Usability and Feasibility of a Contrast Avoidance Model-Based Virtual Reality Protocol Designed for Generalized Anxiety Disorder

1. Introduction

Generalized anxiety disorder (GAD) is characterized by persistent, unmanageable, and excessive worry and tension that significantly impairs an individual’s daily functioning and overall quality of life [1,2]. GAD has a moderately high lifetime prevalence of approximately 3.7% to 5.0%, yet it remains under-researched compared to other anxiety disorders [3,4], likely in part because it was historically treated as a residual and diagnostically uncertain category, and repeated revisions to its diagnostic criteria hindered the accumulation of a stable evidence base [5,6]. Despite advances in evidence-based psychotherapeutic treatments, such as traditional cognitive-behavioral therapy (CBT), its efficacy remains limited, with approximately 50% of GAD patients failing to achieve full remission or experiencing relapse [7,8]. This treatment gap underscores the need for novel theoretical frameworks and intervention delivery methods that address the underlying mechanisms of pathological worry [3,9].

A promising perspective is offered by the Contrast Avoidance Model (CAM), which suggests that individuals with GAD engage in worry as a maladaptive emotion regulation strategy [3,10]. Unlike earlier models suggesting that worry serves to dampen or avoid somatic activation, CAM proposes that individuals worry to intentionally create and sustain a state of negative emotional arousal [10,11,12,13,14]. By maintaining this constant negative affect, they avoid sharp, aversive increases in negative emotion, referred to as negative emotional contrasts, that would otherwise occur in response to unexpected negative events [10,12].

Recent evidence from ecological momentary assessment (EMA) and laboratory studies has supported the tenets of CAM, showing that sustained anxiety indeed reduces the shock of negative transitions while simultaneously increasing the probability of experiencing a positive emotional contrast [12,15,16]. Based on these findings, the authors of the model have proposed a novel contrast exposure framework which aims to induce strong negative emotion immediately following a period of contiguous relaxation; this approach is designed to help patients achieve emotional processing by training them to tolerate sharp affective shifts rather than preemptively avoiding them through worry [10,16].

Virtual Reality (VR) technology provides a unique opportunity to implement CAM-based interventions by offering immersive, safe, and highly controlled environments [17,18,19]. Virtual reality exposure therapy (VRET) allows for a consistent structure and the possibility of gradual exposure, making it well suited to helping patients confront and tolerate the emotional contrasts they typically seek to avoid [17,19]. By transitioning users from a state of guided relaxation to sudden, discomfort-evoking virtual scenarios, clinicians can systematically challenge the avoidance behaviors central to GAD [10,12]. VR is particularly useful here because real-world environments rarely allow the deliberate and repeatable orchestration of sharp contrasts between calm and anxiety-provoking situations, whereas VR enables therapists to do so safely while controlling both the intensity and duration of exposure [20]. However, for such applications to be effective, they must be designed with high usability and visual fidelity to ensure participant engagement and emotional presence [21,22]. Accordingly, early-stage feasibility and user-experience evaluation is an essential step in translating this approach into clinical application [23,24].

The primary objective of this study was to evaluate the usability and feasibility of a VR-based protocol designed to simulate emotional contrasts in accordance with CAM of GAD. Because the protocol’s central therapeutic mechanism involves inducing transitions from relaxation to threat exposure, its capacity to reliably generate such emotional contrasts was conceptualized as a core indicator of feasibility rather than as a measure of clinical efficacy. Accordingly, the study pursued four specific aims: (1) to determine whether the protocol could elicit the intended autonomic and subjective shifts from a relaxed baseline to anxiety-provoking states; (2) to assess user comfort, including the tolerability of wearable biometric sensors; (3) to evaluate the degree of user immersion and sense of presence achieved within the virtual environments; and (4) to identify technical and design requirements necessary for future clinical implementation. Through this feasibility-focused investigation, we sought to determine whether this protocol could produce rapid, within-session affective transitions required for a CAM-based intervention, while meeting key usability criteria related to comfort, immersion, and system implementation.

2. Materials and Methods

2.1. Study Design

The study followed a prospective, within-subject experimental design. Each participant completed a single experimental session lasting approximately 20–30 minutes, with the core VR protocol lasting 12–15 minutes. During the VR session, physiological measures were collected via wearables, and subjective ratings of distress and affect were collected in VR using standardized self-report scales. After the VR protocol, participants completed post-session questionnaires, followed by a short recorded semi-structured interview to provide qualitative feedback.

