A Transdiagnostic pilot study of the efficacy of respiratory rate–based biofeedback in the treatment of depressive symptoms

A Transdiagnostic pilot study of the efficacy of respiratory rate–based biofeedback in the treatment of depressive symptoms | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Transdiagnostic pilot study of the efficacy of respiratory rate–based biofeedback in the treatment of depressive symptoms Aleksey Ovchinnikov, Ksenia Sryvkova, Vadim Kryukov, Aleksandr Kolsanov, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8910823/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract There remains a need to identify short-term, safe interventions for depressive symptoms that can be integrated into standard treatment without imposing a substantial burden on patients or clinical staff. Aims This study evaluated the efficacy of respiratory rate–based biofeedback as an adjunctive intervention for depressive symptoms in hospitalized patients with mental disorders. Methods This prospective pilot study included 84 patients diagnosed with depressive or anxiety disorders. In the intervention group, participants received biofeedback therapy once daily for 10 days in addition to standard pharmacotherapy. The comparison group received pharmacotherapy alone. Results The adjusted between-group difference in the total Montgomery–Asberg Depression Rating Scale (MADRS) score after 3 weeks of treatment was 2.18 points (95% CI [0.17;4.18]; p = 0.034). Among study completers, 40% of patients in the biofeedback group met the criterion for treatment response, compared with 28% in the comparison group; the number needed to treat (NNT) was 9. The addition of biofeedback therapy to standard treatment was not associated with a greater reduction in anxiety symptoms. No clinically prominent adverse events were reported. Conclusions Adding biofeedback therapy sessions to standard treatment resulted in a small reduction in depressive symptoms compared with standard therapy alone. These findings support consideration of respiratory rate–based biofeedback as a potential adjunctive intervention that may enhance the effectiveness of treatment for depressive symptoms in inpatient settings within routine clinical practice. Trial registration The study was registered retrospectively (https://doi.org/10.17605/OSF.IO/R38YW; 2026, February 12). biofeedback depression virtual reality intervention Figures Figure 1 Figure 2 Figure 3 Introduction According to analyses from the Global Burden of Disease study, more than 332 million people worldwide are living with depressive disorders (Zhou et al., 2025 ). Despite the high efficacy of psychotherapy and pharmacotherapy, a substantial proportion of patients do not achieve sufficient symptom reduction with antidepressant treatment (Oliveira-Maia et al., 2024 ). The need to identify additional therapeutic approaches is also driven by the limited tolerability of pharmacotherapy (Gartlehner et al., 2023 ), the insufficient availability of psychotherapy (Fonagy & Luyten, 2021 ), and patient preferences (McHugh et al., 2013 ). Collectively, these considerations sustain interest in short-term, safe, and reproducible interventions that can be incorporated into standard treatment without imposing a substantial burden on patients or clinical staff. One such approach is biofeedback (BFB) therapy. Within this framework, patients are provided with information about parameters of a physiological process, thereby rendering typically nonconscious responses accessible for voluntary regulation and facilitating the acquisition of self-regulation skills (Fernández-Alvarez et al., 2022 ). The development of portable sensors, mobile applications, and remote monitoring technologies broadens the feasibility of implementing biofeedback therapy in routine clinical practice. In addition, biofeedback can be delivered using virtual reality (VR) headsets, which may increase patient engagement and facilitate the performance of exercises (Pancini et al., 2025 ). Across a large number of studies, slow breathing without feedback has demonstrated efficacy in reducing the severity of stress, anxiety, and depressive symptoms in healthy volunteers (Fincham et al., 2023 ). In a recent randomized clinical trial, adjunctive use of resonant slow breathing was well tolerated, reduced anxiety, and improved sleep quality in hospitalized patients with depression, supporting the relevance of such approaches in inpatient practice (Canazei et al., 2025 ). The primary aim of the present study was to evaluate the efficacy of respiratory rate–based biofeedback as an adjunctive treatment in hospitalized patients with anxiety or depressive disorders. It was hypothesized that 10 days of biofeedback therapy sessions would result in a greater reduction in the total MADRS score by the end of hospitalization. Secondary objectives included assessing the efficacy of biofeedback therapy in alleviating anxiety symptoms, as well as investigating factors related to the effects of biofeedback treatment. Materials and Methods Patients The study included patients aged 18 to 60 years receiving inpatient treatment at the Affective Disorders Unit of the Moscow Research Institute of Psychiatry in 2024 and 2025. Eligible participants had International Classification of Diseases, 10th Revision (ICD-10) diagnoses of depressive and anxiety disorders: depressive episode (F32.0–F32.2), recurrent depressive disorder (F33.0–F33.2), mixed anxiety and depressive disorder (F41.2), generalized anxiety disorder (F41.1), a depressive episode within bipolar affective disorder (F31.3), or cyclothymia (F34.0). Only patients with clinically significant depressive symptoms (MADRS ≥ 10) were included. Exclusion criteria were: 1) indications of an organic etiology of the mental disorder (e.g., neurological disease, traumatic brain injury); 2) intellectual disability or schizotypal disorder; 3) substance-related and addictive disorders; 4) a history of psychotic symptoms; 5) receiving additional treatments not included in the study design. Assessment Assessment included a clinical interview, collection of anamnestic information, and completion of standardized clinical psychometric instruments. The following variables were recorded: age, sex, duration of illness, treatments administered during hospitalization, and length of stay. The severity of depressive and anxiety symptoms was evaluated using the Montgomery–Asberg Depression Rating Scale (MADRS) (Montgomery & Asberg, 1979 ) and the Hamilton Anxiety Rating Scale (HARS) (Hamilton, 1959 ). Study Design This was a prospective study. Each patient was assessed with the MADRS and HARS after enrollment and at the end of the study. Because of the inpatient setting and the possibility of early discharge, the follow-up assessment was performed 20–27 days after the initial assessment. In cases of earlier discharge, the follow-up assessment was conducted immediately prior to discharge and was used in the analysis as the endpoint. Half of the enrolled patients were allocated to standard therapy (ST), and the other half to standard pharmacotherapy combined with biofeedback sessions delivered via the ReviSide system (ST + BFB). Participants were assigned sequentially based on their enrollment order: the first enrolled patient was placed in the biofeedback group, the second in the control group, and this pattern continued for all subsequent participants. Pharmacological treatment was prescribed by the treating physician in accordance with clinical guidelines, irrespective of study participation. Biofeedback Participants allocated to the ST + BFB group completed at least 10 sessions on the ReviSide system at a frequency of 5 sessions per week; each session lasted approximately 25 minutes. Patients who wished to continue biofeedback sessions beyond the 10 sessions stipulated in the study protocol were permitted to do so at their request. The ReviSide system includes a VR headset and a respiratory rate sensor. The sessions took place in a quiet room, and the patient stayed seated. In each session, participants listened to soothing music and viewed a virtual landscape via a VR headset. Each session consisted of five core stages with progressively increasing task difficulty and two diagnostic stages. Session difficulty was calculated based on the participant’s respiratory rate during the first diagnostic stage. Across each of the five training stages, the task became more demanding, and the participant was required to reduce respiratory rate by 10% relative to baseline. If the breathing rate did not exceed the acceptable threshold, patients observed positive changes in the landscape (calm sea, northern lights) (Fig. 1 ). All sessions were conducted under the supervision of a researcher. Statistical Analysis Statistical analyses were performed using SPSS (IBM SPSS Statistics 31.0.1.0). Two-sided tests were used throughout. The null hypothesis was rejected at a statistical significance level of p ≤ 0.05. The primary analysis was conducted per protocol (per-protocol, PP) and included patients who completed the biofeedback course (at least 10 sessions) and had MADRS endpoint data. To assess the robustness of the per-protocol findings, we repeated the primary analysis in the full intention-to-treat (ITT) population. Quantitative variables are presented as median and quartiles. Baseline comparability between groups was assessed using the standardized mean difference (d). The effect of biofeedback therapy on MADRS and HARS scores at follow-up was assessed using a general linear model with analysis of covariance (ANCOVA). Potential predictors of biofeedback therapy effectiveness were examined using linear regression. The within-group effect size was calculated using the standardized mean difference. Figures were generated in JASP, version 0.95.4. Comparisons between participants who discontinued the study and those who completed follow-up were conducted using the Mann–Whitney U test and Fisher’s exact test. Sample Size The planned sample size was estimated using G*Power, version 3.1. Expected differences in depression severity were derived from the systematic review by Fernández-Alvarez J. (2022), which pooled different biofeedback therapy modalities. In the meta-analysis, the standardized effect size for biofeedback therapy versus control was g = 0.717. With α = 0.05 and 80% power, the minimum group size was 32 participants. Thus, the estimated minimum total sample size required to detect statistically significant differences in mean reductions in MADRS scores was 64 participants. Results A total of 84 patients were enrolled, with 42 allocated to the biofeedback group and 42 to the control group (Fig. 2 ). In four cases, participants were determined to not meet the inclusion criteria after allocation; therefore, their data were not included in the analysis (history of psychotic symptoms, diagnostic revision during treatment, and additional transcranial magnetic stimulation during study participation). Follow-up data were obtained for 78 patients (39 in the intervention group and 39 in the control group). Six cases were excluded from the final analysis due to insufficient biofeedback sessions (fewer than 