Efficacy of Virtual Reality‐Based Intervention for Reducing Preoperative Anxiety in Adult Surgical Patients: A Randomized Controlled Trial

ABSTRACT

Background

Preoperative anxiety affects a substantial proportion of surgical patients and may adversely influence perioperative outcomes. Virtual reality (VR) technology offers an innovative approach for anxiety management, yet evidence regarding its efficacy in surgical settings remains limited.

Objective

This study aimed to evaluate the effectiveness of an immersive VR‐based intervention for reducing preoperative anxiety among adult patients undergoing elective abdominal surgery.

Methods

A prospective, single‐center, randomized controlled trial was conducted from March 2023 to December 2024. Three hundred eight patients scheduled for elective abdominal surgery were randomly allocated to either the VR intervention group (n = 155) or the standard care control group (n = 153). The VR group received a 10–15 min immersive relaxation experience prior to anesthesia induction. The primary outcome was pre‐induction anxiety measured using the State–Trait Anxiety Inventory, State subscale (STAI‐S). Secondary outcomes included intraoperative cooperation scores, physiological stress markers, and patient satisfaction.

Results

Patients in the VR group demonstrated significantly lower pre‐induction STAI‐S scores compared to controls (36.5 ± 10.5 vs. 48.0 ± 10.9, mean difference −11.5, 95% CI −13.9 to −9.2, Cohen's d = 1.08, p < 0.001). The VR group also exhibited higher intraoperative cooperation scores (82.8 ± 9.3 vs. 74.8 ± 11.8, mean difference 8.0, Cohen's d = 0.75, p < 0.001) and attenuated physiological stress responses including heart rate (82.5 ± 12.8 vs. 89.5 ± 12.4 bpm, mean difference −7.0, Cohen's d = 0.56, p < 0.001), systolic blood pressure (133.3 ± 15.0 vs. 142.0 ± 14.5 mmHg, mean difference −8.7, Cohen's d = 0.59, p < 0.001), and serum cortisol (14.9 ± 4.3 vs. 20.1 ± 4.8 μg/dL, mean difference −5.2, Cohen's d = 1.14, p < 0.001). The VR group reported higher satisfaction scores (8.1 ± 1.1 vs. 7.4 ± 1.3, p < 0.001). Subgroup analyses revealed consistent benefits across surgery types, anesthesia modalities, and demographic characteristics. Adverse events were minimal, with only 4.5% of VR participants reporting mild transient symptoms including dizziness (n = 3, 1.9%), headache (n = 3, 1.9%), and eye strain (n = 1, 0.6%), all of which resolved spontaneously within minutes.

Conclusions

Immersive VR‐based intervention effectively reduces preoperative anxiety and improves patient cooperation in adults undergoing elective abdominal surgery. This non‐pharmacological approach represents a promising adjunct to standard perioperative care protocols.

In this randomized controlled trial (N = 308), a 10‐ to 15‐min immersive virtual reality (VR) intervention significantly reduced preoperative anxiety in adult patients undergoing elective abdominal surgery compared to standard care (S‐AI score: 36.5 vs. 48.0; mean difference −11.5; p < 0.001; Cohen's d = 1.08). The VR group also showed better intraoperative cooperation, lower physiological stress markers (heart rate, blood pressure, cortisol), and higher patient satisfaction, with only 4.5% reporting mild transient symptoms. VR is a safe and effective non‐pharmacological approach for preoperative anxiety management.

1. Introduction

Preoperative anxiety represents one of the most prevalent psychological challenges encountered in surgical medicine, with reported prevalence rates ranging from 60% to 80% among patients awaiting elective procedures [1, 2, 3]. This anticipatory emotional state encompasses a constellation of psychological and physiological responses, including apprehension regarding surgical outcomes, fear of anesthesia‐related complications, concerns about postoperative pain, and uncertainty about the recovery process. The significance of preoperative anxiety extends beyond mere psychological discomfort, as mounting evidence indicates its profound influence on perioperative outcomes, including increased anesthetic requirements, heightened postoperative pain sensitivity, prolonged recovery trajectories, and diminished overall patient satisfaction with surgical care [4, 5, 6]. Furthermore, elevated preoperative anxiety has been associated with immunological alterations that may impair wound healing and increase susceptibility to postoperative infections [7]. The substantial prevalence and clinical consequences of preoperative anxiety have prompted sustained interest in developing effective interventions that can mitigate this condition while maintaining compatibility with existing perioperative workflows.

