Hypnosis Enhances Prefrontal Performance, Negative Memories Management and Reduces Stress and Anxiety in Medical Students: A Network and Bayesian Psychophysiological Study

Hypnosis Enhances Prefrontal Performance, Negative Memories Management and Reduces Stress and Anxiety in Medical Students: A Network and Bayesian Psychophysiological Study | 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 Hypnosis Enhances Prefrontal Performance, Negative Memories Management and Reduces Stress and Anxiety in Medical Students: A Network and Bayesian Psychophysiological Study Queirolo Luca, Boscolo Annalisa, Cracco Tommaso, Moscardi Otello, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7115279/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Feb, 2026 Read the published version in Scientific Reports → Version 1 posted 11 You are reading this latest preprint version Abstract Background Stress and anxiety affect executive functions, work performance, and well-being, with negative impacts documented in medical doctors. However, the benefits of hypnosis remain under investigation. Hypothesis: This study aims to evaluate the impact of hypnosis on stress management in medical students, particularly in relation to negative academic experiences. Methods 26 volunteers, attending the last year of Medical School at the University of Padua, were enrolled ( Clinicaltrials.gov : NCT06778109). Evaluations of executive function, stress and anxiety through the Tower of London revised (TOL-R), Visual Analog Scale (VASs and VASa), and the Perceived Stress Scale (PSS-10) were conducted. Additionally, heart rate (HR), heart rate variability (HRV), electrodermal activity (EDA), skin conductance responses (SCR/min) and percentage of time in stress response (%) were recorded. Results TOL-R scores improved (p < 0.001), while stress and anxiety decreased (p < 0.001). Hypnosis affected EDA, SCR/min, and % (ANOVAs p < 0.001). HR decreased (p < 0.01) and HRV increased (p < 0.001) post-intervention. Bayesian analysis confirmed these findings (BF₁₀ = 184,738 for TOL-R; 23,017 for VASs; 35,952 for VASa). Network analysis identified EDA as the hub linking stress markers and cognitive performance Conclusions Based on the sample size evaluated our findings support hypnosis as an effective intervention for improving executive function, emotional regulation and stress response in medical students. Health sciences/Health care Biological sciences/Neuroscience Biological sciences/Psychology Social science/Psychology Executive function TOL hypnosis stress management HRV EDA medical students Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION Stress and anxiety are two related aspects of human beings able to affect performance, executive functions, emotional well-being, and overall quality of life ( 1 – 4 ). Medical doctors – especially those involved in invasive procedures, urgency and emergency care – often experience high levels of stress (probably due to an effort-reward imbalance), making them prone to anxiety, burnout, and impaired decision-making ( 5 – 8 ). Given their detrimental effects on psychophysical health, an increasing interest has developed in techniques able to modulate stress, anxiety and cognitive functioning ( 9 , 10 ). Among these techniques, hypnosis has emerged as a promising intervention ( 11 – 15 ). Hypnosis can facilitate changes in perception, cognition, and emotional states by altering the way to respond to stressors. Hypnosis modulates autonomic functions, including heart rate (HR), heart rate variability (HRV), electrodermal activity (EDA), and skin conductance responses (SCR/min), valid indicators of stress level and emotional regulation. HRV, a marker of parasympathetic nervous system activity ( 16 ), has been associated with greater resilience to stress and better cognitive flexibility, while EDA has gained attention as a valuable sympathetic index to investigate the flight or fight system and to predict perceived stress ( 17 ). The effects of hypnosis on stress and cognitive performance have been explored in several studies, but their mechanisms are not fully understood yet ( 18 , 19 ). Hypnosis may increase the parasympathetic activity and reduce the sympathetic response to stress, lowering physiological markers such as HR and blood pressure. Additionally, hypnosis may enhance cognitive processing by improving focus, attention, and memory recall, possibly enhancing prefrontal cortex processes like working memory, flexibility which are negatively affected by acute stress ( 20 – 24 ). Therefore, its potential to enhance cognitive performance, reduce stress and modulate negative memories could be particularly beneficial for high-pressure professionals, who need optimal cognitive functioning and stress regulation. The aim of this study was to evaluate the effects of hypnosis in medical students, whose limited professional experience make them more prone to stress when managing adverse events. Based on these assumptions, our hypothesis is that hypnosis, when appropriately administered, may improve: i) cognitive performance (evaluated using the revised Tower of London, TOL-R); ii) modulate stress and anxiety; iii) affect physiological parameters, such as HR, HRV and EDA. To check these potential benefits, our study enrolled medical students, and a stressful emergency situation was simulated by recalling a negative memory of their previous academic experience. Moreover, the application of multimodal statistical approaches (based on network analysis and Bayesian statistics) can provide strong evidence for supporting the hypothesis that hypnosis is an effective tool for enhancing prefrontal executive performance by reducing stress and anxiety. MATERIALS AND METHODS Participants 26 volunteers – 14 (54%) males and 12 (46%) females, mean age 25±2 years, – attending the last year of the Medical School at the University of Padua were prospectively enrolled between February 6 and April 1, 2025. The study was conducted in accordance with the principles of Good Clinical Practice outlined in the Declaration of Helsinki. Participants enrolled in the present study have signed informed consent prior to participation. Students with cardiovascular diseases, psychiatric disorders, ongoing medication that could affect heart rate, sweating, or stress responses and prior experience with hypnosis were excluded. This study was approved by the Ethical Committee of the Department of General Psychology, University of Padua (reference n. 3274/2019 on 05 November 2019, Chairwoman Professor A. Falco), registered on ClinicalTrial.gov (NCT06778109)), and written in accordance with the ‘Strengthening the reporting of observational studies in epidemiology’ reporting checklist ( see SDC1 ). Measures Cognitive performance, stress and anxiety were assessed with the following tests: i) the Revised Tower of London (TOL-R) a test allowing to evaluate the cognitive performance with its fronto-parietal components (25); ii) the Visual Analog Scale for Anxiety (VASa) (26); iii) the the Visual Analog Scale for Stress to assess subjective stress levels (27); iv) the Perceived Stress Scale (PSS)-10 to estimate the perceived stress level in the last month (28,29). The following physiological parameters were also recorded: i) electrodermal activity (EDA), skin conductance response (SCR/min), percent (%) of time spent in stress responses, in order to record the changes of electrical conduction in response to sympatho-cholinergic, stress-induced sweat secretions(30); ii) HR and heart rate variability (HRV). Specifically, EDA, an indicator of stress-related sympathetic activity, was recorded using the eSense Galvanometer (Mindfield Biofeedback); HR and HRV were recorded using the HRV Camera App on a smartphone, which provides non-invasive measurements detecting changes in blood flow by photoplethysmography through the camera lens. This method has been validated and shown to produce results comparable to traditional ECG-based measurements (31,32). Procedure Figure 1 shows the design of the study. All participants were submitted to HIP (Hypnotic Induction Profile)(33), PSS-10, VASa and VASs, TOL-R and measurement of physiological parameters (i.e., HR, HRV, EDA, SCR/min, %). Then, each participant was exposed to a stress induction (i.e., recalling a negative memory derived from past negative academic experience), followed by an 8 minutes session of hypnosis during which participants relived a previous pleasant experience, such as sunbathing at the beach, relaxing under trees etc, previously agreed upon with the hypnotherapist. A few minutes later, the negative memory was recalled once again to check possible differences in stress-response after the intervention. After each step the physiological parameters were recorded, while TOL-R, VASa and VASs were retested at the end of the experimental session. Statistical analysis and network analysis According to the a priori power analysis, a sample of 19 participants was initially estimated as appropriate to check a difference in executive function between pre and post intervention, with a power of 0.8, an expected effect size of 0.6 and a level of significance α= 0.05. After the enrollment of 26 volunteers, a post hoc power analysis confirmed our a priori analysis and showed that the enrollment of 26 volunteers was enough to detect the observed effect with a statistical power of 1.00 (Cohen’s d=1.33, α=0.05). Continuous data were presented as mean ± standard deviation (SD), when normally distributed, or as the median when non-normally distributed. The Shapiro-Wilk test was used to assess normality. Categorical data were summarized using absolute and relative frequencies. To compare paired data, the Paired T-test or Wilcoxon matched-pairs test was applied. Pearson’s or Spearman’s coefficient were calculated to evaluate associations between variables. The normality of residuals and homoscedasticity of variance (Levene’s test) were checked before