these studies make it diffi- exhalation ratio is an important parameter for breathing- cult to obtain a clear conclusion about the instability of RF. based interventions. In general, longer exhalations than inha- On the other hand, there is also evidence for the stability of lations are recommended (e.g., 4:6) to increase RSA (Lehrer, RF. For example, Fisher and Lehrer (2022) found that RF 2013; Strauss-Blasche et al., 2000), even though the effects showed a high level of stability, comparing a new “sliding of the inhalation-to-exhalation (I/E) ratio on HRV remain protocol” to the traditional “stepped method”. This new pro- unclear (Shaffer & Ginsberg, 2017). From the included stud- tocol is characterized by a constant change in pace (a fixed ies/interventions, only 27 reported the inhalation/exhalation rate change of 67.04ms per breath) at each of 78 breathing ratio, with the exhalation usually being longer (e.g., Allen & cycles ranging from 4.25 to 6.75 breaths per minute. There- Friedman, 2012; Brabant et al., 2017). Interestingly, two of fore, the stability of RF during the HRVB intervention is the included studies compared different inhalation/exhala- still a topic of debate. For future “optimal RF” interven- tion ratios with contradictory results. While Lin et al. (2014) tions, we recommend following a published protocol, either discovered that an equal inhalation/exhalation ratio was the a “stepped method” (e.g., Lehrer et al., 2013) or a “sliding best option for achieving greater HRV (even though with protocol” (Fisher & Lehrer, 2022). However, for interven- longer exhalations, HRV was also increased compared to tions where available time is not a constraining factor, we spontaneous breathing), van Diest et al. (2014) discovered suggest checking the optimal RF more often, to both: (i) be that longer exhalations increased the high-frequency param- sure that participants/patients breathe at a comfortable rate, eter of HRV and increased perceived relaxation compared and (ii) increase the evidence about the stability of RF. to longer inhalations. Therefore, we recommend reporting Having detected the optimal RF for each participant/ the inhalation/exhalation ratio as well as the instructions patient, the mean RF of the sample is a useful data point for provided to participants. In addition, owing to different out- future HRVB studies. For example, “Preset-Pace” studies comes about the best inhalation/exhalation ratio, this facet could choose a more accurate breathing rate depending on of the breathing intervention deserves further investigation. the type of sample or “Optimal RF” studies could adjust the Although these breathing parameters must be selected for RF range. For instance, previous studies failed to find par- any HRVB intervention, it is noteworthy that approximately ticipants with an optimal RF of 4.5b/m (Steffen et al., 2017) 2/3 of the included studies did not provide complete infor- and in a sample of late-adults the mean of RF was between mation about these breathing parameters. Furthermore, this 6 and 6.5 b/m (Hasuo et al., 2018). The mean RF can also lack of methodological information increases the risk of bias be calculated in “Individual” studies, so for this parameter (see below) of both experimental and quasi-experimental we pooled “Optimal RF” and “Individual” studies (n = 85, studies and makes the replication of the interventional stud- Fig. 6, 4th row). In total, only 20 studies reported the mean ies very difficult (Michie et al., 2009). RF (e.g., Paul & Garg, 2012; Prinsloo et al., 2011). Last but not least, we encourage measurement of the The optimal RF for each participant/patient and the estab- breathing rate as well as the inhalation/exhalation ratio to lished Preset-Pace breathing rate for all samples should be sure that the prescribed intervention is followed by the bemonitored to ensure that all participants breathe at the participants/patients. Respiratory monitoring is also rec- correct rate. In other words, the interpretation of HRVB ommended to detect dysfunctional breathing behaviors like findings may not be accurate if the participants’ breath- apnea or over breathing during the practice of HRVB (Shaf- ing rates are not properly monitore (for example, using a fer & Meehan, 2020). There are several devices that can respirometer). Only 19 out of 88 studies (e.g., Clamor et al., be used for such a purpose. The respirometer is an optimal 2016; Sutarto et al., 2012) reported any sort of monitoring solution to assess the breathing rate of the user. It consists of of the breathing rate. Among the “Optimal RF” studies, one a flexible sensor band that detects the thoracic or abdominal reported only the first two sessions with an expected result, expansion during breathing. As an alternative, HRV software because participants breathed close to the RF (~ 5.5–6 b/m) can also extract breathing data; this information is obtained (Gross et al., 2016). Another reported that the breathing rate after the practice, however (e.g., Capdevila et al., 2021). was higher at the beginning but correct at the end of the Interbeat interval (IBI) is the basic element of HRVB and HRVB intervention (from ~ 8.5 to 6.3 b/m) (Sutarto et al., it can be