Visual communication design in laboratory safety effectiveness and optimization of warning signs

Abstract

This study proposes a comprehensive framework for evaluating and optimizing laboratory warning sign systems, grounded in the principles of visual communication design, cognitive psychology, and safety management. A mixed-methods experimental design involving 120 participants was employed, integrating eye-tracking analysis, comprehension and memory assessments, and behavioral response evaluations. The results identified key factors contributing to the effectiveness of warning signs, including color contrast ratio, symbol standardization, and information hierarchy. A validated optimization procedure was developed, emphasizing visual detectability, information organization, and contextual relevance. It led to significant improvements in attention capture (35.9%), hazard detection accuracy (42.3%), and procedural compliance (37.8%). Evidence-based design specifications for laboratory warning signs were established to balance standardization requirements with the need for contextual adaptation across diverse laboratory environments. These specifications were further validated through a case study conducted at Fujian University of Technology, demonstrating the effective translation of theoretical frameworks into enhanced safety communication practices.

Introduction

Laboratory safety management is a critical concern in both industrial and academic settings, given the wide range of hazards that pose risks to personnel, equipment, and the surrounding environment¹. Among various protective strategies, effective safety communication via warning signals is essential for both accident prevention and regulatory compliance. However, laboratory warning signs are frequently poorly designed, inconsistently implemented, and insufficiently effective in conveying critical safety information². The effectiveness of such signals hinges on their ability to capture attention, convey relevant information, and prompt appropriate behavioral responses. As noted by Laughery and Wogalter, many warning systems fail due to deficiencies in detectability, comprehensibility, or alignment with expected behavioral responses³. As laboratories increasingly incorporate complex equipment, hazardous chemicals, and intricate procedures, the need for robust and reliable safety communication has become more urgent than ever.

Beyond practical limitations, inadequate warning design also carries broader implications for overall safety. Research on warnings and risk communication has shown that deficiencies in detectability, comprehensibility, and actionability are closely linked to human errors, unsafe behaviors, and non-compliance with safety procedures^3,4. Cross-cultural studies further indicate that symbol comprehension varies considerably across different user groups⁵, suggesting that even standardized signs may be subject to inconsistent interpretations in diverse laboratory settings. As Reason argued in his seminal work on human error, latent design flaws can escalate into systemic failures if not mitigated through structured communication strategies⁶. These insights underscore the pressing need for warning sign design specifications that are not only standardized but also contextually adaptable, thereby providing a strong rationale for the present study.

International and national design standards have long provided widely adopted baselines for visual safety communication. For example, ISO 3864 and ISO 7010 define safety colors and symbols; the ANSI Z535 series outlines product and environmental labeling practices; and the Globally Harmonized System (GHS) mandates the use of chemical hazard pictograms. Although these standards ensure baseline consistency across industries, their direct application in laboratory environments reveals critical limitations. Laboratory settings are characterized by overlapping hazards, high information density, and heterogeneous user groups, which are factors that often fall outside the scope of generic signage standards. Moreover, existing standards rarely account for contextual adaptability, cognitive demands, or interdisciplinary research environments. It is precisely this limited applicability of current design standards to complex laboratory settings, rather than inconsistent implementation, that motivates the present study.

The aim of this study is to bridge the theoretical foundations of visual communication design with their practical application in laboratory warning signage specifications. Guided by a multidisciplinary perspective, this research integrates visual communication, cognitive psychology, and human factors engineering to develop a comprehensive framework for evaluating and improving the effectiveness of warning signs. Using a mixed-methods approach that combines eye-tracking, comprehension assessments, memory tasks, and behavioral response evaluations, the study examines the key factors that influence the functioning of warning signs in laboratory contexts. Building on these findings, the study proposes evidence-based strategies to optimize visual processing, information transfer, and compliance behavior, with the ultimate goal of enhancing laboratory safety⁷.

The methodological framework builds on research-based guidelines developed by Wogalter and Conzola³ and extends their applicability to laboratory environments, where multiple hazards coexist and necessitate integrated communication strategies. Within the specific operational constraints of laboratories, the study proposes design solutions that address context-sensitive challenges identified in previous research. Lesch⁷ demonstrated that symbolic warning design influences hazard recognition and memory, thereby providing a foundation for investigating how enhanced visual features can improve safety outcomes. Through a systematic assessment of warning sign effectiveness across diverse laboratory disciplines and operational conditions, this research establishes evidence-based design principles that are scientifically validated and widely applicable. The resulting framework provides a validated methodology that links theoretical understanding with practical implementation. This approach addresses the limitations of generic standards and advances the management of laboratory safety.