2.2. Participants

A recruitment target of 20 participants was selected, consistent with published guidance for pilot-study sample sizes and appropriate for an early-stage feasibility evaluation [25,26]. Participants were recruited through professional and community networks using informal announcements and direct outreach. To ensure the sample reflected individuals experiencing elevated levels of worry, recruitment targeted a subclinical population reporting at least mild symptoms of anxiety. Eligibility was determined according to the inclusion and exclusion criteria summarized in Table 1.

2.3. Procedure

After providing written informed consent, participants were fitted with a Meta Quest 3 VR headset (Meta Platforms Technologies, LLC, Menlo Park, CA, USA) and a Polar H10 heart rate sensor (Polar Electro Oy, Kempele, Finland). The experimental setup is shown in Figure 1. The Polar device was used to continuously record heart rate (HR) and heart rate variability (HRV), which served as objective indicators of autonomic arousal [27].

After equipping the participants with the two wearables, they completed baseline questionnaires within the virtual environment using standard Meta Quest 3 controllers, including demographic questions and the GAD-7 [28]. Participants who did not meet the eligibility criteria discontinued the study, the equipment was removed, and no data were recorded or retained. Eligible participants were then placed in a neutral virtual garden environment for three minutes to experience the first relaxation period. During this phase, participants engaged in a guided meditation involving paced diaphragmatic breathing with a 4:6 inhale–exhale ratio, synchronized with visual light stimuli to ensure a state of initial relaxation [28]. The structure of this component was informed by our group’s prior work on guided relaxation in VR [29].

Following the initial relaxation segment, participants were exposed to three distinct anxiety-inducing virtual scenarios, each lasting one minute. To control for potential order effects, the sequence of scenarios was counterbalanced using a 3x3 Latin square design [30]. Immediately following each exposure scenario, participants provided subjective ratings within the VR environment using Self-Assessment Manikin (SAM) and Subjective Units of Distress Scale (SUDS) on a 1–9 scale [31,32]. Between scenarios, participants returned to the neutral virtual garden for a three-minute guided relaxation segment to facilitate physiological recovery and prepare for the next exposure. Participants completed the whole procedure standing to match the posture implied by the implemented exposure scenarios, and thereby minimize mismatch between the participant’s physical stance and the virtual context [33,34].

To preserve the intended affective contrast, subjective relaxation baselines were not assessed in real time after the guided meditation segments; instead, they were rated retrospectively at the end of the session, when participants recalled their average affective state during the relaxation periods after completing all scenarios. Then participants completed post-experiment VR-administered questionnaires assessing presence using the Igroup Presence Questionnaire (IPQ) and cybersickness using the Cybersickness in Virtual Reality Questionnaire (CSQ-VR) [35,36,37], after which the VR headset and heart rate sensor were removed. The procedure was followed by a short semi-structured interview designed to gather feedback on general experience, equipment comfort, scenario realism, emotional impact, and technical feasibility, consistent with a user-centered design approach. Interviews were audio-recorded and transcribed prior to analysis. An overview of the study procedure is shown in Figure 2.

2.4. Virtual Environments and Scenario Design

The application was developed in the Unity game engine (Unity Technologies, San Francisco, CA, USA) for the Meta Quest 3 VR headset. Candidate scenarios were identified through our systematic review of VR/video exposure and symptom-provocation paradigms in generalized anxiety disorder and related populations [38]. These candidates were then refined in a scenario-selection study using therapist and patient ratings [33]. In our systematic review, thematic analysis identified recurrent categories of uncertainty, social evaluation, and physical threat; these are consistent with prior accounts of common GAD concerns [3,39,40] and with VR scenarios used in related work [41,42,43,44]. The four virtual environments, including the relaxation scene, are described in Table 2 and shown in Figure 3.

2.5. Data Analysis

2.5.1. Quantitative Analysis

Quantitative analyses were conducted in Python using pandas, numpy, statsmodels, scipy, and matplotlib. Descriptive statistics were used to summarize sample characteristics, physiological parameters, and post-session scale scores, with categorical variables reported as counts and percentages and continuous variables as means, standard deviations, and ranges. Statistical significance was evaluated at α = .05. Coefficient-level effects were evaluated with two-tailed z tests, whereas multi-parameter omnibus effects were evaluated with joint Wald chi-square tests. Where multiple related outcomes were tested, p-values were adjusted within outcome families using the Benjamini–Hochberg false discovery rate (FDR) procedure.