measured using different technologies. Briefly, an 2012). Regarding the “Preset-Pace” studies that monitored electrocardiogram (ECG) detects the IBI with high accu- the RF, most of them reported correct breathing rates (e.g., racy, but it is more invasive and difficult to use than other 13 284 Applied Psychophysiology and Biofeedback (2023) 48:275–297 methods. On the other hand, a photoplethysmograph (PPG), and environmental conditions could affect HRV parameters which optically detects pulse waves by assessing changes in (Laborde et al., 2017), so it is relevant not only to control light absorption caused by blood flow, is easier to use, more them, but also explain them in the paper. For instance, noise comfortable for the user and can be used daily (e.g., you could increase sympathetic activity (Lee et al., 2010) and can use an app on your own smartphone). However, PPG smell might also affect cardiovascular parameters, as aro- does not detect the beat-to-beat interval as accurately as the matherapy has been observed to increase parasympathetic ECG and it is influenced by the breathing pace, the recording activity (Chang & Shen, 2011; Huang & Capdevila, 2017). place, and basal sympathetic activation (Allen, 2007; Dagher Circadian rhythms also affect our metabolism, including et al., 2020; Lu et al., 2009; Shabaan et al., 2020; Shaffer & cardiovascular parameters (Mistry et al., 2017). The time of Combatalade, 2013; Shaffer & Meehan, 2020). Therefore, day when HRVB was applied, and its effects assessed, could PPG is less accurate during a paced breathing protocol with thus impact the final outcomes depending on the experi- the RF range. Interestingly, Jan et al. (2019) compared ECG mental design. In a within-subject design, each participant and PPG on healthy subjects with/without controlled breath- should be measured consistently at the same time of day, ing. They found that ECG signals were more precise than while in a between-subject design, all participants in the PPG wave signals during respiratory fluctuations like during same group should be measured simultaneously. Again, a HRV detection. low percentage of studies reported time of day (21%) (e.g., Deschodt-Arsac et al., 2018; Henriques et al., 2011). Controlling Contextual Factors Even lower is the number of studies that reported how many participants/patients were together on the HRVB Despite the fact that contextual factors may also impact the sessions (12%) (e.g., Climov et al., 2014; Patron et al., experimental results, they were not often included in the 2020). Again, there is no evidence that proves the number selected studies. These factors, for example, from taking a of participants in a room affects cardiovascular parameters, certain medication to just the need to use the toilet (blad- but because it is a methodological parameter it should be der distension) (Heathers, 2014), have the potential to alter reported as well. For example, being in a social context HRV parameters (for a review, Laborde et al., 2017). From could both increase or decrease social discomfort, which rows seven to 13 in Fig. 6, we assessed the number of stud- would affect the sympathetic/parasympathetic activity. ies that just reported the main contextual factors that could Finally, not even 1/3 of the studies reported that instruc- affect breathing and cardiovascular parameters such as HRV tions like ‘do not smoke for 2 hours before’ or ‘sleep at least indices. 6 hours the previous night’ were given to the participants One of the basic factors for cardiovascular assessments before the HRVB intervention or cardiovascular assess- is body position (Watanabe et al., 2007). Significant dif- ment (e.g., Bartur et al., 2014; Caldwell & Steffen, 2018). ferences in the main parameters of HRV have been found What’s more, only 35% of them reported measurement of between supine, sitting or standing positions. HRV param- at least one of these instructions or conditions (e.g., Meule eters increased in supine positions and decreased in standing et al., 2012; Tsai et al., 2015). In other words, several studies positions (Young & Leicht, 2011). Body position during the required some conditions to participate in the HRVB ses- HRVB sessions, whether in the laboratory or home, was sions or cardiovascular assessment, but then these conditions reported in less than half of the studies (e.g., Patron et al., were neither measured nor enforced. It is well known that 2013; Wang et al., 2010). some drugs of abuse (Quintana et al., 2013; Sjoberg & Saint, The only contextual variable that was reported by most 2011), antidepressant medications (Kemp et al., 2010), phys- of the studies was Eyes (open or closed). However, this is a ical activity (Melanson, 2000; Stanley et al., 2013) or sleep masked outcome, because we considered studies that used a quality (Meerlo et al., 2008) could alter the cardiovascular display or screen as a biofeedback interface as “eyes open” response and autonomic functions (like HRV). Thus, it is (e.g., Eddie et al., 2018; Kudo et al., 2014). Although, to crucial to first indicate to the participants that they must fol- the best of our knowledge, there is no evidence reporting low certain rules, second check them and finally