10). Specifically, two participants were unable to initiate therapy due to technical difficulties, while four were transferred to a partial hospitalization setting by the treating physician. Participants who completed an insufficient number of biofeedback sessions did not differ from study completers on key baseline characteristics (see Appendix for details). Table 1 presents baseline demographic and clinical characteristics of participants at enrollment (excluding the four cases classified as inclusion errors). Most participants received antidepressants (65%) and anxiolytics (58%). Nearly all participants were already receiving medication at the time of enrollment. The median duration of illness was 2.5 years (interquartile range = 3.0). Most participants completed 10 biofeedback sessions (median = 10; maximum = 17) (see Appendix for details). The number of sessions was not associated with reductions in MADRS (r = 0.15, p = 0.37) or HARS scores (r = − 0.20, p = 0.24). Table 1 Comparison of baseline characteristics of the study samples Biofeedback group Control group Standardized mean difference (d) Total N 41 39 Age, median (Q1–Q3) 27 (23–43) 26 (21–34) 0.31 Female, n (%) 21 (53.8%) 17 (41.5%) 0.25 Illness duration, median (Q1–Q3) 2.5 (1–4) 3.0 (1–4) −0.18 Receiving an antidepressant, n (%) 28 (68%) 24 (61.5%) 0.28 Receiving an anxiolytic, n (%) 24 (58.5%) 22 (56.4%) 0.11 Receiving a mood stabilizer, n (%) 19 (46%) 23 (59%) -0.15 MADRS, median (Q1–Q3) 19 (16 − 22) 18 (16–21) 0.15 HARS, median (Q1–Q3) 21 (16–24) 18 (15–22) 0.32 Depressive episode (F32), n (%) 6 (15%) 7 (18%) 0.09 Recurrent depressive disorder (F33), n (%) 9 (22%) 11 (28%) 0.14 Mixed anxiety and depressive disorder (F41.2), n (%) 7 (17%) 6 (15%) -0.05 Generalized anxiety disorder (F41.1), n (%) 3 (7%) 3 (8%) 0.01 Bipolar disorder, current depressive episode, n (%) 10 (24%) 8 (21%) -0.09 Cyclothymia, n (%) 6 (15%) 4 (10%) -0.13 Efficacy of biofeedback therapy in reducing depressive symptom severity Both groups demonstrated a substantial reduction in depressive symptom severity over the observation period: the median reduction in MADRS scores was 8 points in the biofeedback group and 6 points in the control group (Table 2 ). The pre–post difference in total MADRS scores was statistically significant in both groups (p < 0.001). Table 2 Changes in MADRS and HARS scores during treatment Baseline, median (Q1–Q3) End of study, median (Q1–Q3) p for within-group Δ Median reduction, median (Q1–Q3) Standardized mean difference (within-group effect size), d [95% CI] Standard therapy + biofeedback MADRS 18.5 (16–21) 9 (8–11) < 0.001 8 (6.25–12) 1.81 [0.18;3.44] HARS 21 (16–24) 10 (7–13.5) < 0.001 11 (9–13) 2.49 [1.04;3.94] Standard therapy MADRS 18 (16–21) 12 (9–15) < 0.001 6 (3–9) 1.34 [− 0.11;2.79] HARS 19 (15–22) 11 (9–14) < 0.001 8 (4–11) 1.86 [0.53;3.19] The main study outcomes are presented in Table 3 . Reductions in MADRS scores did not depend on diagnostic group membership (see Appendix for details) but were associated with baseline symptom severity. The adjusted between-group difference in total MADRS scores at the follow-up assessment was 2.18 points (95% CI [0.17, 4.18]; p = 0.034). ITT analyses yielded results comparable to the primary analysis (see Appendix). Table 3 ANCOVA results for MADRS and HARS outcomes at the end of the study df Adjusted between-group difference F 95% CI p Partial η² MADRS Biofeedback therapy 1 2.18 4.70 [0.17;4.18] 0.034 0.07 Diagnosis 2 — 0.83 ⸻ 0.442 0.024 Antidepressant prescribed (yes vs no) 1 -0.62 0.34 [-2.73; 1.49] 0.56 0.005 Anxiolytic prescribed (yes vs no) 1 0.58 0.26 [-1.71; 2.88] 0.61 0.004 Mood stabilizer prescribed (yes vs no) 1 1.84 2.61 [-0.43; 4.12] 0.11 0.035 Baseline MADRS 1 — 10.55 — 0.002 0.129 HARS Biofeedback therapy 1 1.62 3.167 [-0.19; 3.43] 0.079 0.043 Diagnosis 2 — 0.3 ⸻ 0.74 0.01 Antidepressant prescribed (yes vs no) 1 -0.83 0.658 [-2.86; 1.20] 0.42 0.009 Anxiolytic prescribed (yes vs no) 1 2.23 4.56 [0.14; 4.31] 0.037 0.065 Mood stabilizer prescribed (yes vs no) 1 -0.97 0.92 [-2.99; 1.05] 0.34 0.012 Baseline HARS 1 — 12.16 — 0.001 0.146 Note. N = 74. MADRS scores at the second assessment point were specified as the dependent variable. All factors listed in the table were entered into a single model (“biofeedback therapy,” “diagnosis,” “antidepressant prescribed,” “anxiolytic prescribed,” and “mood stabilizer prescribed” as fixed factors; baseline MADRS or baseline HARS as the covariate). The “adjusted between-group difference” column reports the difference in the dependent variable (MADRS or HARS score at follow-up) between categories after adjustment for the other model variables. Partial η² represents the proportion of variance in the dependent variable explained by the predictor after accounting for the remaining predictors. The diagnosis variable had three categories: 1) unipolar depressions (F32 and F33); 2) bipolar spectrum disorders (F31 and F34); 3) anxiety disorders (F41 and F41.2). Among participants who completed the study, treatment response (≥ 50% reduction in total MADRS score) was achieved by 14 (40%) patients in the biofeedback group and by 11 (28%) patients in the comparison group. Accordingly, the NNT for biofeedback therapy was 9. No factors associated with the efficacy of biofeedback therapy in the treatment of depressive symptoms were identified (Table 4 ). Table 4 Associations of additional factors with biofeedback therapy outcomes Factor B 95% CI for B p ΔR² B 95% CI for B p ΔR² MADRS HARS Length of observation in the ward (days) -0.008 [-0.19; 0.18] 0.93 0.001 -0.09 [-0.26; 0.07] 0.24 0.27 Age (years) -0.019 [-0.1; 0.07] 0.65 0.05 0.10 [0.02; 0.18] 0.02 0.39 Sex 0.78 [-1.80; 3.37] 0.54 0.013 0.67 [-1.52; 2.86] 0.53 0.23 Illness duration (years) -0.04 [-0.68; 0.6] 0.9 0.003 0.49 [-0.05; 1.05] 0.07 0.29 Diagnosis (unipolar depression vs anxiety disorders) 0.10 [-0.26; 0.34] 0.94 0.06 0.59 [-1.5; 2.72] 0.57 0.23 Diagnosis (bipolar spectrum vs anxiety disorders) -1.57 [-4.56; 1.43] 0.29 0.056 -0.55 [-2.86; 1.75] 0.63 0.23 Note. To test the effect of each factor, a separate linear regression model was built. Only patients from the biofeedback group were included. The MADRS or HARS scores at the end of the study were specified as the dependent variable. In each model, baseline MADRS or baseline HARS was included as an independent predictor. In all cases n = 35. Both study groups also demonstrated a significant reduction in anxiety symptom severity: the median reduction in HARS scores was 11 points in the biofeedback group and 8 points in the standard therapy group. However, between-group differences were not statistically significant after controlling for other factors (adjusted between-group difference = 1.62; 95% CI [− 0.19, 3.43]; p = 0.079) (Table 3 ). As expected, reductions in HARS scores were associated with baseline anxiety severity (p = 0.001) and the prescription of an anxiolytic (adjusted between-group difference = 2.23; 95% CI [0.14, 4.31]; p = 0.037). Less improvement in anxiety symptoms within the biofeedback group was observed among older patients (B = 0.10; 95% CI [0.02, 0.18]; p = 0.02) and among patients with longer illness duration (B = 0.49; 95% CI [− 0.05, 1.05]; p = 0.07) (Table 4 ). Biofeedback therapy was well tolerated. Participants reported a total of four adverse events: dizziness (two cases), increased anxiety (one case), and back pain (one case). Several participants reported discomfort when wearing a VR headset concurrently with their prescription eyeglasses. Discussion The present study evaluated the efficacy of respiratory rate–based biofeedback therapy in the treatment of depressive symptoms in a transdiagnostic inpatient sample. The addition of biofeedback sessions to standard treatment yielded a small but statistically significant reduction in depressive symptoms. The adjusted between-group difference in MADRS scores was 2.18 points. Among study completers, 40% of participants in the biofeedback group met the response criterion, compared with 28% in the comparison group, corresponding to an NNT of 9. Adding biofeedback therapy to standard treatment did not result in a greater reduction in anxiety symptom severity. No predictors of biofeedback efficacy for depressive symptoms were identified among the examined parameters. However, among patients receiving biofeedback therapy, lower anxiety severity at study end was observed in younger patients with shorter illness duration. A large systematic review by Fernández-Alvarez J. (2022), which combined multiple biofeedback modalities, similarly reported no clinical or sociodemographic factors associated with treatment efficacy. At the same time, younger age and shorter illness duration are often considered potential moderators of pharmacotherapy and psychotherapy outcomes for anxiety disorders (Mills et al., 2024 ; Kim et al., 2021; González-Blanch et al., 2021 ). The modest between-group difference in MADRS reduction may reflect a relatively short observation period and a limited number of biofeedback sessions. However, systematic reviews encompassing different biofeedback modalities have not identified an association between the number of sessions and treatment efficacy (Vann-Adibe et al., 2025 ; Fernández-Alvarez et al., 2022 ). No other studies evaluating respiratory rate–based biofeedback therapy for depressive symptoms were identified. All identified studies that examined biofeedback based on respiratory parameters (respiratory rate or exhaled CO₂ concentration) focused on the treatment of panic disorder (Meuret et al., 2008 ; Meuret et al., 2010 ; Kim et al., 2012 ; Tolin et al., 2017 ; Cuyler et al., 2022 ). In two of these studies, statistically significant reductions in depressive symptom severity were also reported during treatment compared with patients placed on a waitlist (Meuret et al., 2008 ; Kim et al., 2012 ). In addition, a substantial literature exists on depression treatment using heart rate variability (HRV) biofeedback. This approach trains patients to modulate heart rhythm through controlled, slow, rhythmic breathing and appears to involve mechanisms that overlap with respiratory rate–based biofeedback. A systematic review by Vann-Adibe S (2025), encompassing 10 randomized controlled trials, found that HRV therapy demonstrated a moderate effect size in alleviating depressive symptoms. The absence of a statistically significant between-group difference in HARS scores is inconsistent with prior studies reporting efficacy of respiratory biofeedback approaches in panic disorder (Meuret et al., 2008 ; Meuret et al., 2010 ; Kim et al., 2012 ; Tolin et al., 2017 ; Cuyler et al., 2022 ). This discrepancy may be attributable to the inpatient context of treatment, the high frequency of anxiolytic prescriptions, and consequently the marked reduction in anxiety symptoms in both groups in the present study. However, despite controlling for anxiolytic prescriptions, the differences between the groups remained statistically non-significant. Additionally, the distribution of HARS scores at the end of the study showed considerable variability and did not exhibit a clear clustering at the lower end of the scale, indicating that a "floor