fitting ANOVA models. A repeated measures ANOVA was used to determine any significant difference in terms of physiological data (i.e., EDA, HR, HRV etc, defined as dependent variable) across four different conditions (“baseline”, “stress induction”, “hypnosis,” “repeated stress induction”). For any violations of the parametric ANOVA assumptions, Friedman’s ANOVA was performed. Sphericity was evaluated with Mauchly’s test and corrected if necessary with Huynh-Feldt. Bonferroni correction was applied for post-hoc analysis. The acronym ΔTOL-R was used to indicate the difference between data recorded after and before intervention. A Bayesian analysis was conducted to identify if observed results, related to TOL-R, VAS anxiety and stress, EDA and other physiological parameters, were due to chance or a true effect. The Bayes Factor (BF 10 ), quantifies the probability of a true pattern (“hypnosis improves prefrontal functioning, reduces stress and anxiety while improving perceived wellbeing”) compared with the random assumption. We used Jeffreys’ scale to assess the strength of the BF 10 in support of one hypothesis over another. According to this scale (34), BF 10 1-3 is considered anecdotal evidence , a value of 3-10 moderate evidence , 10-30 and 30-100 strong and very strong evidence, respectively , and BF 10 > 100 extreme evidence . Finally, a two-step dimensionality reduction approach was employed to identify a parsimonious set of variables maximizing explainable variance in performance while preserving informative inter-variable relationships, reducing redundancy. Specifically, in the first step, variables were retained if they exhibited at least five moderate-to-strong significant correlations (r ≥ 0.4) with other variables in the dataset (using the appropriate correlation coefficients based on data distribution). This ensures that the selected variables are meaningfully embedded within the overall structure. Then, the Kaiser-Meyer-Olkin (KMO), measure of sampling adequacy, was applied to assess the suitability of the selected subset for multivariate analysis. Variables with individual measure of sampling adequacy for single variable (MSA) lower than 0.5 were excluded, overall all the selected variables must show at least an MSA>0.8. To construct the network, a stricter correlation threshold (r ≥ 0.5) was used to define edges in a weighted adjacency matrix serving as the basis for a spectral graph representation. Network topology was then evaluated using standard graph-theoretical metrics, including number of nodes and edges, average path length, network diameter, density, betweenness centrality, and closeness centrality. These measures were used to assess the integration and efficiency of information flow across physiological and cognitive domains. RESULTS At baseline, 4 out of 26 students (15.4%) reported ‘low stress’ (range 0-13 points PSS-10 scale), 19 (73%) showed ‘moderate stress’ (range 14-26 points), and 3 (11.5 %) high stress (>26 points). All volunteers showed a significant improvement of TOL-R after hypnosis (pre: 19.9±5.01 vs post: 24.3±3.58, p < 0.001; Figure 2A ), accompanied by a modulation of stress, as defined by VASs (pre: 4.83±2.78 vs post: 2.73±2.20, p < 0.001; Figure 2B ), and anxiety, defined by VASa (pre = 4.02±2.39 vs post = 2.31±2.05, p < 0.001; Figure 2C ; further data are reported on SDC 2 ). The Bayesian paired samples T-test confirmed a very strong evidence in favor of the alternative hypothesis (H1) – i.e., the use of hypnosis may facilitate better management of the negative memory both in terms of TOL-R improvements (BF₁₀= 184,738; error < 0.001), stress modulation (BF₁₀= 23 017; error < 0.001) and anxiety regulation (BF₁₀= 35,952; error < 0.001). With regards to physiological activity, Figure 3A shows electrodermal variability between different time-points (Friedman’s repeated measures ANOVA: X²= 22.3, df= 3, p < 0.001), with lower EDA values at rest and an increment of electrodermal activity during hypnosis (p, Bonferroni corrected < 0.001, as compared to baseline), during the second negative memory recalling (p, Bonferroni corrected < 0.001, as compared to baseline) and a significant difference between the first and the second stress induction (p, Bonferroni corrected <0.001) (additional data are reported in SDC 2 ). Considering SCR/min and % of time spent in stress responses, all significant differences are shown in Figure 3B-C (Friedman’s repeated measures ANOVA for SCR/min: X²= 23.9, df= 3, p < 0.001 for the % of time in stress responses, X² = 24, df = 3, p < 0.001). More specifically, SCR/min increased from baseline and from the first stress induction to hypnosis. It then decreased from hypnosis to the second negative recall and also decreased between the first and second stress induction (p < 0.001, Bonferroni corrected). Similarly, HR decreased between the first and the second stress induction, which was conducted after the hypnosis intervention (p= 0.007, Bonferroni corrected) ( Figure 4A ); while, evaluating HRV across different conditions (χ² = 14.1, df = 3, p = 0.0028), a significant increase of HRV was recorded between the first and the second negative recall (p < 0.001, Bonferroni corrected) ( Figure 4B ). Globally, the ANOVA repeated measure, after Mauchly’s test of sphericity, Huynh-Feldt correction, and Bonferroni correction, indicated a significant effect of condition on HR (F= 4.9, df= 3, SS= 427, p < 0.01). Bayesian Paired Sample T-Test comparing the two stress conditions showed: EDA BF₁₀= 29.5, error < 0.001, HR BF₁₀= 11, error < 0.001, SCR BF₁₀= 3.5 error < 0.001, HRV BF₁₀= 100, error 0.8 (effective KMO = 0.826), as shown in Figure 5 . After applying a 0.5 correlation threshold, the spectral matrix for network analysis was constructed, and a well-connected structure, based on 9 nodes and 33 edges, was revealed, forming a single connected component. Specifically, the network showed high efficiency, with an average path length of 1.31 and a diameter of 3. Moreover, the network displayed a moderate density (equal to 0.458), highlighting a robust association between physiological and cognitive performance. Three nodes, underlined in red, showed high betweenness centrality: EDA during stress induction (1.0), HR during hypnosis (0.741), and SCR/min during stress induction (0.714). Specifically, these three parameters are bridges/hubs playing a critical mediating role; while closeness centrality between HR during hypnosis and % of time in stress response during stress induction is 0.111, suggesting that these nodes are central in accessing the whole network quickly. HIP score ranges were 7±2.56, with all profiles (‘low’, ‘medium’, ‘high’) well represented, but the relationship between hypnotic ability and results was not significant (see SDC 3 ). DISCUSSION This study aimed to evaluate the impact of hypnosis on cognitive performance, stress, and anxiety in medical students, particularly in relation to the management of negative academic memories. Our results suggest that a single session of hypnosis in medical students naïve to hypnosis attending their last years of the medical school, was associated with significant improvements in executive function, and with reductions in both subjective and physical indices of stress and anxiety. The analysis showed the relevance of HRV, HR, EDA, SCR and % of time spent in stress responses as core hubs for performance under stress induction and hypnosis. Bayesian statistics and a robust network analysis, highlighted EDA during stress induction as the key biomarker connecting stress responses and cognitive performance. These findings align with the existing literature, which has consistently shown that high levels of stress and anxiety, negatively impact executive functioning and mental well-being (1–4,6–8,35,36). Chronic stress has been linked to cognitive impairment, emotional exhaustion, burnout and even suicidal ideation among physicians and trainees (2,5,7). Interventions range from mindfulness to cognitive-behavioral therapy (9,10,36) with meta-analyses suggesting modest benefits. Within this context, hypnosis has emerged as a promising but understudied tool. Previous studies and meta-analyses have reported on the efficacy of hypnosis in reducing anxiety and stress (12–14,37), and improving resilience and well-being among healthcare workers as well as autonomic nervous system equilibrium (18,38). Physiological correlates of stress – such as HR, HRV, EDA, and SCR – are well-established markers of autonomic nervous system activity and emotional regulation (17,17,39–44), but, to our knowledge, no studies have been published on their combined modulation by hypnosis. Executive Function Regarding Aim 1 , the intervention produced effects exceeeding the a-priori expectations. While the power analysis was based on an anticipated medium effect (Cohen’s d = 0.60), the observed effect reached d = 1.40. A Bayesian factor of 1.85 × 10⁵ provided decisive evidence for the treatment effect according to Jeffreys’ interpretative scale. Our TOL-R data, independently of HIP scores, are concordant with fMRI studies linking task performance to rostrolateral and dorsolateral PFC engagement (25,45), a fact suggesting that hypnosis may facilitate planning and working memory by modulating prefrontal circuits. In short, the absence of a negative predictive value for low hypnotizability in our study may be explained by the easy hypnotic task and its tailoring according to participant’s previous experience, that may improve individual executive functions within the limits of his/her hypnotic ability. This is also in line with the increasing evidence that appropriate hypnotic suggestions may improve working-memory capacity also in patients with acquired brain injury regardless of hypnotizability(46). In sum, our results (i) provide strong statistical evidence for a large treatment effect on executive function, (ii) question the view that such effects depend solely on