Alpha and Theta Audiovisual Interventions in a Reflective Chamber Demonstrate Acute Effects on Stress and Burnout

Alpha and Theta Audiovisual Interventions in a Reflective Chamber Demonstrate Acute Effects on Stress and Burnout | 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 Article Alpha and Theta Audiovisual Interventions in a Reflective Chamber Demonstrate Acute Effects on Stress and Burnout Aidan Cone, Sam Zuzick, Tiffany Durinski, Eric Yates, Ninette Simonian, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7842751/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Mar, 2026 Read the published version in npj Digital Medicine → Version 1 posted 9 You are reading this latest preprint version Abstract Escalating stress prevalence, particularly among essential service personnel whose cognitive compromise threatens public welfare, necessitates rapid, accessible, and non-pharmacological interventions. This pilot investigation (n = 74) evaluated audiovisual stimulation delivered through an immersive reflective chamber (MindGym) as an acute stress mitigation strategy for high-burnout-risk populations. Participants underwent randomized assignment to alpha (9-11Hz) or theta (4-7Hz) frequency protocols combining synchronized binaural beats with stroboscopic light during an 11-minute active intervention. Both protocols demonstrated substantial therapeutic efficacy without adverse events. State anxiety reduction (STAI) achieved magnitudes comparable to established pharmacological and psychotherapeutic interventions requiring significantly longer treatment durations. Depression, tension, and negative affect showed similarly robust improvements, while flow states and subjective vitality were significantly enhanced. Moderation analyses revealed protocol-specific responsiveness patterns: alpha stimulation yielded universal stress reduction independent of baseline psychological state, whereas theta selectively enhanced purpose-in-life among participants with elevated mood disturbance, suggesting phenotype-guided optimization potential. These findings establish feasibility and preliminary efficacy for rapid stress management in operationally demanding contexts. Health sciences/Health care Biological sciences/Neuroscience Biological sciences/Psychology Social science/Psychology Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Stress prevalence has reached epidemic proportions globally, with well-documented pathological trajectories (Schneiderman et al., 2005 ) and escalating prevalence (Daly & Macchia, 2023 )—evidenced by 85% of countries reporting increased emotional distress between 2008–2020 (Piao & Managi, 2024) while American stress prevalence escalated from 33% to 49% between 2003–2023 (Fioroni & Foy, 2024 ). The often insidious nature of chronic stress manifests through multifaceted deterioration spanning psychological, cognitive, and physiological domains. Stress-related pathology encompasses heightened suicide risk (O'Connor et al., 2020 ), substance abuse disorders (Sinha, 2008 ), and cognitive deterioration including impaired working memory and attention (Arnsten, 2009 ), response inhibition deficits (Liston et al., 2009 ), and reduced cognitive flexibility (Shields et al., 2016 ). These manifestations reflect underlying neurobiological dysregulation involving HPA-axis hyperactivity and cortisol desensitization (Ulrich-Lai & Herman, 2009 ; de Kloet et al., 2005 ), culminating in hippocampal neurotoxicity, dendritic retraction, and eventual volume loss that precipitates memory deficits and mood disorders (Lupien et al., 2009 ; McEwen et al., 2016 ; Sheline et al., 1996 ; Buckley & Schatzberg, 2005 ; Coryell et al., 2006 ). This mounting psychological burden transcends individual discomfort to encompass systemic societal vulnerabilities, generating cascading risks that threaten civilian welfare through stress-compromised decision-making among essential service personnel operating in life-critical contexts: military personnel experiencing compromised combat readiness and elevated burnout risk (Sekel et al., 2023 ; Hosseini et al., 2023 ), healthcare providers including nurses (Li et al., 2024 ) and physicians (Rotenstein et al., 2018 ), and first responders (Igboanugo et al., 2021 ). This escalating epidemiological trajectory necessitates targeted therapeutic interventions that can mitigate stress-induced pathophysiology while preserving operational capacity, as stress-compromised decision-making among essential service personnel constitutes both a public health crisis and a strategic national security vulnerability requiring evidence-based solutions that enhance cognitive resilience and operational effectiveness while safeguarding civilian welfare. Contemporary treatment modalities demonstrate variable efficacy across diverse intervention frameworks. Pharmacological approaches encompass both conventional anxiolytics and emerging psychedelic-assisted therapies, the latter demonstrating capacity to induce altered states of consciousness that fundamentally reconfigure experiential patterns and promote updating of maladaptive beliefs (Carhart-Harris & Friston, 2019 ). However, these interventions carry substantial operational constraints: conventional medications risk cognitive impairment and increased risk of dementia (Billioti de Gage et al., 2012) and dependency (Baldwin et al., 2013 ), while psychedelic interventions often require extended periods of functional incapacitation, present potential for false insights and strengthening of maladaptive beliefs (Safron et al., 2025 ), and systematically exclude individuals with psychotic predispositions, concurrent antidepressant regimens, or cardiovascular complications (O'Donnell et al., 2019 ). Behavioral interventions, particularly mindfulness-based approaches, demonstrate efficacy for burnout prevention (Labelle et al., 2010 ) yet reveal a therapeutic paradox: populations experiencing the greatest benefit—those with depressive rumination, cognitive reactivity, or chronic pain (Crane & Williams, 2010 ; Hilton et al., 2017 ; Mackenzie et al., 2018 )—simultaneously exhibit the most pronounced adherence difficulties, even among highly motivated practitioners (Brandmeyer & Delorme, 2013 ; Lomas et al., 2015 ). Implementation barriers manifest as substantial dropout rates—19.1% weighted average across 114 studies (Lam et al., 2022 )—particularly problematic for populations experiencing stress-compromised cognitive resources and demanding operational schedules that systematically undermine sustained contemplative practice requirements. These clinical and practical limitations highlight the imperative for rapid-onset, non-pharmacological interventions that circumvent traditional therapeutic constraints while maintaining operational readiness. Non-invasive, non-pharmacological induction of beneficial neural oscillatory patterns represents a promising alternative approach. Electroencephalography (EEG) studies demonstrate that alpha oscillations (9–11 Hz) reflect relaxed wakefulness and cortical inhibition, while theta oscillations (4–7 Hz) facilitate memory consolidation, internal attention, and meditative states (Klimesch, 1999 ; Başar et al., 2001 ). Chronic stress systematically dysregulates these protective neural signatures, manifesting as reduced alpha power and altered theta activity that compromise resting-state networks and cognitive-emotional balance (Golonka et al., 2019 ; Leuchter et al., 2012 ). Additionally, restoration of theta and alpha activity through targeted interventions correlates with enhanced psychological well-being, reduced anxiety, and improved emotional regulation (Cahn & Polich, 2006 ; Goyal et al., 2014 ). Steady-state visual evoked potentials (SSVEPs)—neural entrainment whereby stroboscopic stimulation elicits brain responses across the cortex at matching frequencies (Frohlich et al., 2023 )—through audiovisual stimulation (AVS) presents as a promising route to inducing beneficial brain states that may be more elusive to populations suffering from high-stress and a risk of burnout. Indeed, brief stroboscopic visual and binaural auditory stimulation protocols demonstrate comparable acute mood-regulating benefits to traditional meditation practices while requiring approximately 25% of the temporal investment and exhibiting substantially reduced attrition risk (Johnson et al., 2024 ), suggesting that audiovisual entrainment represents a highly accessible "plug-and-play" modality for rapidly inducing beneficial neural oscillatory patterns and accompanying affective states without the sustained attentional demands that systematically compromise traditional contemplative approaches in high-stress populations. Such entrainment effects stand to be substantially enhanced through immersive, multisensory environments that promote enhanced attentional and emotional engagement (Reggente, 2023 ). MindGym (Lumena, Inc.) exemplifies this technological approach—a reflective chamber featuring LED arrays at cube vertices and mirrored surfaces capable of generating mood-elevating experiences (Simonian et al., 2025 ). Furthermore, individual neurophysiological variability necessitates personalized protocols that accommodate neurodiversity, acknowledging that while some individuals demonstrate optimal therapeutic responsiveness through alpha-frequency entrainment, others exhibit superior outcomes via theta-band stimulation (Brandmeyer et al., 2023 ). The current investigation sought to evaluate the differential therapeutic capacity of alpha versus theta entrainment interventions within MindGym platform among high-stress occupational cohorts exhibiting elevated burnout vulnerability. This study employed a phenotypic approach designed to identify trait-level moderators that determine optimal intervention responsiveness—specifically elucidating which psychological characteristics predict superior therapeutic outcomes from alpha-frequency versus theta-frequency protocols. This methodological framework addresses a fundamental question in neurotechnology applications: whether therapeutic efficacy can be achieved through purely neurobiological frequency targeting, or whether individual phenotypic characteristics represent the critical determinants of intervention responsiveness. Beyond establishing overall acute anxiolytic efficacy within this at-risk population, the investigation examined whether targeted entrainment protocols generated measurable improvements in subjective well-being indices and corresponding reductions in burnout risk trajectories. Methods Participants A power analysis utilizing Cohen's conventional frameworks determined that detecting a medium-to-large effect size (d = 0.7) with 80% statistical power at α = 0.05 required 34 participants per condition. Anticipating behavioral exclusions and technical complications inherent in complex neurotechnology protocols, a total of 74 individuals from the greater Los Angeles area (41 females; age range 20–69 years; µ = 39.69, σ = 13.35) participated in the study, of which 67 were employed either full time or part time. Five participants were excluded from the behavioral analysis due to technical issues (e.g., lack of audio; N = 2), behavioral errors (e.g., facing the wrong direction during the experience; N = 1), or incomplete questionnaire data (N = 2). As a result, a total of 69 participants were included in the behavioral analysis (38 females; age range 20–69 years; µ = 40.09, σ = 13.67) Forty-three participants were excluded from the physiological analysis due to a connection error that prevented data writing, resulting in a total of 31 participants included in the statistical analyses related to physiology (20 females; age range 21–63 years; µ = 40.74, σ = 12.67). Eight participants were excluded from the EEG analysis due to a connection error that prevented data from being saved and technical data storage error, resulting in a total of 66 participants included in the statistical analysis (37 females; age range 20–69 years; µ = 40.33, σ = 13.14). Ten participants were excluded from the EEG/Behavioral Moderation analysis due to the above issues with EEG analysis (N = 8) and incomplete questionnaire data (N = 2), resulting in a total of 64 participants included in the EEG/Behavioral moderation analysis (35 females; age range 21–63 years; µ = 39.69; σ = 13.45). All participants were randomly assigned to one of two groups (Table 1). Participant flow through enrollment, allocation, exclusions and analysis (Fig. 1). Table 1 Participant characteristics for measures by group and analysis type. F = female; M = male. Age is reported in years. Μ and σ represent the mean and standard deviation of age, respectively. Measure Group N Gender (M/F) Age Range µ σ Behavior Alpha 36 16 Male, 20 Female 20–69 39.56 14.33 Theta 33 15 Male, 18 Female 21–63 40.67 13.12 Physiology Alpha 14 1 Male, 13 Female 21–63 40 14.63 Theta 17 10 Male, 7 Female 21–61 41.35 11.24 EEG Alpha 34 15 Male, 19 Female 20–69 38.97 13.80 Theta 32 14 Male, 18 Female 21–63 41.78 12.45 EEG / Behavioral Moderation Alpha 33 15 Male, 18 Female 20–69 39.18 13.95 Theta 31 14 Male; 17 Female 21–63 41.84 12.65 Randomization Subjects were assigned to one of two groups using a MATLAB-based randomization algorithm that maintained gender balance, with recruitment ceasing for each gender category upon reaching the predetermined quota. Participants were randomly assigned to one of two stimuli: Alpha or Theta. Recruitment Participants were recruited through multiple channels—newsletters to previous research participants and targeted social media advertisements (Facebook, Craigslist, Instagram)—within a 50-mile radius of Santa Monica, California (July 22, 2024–March 4, 2025). Compensation comprised $ 30 per hour (cash or Venmo), calculated from check-in to departure and rounded to the nearest quarter-hour increment, with validated parking provided. Eligibility Participants were eligible for the study if they met all of the following criteria: (1) had no hairstyles such as braids, cornrows, dreadlocks, weaves, or extensions that could interfere with scalp sensor contact; (2) were not pregnant or possibly pregnant; (3) had no history of neurological conditions including epilepsy, seizures, or stroke; (4) had an absence of psychiatric disorders such as bipolar disorder or schizophrenia; (5) had no history of migraines; (6) had no photosensitivity or photophobia; (7) were free from eye conditions including cataracts, corneal abrasions, keratitis, or uveitis; (8) had no hearing impairments; (9) had no history of claustrophobia; (10) had no history of vertigo or motion sickness; (11) had no fear of darkness; (12) had normal or corrected-to-normal vision; (13) had sufficient mobility to participate without wheelchairs, walkers, or canes; and (14) were not currently taking medications affecting the central nervous system (including psychostimulants, antidepressants, or antipsychotics) or specific medications known to affect sensory perception (including but not limited to regular doses of NSAIDs, Dilantin, Methotrexate, tetracycline antibiotics, Digoxin, Amiodarone, Atropine, phenothiazine antipsychotics, H2 blockers, Fingolimod, aminoglycoside antibiotics, loop diuretics, and certain chemotherapeutics); (15) had not selected the response option indicating they had "seriously thought of it as a way out" on the suicide-related item from the Purpose in Life (PIL) (Crumbaugh & Maholick 1964 ); and (16) received a score of 14 or higher on the Perceived Stress Scale (PSS) (Cohen et al., 1983 ), indicating moderate to high perceived stress levels. All potential participants completed a comprehensive online screening questionnaire via Google Forms to verify eligibility before study enrollment. This preliminary assessment verified that all participants met the established inclusion and exclusion parameters prior to beginning the research protocol. IRB All recruitment and testing procedures were reviewed and approved by the Advarra Institutional Review Board (Columbia, MD) prior to the start of participant enrollment (Pro00079710). In accordance with ethical guidelines and legal obligations, all participants provided written informed consent via a document hosted on DropboxSign. Participants were given sufficient time to ask questions and receive clarification from the Principal Investigator or study staff. The consent process included the California Experimental Research Bill of Rights, as required by Health and Safety Code Section 24172. The study was conducted in alignment with the principles of the Declaration of Helsinki. In addition, all laboratory staff held current certifications in Good Clinical Practice and Human Research Participant Protection, completed through accredited online training programs. The clinical trial number is not applicable. Given the sensitivity of the study population, research staff were trained to follow a safety protocol in the event of participant suicidality. A licensed physician was on call during all sessions and was to be contacted immediately for clinical assessment if a participant exhibited urgent signs (e.g., suicidal intent or severe distress). If further action was deemed necessary, staff were instructed to call 911 and coordinate emergency transport to one of two pre-identified hospitals within 1.5 miles of the testing site, with staff instructed to remain with the participant until help arrived and report the incident to the Principal Investigator, IRB, and study sponsors in accordance with adverse event procedures. However, no such adverse events occurred. Materials Stimuli Participants underwent one of two audiovisual entrainment protocols—theta (4–7 Hz) or alpha (9–11 Hz)—administered within MindGym, a geometrically configured reflective chamber equipped with LED arrays positioned at structural vertices. The experimental conditions maintained identical temporal sequences, visual progression patterns, and instructional frameworks, differing exclusively in the frequency parameters of both visual stimulation and synchronized binaural audio tracks delivered through noise-canceling headphones. The standardized 23-minute protocol (including pre-recorded instructions) commenced with a 5-minute baseline period during which participants were encouraged to close their eyes and allow their minds to wander, establishing pre-intervention resting state conditions. The subsequent sequence progressed through six alternating eyes-open (utilizing purple, red, green, and blue spectral illumination) and eyes-closed (employing full-spectrum white light) phases (Fig. 2). Throughout the complete audiovisual sequence, synchronized binaural audio tracks reinforced targeted theta (4–7 Hz) or alpha-mu (9–11 Hz) frequency bands, encouraging multisensory entrainment. Phase 1 eyes-open (30 seconds) involved single vertical LEDs illuminated at both posterior vertices relative to the participant's heading direction, expanding from center positions to 25% contiguous LED coverage with undulating intensity modulation synchronized to condition-specific frequency parameters. Phase 1 eyes-closed (30 seconds) featured complete LED activation across all cube vertices utilizing identical stroboscopic luminosity effects. Subsequent eyes-closed phases (Phases 2–5, 30 seconds each) maintained these established full-spectrum white light activation protocols. Phase 2 eyes-open (30 seconds) progressed vertical LED coverage from 25% to 50% while preserving frequency-synchronized undulation patterns. Phase 3 eyes-open (30 seconds) achieved complete vertical LED activation at 100% coverage. Phase 4 eyes-open (30 seconds) sustained 100% vertical activation while introducing horizontal LED arrays positioned posterior and superior to the participant's heading direction. These horizontal arrays exhibited dynamic positional oscillation patterns utilizing 25% of available LEDs, with illuminated segments moving laterally from left to right and returning in continuous cycles synchronized to entrainment frequencies. Phase 5 eyes-open (30 seconds) maintained 100% vertical activation while implementing center-initiated horizontal LED expansion to 50% coverage, eliminating oscillatory movement patterns in favor of static radial expansion. Phase 6 eyes-open (60 seconds) culminated the visual sequence with synchronized vertical-horizontal LED activation at 100% coverage, generating complementary flickering patterns across the extended duration. The final eyes-closed phase (Phase 7; 120 seconds) diverged from preceding white light intervals by implementing progressive luminosity intensification, systematically increasing brightness parameters to create an intensified sensory finale. The protocol concluded with a 5-minute post-intervention rest period (eyes closed, LED arrays deactivated, audio muted). Materials All participants sat on an OMEGA Gaming Chair (SecretLab, Inc.), wore noise-canceling, over-ear Bluetooth QuietComfort 45 headphones (Bose Corporation), and completed the behavioral questionnaires (administered through Google Forms) on a 27-inch 2022 iMac (Apple, Inc.), using a wireless keyboard and mouse, regardless of group. Content delivery system MindGym (Lumena, Inc.), is a 7' isotropic MindGym lined with reflective mylar on its interior walls, while its floor and ceiling are equipped with mirrors. MindGym incorporates WS2815 LEDs, with 121 pixels per edge between the vertices, totaling 1452 pixels across 12 edges. It utilizes a SMD5050 RGB LED chip, offering RGB color with 256 grayscale levels and an output of 990–1080 lumens per meter. The LEDs are operated at less than half of their maximum capacity. Additionally, the system features a color temperature of 5500K. MindGym has been used previously by our group as an anxiolytic experiential technology (Simonian et al., 2025 ). Muse-S All participants wore the Muse-S (InteraXon, Inc.), a consumer-grade, multi-sensory headband featuring four EEG sensors (two on the forehead [AF7, AF8]; two behind the ears [TP9, TP10]; reference at FPz) with a sampling rate of 256 Hz, along with Photoplethysmography (PPG). The Muse-S connected to the “Muse: Meditation & Sleep” app on a 10.9-inch 2022 iPad Air (Apple, Inc.) to initialize satisfactory signal quality via the built-in quality check. Neuropype Neuropype (Intheon, San Diego, CA) was leveraged to receive raw EEG data via a lab-streaming layer (LSL) stream. The pipeline applies minimal preprocessing: timestamp dejittering to create evenly spaced samples across channels, followed by a FIR bandpass filter with edge frequencies at 0.5, 1, 65, and 70 Hz to eliminate typical noise artifacts. Behavioral Questionnaires Behavioral questionnaires were administered during screening, pre and post experiment to gather trait and state