effect" was not evident (see Appendix). In prior studies pharmacotherapy was not restricted, and its effects on symptom reduction were not accounted for (Meuret et al., 2008 ; Kim et al., 2012 ; Cuyler et al., 2022 ). Another potential explanation is that respiratory biofeedback may be specifically effective for panic disorder rather than for other anxiety disorders. It has been proposed that regular respiratory slowing exercises contribute to chemoreceptor desensitization, thereby reducing vulnerability to CO₂ fluctuation–triggered panic attacks and decreasing sensitivity to the “suffocation false alarm” mechanism (suffocation false alarm theory) (Meuret et al., 2008 ; Meuret et al., 2010 ). Several mechanisms may account for the efficacy of respiratory rate–based biofeedback therapy in reducing depressive symptoms. Biofeedback therapy requires the patient to concentrate on breathing, which is similar to mindfulness- and meditation-based practices; focusing attention on the present moment and bodily sensations has been associated with reductions in ruminative thinking (Lehrer & Gevirtz, 2014 ). Rhythmic breathing at approximately 6 cycles per minute synchronizes respiratory, cardiac, and baroreflex rhythms, thereby increasing vagal afferent signaling to the nucleus tractus solitarius in the brainstem (Sevoz-Couche & Laborde, 2022 ). Enhanced vagal afferent input is proposed to activate the nucleus tractus solitarius and modulate activity in ventromedial and dorsolateral prefrontal cortex, anterior cingulate cortex, insular cortex, amygdala, hypothalamus, thalamus, and brainstem structures. These regions comprise the central autonomic network, which plays an important role in emotion regulation (Rosso et al., 2020 ; Sevoz-Couche & Laborde, 2022 ; Krieger & Skibicka, 2025 ). Another potential consequence of nucleus tractus solitarius activation is enhanced descending vagal influence (Sevoz-Couche & Laborde, 2022 ), including activation of the cholinergic anti-inflammatory pathway and reduced release of TNF-α, IL-6, and other cytokines by macrophages (Matteoli et al., 2014 ; Bonaz et al., 2016 ; Wu et al., 2025 ). However, hypothesized mechanisms remain either speculative or represent an extrapolation from data on HRV biofeedback mechanisms. Overall, the method was generally well tolerated; however, the frequency of adverse events was not systematically assessed. Other studies have likewise reported an absence of prominent adverse events associated with respiratory biofeedback interventions. In similar studies, the most commonly reported adverse events were dizziness, lightheadedness, and a sensation of air hunger, typically occurring early in treatment (Tolin et al., 2017 ; Cuyler et al., 2022 ; Vann-Adibe et al., 2025 ). This aligns with the broader literature indicating good tolerability across various biofeedback modalities (Cuyler et al., 2022 ; Fernández-Alvarez et al., 2022 ; Vann-Adibe et al., 2025 ). The study has several substantial limitations. First, the alternating method of group assignment does not constitute full randomization. Nevertheless, the study groups did not differ materially in baseline characteristics. The absence of blinding among patients and investigators may have increased expectancy effects and influenced ratings on administered scales. Participants in the intervention group received more attention from clinical staff due to the regularity of biofeedback sessions. Adverse event monitoring in this study was based on spontaneous reporting. As a result, mild adverse events are likely to have been underreported. Pharmacological treatment was not standardized; changes in medication type and dosage were permitted during treatment. In statistical analyses, control for pharmacotherapy was limited to medication classes, without accounting for specific agents and dosages. This limitation reflected the small sample size and the restricted number of predictors that could be simultaneously included in ANCOVA models. Additional limitations include the brief duration of active treatment and the absence of delayed follow-up assessments to evaluate the durability of effects. Attrition was uneven and related to the operational characteristics of the inpatient unit. A proportion of patients in both groups who showed symptom improvement and good medication tolerability were transferred to a semi-inpatient regimen involving clinic visits twice weekly. This did not prevent the collection of follow-up data for these patients at the second time point; however, it limited the completion of sufficient biofeedback sessions. As a result, attrition was more frequent in the intervention group. ITT results were comparable to the primary analysis (see Appendix). Comparisons between patients who discontinued participation and those who completed follow-up did not reveal substantial baseline differences. Finally, the sample was highly heterogeneous, as patients with different diagnoses were included, provided that clinically significant depressive symptoms were present. Such pooling was considered acceptable because the presumed mechanisms of efficacy were hypothesized to involve shared pathogenic pathways across different mental disorders. It should also be noted that, in routine clinical practice, diagnoses of affective and anxiety disorders demonstrate low reproducibility and temporal stability (Baca-García et al., 2007 ; Regier et al., 2013 ; Marchi et al., 2021 ). Diagnosis did not affect treatment efficacy in the statistical analyses. Diagnostic groups did not differ significantly in the magnitude of depressive symptom reduction, whereas reductions in MADRS scores were clearly associated with baseline symptom severity. Conclusion In a prospective pilot study conducted under real-world clinical conditions with a transdiagnostic inpatient sample, the addition of respiratory rate-based biofeedback therapy utilizing the ReviSide hardware-software system was found to be both feasible and implementable. This intervention was associated with a greater improvement in depressive symptoms compared to standard therapy alone. These findings support consideration of respiratory rate–based biofeedback as a potential adjunctive intervention that may enhance the efficacy of treatment for depressive symptoms among inpatients in routine clinical practice. These preliminary results necessitate further investigation through longer and methodologically more rigorous studies. Declarations Author information Authors and Affiliations Moscow Research Institute of Psychiatry – branch of V. Serbsky National Medical Research Centre for Psychiatry and Narcology, 107076, Russia, Moscow, Kropotkinsky Lane, Building 23. Ovchinnikov A.V., Sryvkova K.A., Kryukov V.V., Akhapkin R.V., Shport S.V. Samara State Medical University (SamSMU), 443099, Russia, Samara, 89 Chapayevskaya Street Kolsanov A.V., Berkovich E. N., Isaev D.S., Berkovich E. N. Contributions ARV, OVA and KVV contributed to the study conception and design. Material preparation, data collection and analysis were performed by OVA, SKA and KVV. The first draft of the manuscript was written by OVA and all authors commented on previous versions of the manuscript. ARV and SSV supervised and revised the manuscript. KAV, CSS, BEN and IDS were responsible for providing the necessary equipment and technical support for the study. All authors read and approved the final manuscript. Author Information: Ovchinnikov A.V. — https://orcid.org/0000-0002-9605-8527 Sryvkova K.A. — https://orcid.org/0009-0000-9902-1749 Kryukov V.V. — https://orcid.org/0000-0002-9099-0989 Kolsanov A.V. — https://orcid.org/0000-0002-4144-7090 Chaplygin S.S. — https://orcid.org/0000-0002-9027-6670 Isaev D.S. — https://orcid.org/0009-0008-6193-0478 Berkovich E. N. — https://orcid.org/0009-0003-3861-485X Akhapkin R.V. — https://orcid.org/0000-0002-7045-0547 Shport S.V. — https://orcid.org/0000-0003-0739-4121 Conflict of interest The authors declare that there is no financial conflict of interest. ReviSide Inc. provided the devices used in the present study during the research period. Ethical Approval This research was performed in line with the principles of the Declaration of Helsinki. This study was approved by the Research Ethics Committee of the Moscow Research Institute of Psychiatry. Consent for Participation Informed consent was obtained from all individual participants included in the study. Consent for Publication The participant has consented to the submission of the research to the journal. Funding This study was conducted within the framework of the State Task “Development of a clinical–pathogenetic model and a diagnostic module for anxiety–depressive spectrum disorders in patients with chronic pathology” (registration number: НИОКТР 124020800061-8) and was funded by the Ministry of Health of the Russian Federation. Author Contribution ARV, OVA and KVV contributed to the study conception and design. Material preparation, data collection and analysis were performed by OVA, SKA and KVV. The first draft of the manuscript was written by OVA and all authors commented on previous versions of the manuscript. ARV and SSV supervised and revised the manuscript. KAV, CSS, BEN and IDS were responsible for providing the necessary equipment and technical support for the study. All authors read and approved the final manuscript. Data Availability Due to the nature of this research, participants of this study did not agree for their data to be shared publicly, so supporting data is not available. References Baca-García, E., Perez-Rodriguez, M. M., Basurte-Villamor, I., et al. (2007). Diagnostic stability of psychiatric disorders in clinical practice. The British Journal of Psychiatry , 190 (3), 210–216. 10.1192/bjp.bp.106.024026 Bonaz, B., Sinniger, V., & Pellissier, S. (2016). Anti-inflammatory properties of the vagus nerve: Potential therapeutic implications of vagus nerve stimulation. The Journal of Physiology , 594 (20), 5781–5790. 10.1113/JP271539 Canazei, M., Hüfner, K., Sperner-Unterweger, B., et al. (2025). Resonant breathing in hospitalised psychiatric patients with persistent somatic symptoms: A randomised controlled trial. General Psychiatry , 38 (6), e102357. 10.1136/gpsych-2025-102357 PMID: 41324027; PMCID: PMC12658502. Cuyler, R. N., Valdes, J., Porges, S. W., et al. (2022). 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Nonpharmacologic and pharmacologic treatments of adult patients with major depressive disorder: A systematic review and network meta-analysis for a clinical guideline by the American College of Physicians. Annals of Internal Medicine , 176 (2), 196–211. 10.7326/M22-1845 González-Blanch, C., Muñoz-Navarro, R., Medrano, L. A., et al. (2021). Moderators and predictors of treatment outcome in transdiagnostic group cognitive-behavioral therapy for primary care patients with emotional disorders. Depression and Anxiety , 38 (7), 757–767. 10.1002/da.23164 Hamilton, M. (1959). The assessment of anxiety states by rating. British Journal of Medical Psychology , 32 (1), 50–55. 10.1111/j.2044-8341.1959.tb00467.x Kim, S., Park, D., Lee, S., et al. (2012). Breathing training for panic disorder: Effects on panic symptoms and respiratory physiology. Journal of Anxiety Disorders , 26 (1), 42–50. 