act in case that open or closed eyes influence cardiovascular param- these conditions are not followed. eters, it could affect the levels of concentration, relaxation, or distraction. Risk of Bias We united all factors related to the physical environment under the same variable, Room: light, noise, smell and tem- In general, experimental studies showed lower levels of risk perature; and we considered studies reporting at least one of bias (methodological quality) than quasi-experimental of these variables as “reported” for this variable. Even so, (Fig. 7). Experimental studies showed risk scores in Other only 27% of the studies reported even one Room variable sources of bias, mainly due to a lack of methodological (e.g., Chen et al., 2016; Schumann et al., 2019). Physical information and protocol details. This domain was assessed 13 Applied Psychophysiology and Biofeedback (2023) 48:275–297 285 as “low risk” in less than 30% of the studies (Fig. 7A). The Quintana et al., 2016), but to the best of our knowledge there other domains were assessed as “low risk” in more than are not any specific guidelines for HRVB yet. Thereby, we 60% of the studies. Surprisingly, 17% of the studies did not propose a eight-point guideline/checklist to consider before properly address (or report) the randomized designation of the HRVB intervention and while writing the scientific participants to the experimental/control groups. As experi- manuscript. In addition, we present a checklist table to mental designs are based on randomization, this issue should facilitate the implementation of the guidelines (Table 2), be clarified in future studies. Finally, due to the character because checklists are excellent tools to improve the quality of HRVB interventions, it is not surprising to find that all of research reports (Han et al., 2017). We advise future users studies correctly addressed the domain Blinding of outcome to adapt the checklist for each experiment or intervention. assessment, which is about the need to blind outcome asses- For example, in a single case study there are no experimental sors from knowledge of which intervention a participant groups, so one just needs to indicate the age of the patient, received. not the average. Quasi-experimental studies (Fig. 7B), on the other hand, showed medium methodological quality. Deviation (Bias (0) Pre-Registration or Registration Report: Preregistration due to deviations from intended interventions) was the (a short document answering basic questions about the domain with the highest risk of bias, since it presented lower study design and the analysis plan before starting the levels of “low risk” (only 17% of the studies). It refers to the study) has already become a norm in clinical trials, homogeneity of the intervention between participants. It is because it is an efficient way to reduce questionable important tomonitor and/or guarantee that all participants research practices like p-hacking or HARKing and follow the same intervention, because without monitoring consequently to increase the possibility of replication. it, one cannot ensure that the participants were compara- Alternatively, a “registration report” answers the basic ble. Because most of the interventions were home-based in questions of the study and explains the study design HRVB interventions, some extra tools are needed to guar- in a more rigorous format and is submitted to a peer- antee the homogeneity of the intervention, for example the reviewed journal. When the study is completed, the use of an electronic diary to check the HRVB sessions at reviewers need only check the registration report and home using mHealth technology. Selection (Bias in selec- if the researchers followed the original plan, the final tion of participants into the study) and Confounding (Bias paper is published (Nosek et al., 2018; Chamber et al., due to confounding) are related to enrolment of participants, 2014). We therefore encourage researchers to prereg- and to the characteristics of participants, respectively. Both ister or publish a registration report before conducting criteria could increase the variability of the data and mask an HRVB study or clinical trial. the effect of HRVB interventions.If the baseline characteris- (1) Sample: Regarding the type of sample, it is relevant tics of participants and correct enrolment are not adequately to provide information for each experimental group controlled, the sample could be biased and could skew the regarding biological sex and age. Optionally, we also effects attributable to the HRVB interventions. These two recommend indicating the weight and the height if it domains presented “low risk” levels in only 28–33% of the is possible to obtain this information without disturb- selected studies. The domain of Missing data (Bias due to ing the intervention. One of the threats to reproduc- missing data) was well addressed in 42% of studies. It is ible science is low statistical power (small sample size, also relevant for HRVB interventions, because a high num- small effects or both), which is a risk factor for obtain- ber of missing participants could indicate that the HRVB ing false-positive and false-negative results as well intervention is