information (See Table 2). Table 2 Behavioral questionnaires denoted by measure and timepoint. Measure Time Questionnaire Description Trait Pre Ten-Item Personality Inventory (TIPI) Ten items to measure the Big Five personality dimensions: openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism (Thørrisen & Sadeghi, 2023 ). Dispositional Hope Scale (DHS) Twelve items to measure the feeling of hope on a Likert scale from 1 (definitely false) to 4 (definitely true), divided among three subscales: pathways, agency, and negative filler items that aren't related to hope (Snyder et al., 1991 ). General Self-Efficacy Scale (GSES) Ten items to measure self-efficacy in a professional setting on a Likert scale from 1 (not at all true) to 4 (exactly true). Also measures if self-efficacy is a predictor of burnout and engagement (Ventura et al., 2015 ). Multidimensional Health Locus of Control (MHLC) Eighteen items to assess the extent to which individuals believe they have control over their health, divided among three subscales: internality, powerful others externality, and chance externality (Wallston et al., 1978 ). Connor-Davidson Resilience Scale (CD-RISC-10) Ten items to measure resilience (the ability to adapt from stress, trauma, and adversity), on a Likert scale from 0 (not true at all) to 4 (nearly true all the time), using five subscales: personal competence, acceptance of change and secure relationships, trust/tolerance/strengthening effects of stress, control, and spiritual influences (Connor & Davidson, 2003 ). Dispositional Resilience 'Hardiness' Scale (HARDY) Forty-five items to measure hardiness–a trait associated with resilience and stress tolerance–using three subscales: communication scale, challenge scale, and control scale (Bartone et al., 1989 ). State-Trait Anxiety Inventory (STAI) A measure of state anxiety (temporary/situational) and trait anxiety (enduring propensity) (Spielberger et al., 1983). State Pre & Post Profile of Mood States (POMS) A measure of current mood states across affective dimensions like anger, confusion, depression, fatigue, tension, and vigor (Heuchert & McNair, 2012 ). Anxiety-Emoji-based Scale A single-item measure using five animated emoji images, ranging from very happy to very sad, to represent the respondent's current level of anxiety (Setty et al., 2019 ). Subjective Vitality Scale (SVS) Six items to assess subjective vitality via self-reported positive mental energy and alertness, using a Likert scale from 1 (not at all true) to 7 (very true) (Saricam, 2015). Positive and Negative Affect Schedule (PANAS) Twenty items used to measure the presence and intensity of emotions, using two subscales: positive affect and negative affect (Watson et al., 1988 ). Flow State Scale (FFS) (short version) Nine items to assess flow experience using two subscales: absorption by activity factor and fluency of performance factor (Rheinberg et al., 2003). Outcome Screening & Post Purpose in Life Test (PIL) Twenty items to measure one's sense of perceived purpose or meaning in life. Respondents rate their agreement with statements about their life experience on a scale from 1 (feelings of no purpose) to 5 (the greatest feelings of purpose) (Crumbaugh & Maholick, 1964 ). Perceived Stress Scale (PSS) Ten items to measure how different situations affect feelings of stress, measured on a scale from 0 (never) to 4 (very often) (Cohen et al., 1983 ). Post Emotional Breakthrough Inventory (EBI) Six items to assess acute emotional breakthroughs using a scale from 0 (no, not more than usual) to 10 (yes, entirely or completely) (Roseman et al., 2019 ). Toronto Mindfulness Scale (TMS) Thirteen items to measure state mindfulness (administered post-meditation), differentiating between reflective awareness and ruminative attention, using two subscales: curiosity (gauging interest in one's experiences) and decentering (reflecting the ability to view thoughts and feelings as transient mental events) (Lau et al., 2006 ). Software All first pass analyses were conducted in JASP 0.19.3 (JASP Team, 2024 ). FDR corrections for moderation analyses were conducted in Python 3.12.2 using the statsmodel module version 0.14.0 leveraging the Benjamini-Hochberg method (Statsmodels Development Team, 2024 ). Post-hoc EEG moderation of behavioral measures were conducted in Python 3.12.2 using the statsmodel module version 0.14.0 and figures were made using matplotlib version 3.10.0 and seaborn version 0.13.2 (Statsmodels Development Team, 2024 ; Hunter, 2007 ; Waskom, 2021 ). Procedure Overview Before each session, all participants signed eConsent forms (DropboxSign). They began the session by filling out pre-experience questionnaires, followed by Muse-S Headband setup. Subsequently, each group underwent a 25-minute experiential phase, after which they completed post-experience questionnaires and tasks. The total participation time was roughly 90 minutes. Procedure Upon arrival, participants were seated on an office chair facing a 35.5” x 55” desk and given an overview of the session (pre-questionnaires, equipment setup, 25-minute experience, post-questionnaires). They were informed that their “experience” would involve sitting for 25 minutes in an immersive audiovisual environment. For approximately the first 30 minutes, participants completed a set of questionnaires (TIPI, DHS, GSES, MHLC, CD-RISC-10, HARDY, STAI, GA-VAS, POMS, SVS, PANAS, FFS-short version, and Anxiety Emoji-based scale) on Google Forms. Participants were instructed to silence their phones and remove smartwatches or electronic wristbands that emit light. Using a cotton pad and 91% isopropyl alcohol, the experimenter cleansed the participant’s forehead and areas behind the ears, before outfitting the participant with the Muse-S headband, ensuring a snug fit on the forehead to optimize sensor connectivity. The experimenter used the Muse: Meditation & Sleep app to check signal quality. The app displayed visual indicators for each sensor, with green signifying a good connection and red denoting no connection. The experimenter adjusted the headband as needed until all sensors displayed a green indicator. Furthermore, the filtered data from Neuropype (see Materials) was displayed in a live time-series plot showing all EEG channels. A research assistant visually inspected the plot to confirm that each channel was delivering a stable and discernible signal. If a channel showed a weak or missing signal, the assistant checked for possible obstructions, such as hair or clothing interfering with sensor contact until the signal was visually acceptable. Participants were led intoMindGym, seated centrally, provided headphones, and instructed to sit still, face the wall 90 degrees to their left when facing the entrance, and follow the instructions provided through the headphones during the 25-minute experience without falling asleep. Participants were shown how to exit MindGym if they chose to end the experience early, otherwise, the experimenter would return to assist them once the experience ended. The experience began within 30 seconds of MindGym door closing. After the experience, the Muse-S headband was removed and participants were given the opportunity to use the restroom if needed before completing post-experience behavioral assessments (STAI, GA-VAS, POMS, SVS, PANAS, FFS-short version, EBI, PIL, PSS, TMS, and Anxiety Emoji-based scale). Finally, participants were remunerated, their parking validated, and dismissed. Behavioral Analyses Dependent variables The primary dependent variables in this study were scores on self-report measures administered pre- and post-intervention, including: anxiety measures—State-Trait Anxiety Inventory (STAI-State) and Anxiety Emoji Scale; mood measures—Profile of Mood States (POMS) subscales (Depression, Tension, Anger, Fatigue, Confusion) and total score, and Positive and Negative Affect Schedule (PANAS); flow measures—Flow State Scale (FSS) subscales (Absorption by Activity, Fluency of Performance) and total score; and vitality measure—Subjective Vitality Scale (SVS). Independent variables The primary independent variables were: condition (between-subjects factor), comparing alpha neurostimulation (9–11 Hz) with theta neurostimulation (4–7 Hz); deltas between Pre-intervention and Post-intervention assessments; and Pre-intervention versus Post-intervention assessments. Nonparametric tests Prior to conducting the ANOVAs, the data were assessed for violations of parametric assumptions, including normality using Shapiro-Wilk tests and homogeneity of variance using Levene's test. In cases where these assumptions were substantially violated, equivalent nonparametric alternatives (e.g., Wilcoxon signed-rank tests for within-subject comparisons and Mann-Whitney U tests for between-subject comparisons) were utilized. Moderation To examine whether individual differences moderated the effects of the interventions, linear regression analyses were conducted. In these analyses, changes in variables (post-pre difference scores) and also outcome variables were regressed on condition (alpha vs. theta), potential moderator variables (TIPI, DHS, GSES, MHLC, CD-RISC-10, HARDY, etc.), and their interaction terms. Significant interaction terms would indicate that the effectiveness of the interventions varied as a function of individual differences on the trait measures. EEG baseline measures were also examined as potential moderators of intervention effects. Linear regression analyses were conducted with changes in outcome variables regressed on condition (alpha vs. theta), baseline EEG parameters, and their interaction terms. Significant interactions would indicate that baseline brain activity patterns influenced differential responsiveness to alpha versus theta interventions. Repeated measures ANOVA A series of 2 × 2 mixed-design repeated measures ANOVAs were conducted to evaluate the effects of the interventions on all dependent variables. Each ANOVA included condition (alpha vs. theta) as a between-subjects factor and time (pre-intervention vs. post-intervention) as a within-subjects factor. The main effects of condition and time, as well as their interaction, were examined for each dependent variable. Post hoc analyses were conducted on initial significant results. Effect sizes were reported using generalized eta squared ( η² G ) for the mixed design ANOVAs, and Cohen’s d ( d ) for post hoc analyses. For d , values of 0.2, 0.5, and 0.8 indicated small, medium, and large effects, respectively (Cohen, 1988 ). For η² G , values of 0.02, 0.13, and 0.26 indicated small, medium, and large effects, respectively (Bakeman, 2005 ). Mediation Mediation analyses were conducted to explore potential mechanisms underlying the observed effects. Specifically, we examined whether changes in state anxiety and mood states mediated the relationship between the interventions and changes in outcome variables. These analyses followed the bootstrapping approach recommended by Preacher and Hayes ( 2008 ) using 5,000 bootstrap samples to estimate indirect effects and their 95% confidence intervals. EEG analysis EEG preprocessing began with timestamp dejittering to ensure evenly spaced samples across all channels, followed by the removal of bad channels identified during a 60-second calibration period based on signal variance. A FIR highpass filter (0.5–1 Hz passband, 80 dB stopband attenuation) was then applied to eliminate slow drifts and baseline shifts while preserving low-frequency neural activity. After filtering, artifact removal was performed by excluding data segments that exceed predefined thresholds. A FIR notch filter (55–65 Hz) was applied to suppress 60 Hz line noise common in lab environments, and a FIR lowpass filter (95–100 Hz) was used to attenuate high-frequency muscle and equipment artifacts. Channels previously removed due to poor signal quality are then reinterpolated using spatial information from neighboring electrodes, restoring full topographic coverage for downstream analysis. Multiple Comparison Corrections Multiple comparison corrections were applied according to each analysis's statistical structure and research objectives. Primary hypotheses regarding main effects of time and condition underwent Bonferroni correction (α = 0.05) as confirmatory analyses requiring stringent Type I error control. Moderation analyses, designated as exploratory for future hypothesis generation, were corrected using the Benjamini–Hochberg False Discovery Rate (FDR) (α = 0.05) applied separately within five conceptually distinct families: (1) state moderation—pre-intervention state measures moderating changes in corresponding state variables (15 tests); (2) trait moderation—personality traits moderating state changes (120 tests); (3) state–outcome moderation—pre-intervention states moderating outcome changes (60 tests); (4) trait–outcome moderation—personality traits moderating outcome changes (32 tests); and (5) EEG moderation—baseline brain activity moderating intervention effectiveness on behavioral outcomes (64 tests). Within each family, FDR was applied exclusively to interaction effects, targeting exploratory moderation findings. This family-wise FDR framework increased sensitivity to potential moderator effects while maintaining principled control over false discoveries within each conceptual domain, aligning with established approaches for exploratory analyses aimed at identifying predictors of treatment response (Benjamini & Hochberg, 1995 ; Wang & Ware, 2013 ). Results Psychological Measures Outcome Measures Repeated measures ANOVAs revealed significant main effects of time for the primary outcome measures after correction for multiple comparisons (Tables 3a and 3b), with post hoc analyses conducted for significant findings. Perceived stress (PSS) decreased significantly from pre- to post-intervention ( F(1,67) = 28.458, p < .001, p bonf < 0.001, η² G = 0.051, d = 0.458 [95% CI, 0.270, 0.647]) and purpose in life (PIL) increased significantly ( F(1,67) = 14.496, p < .001, p bonf < 0.001, η² G = 0.071, d = -0.547 [95% CI, -0.849–0.245]). No significant main effects of condition were observed for either PSS ( F(1,67) = 0.073, p = 0.788, p bonf = 0.788, η² G = < 0.001) or PIL ( F(1,67) = 0.263, p = 0.610, p bonf = 0.732, η² G = 0.003). The time × condition interaction for PSS ( F(1,67) = 3.814, p = 0.055, p bonf = 0.110, η² G = 0.007) and PIL ( F(1,67) = 1.474, p = 0.229, p bonf = 0.344, η² G = 0.008) were also non-significant. Table 3 a. Results of repeated measures ANOVA in outcome measures. Time effects pertain to the repeated measures from questionnaire responses during screening and then again following the intervention. Condition effects pertain to alpha vs. theta group comparisons. Measure Category Specific Measure F-statistic p-value Effect Size ( η² G ; Cohen’s d ) Bonferroni Corrected p-value Stress PSS Time Effect 28.458 < 0.001 0.051; 0.458 [95% CI, 0.270–0.647] < 0.001 PSS Condition Effect 0.073 0.788 < 0.001; 0.061 [95% CI, -0.380–0.510] 0.788 PSS Time × Condition 3.814 0.055 0.007 0.110 Purpose PIL Time Effect 14.496 < 0.001 0.071; -0.547 [95% CI, -0.849 – -0.245] < 0.001 PIL Condition Effect 0.263 0.610 0.003; 0.099 [95% CI, -0.287–0.486] 0.732 PIL Time × Condition 1.474 0.229 0.008 0.344 Table 3 b. Results of between group t-tests in post-intervention outcome measures . T-tests of the Emotional Breakthrough Inventory (EBI) and Toronto Mindfulness Scale (TMS). Results show no statistical significance between the two conditions in either measure. Measure t-statistic p-value Cohen’s d Emotional Breakthrough Inventory -1.075 0.286 -0.259 Toronto Mindfulness Scale -0.750 0.456 -0.181 Post hoc analyses revealed significant improvements across both conditions, with reductions in PSS (Alpha: -3.72; Theta: -1.73) and increases in PIL (Alpha: +4.69; Theta: +9.09). Independent samples t-tests on change scores (post minus pre) showed a marginally significant difference between groups for reduction in PSS scores ( t(67) = -1.953, p = 0.055, d = -0.471), with Alpha participants showing numerically greater stress reduction, but no significant difference for purpose in life changes (t(67) = -1.214, p = 0.229, d = -0.293). Timepoint effects Nearly all state measures demonstrated significant main effects of time (Table 4), indicating that both alpha and theta conditions elicited comparably substantial improvements from pre- to post-intervention, with no significant time × condition interactions or between-group differences emerging, thus suggesting equivalent therapeutic impact across stimulation protocols. Table 4 Results of repeated measures ANOVA in state measures. Measure Category Specific Measure F-statistic (1, 67) p-value Effect size ( η² G ; Cohen’s d ) Bonferroni Corrected p-value Anxiety STAI-State 95.862 < 0.001 0.324; 1.365 [95% CI, 1.001–1.730] < 0.001 Anxiety Emoji Scale 20.252 < 0.001 0.115; 0.713 [95% CI, 0.374–1.052] < 0.001 Depression/Mood POMS Depression 74.687 < 0.001 0.258; 1.162 [95% CI, 0.827–1.497] < 0.001 POMS Total Mood Disturbance 58.491 < 0.001 0.261; 1.172 [95% CI, 0.811–1.534] < 0.001 POMS Tension 53.559 < 0.001 0.219; 1.045 [95% CI, 0.708–1.382] < 0.001 POMS Fatigue 45.771 < 0.001 0.185; 0.941 [95% CI, 0.619–1.262] < 0.001 POMS Confusion 36.949 < 0.001 0.157; 0.850 [95% CI, 0.535–1.166] < 0.001 POMS Anger 34.785 < 0.001 0.193; 0.963 [95% CI, 0.598–1.329] < 0.001 POMS Vigor 1.087 0.301 0.005; -0.098 [95% CI, -0.393–0.124) N/A PANAS Negative Affect 33.735 < 0.001 0.034; 0.848 [95% CI, 0.522–1.174] < 0.001 Flow States FSS Total 54.016 < 0.001 0.151; -0.832 [95% CI, -1.100 – -0.564] < 0.001 FSS Fluency of Performance 46.893 < 0.001 0.155; -0.844 [95% CI, -1.130 – -0.558] < 0.001 FSS Absorption by Activity 29.071 < 0.001 0.084; -0.598 [95% CI, -0.842 – -0.354] < 0.001 Positive Affect PANAS Positive Affect 9.505 0.003 0.034; -0.369 [95% CI, -0.616 – -0.122 0.045 Subjective Vitality Scale 17.498 < 0.001 0.059; -0.493 [95% CI, -0.743 – -0.243] < 0.001 Both anxiety measures demonstrated robust pre-to-post intervention improvements: STAI-State (Fig. 3; F(1,67) = 95.862, p bonf < .001, η² G = 0.324) and the Anxiety Emoji Scale ( F(1,67) = 20.252, p bonf < .001, η² G = 0.115). The particularly large effect size for STAI-State anxiety reduction represents one of the most pronounced effects observed across all measured domains, emphasizing the intervention's potent anxiolytic properties. All mood measures also showed significant improvements: POMS Depression ( F(1,67) = 74.687, p bonf < .001, η² G = 0.258), POMS Tension ( F(1,67) = 53.559, p bonf < .001, η² G = 0.219), POMS Anger ( F(1,67) = 34.785, p bonf < .001, η² G = 0.193), POMS Fatigue ( F(1,67) = 45.771, p bonf < .001, η² G = 0.185), POMS Confusion ( F(1,67) = 36.949, p bonf < .001, η² G = 0.157), POMS Total Mood Disturbance(TMD; Fig. 4; F(1,67) = 58.491, p bonf < .001, η² G = 0.261), PANAS Positive Affect ( F(1,67) = 9.505, p bonf = 0.045, η² G = 0.034), and PANAS Negative Affect ( F(1,67) = 33.735, p bonf < .001, η² G = 0.034). Flow measures also demonstrated significant increases: FSS Absorption by Activity ( F(1,67) = 29.071, p bonf < .001, η² G = 0.084), FSS Fluency of Performance ( F(1,67) = 46.893, p < .001, η² G = 0.155), and FSS Total ( F(1,67) = 54.016, p bonf < .001, η² G = 0.151). Similarly, the Subjective Vitality Scale showed a significant increase ( F(1,67) = 17.498, p bonf < .001, η² G = 0.059). The effect sizes indicate that the time effects were particularly strong for POMS Depression ( η² G = 0.258, Cohen’s d = 1.162 [95% CI, 0.827–1.497]), POMS Total Mood Disturbance (TMD) ( η² G = 0.261, Cohen’s d = 1.172 [95% CI, 0.811–1.534]), and FSS Total ( η² G = 0.151, Cohen’s d = -0.832 [95% CI, -1.100 – -0.564]), demonstrating these measures showed large effect size changes from pre to post across both conditions. All time effects remained significant after applying Bonferroni correction for multiple comparisons across all 15 state comparisons (all p bonf < 0.004), indicating robust improvements across anxiety, mood, flow, and vitality domains. Mediation Mediation analyses revealed no significant indirect effects of condition (alpha vs. theta) through any psychological mediating variables to either primary outcome (PIL or PSS). The indirect effects of condition on both outcomes were consistently non-significant across all models, indicating that the equivalent therapeutic benefits observed for both interventions were not mediated through the measured psychological variables. While several psychological variables showed significant direct relationships with outcomes, such as anxiety and mood improvements predicting enhanced purpose in life, and multiple well-being indicators relating to stress reduction, these relationships were independent of intervention condition. These findings suggest that alpha and theta protocols may achieve similar therapeutic outcomes through distinct neurobiological pathways not captured by self-report psychological measures. Moderation Predictors of Change in Outcome Measures We examined whether pre-intervention psychological states moderated the effects of alpha versus theta on outcome measures. Several significant findings emerged as interaction effects between condition and baseline measures, indicating differential moderating patterns between the two intervention types (Table 5). Table 5 State predictors moderation of change in outcome measure Outcome Significant Moderators Key Finding Purpose in Life (PIL) POMS TMD ( p FDR = 0.033) POMS Anger ( p FDR = 0.019) POMS Depression ( p FDR = 0.033) POMS Confusion ( p FDR < 0.001) Several POMS subscales and total scale significantly moderate changes in PIL when interacting with condition Perceived Stress Scale (PSS) Non-significant No significant findings Significant findings included moderation of the relationship between condition and Purpose in Life (PIL) Outcomes by POMS Total Mood Disturbance (Fig. 5), Anger, Depression, and Confusion. Participants with higher baseline mood disturbance showed greater PIL improvements in the theta condition compared to the alpha condition, while those with lower baseline mood disturbance showed similar improvements across both interventions. Analysis of Perceived Stress Scale outcomes identified several pre-intervention predictors including Flow State Scale Total scores, FSS Fluency of Performance subscale ratings, anxiety emoji assessments, and PANAS Negative Affect levels; however, none remained significant following FDR correction. Alpha protocol participants demonstrated greater mean stress reduction (M = -3.72, SD = 3.10) compared to theta participants (M = -1.73, SD = 5.20). No baseline state measures significantly moderated Emotional Breakthrough Inventory or Toronto Mindfulness Scale