hypnotizability, and (iii) support the effectiveness of individualized hypnosis in enhancing prefrontal executive processes, regardless of suggestibility. Anxiety, stress, wellbeing and Hypnotic profile Similar results were found for Aim 2 , i.e., the improvement of self-reported stress, anxiety (Bayes Factors > 20,000) and wellbeing – with 25 out of 26 participants reporting feeling better and one unchanged (χ²= 40.91, p < 0.001). These results are in line with previous studies and confirm the promising effects of hypnosis in medical students’ wellbeing and stress modulation (28). In addition, we explored whether hypnotizability would modulate the observed effects. Unlike other studies emphasizing the relevance of hypnotic ability (47–49), we unexpectedly found no correlation, contributing to the ongoing debate on hypnosis as a stable trait or an altered state of consciousness. In this regard, a dynamic interaction between trait and state seems to be more reasonable (50,51) where high hypnotizablility is relevant for the most difficult hypnotic tasks, like analgesia or gag reflex control (50). Accordingly, behavioral attempts to improve hynotizability have provided inconsistent results, while the neuromodulation of the left dorsolateral prefrontal cortex (L-DLPFC) by transcranial brain stimulation can transiently enhance hypnotizability by strengthening L-DLPFC–dACC (dorsal Anterior Cingulate Cortex) connectivity (52) . Overall, hypnotic responsiveness depends on several factors besides suggestibility, emphasizing the value of tailoring interventions according to subject’s experience and needs (19,51,53,54). Our personalized hypnosis, using individually crafted suggestions rather than standard scripts, was an easy task, probably feasible for most people, aligning interventions with the individual's inner world. On neuropsychological stand point, it may reflect the dynamic interaction between central executive, salience, and default mode networks (55). Further research should clarify the link between hypnotizability and outcome, since hypnotizability scales are based on the concept of suggestibility, a leitmotif in the history of hypnosis still remaining questionable over one century from its introduction (55,56). and 4) Physiological Indicators and Network Connectivity When Aim 3 is concerned , hypnosis did not prevent physiological arousal but promoted more efficient resource mobilization. We observed increased tonic EDA, decreased SCR (phasic component of sympathetic activity), and reduced time in stress response states, particularly during the second recall of negative academic memories, indicating an effective stress management. This pattern has already been demonstrated in previous research, where EDA and SCR showed opposite effects following hypnosis (57). In light of the results presented here, we suggest that SCR is crucial for initiating physiological mobilization responses (as indicated by closeness centrality in the network), whereas EDA, the tonic component, is essential for sustaining the utilization of these resources over the long term (as reflected by improvements in TOL-R scores). The initial decrease in parasympathetic activity during the first recall aligns with prior findings linking negative emotions to reduced parasympathetic tone (58), while higher parasympathetic activity correlates with lower rumination and anxiety, reflecting emotional regulation (59). Elevated HR after stress indicates residual anxiety as well (43,44). HR decreased and HRV increased, alongside EDA and SCR modulation after hypnosis, aligning with biopsychosocial models of arousal regulation (60–62). Furthermore, the significant negative correlation between ΔEDA and ΔTOL-R (r = –0.556, p = 0.03, df = 24) suggests that participants showing more controlled increases in EDA also exhibited the greatest cognitive improvements. This supports the notion that a better performance is driven by regulated resource mobilization rather than by arousal suppression, a fact in line with Bayesian models of energy allocation under cognitive load (63). The network analysis confirmed EDA during negative memory recall as a central node linking stress responses and executive function. Closeness centrality highlighted HR during hypnosis and SCR post-hypnosis as key connectors in emotional and cognitive regulation. Although HRV was excluded due to overlap with HR, combined HR, HRV, and EDA changes indicate improved autonomic regulation post-intervention. The position of EDA as a central node highlights the sympathetic system’s role as a core mechanism in adaptive stress management, providing a novel, actionable target for stress intervention. These findings align with stress physiology, indicating a shift from threat to challenge states (60). Strong Bayesian factors for HR, HRV and EDA before and after hypnosis further support that hypnosis may help reframe overwhelming situations as manageable challenges, possibly by enhancing neural efficiency (64). Limitations and Future Directions While promising, this study has some limitations. Neuroimaging (e.g., fMRI, EEG) could clarify neural mechanisms (65), particularly the involvement of the PFC, underlying hypnosis-related changes in the relationship between executive function and autonomic regulation. Another relevant limitation concerns the absence of an active control group. Without a comparison group undergoing a similarly structured but non-hypnotic intervention (e.g., relaxation or guided imagery), we cannot fully exclude the contribution of non-specific effects. Future studies should include active control conditions to better isolate the specific effects of hypnosis from general therapeutic or contextual factors. Replication in larger samples with active control groups and longitudinal designs is needed to assess the durability of effects on cognition and well-being. Additionally, exploring different hypnosis modalities, including self-hypnosis, could further define its potential for enhancing executive function, stress reduction, and resilience, supporting its integration into medical education and stress management programs. CONCLUSION In the clinical setting, increasingly dominated by concerns about burnout, cognitive fatigue, and emotional distress, this study offers a scientifically grounded, non-invasive, fast and promising intervention. Based on the sample size evaluated our findings suggest that a single personalized hypnosis session can enhance executive function, resilience, and reduce stress and anxiety in medical students, regardless of hypnotizability. EDA emerged as a key biomarker linking stress regulation with cognitive performance, supporting hypnosis as a scalable intervention for stress management. These results encourage further studies to better understand neural mechanisms and long-term effects, paving the way to integrate hypnosis into medical education and resilience training. Declarations Author contributions: All authors directly accessed and verified the underlying data reported in the manuscript and take full responsibility for its submission and content. All have approved the final version for publication and agree to be accountable for all aspects of the work, ensuring that any questions related to its accuracy or integrity are appropriately investigated and resolved. Substantial contributions to the conception or design of the work: LQ, AB Acquisition, analysis, or interpretation of data: LQ, AB, CT, MO, EF Drafting of the manuscript: LQ, AB, EF Critical revision for important intellectual content: LQ, AB, EF, GZ, ES, PN ° These authors equally contributed to the work. Data availability statement: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests: We declare no competing interests. Funding: 'Not applicable'. References Zhou, A. Y. et al. Factors Associated With Burnout and Stress in Trainee Physicians: A Systematic Review and Meta-analysis. JAMA Netw. Open. 3 agosto . 3 (8), e2013761 (2020). Dutheil, F. et al. Suicide among physicians and health-care workers: A systematic review and meta-analysis. PloS One . 14 (12), e0226361 (2019). Boscolo, A., Queirolo, L. & Navalesi, P. The impact of psychophysiological well being on executive functions among anaesthesia residents. Eur. J. Anaesthesiol. 1 aprile . 42 (4), 366–368 (2025). Queirolo, L. et al. Psychophysiological wellbeing in a class of dental students attending dental school: anxiety, burnout, post work executive performance and a 24 hours physiological investigation during a working day. Front. 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L. Is Mediation of Sweating Cholinergic, Adrenergic, or Both? A Comment on the Literature. Psychophysiology 24 (3), 312–319 (1987). Schuurmans, A. A. T. et al. Validity of the Empatica E4 Wristband to Measure Heart Rate Variability (HRV) Parameters: a Comparison to Electrocardiography (ECG). J. Med. Syst. 23 settembre . 44 (11), 190 (2020). Tarniceriu, A. et al. Detection of beat-to-beat intervals from wrist photoplethysmography in patients with sinus rhythm and atrial fibrillation after surgery. In: IEEE EMBS International Conference on Biomedical & Health Informatics (BHI). 2018. pp. 133–6. (2018). Alexander, J. E., Stimpson, K. H., Kittle, J. & Spiegel, D. The Hypnotic Induction Profile (HIP) in Clinical Practice and Research. Int. J. Clin. Exp. Hypn. marzo . 69 (1), 72–82 (2021). Jeffreys, H. Theory of Probability [Internet] (Oxford University Press, 1961). International series of monographs on physics https://books.google.it/books?id=tXp5AQAACAAJ Grech, M. The Effect of the Educational Environment on the rate of Burnout among Postgraduate Medical Trainees - A Narrative Literature Review. J. Med. Educ. Curric. Dev. dicembre . 8 , 23821205211018700 (2021). Bennett-Weston, A. et al. Interventions to promote medical student well-being: an overview of systematic reviews. BMJ Open. 9 maggio . 