Conventional approaches to managing preoperative anxiety have traditionally relied on pharmacological interventions, particularly benzodiazepines and other sedative‐anxiolytic agents administered during the preoperative period. While these medications demonstrate efficacy in reducing acute anxiety symptoms, their clinical utility is constrained by several important limitations [8]. Pharmacological anxiolysis may cause cognitive impairment, respiratory depression, paradoxical reactions, and prolonged sedation that can interfere with early postoperative mobilization protocols [9, 10]. Additionally, benzodiazepine premedication has been associated with increased rates of postoperative delirium, particularly among elderly surgical populations [11, 12, 13]. These considerations have stimulated growing interest in non‐pharmacological alternatives that can achieve comparable anxiolytic effects without the inherent risks and side effects of drug‐based interventions. Various non‐pharmacological strategies have been evaluated, including preoperative education programs, cognitive‐behavioral interventions, music therapy, aromatherapy, and guided imagery techniques [11, 12]. While many of these approaches have demonstrated modest benefits, their implementation often requires substantial personnel resources, specialized training, or extended time commitments that may limit practical applicability in busy surgical environments [9, 10].

Virtual reality technology has emerged as a particularly promising platform for delivering immersive anxiolytic interventions in clinical settings. Contemporary VR systems enable users to experience computer‐generated multisensory environments that can effectively capture attention, promote psychological absorption, and facilitate dissociation from immediate stressors [13]. The theoretical foundation for VR‐based anxiety reduction rests upon established psychological principles, including distraction theory, presence theory, and attention allocation mechanisms [14, 15]. By engaging multiple sensory modalities and creating a compelling sense of presence within a virtual environment, VR interventions may effectively redirect cognitive resources away from anxiety‐provoking stimuli associated with the surgical experience. Moreover, VR technology offers unique advantages for perioperative applications, including standardized delivery of intervention content, minimal requirements for specialized personnel, portability to various clinical locations, and the capacity to provide personalized experiences tailored to individual patient preferences [16]. Previous research has demonstrated the feasibility and acceptability of VR interventions across diverse clinical contexts, including pediatric procedural sedation, labor analgesia, burn wound care, and chronic pain management [17, 18, 19]. However, rigorous evidence regarding the efficacy of immersive VR for preoperative anxiety reduction in adult surgical populations remains relatively sparse, with existing studies often limited by small sample sizes, non‐randomized designs, or inadequate outcome assessment methodologies [20].

Given the clinical significance of preoperative anxiety and the potential advantages of VR‐based interventions, we designed and conducted a prospective randomized controlled trial to systematically evaluate the efficacy of immersive VR technology for reducing preoperative anxiety among adult patients undergoing elective abdominal surgery. Our investigation was specifically designed to address methodological limitations of prior research through adequate statistical power, comprehensive outcome assessment, and systematic evaluation of intervention effects across clinically relevant patient subgroups. We hypothesized that patients receiving the VR intervention would demonstrate significantly lower anxiety levels, improved intraoperative cooperation, attenuated physiological stress responses, and higher satisfaction compared to patients receiving standard care alone. The findings from this investigation are intended to inform clinical practice and contribute to the evidence base supporting integration of digital health technologies into contemporary perioperative care protocols.

2. Methods

2.1. Study Design and Setting

This prospective, single‐center, two‐arm, parallel‐group randomized controlled trial was conducted at the Department of Anesthesiology, Xianning Central Hospital (The First Affiliated Hospital of Hubei University of Science and Technology) from March 2023 to December 2024. The study protocol was approved by the institutional ethics committee. All procedures were conducted in accordance with the Declaration of Helsinki and Good Clinical Practice guidelines. Written informed consent was obtained from all participants following comprehensive explanation of study objectives, procedures, potential risks, and alternatives.