not adequate for all participants. Finally, the as an inflated effect size (Button et al., 2013). Thus, domain Classification (Bias in classification of interven- we encourage calculation of the statistical power in tions) showed adequate levels of methodological quality, as advance. Another good practice for estimating the mag- 69% of the studies presented “low risk”. nitude of the intervention is to include the effect size of the intervention in the final report (Schäfer & Schwarz, Methodological Guidelines and Reporting Checklist 2019). (2) Allocation: Directly related to the sample, it is relevant The third and most important objective of this systematic to indicate how participants/patients were recruited review was to provide guidelines to improve both the appli- and contacted, if they were paid or compensated in cation of HRVB and the reporting of the methodological any way and if they were aware of all conditions of the information regarding the HRVB protocol, which is crucial experiment (e.g. being part of the control group). As to allow replication between research groups and clinical allocation was not well covered in the risk of bias, we practitioners. Previous publications have already proposed strongly recommend reviewing this point. Allocation guidelines for HRV (Catai et al., 2020; Laborde et al., 2017; also refers to the inclusion and exclusion criteria, which 13 286 Applied Psychophysiology and Biofeedback (2023) 48:275–297 Table 2   HRVB intervention and reporting quality checklist HRVB methodological guidelines Considered Reported (0) Pre-Registration or Registration (1) Sample Power analysis: calculation of the minimum sample size to obtain an appropriate effect size. Biological sex: number of women and men per group Age: mean age for each group Condition: e.g. students, cardiovascular patients or suffering from obesity Weight (optional): mean weight for each group Height (optional): mean height for each group (2) Allocation Recruitment of participants/patients/clients to the study Compensation for participating in the study (payment, credits, holidays, etc.) Inclusion and exclusion criteria assessed and explained Awarenessor suspicion of participants of the experimental group assignation Random (optional): assignation (3) Missing participants and missing data Initial sample: once the participants have agreed to participate or come to the first session Final sample: participants included for the data analysis Causes for losing participants/patients (optionally use a diagram) Missing data for the statistical analysis (4) Breathing protocol Type of HRVB intervention based on the category of breathing technique. The type of intervention determines which items need to be completed Resonance Frequency detection (optional): details about the establishment of the individual resonance frequency (RF). This item also includes when and how many times the RF was detected across the entire HRVB intervention Mean of the Resonance Frequency (optional) for the experimental group “Preset or fixed” Resonance Frequency (optional): for the “preset-pace” or slow-breathing intervention Control of breathing rate (optional): for intervention with a collective or individual resonance frequency. E.g. use of a respirometer Inhalation, holding and exhalation seconds for each breathing cycle (5) Breathing intervention Number of laboratory sessions of the HRVB intervention Minutes at the laboratory actually breathing (not doing other experimental tasks) Number of home-practice sessions (optional) Minutes per each home-practice session (optional) Control assessment for the home-practice sessions (optional) (6) Conditions of the intervention Laboratory conditions: ambient light Laboratory conditions: temperature of the room Laboratory conditions: body position Laboratory conditions: time of day Laboratory conditions: number of participants at the same time Laboratory conditions (optional): smell/aroma, humidity and eyes (closed or open) Home-practice sessions (optional): like time of day, ambient conditions, etc. Recommendations for participants: like caffeine or alcohol intake, minimum hours of sleep, exercise before the session, etc. Control of the recommendations for participants: how to assess the accomplishment of the previous recommendations and what to do if a participant does not follow them (7) Equipment HRVB apparatus: brand, type of metronome, type of biofeedback, is it validated? is it invasive? etc. HRV apparatus (optional): brand, type of metronome, type of biofeedback, is it validated? is it invasive? etc. for the analysis of heart rate variability Other apparatus for physiological analysis that can interact with the breathing performance such as a thoracic belt for breathing analysis (e.g. respirometer) Mark with and X whether you have considered or think about the item before applying the HRVB intervention. Mark with and X whether you have reported each item in the manuscript giving the necessary details 13 Applied Psychophysiology and Biofeedback (2023) 48:275–297 287 b. RF detection: For interventions applying a previ- ous RF detection, information about the ranges, the minutes of each range and the pause between ranges should be indicated. Information