Physiological analyses were based on HR and HRV derived from RR intervals. Data were segmented by condition, that is, relaxation versus exposure. The root mean square of successive differences (RMSSD) was used as the primary HRV index. Segments with low signal quality or physiologically implausible RR values were excluded according to prespecified validity thresholds, and RMSSD was analyzed on the log scale when residual diagnostics indicated improved model fit. RR intervals outside 300–2000 ms were treated as invalid; segments were retained only when at least 80% of rows were valid and at least 20 valid RR observations were available, and complete relaxation–exposure cycles were excluded if either segment failed these criteria.

The primary analyses tested whether the protocol induced the intended emotional contrast. For HR and RMSSD, linear mixed-effects models with Participant as a random intercept were fitted with Segment Type and Scenario as fixed effects, with Scenario interaction terms evaluated in full models; model-based exposure-minus-relaxation contrasts were then estimated to test whether contrast magnitude varied across scenarios.

The general model structure was:

Outcome_ij = β₀ + β₁(Predictor_ij) + β₂(Scenario_ij) + β₃(Predictor × Scenario_ij) + u_0j + ε_ij.

(1)

Subjective analyses focused on post-exposure ratings and baseline-referenced change scores calculated relative to the retrospective relaxation baseline. These outcomes were analyzed using mixed-effects models with Scenario as a fixed effect and Participant as a random intercept. IPQ and CSQ-VR scores were summarized descriptively.

To examine whether baseline anxiety severity was associated with physiological reactivity, GAD-7 and its interaction with Segment Type were added to the physiological models. Exploratory analyses also examined associations between physiological contrast indices and post-exposure subjective responding. Model assumptions were inspected using residual diagnostics for primary mixed-effects analyses, and results are reported as parameter estimates, standard errors, 95% confidence intervals, and p-values.

2.5.2. Qualitative Analysis

Interview transcripts were analyzed using the reflexive thematic analysis framework (Braun & Clarke, 2006). A single researcher conducted all coding, supported by NLP-assisted preprocessing, including keyword extraction, semantic clustering, and deviant case flagging, to support organization and data familiarization. Computationally derived groupings served as analytic scaffolding and were reviewed, revised, and interpreted iteratively to ensure themes were internally coherent, meaningfully distinct, and well supported by participants’ accounts. Final themes were developed iteratively and are reported in relation to the study objectives. The semi-structured interview guide is available in the project OSF repository [45].

3. Results

3.1. Quantitative Findings

A total of 20 participants met the inclusion criteria and participated in the study, 35% of whom were women (n = 7). All eligible participants were able to complete the full VR protocol and post-session assessment procedures. Table 3 provides a descriptive overview of the sample and the principal feasibility measures, including baseline anxiety severity, presence (Objective 3), and cybersickness (Objective 2).

3.1.1. Physiological Reactivity

To assess the contrast-inducing potential of the protocol (Objective 1), HR and HRV were examined across relaxation and exposure segments. Analysis of HR revealed a non-significant main effect of Segment Type (β = 0.35 bpm, SE = 0.52, 95% CI [-0.67, 1.38], p = .500), with slightly higher HR during exposure than relaxation segments. Neither the main effect of Scenario (p = .108) nor the Segment Type × Scenario interaction (p = .970) reached significance. In contrast, log-transformed RMSSD showed a significant decrease during exposure segments relative to relaxation (β = -0.185, SE = 0.038, 95% CI [-0.259, -0.111], p < .001), consistent with reduced parasympathetic activity during anxiety induction.

After FDR correction within the physiological outcome family, the Segment Type effect remained statistically significant for RMSSD, whereas the corresponding HR effect did not. Contrast magnitude did not differ reliably across scenarios. Model-estimated marginal means for both physiological outcomes are presented in Figure 4.

3.1.2. Subjective Emotional Reactivity

Complementing the physiological indices of contrast (Objective 1), subjective ratings showed higher distress on SUDS, lower valence, higher arousal, and lower dominance across scenarios during post-exposure ratings. Mixed-effects models of these baseline-referenced change scores indicated a significant overall increase in SUDS, β = 2.23 (SE = 0.45, 95% CI [1.36, 3.11], p < .001), a significant decrease in SAM valence, β = -2.68 (SE = 0.44, 95% CI [-3.54, -1.83], p < .001), a significant increase in SAM arousal, β = 1.95 (SE = 0.57, 95% CI [0.84, 3.06], p < .001), and a significant decrease in SAM dominance, β = -1.70 (SE = 0.60, 95% CI [-2.87, -0.53], p = .005). All four effects remained significant after FDR correction within the subjective outcome family.