2.2. Participants

Adult patients aged 18–70 years scheduled for elective abdominal surgery under general, spinal, or local anesthesia were screened for eligibility. Inclusion criteria comprised: (1) American Society of Anesthesiologists (ASA) physical status classification I or II; (2) anticipated surgery duration less than 4 h; (3) ability to understand and complete study questionnaires; and (4) willingness to participate in the VR intervention if randomized to the intervention group. Exclusion criteria included: (1) history of psychiatric disorders requiring pharmacotherapy; (2) current use of anxiolytic, antidepressant, or antipsychotic medications; (3) cognitive impairment or dementia; (4) uncorrected visual or auditory deficits precluding VR headset use; (5) history of motion sickness or cybersickness; (6) active vestibular disorders; (7) claustrophobia; and (8) previous participation in VR‐based clinical research, which was excluded to minimize potential bias from pre‐formed expectations, habituation effects, or familiarity with VR equipment that could confound the assessment of VR's anxiolytic efficacy.

2.3. Randomization and Blinding

Eligible participants were randomized in a 1:1 ratio to either the VR intervention group or the standard care control group using a computer‐generated random sequence with permuted blocks of varying sizes (4, 6, and 8). Randomization assignments were concealed in sequentially numbered, opaque, sealed envelopes that were opened by research staff only after completion of baseline assessments. Due to the nature of the intervention, participant blinding was not feasible; however, outcome assessors and data analysts remained masked to group allocation throughout the study.

2.4. Interventions

Patients randomized to the VR group received an immersive VR‐based relaxation intervention using a commercially available head‐mounted display system (Pico Neo 3 Pro, Pico Technology, China) with integrated headphones. The VR content consisted of a curated selection of calming natural environments, including serene forest landscapes, tranquil beach settings, and peaceful garden scenes, accompanied by synchronized spatial audio featuring nature sounds and relaxing background music. Participants were invited to select their preferred virtual environment from available options. The intervention was administered in a quiet, comfortable preoperative holding area approximately 30–45 min prior to transfer to the operating room. Trained research staff assisted with headset fitting and ensured participant comfort throughout the intervention. The VR session duration was standardized at 10–15 min, with participants having the option to discontinue the experience at any time. Following the VR intervention, patients received routine preoperative care per institutional protocols. Patients randomized to the control group received standard preoperative care alone, which included routine nursing assessments, anesthetic consultation, and verbal reassurance from clinical staff as per usual practice.

2.5. Outcome Measures

The primary outcome was state anxiety level measured using the State–Trait Anxiety Inventory (STAI) Form Y, State Anxiety subscale (STAI‐S, hereafter referred to as S‐AI), a validated 20‐item self‐report instrument developed by Spielberger with scores ranging from 20 to 80, with higher scores indicating greater anxiety [21]. The minimal clinically important difference (MCID) for the STAI‐S has been estimated at approximately 10 points based on distribution‐based methods (0.5 SD) and anchor‐based approaches in surgical populations [21, 22]. S‐AI assessments were conducted at three time points: baseline upon admission to the preoperative area (T0), immediately prior to anesthesia induction following completion of the intervention or equivalent waiting period (T1), and 24 h postoperatively (T2). Secondary outcomes included: (1) intraoperative cooperation assessed using the Intraoperative Observer Rating Scale (IORS), a standardized instrument scored from 0 to 100 with higher scores indicating better cooperation—cooperation was assessed by blinded observers during the perioperative phases preceding the onset of general anesthesia and neuromuscular blockade (i.e., patient positioning, monitoring placement, and anesthesia induction); for patients under spinal or local anesthesia, cooperation was additionally assessed during the intraoperative period; (2) physiological stress markers including heart rate, systolic blood pressure, and serum cortisol levels measured at baseline and pre‐induction; and (3) patient satisfaction assessed using a 10‐point numerical rating scale at the 24‐h postoperative assessment. Adverse events related to the VR intervention, including motion sickness, headache, eye strain, and dizziness, were systematically recorded.