Theoretical foundation and current status analysis

The theoretical foundation of laboratory warning sign design is grounded in safety management, visual communication design, cognitive psychology, and human factors engineering⁸. Safety management provides fundamental principles for identifying and mitigating hazards, while visual communication design offers strategies for delivering critical information through effective use of visual elements. The cognitive processing of warning signs follows the Communication–Human Information Processing (C-HIP) model proposed by Wogalter and Laughery⁹, which outlines a sequence in which information is transmitted, processed cognitively, and ultimately translated into behavior. Color is one of the most salient design variables, and research by Zielinska et al.¹⁰ shows that carefully applied color coding can significantly improve hazard identification and convey a sense of urgency. Symbols are equally important because graphical representations transcend language barriers and communicate hazards more rapidly than text-based descriptions.

The integration of these disciplinary perspectives enables a holistic understanding of how warning signs function within complex laboratory environments. The C-HIP model is particularly valuable because it breaks down the information processing chain into discrete stages, including attention capture, attention maintenance, comprehension, attitude and belief formation, motivation, and behavioral response. Each of these stages represents a potential point of failure, at which users may ignore, misinterpret, or disregard safety information. As such, the model emphasizes the importance of designing warning signs that guide users smoothly through the full sequence, rather than focusing solely on visibility or comprehension. The application of color psychology, as examined by Braun and Silver¹¹, demonstrates that associations between specific colors and perceived danger levels are deeply embedded in cognitive structures: red is most consistently linked to the highest level of threat, followed by orange, yellow, and blue. These associations affect both conscious and pre-attentive processing, making the systematic use of color a critical component of effective hazard communication. Similarly, symbol comprehension depends on multiple factors identified by Hancock et al.¹², including visual discriminability, semantic clarity, and prior exposure. Their findings indicate that comprehension rates vary significantly by age, experience, and cultural background, highlighting the importance of design specifications that are standardized yet adaptable to diverse laboratory user populations.

Empirical evidence regarding laboratory safety signage reveals a substantial gap between theoretical expectations and practical implementation. A comprehensive review of 35 university laboratories by Zhang and Chan¹³ found that the average comprehension rate of safety signs was only 68.5%, with particularly low understanding of specialized hazard symbols. The current state of laboratory warning signage is marked by persistent problems, including the limited applicability and inconsistent use of visual communication principles¹⁴, insufficient attention to context-specific factors in laboratory settings¹⁵, and excessive information density that undermines user comprehension and behavioral compliance¹⁶. Even in educational institutions where formal safety training is provided, the effectiveness of warning signage often falls short of expected standards. As noted by Reniers et al.¹⁴, inconsistencies in color schemes, typography, and symbol design force users to navigate multiple visual languages, thereby creating cognitive challenges. Fernandes et al.¹⁵ further point out that contextual factors such as viewing distance, lighting conditions, and competing visual stimuli exert strong influences that are frequently overlooked by standardized procedures. Lehto¹⁶ demonstrates that when multiple hazards are presented simultaneously, signage clutter can overwhelm users’ cognitive capacity, thus diminishing rather than enhancing safety awareness.

The primary challenges in laboratory warning sign design lie in striking a balance between informational detail and visual clarity, accommodating users with varying levels of expertise, and adapting to complex and dynamic environments¹⁷. The global nature of modern research laboratories introduces additional complexity, as linguistic and cultural differences profoundly shape hazard perception and risk communication. Salazar et al.¹⁷ stress the necessity of design specifications that effectively communicate with both novice students and experienced researchers, potentially requiring adjustments in information density and technical content based on user profiles. This study addresses these shortcomings by proposing a systematic approach to testing and optimizing laboratory warning signs, combining theoretical models with empirical validation conducted under real-world laboratory conditions. By applying the C-HIP model⁹ and incorporating the contextual factors identified in recent studies^{13,14,15,16,17}, the research aims to develop standardized yet adaptable design specifications that effectively bridge the gap between theoretical understanding and practical application.

Laboratory warning sign effectiveness evaluation research

To clarify the scope and methodological structure of the study, Fig. 1 presents a schematic research roadmap that links the research objectives, methods, and outcomes. The study design integrates four complementary components: (1) development of an evaluation indicator system based on the C-HIP model; (2) controlled laboratory experiments and quasi-field observations incorporating eye-tracking, comprehension, memory, and behavioral tests; (3) collection of qualitative user feedback to capture experiential perspectives; and (4) validation experiments conducted under realistic laboratory conditions to test optimized prototypes. Each methodological component corresponds directly to the results presented in the section “Warning sign optimization design and verification”. Specifically, the sections “Optimization design principles and methods”, “Visual elements and information transmission optimization”, “Environmental integration and systematic design” report findings from controlled and field experiments, the section “Validation experiments and results analysis” presents the validation results, and qualitative feedback is integrated to complement the quantitative analyses. This clear alignment ensures that all methods are transparently reflected in the results, enabling a coherent progression from theoretical design principles to empirical validation.