about when the RF was assessed is also relevant. c. Mean RF: Except for the “Preset-Pace” or slow- breathing intervention, knowing the mean RF is relevant to connect the sample type with the average RF and, for example, apply a more accurate “Preset- Pace” or fixed breathing ratio in future studies. d. Preset RF: Obviously, the breathing rate used in studies applying a “Preset-Pace” or slow-breathing intervention must be indicated. Fig. 2  Type of HRVB intervention (n = 145). Optimal RF: interven- e. Monitoring of the breathing rate: Once the RF or the tions that followed the original protocol by Lehrer et al. (2000) and preset pace has been established (except for in the applied a range of breathing rates before each HRVB session or for “individual” studies), monitoring whether partici- the total HRVB intervention in order to detect the optimal resonance pants/patients breathe at the correct ratio is crucial frequency (RF) for each participant. Individual: those interventions that used a biofeedback system that indicates the actual breathing to assure that the intervention was accomplished rhythm and the optimal breathing rhythm in real time for each par- correctly. This assessment, however, requires spe- ticipant. Thereby, each participant individually adapted the breathing cialized equipment. Respirometers are non-invasive, rate to the optimal rhythm or rate indicated by the biofeedback sys- easy-to-use tools to measure the respiratory rate and tem. Preset-Pace: a fixed breathing ratio is set up for all participants and all HRVB sessions, usually 6 b/m. Referenced: those studies that the inhalation/exhalation ratio. did not report enough information to determine the type of HRVB f. Inhalation, holding and exhalation: As the inhala- intervention, because the authors referred to an HRVB intervention tion/exhalation ratio could affect the cardiovascular from a previous study system and consequently the efficacy of the HRVB intervention, this information should be reported. must be clear in the manuscript. Even though it was not a critical item in the risk of bias, the assignment of each (5) Breathing Intervention: All the information regarding participant to the experimental or control groups is also laboratory and home practices, number of sessions, a relevant issue. minutes per sessions as well as the control mechanisms (3) Missing participants and data: Working with humans to guarantee that the intervention was followed cor- implies more experimental death and loss of partici- rectly are extremely relevant because it is, together with pants as the experiment involves more time and effort. the “breathing protocol,” the core of the HRVB inter- High levels of missing participants could indicate that vention. We strongly advise reporting this information. the intervention was too demanding and involved a self- (6) Conditions of the intervention: The physical and con- selection bias, as only highly motivated participants textual conditions of the breathing intervention during finished it. Missing data points could imply that the the laboratory or clinical sessions are easy to control. assessment and/or equipment are not reliable or even Thus, we encourage researchers to control and report valid. Therefore, detailed information about missing them. The contextual conditions during home prac- participants and missing data, including the reasons, tices are more difficult to control, however, as each should be provided. We recommend presenting this participant/patient has their own life, for example, dif- information in a diagram format. ferent light environments, noise backgrounds, working (4) Breathing protocol: This is the core of the intervention routines, etc. On the other hand, the current mHealth and should be explained in detail. We suggest avoiding technology allows us to record practice frequency referring to the breathing protocol of a previous study. and duration data from the home breathing sessions, Not all studies are accessible for everyone and usually including whether participants/patients are following the referred protocol is adapted. The level of “adapta- the prescribed breathing rate, number of sessions and tion” is often unknown to the scientific community and duration. a lot of crucial information is lost. a. Laboratory Conditions: As a minimum, the light, a. Type: The type of HRVB intervention needs to be temperature, body position, time of day and the indicated clearly as the terminology HRVB is used number of participants at the same time ought to be for three similar but distinct breathing techniques. reported as these factors can alter the cardiovascular 13 288 Applied Psychophysiology and Biofeedback (2023) 48:275–297 13 Applied Psychophysiology and Biofeedback (2023) 48:275–297 289 ◂Fig. 3  Characteristics of the HRVB intervention by type of HRVB c. Recommendation for participants: All the indi- intervention. Based on the four categories of HRVB interventions cations that participants received regarding their (columns for: Optimal RF, Individual, Preset-Pace, and Referenced), we indicated in rows: (1) the total duration of the HRVB intervention homeostatic state such as the amount of sleep or in weeks; (2) the number of laboratory sessions