14 (5), e082910 (2024). Fernandez, A., Urwicz, L., Vuilleumier, P. & Berna, C. Impact of hypnosis on psychophysiological measures: A scoping literature review. Am. J. Clin. Hypn. agosto . 64 (1), 36–52 (2022). De Benedittis, G. Hypnotic Modulation of Autonomic Nervous System (ANS) Activity. Brain Sci. 4 marzo ; 14 (3). (2024). Beauchaine, T. P. & Thayer, J. F. Heart rate variability as a transdiagnostic biomarker of psychopathology. Int. J. Psychophysiol. Off J. Int. Organ. Psychophysiol. novembre . 98 (2 Pt 2), 338–350 (2015). Thayer, J. F. & Lane, R. D. A model of neurovisceral integration in emotion regulation and dysregulation. J. Affect. Disord dicembre . 61 (3), 201–216 (2000). Klimek, A., Mannheim, I., Schouten, G., Wouters, E. J. M. & Peeters, M. W. H. Wearables measuring electrodermal activity to assess perceived stress in care: a scoping review. Acta Neuropsychiatr 24 marzo . 37 , e19 (2023). Hickey, B. A. et al. Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review. Sensors. 16 maggio. ;21(10). (2021). Verkuil, B., Brosschot, J. F. & Thayer, J. F. Cardiac reactivity to and recovery from acute stress: temporal associations with implicit anxiety. Int. J. Psychophysiol. Off J. Int. Organ. Psychophysiol. maggio . 92 (2), 85–91 (2014). Pieper, S., Brosschot, J. F., van der Leeden, R. & Thayer, J. F. Prolonged cardiac effects of momentary assessed stressful events and worry episodes. Psychosom. Med. luglio . 72 (6), 570–577 (2010). Wagner, G., Koch, K., Reichenbach, J. R., Sauer, H. & Schlösser, R. G. M. The special involvement of the rostrolateral prefrontal cortex in planning abilities: an event-related fMRI study with the Tower of London paradigm. Neuropsychologia 44 (12), 2337–2347 (2006). Lindeløv, J. K., Overgaard, R. & Overgaard, M. Improving working memory performance in brain-injured patients using hypnotic suggestion. Brain J. Neurol. 1 aprile . 140 (4), 1100–1106 (2017). Raz, A., Shapiro, T., Fan, J. & Posner, M. I. Hypnotic suggestion and the modulation of Stroop interference. Arch. Gen. Psychiatry dicembre . 59 (12), 1155–1161 (2002). Landry, M., Lifshitz, M. & Raz, A. Brain correlates of hypnosis: A systematic review and meta-analytic exploration. Neurosci. Biobehav Rev. ottobre . 81 (Pt A), 75–98 (2017). Thompson, T. et al. The effectiveness of hypnosis for pain relief: A systematic review and meta-analysis of 85 controlled experimental trials. Neurosci. Biobehav Rev. aprile . 99 , 298–310 (2019). Facco, E. On the Hard Process of Understanding Hypnosis: Epistemological Issues in the Debate Between State, Trait, and Hypofrontality Theories Facco. In: The Routledge International Handbook of Clinical Hypnosis Facco, (eds Linden, J. H., De, B. G. & L I Sugarman) Routledge; 22–38. (2024). Pintar, J., Lynn, S. J. & Hypnosis A brief history. Hoboken, NJ, US: Wiley Blackwell; xiv, 221 p. (Hypnosis: A brief history.). (2008). Faerman, A. et al. Stanford Hypnosis Integrated with Functional Connectivity-targeted Transcranial Stimulation (SHIFT): a preregistered randomized controlled trial. Nat. Ment Health 1 gennaio . 2 (1), 96–103 (2024). Woody, E. Z. & Barnier, A. J. Hypnosis scales for the twenty-first century: What do we need and how should we use them? In: The Oxford handbook of hypnosis: Theory, research, and practice. New York, NY, US: Oxford University Press; 255–280. (2008). Facco, E. et al. Psychological Features of Hypnotizability: A First Step Towards Its Empirical Definition. Int. J. Clin. Exp. Hypn. 2 gennaio . 65 (1), 98–119 (2017). Facco, E. et al. Dissociative identity as a continuum from healthy mind to psychiatric disorders: Epistemological and neurophenomenological implications approached through hypnosis. Med. Hypotheses settembre . 130 , 109274 (2019). Facco, E. Hypnosis and Hypnotic ability between old beliefs and new evidences: An epistemological reflection. Am. J. Clin. Hypn. 15 ottobre . 64 (1), 20–35 (2021). Queirolo, L. et al. De-stress your physiological activation by compressing your imagination: a brief session of hypnosis decreases sympathetic stress response in moderately stressed dentists. Front. Psychol. [Internet] 2025;16-2025. Disponibile su: https://www.frontiersin.org/journals/psychology/articles/ 10.3389/fpsyg.2025.1577325 Weber, C. S. et al. Low vagal tone is associated with impaired post stress recovery of cardiovascular, endocrine, and immune markers. Eur. J. Appl. Physiol. maggio . 109 (2), 201–211 (2010). Williams, D. P. et al. Resting heart rate variability predicts self-reported difficulties in emotion regulation: a focus on different facets of emotion regulation. Front. Psychol. 6 , 261 (2015). Blascovich, J. Challenge, threat, and health. Handb. Motiv Sci. ;481–493. (2008). Blascovich, J. & Tomaka, J. The Biopsychosocial Model of Arousal Regulation. In: Zanna MP, curatore. Academic Press; pp. 1–51. (Advances in Experimental Social Psychology; vol. 28). Disponibile su: (1996). https://www.sciencedirect.com/science/article/pii/S006526010860235X Queirolo, L. et al. Effects of forest bathing (Shinrin-yoku) in stressed people. Front. Psychol. 15 , 1458418 (2024). Friston, K. The free-energy principle: a unified brain theory? Nat. Rev. Neurosci. febbraio . 11 (2), 127–138 (2010). Gruzelier, J. H. Frontal functions, connectivity and neural efficiency underpinning hypnosis and hypnotic susceptibility. Contemp. Hypn. 23 (1), 15–32 (2006). Alchihabi, A., Ekmekci, O., Kivilcim, B. B., Newman, S. D. & Yarman Vural, F. T. Analyzing Complex Problem Solving by Dynamic Brain Networks. Front. Neuroinformatics . 15 , 670052 (2021). Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7115279","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":493858792,"identity":"1971eb71-82b3-4d5a-bcb6-c6cce94ab427","order_by":0,"name":"Queirolo Luca","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5ElEQVRIiWNgGAWjYBACPhiDjYGB8QBDBZhhwJCARwsbMuMAwxmYFjx62JA5BxjbwLQBAz5r2CSSH35gKDssxyd9+MCBj/MO5/FJN29gePgDn5Y0YwmGc4eN2fjSEg7O3Ha4mE3mWAF+h0nkMEgwth1ObOPhMTjMuw3IkMgh4BeJHOYfQC31EC1ziNPCBrIlgQ2spYEYLTzPzCwSzqUbtvGwJRyccSw9sQ3olwMJabi18LMnP77xocxaXr6H+eCDDzXWifNnN298+MMGtxYwSECJHQlQnBIE6FpGwSgYBaNgFCADAABnSyobkKJ7AAAAAElFTkSuQmCC","orcid":"","institution":"University of Padua","correspondingAuthor":true,"prefix":"","firstName":"Queirolo","middleName":"","lastName":"Luca","suffix":""},{"id":493858793,"identity":"672d6dbd-9384-495f-b91b-6b1645893644","order_by":1,"name":"Boscolo Annalisa","email":"","orcid":"","institution":"Padova University Hospital","correspondingAuthor":false,"prefix":"","firstName":"Boscolo","middleName":"","lastName":"Annalisa","suffix":""},{"id":493858794,"identity":"860c62f9-6ee5-4ac4-a2a4-5e325849d219","order_by":2,"name":"Cracco Tommaso","email":"","orcid":"","institution":"University of Padua","correspondingAuthor":false,"prefix":"","firstName":"Cracco","middleName":"","lastName":"Tommaso","suffix":""},{"id":493858795,"identity":"d6640120-5ca2-4889-ad84-b0b8730b55c2","order_by":3,"name":"Moscardi Otello","email":"","orcid":"","institution":"University of Padua","correspondingAuthor":false,"prefix":"","firstName":"Moscardi","middleName":"","lastName":"Otello","suffix":""},{"id":493858796,"identity":"e9577c48-667b-492d-8ffe-f80b63538321","order_by":4,"name":"Facco Enrico","email":"","orcid":"","institution":"University of Padua","correspondingAuthor":false,"prefix":"","firstName":"Facco","middleName":"","lastName":"Enrico","suffix":""},{"id":493858797,"identity":"998323c8-ef24-4114-b145-9c1310c08c19","order_by":5,"name":"Zanette Gastone","email":"","orcid":"","institution":"University of Padua","correspondingAuthor":false,"prefix":"","firstName":"Zanette","middleName":"","lastName":"Gastone","suffix":""},{"id":493858798,"identity":"d3e5b31b-b0d6-4d4c-b1e5-5a2b8d1f9068","order_by":6,"name":"Stellini Edoardo","email":"","orcid":"","institution":"University of Padua","correspondingAuthor":false,"prefix":"","firstName":"Stellini","middleName":"","lastName":"Edoardo","suffix":""},{"id":493858799,"identity":"ff5e0fae-0eec-4690-a235-b805fde03a19","order_by":7,"name":"Navalesi Paolo","email":"","orcid":"","institution":"University of Padua","correspondingAuthor":false,"prefix":"","firstName":"Navalesi","middleName":"","lastName":"Paolo","suffix":""}],"badges":[],"createdAt":"2025-07-13 20:08:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7115279/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7115279/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-026-40770-6","type":"published","date":"2026-02-26T15:59:39+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88103916,"identity":"38dbff1a-9684-4f36-9fde-3da851e0c69f","added_by":"auto","created_at":"2025-08-01 12:04:28","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":175089,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flow-chart. | BioRender\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations: \u003c/em\u003eTOL-R, Tower of London-Revised; VASa, Visual Analog Scale for Anxiety; VAs, Visual Analog Scale for Stress; EDA, Electrodermal Activity; SCR, skin conductance response; min, minute; HR, Heart Rate; HRV, Heart Rate Variability; PSS-10, Perceived Stress Scale- 10 Item Version. Created in BioRender. Science Suite Inc. dba BioRender (\"BioRender\") has granted CC BY open access license permission to use this Completed Graphic in accordance with BioRender's Terms of Service and Academic License Terms (\"License Terms\").\u003c/p\u003e\n\u003cp\u003eQueirolo, L. (2025)\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7115279/v1/467d5148dae148a89b9534e7.jpg"},{"id":88103918,"identity":"75705c3d-16ec-45fd-be67-87d7548374e7","added_by":"auto","created_at":"2025-08-01 12:04:28","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":64679,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCognitive performance, stress and anxiety before and after hypnosis.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. TOL-R; \u003cstrong\u003eB. \u003c/strong\u003eVAS \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;for stress (VASs); \u003cstrong\u003eC. \u003c/strong\u003eVAS for \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;anxiety (VASa).