Fig. 1

Research roadmap outlining the theoretical foundations, methodological components (indicator system, experimental tests, validation), and application of optimized warning sign systems.

Evaluation indicator system and experimental design

The development of a comprehensive evaluation indicator system is essential for assessing the effectiveness of laboratory warning signs. Grounded in the C-HIP model⁹, this research constructs a four-dimensional indicator system encompassing perception, comprehension, retention, and behavioral response. Each dimension is associated with specific metrics, as shown in Table 1. These criteria are explicitly linked to the sequential stages of user processing defined by the C-HIP framework, including attention, comprehension, memory, and behavior. For instance, the perception dimension aligns with the attention stage; comprehension and retention reflect the information processing and memory stages; and the response dimension corresponds to observable user behaviors. In addition, the specific metrics were informed by established guidelines for warning design and evaluation³, ensuring that each criterion is grounded in a clear theoretical basis.

Table 1 Laboratory warning sign effectiveness evaluation indicator System.

The research adopts a mixed-methods strategy, combining quantitative measures with qualitative assessments. Following the approach outlined by Zhang and Chan¹³ and extended by Fernandes et al.¹⁵, the experimental design comprises three phases: (1) controlled laboratory experiments, (2) quasi-field observations, and (3) validation studies. This triangulated design enhances both the methodological rigor and ecological validity of the findings.

Participants were recruited through stratified and purposive sampling to ensure representation across distinct user groups, including laboratory technicians, students, researchers, and administrative personnel. This heterogeneity enabled an analysis of how user experience and domain knowledge influence the interpretation of warning signs, consistent with prior findings by Hancock et al.¹² that highlight significant user variability.

Four distinct experimental tasks were designed, each aligned with one of the evaluation dimensions. Eye-tracking tests assessed attentional allocation (perception), comprehension tasks measured message understanding, memory tasks evaluated retention of hazard information, and behavioral observations in simulated hazard scenarios captured actual response behaviors. Collectively, these measures provided an integrated assessment of the entire information-processing sequence.

Finally, experimental variables were systematically manipulated to examine contextual influences, including design-related factors (e.g., color, typography, symbols, layout), viewing conditions (e.g., distance, angle, lighting), user characteristics (e.g., experience level, training, cultural background), and environmental factors (e.g., visual distractions, task complexity).

Data collection and analysis methods

Data collection employed a mixed-methods approach that combined both quantitative and qualitative techniques to provide a comprehensive evaluation of warning sign effectiveness. An overall appraisal was conducted for each evaluation dimension, integrating objective performance metrics with user-reported feedback. The quantitative dataset was collected from 120 participants through controlled experiments, including eye-tracking metrics (fixation duration, dwell time), comprehension and memory test scores, and behavioral response observations. Simultaneously, qualitative feedback was obtained during post-test debriefings, where participants shared their perceptions regarding clarity, cognitive load, and contextual relevance. These qualitative insights were later used to contextualize and enrich the statistical results.

The data presented in Table 2 were derived directly from the original dataset, integrating quantitative performance indicators with subjective user ratings. Task sequences were counterbalanced to control for learning effects. Eye-tracking data were processed using Tobii Pro Lab, while comprehension and memory were scored using standardized procedures. Statistical analyses were conducted using repeated-measures ANOVA, and effect sizes were reported to ensure that the findings are both reproducible and interpretable. In addition, a final validation experiment was designed to test optimized warning sign prototypes under realistic laboratory conditions, with detailed procedures and results reported in the section “Validation experiments and results analysis”.

Table 2 Data collection methods and analysis Techniques.

The Tobii Pro Spectrum eye tracker was employed for visual attention data collection at a sampling rate of 1200 Hz, enabling high-resolution analysis of gaze patterns. Participants viewed a sequence of laboratory warning signs on a 24-inch display in a light-controlled environment. Predefined Areas of Interest (AOIs) were designated for the signal word, pictogram, and instructional message, allowing for detailed analysis of attention allocation. Comprehension and memory were evaluated using standardized questionnaires administered before exposure, immediately after exposure, and one week later, thereby assessing both short-term understanding and longer-term retention. Behavioral responses were measured through simulated laboratory scenarios, in which participants encountered hazard cues and were required to respond in accordance with the presented warning information.

Data analysis followed a structured mixed-methods framework. Quantitative data were analyzed using SPSS 26.0, including descriptive statistics for all indicators and inferential analyses such as ANOVA, multiple regression, and factor analysis to examine significant relationships and predictive variables. Eye-tracking data were processed in Tobii Pro Lab to generate heat maps, gaze plots, and AOI-specific metrics (e.g., time to first fixation, fixation duration, number of visits). Qualitative data from post-test interviews and open-ended responses were analyzed using Braun and Clarke’s six-step thematic analysis framework. Triangulation was employed to synthesize quantitative and qualitative findings, with convergence enhancing internal validity and divergence identifying areas for further investigation.