2.6. Statistical Analysis

Sample size was determined based on the primary outcome of pre‐induction S‐AI scores. To ensure sufficient statistical power to detect a conservative treatment effect, we powered our study to detect a difference of five points between groups (standard deviation of 12 points, two‐sided alpha of 0.05, and statistical power of 90%), requiring a minimum of 122 participants per group. Of note, this five‐point threshold was used solely for sample size estimation and is distinct from the established MCID for the STAI‐S, which is approximately 10 points [22]. Thus, our trial was designed to be adequately powered to detect effects both below and above this MCID. To accommodate potential attrition of up to 20%, we targeted enrollment of 150 participants per group. Continuous variables were summarized as mean ± standard deviation and compared between groups using independent samples t‐tests or Mann–Whitney U tests as appropriate based on distributional characteristics. Categorical variables were presented as frequencies and percentages and compared using chi‐square tests or Fisher's exact tests. Effect sizes were calculated using Cohen's d with 95% confidence intervals. For the primary outcome (pre‐induction S‐AI at T1), a two‐sided p < 0.05 was considered statistically significant. For the seven pre‐specified secondary outcomes (cooperation score, postoperative S‐AI at T2, pre‐induction heart rate, pre‐induction systolic blood pressure, pre‐induction serum cortisol, patient satisfaction, and adverse events), Bonferroni correction was applied, yielding an adjusted significance threshold of p < 0.007 (0.05/7). Pearson correlation coefficients were computed as exploratory analyses to examine associations among primary and secondary outcome variables; these analyses were interpreted with nominal p < 0.05 and were not included in the Bonferroni correction as they were considered hypothesis‐generating rather than confirmatory. Subgroup analyses were conducted to evaluate intervention effects across strata defined by surgery type, anesthesia modality, ASA classification, and age categories. All analyses were performed using R statistical software (version 4.3.1) according to the intention‐to‐treat principle.

3. Results

3.1. Participant Enrollment and Baseline Characteristics

A total of 380 patients were assessed for eligibility during the study period, of whom 72 were excluded for not meeting inclusion criteria (n = 38), declining participation (n = 25), or other reasons (n = 9). The remaining 308 patients were randomized to the VR group (n = 155) or control group (n = 153). All randomized participants completed their assigned interventions and provided complete outcome data; thus, the final analysis included 155 patients in the VR group and 153 patients in the control group (Figure 1).

FIGURE 1.

CONSORT flow diagram illustrating participant enrollment, allocation, follow‐up, and analysis.

Baseline demographic and clinical characteristics were generally comparable between groups (Table 1). The mean age was 47.0 ± 11.9 years in the VR group and 45.0 ± 11.9 years in the control group. Gender distribution was similar, with males comprising 52.3% and 49.0% of the VR and control groups, respectively. Anesthesia modality distribution was also comparable between groups (general anesthesia: VR 65.2% vs. Control 70.6%; spinal/local: VR 34.8% vs. Control 29.4%). The distribution of surgery types was well‐balanced, including laparoscopic cholecystectomy (VR: 29.0%, Control: 30.1%), laparoscopic appendectomy (VR: 29.0%, Control: 29.4%), inguinal hernia repair (VR: 23.2%, Control: 22.2%), and other abdominal procedures (VR: 18.7%, Control: 18.3%). Baseline S‐AI scores did not differ significantly between groups (44.1 ± 9.5 vs. 45.3 ± 10.5, p = 0.300), confirming successful randomization with respect to the primary outcome measure.

TABLE 1.

Baseline demographic and clinical characteristics.