10.1016/j.janxdis.2011.09.002 Kim, S. K. (2021). Age moderated-anxiety mediation for multimodal treatment outcomes in children with OCD and anxiety disorders. Journal of Anxiety Disorders. PubMed PMID: 33601717. Krieger, J. P., & Skibicka, K. P. (2025). From physiology to psychiatry: Key role of vagal interoceptive pathways in emotional control. Biological Psychiatry. ;advance online publication. 10.1016/j.biopsych.2025.04.012 Lehrer, P. M., & Gevirtz, R. (2014). Heart rate variability biofeedback: How and why does it work? Frontiers in Psychology , 5 , 756. 10.3389/fpsyg.2014.00756 Marchi, M., Magarini, F. M., Mattei, G., et al. (2021). Diagnostic agreement between physicians and a consultation–liaison psychiatry team at a general hospital: An exploratory study across 20 years of referrals. International Journal of Environmental Research and Public Health , 18 (2), 749. 10.3390/ijerph18020749 Matteoli, G., Gomez-Pinilla, P. J., Nemethova, A., et al. (2014). A distinct vagal anti-inflammatory pathway modulates intestinal muscularis resident macrophages independent of the spleen. Gut , 63 (6), 938–948. 10.1136/gutjnl-2013-304676 McHugh, R. K., Whitton, S. W., Peckham, A. D., et al. (2013). Patient preference for psychological vs pharmacologic treatment of psychiatric disorders: A meta-analytic review. Journal of Clinical Psychiatry , 74 (6), 595–602. 10.4088/JCP.12r07757 Meuret, A. E., Rosenfield, D., Seidel, A., Bhaskara, L., & Hofmann, S. G. (2010). Respiratory and cognitive mediators of treatment change in panic disorder: Evidence for intervention specificity. Journal of Consulting and Clinical Psychology , 78 (5), 691–704. 10.1037/a0019552 Meuret, A. E., Wilhelm, F. H., Ritz, T., et al. (2008). Breathing training for treating panic disorder: Useful intervention or placebo? Behaviour Research and Therapy , 46 (9), 1065–1074. 10.1016/j.brat.2008.06.004 Mills, J. A., Mendez, E. M., & Strawn, J. R. (2024). The impact of development on antidepressant and placebo response in anxiety disorders: A Bayesian hierarchical meta-analytic examination of randomized controlled trials in children, adolescents, and adults. Journal of Child and Adolescent Psychopharmacology , 34 (7). 10.1089/cap.2024.0016 Montgomery, S. A., & Asberg, M. (1979). A new depression scale designed to be sensitive to change. British Journal of Psychiatry. ;134:382–389. 10.1192/bjp.134.4.382 . PMID: 444788. Oliveira-Maia, A. J., Bobrowska, A., Constant, E., et al. (2024). Treatment-Resistant Depression in Real-World Clinical Practice: A Systematic Literature Review of Data from 2012 to 2022. Advances in Therapy , 41 , 34–64. 10.1007/s12325-023-02700-0 Pancini, E., Di Natale, A. F., & Villani, D. (2025). Breathing in virtual reality for promoting mental health: A scoping review. Virtual Reality , 29 , 29. 10.1007/s10055-024-01096-8 Regier, D. A., Narrow, W. E., Clarke, D. E., et al. (2013). DSM-5 field trials in the United States and Canada, Part II: Test-retest reliability of selected categorical diagnoses. American Journal of Psychiatry , 170 (1), 59–70. 10.1176/appi.ajp.2012.12070999 Rosso, P., Iannitelli, A., Pacitti, F., et al. (2020). Vagus nerve stimulation and neurotrophins: A biological psychiatric perspective. Neuroscience & Biobehavioral Reviews , 113 , 338–353. 10.1016/j.neubiorev.2020.03.034 Sevoz-Couche, C., & Laborde, S. (2022). Heart rate variability and slow-paced breathing: When coherence meets resonance. Neuroscience & Biobehavioral Reviews , 135 , 104576. 10.1016/j.neubiorev.2022.104576 Tolin, D. F., Davies, C. D., Moskow, D. M., et al. (2017). Long-term outcomes of capnometry-assisted respiratory training for panic disorder: A naturalistic study. Applied Psychophysiology and Biofeedback , 42 (3), 183–191. 10.1007/s10484-017-9365-4 Vann-Adibe, S., Tsui, H. K. H., Zhou, H. Q. (2025). Efficacy and methodology of remote heart rate variability biofeedback interventions for mental health: A systematic review and meta-analysis. Applied Psychophysiology and Biofeedback. Nov 27. 10.1007/s10484-025-09750-w . Epub ahead of print. PMID: 41310318. Wu, L., Li, J., Zou, J., et al. (2025). Vagus nerve modulates acute-on-chronic liver failure progression via CXCL9. Chinese Medical Journal , 138 (9), 1103–1115. 10.1097/CM9.0000000000003104 Zhou, J., Zhang, Y., He, S., et al. (2025). Accelerated global burden of depressive disorders during the COVID-19 pandemic from 2019 to 2021. Scientific Reports , 15 , 9529. 10.1038/s41598-025-93923-4 Additional Declarations No competing interests reported. Supplementary Files Appendix.docx Additional information Appendix containing Tables A1-A3, Figures A1-A5 Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 25 Feb, 2026 Editor assigned by journal 20 Feb, 2026 Submission checks completed at journal 20 Feb, 2026 First submitted to journal 18 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8910823","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":597413444,"identity":"f40b9c66-0a38-4e55-9697-9cd9417e9ac5","order_by":0,"name":"Aleksey Ovchinnikov","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIie3OsYrCQBCA4cktWK3YzpLovcKGhbO8V9kQ0MbOxkKiNkkT+8DJPYZcGVg4m30EOZRAKh9Ai4PTyIEWK7ET2R8GppgPBsBme8waIAEoVvvoOAjkHqLrEqgOjzlxDdLCsNxsv9YeS1IOh8+o0/1ICkHhJ5gaCMt6XR7okrpUc2e+VMJbaxFSGBoJ17qBQaxoB3sSmss8yHBAFAVZjzi/i2iSYb+4TVbpmbgY5qQ5JRJRnh4zE5bEbxVhqcqV9638zNPCX3ApTKRFSMkOsXrH1Wy23Y2jV3STAncj2TaRq/L/5YXyOveXOft7hc1msz1zf5rLUbsreRJVAAAAAElFTkSuQmCC","orcid":"","institution":"V. 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Serbsky National Medical Research Centre for Psychiatry and Narcology","correspondingAuthor":false,"prefix":"","firstName":"Vadim","middleName":"","lastName":"Kryukov","suffix":""},{"id":597413451,"identity":"f8bc0085-8a50-48e2-8495-0647469d7e57","order_by":3,"name":"Aleksandr Kolsanov","email":"","orcid":"","institution":"Samara State Medical University (SamSMU)","correspondingAuthor":false,"prefix":"","firstName":"Aleksandr","middleName":"","lastName":"Kolsanov","suffix":""},{"id":597413453,"identity":"950320bb-fa36-49fb-83d2-1f0668df8938","order_by":4,"name":"Sergei Chaplygin","email":"","orcid":"","institution":"Samara State Medical University (SamSMU)","correspondingAuthor":false,"prefix":"","firstName":"Sergei","middleName":"","lastName":"Chaplygin","suffix":""},{"id":597413456,"identity":"b61698b7-2671-4f54-a36f-4d124dd880aa","order_by":5,"name":"Denis Isaev","email":"","orcid":"","institution":"Samara State Medical University (SamSMU)","correspondingAuthor":false,"prefix":"","firstName":"Denis","middleName":"","lastName":"Isaev","suffix":""},{"id":597413457,"identity":"80592603-418c-46df-a1ed-b916f16b796c","order_by":6,"name":"Elena Berkovich","email":"","orcid":"","institution":"Samara State Medical University (SamSMU)","correspondingAuthor":false,"prefix":"","firstName":"Elena","middleName":"","lastName":"Berkovich","suffix":""},{"id":597413462,"identity":"9fa14813-3814-41fd-adf8-06812cb0815e","order_by":7,"name":"Roman Akhapkin","email":"","orcid":"","institution":"V. Serbsky National Medical Research Centre for Psychiatry and Narcology","correspondingAuthor":false,"prefix":"","firstName":"Roman","middleName":"","lastName":"Akhapkin","suffix":""},{"id":597413470,"identity":"712f279d-1576-4b26-8a9d-c111cf586cdd","order_by":8,"name":"Svetlana Shport S.V.","email":"","orcid":"","institution":"V. Serbsky National Medical Research Centre for Psychiatry and Narcology","correspondingAuthor":false,"prefix":"","firstName":"Svetlana","middleName":"Shport","lastName":"S.V.","suffix":""}],"badges":[],"createdAt":"2026-02-18 16:23:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8910823/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8910823/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104168533,"identity":"b87a0cfd-7258-44ed-84ec-d10fbc2b7ad1","added_by":"auto","created_at":"2026-03-08 14:33:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":236357,"visible":true,"origin":"","legend":"\u003cp\u003eBiofeedback system and task interface. (a) The ReviSide \u003cstrong\u003ecomprises\u003c/strong\u003ea VR headset and a respiratory rate sensor. (b) Screenshot of the virtual landscape used during training; achieving the required 10% reduction in respiratory rate triggered positive visual changes in the environment.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8910823/v1/ab141983d85913bdd0db0456.png"},{"id":104168534,"identity":"b66f041e-809c-41cd-96e3-4e1c12d8e8b0","added_by":"auto","created_at":"2026-03-08 14:33:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":54049,"visible":true,"origin":"","legend":"\u003cp\u003eFlow Diagram of Participant Enrollment and Follow-Up\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8910823/v1/f550134107c098b35c227974.png"},{"id":104403872,"identity":"e8ab28e7-2483-4e92-a244-f1d47bd81805","added_by":"auto","created_at":"2026-03-11 12:19:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":35262,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in MADRS and HARS scores in the study groups. Box plots show the median (horizontal line inside the box) and interquartile range (box) of score reductions from baseline to end of treatment. ST: standard therapy; ST+BFB: standard therapy combined with biofeedback. Both groups exhibited significant within-group reductions (p\u0026lt;0.001); the ST+BFB group achieved larger median decreases in both scales.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8910823/v1/c249ae8ca9068004229a2dfe.png"},{"id":104409243,"identity":"5fb6b097-d9d7-43ae-a054-0116b5f1f3d3","added_by":"auto","created_at":"2026-03-11 12:44:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1287448,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8910823/v1/4f7d324c-1773-49ea-b638-cc8202d5057d.pdf"},{"id":104403884,"identity":"9269b1a1-8cf6-4c70-9b13-7e49d8801bb3","added_by":"auto","created_at":"2026-03-11 12:19:17","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":172544,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAppendix containing Tables A1-A3, Figures A1-A5\u003c/p\u003e","description":"","filename":"Appendix.docx","url":"https://assets-eu.researchsquare.com/files/rs-8910823/v1/aac662b19e058c7a523591d7.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Transdiagnostic pilot study of the efficacy of respiratory rate–based biofeedback in the treatment of depressive symptoms","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccording to analyses from the Global Burden of Disease study, more than 332\u0026nbsp;million people worldwide are living with depressive disorders (Zhou et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Despite the high efficacy of psychotherapy and pharmacotherapy, a substantial proportion of patients do not achieve sufficient symptom reduction with antidepressant treatment (Oliveira-Maia et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The need to identify additional therapeutic approaches is also driven by the limited tolerability of pharmacotherapy (Gartlehner et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), the insufficient availability of psychotherapy (Fonagy \u0026amp; Luyten, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and patient preferences (McHugh et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Collectively, these considerations sustain interest in short-term, safe, and reproducible interventions that can be incorporated into standard treatment without imposing a substantial burden on patients or clinical staff.