per week; (3) minutes caffeine intake must be written as well as the con- of exclusively breathing during laboratory HRVB sessions (in green trol measures to guarantee the recommendations are those studies that only applied home sessions, in purple those stud- fulfilled. ies that only reported the duration of the entire session, but not the breathing time specifically); (4) daily minutes of exclusively breath- d. Strategies to control home practices: Indicate the ing during the home HRVB sessions (in green those studies that only strategies and tools to ensure that the prescribed applied laboratory sessions). The numbers (n) in the bars indicate the breathing regime is followed. number of studies/interventions per each category (7) Equipment: As there are several technologies and system. Additionally, we also recommend indicating brands available to assess breathing, apply HRVB and alterations in smell or ambient aroma, humidity, and measure HRV, precisely indicating the different appa- eyes (open or closed). ratus used is recommended. Equipment to measure b. Recommendations for home-practice sessions: The the breathing rate, like respirometers, is highly recom- time of day, the type of room, ambient conditions, mended. and so on, should be noted. Fig. 4  Design and control group of the included studies and inter- screen, writing in a diary or running. Passive: participants did not do ventions (n = 143). A Study designs: Experimental/BS (between- anything active, they were on a waiting list or sat in the laboratory. subjects): studies that applied an experimental (randomized and/or Studies that only reported a control group were included in this cat- equivalent control group) between-subjects design (each participant egory. Both: studies that included two or more control groups/con- was assigned to one experimental group). Experimental/WS (within- ditions and at least one was active, and one was passive. No control subjects): those studies that applied an experimental within-subjects group: this category included quasi-experimental studies that did not design (each participant was assigned to one order of the experimen- have a control group. Exp/WS (within-subjects): studies in which all tal groups). Quasi-Experimental: those studies that applied a quasi- participants received both the control and the experimental condi- experimental design (non-randomized and/or non-equivalent control tions. The numbers (n) in the graphs indicate the number of studies group). B The type of control group/s or condition/s. Active: partici- per each category pants did something active such as breathing without a biofeedback Fig. 5  Characteristics of the samples used in the included stud- 55 years, Late Adulthood: between 56 and 65 years, Seniors: more ies and experiments (n = 143). A Type of sample divided between than 65 years. C Total males and females considering the final sample those studies that included students and those that did not include of each study. The numbers (n) in the graphs indicate the number of students. B Age of the samples based on the reported “mean age” or studies per each category. 1Four studies did not report the biological “age range”. Children & Adolescents: less than 18 years, Early Adult- sex of the participants (n = 139) hood: between 18 and 39 years, Middle Adulthood: between 40 and 13 290 Applied Psychophysiology and Biofeedback (2023) 48:275–297 Strengths and Limitations 2019; Jimenez Morgan & Molina Mora, 2017; Lehrer et al., 2020; Leyro et al., 2019; Pinter et al., 2019; Reneau, 2020). The main limitation of the present review is the lack of any Another limitation of this review is that we did not delve efficiency measurement to determine which category and into the RF measurements and HRV analysis. Accurate protocol of HRVB is the most recommended. However, the detection of RR intervals can be impaired by such factors as comparison between the different categories of HRVB inter- presence of ectopic beats or other abnormal heart rhythms, ventions in terms of efficacy was not within the scope of this line, movement, or EMG artifacts, etc. Thus, we strongly review. Hence, we suggest checking other published reviews recommend including a plan for artifact prevention and data and meta-analyses that assessed the efficacy of HRVB analysis before starting the HRV study. (Gevirtz, 2013; Goessl et al., 2017; Herbell & Zauszniewski, Fig. 6  Methodological features and co-variables reported in the and temperature; it was considered “reported” if just one condition selected papers. RF Range: the breathing rates or range applied to was reported. Time of day: the time of day when the HRVB sessions detect the optimal resonance frequency (RF). Minutes RF range: were performed. Num. participants at the same time: how many par- the minutes of each breathing rate from the “RF Range”. Check RF ticipants, clients or patients were together during an HRVB session. each Ses.: the optimal RF was assessed before each HRVB session; Instructions: recommendations given to for participants before each “yes” instead of “reported”. Mean RF: the mean of the RF in the HRVB session, like no smoking 3 h before the session. Control of the total sample. RF/Preset-Pace