Variable	VR group (n = 155)	Control group (n = 153)	Statistic	p
Age (years)	47.0 ± 11.9	45.0 ± 11.9	t = 1.52	0.129
Gender (male/female)	81 (52.3%)/74 (47.7%)	75 (49.0%)/78 (51.0%)	χ 2 = 0.21	0.650
BMI (kg/m2)	24.1 ± 3.4	24.9 ± 3.3	t = −2.21	0.028
Education (≤ middle/high/≥ college)	30 (19.4%)/53 (34.2%)/72 (46.5%)	44 (28.8%)/60 (39.2%)/49 (32.0%)	χ 2 = 7.44	0.024
Anesthesia modality
General anesthesia	101 (65.2%)	108 (70.6%)	χ 2 = 1.04	0.308
Spinal/local	54 (34.8%)	45 (29.4%)
Surgery type
Cholecystectomy	45 (29.0%)	46 (30.1%)	χ 2 = 0.07	0.995
Appendectomy	45 (29.0%)	45 (29.4%)
Hernia repair	36 (23.2%)	34 (22.2%)
Other	29 (18.7%)	28 (18.3%)
ASA grade (I/II)	58 (37.4%)/97 (62.6%)	57 (37.3%)/96 (62.7%)	χ 2 = 0.00	1.000
Baseline S‐AI (T0)	44.1 ± 9.5	45.3 ± 10.5	t = −1.04	0.300
Baseline HR (bpm)	76.5 ± 11.8	76.5 ± 10.8	t = 0.01	0.992

Note: Data presented as mean ± SD or n (%).

Abbreviations: ASA, American Society of Anesthesiologists; BMI, body mass index; HR, heart rate; S‐AI, State Anxiety Inventory.

3.2. Primary Outcome: Pre‐Induction Anxiety

State anxiety levels, as measured by the S‐AI, were assessed at three time points, as shown in Figure 2: baseline (T0), pre‐induction (T1), and 24 h postoperatively (T2). At baseline (T0), there was no statistically significant difference in S‐AI scores between the VR group and control group (44.1 ± 9.5 vs. 45.3 ± 10.5, p = 0.300). At the pre‐induction time point (T1), the VR group demonstrated significantly lower S‐AI scores compared to the control group (36.5 ± 10.5 vs. 48.0 ± 10.9, mean difference −11.5, 95% CI −13.9 to −9.2, p < 0.001, Cohen's d = 1.08). This difference exceeded the MCID of 10 points for the STAI‐S. The VR group showed a reduction of 7.6 points from baseline, while the control group experienced an increase of 2.7 points. At 24 h postoperatively (T2), the VR group maintained lower S‐AI scores compared to controls (32.9 ± 7.0 vs. 37.3 ± 8.0, mean difference −4.3, 95% CI −6.0 to −2.7, p < 0.001, Cohen's d = 0.58).

FIGURE 2.

State Anxiety Inventory scores at baseline (T0), pre‐induction (T1), and 24‐h postoperative (T2) time points. Error bars represent standard error of the mean. p < 0.001 (Bonferroni corrected).

3.3. Secondary Outcomes

Intraoperative cooperation, as assessed by the IORS, was significantly higher in the VR group compared to controls (82.8 ± 9.3 vs. 74.8 ± 11.8, mean difference 8.0 points, 95% CI 5.6–10.4, p < 0.001, Cohen's d = 0.75). The distribution of cooperation scores is shown in Figure 3.

FIGURE 3.

Violin plot showing the distribution of Intraoperative Observer Rating Scale (IORS) cooperation scores. Box plots indicate median and interquartile range; individual data points are overlaid. p < 0.001.

Physiological stress markers demonstrated statistically significant differences between groups. Pre‐induction heart rate was lower in VR patients (82.5 ± 12.8 vs. 89.5 ± 12.4 bpm, mean difference −7.0 bpm, 95% CI −9.8 to −4.2, p < 0.001, Cohen's d = 0.56). Pre‐induction systolic blood pressure was lower in the VR group (133.3 ± 15.0 vs. 142.0 ± 14.5 mmHg, mean difference −8.7 mmHg, 95% CI −12.0 to −5.4, p < 0.001, Cohen's d = 0.59). Serum cortisol levels at pre‐induction were lower in VR patients compared to controls (14.9 ± 4.3 vs. 20.1 ± 4.8 μg/dL, mean difference −5.2 μg/dL, 95% CI −6.2 to −4.2, p < 0.001, Cohen's d = 1.14) (Figure 4).

FIGURE 4.