Omnibus tests of Scenario were non-significant for all four outcomes (SUDS: p = .197; SAM valence: p = .618; SAM arousal: p = .144; SAM dominance: p = .911), indicating that baseline-referenced subjective change did not vary significantly across scenarios. Descriptively, the largest increase in distress and arousal was observed in Skyline Plank (ΔSUDS = 2.85, 95% CI [1.74, 3.96]; ΔSAM arousal = 2.60, 95% CI [1.26, 3.94]), whereas the largest decrease in valence and dominance was observed in Loose Dog (ΔSAM valence = -2.95, 95% CI [-4.11, -1.79]; ΔSAM dominance = -1.80, 95% CI [-3.16, -0.44]). Scenario-specific comparisons against the relaxation baseline further suggested that SUDS increased and valence decreased significantly for all three scenarios, arousal increased significantly for Skyline Plank and Loose Dog, and dominance decreased significantly for all three scenarios. Participant-level ΔSUDS values by scenario are shown in Figure 5a, and model-estimated changes across all outcomes and scenarios are displayed in Figure 5b.

3.1.3. Associations with Baseline Anxiety

To further evaluate Objective 1, GAD-7 scores were included as a continuous predictor in mixed-effects models to examine whether the contrast-inducing effect varied systematically with baseline anxiety severity. The interaction between Segment Type and GAD-7 was significant for HR (β = -0.296, SE = 0.127, 95% CI [-0.544, -0.047], p = .020) and remained significant after FDR correction, indicating that individuals with higher baseline anxiety showed a reduced HR reactivity during exposure segments. In contrast, RMSSD, indexing parasympathetic activity, showed no comparable moderation by GAD-7. Figure 6 illustrates the interaction effect for HR at low (-1 SD), mean, and high (+1 SD) levels of baseline anxiety.

3.1.4. Subjective–Objective Correspondence

To inform assessment methodology and technical requirements for future clinical iterations (Objective 4), analyses examined whether post-scenario subjective ratings corresponded to physiological reactivity and whether scenario-specific mismatch profiles suggested differential engagement of cognitive versus somatic components of the stress response. Associations between subjective ratings and physiological contrast indices were non-significant, both for ΔHR (β = 0.067, SE = 0.563, 95% CI [-1.036, 1.171], p = .905) and for ΔRMSSD reactivity (β = -0.056, SE = 0.049, 95% CI [-0.152, 0.040], p = .251). Descriptively, Crowded Elevator showed the largest positive mismatch, whereas Skyline Plank showed the largest mismatch in the opposite direction; however, both discrepancies were small. The Loose Dog scenario showed the closest correspondence between subjective and objective responding.

3.2. Qualitative Findings

Thematic analysis identified four themes that closely aligned with the four prespecified study objectives. Overall, the interviews suggested that the application was well received; one participant described it as “one of the most immersive … VR experience[s] I’ve had” (P19).

Participants’ accounts supported Objective 1 by indicating that the protocol produced the intended alternation between relaxation and anxiety-provoking exposure. Several described the shift from the calming garden environment into the first stress scenario as particularly impactful. One participant stated that the transitions were “very powerful” and “very effective to create a sense of anxiety” (P02), while another noted, “I could feel my heart rate growing and changing throughout” (P16). Some participants also described lingering effects beyond the scenario itself; for example, one reported that after the experience “it is taking me some time to really get to the view of [the] world again” (P14). At the same time, emotional impact varied by scenario and by personal relevance. Heights, social closeness, and unpredictability affected participants differently, and several noted that the contrast became less striking once the switching pattern was familiar.

For Objective 2, most participants described the procedure as manageable in terms of comfort and sensor burden. The heart rate sensor was especially well tolerated and was often described as fading into the background; participants reported, for example, “I didn’t think about it at all” (P03) and “I forgot it was there” (P04). The VR headset was also generally acceptable for the duration of the protocol, although some participants reported localized discomfort related to heat, weight, eye strain, or prolonged standing. One participant remarked, “they were quite heavy, and I was sweating under the cushioning” (P05), while others noted that standing for the full session could become tiring or limit accessibility for some users.