outcomes across either condition. No trait variables collected during the screening significantly moderated outcome variables. Neurophysiological Results Physiology Changes Over Time To examine changes over time in HR and HRV we employed repeated measures ANOVA which resulted in no significant changes over time comparing the pre-rest and post-rest stages (See Supplementary Materials: Results, Table 1). EEG Changes Over Time To examine EEG changes over time, we employed repeated measures ANOVA which resulted in a significant difference in Alpha power comparing the pre-rest and post-rest stages, but did not survive Bonferroni correction (See Supplementary Materials: Results, Tables 2,4). Physiology Group Differences Post-Intervention All independent sample t-tests for analysis of physiological measures (HR and HRV) revealed no statistical differences between the Alpha and Theta groups after correcting for multiple comparisons (See Supplementary Materials: Results, Table 3). EEG Group Differences Post-Intervention All independent sample t-tests for analysis of EEG measures (including power band ratios) revealed no statistical differences between the Alpha and Theta groups after correcting for multiple comparisons (See Supplementary Materials: Results, Table 3). EEG Band Powers Mediating Behavioral Measures Mediation analyses were conducted to examine whether changes in EEG band powers served as mediating mechanisms linking treatment condition to behavioral outcomes. However, no significant indirect effects were observed across any of the EEG frequency bands examined, indicating that the measured neural oscillatory changes did not significantly mediate the relationship between treatment condition and behavioral improvements. These findings suggest that the psychological benefits observed in both conditions may operate through alternative neurobiological pathways not captured by the specific EEG frequency bands analyzed, or that the mediating effects occur through more complex neural network interactions beyond simple power changes in isolated frequency ranges. EEG Band Powers Moderating Behavioral Measures Several potential moderation effects of baseline EEG measures on treatment outcomes were observed at the uncorrected statistical level; however, none of these effects survived correction for multiple comparisons using the False Discovery Rate (FDR) method (all p FDR >0.05).Additionally, baseline alpha/theta ratios showed a significant negative correlation with intervention-related changes of the same ( r = − .38, p = 0.002), suggesting a regression-to-the-mean effect where the intervention may normalize rather than uniformly alter neurophysiological activity (See Supplemental Materials: Results, Fig. 1). Discussion This pilot investigation examined whether audiovisual stimulation—binaural beats synchronized with stroboscopic light at alpha (9–11 Hz) vs. theta (4–7 Hz) frequencies—delivered through an immersive reflective chamber (MindGym) could meaningfully impact stress, burnout mitigation, and psychological well-being in 74 participants. Both 11-minute protocols, alternating between traditional closed-eye periods and open-eye segments within the chamber's mirrored environment, demonstrated robust feasibility and tolerability while yielding relevant improvements across multiple psychological domains critical to this vulnerable population. The comprehensive assessment battery revealed effect sizes suggesting that even brief, single-session interventions may substantially "move the needle" on traditionally resistant burnout indicators—a finding particularly salient for populations wherein any measurable relief from chronic stress represents meaningful therapeutic progress, potentially obviating traditional controlled comparison requirements when evaluating interventions for acute distress states. Primary Findings and Clinical Significance The magnitude of observed effects across burnout-relevant measures of affect was remarkable, with nearly all psychological domains demonstrating significant improvement. State anxiety (STAI) exhibited the most substantial change (F(1,67) = 95.862, η²p = 0.589, d = 1.365), followed by depression-related mood disturbance (F = 74.687, η²p = 0.527, d = 1.162) and flow experience enhancement (F = 54.016, η²p = 0.446, d = -0.832). The magnitude of observed effects provides important context when considered alongside established interventions. Pharmacological anxiolytics achieve substantial STAI reductions—SSRIs (d = 2.09), benzodiazepines (d = 2.15)—yet require 8–12 weeks of continuous administration with attendant side effect profiles (Bandelow et al., 2015 ). Psychological interventions yield comparable magnitudes (relaxation: d = 1.36; individual CBT: d = 1.30) across multiple therapeutic sessions spanning weeks. Our single 25-minute session achieved STAI reduction of d = 1.365—effectively 11 minutes of active audiovisual stimulation producing anxiolytic effects approaching those of established treatments. This temporal efficiency, achieved without training prerequisites, medication adherence, or contraindications, distinguishes the intervention's clinical utility. However, these data reflect solely acute post-stimulation measurement; longitudinal durability remains empirically unestablished, precluding claims of therapeutic equivalence pending evidence of sustained efficacy. Additionally, improvements in burnout-specific indicators were also particularly noteworthy. The Subjective Vitality Scale showed significant enhancement (F(1,67) = 17.498, p < .001, η²p = 0.207), critical given that vitality mediates the relationship between self-efficacy and burnout resistance (Saricam, 2015); higher vitality predicts sustained work engagement even under stressful conditions. This finding gains additional significance considering burnout may a physiologically "sticky" state that rarely improves without substantial environmental change such as job departure (Chernenko, 2023). Demonstrating measurable improvement in this treatment-resistant population provides evidence exceeding typical control group expectations. The effect sizes consistently surpassed established non-pharmacological interventions. Our PSS reduction (d = 0.458) exceeded brief mindfulness interventions (d = 0.37; Cavanagh et al., 2018), while anxiety improvements substantially exceeded those from 8-week meditation programs (d = 0.38; Goyal et al., 2014 ). Most remarkably, we demonstrated measurable flow state induction—a phenomenon no prior intervention has conclusively achieved through experimental manipulation (Goddard et al., 2021 ), despite flow's recognized importance for performance and well-being. Mechanistic Considerations Surprisingly, we found no evidence supporting neural entrainment as the primary therapeutic mechanism. Neither protocol produced significant changes in target frequency band power from pre- to post-intervention, nor did post-intervention EEG profiles differ between groups despite frequency-specific stimulation (all pFDR > 0.05). The absence of measurable entrainment—potentially attributable to limitations inherent to the consumer-grade EEG system (see Limitations), given previous evidence of entrainment with research-grade systems (e.g., Frohlich et al., 2023 )—suggests therapeutic effects may, at least somewhat, arise through alternative neurophenomenological pathways. For example, the immersive reflective environment itself can induce psychological awe (Simonian et al., 2025 ), a state robustly associated with enhanced meaning-making (Sawada et al., 2024 ), lessened sympathetic activation (Bai et al., 2021 ), and well-being (Monroy et al., 2025 ). Alternatively, synchronized audiovisual stimulation may trigger relaxation responses through subcortical pathways (Thaut, 2003 ) or network-level changes not captured by traditional spectral analysis. The therapeutic equivalence observed across stimulation frequencies in our study further reinforces the possibility that the immersive multisensory environment itself, rather than frequency-specific neural entrainment, may constitute the primary therapeutic mechanism. However, pre vs. post changes in measures like STAI were notably more drastic in the current intervention compared to previous MindGym interventions (Simonian et al., 2025 ), suggesting that these particular stroboscopic interventions were multiplicative of MindGym-only effects. Frequency-Specific Therapeutic Profiles Despite mechanistic uncertainty, some frequency-dependent dissociations emerged that suggest distinct neurotherapeutic profiles. Primary outcome analyses revealed robust improvements across both protocols, yet post-hoc examination unveiled a nuanced dissociation: alpha stimulation yielded numerically superior stress reduction (ΔPSS = -3.72 vs. -1.73, p = 0.055), while theta stimulation engendered more pronounced enhancement of existential purpose (ΔPIL = + 9.09 vs. +4.69). The pattern extended to state measures, where theta consistently yielded numerically superior improvements across POMS Depression, Tension, Anger, and Fatigue subscales, as well as flow state enhancement (+ 6.091 vs + 4.361). While these differences failed to achieve conventional significance thresholds, such incremental gains hold substantial clinical relevance for individuals experiencing burnout and anxiety, where even marginal improvements in mood regulation or positive affect can meaningfully impact functional capacity and quality of life. This divergent pattern extended to phenomenological outcomes, with theta participants demonstrating enhanced emotional breakthrough (28.3 vs. 24.3) and systematically amplified contemplative dimensions: heightened curiosity (15.5 vs. 15.3), decentering (17.2 vs. 15.5), and overall mindful awareness (32.7 vs. 30.8). These theta-specific enhancements align with established associations between frontal midline theta and meditative states, whereas alpha-meditation relationships exhibit greater individual variability (Brandmeyer & Delorme, 2013 ; Reggente et al., 2025 ). Individual Differences and Precision Medicine The observed therapeutic efficacy of the interventions with equivalence between alpha and theta protocols could reflect response distributions wherein strong and weak responders populate each condition in approximately equal proportions. Such a potential motivates a reconceptualization of population-level, “one-size-fits-all” interventions toward personalized paradigms—replacing random assignment with algorithmic stratification based on individual phenotypic markers encompassing both who participants fundamentally are (trait characteristics) and how they present at intervention onset (state variables). To elucidate potential biomarkers for such personalized protocol selection, we conducted comprehensive moderation analyses examining trait and state (including EEG measures) moderators of therapeutic response. Despite theoretical expectations that dispositional characteristics—particularly trait mindfulness, openness to experience, or beliefs around the role of personal agency in health outcomes—might moderate receptivity to passive audiovisual stimulation, no trait variables demonstrated significant moderating effects. Similarly, pre-intervention neurophysiological profiles (EEG spectral power across frequency bands) failed to predict differential outcomes between protocols after correcting for multiple comparisons. However, state-dependent psychological variables revealed striking protocol-specific moderation patterns exclusively for existential outcomes. The relationship between intervention condition and Purpose in Life enhancement was significantly moderated by multiple baseline mood disturbance indicators—POMS Total Mood Disturbance (pFDR = 0.033), Anger (pFDR = 0.019), Depression (pFDR = 0.033), and Confusion (pFDR < 0.001). Participants presenting with elevated baseline psychological dysfunction demonstrated preferential PIL enhancement under theta stimulation, while those with lower baseline disturbance achieved comparable improvements across both protocols. Conversely, stress reduction outcomes exhibited no significant moderation despite alpha's numerically superior mean reduction (M = -3.72, SD = 3.10) compared to theta (M = -1.73, SD = 5.20), with initially promising predictors (flow states, anxiety assessments, negative affect) failing multiple comparison correction. Implications for High-Stress Operational Populations These findings hold particular relevance for operational contexts (e.g., military aviators managing G-forces and split-second decisions, special operations personnel sustaining hypervigilance in denied environments, first responders navigating cumulative trauma exposure) where traditional pharmacological stress interventions may induce states of compromised sobriety that prove incompatible with mission demands. Unlike meditation requiring sustained disciplined practice or psychotherapy spanning months, audiovisual stimulation offers immediate stress relief without extensive training. The technology's "plug-and-play" nature directly addresses Brandmeyer and Delorme's (2013) observation that Western populations struggle maintaining contemplative practices due to factors "ranging from lack of time to general laziness." For military personnel experiencing allostatic load from prolonged deployment cycles, cultural barriers to help-seeking, and limited recovery opportunities, an 11-minute intervention producing effects comparable to weeks of traditional treatment represents a transformative possibility. The absence of stigma associated with technology-based interventions may facilitate adoption where traditional mental health services encounter resistance rooted in military culture's emphasis on stoicism and self-reliance. Limitations Technical constraints inherent to the consumer-grade Muse-S EEG and PPG system—including substantial data loss, limited spatiotemporal resolution (7 sensors, 256 Hz), and potential electromagnetic interference from the reflective chamber—fundamentally restricted neurophysiological assessment capacity. The current study acknowledged this limitation at the study design stage, weighing it against the increased ecological validity of leveraging devices that ship with MindGym. This methodological trade-off was deliberated during study conceptualization, ultimately prioritizing ecological validity by testing the biosensor technology commercially integrated with MindGym, given the platform's existing neurofeedback capabilities and anticipated future implementations wherein experience progression would be algorithmically modulated contingent upon successful entrainment verification using these same consumer-grade sensors. Regrettably, this constraint prevented us from addressing a critical gap in audiovisual stimulation research, where behavioral improvements are widely assumed to reflect neural entrainment despite scarce empirical verification of such mechanisms (Johnson et al., 2024 ). The absence of control conditions precludes both mechanistic attribution and assessment of spontaneous fluctuations in outcome measures. While psychological states like burnout typically demonstrate temporal stability absent intervention (Maslach & Leiter, 2016 ), distinguishing specific therapeutic mechanisms from expectancy effects, environmental novelty, or simple rest remains impossible. This interpretive constraint extends to our null between-protocol differentiation, which admits dual interpretations: either shared therapeutic mechanisms transcending frequency-specific parameters, or heterogeneous individual responses masked by group-level aggregation.Our protocol design also introduces similar confounds—primary outcomes spanning screening to post-intervention cannot exclude intervening life events, though immediate pre-state moderation analyses partially mitigate this concern by demonstrating that proximal psychological states predicted differential responsiveness. The single-session design eliminates durability assessment, while our stressed but non-clinical sample constrains generalizability. Nevertheless, robust moderation patterns transcend these methodological constraints. The finding that baseline psychological profiles predicted protocol-specific responses—independent of trait characteristics, neurophysiology, or autonomic indices—suggests phenotypic markers for intervention optimization beyond simple placebo effects. While requiring controlled replication, these differential patterns advance precision frameworks wherein momentary psychological states, rather than stable individual differences, guide neurostimulation selection. Future Directions This successful pilot demonstrated feasibility, tolerability, and preliminary efficacy of audiovisual stimulation in a burnout-risk population without adverse events, establishing foundation for expanded investigation across multiple critical domains. Longitudinal efficacy studies should prioritize durability assessment through controlled trials incorporating follow-up measurements at standardized intervals (1-week, 1-month, 3-month, 6-month) to determine whether acute effects persist or require maintenance dosing. An 8-week protocol analogous to Minduflness Based Stress Reduction would enable direct comparison with established interventions while incorporating waitlist controls to quantify spontaneous fluctuations and active controls (random multi-frequency stimulation) to isolate frequency-specific effects from expectancy and environmental factors inherent to MindGym, including awe-induction. Precision medicine optimization emerges as particularly promising given our moderation findings. Machine learning algorithms incorporating baseline psychological profiles, particularly mood disturbance indicators that predicted differential responsiveness, could enable algorithmic protocol assignment surpassing random allocation efficacy. Variables approaching but not achieving significance after correction warrant inclusion in multivariate prediction models, potentially revealing combinatorial phenotypes optimizing individual treatment matching. Mechanistic clarification requires research-grade neurophysiological assessment. Higher-density EEG arrays (e.g., 64-channels) with enhanced spatiotemporal resolution could detect entrainment signatures potentially mediating therapeutic effects would elucidate network-level changes underlying psychological improvements. Such investigations should examine whether behavioral benefits necessitate classical entrainment or emerge through alternative neuromodulatory pathways. Clinical translation demands systematic investigation across diagnostic populations (e.g., anxiety disorders, major depressive disorder, post traumatic stress disorder), dose-response characterization (session frequency, duration, total exposure), and comparative effectiveness trials against pharmacological and psychotherapeutic standards. Implementation research examining scalability through virtual reality platforms, mobile applications, and home-use devices could democratize access while maintaining therapeutic fidelity—particularly crucial for operational populations requiring immediate, stigma-free interventions. Conclusion This pilot investigation demonstrated that single-session audiovisual stroboscopic stimulation within an immersive reflective chamber (MindGym) produced substantial anxiolytic and mood-enhancing effects comparable to pharmacological interventions requiring weeks of administration, without adverse events or training prerequisites. Despite absent neural entrainment signatures, both alpha and theta protocols yielded robust psychological improvements, though through potentially distinct pathways: alpha demonstrating universal stress reduction independent of baseline psychological state, while theta selectively enhanced existential purpose among individuals with elevated mood disturbance. These differential response patterns, wherein momentary psychological profiles rather than trait characteristics or neurophysiological markers predicted protocol-specific outcomes, advance precision neurostimulation frameworks beyond population-level applications toward algorithmic phenotype-guided selection. For operational populations experiencing chronic stress exposure and barriers to traditional interventions—particularly military personnel confronting burnout, hypervigilance, and cultural stigma around help-seeking—this accessible, rapidly-acting technology offers transformative potential for acute stress management. The convergence of substantial effect magnitudes, differential moderation patterns suggesting mechanistic specificity beyond placebo, and implementation feasibility positions audiovisual stimulation as a promising complement to existing therapeutics, warranting controlled longitudinal investigations to establish durability, optimize personalization algorithms, and elucidate whether therapeutic benefits necessitate classical entrainment or emerge through alternative neuromodulatory pathways transcending frequency-specific oscillatory coupling. Funding Declarations This investigation received financial support through a Small Business Innovation Research (SBIR) award from the Department of Defense: Air Force, granted to Lumena, Inc. (Denver, CO) in collaboration with the Institute for Advanced Consciousness Studies (IACS; 501(c)(3) nonprofit organization) serving as the associated research institution, with N.R. designated as principal investigator. Declarations Conflicts of Interests Financial support was provided via Research Services Agreement between IACS and Lumena, Inc., structured without outcome-dependent provisions or performance-based compensation mechanisms. Lumena, Inc. exercised no influence over experimental design or data analysis protocols, with their contribution limited to providing MindGym content libraries, technological infrastructure (hardware and software systems), and reflective chamber control programs developed according to experiential sequence specifications provided by N.R. to Lumena's engineering team. Additionally, Lumena recorded audio instructions and experiential content as directed by the research team. The funding arrangement exclusively supported research operational expenses while maintaining complete investigative independence, with Lumena's role confined to providing requisite technological tools and implementation resources without compromising scientific integrity or methodological autonomy. E.Y. was employed by Lumena, Inc. during data collection and processing but left prior to manuscript preparation, subsequently contributing to manuscript writing through an independent affiliation with IACS. E.Y. owns shares in Lumena, Inc. but had no role in study design