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations: \u003c/em\u003eTOL-R,Tower of London-Revised; VASa, Visual Analog Scale for Anxiety;VASs, Visual Analog Scale for Stress; *: p-value \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7115279/v1/b8d409ed4f8f67e8e2f4efd6.jpg"},{"id":88103915,"identity":"0b113b38-97e0-46f5-ab12-0411fd795295","added_by":"auto","created_at":"2025-08-01 12:04:28","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":87621,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhysiological parameters at different time-points.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. EDA; \u003cstrong\u003eB. \u003c/strong\u003eSCR/min;\u003cstrong\u003e C. \u003c/strong\u003e% of time spent in stress \u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;\u0026nbsp;response.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations:\u003c/em\u003e \u003cem\u003eμS \u003c/em\u003e, microsiemens;\u003cem\u003e \u003c/em\u003eEDA, Electrodermal Activity; SCR, skin conductance response; %, percent; min, minute.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7115279/v1/0fb07b78304aa2e8159f0a34.jpg"},{"id":88105113,"identity":"28baf6c9-87cd-4ea4-af01-f96861318570","added_by":"auto","created_at":"2025-08-01 12:20:28","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":49086,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional physiological parameters at different time-points.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA. HR per minute; \u003cstrong\u003eB. \u003c/strong\u003eHRV.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations: \u003c/em\u003eHR, Heart Rate; HRV, Heart Rate Variability; min, minute.\u003c/p\u003e","description":"","filename":"Picture4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7115279/v1/b122c875f587615822c874cf.jpg"},{"id":88103921,"identity":"9177de58-e2a0-404d-afb8-b8a2b74b01b1","added_by":"auto","created_at":"2025-08-01 12:04:28","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":86258,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eNetwork physiology of performance.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNetwork analysis across four time-points: at baseline, during stress induction (recalling negative memory), during hypnosis, and during the second stress induction (recalling for the second time the same negative memory). The following variables were included: HR at baseline, during stress induction, during hypnosis and during the second (2) stress induction; SCR/min at baseline; percent: %SCR/min at baseline and during stress indcution; EDA during stress induction; and ΔTOL-R, defined as the difference between TOL-R after hypnosis and before hypnosis. Specifically, three red nodes, which are ‘EDA during stress induction’, ‘%SCR/min during stress induction’ and ‘HR during hypnosis’, show high betweenness centrality. EDA at stress induction acts as a hub linking physiological activity to performance improvements (ΔTOL-R). The %SCR/min during stress induction and HR during hypnosis facilitate integration across different time-points, enabling efficient access to system-wide resources.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations: \u003c/em\u003eTOL-R, Tower of London-Revised; EDA, Electrodermal Activity; HR, Heart Rate; %SCR/min, percentage of skin conductance responses per minute, SCR/min number of Skin Conductance Responses per minute.\u003c/p\u003e","description":"","filename":"Picture5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7115279/v1/74fee947690b3ab5fc45d2da.jpg"},{"id":103765750,"identity":"fc0db45c-29ff-4839-9965-226dfe291439","added_by":"auto","created_at":"2026-03-02 16:08:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1339628,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7115279/v1/0117ab24-24d7-4157-9f9c-2320f37829c8.pdf"},{"id":88104860,"identity":"414756d7-48b2-4088-b179-6d7864e01124","added_by":"auto","created_at":"2025-08-01 12:12:28","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":25943,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarydigitalcontent.docx","url":"https://assets-eu.researchsquare.com/files/rs-7115279/v1/4ae74606069e57ac5618bb1c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Hypnosis Enhances Prefrontal Performance, Negative Memories Management and Reduces Stress and Anxiety in Medical Students: A Network and Bayesian Psychophysiological Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eStress and anxiety are two related aspects of human beings able to affect performance, executive functions, emotional well-being, and overall quality of life (\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Medical doctors \u0026ndash; especially those involved in invasive procedures, urgency and emergency care \u0026ndash; often experience high levels of stress (probably due to an effort-reward imbalance), making them prone to anxiety, burnout, and impaired decision-making (\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Given their detrimental effects on psychophysical health, an increasing interest has developed in techniques able to modulate stress, anxiety and cognitive functioning (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Among these techniques, hypnosis has emerged as a promising intervention (\u003cspan additionalcitationids=\"CR12 CR13 CR14\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHypnosis can facilitate changes in perception, cognition, and emotional states by altering the way to respond to stressors. Hypnosis modulates autonomic functions, including heart rate (HR), heart rate variability (HRV), electrodermal activity (EDA), and skin conductance responses (SCR/min), valid indicators of stress level and emotional regulation. HRV, a marker of parasympathetic nervous system activity (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), has been associated with greater resilience to stress and better cognitive flexibility, while EDA has gained attention as a valuable sympathetic index to investigate the flight or fight system and to predict perceived stress (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe effects of hypnosis on stress and cognitive performance have been explored in several studies, but their mechanisms are not fully understood yet (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Hypnosis may increase the parasympathetic activity and reduce the sympathetic response to stress, lowering physiological markers such as HR and blood pressure. Additionally, hypnosis may enhance cognitive processing by improving focus, attention, and memory recall, possibly enhancing prefrontal cortex processes like working memory, flexibility which are negatively affected by acute stress (\u003cspan additionalcitationids=\"CR21 CR22 CR23\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTherefore, its potential to enhance cognitive performance, reduce stress and modulate negative memories could be particularly beneficial for high-pressure professionals, who need optimal cognitive functioning and stress regulation. The aim of this study was to evaluate the effects of hypnosis in medical students, whose limited professional experience make them more prone to stress when managing adverse events.\u003c/p\u003e\u003cp\u003eBased on these assumptions, our hypothesis is that hypnosis, when appropriately administered, may improve: i) cognitive performance (evaluated using the revised Tower of London, TOL-R); ii) modulate stress and anxiety; iii) affect physiological parameters, such as HR, HRV and EDA. To check these potential benefits, our study enrolled medical students, and a stressful emergency situation was simulated by recalling a negative memory of their previous academic experience. Moreover, the application of multimodal statistical approaches (based on network analysis and Bayesian statistics) can provide strong evidence for supporting the hypothesis that hypnosis is an effective tool for enhancing prefrontal executive performance by reducing stress and anxiety.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e26 volunteers \u0026ndash; 14 (54%) males and 12 (46%) females, mean age 25\u0026plusmn;2 years, \u0026ndash; attending the last year of the Medical School at the University of Padua were prospectively enrolled between \u0026nbsp;February 6 and \u0026nbsp;April 1, 2025. The study was conducted in accordance with the principles of Good Clinical Practice outlined in the Declaration of Helsinki. Participants enrolled in the present study have signed informed consent prior to participation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStudents with cardiovascular diseases, psychiatric disorders, ongoing medication that could affect heart rate, sweating, or stress responses and prior experience with hypnosis were excluded.\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethical Committee of the Department of General Psychology, University of Padua (reference n. 3274/2019 on 05 November 2019, Chairwoman Professor A. Falco), registered on ClinicalTrial.gov (NCT06778109)), and written in accordance with the \u0026lsquo;Strengthening the reporting of observational studies in epidemiology\u0026rsquo; reporting checklist (\u003cstrong\u003esee\u003c/strong\u003e \u003cstrong\u003e\u003cem\u003eSDC1\u003c/em\u003e\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCognitive performance, stress and anxiety were assessed with the following tests: i) the Revised Tower of London (TOL-R) a test allowing to evaluate the cognitive performance with its fronto-parietal components (25); ii) the Visual Analog Scale for Anxiety (VASa) (26); iii) \u0026nbsp;the the Visual Analog Scale for Stress to assess subjective stress levels (27); iv) the Perceived Stress Scale (PSS)-10 to estimate the perceived stress level in the last month (28,29).