controlled: any attempt to ensure that instructions: it was considered “reported” if just one of the instruc- participants/patients breathed at the indicated RF or preset breathing tions were reported in the study. n = 145, except for: 1only for “Opti- rate. Inhalation/Exhalation Ratio: the ratio of inhalation, hold and mal RF”, n = 37; 2only for “Optimal RF” and “Individual”, n = 85; 3 exhalation during breathing. Body Position: the body position dur- only for “Optimal RF” and “Preset-Pace”, n = 88; 4only for those ing the HRVB sessions. Eyes: open or closed eyes during the HRVB studies that reported any pre-HRVB instruction, n = 43. The numbers intervention. In studies that used a screen or a display, “open eyes” (n) in the graphs indicate the number of studies per each category are inferred. Room: room conditions including: light, noise, smell 13 Applied Psychophysiology and Biofeedback (2023) 48:275–297 291 Fig. 7  Risk of Bias for the experimental and quasi-experimental stud- I was reformulated using the terminology of Cochrane, and reduced ies/interventions. A Risk of Bias for Experimental (n = 107) stud- to 3 categories, merging Moderate and Serious Risk of Bias into a ies; B Risk of Bias for Quasi-Experimental studies (n = 36). Values “Medium Risk” category, in order to simplify its interpretation and are expressed in terms of percentage of studies with a certain score. assessment. Those items related to “reporting outcomes” were not The “Cochrane Risk of Bias Tool for Randomised Trials” tool was included, because it was not the objective of this review used for experimental studies. The 5-Score system of the ROBINS- On the other hand, this systematic review pioneers the to criticize these studies, but rather to offer an opportunity analysis of different HRVB interventions in terms of meth- to improve future research. Therefore, we propose methodo- odological quality, reporting information and risk of bias. In logical guidelines for designing the HRVB intervention and addition, even though we could not find full-text versions of writing the manuscript to firstly rethink the most relevant eight studies and we only included studies in English, Cata- factors and contextual variables related to HRVB and sec- lan or Spanish, we searched four of the major databases fol- ondly report all relevant methodological details. Finally, we lowing the PRESS guidelines, thus we expect to have located also propose a checklist for better implementation of the the main studies applying HRVB interventions. guidelines. Supplementary Information The online version contains supplemen- tary material available at https://d​ oi.o​ rg/1​ 0.1​ 007/s​ 10484-0​ 23-0​ 9582-6. Conclusion Acknowledgements Thisstudy was supported by the Grants PID2019-107473RB-C21 and PGC2018-100675-B-I00funded by There are three main approaches to implement an HRVB MCIN/AEI/10.13039/501100011033 by Spanish Government, and intervention, which we categorized as: “Optimal RF”, “Indi- 2021SGR-00806 funded byCatalonian Government. vidual” and “Preset-Pace”. All three are based on breathing Author Contributions JFL designed the study, performed the search at the resonance frequency (RF) to enhance the activation and analysis ofpublications, analyzed the results, and wrote the main of the vagus nerve and parasympathetic system. While the manuscript text. LCdesigned the study, analyzed the results, wrote the “Optimal RF” and “Individual” categories are actual bio- main manuscript text, andfunded the study. SL, RB and CG performed the search and analysis ofpublications. JML designed the study, ana- feedback techniques, “Preset-Pace” applies the most com- lyzed the results, and reviewed themanuscript. mon RF breathing rate, 6b/m. Beyond this general categori- zation, there are almost as many HRVB protocols as studies Funding Open Access Funding provided by Universitat Autònoma de in terms of total duration of the intervention, minutes of Barcelona. breathing, number of sessions per day and week, laboratory sessions combined with home sessions and so on. This vari- Declarations ety of methodological protocols, even though they are based Competing Interest Theauthors have no competing interests to declare on the protocols proposed by Lehrer and colleagues (Lehrer that are relevant to the contentof this article. et al., 2000, 2013), hinders comparison between studies. Thereby, future systematic reviews and meta-analyses ought Open Access This article is licensed under a Creative Commons Attri- to analyze the efficiency of the different methodological bution 4.0 International License, which permits use, sharing, adapta- tion, distribution and reproduction in any medium or format, as long approaches to HRVB. as you give appropriate credit to the original author(s) and the source, This methodological variety, however, was not well provide a link to the Creative Commons licence, and indicate if changes reported in most of the studies and we detected several rel- were made. The images or other third party material in this article are evant deficiencies in the published studies that applied an included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in HVRB intervention. 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