\u003c/p\u003e \u003cp\u003eOne such approach is biofeedback (BFB) therapy. Within this framework, patients are provided with information about parameters of a physiological process, thereby rendering typically nonconscious responses accessible for voluntary regulation and facilitating the acquisition of self-regulation skills (Fern\u0026aacute;ndez-Alvarez et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The development of portable sensors, mobile applications, and remote monitoring technologies broadens the feasibility of implementing biofeedback therapy in routine clinical practice. In addition, biofeedback can be delivered using virtual reality (VR) headsets, which may increase patient engagement and facilitate the performance of exercises (Pancini et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAcross a large number of studies, slow breathing without feedback has demonstrated efficacy in reducing the severity of stress, anxiety, and depressive symptoms in healthy volunteers (Fincham et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In a recent randomized clinical trial, adjunctive use of resonant slow breathing was well tolerated, reduced anxiety, and improved sleep quality in hospitalized patients with depression, supporting the relevance of such approaches in inpatient practice (Canazei et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe primary aim of the present study was to evaluate the efficacy of respiratory rate\u0026ndash;based biofeedback as an adjunctive treatment in hospitalized patients with anxiety or depressive disorders. It was hypothesized that 10 days of biofeedback therapy sessions would result in a greater reduction in the total MADRS score by the end of hospitalization. Secondary objectives included assessing the efficacy of biofeedback therapy in alleviating anxiety symptoms, as well as investigating factors related to the effects of biofeedback treatment.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients\u003c/h2\u003e \u003cp\u003eThe study included patients aged 18 to 60 years receiving inpatient treatment at the Affective Disorders Unit of the Moscow Research Institute of Psychiatry in 2024 and 2025. Eligible participants had International Classification of Diseases, 10th Revision (ICD-10) diagnoses of depressive and anxiety disorders: depressive episode (F32.0\u0026ndash;F32.2), recurrent depressive disorder (F33.0\u0026ndash;F33.2), mixed anxiety and depressive disorder (F41.2), generalized anxiety disorder (F41.1), a depressive episode within bipolar affective disorder (F31.3), or cyclothymia (F34.0). Only patients with clinically significant depressive symptoms (MADRS\u0026thinsp;\u0026ge;\u0026thinsp;10) were included.\u003c/p\u003e \u003cp\u003eExclusion criteria were: 1) indications of an organic etiology of the mental disorder (e.g., neurological disease, traumatic brain injury); 2) intellectual disability or schizotypal disorder; 3) substance-related and addictive disorders; 4) a history of psychotic symptoms; 5) receiving additional treatments not included in the study design.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAssessment\u003c/h3\u003e\n\u003cp\u003eAssessment included a clinical interview, collection of anamnestic information, and completion of standardized clinical psychometric instruments. The following variables were recorded: age, sex, duration of illness, treatments administered during hospitalization, and length of stay. The severity of depressive and anxiety symptoms was evaluated using the Montgomery\u0026ndash;Asberg Depression Rating Scale (MADRS) (Montgomery \u0026amp; Asberg, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1979\u003c/span\u003e) and the Hamilton Anxiety Rating Scale (HARS) (Hamilton, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e1959\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eStudy Design\u003c/h3\u003e\n\u003cp\u003eThis was a prospective study. Each patient was assessed with the MADRS and HARS after enrollment and at the end of the study. Because of the inpatient setting and the possibility of early discharge, the follow-up assessment was performed 20\u0026ndash;27 days after the initial assessment. In cases of earlier discharge, the follow-up assessment was conducted immediately prior to discharge and was used in the analysis as the endpoint. Half of the enrolled patients were allocated to standard therapy (ST), and the other half to standard pharmacotherapy combined with biofeedback sessions delivered via the ReviSide system (ST\u0026thinsp;+\u0026thinsp;BFB). Participants were assigned sequentially based on their enrollment order: the first enrolled patient was placed in the biofeedback group, the second in the control group, and this pattern continued for all subsequent participants. Pharmacological treatment was prescribed by the treating physician in accordance with clinical guidelines, irrespective of study participation.\u003c/p\u003e\n\u003ch3\u003eBiofeedback\u003c/h3\u003e\n\u003cp\u003eParticipants allocated to the ST\u0026thinsp;+\u0026thinsp;BFB group completed at least 10 sessions on the ReviSide system at a frequency of 5 sessions per week; each session lasted approximately 25 minutes. Patients who wished to continue biofeedback sessions beyond the 10 sessions stipulated in the study protocol were permitted to do so at their request. The ReviSide system includes a VR headset and a respiratory rate sensor. The sessions took place in a quiet room, and the patient stayed seated. In each session, participants listened to soothing music and viewed a virtual landscape via a VR headset. Each session consisted of five core stages with progressively increasing task difficulty and two diagnostic stages. Session difficulty was calculated based on the participant\u0026rsquo;s respiratory rate during the first diagnostic stage. Across each of the five training stages, the task became more demanding, and the participant was required to reduce respiratory rate by 10% relative to baseline. If the breathing rate did not exceed the acceptable threshold, patients observed positive changes in the landscape (calm sea, northern lights) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). All sessions were conducted under the supervision of a researcher.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using SPSS (IBM SPSS Statistics 31.0.1.0). Two-sided tests were used throughout. The null hypothesis was rejected at a statistical significance level of p\u0026thinsp;\u0026le;\u0026thinsp;0.05. The primary analysis was conducted per protocol (per-protocol, PP) and included patients who completed the biofeedback course (at least 10 sessions) and had MADRS endpoint data. To assess the robustness of the per-protocol findings, we repeated the primary analysis in the full intention-to-treat (ITT) population. Quantitative variables are presented as median and quartiles. Baseline comparability between groups was assessed using the standardized mean difference (d). The effect of biofeedback therapy on MADRS and HARS scores at follow-up was assessed using a general linear model with analysis of covariance (ANCOVA). Potential predictors of biofeedback therapy effectiveness were examined using linear regression. The within-group effect size was calculated using the standardized mean difference. Figures were generated in JASP, version 0.95.4. Comparisons between participants who discontinued the study and those who completed follow-up were conducted using the Mann\u0026ndash;Whitney U test and Fisher\u0026rsquo;s exact test.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eSample Size\u003c/h2\u003e \u003cp\u003eThe planned sample size was estimated using G*Power, version 3.1. Expected differences in depression severity were derived from the systematic review by Fern\u0026aacute;ndez-Alvarez J. (2022), which pooled different biofeedback therapy modalities. In the meta-analysis, the standardized effect size for biofeedback therapy versus control was g\u0026thinsp;=\u0026thinsp;0.717. With α\u0026thinsp;=\u0026thinsp;0.05 and 80% power, the minimum group size was 32 participants. Thus, the estimated minimum total sample size required to detect statistically significant differences in mean reductions in MADRS scores was 64 participants.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 84 patients were enrolled, with 42 allocated to the biofeedback group and 42 to the control group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In four cases, participants were determined to not meet the inclusion criteria after allocation; therefore, their data were not included in the analysis (history of psychotic symptoms, diagnostic revision during treatment, and additional transcranial magnetic stimulation during study participation).\u003c/p\u003e \u003cp\u003eFollow-up data were obtained for 78 patients (39 in the intervention group and 39 in the control group). Six cases were excluded from the final analysis due to insufficient biofeedback sessions (fewer than 10). Specifically, two participants were unable to initiate therapy due to technical difficulties, while four were transferred to a partial hospitalization setting by the treating physician.\u003c/p\u003e \u003cp\u003eParticipants who completed an insufficient number of biofeedback sessions did not differ from study completers on key baseline characteristics (see Appendix for details). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents baseline demographic and clinical characteristics of participants at enrollment (excluding the four cases classified as inclusion errors).\u003c/p\u003e \u003cp\u003eMost participants received antidepressants (65%) and anxiolytics (58%). Nearly all participants were already receiving medication at the time of enrollment. The median duration of illness was 2.5 years (interquartile range\u0026thinsp;=\u0026thinsp;3.0).\u003c/p\u003e \u003cp\u003eMost participants completed 10 biofeedback sessions (median\u0026thinsp;=\u0026thinsp;10; maximum\u0026thinsp;=\u0026thinsp;17) (see Appendix for details). The number of sessions was not associated with reductions in MADRS (r\u0026thinsp;=\u0026thinsp;0.15, p\u0026thinsp;=\u0026thinsp;0.37) or HARS scores (r\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.20, p\u0026thinsp;=\u0026thinsp;0.24).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of baseline characteristics of the study samples\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBiofeedback\u003c/p\u003e \u003cp\u003egroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStandardized mean difference (d)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, median (Q1\u0026ndash;Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (23\u0026ndash;43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (21\u0026ndash;34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (53.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (41.