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe following physiological parameters were also recorded: i) electrodermal activity (EDA), skin conductance response (SCR/min), percent (%) of time spent in stress responses, in order to record the changes \u0026nbsp;of electrical conduction in response to sympatho-cholinergic, stress-induced sweat secretions(30); ii) HR and \u0026nbsp;heart rate variability (HRV). Specifically, EDA, an indicator of stress-related sympathetic activity, was recorded using the eSense Galvanometer (Mindfield Biofeedback); HR and HRV were recorded using the HRV Camera App on a smartphone, which provides non-invasive measurements detecting changes in blood flow by photoplethysmography through the camera lens. This method has been validated and shown to produce results comparable to traditional ECG-based measurements (31,32).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFigure 1\u003c/em\u003e\u003c/strong\u003e shows the design of the study. All participants were submitted to HIP (Hypnotic Induction Profile)(33), PSS-10, VASa and VASs, TOL-R and measurement of physiological parameters (i.e., HR, HRV, EDA, SCR/min, %). Then, each participant was exposed to a stress induction (i.e., recalling a negative memory derived from past negative academic experience), followed by an 8 minutes session of hypnosis during which participants relived a previous pleasant experience, such as \u0026nbsp;sunbathing at the beach, relaxing under trees etc, previously agreed upon with the hypnotherapist. A few minutes later, the negative memory was recalled once again to check possible differences in stress-response after the intervention. After each step the physiological parameters were recorded, while \u0026nbsp;TOL-R, VASa and VASs were \u0026nbsp;retested at the end of the experimental session.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis and network analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the a priori power analysis, a sample of 19 participants was initially estimated as appropriate to check a difference in executive function between pre and post intervention, with a power of 0.8, an expected effect size of 0.6 and a level of significance \u0026alpha;= 0.05.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAfter the enrollment of 26 volunteers, a post hoc power analysis confirmed our a priori analysis and showed that the enrollment of 26 volunteers was enough to detect the observed effect \u0026nbsp; with a statistical power of 1.00 (Cohen\u0026rsquo;s d=1.33, \u0026alpha;=0.05).\u003c/p\u003e\n\u003cp\u003eContinuous data were presented as mean \u0026plusmn; standard deviation (SD), when normally distributed, or as the median when non-normally distributed. The Shapiro-Wilk test was used to assess normality. Categorical data were summarized using absolute and relative frequencies. To compare paired data, the Paired T-test or Wilcoxon matched-pairs test was applied. Pearson\u0026rsquo;s or Spearman\u0026rsquo;s coefficient were calculated to evaluate associations between variables. The normality of residuals and homoscedasticity of variance (Levene\u0026rsquo;s test) were checked before fitting ANOVA models. A repeated measures ANOVA was used to determine any significant difference in terms of physiological data (i.e., EDA, HR, HRV etc, defined as dependent variable) across four different conditions (\u0026ldquo;baseline\u0026rdquo;, \u0026ldquo;stress induction\u0026rdquo;, \u0026ldquo;hypnosis,\u0026rdquo; \u0026ldquo;repeated stress induction\u0026rdquo;). For any violations of the parametric ANOVA assumptions, Friedman\u0026rsquo;s ANOVA was performed. Sphericity was evaluated with Mauchly\u0026rsquo;s test and corrected if necessary with Huynh-Feldt. Bonferroni correction was applied for post-hoc analysis. The acronym \u0026Delta;TOL-R was used to indicate the difference between data recorded after and before intervention.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA Bayesian analysis was conducted to identify if observed results, related to TOL-R, VAS anxiety and stress, EDA and other physiological parameters, \u0026nbsp;were due to chance or a true effect. The Bayes Factor (BF\u003csub\u003e10\u003c/sub\u003e), quantifies the probability of a true pattern (\u0026ldquo;hypnosis improves prefrontal functioning, reduces stress and anxiety while improving perceived wellbeing\u0026rdquo;) compared with the random assumption. We used Jeffreys\u0026rsquo; scale to assess the strength of the BF\u003csub\u003e10\u003c/sub\u003e in support of one hypothesis over another. According to this scale (34), \u0026nbsp;BF\u003csub\u003e10\u003c/sub\u003e 1-3 is considered \u003cem\u003eanecdotal evidence\u003c/em\u003e, a value of 3-10 \u003cem\u003emoderate evidence\u003c/em\u003e, 10-30 and 30-100 \u003cem\u003estrong and very strong evidence, respectively\u003c/em\u003e, and BF\u003csub\u003e10\u0026nbsp;\u003c/sub\u003e\u0026gt; 100 \u003cem\u003eextreme evidence\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinally, a two-step dimensionality reduction approach was employed to identify a parsimonious set of variables maximizing explainable variance in performance while preserving informative inter-variable relationships, reducing redundancy. Specifically, in the first step, variables were retained if they exhibited at least five moderate-to-strong significant correlations (r \u0026ge; 0.4) with other variables in the dataset (using the appropriate correlation coefficients based on data distribution). This ensures that the selected variables are meaningfully embedded within the overall structure. Then, the Kaiser-Meyer-Olkin (KMO), measure of sampling adequacy, was applied to assess the suitability of the selected subset for multivariate analysis. Variables with individual measure of sampling adequacy for single variable (MSA) lower than 0.5 were excluded, overall all the selected variables must show at least an MSA\u0026gt;0.8. To construct the network, a stricter correlation threshold (r \u0026ge; 0.5) was \u0026nbsp;used to define edges in a weighted adjacency matrix serving as the basis for a spectral graph representation. Network topology was then evaluated using standard graph-theoretical metrics, including number of nodes and edges, average path length, network diameter, density, betweenness centrality, and closeness centrality. These measures were used to assess the integration and efficiency of information flow across physiological and cognitive domains.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eAt baseline, 4 out of 26 \u0026nbsp;students (15.4%) reported \u0026lsquo;low stress\u0026rsquo; (range 0-13 points PSS-10 scale), 19 (73%) showed \u0026lsquo;moderate stress\u0026rsquo; (range 14-26 points), and 3 (11.5 %) high stress (\u0026gt;26 points). All volunteers showed a significant improvement of TOL-R after hypnosis (pre: 19.9\u0026plusmn;5.01 vs post: 24.3\u0026plusmn;3.58, p \u0026lt; 0.001; \u003cstrong\u003e\u003cem\u003eFigure 2A\u003c/em\u003e\u003c/strong\u003e), accompanied by a modulation of stress, as defined by VASs (pre: 4.83\u0026plusmn;2.78 vs post: 2.73\u0026plusmn;2.20, p \u0026lt; 0.001; \u003cstrong\u003e\u003cem\u003eFigure 2B\u003c/em\u003e\u003c/strong\u003e), and anxiety, defined by VASa (pre \u0026nbsp;= 4.02\u0026plusmn;2.39 vs post = 2.31\u0026plusmn;2.05, p \u0026lt; 0.001; \u003cstrong\u003e\u003cem\u003eFigure 2C\u003c/em\u003e\u003c/strong\u003e; further data are reported on\u003cstrong\u003e\u003cem\u003e\u0026nbsp;SDC 2\u003c/em\u003e\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Bayesian paired samples T-test confirmed a very strong evidence in favor of the alternative hypothesis (H1) \u0026nbsp;\u0026ndash; i.e., the use of hypnosis may facilitate better management of the negative memory both in terms of TOL-R improvements (BF₁₀= 184,738; error \u0026lt; 0.001), stress modulation (BF₁₀= 23 017; error \u0026lt; 0.001) and anxiety regulation (BF₁₀= 35,952; error \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003eWith regards to physiological activity, \u003cstrong\u003e\u003cem\u003eFigure 3A\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eshows electrodermal variability between different time-points (Friedman\u0026rsquo;s repeated measures ANOVA: X\u0026sup2;= 22.3, df= \u0026nbsp;3, p \u0026lt; 0.001), with lower EDA values at rest and an increment of electrodermal activity during hypnosis (p, Bonferroni corrected \u0026lt; 0.001, as compared to baseline), during the second negative memory recalling (p, Bonferroni corrected \u0026nbsp;\u0026lt; 0.001, as compared to baseline) and a significant difference between the first and the second stress induction (p, Bonferroni corrected \u0026lt;0.001) (additional data are reported in \u003cstrong\u003e\u003cem\u003eSDC 2\u003c/em\u003e\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsidering SCR/min and % of time spent in stress responses, all significant differences are shown in \u003cstrong\u003e\u003cem\u003eFigure 3B-C\u003c/em\u003e\u003c/strong\u003e (Friedman\u0026rsquo;s repeated measures ANOVA for SCR/min: X\u0026sup2;= 23.9, df= 3, p \u0026lt; 0.001 for the % of time in stress responses, X\u0026sup2; = 24, df = 3, p \u0026lt; 0.001). More specifically, SCR/min increased from baseline and from the first stress induction to hypnosis. It then decreased from hypnosis to the second negative recall and also decreased between the first and second stress induction (p \u0026lt; 0.001, Bonferroni corrected).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSimilarly, HR decreased between the first and the second stress induction, which was conducted after the hypnosis intervention (p= 0.007, Bonferroni corrected) (\u003cstrong\u003e\u003cem\u003eFigure 4A\u003c/em\u003e\u003c/strong\u003e); while, evaluating HRV across different conditions (\u0026chi;\u0026sup2; = 14.1, df = 3, p = 0.0028), a significant increase of HRV was recorded between the first and the second negative recall (p \u0026lt; 0.001, Bonferroni corrected) (\u003cstrong\u003e\u003cem\u003eFigure 4B\u003c/em\u003e\u003c/strong\u003e). Globally, the ANOVA repeated measure, after Mauchly\u0026rsquo;s test of sphericity, Huynh-Feldt correction, and Bonferroni correction, indicated a significant effect of condition on HR (F= 4.9, df= 3, SS= 427, p \u0026lt; 0.01). Bayesian Paired Sample T-Test \u0026nbsp;comparing the two stress conditions showed: EDA BF₁₀= 29.5, error \u0026lt; 0.001, HR BF₁₀= 11, error \u0026lt; 0.001, SCR BF₁₀= 3.5 error \u0026lt; 0.001, HRV BF₁₀= 100, error \u0026lt; 0.001.