or statistical analysis, providing only processed data through Lumena's established pipeline. Competing Interests Financial support was provided via Research Services Agreement between IACS and Lumena, Inc., structured without outcome-dependent provisions or performance-based compensation mechanisms. Lumena, Inc. exercised no influence over experimental design or data analysis protocols, with their contribution limited to providing MindGym content libraries, technological infrastructure (hardware and software systems), and reflective chamber control programs developed according to experiential sequence specifications provided by N.R. to Lumena's engineering team. Additionally, Lumena recorded audio instructions and experiential content as directed by the research team. The funding arrangement exclusively supported research operational expenses while maintaining complete investigative independence, with Lumena's role confined to providing requisite technological tools and implementation resources without compromising scientific integrity or methodological autonomy. E.Y. was employed by Lumena, Inc. during data collection and processing but left prior to manuscript preparation, subsequently contributing to manuscript writing through an independent affiliation with IACS. E.Y. owns shares in Lumena, Inc. but had no role in study design or statistical analysis, providing only processed data through Lumena's established pipeline. Author Contribution Study conceptualization and design: N.R. Study implementation and logistics: N.R., N.S., E.Y. Data collection: A.C., S.Z., T.D., N.S. Data analysis: A.C., S.Z., N.R. All authors contributed to manuscript writing and approved the final version for submission. Acknowledgement We extend gratitude to all research participants who enabled this investigation, and acknowledge the invaluable contributions of the Lumena, Inc. team, including Scott McCormick for developing the audiovisual programming architecture, Pamela Glick for managerial coordination, and Brandon Murphy and Stetson Jenkins for their collaborative support. Data Availability The behavioral questionnaire data, EEG data, and physiological data (heart rate and heart rate variability) that support the findings of this study are openly available on the Open Science Framework (OSF) at https://osf.io/3sjeu.Analysis code used to process the behavioral data and generate figures is available at https://github.com/akcone2003/P006_Code.The audiovisual stimulation protocols (alpha and theta conditions) utilized proprietary MindGym hardware and software systems developed by Lumena, Inc. While the general parameters of these protocols are described in detail in the Methods section, the specific control programs and LED sequences are proprietary to Lumena, Inc. and are not publicly available. Researchers interested in replicating these protocols using the MindGym platform should contact Lumena, Inc. directly.Raw consent forms and participant identification information are not publicly available to protect participant privacy and confidentiality in accordance with IRB approval (Advarra IRB Pro00079710) and HIPAA regulations. De-identified data are available as described above.Requests for additional information or materials should be directed to the corresponding author. References Arnsten, A. F. T. (2009). Stress signalling pathways that impair prefrontal cortex structure and function. Nature Reviews Neuroscience, 10(6), 410–422. https://doi.org/10.1038/nrn2648 Bai, Y., Ocampo, J., Jin, G., Chen, S., Benet-Martinez, V., Monroy, M., Anderson, C., & Keltner, D. (2021). Awe, daily stress, and elevated life satisfaction. Journal of Personality and Social Psychology , 120 (4), 837–860. https://doi.org/10.1037/pspa0000267 Bakeman, R. (2005). 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Lumena, Inc. exercised no influence over experimental design or data analysis protocols, with their contribution limited to providing MindGym content libraries, technological infrastructure (hardware and software systems), and reflective chamber control programs developed according to experiential sequence specifications provided by N.R. to Lumena's engineering team. Additionally, Lumena recorded audio instructions and experiential content as directed by the research team. The funding arrangement exclusively supported research operational expenses while maintaining complete investigative independence, with Lumena's role confined to providing requisite technological tools and implementation resources without compromising scientific integrity or methodological autonomy. E.Y. was employed by Lumena, Inc. during data collection and processing but left prior to manuscript preparation, subsequently contributing to manuscript writing through an independent affiliation with IACS. E.Y. owns shares in Lumena, Inc. but had no role in study design or statistical analysis, providing only processed data through Lumena's established pipeline. Supplementary Files P006M001ConeetalOct2025SupplementalMaterials.docx Cite Share Download PDF Status: Published Journal Publication published 28 Mar, 2026 Read the published version in npj Digital Medicine → Version 1 posted Editorial decision: Revision requested 03 Dec, 2025 Reviews received at journal 02 Dec, 2025 Reviewers agreed at journal 11 Nov, 2025 Reviews received at journal 11 Nov, 2025 Reviewers agreed at journal 27 Oct, 2025 Reviewers invited by journal 16 Oct, 2025 Editor assigned by journal 16 Oct, 2025 Submission checks completed at journal 16 Oct, 2025 First submitted to journal 12 Oct, 2025 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. 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12:06:55","extension":"png","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":27952,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-7842751/v1/5e0286933e92307781669b60.png"},{"id":94761117,"identity":"466ea469-8163-4450-b123-037499dd58ad","added_by":"auto","created_at":"2025-10-30 12:06:55","extension":"xml","order_by":14,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":235170,"visible":true,"origin":"","legend":"","description":"","filename":"9049e775e78b45b0a3b2dd43907b381f1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7842751/v1/5ed11d23eb5ab89e846b0c12.xml"},{"id":94761119,"identity":"c3f22ca1-23ec-4ede-9dfd-68e587766b93","added_by":"auto","created_at":"2025-10-30 12:06:55","extension":"html","order_by":15,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":254778,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7842751/v1/5ea10e0534ee99a961cd7eeb.html"},{"id":94761097,"identity":"369bc70f-6c34-4f90-a429-f432a929081d","added_by":"auto","created_at":"2025-10-30 12:06:54","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":274158,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCONSORT-style flow diagram\u003c/strong\u003e. CONSORT-style flow diagram depicting movement of participants and data through the experiment.\u003c/p\u003e","description":"","filename":"image1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7842751/v1/65ef520e31dd1c68e55690f5.jpg"},{"id":94761101,"identity":"d22af392-e79f-4c1a-8dc1-24f41c8428e1","added_by":"auto","created_at":"2025-10-30 12:06:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":998448,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA. Procedure Overview.\u003c/strong\u003e Total participation time was roughly 105 minutes. \u003cstrong\u003eB. Sequential Progression of Audiovisual Entrainment Protocol Within MindGym Chamber. \u003c/strong\u003eThe 25-minute protocol comprises three sequential phases with systematic audiovisual\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7842751/v1/150482e1ae96d45cc6737642.png"},{"id":94761096,"identity":"dddea540-9239-43cd-aec5-38b013a94f0b","added_by":"auto","created_at":"2025-10-30 12:06:54","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":33970,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMean STAI State Anxiety scores (±SE) for alpha and theta conditions at pre- and post-intervention time points. \u003c/strong\u003eBoth conditions showed substantial reductions in state anxiety from pre- to post-intervention, with no significant differences between conditions. Lower scores represent less reported anxiety.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7842751/v1/ff95ccb4588e5bb76188def7.png"},{"id":94761099,"identity":"26fd8fce-222b-4802-8760-ab6af7404363","added_by":"auto","created_at":"2025-10-30 12:06:54","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":35929,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMean POMS Total Mood Disturbance (TMD) scores before and after 25-minute audiovisual stimulation for alpha and theta conditions\u003c/strong\u003e. Both conditions demonstrated substantial TMD reductions from approximately 17 to near zero. Error bars represent standard error of the mean. Lower scores indicate improved mood states.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7842751/v1/c80e080b61666c212e2666e9.png"},{"id":94761105,"identity":"f207b776-3533-4189-b7f5-f923be00a4ee","added_by":"auto","created_at":"2025-10-30 12:06:54","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":101494,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eModeration of Purpose in Life outcomes by pre-intervention mood disturbance across intervention conditions.\u003c/strong\u003e Scatterplot shows the relationship between baseline POMS Total Mood Disturbance scores (x-axis) and change in Purpose in Life scores from pre- to post-intervention (y-axis) for Alpha (green) and Theta (gray) conditions. Lines represent fitted regression slopes with 95% confidence intervals (shaded areas). A significant interaction effect was observed (\u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003eFDR\u003c/em\u003e\u003c/sub\u003e = 0.033), indicating that pre-intervention mood disturbance differentially predicted PIL improvements between conditions.\u0026nbsp; PIL Delta = post-intervention PIL score minus pre-intervention PIL score; positive values indicate improvement in sense of purpose.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-7842751/v1/ac0cfe3f7367d56350e5679b.png"},{"id":105754844,"identity":"2f3f546b-5e3f-4e83-8701-c0a18e80684f","added_by":"auto","created_at":"2026-03-30 16:22:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3293262,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7842751/v1/7650d0e6-b9f1-4d5a-8f7b-dd97c5fbb4b3.pdf"},{"id":94761107,"identity":"bc8084eb-c3e4-41ca-9e2c-4c74ecca0a14","added_by":"auto","created_at":"2025-10-30 12:06:54","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":66460,"visible":true,"origin":"","legend":"","description":"","filename":"P006M001ConeetalOct2025SupplementalMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-7842751/v1/8977b44542a4e0517eec8782.docx"}],"financialInterests":"Competing interest reported. Financial support was provided via Research Services Agreement between IACS and Lumena, Inc., structured without outcome-dependent provisions or performance-based compensation mechanisms. Lumena, Inc. exercised no influence over experimental design or data analysis protocols, with their contribution limited to providing MindGym content libraries, technological infrastructure (hardware and software systems), and reflective chamber control programs developed according to experiential sequence specifications provided by N.R. to Lumena's engineering team. Additionally, Lumena recorded audio instructions and experiential content as directed by the research team. The funding arrangement exclusively supported research operational expenses while maintaining complete investigative independence, with Lumena's role confined to providing requisite technological tools and implementation resources without compromising scientific integrity or methodological autonomy. E.Y. was employed by Lumena, Inc. during data collection and processing but left prior to manuscript preparation, subsequently contributing to manuscript writing through an independent affiliation with IACS. E.Y. owns shares in Lumena, Inc. but had no role in study design or statistical analysis, providing only processed data through Lumena's established pipeline.","formattedTitle":"Alpha and Theta Audiovisual Interventions in a Reflective Chamber Demonstrate Acute Effects on Stress and Burnout","fulltext":[{"header":"Introduction","content":"\u003cp\u003eStress prevalence has reached epidemic proportions globally, with well-documented pathological trajectories (Schneiderman et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) and escalating prevalence (Daly \u0026amp; Macchia, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u0026mdash;evidenced by 85% of countries reporting increased emotional distress between 2008\u0026ndash;2020 (Piao \u0026amp; Managi, 2024) while American stress prevalence escalated from 33% to 49% between 2003\u0026ndash;2023 (Fioroni \u0026amp; Foy, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The often insidious nature of chronic stress manifests through multifaceted deterioration spanning psychological, cognitive, and physiological domains. Stress-related pathology encompasses heightened suicide risk (O'Connor et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), substance abuse disorders (Sinha, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), and cognitive deterioration including impaired working memory and attention (Arnsten, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), response inhibition deficits (Liston et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), and reduced cognitive flexibility (Shields et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). These manifestations reflect underlying neurobiological dysregulation involving HPA-axis hyperactivity and cortisol desensitization (Ulrich-Lai \u0026amp; Herman, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; de Kloet et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), culminating in hippocampal neurotoxicity, dendritic retraction, and eventual volume loss that precipitates memory deficits and mood disorders (Lupien et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; McEwen et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Sheline et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Buckley \u0026amp; Schatzberg, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Coryell et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis mounting psychological burden transcends individual discomfort to encompass systemic societal vulnerabilities, generating cascading risks that threaten civilian welfare through stress-compromised decision-making among essential service personnel operating in life-critical contexts: military personnel experiencing compromised combat readiness and elevated burnout risk (Sekel et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hosseini et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), healthcare providers including nurses (Li et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and physicians (Rotenstein et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), and first responders (Igboanugo et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis escalating epidemiological trajectory necessitates targeted therapeutic interventions that can mitigate stress-induced pathophysiology while preserving operational capacity, as stress-compromised decision-making among essential service personnel constitutes both a public health crisis and a strategic national security vulnerability requiring evidence-based solutions that enhance cognitive resilience and operational effectiveness while safeguarding civilian welfare. Contemporary treatment modalities demonstrate variable efficacy across diverse intervention frameworks. Pharmacological approaches encompass both conventional anxiolytics and emerging psychedelic-assisted therapies, the latter demonstrating capacity to induce altered states of consciousness that fundamentally reconfigure experiential patterns and promote updating of maladaptive beliefs (Carhart-Harris \u0026amp; Friston, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, these interventions carry substantial operational constraints: conventional medications risk cognitive impairment and increased risk of dementia (Billioti de Gage et al., 2012) and dependency (Baldwin et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), while psychedelic interventions often require extended periods of functional incapacitation, present potential for false insights and strengthening of maladaptive beliefs (Safron et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), and systematically exclude individuals with psychotic predispositions, concurrent antidepressant regimens, or cardiovascular complications (O'Donnell et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Behavioral interventions, particularly mindfulness-based approaches, demonstrate efficacy for burnout prevention (Labelle et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) yet reveal a therapeutic paradox: populations experiencing the greatest benefit\u0026mdash;those with depressive rumination, cognitive reactivity, or chronic pain (Crane \u0026amp; Williams, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Hilton et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Mackenzie et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u0026mdash;simultaneously exhibit the most pronounced adherence difficulties, even among highly motivated practitioners (Brandmeyer \u0026amp; Delorme, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Lomas et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Implementation barriers manifest as substantial dropout rates\u0026mdash;19.1% weighted average across 114 studies (Lam et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u0026mdash;particularly problematic for populations experiencing stress-compromised cognitive resources and demanding operational schedules that systematically undermine sustained contemplative practice requirements.\u003c/p\u003e\u003cp\u003eThese clinical and practical limitations highlight the imperative for rapid-onset, non-pharmacological interventions that circumvent traditional therapeutic constraints while maintaining operational readiness. Non-invasive, non-pharmacological induction of beneficial neural oscillatory patterns represents a promising alternative approach. Electroencephalography (EEG) studies demonstrate that alpha oscillations (9\u0026ndash;11 Hz) reflect relaxed wakefulness and cortical inhibition, while theta oscillations (4\u0026ndash;7 Hz) facilitate memory consolidation, internal attention, and meditative states (Klimesch, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Başar et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Chronic stress systematically dysregulates these protective neural signatures, manifesting as reduced alpha power and altered theta activity that compromise resting-state networks and cognitive-emotional balance (Golonka et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Leuchter et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Additionally, restoration of theta and alpha activity through targeted interventions correlates with enhanced psychological well-being, reduced anxiety, and improved emotional regulation (Cahn \u0026amp; Polich, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Goyal et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSteady-state visual evoked potentials (SSVEPs)\u0026mdash;neural entrainment whereby stroboscopic stimulation elicits brain responses across the cortex at matching frequencies (Frohlich et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u0026mdash;through audiovisual stimulation (AVS) presents as a promising route to inducing beneficial brain states that may be more elusive to populations suffering from high-stress and a risk of burnout. Indeed, brief stroboscopic visual and binaural auditory stimulation protocols demonstrate comparable acute mood-regulating benefits to traditional meditation practices while requiring approximately 25% of the temporal investment and exhibiting substantially reduced attrition risk (Johnson et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), suggesting that audiovisual entrainment represents a highly accessible \"plug-and-play\" modality for rapidly inducing beneficial neural oscillatory patterns and accompanying affective states without the sustained attentional demands that systematically compromise traditional contemplative approaches in high-stress populations.\u003c/p\u003e\u003cp\u003eSuch entrainment effects stand to be substantially enhanced through immersive, multisensory environments that promote enhanced attentional and emotional engagement (Reggente, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). MindGym (Lumena, Inc.) exemplifies this technological approach\u0026mdash;a reflective chamber featuring LED arrays at cube vertices and mirrored surfaces capable of generating mood-elevating experiences (Simonian et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Furthermore, individual neurophysiological variability necessitates personalized protocols that accommodate neurodiversity, acknowledging that while some individuals demonstrate optimal therapeutic responsiveness through alpha-frequency entrainment, others exhibit superior outcomes via theta-band stimulation (Brandmeyer et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe current investigation sought to evaluate the differential therapeutic capacity of alpha versus theta entrainment interventions within MindGym platform among high-stress occupational cohorts exhibiting elevated burnout vulnerability. This study employed a phenotypic approach designed to identify trait-level moderators that determine optimal intervention responsiveness\u0026mdash;specifically elucidating which psychological characteristics predict superior therapeutic outcomes from alpha-frequency versus theta-frequency protocols. This methodological framework addresses a fundamental question in neurotechnology applications: whether therapeutic efficacy can be achieved through purely neurobiological frequency targeting, or whether individual phenotypic characteristics represent the critical determinants of intervention responsiveness. Beyond establishing overall acute anxiolytic efficacy within this at-risk population, the investigation examined whether targeted entrainment protocols generated measurable improvements in subjective well-being indices and corresponding reductions in burnout risk trajectories.