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIllness duration, median (Q1\u0026ndash;Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5 (1\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.0 (1\u0026ndash;4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReceiving an antidepressant, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (61.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReceiving an anxiolytic, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (58.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (56.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReceiving a mood stabilizer, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (46%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (59%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMADRS, median (Q1\u0026ndash;Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (16 \u0026minus;\u0026thinsp;22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (16\u0026ndash;21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHARS, median (Q1\u0026ndash;Q3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (16\u0026ndash;24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (15\u0026ndash;22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepressive episode (F32), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (18%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecurrent depressive disorder (F33), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (22%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed anxiety and depressive disorder (F41.2), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneralized anxiety disorder (F41.1), n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBipolar disorder, current depressive episode, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCyclothymia, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eEfficacy of biofeedback therapy in reducing depressive symptom severity\u003c/h3\u003e\n\u003cp\u003eBoth groups demonstrated a substantial reduction in depressive symptom severity over the observation period: the median reduction in MADRS scores was 8 points in the biofeedback group and 6 points in the control group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The pre\u0026ndash;post difference in total MADRS scores was statistically significant in both groups (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eChanges in MADRS and HARS scores during treatment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBaseline, median (Q1\u0026ndash;Q3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnd of study, median (Q1\u0026ndash;Q3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep for within-group Δ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMedian reduction, median (Q1\u0026ndash;Q3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStandardized mean difference (within-group effect size), d [95% CI]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eStandard therapy\u0026thinsp;+\u0026thinsp;biofeedback\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMADRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.5 (16\u0026ndash;21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (8\u0026ndash;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (6.25\u0026ndash;12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.81 [0.18;3.44]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHARS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (16\u0026ndash;24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (7\u0026ndash;13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 (9\u0026ndash;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.49 [1.04;3.94]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eStandard therapy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMADRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18 (16\u0026ndash;21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (9\u0026ndash;15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (3\u0026ndash;9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.34 [\u0026minus;\u0026thinsp;0.11;2.79]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHARS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (15\u0026ndash;22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (9\u0026ndash;14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (4\u0026ndash;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.86 [0.53;3.19]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe main study outcomes are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Reductions in MADRS scores did not depend on diagnostic group membership (see Appendix for details) but were associated with baseline symptom severity. The adjusted between-group difference in total MADRS scores at the follow-up assessment was 2.18 points (95% CI [0.17, 4.18]; p\u0026thinsp;=\u0026thinsp;0.034). ITT analyses yielded results comparable to the primary analysis (see Appendix).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eANCOVA results for MADRS and HARS outcomes at the end of the study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdjusted between-group difference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePartial η\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMADRS\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBiofeedback therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[0.17;4.18]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.034\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDiagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e⸻\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAntidepressant prescribed (yes vs no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-2.73; 1.49]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAnxiolytic prescribed (yes vs no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-1.71; 2.88]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMood stabilizer prescribed (yes vs no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-0.43; 4.12]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBaseline MADRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c8\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHARS\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBiofeedback therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.167\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-0.19; 3.43]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDiagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e⸻\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAntidepressant prescribed (yes vs no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-2.86; 1.20]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAnxiolytic prescribed (yes vs no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[0.14; 4.31]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.037\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.065\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMood stabilizer prescribed (yes vs no)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e[-2.99; 1.05]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBaseline HARS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cem\u003eNote.\u003c/em\u003e N\u0026thinsp;=\u0026thinsp;74. MADRS scores at the second assessment point were specified as the dependent variable. All factors listed in the table were entered into a single model (\u0026ldquo;biofeedback therapy,\u0026rdquo; \u0026ldquo;diagnosis,\u0026rdquo; \u0026ldquo;antidepressant prescribed,\u0026rdquo; \u0026ldquo;anxiolytic prescribed,\u0026rdquo; and \u0026ldquo;mood stabilizer prescribed\u0026rdquo; as fixed factors; baseline MADRS or baseline HARS as the covariate). The \u0026ldquo;adjusted between-group difference\u0026rdquo; column reports the difference in the dependent variable (MADRS or HARS score at follow-up) between categories after adjustment for the other model variables. Partial η\u0026sup2; represents the proportion of variance in the dependent variable explained by the predictor after accounting for the remaining predictors. The diagnosis variable had three categories: 1) unipolar depressions (F32 and F33); 2) bipolar spectrum disorders (F31 and F34); 3) anxiety disorders (F41 and F41.2).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong participants who completed the study, treatment response (\u0026ge;\u0026thinsp;50% reduction in total MADRS score) was achieved by 14 (40%) patients in the biofeedback group and by 11 (28%) patients in the comparison group. Accordingly, the NNT for biofeedback therapy was 9. No factors associated with the efficacy of biofeedback therapy in the treatment of depressive symptoms were identified (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociations of additional factors with biofeedback therapy outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFactor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI for B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eΔR\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95% CI for B\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eΔR\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eMADRS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c11\" namest=\"c7\"\u003e \u003cp\u003eHARS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLength of observation in the ward (days)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-0.19; 0.18]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-0.26; 0.07]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-0.1; 0.07]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[0.02; 0.18]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-1.80; 3.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-1.52; 2.86]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eIllness duration (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-0.68; 0.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-0.05; 1.05]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDiagnosis (unipolar depression vs anxiety disorders)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-0.26; 0.34]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-1.5; 2.72]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDiagnosis (bipolar spectrum vs anxiety disorders)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e[-4.56; 1.43]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e[-2.86; 1.75]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c11\" namest=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003e\u003cem\u003eNote.\u003c/em\u003e To test the effect of each factor, a separate linear regression model was built. Only patients from the biofeedback group were included. The MADRS or HARS scores at the end of the study were specified as the dependent variable. In each model, baseline MADRS or baseline HARS was included as an independent predictor. In all cases n\u0026thinsp;=\u0026thinsp;35.