Objective 3 was reflected in participants’ descriptions of the scenarios as emotionally engaging even when realism was incomplete. Positive responses were especially evident when the scenario matched a participant’s own sensitivities or felt socially plausible. One participant reported, “with the elevator one I was very immersed” (P20), while another said, “I really felt like I was transported into the scenarios” (P19). However, participants also repeatedly emphasized that visual fidelity shaped the depth and persistence of immersion. As one participant put it, the experience could become “a simple little pixelated world” (P02), and another commented that the avatars “just feel like some dummies and mannequins” (P07). In addition to realism, participants noted that loading artifacts, abrupt scene changes, limited environmental detail, and repetitive or less dynamic animations could weaken presence over time.

Findings relevant to Objective 4 centered on usability, feasibility, and priorities for future refinement. Instructions were generally described as clear, and many participants found the pacing and pauses sufficient to support recovery between scenarios. At the same time, the breathing guidance and in-VR ratings emerged as the two most consistent sources of friction. Although breathing instructions were usually understandable, some participants found the pace too fast, the visual cues insufficiently smooth or intuitive, or the environment too stimulating for relaxation. One participant noted that “the breathing actually kind of forced me to go like a little faster” (P20). Similarly, the SUDS and SAM ratings were typically learnable after one or two trials, but participants pointed to issues with slider precision, unclear anchors, readability, mixed visual formats, and the effort of completing some forms in VR. Several also suggested that more in-app prompting or onboarding would help users know when and how to respond. Participants also viewed the application as broadly feasible and potentially useful, particularly as a safe and controlled way of eliciting emotionally relevant experiences. One participant explicitly described it as “a safe way of doing it” (P12). Most participants felt that other users could complete the study, although some noted that additional support might be useful for those unfamiliar with VR or less able to tolerate standing, text entry, or controller-based interaction. Across interviews, the most common improvement targets were clearer in-app guidance, reduced burden for nonessential VR-based data entry, more intuitive and readable rating interfaces, smoother and more effective relaxation cues, and greater visual and behavioral realism within the scenarios. The frequency of feedback for each theme is detailed in Table 4.

4. Discussion

Taken together, the findings broadly support the feasibility of the protocol across all four objectives: physiological and subjective indices suggested genuine affective shifts during exposure (Objective 1), wearables and VR hardware were generally well tolerated (Objective 2), presence was sufficient to elicit emotional engagement (Objective 3), and participants identified concrete priorities for refinement (Objective 4).

4.1. Contrast-Inducing Potential

Together, the physiological and subjective findings supported the contrast-inducing potential of the protocol. While HR did not show a significant overall effect, RMSSD provided the main physiological evidence of differentiation between relaxation and exposure, likely because it is more sensitive to rapid parasympathetic shifts than mean HR and can detect change more reliably in brief recording windows [46,47]. The significant subjective shifts observed across all four affective dimensions alongside this physiological pattern further suggest that the protocol elicited genuine affective contrast rather than merely demand-driven responding, consistent with prior VR anxiety induction work [17,19]. Notably, baseline anxiety severity significantly moderated HR reactivity, with higher GAD-7 scores associated with attenuated autonomic differentiation between relaxation and exposure segments. This aligns with CAM’s core prediction that sustained anticipatory arousal narrows the dynamic range of subsequent physiological responses [10,12] and extends laboratory-based observations of reduced emotional variability in chronic anxiety to a controlled VR paradigm [11,15,48,49].

Although physiological and subjective measures shifted in the expected direction, they were not significantly correlated at the individual level: participants reporting greater subjective distress did not necessarily show greater autonomic reactivity. This pattern is consistent with response desynchrony, in which subjective and physiological components of fear do not necessarily co-vary [50,51], and theoretically expected in GAD, where sustained worry may inhibit somatic activation [10,11,15].

Qualitative accounts also supported the overall pattern of contrast induction. Participants described noticeable transitions from calm to stress, with several reporting these shifts as physically palpable. At the same time, emotional impact varied with personal relevance and novelty: in the interviews, some participants reported that the contrast felt weaker once the switching pattern became familiar, and different triggers resonated differently across individuals. This suggests that contrast potency depends not only on stimulus intensity but also on how personally relevant and how novel or unpredictable a scenario remains to the individual [3].

4.2. User Comfort and Wearable Burden

Cybersickness scores were low and within acceptable ranges for modern consumer VR environments [36,37], indicating good overall tolerability. The Polar H10 heart rate sensor, previously validated for HRV measurement in resting and active conditions [27], imposed minimal burden and functioned without interruption across sessions.