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eParticipants\u003c/h2\u003e\u003cp\u003eA power analysis utilizing Cohen's conventional frameworks determined that detecting a medium-to-large effect size (d\u0026thinsp;=\u0026thinsp;0.7) with 80% statistical power at α\u0026thinsp;=\u0026thinsp;0.05 required 34 participants per condition. Anticipating behavioral exclusions and technical complications inherent in complex neurotechnology protocols, a total of 74 individuals from the greater Los Angeles area (41 females; age range 20\u0026ndash;69 years; \u0026micro;\u0026thinsp;=\u0026thinsp;39.69, σ\u0026thinsp;=\u0026thinsp;13.35) participated in the study, of which 67 were employed either full time or part time.\u003c/p\u003e\u003cp\u003eFive participants were excluded from the behavioral analysis due to technical issues (e.g., lack of audio; N\u0026thinsp;=\u0026thinsp;2), behavioral errors (e.g., facing the wrong direction during the experience; N\u0026thinsp;=\u0026thinsp;1), or incomplete questionnaire data (N\u0026thinsp;=\u0026thinsp;2). As a result, a total of 69 participants were included in the behavioral analysis (38 females; age range 20\u0026ndash;69 years; \u0026micro;\u0026thinsp;=\u0026thinsp;40.09, σ\u0026thinsp;=\u0026thinsp;13.67)\u003c/p\u003e\u003cp\u003eForty-three participants were excluded from the physiological analysis due to a connection error that prevented data writing, resulting in a total of 31 participants included in the statistical analyses related to physiology (20 females; age range 21\u0026ndash;63 years; \u0026micro;\u0026thinsp;=\u0026thinsp;40.74, σ\u0026thinsp;=\u0026thinsp;12.67).\u003c/p\u003e\u003cp\u003eEight participants were excluded from the EEG analysis due to a connection error that prevented data from being saved and technical data storage error, resulting in a total of 66 participants included in the statistical analysis (37 females; age range 20\u0026ndash;69 years; \u0026micro;\u0026thinsp;=\u0026thinsp;40.33, σ\u0026thinsp;=\u0026thinsp;13.14).\u003c/p\u003e\u003cp\u003eTen participants were excluded from the EEG/Behavioral Moderation analysis due to the above issues with EEG analysis (N\u0026thinsp;=\u0026thinsp;8) and incomplete questionnaire data (N\u0026thinsp;=\u0026thinsp;2), resulting in a total of 64 participants included in the EEG/Behavioral moderation analysis (35 females; age range 21\u0026ndash;63 years; \u0026micro;\u0026thinsp;=\u0026thinsp;39.69; σ\u0026thinsp;=\u0026thinsp;13.45).\u003c/p\u003e\u003cp\u003eAll participants were randomly assigned to one of two groups (Table\u0026nbsp;1). Participant flow through enrollment, allocation, exclusions and analysis (Fig.\u0026nbsp;1).\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\u003e\u003cb\u003eParticipant characteristics for measures by group and analysis type.\u003c/b\u003e F\u0026thinsp;=\u0026thinsp;female; M\u0026thinsp;=\u0026thinsp;male. Age is reported in years. Μ and σ represent the mean and standard deviation of age, respectively.\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=\"char\" char=\".\" 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=\"char\" char=\".\" 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\" colname=\"c1\"\u003e\u003cp\u003eMeasure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGroup\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGender (M/F)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAge Range\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026micro;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eσ\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBehavior\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAlpha\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 Male, 20 Female\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20\u0026ndash;69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e39.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e14.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTheta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15 Male, 18 Female\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21\u0026ndash;63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e40.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e13.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePhysiology\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAlpha\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 Male, 13 Female\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21\u0026ndash;63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e14.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTheta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 Male, 7 Female\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21\u0026ndash;61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e41.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEEG\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAlpha\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15 Male, 19 Female\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20\u0026ndash;69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e38.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e13.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTheta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 Male, 18 Female\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21\u0026ndash;63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e41.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e12.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEEG /\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eBehavioral Moderation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAlpha\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15 Male, 18 Female\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20\u0026ndash;69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e39.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e13.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTheta\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 Male; 17 Female\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21\u0026ndash;63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e41.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e12.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\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\u003c/div\u003e\n\u003ch3\u003eRandomization\u003c/h3\u003e\n\u003cp\u003eSubjects were assigned to one of two groups using a MATLAB-based randomization algorithm that maintained gender balance, with recruitment ceasing for each gender category upon reaching the predetermined quota. Participants were randomly assigned to one of two stimuli: Alpha or Theta.\u003c/p\u003e\n\u003ch3\u003eRecruitment\u003c/h3\u003e\n\u003cp\u003eParticipants were recruited through multiple channels\u0026mdash;newsletters to previous research participants and targeted social media advertisements (Facebook, Craigslist, Instagram)\u0026mdash;within a 50-mile radius of Santa Monica, California (July 22, 2024\u0026ndash;March 4, 2025). Compensation comprised \u003cspan\u003e$\u003c/span\u003e30 per hour (cash or Venmo), calculated from check-in to departure and rounded to the nearest quarter-hour increment, with validated parking provided.\u003c/p\u003e\n\u003ch3\u003eEligibility\u003c/h3\u003e\n\u003cp\u003eParticipants were eligible for the study if they met all of the following criteria: (1) had no hairstyles such as braids, cornrows, dreadlocks, weaves, or extensions that could interfere with scalp sensor contact; (2) were not pregnant or possibly pregnant; (3) had no history of neurological conditions including epilepsy, seizures, or stroke; (4) had an absence of psychiatric disorders such as bipolar disorder or schizophrenia; (5) had no history of migraines; (6) had no photosensitivity or photophobia; (7) were free from eye conditions including cataracts, corneal abrasions, keratitis, or uveitis; (8) had no hearing impairments; (9) had no history of claustrophobia; (10) had no history of vertigo or motion sickness; (11) had no fear of darkness; (12) had normal or corrected-to-normal vision; (13) had sufficient mobility to participate without wheelchairs, walkers, or canes; and (14) were not currently taking medications affecting the central nervous system (including psychostimulants, antidepressants, or antipsychotics) or specific medications known to affect sensory perception (including but not limited to regular doses of NSAIDs, Dilantin, Methotrexate, tetracycline antibiotics, Digoxin, Amiodarone, Atropine, phenothiazine antipsychotics, H2 blockers, Fingolimod, aminoglycoside antibiotics, loop diuretics, and certain chemotherapeutics); (15) had not selected the response option indicating they had \"seriously thought of it as a way out\" on the suicide-related item from the Purpose in Life (PIL) (Crumbaugh \u0026amp; Maholick \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1964\u003c/span\u003e); and (16) received a score of 14 or higher on the Perceived Stress Scale (PSS) (Cohen et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1983\u003c/span\u003e), indicating moderate to high perceived stress levels.\u003c/p\u003e\u003cp\u003eAll potential participants completed a comprehensive online screening questionnaire via Google Forms to verify eligibility before study enrollment. This preliminary assessment verified that all participants met the established inclusion and exclusion parameters prior to beginning the research protocol.\u003c/p\u003e\n\u003ch3\u003eIRB\u003c/h3\u003e\n\u003cp\u003eAll recruitment and testing procedures were reviewed and approved by the Advarra Institutional Review Board (Columbia, MD) prior to the start of participant enrollment (Pro00079710). In accordance with ethical guidelines and legal obligations, all participants provided written informed consent via a document hosted on DropboxSign. Participants were given sufficient time to ask questions and receive clarification from the Principal Investigator or study staff. The consent process included the California Experimental Research Bill of Rights, as required by Health and Safety Code Section 24172. The study was conducted in alignment with the principles of the Declaration of Helsinki. In addition, all laboratory staff held current certifications in Good Clinical Practice and Human Research Participant Protection, completed through accredited online training programs. The clinical trial number is not applicable.\u003c/p\u003e\u003cp\u003eGiven the sensitivity of the study population, research staff were trained to follow a safety protocol in the event of participant suicidality. A licensed physician was on call during all sessions and was to be contacted immediately for clinical assessment if a participant exhibited urgent signs (e.g., suicidal intent or severe distress). If further action was deemed necessary, staff were instructed to call 911 and coordinate emergency transport to one of two pre-identified hospitals within 1.5 miles of the testing site, with staff instructed to remain with the participant until help arrived and report the incident to the Principal Investigator, IRB, and study sponsors in accordance with adverse event procedures. However, no such adverse events occurred.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eMaterials\u003c/h2\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003eStimuli\u003c/h2\u003e\u003cp\u003eParticipants underwent one of two audiovisual entrainment protocols\u0026mdash;theta (4\u0026ndash;7 Hz) or alpha (9\u0026ndash;11 Hz)\u0026mdash;administered within MindGym, a geometrically configured reflective chamber equipped with LED arrays positioned at structural vertices. The experimental conditions maintained identical temporal sequences, visual progression patterns, and instructional frameworks, differing exclusively in the frequency parameters of both visual stimulation and synchronized binaural audio tracks delivered through noise-canceling headphones.\u003c/p\u003e\u003cp\u003eThe standardized 23-minute protocol (including pre-recorded instructions) commenced with a 5-minute baseline period during which participants were encouraged to close their eyes and allow their minds to wander, establishing pre-intervention resting state conditions. The subsequent sequence progressed through six alternating eyes-open (utilizing purple, red, green, and blue spectral illumination) and eyes-closed (employing full-spectrum white light) phases (Fig.\u0026nbsp;2). Throughout the complete audiovisual sequence, synchronized binaural audio tracks reinforced targeted theta (4\u0026ndash;7 Hz) or alpha-mu (9\u0026ndash;11 Hz) frequency bands, encouraging multisensory entrainment.\u003c/p\u003e\u003cp\u003ePhase 1 eyes-open (30 seconds) involved single vertical LEDs illuminated at both posterior vertices relative to the participant's heading direction, expanding from center positions to 25% contiguous LED coverage with undulating intensity modulation synchronized to condition-specific frequency parameters. Phase 1 eyes-closed (30 seconds) featured complete LED activation across all cube vertices utilizing identical stroboscopic luminosity effects. Subsequent eyes-closed phases (Phases 2\u0026ndash;5, 30 seconds each) maintained these established full-spectrum white light activation protocols. Phase 2 eyes-open (30 seconds) progressed vertical LED coverage from 25% to 50% while preserving frequency-synchronized undulation patterns. Phase 3 eyes-open (30 seconds) achieved complete vertical LED activation at 100% coverage. Phase 4 eyes-open (30 seconds) sustained 100% vertical activation while introducing horizontal LED arrays positioned posterior and superior to the participant's heading direction. These horizontal arrays exhibited dynamic positional oscillation patterns utilizing 25% of available LEDs, with illuminated segments moving laterally from left to right and returning in continuous cycles synchronized to entrainment frequencies. Phase 5 eyes-open (30 seconds) maintained 100% vertical activation while implementing center-initiated horizontal LED expansion to 50% coverage, eliminating oscillatory movement patterns in favor of static radial expansion. Phase 6 eyes-open (60 seconds) culminated the visual sequence with synchronized vertical-horizontal LED activation at 100% coverage, generating complementary flickering patterns across the extended duration. The final eyes-closed phase (Phase 7; 120 seconds) diverged from preceding white light intervals by implementing progressive luminosity intensification, systematically increasing brightness parameters to create an intensified sensory finale. The protocol concluded with a 5-minute post-intervention rest period (eyes closed, LED arrays deactivated, audio muted).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003eMaterials\u003c/h3\u003e\n\u003cp\u003eAll participants sat on an OMEGA Gaming Chair (SecretLab, Inc.), wore noise-canceling, over-ear Bluetooth QuietComfort 45 headphones (Bose Corporation), and completed the behavioral questionnaires (administered through Google Forms) on a 27-inch 2022 iMac (Apple, Inc.), using a wireless keyboard and mouse, regardless of group.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eContent delivery system\u003c/h2\u003e\u003cp\u003eMindGym (Lumena, Inc.), is a 7' isotropic MindGym lined with reflective mylar on its interior walls, while its floor and ceiling are equipped with mirrors. MindGym incorporates WS2815 LEDs, with 121 pixels per edge between the vertices, totaling 1452 pixels across 12 edges. It utilizes a SMD5050 RGB LED chip, offering RGB color with 256 grayscale levels and an output of 990\u0026ndash;1080 lumens per meter. The LEDs are operated at less than half of their maximum capacity. Additionally, the system features a color temperature of 5500K. MindGym has been used previously by our group as an anxiolytic experiential technology (Simonian et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eMuse-S\u003c/h2\u003e\u003cp\u003eAll participants wore the Muse-S (InteraXon, Inc.), a consumer-grade, multi-sensory headband featuring four EEG sensors (two on the forehead [AF7, AF8]; two behind the ears [TP9, TP10]; reference at FPz) with a sampling rate of 256 Hz, along with Photoplethysmography (PPG). The Muse-S connected to the \u0026ldquo;Muse: Meditation \u0026amp; Sleep\u0026rdquo; app on a 10.9-inch 2022 iPad Air (Apple, Inc.) to initialize satisfactory signal quality via the built-in quality check.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eNeuropype\u003c/h2\u003e\u003cp\u003eNeuropype (Intheon, San Diego, CA) was leveraged to receive raw EEG data via a lab-streaming layer (LSL) stream. The pipeline applies minimal preprocessing: timestamp dejittering to create evenly spaced samples across channels, followed by a FIR bandpass filter with edge frequencies at 0.5, 1, 65, and 70 Hz to eliminate typical noise artifacts.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eBehavioral Questionnaires\u003c/h2\u003e\u003cp\u003eBehavioral questionnaires were administered during screening, pre and post experiment to gather trait and state information (See Table\u0026nbsp;2).\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\u003eBehavioral questionnaires denoted by measure and timepoint.\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeasure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTime\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQuestionnaire\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDescription\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e\u003cp\u003e\u003cb\u003eTrait\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"6\" rowspan=\"7\"\u003e\u003cp\u003e\u003cb\u003ePre\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTen-Item Personality Inventory (TIPI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTen items to measure the Big Five personality dimensions: openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism (Th\u0026oslash;rrisen \u0026amp; Sadeghi, \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDispositional Hope Scale (DHS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTwelve items to measure the feeling of hope on a Likert scale from 1 (definitely false) to 4 (definitely true), divided among three subscales: pathways, agency, and negative filler items that aren't related to hope (Snyder et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1991\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGeneral Self-Efficacy Scale (GSES)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTen items to measure self-efficacy in a professional setting on a Likert scale from 1 (not at all true) to 4 (exactly true). Also measures if self-efficacy is a predictor of burnout and engagement (Ventura et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMultidimensional Health Locus of Control (MHLC)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEighteen items to assess the extent to which individuals believe they have control over their health, divided among three subscales: internality, powerful others externality, and chance externality (Wallston et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e1978\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConnor-Davidson Resilience Scale (CD-RISC-10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTen items to measure resilience (the ability to adapt from stress, trauma, and adversity), on a Likert scale from 0 (not true at all) to 4 (nearly true all the time), using five subscales: personal competence, acceptance of change and secure relationships, trust/tolerance/strengthening effects of stress, control, and spiritual influences (Connor \u0026amp; Davidson, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDispositional Resilience 'Hardiness' Scale (HARDY)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eForty-five items to measure hardiness\u0026ndash;a trait associated with resilience and stress tolerance\u0026ndash;using three subscales: communication scale, challenge scale, and control scale (Bartone et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1989\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eState-Trait Anxiety Inventory (STAI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA measure of state anxiety (temporary/situational) and trait anxiety (enduring propensity) (Spielberger et al., 1983).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u003cb\u003eState\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u003cb\u003ePre \u0026amp; Post\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eProfile of Mood States (POMS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA measure of current mood states across affective dimensions like anger, confusion, depression, fatigue, tension, and vigor (Heuchert \u0026amp; McNair, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAnxiety-Emoji-based Scale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eA single-item measure using five animated emoji images, ranging from very happy to very sad, to represent the respondent's current level of anxiety (Setty et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSubjective Vitality Scale (SVS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSix items to assess subjective vitality via self-reported positive mental energy and alertness, using a Likert scale from 1 (not at all true) to 7 (very true) (Saricam, 2015).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePositive and Negative Affect Schedule (PANAS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTwenty items used to measure the presence and intensity of emotions, using two subscales: positive affect and negative affect (Watson et al., \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e1988\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFlow State Scale (FFS) (short version)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNine items to assess flow experience using two subscales: absorption by activity factor and fluency of performance factor (Rheinberg et al., 2003).