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eBoth study groups also demonstrated a significant reduction in anxiety symptom severity: the median reduction in HARS scores was 11 points in the biofeedback group and 8 points in the standard therapy group. However, between-group differences were not statistically significant after controlling for other factors (adjusted between-group difference\u0026thinsp;=\u0026thinsp;1.62; 95% CI [\u0026minus;\u0026thinsp;0.19, 3.43]; p\u0026thinsp;=\u0026thinsp;0.079) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). As expected, reductions in HARS scores were associated with baseline anxiety severity (p\u0026thinsp;=\u0026thinsp;0.001) and the prescription of an anxiolytic (adjusted between-group difference\u0026thinsp;=\u0026thinsp;2.23; 95% CI [0.14, 4.31]; p\u0026thinsp;=\u0026thinsp;0.037). Less improvement in anxiety symptoms within the biofeedback group was observed among older patients (B\u0026thinsp;=\u0026thinsp;0.10; 95% CI [0.02, 0.18]; p\u0026thinsp;=\u0026thinsp;0.02) and among patients with longer illness duration (B\u0026thinsp;=\u0026thinsp;0.49; 95% CI [\u0026minus;\u0026thinsp;0.05, 1.05]; p\u0026thinsp;=\u0026thinsp;0.07) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBiofeedback therapy was well tolerated. Participants reported a total of four adverse events: dizziness (two cases), increased anxiety (one case), and back pain (one case). Several participants reported discomfort when wearing a VR headset concurrently with their prescription eyeglasses.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study evaluated the efficacy of respiratory rate\u0026ndash;based biofeedback therapy in the treatment of depressive symptoms in a transdiagnostic inpatient sample. The addition of biofeedback sessions to standard treatment yielded a small but statistically significant reduction in depressive symptoms. The adjusted between-group difference in MADRS scores was 2.18 points. Among study completers, 40% of participants in the biofeedback group met the response criterion, compared with 28% in the comparison group, corresponding to an NNT of 9. Adding biofeedback therapy to standard treatment did not result in a greater reduction in anxiety symptom severity.\u003c/p\u003e \u003cp\u003eNo predictors of biofeedback efficacy for depressive symptoms were identified among the examined parameters. However, among patients receiving biofeedback therapy, lower anxiety severity at study end was observed in younger patients with shorter illness duration. A large systematic review by Fern\u0026aacute;ndez-Alvarez J. (2022), which combined multiple biofeedback modalities, similarly reported no clinical or sociodemographic factors associated with treatment efficacy. At the same time, younger age and shorter illness duration are often considered potential moderators of pharmacotherapy and psychotherapy outcomes for anxiety disorders (Mills et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Kim et al., 2021; Gonz\u0026aacute;lez-Blanch et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe modest between-group difference in MADRS reduction may reflect a relatively short observation period and a limited number of biofeedback sessions. However, systematic reviews encompassing different biofeedback modalities have not identified an association between the number of sessions and treatment efficacy (Vann-Adibe et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Fern\u0026aacute;ndez-Alvarez et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). No other studies evaluating respiratory rate\u0026ndash;based biofeedback therapy for depressive symptoms were identified. All identified studies that examined biofeedback based on respiratory parameters (respiratory rate or exhaled CO₂ concentration) focused on the treatment of panic disorder (Meuret et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Meuret et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Kim et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Tolin et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Cuyler et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In two of these studies, statistically significant reductions in depressive symptom severity were also reported during treatment compared with patients placed on a waitlist (Meuret et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Kim et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In addition, a substantial literature exists on depression treatment using heart rate variability (HRV) biofeedback. This approach trains patients to modulate heart rhythm through controlled, slow, rhythmic breathing and appears to involve mechanisms that overlap with respiratory rate\u0026ndash;based biofeedback. A systematic review by Vann-Adibe S (2025), encompassing 10 randomized controlled trials, found that HRV therapy demonstrated a moderate effect size in alleviating depressive symptoms.\u003c/p\u003e \u003cp\u003eThe absence of a statistically significant between-group difference in HARS scores is inconsistent with prior studies reporting efficacy of respiratory biofeedback approaches in panic disorder (Meuret et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Meuret et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Kim et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Tolin et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Cuyler et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This discrepancy may be attributable to the inpatient context of treatment, the high frequency of anxiolytic prescriptions, and consequently the marked reduction in anxiety symptoms in both groups in the present study. However, despite controlling for anxiolytic prescriptions, the differences between the groups remained statistically non-significant. Additionally, the distribution of HARS scores at the end of the study showed considerable variability and did not exhibit a clear clustering at the lower end of the scale, indicating that a \"floor effect\" was not evident (see Appendix). In prior studies pharmacotherapy was not restricted, and its effects on symptom reduction were not accounted for (Meuret et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Kim et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Cuyler et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Another potential explanation is that respiratory biofeedback may be specifically effective for panic disorder rather than for other anxiety disorders. It has been proposed that regular respiratory slowing exercises contribute to chemoreceptor desensitization, thereby reducing vulnerability to CO₂ fluctuation\u0026ndash;triggered panic attacks and decreasing sensitivity to the \u0026ldquo;suffocation false alarm\u0026rdquo; mechanism (suffocation false alarm theory) (Meuret et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Meuret et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral mechanisms may account for the efficacy of respiratory rate\u0026ndash;based biofeedback therapy in reducing depressive symptoms. Biofeedback therapy requires the patient to concentrate on breathing, which is similar to mindfulness- and meditation-based practices; focusing attention on the present moment and bodily sensations has been associated with reductions in ruminative thinking (Lehrer \u0026amp; Gevirtz, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Rhythmic breathing at approximately 6 cycles per minute synchronizes respiratory, cardiac, and baroreflex rhythms, thereby increasing vagal afferent signaling to the nucleus tractus solitarius in the brainstem (Sevoz-Couche \u0026amp; Laborde, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Enhanced vagal afferent input is proposed to activate the nucleus tractus solitarius and modulate activity in ventromedial and dorsolateral prefrontal cortex, anterior cingulate cortex, insular cortex, amygdala, hypothalamus, thalamus, and brainstem structures. These regions comprise the central autonomic network, which plays an important role in emotion regulation (Rosso et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Sevoz-Couche \u0026amp; Laborde, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Krieger \u0026amp; Skibicka, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Another potential consequence of nucleus tractus solitarius activation is enhanced descending vagal influence (Sevoz-Couche \u0026amp; Laborde, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), including activation of the cholinergic anti-inflammatory pathway and reduced release of TNF-α, IL-6, and other cytokines by macrophages (Matteoli et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Bonaz et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). However, hypothesized mechanisms remain either speculative or represent an extrapolation from data on HRV biofeedback mechanisms.\u003c/p\u003e \u003cp\u003eOverall, the method was generally well tolerated; however, the frequency of adverse events was not systematically assessed. Other studies have likewise reported an absence of prominent adverse events associated with respiratory biofeedback interventions. In similar studies, the most commonly reported adverse events were dizziness, lightheadedness, and a sensation of air hunger, typically occurring early in treatment (Tolin et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Cuyler et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Vann-Adibe et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). This aligns with the broader literature indicating good tolerability across various biofeedback modalities (Cuyler et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Fern\u0026aacute;ndez-Alvarez et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Vann-Adibe et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study has several substantial limitations. First, the alternating method of group assignment does not constitute full randomization. Nevertheless, the study groups did not differ materially in baseline characteristics. The absence of blinding among patients and investigators may have increased expectancy effects and influenced ratings on administered scales. Participants in the intervention group received more attention from clinical staff due to the regularity of biofeedback sessions. Adverse event monitoring in this study was based on spontaneous reporting. As a result, mild adverse events are likely to have been underreported. Pharmacological treatment was not standardized; changes in medication type and dosage were permitted during treatment. In statistical analyses, control for pharmacotherapy was limited to medication classes, without accounting for specific agents and dosages. This limitation reflected the small sample size and the restricted number of predictors that could be simultaneously included in ANCOVA models. Additional limitations include the brief duration of active treatment and the absence of delayed follow-up assessments to evaluate the durability of effects. Attrition was uneven and related to the operational characteristics of the inpatient unit. A proportion of patients in both groups who showed symptom improvement and good medication tolerability were transferred to a semi-inpatient regimen involving clinic visits twice weekly. This did not prevent the collection of follow-up data for these patients at the second time point; however, it limited the completion of sufficient biofeedback sessions. As a result, attrition was more frequent in the intervention group. ITT results were comparable to the primary analysis (see Appendix). Comparisons between patients who discontinued participation and those who completed follow-up did not reveal substantial baseline differences.