Qualitative feedback was also consistent with this pattern: participants often described the sensor as fading from awareness, and the VR headset was generally acceptable, although some reported heat, weight, eye strain, and discomfort during prolonged standing. Standing emerged as the main physical concern and led to revision of the protocol to a seated format, along with an improved VR headset strap and silicone facial cushion.

4.3. Immersion and Presence

IPQ scores indicated moderate presence overall, with spatial presence and general presence scoring higher than realism, which was negative on average. This pattern is consistent with prior work showing that VR-based anxiety paradigms do not require perfect perceptual convincingness to elicit emotional engagement, and that moderate immersion can be sufficient to support affective responding [21,22]. In this context, the presence scores suggest that the protocol was immersive enough to engage participants emotionally, while the lower realism scores point to visual fidelity as the main target for improvement.

Qualitative feedback clarified this pattern further. Participants described genuine immersion, particularly in the elevator and height scenarios, but also identified avatar quality, environmental detail, scene transition smoothness, and repetitive animations as factors that weakened sustained presence. These concerns informed refinements to scene detail, character movement, background activity, and transition smoothness.

4.4. Technical Requirements and Future Directions

From an assessment standpoint, the scenario-specific mismatch profiles observed in the correspondence analyses suggest that subjective and physiological measures are not fully interchangeable and may capture partly distinct aspects of the stress response. With Crowded Elevator showing relatively stronger objective activation and Skyline Plank the reverse, these findings support retaining multimodal assessment in future clinical iterations rather than relying on either index alone, and further support individualized scenario selection to match exposure content to a patient’s dominant worry profile [3,39,50,51].

Qualitative feedback identified several refinement priorities that were incorporated into the revised protocol. Breathing guidance was simplified through softer, slower voice instructions, more linear and pronounced cues, and a less visually complex daytime relaxation environment. In-VR ratings and onboarding were streamlined through clearer endpoint labels and anchors, mandatory item completion, a tutorial with spoken prompts, relocation of intake measures to a tablet, and hand tracking to reduce controller burden. Application-controlled volume standardization addressed session-to-session inconsistency. More broadly, given the substantial individual variability observed in our participants’ responses, future iterations could also benefit from flexible relaxation options, vary scenario content across sessions, and allow adjustment of exposure intensity to better match individual tolerance and therapeutic needs [10,12].

4.5. Limitations

Several limitations should be considered when interpreting these findings. First, the modest sample size limited statistical power, particularly for detecting interaction effects, and constrains the precision of parameter estimates; accordingly, moderation findings should be interpreted cautiously pending replication in larger samples.

Second, the use of a subclinical sample, while appropriate for feasibility testing, limits generalizability to clinically diagnosed populations, who may exhibit different patterns of autonomic flexibility or habituation.

Third, although the protocol incorporated repeated relaxation–exposure transitions, the absence of a prolonged resting baseline outside VR restricts inferences about absolute autonomic set points, emphasizing within-session contrasts rather than trait-level differences.

Additionally, subjective measures (SUDS and SAM) were collected immediately post-exposure, whereas relaxation-period ratings were obtained retrospectively to avoid disrupting the intended contrast; this introduces potential recall bias and limits resolution of moment-to-moment subjective variation. This issue has been addressed in subsequent iterations by incorporating a rateable relaxation segment following exposure.

Collectively, these limitations highlight the need for replication in larger and more diverse samples, as well as longitudinal designs to assess whether repeated exposure to controlled emotional contrast yields durable changes in physiological and subjective reactivity.

5. Conclusions

The findings of this study support the feasibility of a VR-based protocol designed to operationalize emotional contrast in accordance with the Contrast Avoidance Model. Repeated transitions between guided relaxation and immersive threat scenarios produced measurable autonomic and subjective shifts within a single VR session, indicating that the system can reliably induce the targeted relaxation-to-exposure contrast across multiple thematic domains of anxiety. Consistent with theoretical expectations, higher baseline anxiety severity was associated with attenuated autonomic reactivity, highlighting the importance of accounting for chronic affective state when interpreting acute stress responses. From a usability perspective, the protocol was well tolerated, with acceptable levels of comfort related to wearable sensors, minimal cybersickness, and sufficient immersion and presence to support emotional engagement despite limitations in visual fidelity. Participant feedback yielded specific and actionable insights that directly informed iterative improvements, addressing key technical considerations for future clinical implementation. Collectively, these results establish a methodological foundation for the controlled induction of emotional contrast within VR; however, whether modulation of such contrast represents a viable therapeutic target remains an open question for future clinical investigation.