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eOutcome\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eScreening \u0026amp; Post\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePurpose in Life Test (PIL)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTwenty items to measure one's sense of perceived purpose or meaning in life. Respondents rate their agreement with statements about their life experience on a scale from 1 (feelings of no purpose) to 5 (the greatest feelings of purpose) (Crumbaugh \u0026amp; Maholick, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1964\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePerceived Stress Scale (PSS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTen items to measure how different situations affect feelings of stress, measured on a scale from 0 (never) to 4 (very often) (Cohen et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1983\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003ePost\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEmotional Breakthrough Inventory (EBI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSix items to assess acute emotional breakthroughs using a scale from 0 (no, not more than usual) to 10 (yes, entirely or completely) (Roseman et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eToronto Mindfulness Scale (TMS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eThirteen items to measure state mindfulness (administered post-meditation), differentiating between reflective awareness and ruminative attention, using two subscales: curiosity (gauging interest in one's experiences) and decentering (reflecting the ability to view thoughts and feelings as transient mental events) (Lau et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2006\u003c/span\u003e).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eSoftware\u003c/h2\u003e\u003cp\u003eAll first pass analyses were conducted in JASP 0.19.3 (JASP Team, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). FDR corrections for moderation analyses were conducted in Python 3.12.2 using the statsmodel module version 0.14.0 leveraging the Benjamini-Hochberg method (Statsmodels Development Team, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Post-hoc EEG moderation of behavioral measures were conducted in Python 3.12.2 using the statsmodel module version 0.14.0 and figures were made using matplotlib version 3.10.0 and seaborn version 0.13.2 (Statsmodels Development Team, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Hunter, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Waskom, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eProcedure\u003c/h2\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003ch2\u003eOverview\u003c/h2\u003e\u003cp\u003e Before each session, all participants signed eConsent forms (DropboxSign). They began the session by filling out pre-experience questionnaires, followed by Muse-S Headband setup. Subsequently, each group underwent a 25-minute experiential phase, after which they completed post-experience questionnaires and tasks. The total participation time was roughly 90 minutes.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eProcedure\u003c/h2\u003e\u003cp\u003eUpon arrival, participants were seated on an office chair facing a 35.5\u0026rdquo; x 55\u0026rdquo; desk and given an overview of the session (pre-questionnaires, equipment setup, 25-minute experience, post-questionnaires). They were informed that their \u0026ldquo;experience\u0026rdquo; would involve sitting for 25 minutes in an immersive audiovisual environment.\u003c/p\u003e\u003cp\u003eFor approximately the first 30 minutes, participants completed a set of questionnaires (TIPI, DHS, GSES, MHLC, CD-RISC-10, HARDY, STAI, GA-VAS, POMS, SVS, PANAS, FFS-short version, and Anxiety Emoji-based scale) on Google Forms. Participants were instructed to silence their phones and remove smartwatches or electronic wristbands that emit light. Using a cotton pad and 91% isopropyl alcohol, the experimenter cleansed the participant\u0026rsquo;s forehead and areas behind the ears, before outfitting the participant with the Muse-S headband, ensuring a snug fit on the forehead to optimize sensor connectivity. The experimenter used the Muse: Meditation \u0026amp; Sleep app to check signal quality. The app displayed visual indicators for each sensor, with green signifying a good connection and red denoting no connection. The experimenter adjusted the headband as needed until all sensors displayed a green indicator. Furthermore, the filtered data from Neuropype (see Materials) was displayed in a live time-series plot showing all EEG channels. A research assistant visually inspected the plot to confirm that each channel was delivering a stable and discernible signal. If a channel showed a weak or missing signal, the assistant checked for possible obstructions, such as hair or clothing interfering with sensor contact until the signal was visually acceptable.\u003c/p\u003e\u003cp\u003eParticipants were led intoMindGym, seated centrally, provided headphones, and instructed to sit still, face the wall 90 degrees to their left when facing the entrance, and follow the instructions provided through the headphones during the 25-minute experience without falling asleep. Participants were shown how to exit MindGym if they chose to end the experience early, otherwise, the experimenter would return to assist them once the experience ended. The experience began within 30 seconds of MindGym door closing.\u003c/p\u003e\u003cp\u003eAfter the experience, the Muse-S headband was removed and participants were given the opportunity to use the restroom if needed before completing post-experience behavioral assessments (STAI, GA-VAS, POMS, SVS, PANAS, FFS-short version, EBI, PIL, PSS, TMS, and Anxiety Emoji-based scale). Finally, participants were remunerated, their parking validated, and dismissed.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eBehavioral Analyses\u003c/h2\u003e\u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\u003ch2\u003eDependent variables\u003c/h2\u003e\u003cp\u003eThe primary dependent variables in this study were scores on self-report measures administered pre- and post-intervention, including: anxiety measures\u0026mdash;State-Trait Anxiety Inventory (STAI-State) and Anxiety Emoji Scale; mood measures\u0026mdash;Profile of Mood States (POMS) subscales (Depression, Tension, Anger, Fatigue, Confusion) and total score, and Positive and Negative Affect Schedule (PANAS); flow measures\u0026mdash;Flow State Scale (FSS) subscales (Absorption by Activity, Fluency of Performance) and total score; and vitality measure\u0026mdash;Subjective Vitality Scale (SVS).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eIndependent variables\u003c/h2\u003e\u003cp\u003eThe primary independent variables were: condition (between-subjects factor), comparing alpha neurostimulation (9\u0026ndash;11 Hz) with theta neurostimulation (4\u0026ndash;7 Hz); deltas between Pre-intervention and Post-intervention assessments; and Pre-intervention versus Post-intervention assessments.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eNonparametric tests\u003c/h2\u003e\u003cp\u003ePrior to conducting the ANOVAs, the data were assessed for violations of parametric assumptions, including normality using Shapiro-Wilk tests and homogeneity of variance using Levene's test. In cases where these assumptions were substantially violated, equivalent nonparametric alternatives (e.g., Wilcoxon signed-rank tests for within-subject comparisons and Mann-Whitney U tests for between-subject comparisons) were utilized.\u003c/p\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eModeration\u003c/h2\u003e\u003cp\u003eTo examine whether individual differences moderated the effects of the interventions, linear regression analyses were conducted. In these analyses, changes in variables (post-pre difference scores) and also outcome variables were regressed on condition (alpha vs. theta), potential moderator variables (TIPI, DHS, GSES, MHLC, CD-RISC-10, HARDY, etc.), and their interaction terms. Significant interaction terms would indicate that the effectiveness of the interventions varied as a function of individual differences on the trait measures. EEG baseline measures were also examined as potential moderators of intervention effects. Linear regression analyses were conducted with changes in outcome variables regressed on condition (alpha vs. theta), baseline EEG parameters, and their interaction terms. Significant interactions would indicate that baseline brain activity patterns influenced differential responsiveness to alpha versus theta interventions.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eRepeated measures ANOVA\u003c/h2\u003e\u003cp\u003eA series of 2 \u0026times; 2 mixed-design repeated measures ANOVAs were conducted to evaluate the effects of the interventions on all dependent variables. Each ANOVA included condition (alpha vs. theta) as a between-subjects factor and time (pre-intervention vs. post-intervention) as a within-subjects factor. The main effects of condition and time, as well as their interaction, were examined for each dependent variable. Post hoc analyses were conducted on initial significant results. Effect sizes were reported using generalized eta squared (\u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e) for the mixed design ANOVAs, and Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e (\u003cem\u003ed\u003c/em\u003e) for post hoc analyses. For \u003cem\u003ed\u003c/em\u003e, values of 0.2, 0.5, and 0.8 indicated small, medium, and large effects, respectively (Cohen, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). For \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e, values of 0.02, 0.13, and 0.26 indicated small, medium, and large effects, respectively (Bakeman, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003eMediation\u003c/h2\u003e\u003cp\u003eMediation analyses were conducted to explore potential mechanisms underlying the observed effects. Specifically, we examined whether changes in state anxiety and mood states mediated the relationship between the interventions and changes in outcome variables. These analyses followed the bootstrapping approach recommended by Preacher and Hayes (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) using 5,000 bootstrap samples to estimate indirect effects and their 95% confidence intervals.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\u003ch2\u003eEEG analysis\u003c/h2\u003e\u003cp\u003eEEG preprocessing began with timestamp dejittering to ensure evenly spaced samples across all channels, followed by the removal of bad channels identified during a 60-second calibration period based on signal variance. A FIR highpass filter (0.5\u0026ndash;1 Hz passband, 80 dB stopband attenuation) was then applied to eliminate slow drifts and baseline shifts while preserving low-frequency neural activity. After filtering, artifact removal was performed by excluding data segments that exceed predefined thresholds. A FIR notch filter (55\u0026ndash;65 Hz) was applied to suppress 60 Hz line noise common in lab environments, and a FIR lowpass filter (95\u0026ndash;100 Hz) was used to attenuate high-frequency muscle and equipment artifacts. Channels previously removed due to poor signal quality are then reinterpolated using spatial information from neighboring electrodes, restoring full topographic coverage for downstream analysis.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\u003ch2\u003eMultiple Comparison Corrections\u003c/h2\u003e\u003cp\u003eMultiple comparison corrections were applied according to each analysis's statistical structure and research objectives. Primary hypotheses regarding main effects of time and condition underwent Bonferroni correction (α\u0026thinsp;=\u0026thinsp;0.05) as confirmatory analyses requiring stringent Type I error control.\u003c/p\u003e\u003cp\u003eModeration analyses, designated as exploratory for future hypothesis generation, were corrected using the Benjamini\u0026ndash;Hochberg False Discovery Rate (FDR) (α\u0026thinsp;=\u0026thinsp;0.05) applied separately within five conceptually distinct families: (1) state moderation\u0026mdash;pre-intervention state measures moderating changes in corresponding state variables (15 tests); (2) trait moderation\u0026mdash;personality traits moderating state changes (120 tests); (3) state\u0026ndash;outcome moderation\u0026mdash;pre-intervention states moderating outcome changes (60 tests); (4) trait\u0026ndash;outcome moderation\u0026mdash;personality traits moderating outcome changes (32 tests); and (5) EEG moderation\u0026mdash;baseline brain activity moderating intervention effectiveness on behavioral outcomes (64 tests). Within each family, FDR was applied exclusively to interaction effects, targeting exploratory moderation findings.\u003c/p\u003e\u003cp\u003eThis family-wise FDR framework increased sensitivity to potential moderator effects while maintaining principled control over false discoveries within each conceptual domain, aligning with established approaches for exploratory analyses aimed at identifying predictors of treatment response (Benjamini \u0026amp; Hochberg, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Wang \u0026amp; Ware, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\u003ch2\u003ePsychological Measures\u003c/h2\u003e\u003cdiv id=\"Sec30\" class=\"Section3\"\u003e\u003ch2\u003eOutcome Measures\u003c/h2\u003e\u003cp\u003eRepeated measures ANOVAs revealed significant main effects of time for the primary outcome measures after correction for multiple comparisons (Tables\u0026nbsp;3a and 3b), with post hoc analyses conducted for significant findings. Perceived stress (PSS) decreased significantly from pre- to post-intervention (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;28.458, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e \u0026lt; 0.001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.051, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.458 [95% CI, 0.270, 0.647]) and purpose in life (PIL) increased significantly (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;14.496, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e \u0026lt; 0.001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.071, \u003cem\u003ed\u003c/em\u003e = -0.547 [95% CI, -0.849\u0026ndash;0.245]). No significant main effects of condition were observed for either PSS (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.073, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.788, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e = 0.788, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.001) or PIL (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.263, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.610, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e = 0.732, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.003). The time \u0026times; condition interaction for PSS (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.814, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.055, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e = 0.110, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.007) and PIL (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.474, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.229, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e = 0.344, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.008) were also non-significant.\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\u003e\u003cb\u003ea. Results of repeated measures ANOVA in outcome measures.\u003c/b\u003e Time effects pertain to the repeated measures from questionnaire responses during screening and then again following the intervention. Condition effects pertain to alpha vs. theta group comparisons.\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMeasure Category\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpecific Measure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF-statistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEffect Size\u003c/p\u003e\u003cp\u003e(\u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e; Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eBonferroni Corrected p-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eStress\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePSS Time Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28.458\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.051;\u003c/p\u003e\u003cp\u003e0.458 [95% CI, 0.270\u0026ndash;0.647]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePSS Condition Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.073\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.788\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001;\u003c/p\u003e \u003cp\u003e0.061 [95% CI, -0.380\u0026ndash;0.510]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.788\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePSS Time \u0026times; Condition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.814\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.110\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePurpose\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePIL Time Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14.496\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.071;\u003c/p\u003e\u003cp\u003e-0.547 [95% CI, -0.849 \u0026ndash; -0.245]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePIL Condition Effect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.263\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.610\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.003;\u003c/p\u003e\u003cp\u003e0.099 [95% CI, -0.287\u0026ndash;0.486]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.732\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePIL Time \u0026times; Condition\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.474\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.344\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\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003eb. Results of between group t-tests in post-intervention outcome measures\u003c/b\u003e. T-tests of the Emotional Breakthrough Inventory (EBI) and Toronto Mindfulness Scale (TMS). Results show no statistical significance between the two conditions in either measure.\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=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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\u003cp\u003eMeasure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003et-statistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmotional Breakthrough Inventory\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-1.075\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.286\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.259\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eToronto Mindfulness Scale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.750\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.456\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.181\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\u003ePost hoc analyses revealed significant improvements across both conditions, with reductions in PSS (Alpha: -3.72; Theta: -1.73) and increases in PIL (Alpha: +4.69; Theta: +9.09). Independent samples t-tests on change scores (post minus pre) showed a marginally significant difference between groups for reduction in PSS scores (\u003cem\u003et(67)\u003c/em\u003e = -1.953, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.055, \u003cem\u003ed\u003c/em\u003e = -0.471), with Alpha participants showing numerically greater stress reduction, but no significant difference for purpose in life changes (t(67) = -1.214, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.229, d = -0.293).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec31\" class=\"Section2\"\u003e\u003ch2\u003eTimepoint effects\u003c/h2\u003e\u003cp\u003eNearly all state measures demonstrated significant main effects of time (Table\u0026nbsp;4), indicating that both alpha and theta conditions elicited comparably substantial improvements from pre- to post-intervention, with no significant time \u0026times; condition interactions or between-group differences emerging, thus suggesting equivalent therapeutic impact across stimulation protocols.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eResults of repeated measures ANOVA in state measures.\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" 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\u003cp\u003eMeasure Category\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpecific Measure\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eF-statistic (1, 67)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eEffect size\u003c/p\u003e\u003cp\u003e(\u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e; Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eBonferroni Corrected p-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAnxiety\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSTAI-State\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e95.862\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.324;\u003c/p\u003e\u003cp\u003e1.365 [95% CI, 1.001\u0026ndash;1.730]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAnxiety Emoji Scale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.115;\u003c/p\u003e\u003cp\u003e0.713 [95% CI, 0.374\u0026ndash;1.052]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDepression/Mood\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePOMS Depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e74.687\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.258;\u003c/p\u003e\u003cp\u003e1.162 [95% CI, 0.827\u0026ndash;1.497]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePOMS Total Mood Disturbance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e58.491\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.261;\u003c/p\u003e\u003cp\u003e1.172 [95% CI, 0.811\u0026ndash;1.534]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePOMS Tension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53.559\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.219;\u003c/p\u003e\u003cp\u003e1.045 [95% CI, 0.708\u0026ndash;1.382]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePOMS Fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e45.771\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.185;\u003c/p\u003e\u003cp\u003e0.941 [95% CI, 0.619\u0026ndash;1.262]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePOMS Confusion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e36.949\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.157;\u003c/p\u003e\u003cp\u003e0.850 [95% CI, 0.535\u0026ndash;1.166]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePOMS Anger\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e34.785\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.193;\u003c/p\u003e\u003cp\u003e0.963 [95% CI, 0.598\u0026ndash;1.329]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePOMS Vigor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.087\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.301\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.005;\u003c/p\u003e\u003cp\u003e-0.098 [95% CI, -0.393\u0026ndash;0.124)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eN/A\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePANAS Negative Affect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33.735\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.034;\u003c/p\u003e\u003cp\u003e0.848 [95% CI, 0.522\u0026ndash;1.174]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFlow States\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFSS Total\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e54.