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;For network analysis, nine variables met criteria of having at least five moderate-to-strong correlations with other parameters and a KMO Measure of Sampling Adequacy \u0026gt; 0.8 (effective KMO = 0.826), as shown in \u003cstrong\u003eFigure 5\u003c/strong\u003e. After applying a 0.5 correlation threshold, the spectral matrix for network analysis was constructed, and a well-connected structure, based on 9 nodes and 33 edges, was revealed, forming a single connected component. Specifically, the network showed high efficiency, with an average path length of 1.31 and a diameter of 3. Moreover, the network displayed a moderate density (equal to 0.458), highlighting a robust association between physiological and cognitive performance. Three nodes, underlined in red, showed high betweenness centrality: EDA during stress induction (1.0), HR during hypnosis (0.741), and SCR/min during stress induction (0.714).\u003c/p\u003e\n\u003cp\u003eSpecifically, these three parameters are bridges/hubs playing a critical mediating role; while closeness centrality between HR during hypnosis and % of time in stress response during stress induction is 0.111, suggesting that these nodes are central in accessing the whole network quickly.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHIP score ranges were \u0026nbsp;7\u0026plusmn;2.56, with all profiles (\u0026lsquo;low\u0026rsquo;, \u0026lsquo;medium\u0026rsquo;, \u0026lsquo;high\u0026rsquo;) well represented, but the relationship between hypnotic ability and results was not significant (see \u003cstrong\u003e\u003cem\u003eSDC 3\u003c/em\u003e\u003c/strong\u003e).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study aimed to evaluate the impact of hypnosis on cognitive performance, stress, and anxiety in medical students, particularly in relation to the management of negative academic memories. Our results suggest that a single session of hypnosis in medical students na\u0026iuml;ve to hypnosis attending their last years of the medical school, was associated with significant improvements in executive function, and with reductions in both subjective and physical indices of stress and anxiety. The analysis \u0026nbsp;showed \u0026nbsp;the relevance of HRV, HR, EDA, SCR and % of time spent in stress responses as core hubs for performance under stress induction and hypnosis. \u0026nbsp;Bayesian statistics and a robust network analysis, highlighted EDA during stress induction as the key biomarker connecting stress responses and cognitive performance.\u003c/p\u003e\n\u003cp\u003eThese findings align with the existing literature, which has consistently shown that high levels of stress and anxiety, negatively impact executive functioning and mental well-being (1\u0026ndash;4,6\u0026ndash;8,35,36). Chronic stress has been linked to cognitive impairment, emotional exhaustion, burnout and even suicidal ideation among physicians and trainees (2,5,7). Interventions range from mindfulness to cognitive-behavioral therapy (9,10,36) with meta-analyses suggesting modest benefits. Within this context, hypnosis has emerged as a promising but understudied tool. Previous studies and meta-analyses have reported on the efficacy of hypnosis in reducing anxiety and stress (12\u0026ndash;14,37), and improving resilience and well-being among healthcare workers as well as autonomic nervous system equilibrium (18,38). Physiological correlates of stress \u0026ndash; such as HR, HRV, EDA, and SCR \u0026ndash; are well-established markers of autonomic nervous system activity and emotional regulation (17,17,39\u0026ndash;44), but, to our knowledge, no studies have been published on their combined modulation by hypnosis.\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003e\u003cstrong\u003eExecutive Function\u0026nbsp;\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eRegarding \u003cstrong\u003eAim 1\u003c/strong\u003e, the intervention produced effects exceeeding the a-priori expectations. While the power analysis was based on an anticipated medium effect (Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e = 0.60), the observed effect reached \u003cem\u003ed\u003c/em\u003e = 1.40. A Bayesian factor of 1.85 \u0026times; 10⁵ provided decisive evidence for the treatment effect according to Jeffreys\u0026rsquo; interpretative scale.\u003c/p\u003e\n\u003cp\u003eOur TOL-R data, independently of HIP scores, are concordant with fMRI studies linking task performance to rostrolateral and dorsolateral PFC engagement (25,45), a fact suggesting that hypnosis may facilitate planning and working memory by modulating prefrontal circuits.\u003c/p\u003e\n\u003cp\u003eIn short, the absence of a negative predictive value for low hypnotizability in our study may be explained by the easy hypnotic task and its tailoring according to participant\u0026rsquo;s previous experience, that may improve individual executive functions within the limits of his/her hypnotic ability. \u0026nbsp;This is also in line with the increasing evidence \u0026nbsp;that appropriate hypnotic suggestions may improve working-memory capacity also in patients with acquired brain injury regardless of hypnotizability(46).\u003c/p\u003e\n\u003cp\u003eIn sum, our results (i) provide strong statistical evidence for a large treatment effect on executive function, (ii) question the view that such effects depend solely on hypnotizability, and (iii) support the effectiveness of individualized hypnosis in enhancing prefrontal executive processes, regardless of suggestibility.\u003c/p\u003e\n\u003col start=\"2\"\u003e\n \u003cli\u003e\u003cstrong\u003eAnxiety,\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003estress, wellbeing and Hypnotic\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eprofile\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eSimilar results were found for \u003cstrong\u003eAim 2\u003c/strong\u003e, i.e., \u0026nbsp;the improvement of self-reported stress, anxiety (Bayes Factors \u0026gt; 20,000) and wellbeing \u0026ndash; with 25 out of 26 participants reporting feeling better and one unchanged (\u0026chi;\u0026sup2;= 40.91, p \u0026lt; 0.001). These results are in line with previous studies and confirm the promising effects of hypnosis in medical students\u0026rsquo; wellbeing \u0026nbsp;and stress modulation (28).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition, we explored whether hypnotizability would modulate the observed effects. Unlike other studies emphasizing the relevance of hypnotic ability\u0026nbsp;(47\u0026ndash;49), we unexpectedly found no correlation, contributing to the ongoing debate on hypnosis as a stable trait or an altered state of consciousness. In this regard, a dynamic interaction between trait and state seems to be more reasonable (50,51)\u0026nbsp;where high hypnotizablility is relevant for the most difficult hypnotic tasks, like analgesia or gag reflex control\u0026nbsp;(50). Accordingly, behavioral attempts to improve hynotizability have provided inconsistent results, while the neuromodulation of the left dorsolateral prefrontal cortex (L-DLPFC) by transcranial brain stimulation can transiently enhance hypnotizability by strengthening L-DLPFC\u0026ndash;dACC (dorsal Anterior Cingulate Cortex) connectivity\u0026nbsp;(52)\u0026nbsp;. Overall, hypnotic responsiveness depends on several factors besides suggestibility, emphasizing the value of tailoring interventions according to subject\u0026rsquo;s experience and needs\u0026nbsp;(19,51,53,54).\u003c/p\u003e\n\u003cp\u003eOur personalized hypnosis, using individually crafted suggestions rather than standard scripts, was an easy task, probably feasible for most people, aligning interventions with the individual\u0026apos;s inner world. On neuropsychological stand point, it may reflect the dynamic interaction between central executive, salience, and default mode networks (55). Further research should clarify the link between hypnotizability and outcome, since hypnotizability scales are based on the concept of suggestibility, a\u003cem\u003e\u0026nbsp;leitmotif\u0026nbsp;\u003c/em\u003ein the history of hypnosis still remaining \u0026nbsp; questionable over one century from its introduction (55,56).\u0026nbsp;\u003c/p\u003e\n\u003col start=\"3\"\u003e\n \u003cli\u003e\u003cstrong\u003eand 4) Physiological Indicators and Network Connectivity\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eWhen \u0026nbsp;\u003cstrong\u003eAim 3 is concerned\u003c/strong\u003e, hypnosis did not prevent physiological arousal but promoted more efficient resource mobilization. We observed increased tonic EDA, decreased SCR (phasic component of sympathetic activity), and reduced time in stress response states, particularly during the second recall of negative academic memories, indicating an effective stress management.\u0026nbsp;This pattern has already been demonstrated in previous research, where EDA and SCR showed opposite effects following hypnosis (57). In light of the results presented here, we suggest that SCR is crucial for initiating physiological mobilization responses (as indicated by closeness centrality in the network), whereas EDA, the tonic component, is essential for sustaining the utilization of these resources over the long term (as reflected by improvements in TOL-R scores).