\u003c/p\u003e \u003cp\u003eFinally, the sample was highly heterogeneous, as patients with different diagnoses were included, provided that clinically significant depressive symptoms were present. Such pooling was considered acceptable because the presumed mechanisms of efficacy were hypothesized to involve shared pathogenic pathways across different mental disorders. It should also be noted that, in routine clinical practice, diagnoses of affective and anxiety disorders demonstrate low reproducibility and temporal stability (Baca-Garc\u0026iacute;a et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Regier et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Marchi et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Diagnosis did not affect treatment efficacy in the statistical analyses. Diagnostic groups did not differ significantly in the magnitude of depressive symptom reduction, whereas reductions in MADRS scores were clearly associated with baseline symptom severity.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn a prospective pilot study conducted under real-world clinical conditions with a transdiagnostic inpatient sample, the addition of respiratory rate-based biofeedback therapy utilizing the ReviSide hardware-software system was found to be both feasible and implementable. This intervention was associated with a greater improvement in depressive symptoms compared to standard therapy alone. These findings support consideration of respiratory rate\u0026ndash;based biofeedback as a potential adjunctive intervention that may enhance the efficacy of treatment for depressive symptoms among inpatients in routine clinical practice. These preliminary results necessitate further investigation through longer and methodologically more rigorous studies.\u003c/p\u003e "},{"header":"Declarations","content":"\u003ch2\u003e\u003cstrong\u003eAuthor information\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMoscow Research Institute of Psychiatry \u0026ndash; branch of V. Serbsky National Medical Research Centre for Psychiatry and Narcology, 107076, Russia, Moscow, Kropotkinsky Lane, Building 23.\u003c/p\u003e\n\u003cp\u003eOvchinnikov A.V., Sryvkova K.A., Kryukov V.V., Akhapkin R.V., Shport S.V.\u003c/p\u003e\n\u003cp\u003eSamara State Medical University (SamSMU), 443099, Russia, Samara, 89 Chapayevskaya Street\u003c/p\u003e\n\u003cp\u003eKolsanov A.V., Berkovich E. N., Isaev D.S., Berkovich E. N.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eARV, OVA and KVV contributed to the study conception and design. Material preparation, data collection and analysis were performed by OVA, SKA and KVV. The first draft of the manuscript was written by OVA and all authors commented on previous versions of the manuscript. ARV and SSV supervised and revised the manuscript. KAV, CSS, BEN and IDS were responsible for providing the necessary equipment and technical support for the study. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Information:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOvchinnikov A.V. \u0026mdash; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://orcid.org/0000-0002-9605-8527\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eSryvkova K.A. \u0026mdash; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://orcid.org/0009-0000-9902-1749\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eKryukov V.V. \u0026mdash; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://orcid.org/0000-0002-9099-0989\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eKolsanov A.V. \u0026mdash; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://orcid.org/0000-0002-4144-7090\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eChaplygin S.S. \u0026mdash; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://orcid.org/0000-0002-9027-6670\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eIsaev D.S. \u0026mdash; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://orcid.org/0009-0008-6193-0478\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eBerkovich E. N. \u0026mdash; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://orcid.org/0009-0003-3861-485X\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eAkhapkin R.V. \u0026mdash; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://orcid.org/0000-0002-7045-0547\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eShport S.V. \u0026mdash; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://orcid.org/0000-0003-0739-4121\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe authors declare that there is no financial conflict of interest. ReviSide Inc. provided the devices used in the present study during the research period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was performed in line with the principles of the Declaration of Helsinki. This study was approved by the Research Ethics Committee of the Moscow Research Institute of Psychiatry.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eConsent for Participation\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ewas obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe participant has consented to the submission of the research to the journal.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was conducted within the framework of the State Task \u0026ldquo;Development of a clinical\u0026ndash;pathogenetic model and a diagnostic module for anxiety\u0026ndash;depressive spectrum disorders in patients with chronic pathology\u0026rdquo; (registration number: НИОКТР 124020800061-8) and was funded by the Ministry of Health of the Russian Federation.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eARV, OVA and KVV contributed to the study conception and design. Material preparation, data collection and analysis were performed by OVA, SKA and KVV. The first draft of the manuscript was written by OVA and all authors commented on previous versions of the manuscript. ARV and SSV supervised and revised the manuscript. KAV, CSS, BEN and IDS were responsible for providing the necessary equipment and technical support for the study. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n\u003cp\u003eDue to the nature of this research, participants of this study did not agree for their data to be shared publicly, so supporting data is not available.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBaca-Garc\u0026iacute;a, E., Perez-Rodriguez, M. M., Basurte-Villamor, I., et al. (2007). 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Accelerated global burden of depressive disorders during the COVID-19 pandemic from 2019 to 2021. \u003cem\u003eScientific Reports\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e, 9529. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-025-93923-4\u003c/span\u003e\u003cspan address=\"10.1038/s41598-025-93923-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"applied-psychophysiology-and-biofeedback","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"apbi","sideBox":"Learn more about [Applied Psychophysiology and Biofeedback](http://link.springer.com/journal/10484)","snPcode":"10484","submissionUrl":"https://submission.nature.com/new-submission/10484/3","title":"Applied Psychophysiology and Biofeedback","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"biofeedback, depression, virtual reality, intervention","lastPublishedDoi":"10.21203/rs.3.rs-8910823/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8910823/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThere remains a need to identify short-term, safe interventions for depressive symptoms that can be integrated into standard treatment without imposing a substantial burden on patients or clinical staff.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAims\u003c/strong\u003e\u003cbr\u003e\nThis study evaluated the efficacy of respiratory rate–based biofeedback as an adjunctive intervention for depressive symptoms in hospitalized patients with mental disorders.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003cbr\u003e\nThis prospective pilot study included 84 patients diagnosed with depressive or anxiety disorders. In the intervention group, participants received biofeedback therapy once daily for 10 days in addition to standard pharmacotherapy. The comparison group received pharmacotherapy alone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003cbr\u003e\nThe adjusted between-group difference in the total Montgomery–Asberg Depression Rating Scale (MADRS) score after 3 weeks of treatment was 2.18 points (95% CI [0.17;4.18]; p = 0.034). Among study completers, 40% of patients in the biofeedback group met the criterion for treatment response, compared with 28% in the comparison group; the number needed to treat (NNT) was 9. The addition of biofeedback therapy to standard treatment was not associated with a greater reduction in anxiety symptoms. No clinically prominent adverse events were reported.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003cbr\u003e\nAdding biofeedback therapy sessions to standard treatment resulted in a small reduction in depressive symptoms compared with standard therapy alone. These findings support consideration of respiratory rate–based biofeedback as a potential adjunctive intervention that may enhance the effectiveness of treatment for depressive symptoms in inpatient settings within routine clinical practice.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was registered retrospectively (https://doi.org/10.17605/OSF.IO/R38YW; 2026, February 12).\u003c/p\u003e","manuscriptTitle":"A Transdiagnostic pilot study of the efficacy of respiratory rate–based biofeedback in the treatment of depressive symptoms","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-08 14:32:50","doi":"10.21203/rs.3.rs-8910823/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-02-25T20:07:47+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-20T16:31:33+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-20T16:30:43+00:00","index":"","fulltext":""},{"type":"submitted","content":"Applied Psychophysiology and Biofeedback","date":"2026-02-18T15:41:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"applied-psychophysiology-and-biofeedback","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"apbi","sideBox":"Learn more about [Applied Psychophysiology and Biofeedback](http://link.springer.com/journal/10484)","snPcode":"10484","submissionUrl":"https://submission.nature.com/new-submission/10484/3","title":"Applied Psychophysiology and Biofeedback","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"58788d82-d626-4e53-9223-4f89590c8b47","owner":[],"postedDate":"March 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-08T14:32:50+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-08 14:32:50","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8910823","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8910823","identity":"rs-8910823","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}