Changes in physiological parameters from baseline to pre‐induction. (A) Heart rate, (B) systolic blood pressure, (C) serum cortisol levels. Error bars represent standard error of the mean.

Patient satisfaction ratings at 24 h postoperatively were higher in the VR group (8.1 ± 1.1 vs. 7.4 ± 1.3, mean difference 0.7, 95% CI 0.4–1.0, p < 0.001, Cohen's d = 0.54). Complete outcome data are presented in Table 2.

TABLE 2.

Primary and secondary outcome measures.

Outcome	VR group	Control group	Mean diff (95% CI)	p	Cohen's d
Pre‐induction S‐AI (T1)	36.5 ± 10.5	48.0 ± 10.9	−11.5 (−13.9, −9.2)	< 0.001	1.08
Cooperation score	82.8 ± 9.3	74.8 ± 11.8	8.0 (5.6, 10.4)	< 0.001	0.75
Postop S‐AI (T2)	32.9 ± 7.0	37.3 ± 8.0	−4.3 (−6.0, −2.7)	< 0.001	0.58
Pre‐induction HR	82.5 ± 12.8	89.5 ± 12.4	−7.0 (−9.8, −4.2)	< 0.001	0.56
Pre‐induction SBP	133.3 ± 15.0	142.0 ± 14.5	−8.7 (−12.0, −5.4)	< 0.001	0.59
Pre‐induction cortisol	14.9 ± 4.3	20.1 ± 4.8	−5.2 (−6.2, −4.2)	< 0.001	1.14
Satisfaction	8.1 ± 1.1	7.4 ± 1.3	0.7 (0.4, 1.0)	< 0.001	0.54

Note: Data presented as mean ± SD. Cortisol (μg/dL). p values Bonferroni corrected.

Abbreviations: HR, heart rate (bpm); S‐AI, State Anxiety Inventory; SBP, systolic blood pressure (mmHg).

3.4. Subgroup Analyses

Subgroup analyses demonstrated consistent effects of VR intervention across all examined patient strata (Figure 5, Table 3). The intervention effect was observed regardless of surgery type, with mean differences in pre‐induction S‐AI ranging from −7.4 points for cholecystectomy to −16.9 points for other abdominal procedures. Effects were comparable across anesthesia modalities (general anesthesia: −11.8 points; spinal/local: −11.2 points) and ASA classifications (ASA I: −13.1 points; ASA II: −10.6 points). Age‐stratified analyses revealed similar benefits in younger (< 45 years: −11.9 points) and older (≥ 45 years: −11.4 points) patient subgroups.

FIGURE 5.

Forest plot of subgroup analyses showing mean differences in pre‐induction S‐AI scores with 95% confidence intervals. All subgroups demonstrate effects favoring the VR intervention.

TABLE 3.

Subgroup analysis by surgery type.

Surgery type	VR (n)	VR S‐AI	Control (n)	Control S‐AI	p
Cholecystectomy	45	38.2 ± 11.2	46	45.6 ± 9.8	0.001
Appendectomy	45	39.5 ± 9.3	45	48.8 ± 10.2	< 0.001
Hernia repair	36	31.7 ± 9.3	34	47.1 ± 11.4	< 0.001
Other surgery	29	35.1 ± 10.7	28	51.9 ± 12.7	< 0.001

3.5. Correlation Analysis

Exploratory correlation analysis revealed several statistically significant associations among study variables (Figure 6). Pre‐induction anxiety demonstrated a moderate negative correlation with intraoperative cooperation (r = −0.23, p < 0.001). Pre‐induction cortisol levels showed a positive correlation with pre‐induction S‐AI scores (r = 0.24, p < 0.001). Patient satisfaction was negatively correlated with pre‐induction cortisol (r = −0.15, p < 0.05) and heart rate (r = −0.15, p < 0.05).

FIGURE 6.

Correlation matrix displaying Pearson correlation coefficients among primary study variables. HR, heart rate; S‐AI, State Anxiety Inventory; SBP, systolic blood pressure.