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.151;\u003c/p\u003e\u003cp\u003e-0.832 [95% CI, -1.100 \u0026ndash; -0.564]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFSS Fluency of Performance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e46.893\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.155;\u003c/p\u003e\u003cp\u003e-0.844 [95% CI, -1.130 \u0026ndash; -0.558]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFSS Absorption by Activity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29.071\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.084;\u003c/p\u003e\u003cp\u003e-0.598 [95% CI, -0.842 \u0026ndash; -0.354]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePositive Affect\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePANAS Positive Affect\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9.505\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.034;\u003c/p\u003e\u003cp\u003e-0.369 [95% CI, -0.616 \u0026ndash; -0.122\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSubjective Vitality Scale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17.498\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.059;\u003c/p\u003e\u003cp\u003e-0.493 [95% CI, -0.743 \u0026ndash; -0.243]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\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\u003eBoth anxiety measures demonstrated robust pre-to-post intervention improvements: STAI-State (Fig.\u0026nbsp;3; \u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;95.862, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e\u0026lt; .001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.324) and the Anxiety Emoji Scale (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;20.252, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e \u0026lt; .001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.115). The particularly large effect size for STAI-State anxiety reduction represents one of the most pronounced effects observed across all measured domains, emphasizing the intervention's potent anxiolytic properties.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAll mood measures also showed significant improvements: POMS Depression (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;74.687, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e \u0026lt; .001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.258), POMS Tension (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;53.559, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e \u0026lt; .001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.219), POMS Anger (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;34.785, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e \u0026lt; .001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.193), POMS Fatigue (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;45.771, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e \u0026lt; .001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.185), POMS Confusion (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;36.949, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e \u0026lt; .001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.157), POMS Total Mood Disturbance(TMD; Fig.\u0026nbsp;4; \u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;58.491, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e \u0026lt; .001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.261), PANAS Positive Affect (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9.505, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e = 0.045, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.034), and PANAS Negative Affect (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;33.735, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e \u0026lt; .001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.034).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFlow measures also demonstrated significant increases: FSS Absorption by Activity (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;29.071, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e \u0026lt; .001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.084), FSS Fluency of Performance (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;46.893, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.155), and FSS Total (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;54.016, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e \u0026lt; .001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.151). Similarly, the Subjective Vitality Scale showed a significant increase (\u003cem\u003eF(1,67)\u003c/em\u003e\u0026thinsp;=\u0026thinsp;17.498, \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e \u0026lt; .001, \u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.059).\u003c/p\u003e\u003cp\u003eThe effect sizes indicate that the time effects were particularly strong for POMS Depression (\u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.258, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.162 [95% CI, 0.827\u0026ndash;1.497]), POMS Total Mood Disturbance (TMD) (\u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.261, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.172 [95% CI, 0.811\u0026ndash;1.534]), and FSS Total (\u003cem\u003eη\u0026sup2;\u003c/em\u003e\u003csub\u003e\u003cem\u003eG\u003c/em\u003e\u003c/sub\u003e = 0.151, Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e = -0.832 [95% CI, -1.100 \u0026ndash; -0.564]), demonstrating these measures showed large effect size changes from pre to post across both conditions. All time effects remained significant after applying Bonferroni correction for multiple comparisons across all 15 state comparisons (all \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003ebonf\u003c/em\u003e\u003c/sub\u003e \u0026lt; 0.004), indicating robust improvements across anxiety, mood, flow, and vitality domains.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec32\" class=\"Section2\"\u003e\u003ch2\u003eMediation\u003c/h2\u003e\u003cp\u003eMediation analyses revealed no significant indirect effects of condition (alpha vs. theta) through any psychological mediating variables to either primary outcome (PIL or PSS). The indirect effects of condition on both outcomes were consistently non-significant across all models, indicating that the equivalent therapeutic benefits observed for both interventions were not mediated through the measured psychological variables. While several psychological variables showed significant direct relationships with outcomes, such as anxiety and mood improvements predicting enhanced purpose in life, and multiple well-being indicators relating to stress reduction, these relationships were independent of intervention condition. These findings suggest that alpha and theta protocols may achieve similar therapeutic outcomes through distinct neurobiological pathways not captured by self-report psychological measures.\u003c/p\u003e\u003cdiv id=\"Sec33\" class=\"Section3\"\u003e\u003ch2\u003eModeration\u003c/h2\u003e\u003c/div\u003e\u003cdiv id=\"Sec34\" class=\"Section3\"\u003e\u003ch2\u003ePredictors of Change in Outcome Measures\u003c/h2\u003e\u003cp\u003eWe examined whether pre-intervention psychological states moderated the effects of alpha versus theta on outcome measures. Several significant findings emerged as interaction effects between condition and baseline measures, indicating differential moderating patterns between the two intervention types (Table\u0026nbsp;5).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eState predictors moderation of change in outcome measure\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\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\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOutcome\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSignificant Moderators\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eKey Finding\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePurpose in Life (PIL)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePOMS TMD (\u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003eFDR\u003c/em\u003e\u003c/sub\u003e = 0.033)\u003c/p\u003e\u003cp\u003ePOMS Anger (\u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003eFDR\u003c/em\u003e\u003c/sub\u003e = 0.019)\u003c/p\u003e\u003cp\u003ePOMS Depression (\u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003eFDR\u003c/em\u003e\u003c/sub\u003e = 0.033)\u003c/p\u003e\u003cp\u003ePOMS Confusion (\u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003eFDR\u003c/em\u003e\u003c/sub\u003e \u0026lt; 0.001)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSeveral POMS subscales and total scale significantly moderate changes in PIL when interacting with condition\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePerceived Stress Scale (PSS)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-significant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo significant findings\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\u003eSignificant findings included moderation of the relationship between condition and Purpose in Life (PIL) Outcomes by POMS Total Mood Disturbance (Fig.\u0026nbsp;5), Anger, Depression, and Confusion. Participants with higher baseline mood disturbance showed greater PIL improvements in the theta condition compared to the alpha condition, while those with lower baseline mood disturbance showed similar improvements across both interventions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAnalysis of Perceived Stress Scale outcomes identified several pre-intervention predictors including Flow State Scale Total scores, FSS Fluency of Performance subscale ratings, anxiety emoji assessments, and PANAS Negative Affect levels; however, none remained significant following FDR correction. Alpha protocol participants demonstrated greater mean stress reduction (M = -3.72, SD\u0026thinsp;=\u0026thinsp;3.10) compared to theta participants (M = -1.73, SD\u0026thinsp;=\u0026thinsp;5.20). No baseline state measures significantly moderated Emotional Breakthrough Inventory or Toronto Mindfulness Scale outcomes across either condition.\u003c/p\u003e\u003cp\u003eNo trait variables collected during the screening significantly moderated outcome variables.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003eNeurophysiological Results\u003c/h3\u003e\n\u003cdiv id=\"Sec36\" class=\"Section2\"\u003e\u003ch2\u003ePhysiology Changes Over Time\u003c/h2\u003e\u003cp\u003eTo examine changes over time in HR and HRV we employed repeated measures ANOVA which resulted in no significant changes over time comparing the pre-rest and post-rest stages (See Supplementary Materials: Results, Table\u0026nbsp;1).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec37\" class=\"Section2\"\u003e\u003ch2\u003eEEG Changes Over Time\u003c/h2\u003e\u003cp\u003eTo examine EEG changes over time, we employed repeated measures ANOVA which resulted in a significant difference in Alpha power comparing the pre-rest and post-rest stages, but did not survive Bonferroni correction (See Supplementary Materials: Results, Tables\u0026nbsp;2,4).\u003c/p\u003e\u003cdiv id=\"Sec38\" class=\"Section3\"\u003e\u003ch2\u003ePhysiology Group Differences Post-Intervention\u003c/h2\u003e\u003cp\u003eAll independent sample t-tests for analysis of physiological measures (HR and HRV) revealed no statistical differences between the Alpha and Theta groups after correcting for multiple comparisons (See Supplementary Materials: Results, Table\u0026nbsp;3).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec39\" class=\"Section2\"\u003e\u003ch2\u003eEEG Group Differences Post-Intervention\u003c/h2\u003e\u003cp\u003eAll independent sample t-tests for analysis of EEG measures (including power band ratios) revealed no statistical differences between the Alpha and Theta groups after correcting for multiple comparisons (See Supplementary Materials: Results, Table\u0026nbsp;3).\u003c/p\u003e\u003cdiv id=\"Sec40\" class=\"Section3\"\u003e\u003ch2\u003eEEG Band Powers Mediating Behavioral Measures\u003c/h2\u003e\u003cp\u003eMediation analyses were conducted to examine whether changes in EEG band powers served as mediating mechanisms linking treatment condition to behavioral outcomes. However, no significant indirect effects were observed across any of the EEG frequency bands examined, indicating that the measured neural oscillatory changes did not significantly mediate the relationship between treatment condition and behavioral improvements. These findings suggest that the psychological benefits observed in both conditions may operate through alternative neurobiological pathways not captured by the specific EEG frequency bands analyzed, or that the mediating effects occur through more complex neural network interactions beyond simple power changes in isolated frequency ranges.\u003c/p\u003e\u003cp\u003e\u003cb\u003eEEG Band Powers Moderating Behavioral Measures\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSeveral potential moderation effects of baseline EEG measures on treatment outcomes were observed at the uncorrected statistical level; however, none of these effects survived correction for multiple comparisons using the False Discovery Rate (FDR) method (all \u003cem\u003ep\u003c/em\u003e\u003csub\u003e\u003cem\u003eFDR\u003c/em\u003e\u003c/sub\u003e \u0026gt;0.05).Additionally, baseline alpha/theta ratios showed a significant negative correlation with intervention-related changes of the same (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.38, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002), suggesting a regression-to-the-mean effect where the intervention may normalize rather than uniformly alter neurophysiological activity (See Supplemental Materials: Results, Fig.\u0026nbsp;1).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis pilot investigation examined whether audiovisual stimulation\u0026mdash;binaural beats synchronized with stroboscopic light at alpha (9\u0026ndash;11 Hz) vs. theta (4\u0026ndash;7 Hz) frequencies\u0026mdash;delivered through an immersive reflective chamber (MindGym) could meaningfully impact stress, burnout mitigation, and psychological well-being in 74 participants. Both 11-minute protocols, alternating between traditional closed-eye periods and open-eye segments within the chamber's mirrored environment, demonstrated robust feasibility and tolerability while yielding relevant improvements across multiple psychological domains critical to this vulnerable population. The comprehensive assessment battery revealed effect sizes suggesting that even brief, single-session interventions may substantially \"move the needle\" on traditionally resistant burnout indicators\u0026mdash;a finding particularly salient for populations wherein any measurable relief from chronic stress represents meaningful therapeutic progress, potentially obviating traditional controlled comparison requirements when evaluating interventions for acute distress states.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePrimary Findings and Clinical Significance\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe magnitude of observed effects across burnout-relevant measures of affect was remarkable, with nearly all psychological domains demonstrating significant improvement. State anxiety (STAI) exhibited the most substantial change (F(1,67)\u0026thinsp;=\u0026thinsp;95.862, η\u0026sup2;p\u0026thinsp;=\u0026thinsp;0.589, d\u0026thinsp;=\u0026thinsp;1.365), followed by depression-related mood disturbance (F\u0026thinsp;=\u0026thinsp;74.687, η\u0026sup2;p\u0026thinsp;=\u0026thinsp;0.527, d\u0026thinsp;=\u0026thinsp;1.162) and flow experience enhancement (F\u0026thinsp;=\u0026thinsp;54.016, η\u0026sup2;p\u0026thinsp;=\u0026thinsp;0.446, d = -0.832). The magnitude of observed effects provides important context when considered alongside established interventions. Pharmacological anxiolytics achieve substantial STAI reductions\u0026mdash;SSRIs (d\u0026thinsp;=\u0026thinsp;2.09), benzodiazepines (d\u0026thinsp;=\u0026thinsp;2.15)\u0026mdash;yet require 8\u0026ndash;12 weeks of continuous administration with attendant side effect profiles (Bandelow et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Psychological interventions yield comparable magnitudes (relaxation: d\u0026thinsp;=\u0026thinsp;1.36; individual CBT: d\u0026thinsp;=\u0026thinsp;1.30) across multiple therapeutic sessions spanning weeks. Our single 25-minute session achieved STAI reduction of d\u0026thinsp;=\u0026thinsp;1.365\u0026mdash;effectively 11 minutes of active audiovisual stimulation producing anxiolytic effects approaching those of established treatments. This temporal efficiency, achieved without training prerequisites, medication adherence, or contraindications, distinguishes the intervention's clinical utility. However, these data reflect solely acute post-stimulation measurement; longitudinal durability remains empirically unestablished, precluding claims of therapeutic equivalence pending evidence of sustained efficacy.\u003c/p\u003e\u003cp\u003eAdditionally, improvements in burnout-specific indicators were also particularly noteworthy. The Subjective Vitality Scale showed significant enhancement (F(1,67)\u0026thinsp;=\u0026thinsp;17.498, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, η\u0026sup2;p\u0026thinsp;=\u0026thinsp;0.207), critical given that vitality mediates the relationship between self-efficacy and burnout resistance (Saricam, 2015); higher vitality predicts sustained work engagement even under stressful conditions. This finding gains additional significance considering burnout may a physiologically \"sticky\" state that rarely improves without substantial environmental change such as job departure (Chernenko, 2023). Demonstrating measurable improvement in this treatment-resistant population provides evidence exceeding typical control group expectations.\u003c/p\u003e\u003cp\u003eThe effect sizes consistently surpassed established non-pharmacological interventions. Our PSS reduction (d\u0026thinsp;=\u0026thinsp;0.458) exceeded brief mindfulness interventions (d\u0026thinsp;=\u0026thinsp;0.37; Cavanagh et al., 2018), while anxiety improvements substantially exceeded those from 8-week meditation programs (d\u0026thinsp;=\u0026thinsp;0.38; Goyal et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Most remarkably, we demonstrated measurable flow state induction\u0026mdash;a phenomenon no prior intervention has conclusively achieved through experimental manipulation (Goddard et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), despite flow's recognized importance for performance and well-being.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMechanistic Considerations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSurprisingly, we found no evidence supporting neural entrainment as the primary therapeutic mechanism. Neither protocol produced significant changes in target frequency band power from pre- to post-intervention, nor did post-intervention EEG profiles differ between groups despite frequency-specific stimulation (all pFDR\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The absence of measurable entrainment\u0026mdash;potentially attributable to limitations inherent to the consumer-grade EEG system (see Limitations), given previous evidence of entrainment with research-grade systems (e.g., Frohlich et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u0026mdash;suggests therapeutic effects may, at least somewhat, arise through alternative neurophenomenological pathways. For example, the immersive reflective environment itself can induce psychological awe (Simonian et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), a state robustly associated with enhanced meaning-making (Sawada et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), lessened sympathetic activation (Bai et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and well-being (Monroy et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Alternatively, synchronized audiovisual stimulation may trigger relaxation responses through subcortical pathways (Thaut, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) or network-level changes not captured by traditional spectral analysis.\u003c/p\u003e\u003cp\u003eThe therapeutic equivalence observed across stimulation frequencies in our study further reinforces the possibility that the immersive multisensory environment itself, rather than frequency-specific neural entrainment, may constitute the primary therapeutic mechanism. However, pre vs. post changes in measures like STAI were notably more drastic in the current intervention compared to previous MindGym interventions (Simonian et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), suggesting that these particular stroboscopic interventions were multiplicative of MindGym-only effects.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFrequency-Specific Therapeutic Profiles\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDespite mechanistic uncertainty, some frequency-dependent dissociations emerged that suggest distinct neurotherapeutic profiles. Primary outcome analyses revealed robust improvements across both protocols, yet post-hoc examination unveiled a nuanced dissociation: alpha stimulation yielded numerically superior stress reduction (ΔPSS = -3.72 vs. -1.73, p\u0026thinsp;=\u0026thinsp;0.055), while theta stimulation engendered more pronounced enhancement of existential purpose (ΔPIL\u0026thinsp;=\u0026thinsp;+\u0026thinsp;9.09 vs. +4.69). The pattern extended to state measures, where theta consistently yielded numerically superior improvements across POMS Depression, Tension, Anger, and Fatigue subscales, as well as flow state enhancement (+\u0026thinsp;6.091 vs\u0026thinsp;+\u0026thinsp;4.361). While these differences failed to achieve conventional significance thresholds, such incremental gains hold substantial clinical relevance for individuals experiencing burnout and anxiety, where even marginal improvements in mood regulation or positive affect can meaningfully impact functional capacity and quality of life.