\u003c/p\u003e\n\u003cp\u003eThe initial decrease in parasympathetic activity during the first recall aligns with prior findings linking negative emotions to reduced parasympathetic tone (58), while higher parasympathetic activity correlates with lower rumination and anxiety, reflecting emotional regulation (59). Elevated HR after stress indicates residual anxiety as well (43,44).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHR decreased and HRV increased, alongside EDA and SCR modulation after hypnosis, aligning with biopsychosocial models of arousal regulation (60\u0026ndash;62). Furthermore, the significant negative correlation between \u0026Delta;EDA and \u0026Delta;TOL-R (r = \u0026ndash;0.556, p = 0.03, df = 24) suggests that participants showing more controlled increases in EDA also exhibited the greatest cognitive improvements. This supports the notion that a better performance is driven by regulated resource mobilization rather than by arousal suppression, a fact in line with Bayesian models of energy allocation under cognitive load (63).\u003c/p\u003e\n\u003cp\u003eThe network analysis confirmed EDA during negative memory recall as a central node linking stress responses and executive function. Closeness centrality highlighted HR during hypnosis and SCR post-hypnosis as key connectors in emotional and cognitive regulation. Although HRV was excluded due to overlap with HR, combined HR, HRV, and EDA changes indicate improved autonomic regulation post-intervention. The position of EDA as a central node highlights the sympathetic system\u0026rsquo;s role as a core mechanism in adaptive stress management, providing a novel, actionable target for stress intervention.\u003c/p\u003e\n\u003cp\u003eThese findings align with stress physiology, indicating a shift from threat to challenge states\u0026nbsp;(60). Strong Bayesian factors for HR, HRV and EDA before and after hypnosis further support that hypnosis may help reframe overwhelming situations as manageable challenges, possibly by enhancing neural efficiency (64).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations and Future Directions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhile promising, this study has some limitations. Neuroimaging (e.g., fMRI, EEG) could clarify neural mechanisms (65), particularly the involvement of the PFC, underlying hypnosis-related changes in the relationship between executive function and autonomic regulation. Another relevant limitation concerns the absence of an active control group. Without a comparison group undergoing a similarly structured but non-hypnotic intervention (e.g., relaxation or guided imagery), we cannot fully exclude the contribution of non-specific effects. Future studies should include active control conditions to better isolate the specific effects of hypnosis from general therapeutic or contextual factors.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Replication in larger samples with active control groups and longitudinal designs is needed to assess the durability of effects on cognition and well-being. Additionally, exploring different hypnosis modalities, including self-hypnosis, could further define its potential for enhancing executive function, stress reduction, and resilience, supporting its integration into medical education and stress management programs.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn the clinical setting, increasingly dominated by concerns about burnout, cognitive fatigue, and emotional distress, this study offers a scientifically grounded, non-invasive, fast and promising intervention. Based on the sample size evaluated our findings suggest that a single personalized hypnosis session can enhance executive function, resilience, and reduce stress and anxiety in medical students, regardless of hypnotizability. EDA emerged as a key biomarker linking stress regulation with cognitive performance, supporting hypnosis as a scalable intervention for stress management. These results encourage further studies to better understand neural mechanisms and long-term effects, paving the way to integrate hypnosis into medical education and resilience training.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors directly accessed and verified the underlying data reported in the manuscript and take full responsibility for its submission and content.\u003cbr\u003e\u0026nbsp;All have approved the final version for publication and agree to be accountable for all aspects of the work, ensuring that any questions related to its accuracy or integrity are appropriately investigated and resolved.\u003cbr\u003eSubstantial contributions to the conception or design of the work: \u003cstrong\u003eLQ, AB\u003c/strong\u003e\u003cbr\u003eAcquisition, analysis, or interpretation of data: \u003cstrong\u003eLQ, AB, CT, MO, EF\u003c/strong\u003e\u003cbr\u003eDrafting of the manuscript: \u003cstrong\u003eLQ, AB, EF\u003c/strong\u003e\u003cbr\u003eCritical revision for important intellectual content: \u003cstrong\u003eLQ, AB, EF, GZ, ES, PN\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026deg;\u003cem\u003eThese authors equally contributed to the work.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u003c/strong\u003e The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eWe declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e \u0026apos;Not applicable\u0026apos;.\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZhou, A. 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Neuroinformatics\u003c/em\u003e. \u003cb\u003e15\u003c/b\u003e, 670052 (2021).\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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Executive function, TOL, hypnosis, stress management, HRV, EDA, medical students","lastPublishedDoi":"10.21203/rs.3.rs-7115279/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7115279/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eStress and anxiety affect executive functions, work performance, and well-being, with negative impacts documented in medical doctors. However, the benefits of hypnosis remain under investigation.\u003c/p\u003e\u003ch2\u003eHypothesis:\u003c/h2\u003e\u003cp\u003eThis study aims to evaluate the impact of hypnosis on stress management in medical students, particularly in relation to negative academic experiences.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003e26 volunteers, attending the last year of Medical School at the University of Padua, were enrolled (\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eClinicaltrials.gov\u003c/span\u003e: NCT06778109). Evaluations of executive function, stress and anxiety through the Tower of London revised (TOL-R), Visual Analog Scale (VASs and VASa), and the Perceived Stress Scale (PSS-10) were conducted. Additionally, heart rate (HR), heart rate variability (HRV), electrodermal activity (EDA), skin conductance responses (SCR/min) and percentage of time in stress response (%) were recorded.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eTOL-R scores improved (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while stress and anxiety decreased (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Hypnosis affected EDA, SCR/min, and % (ANOVAs p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). HR decreased (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and HRV increased (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) post-intervention. Bayesian analysis confirmed these findings (BF₁₀ = 184,738 for TOL-R; 23,017 for VASs; 35,952 for VASa). Network analysis identified EDA as the hub linking stress markers and cognitive performance\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eBased on the sample size evaluated our findings support hypnosis as an effective intervention for improving executive function, emotional regulation and stress response in medical students.\u003c/p\u003e","manuscriptTitle":"Hypnosis Enhances Prefrontal Performance, Negative Memories Management and Reduces Stress and Anxiety in Medical Students: A Network and Bayesian Psychophysiological Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-01 12:04:23","doi":"10.21203/rs.3.rs-7115279/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-19T08:17:28+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"307307445688689678040825932072798138165","date":"2025-08-13T06:57:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-12T05:29:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"31308608705321488930690533480199155182","date":"2025-08-12T02:36:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-29T11:25:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"106454384166541959002860627456931212082","date":"2025-07-28T16:23:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-28T14:18:56+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-28T14:15:05+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-21T10:29:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-17T22:12:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-07-17T17:22:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ee0f6694-faf9-467a-9bc0-65b1f4d9ec62","owner":[],"postedDate":"August 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":52449963,"name":"Health sciences/Health care"},{"id":52449964,"name":"Biological sciences/Neuroscience"},{"id":52449965,"name":"Biological sciences/Psychology"},{"id":52449966,"name":"Social science/Psychology"}],"tags":[],"updatedAt":"2026-03-02T16:05:51+00:00","versionOfRecord":{"articleIdentity":"rs-7115279","link":"https://doi.org/10.1038/s41598-026-40770-6","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-02-26 15:59:39","publishedOnDateReadable":"February 26th, 2026"},"versionCreatedAt":"2025-08-01 12:04:23","video":"","vorDoi":"10.1038/s41598-026-40770-6","vorDoiUrl":"https://doi.org/10.1038/s41598-026-40770-6","workflowStages":[]},"version":"v1","identity":"rs-7115279","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7115279","identity":"rs-7115279","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}