3.6. Adverse Events

Among 155 participants in the VR group, seven patients (4.5%) reported mild adverse symptoms, including transient dizziness (n = 3, 1.9%), mild headache (n = 3, 1.9%), and brief eye strain (n = 1, 0.6%). All symptoms resolved spontaneously within minutes of headset removal and did not require medical intervention. No participants discontinued the VR experience due to adverse symptoms, and no serious adverse events were attributed to the intervention.

4. Discussion

This randomized controlled trial demonstrates that immersive VR‐based intervention reduces preoperative anxiety, attenuates physiological stress responses, and improves intraoperative cooperation among adult patients undergoing elective abdominal surgery. The magnitude of the anxiolytic effect observed, with a large effect size (Cohen's d = 1.08) exceeding the MCID for the STAI‐S, exceeds that reported in most previous pharmacological and non‐pharmacological intervention studies [23, 24]. These findings provide evidence supporting the potential integration of VR technology into perioperative care protocols.

The substantial reduction in preoperative anxiety achieved through VR intervention aligns with and extends findings from prior research examining VR applications across diverse clinical contexts [25]. Several theoretical mechanisms may account for the observed anxiolytic effects. First, the immersive nature of VR creates a compelling sense of presence within the virtual environment, effectively redirecting attentional resources away from anxiety‐provoking stimuli associated with the impending surgical procedure. This attention‐diversion mechanism has been consistently demonstrated in experimental pain research [26]. Second, the calming natural environments employed in our VR content may have activated parasympathetic nervous system responses associated with relaxation and stress reduction, consistent with biophilia hypothesis predictions regarding human preferences for natural settings [27]. Third, the novelty and engaging quality of the VR experience may have provided a positive distraction that supplanted negative anticipatory cognitions, thereby interrupting the cognitive amplification cycle characteristic of anxiety disorders.

The VR intervention also produced significant differences in physiological stress markers. Compared to the control group, patients in the VR group demonstrated significantly lower pre‐induction heart rate, systolic blood pressure, and serum cortisol levels. Notably, the reduction in serum cortisol was associated with a large effect size (Cohen's d = 1.14). As this study involved patients undergoing elective abdominal surgery rather than a high‐acuity stress state, the observed differences should be interpreted within this population context. Nonetheless, these findings support the conclusion that the VR intervention modulated physiological stress responses, although the clinical significance of such differences remains uncertain.

The improvement in intraoperative cooperation scores represents an important secondary benefit with direct clinical relevance. It is important to note that the IORS assessments were performed exclusively during the perioperative phases preceding the onset of general anesthesia and neuromuscular blockade. During this pre‐induction window, patient cooperation—manifested by ease of patient positioning, monitoring placement, and successful mask ventilation—is critical for safe and efficient anesthesia induction. Anxious patients may exhibit behavioral manifestations that complicate anesthesia induction and perioperative management, including difficulty following instructions, physical tension, and resistance to positioning or monitoring procedures. Enhanced cooperation may facilitate smooth induction of anesthesia and contribute to improved operating room efficiency [28]. From a patient‐centered perspective, the reduced need for physical or verbal redirection during anxiety‐related behavioral episodes preserves patient dignity and contributes to a more positive overall surgical experience. While the IORS is a standardized instrument, a universally established MCID is not yet available for it. Nevertheless, the observed statistically significant difference and large effect size (Cohen's d = 0.75) strongly suggest a clinically meaningful improvement in patient cooperation.

The consistency of intervention effects across patient subgroups strengthens confidence in the generalizability of our findings. VR intervention produced significant anxiolytic effects regardless of surgery type, anesthesia modality, ASA classification, or patient age, suggesting broad applicability across the spectrum of elective surgical procedures and patient populations commonly encountered in surgical practice.

The VR group reported a higher satisfaction score compared to controls. However, it should be noted that our satisfaction measure was a simple 10‐point numerical rating scale without established psychometric validation or MCID. Future studies should consider using validated instruments such as the Iowa Satisfaction with Anesthesia Scale (ISAS) to more robustly evaluate patient satisfaction outcomes.