\u003c/p\u003e\u003cp\u003eThis divergent pattern extended to phenomenological outcomes, with theta participants demonstrating enhanced emotional breakthrough (28.3 vs. 24.3) and systematically amplified contemplative dimensions: heightened curiosity (15.5 vs. 15.3), decentering (17.2 vs. 15.5), and overall mindful awareness (32.7 vs. 30.8). These theta-specific enhancements align with established associations between frontal midline theta and meditative states, whereas alpha-meditation relationships exhibit greater individual variability (Brandmeyer \u0026amp; Delorme, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Reggente et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eIndividual Differences and Precision Medicine\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe observed therapeutic efficacy of the interventions with equivalence between alpha and theta protocols could reflect response distributions wherein strong and weak responders populate each condition in approximately equal proportions. Such a potential motivates a reconceptualization of population-level, \u0026ldquo;one-size-fits-all\u0026rdquo; interventions toward personalized paradigms\u0026mdash;replacing random assignment with algorithmic stratification based on individual phenotypic markers encompassing both who participants fundamentally are (trait characteristics) and how they present at intervention onset (state variables). To elucidate potential biomarkers for such personalized protocol selection, we conducted comprehensive moderation analyses examining trait and state (including EEG measures) moderators of therapeutic response.\u003c/p\u003e\u003cp\u003eDespite theoretical expectations that dispositional characteristics\u0026mdash;particularly trait mindfulness, openness to experience, or beliefs around the role of personal agency in health outcomes\u0026mdash;might moderate receptivity to passive audiovisual stimulation, no trait variables demonstrated significant moderating effects. Similarly, pre-intervention neurophysiological profiles (EEG spectral power across frequency bands) failed to predict differential outcomes between protocols after correcting for multiple comparisons. However, state-dependent psychological variables revealed striking protocol-specific moderation patterns exclusively for existential outcomes. The relationship between intervention condition and Purpose in Life enhancement was significantly moderated by multiple baseline mood disturbance indicators\u0026mdash;POMS Total Mood Disturbance (pFDR\u0026thinsp;=\u0026thinsp;0.033), Anger (pFDR\u0026thinsp;=\u0026thinsp;0.019), Depression (pFDR\u0026thinsp;=\u0026thinsp;0.033), and Confusion (pFDR\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Participants presenting with elevated baseline psychological dysfunction demonstrated preferential PIL enhancement under theta stimulation, while those with lower baseline disturbance achieved comparable improvements across both protocols. Conversely, stress reduction outcomes exhibited no significant moderation despite alpha's numerically superior mean reduction (M = -3.72, SD\u0026thinsp;=\u0026thinsp;3.10) compared to theta (M = -1.73, SD\u0026thinsp;=\u0026thinsp;5.20), with initially promising predictors (flow states, anxiety assessments, negative affect) failing multiple comparison correction.\u003c/p\u003e\u003cp\u003e\u003cb\u003eImplications for High-Stress Operational Populations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThese findings hold particular relevance for operational contexts (e.g., military aviators managing G-forces and split-second decisions, special operations personnel sustaining hypervigilance in denied environments, first responders navigating cumulative trauma exposure) where traditional pharmacological stress interventions may induce states of compromised sobriety that prove incompatible with mission demands. Unlike meditation requiring sustained disciplined practice or psychotherapy spanning months, audiovisual stimulation offers immediate stress relief without extensive training. The technology's \"plug-and-play\" nature directly addresses Brandmeyer and Delorme's (2013) observation that Western populations struggle maintaining contemplative practices due to factors \"ranging from lack of time to general laziness.\"\u003c/p\u003e\u003cp\u003eFor military personnel experiencing allostatic load from prolonged deployment cycles, cultural barriers to help-seeking, and limited recovery opportunities, an 11-minute intervention producing effects comparable to weeks of traditional treatment represents a transformative possibility. The absence of stigma associated with technology-based interventions may facilitate adoption where traditional mental health services encounter resistance rooted in military culture's emphasis on stoicism and self-reliance.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTechnical constraints inherent to the consumer-grade Muse-S EEG and PPG system\u0026mdash;including substantial data loss, limited spatiotemporal resolution (7 sensors, 256 Hz), and potential electromagnetic interference from the reflective chamber\u0026mdash;fundamentally restricted neurophysiological assessment capacity. The current study acknowledged this limitation at the study design stage, weighing it against the increased ecological validity of leveraging devices that ship with MindGym. This methodological trade-off was deliberated during study conceptualization, ultimately prioritizing ecological validity by testing the biosensor technology commercially integrated with MindGym, given the platform's existing neurofeedback capabilities and anticipated future implementations wherein experience progression would be algorithmically modulated contingent upon successful entrainment verification using these same consumer-grade sensors. Regrettably, this constraint prevented us from addressing a critical gap in audiovisual stimulation research, where behavioral improvements are widely assumed to reflect neural entrainment despite scarce empirical verification of such mechanisms (Johnson et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe absence of control conditions precludes both mechanistic attribution and assessment of spontaneous fluctuations in outcome measures. While psychological states like burnout typically demonstrate temporal stability absent intervention (Maslach \u0026amp; Leiter, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), distinguishing specific therapeutic mechanisms from expectancy effects, environmental novelty, or simple rest remains impossible. This interpretive constraint extends to our null between-protocol differentiation, which admits dual interpretations: either shared therapeutic mechanisms transcending frequency-specific parameters, or heterogeneous individual responses masked by group-level aggregation.Our protocol design also introduces similar confounds\u0026mdash;primary outcomes spanning screening to post-intervention cannot exclude intervening life events, though immediate pre-state moderation analyses partially mitigate this concern by demonstrating that proximal psychological states predicted differential responsiveness. The single-session design eliminates durability assessment, while our stressed but non-clinical sample constrains generalizability.\u003c/p\u003e\u003cp\u003eNevertheless, robust moderation patterns transcend these methodological constraints. The finding that baseline psychological profiles predicted protocol-specific responses\u0026mdash;independent of trait characteristics, neurophysiology, or autonomic indices\u0026mdash;suggests phenotypic markers for intervention optimization beyond simple placebo effects. While requiring controlled replication, these differential patterns advance precision frameworks wherein momentary psychological states, rather than stable individual differences, guide neurostimulation selection.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFuture Directions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis successful pilot demonstrated feasibility, tolerability, and preliminary efficacy of audiovisual stimulation in a burnout-risk population without adverse events, establishing foundation for expanded investigation across multiple critical domains.\u003c/p\u003e\u003cp\u003eLongitudinal efficacy studies should prioritize durability assessment through controlled trials incorporating follow-up measurements at standardized intervals (1-week, 1-month, 3-month, 6-month) to determine whether acute effects persist or require maintenance dosing. An 8-week protocol analogous to Minduflness Based Stress Reduction would enable direct comparison with established interventions while incorporating waitlist controls to quantify spontaneous fluctuations and active controls (random multi-frequency stimulation) to isolate frequency-specific effects from expectancy and environmental factors inherent to MindGym, including awe-induction.\u003c/p\u003e\u003cp\u003ePrecision medicine optimization emerges as particularly promising given our moderation findings. Machine learning algorithms incorporating baseline psychological profiles, particularly mood disturbance indicators that predicted differential responsiveness, could enable algorithmic protocol assignment surpassing random allocation efficacy. Variables approaching but not achieving significance after correction warrant inclusion in multivariate prediction models, potentially revealing combinatorial phenotypes optimizing individual treatment matching.\u003c/p\u003e\u003cp\u003eMechanistic clarification requires research-grade neurophysiological assessment. Higher-density EEG arrays (e.g., 64-channels) with enhanced spatiotemporal resolution could detect entrainment signatures potentially mediating therapeutic effects would elucidate network-level changes underlying psychological improvements. Such investigations should examine whether behavioral benefits necessitate classical entrainment or emerge through alternative neuromodulatory pathways.\u003c/p\u003e\u003cp\u003eClinical translation demands systematic investigation across diagnostic populations (e.g., anxiety disorders, major depressive disorder, post traumatic stress disorder), dose-response characterization (session frequency, duration, total exposure), and comparative effectiveness trials against pharmacological and psychotherapeutic standards. Implementation research examining scalability through virtual reality platforms, mobile applications, and home-use devices could democratize access while maintaining therapeutic fidelity\u0026mdash;particularly crucial for operational populations requiring immediate, stigma-free interventions.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis pilot investigation demonstrated that single-session audiovisual stroboscopic stimulation within an immersive reflective chamber (MindGym) produced substantial anxiolytic and mood-enhancing effects comparable to pharmacological interventions requiring weeks of administration, without adverse events or training prerequisites. Despite absent neural entrainment signatures, both alpha and theta protocols yielded robust psychological improvements, though through potentially distinct pathways: alpha demonstrating universal stress reduction independent of baseline psychological state, while theta selectively enhanced existential purpose among individuals with elevated mood disturbance. These differential response patterns, wherein momentary psychological profiles rather than trait characteristics or neurophysiological markers predicted protocol-specific outcomes, advance precision neurostimulation frameworks beyond population-level applications toward algorithmic phenotype-guided selection. For operational populations experiencing chronic stress exposure and barriers to traditional interventions\u0026mdash;particularly military personnel confronting burnout, hypervigilance, and cultural stigma around help-seeking\u0026mdash;this accessible, rapidly-acting technology offers transformative potential for acute stress management. The convergence of substantial effect magnitudes, differential moderation patterns suggesting mechanistic specificity beyond placebo, and implementation feasibility positions audiovisual stimulation as a promising complement to existing therapeutics, warranting controlled longitudinal investigations to establish durability, optimize personalization algorithms, and elucidate whether therapeutic benefits necessitate classical entrainment or emerge through alternative neuromodulatory pathways transcending frequency-specific oscillatory coupling.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFunding Declarations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis investigation received financial support through a Small Business Innovation Research (SBIR) award from the Department of Defense: Air Force, granted to Lumena, Inc. (Denver, CO) in collaboration with the Institute for Advanced Consciousness Studies (IACS; 501(c)(3) nonprofit organization) serving as the associated research institution, with N.R. designated as principal investigator.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflicts of Interests\u003c/h2\u003e\n\u003cp\u003eFinancial support was provided via Research Services Agreement between IACS and Lumena, Inc., structured without outcome-dependent provisions or performance-based compensation mechanisms. Lumena, Inc. exercised no influence over experimental design or data analysis protocols, with their contribution limited to providing MindGym content libraries, technological infrastructure (hardware and software systems), and reflective chamber control programs developed according to experiential sequence specifications provided by N.R. to Lumena\u0026apos;s engineering team. Additionally, Lumena recorded audio instructions and experiential content as directed by the research team. The funding arrangement exclusively supported research operational expenses while maintaining complete investigative independence, with Lumena\u0026apos;s role confined to providing requisite technological tools and implementation resources without compromising scientific integrity or methodological autonomy. E.Y. was employed by Lumena, Inc. during data collection and processing but left prior to manuscript preparation, subsequently contributing to manuscript writing through an independent affiliation with IACS. E.Y. owns shares in Lumena, Inc. but had no role in study design or statistical analysis, providing only processed data through Lumena\u0026apos;s established pipeline.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eFinancial support was provided via Research Services Agreement between IACS and Lumena, Inc., structured without outcome-dependent provisions or performance-based compensation mechanisms. Lumena, Inc. exercised no influence over experimental design or data analysis protocols, with their contribution limited to providing MindGym content libraries, technological infrastructure (hardware and software systems), and reflective chamber control programs developed according to experiential sequence specifications provided by N.R. to Lumena\u0026apos;s engineering team. Additionally, Lumena recorded audio instructions and experiential content as directed by the research team. The funding arrangement exclusively supported research operational expenses while maintaining complete investigative independence, with Lumena\u0026apos;s role confined to providing requisite technological tools and implementation resources without compromising scientific integrity or methodological autonomy. E.Y. was employed by Lumena, Inc. during data collection and processing but left prior to manuscript preparation, subsequently contributing to manuscript writing through an independent affiliation with IACS. E.Y. owns shares in Lumena, Inc. but had no role in study design or statistical analysis, providing only processed data through Lumena\u0026apos;s established pipeline.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eStudy conceptualization and design: N.R. Study implementation and logistics: N.R., N.S., E.Y. Data collection: A.C., S.Z., T.D., N.S. Data analysis: A.C., S.Z., N.R. All authors contributed to manuscript writing and approved the final version for submission.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe extend gratitude to all research participants who enabled this investigation, and acknowledge the invaluable contributions of the Lumena, Inc. team, including Scott McCormick for developing the audiovisual programming architecture, Pamela Glick for managerial coordination, and Brandon Murphy and Stetson Jenkins for their collaborative support.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe behavioral questionnaire data, EEG data, and physiological data (heart rate and heart rate variability) that support the findings of this study are openly available on the Open Science Framework (OSF) at https://osf.io/3sjeu.Analysis code used to process the behavioral data and generate figures is available at https://github.com/akcone2003/P006_Code.The audiovisual stimulation protocols (alpha and theta conditions) utilized proprietary MindGym hardware and software systems developed by Lumena, Inc. While the general parameters of these protocols are described in detail in the Methods section, the specific control programs and LED sequences are proprietary to Lumena, Inc. and are not publicly available. Researchers interested in replicating these protocols using the MindGym platform should contact Lumena, Inc. directly.Raw consent forms and participant identification information are not publicly available to protect participant privacy and confidentiality in accordance with IRB approval (Advarra IRB Pro00079710) and HIPAA regulations. De-identified data are available as described above.Requests for additional information or materials should be directed to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArnsten, A. F. T. (2009). Stress signalling pathways that impair prefrontal cortex structure and function. 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(2021). seaborn: Statistical data visualization. \u003cem\u003eJournal of Open Source Software\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(60), 3021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.21105/joss.03021\u003c/span\u003e\u003cspan address=\"10.21105/joss.03021\" 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":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-digital-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjdigitalmed","sideBox":"Learn more about [npj Digital Medicine](http://www.nature.com/npjdigitalmed/)","snPcode":"41746","submissionUrl":"https://submission.springernature.com/new-submission/41746/3","title":"npj Digital Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7842751/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7842751/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eEscalating stress prevalence, particularly among essential service personnel whose cognitive compromise threatens public welfare, necessitates rapid, accessible, and non-pharmacological interventions. This pilot investigation (n\u0026thinsp;=\u0026thinsp;74) evaluated audiovisual stimulation delivered through an immersive reflective chamber (MindGym) as an acute stress mitigation strategy for high-burnout-risk populations. Participants underwent randomized assignment to alpha (9-11Hz) or theta (4-7Hz) frequency protocols combining synchronized binaural beats with stroboscopic light during an 11-minute active intervention. Both protocols demonstrated substantial therapeutic efficacy without adverse events. State anxiety reduction (STAI) achieved magnitudes comparable to established pharmacological and psychotherapeutic interventions requiring significantly longer treatment durations. Depression, tension, and negative affect showed similarly robust improvements, while flow states and subjective vitality were significantly enhanced. Moderation analyses revealed protocol-specific responsiveness patterns: alpha stimulation yielded universal stress reduction independent of baseline psychological state, whereas theta selectively enhanced purpose-in-life among participants with elevated mood disturbance, suggesting phenotype-guided optimization potential. These findings establish feasibility and preliminary efficacy for rapid stress management in operationally demanding contexts.\u003c/p\u003e","manuscriptTitle":"Alpha and Theta Audiovisual Interventions in a Reflective Chamber Demonstrate Acute Effects on Stress and Burnout","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-30 12:06:50","doi":"10.21203/rs.3.rs-7842751/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-04T01:07:35+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-02T21:34:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"314092454501914156129271649358401791400","date":"2025-11-12T04:02:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-11T10:02:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"83118938443839337875984021212325180890","date":"2025-10-27T08:13:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-16T14:20:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-16T14:15:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-16T04:27:04+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Digital Medicine","date":"2025-10-12T19:38:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-digital-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjdigitalmed","sideBox":"Learn more about [npj Digital Medicine](http://www.nature.com/npjdigitalmed/)","snPcode":"41746","submissionUrl":"https://submission.springernature.com/new-submission/41746/3","title":"npj Digital Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"7b447d92-1f5d-442e-95a6-f1056d80e69b","owner":[],"postedDate":"October 30th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":57013183,"name":"Health sciences/Health care"},{"id":57013184,"name":"Biological sciences/Neuroscience"},{"id":57013185,"name":"Biological sciences/Psychology"},{"id":57013186,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2026-03-30T16:18:08+00:00","versionOfRecord":{"articleIdentity":"rs-7842751","link":"https://doi.org/10.1038/s41746-026-02555-z","journal":{"identity":"npj-digital-medicine","isVorOnly":false,"title":"npj Digital Medicine"},"publishedOn":"2026-03-28 16:10:20","publishedOnDateReadable":"March 28th, 2026"},"versionCreatedAt":"2025-10-30 12:06:50","video":"","vorDoi":"10.1038/s41746-026-02555-z","vorDoiUrl":"https://doi.org/10.1038/s41746-026-02555-z","workflowStages":[]},"version":"v1","identity":"rs-7842751","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7842751","identity":"rs-7842751","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}