The low incidence of adverse symptoms (4.5%) and the mild, self‐limiting nature of all reported events suggest that VR intervention can be safely administered to the majority of surgical patients. Nevertheless, careful patient selection remains important, and VR should be avoided in patients with known susceptibility to motion sickness or previous adverse reactions to VR technology [29].

Several limitations of this study warrant consideration when interpreting the results. First, the single‐center design may limit generalizability to other clinical settings with different patient populations, surgical practices, or institutional cultures. Multicenter replication studies would strengthen external validity. Second, participant blinding was not feasible due to the nature of the intervention, introducing potential for placebo effects and performance bias. Importantly, the absence of a sham or active control condition means we cannot distinguish the specific effects of immersive VR content from nonspecific effects such as novelty, expectation, or the placebo response. Placebo effects can dampen physiological stress responses if patients believe they should be more relaxed, as has been demonstrated in meditation studies; therefore, the observed reductions in physiological markers should not be interpreted as evidence against a placebo contribution. We elected to use a standard care control as this was the first study at our institution evaluating VR for preoperative anxiety, and establishing efficacy against standard care was a necessary first step. Future trials should incorporate sham VR controls to disentangle specific from non‐specific intervention effects. Third, the VR content utilized in this study represented a standardized relaxation experience; future research might explore whether personalized content selection enhances treatment response. Fourth, long‐term follow‐up was limited to 24 h postoperatively; investigation of sustained effects on surgical recovery, postoperative pain, and quality of life would provide valuable additional information. Fifth, the exclusion of patients currently receiving anxiolytic, antidepressant, or antipsychotic medications limits the generalizability of our findings, particularly to patients with preexisting anxiety disorders requiring pharmacotherapy. This means we currently lack data on the efficacy of VR intervention in these high‐risk patients, a subgroup that might potentially derive the greatest benefit from anxiolytic interventions. Whether VR intervention provides additional benefit in patients already receiving such treatments, or could serve as an alternative, remains unknown and warrants future investigation. Sixth, patient satisfaction was assessed using a simple unvalidated 10‐point numerical rating scale; future studies should employ validated satisfaction instruments with established psychometric properties and MCID values.

The practical implementation of VR intervention in perioperative settings involves considerations beyond efficacy demonstration. Equipment costs for head‐mounted display systems have decreased substantially in recent years, enhancing economic feasibility. The standardized nature of VR content delivery reduces requirements for specialized personnel training, and sessions can be supervised by existing nursing staff with minimal additional workload. Additionally, successful implementation requires staff training and availability to assist with VR equipment setup and troubleshooting; variations in staff aptitude and comfort with technology may affect consistency of intervention delivery across different clinical settings. The portability of VR equipment enables flexible deployment across various preoperative care locations. Hygiene considerations can be addressed through use of disposable covers for headset components and adherence to institutional infection control protocols. Future implementation research should evaluate cost‐effectiveness, workflow integration strategies, and optimal timing of intervention delivery.

5. Conclusions

This randomized controlled trial provides evidence that immersive VR‐based intervention effectively reduces preoperative anxiety, attenuates cortisol stress responses, and improves intraoperative cooperation in adult patients undergoing elective abdominal surgery. The anxiolytic effects, demonstrated through both psychometric assessment and physiological markers, combined with a favorable safety profile, support VR technology as a potential non‐pharmacological adjunct to standard perioperative care. Future multicenter trials incorporating sham controls and validated satisfaction instruments are needed to further define the role of VR in perioperative anxiety management.

Author Contributions

Lei Zheng: conceptualization, methodology, writing – original draft. Tian Wang: conceptualization, data curation, investigation, writing – original draft. Tongling Shen: writing – review and editing, supervision, visualization, investigation, funding acquisition.

Funding

This work was supported by the Xianning Central Hospital.

Ethics Statement

The study protocol was approved by the Ethics Committee/Institutional Review Board of Xianning Central Hospital (The First Affiliated Hospital of Hubei University of Science and Technology). The trial was conducted in accordance with the ethical principles of the Declaration of Helsinki and Good Clinical Practice (GCP) guidelines.

Consent

Written informed consent was obtained from all individual participants included in the study after a full explanation of the study procedures, potential risks, and benefits.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.