Despite the methodological rigor, potential confounding variables must be acknowledged. The heterogeneous participant sample introduced variability in educational background, cultural norms, and visual literacy, all of which may have influenced symbol recognition, hazard message comprehension, or sustained visual attention. Although stratified and purposive sampling strategies ensured cross-group representation, it was not possible to control for all inter-group differences. Future research should systematically investigate these factors—for example, through cross-cultural comparisons or stratified analyses by user expertise—to enhance the generalizability of the findings.

Results analysis and key factors identification

The evaluation of laboratory warning sign effectiveness yielded consistent and statistically significant results across all dimensions of the assessment framework. Eye-tracking data revealed distinct visual attention patterns closely associated with sign effectiveness. As illustrated in Fig. 2, effective warning signs elicited a characteristic triangular scanning sequence, beginning with fixations on the pictogram (58.3%), followed by the signal word (26.5%), and concluding with the instructional text (15.2%). In contrast, ineffective signs produced dispersed and unstructured gaze patterns, reflecting the absence of a clear visual hierarchy and indicating reduced cognitive processing efficiency.

Fig. 2

Analysis of Visual Attention Patterns for Laboratory Warning Signs.

Statistical analysis further identified the most influential design factors contributing to effectiveness. As summarized in Table 3, multiple regression analysis revealed three significant predictors: color contrast ratio (β = 0.42, p < 0.001), use of standardized symbols (β = 0.38, p < 0.001), and clarity of textual information (β = 0.35, p < 0.001). Together, these variables accounted for 76.3% of the variance in effectiveness ratings (adjusted R² = 0.763, F(3,116) = 124.87, p < 0.001). These findings underscore that perceptual salience, semantic standardization, and textual clarity serve as primary drivers of effective warning sign design.

Table 3 Key factors influencing laboratory warning sign Effectiveness.

A comparative analysis across laboratory disciplines revealed discipline-specific variation in warning sign recognition. Chemical laboratories exhibited the highest recognition rates (M = 82.6%, SD = 6.8%), followed by biological (M = 78.3%, SD = 7.2%), physical (M = 75.9%, SD = 8.1%), and engineering laboratories (M = 72.4%, SD = 9.2%). These discrepancies were primarily attributable to differences in hazard awareness and safety training across disciplines, rather than intrinsic design deficiencies in the signs themselves. Factor analysis identified four latent dimensions underlying warning sign effectiveness: visual saliency (32.6% of variance explained), information clarity (27.8%), contextual suitability (18.4%), and alignment with user needs (12.5%). Collectively, these findings emphasize the necessity of integrated design strategies that address perceptual, informational, contextual, and user-centered elements in a unified manner, rather than treating these dimensions in isolation.

Warning sign optimization design and verification

Optimization design principles and methods

Perceptual optimization aimed to enhance the relative salience of warning signs by structuring visual elements to guide attention toward high-priority content. Grounded in the attention-prioritization theory proposed by Laughery and Wogalter¹⁸, layouts were designed to elicit rapid pre-attentive detection, sustained gaze fixation, and efficient information uptake. To achieve this, high luminance contrast (≥ 7:1) and discipline-specific chromatic coding (e.g., red for fire, yellow for chemical hazards, blue for required actions) were applied to reduce search time and mitigate ambiguity. As illustrated in Fig. 3, design improvements proceeded through an evidence-based, iterative process that included identifying deficits from evaluation data, formulating testable hypotheses, prototyping, and validating results. Each cycle was intended to address specific processing bottlenecks, such as delayed initial fixation or symbol misclassification. Across iterations, the optimized prototypes consistently met or exceeded predefined performance benchmarks for attention, comprehension, memory, and compliance.

Fig. 3

Iterative optimization process for laboratory warning sign design.

To capture the interdependent effects among design features, a factorial experimental design was implemented. This approach enabled the systematic estimation of both main and interaction effects, clarifying how combinations of color contrast, symbol size, text conciseness, information hierarchy, and contextual adaptation jointly influenced user responses. A total of 243 design permutations were evaluated through computational modeling and expert review, with the goal not merely to rank design alternatives, but to identify synergistic combinations that maximize cognitive efficiency. As a result, informational optimization was not approached as a matter of aesthetics alone, but rather as a strategy for aligning message structure with the sequential stages of cognitive processing identified in prior empirical research. As summarized in Table 4, design specifications for signal words, pictograms, and instructional text were derived from international safety standards (ISO 3864, ISO 7010, ANSI Z535, GHS pictograms), field observations conducted in 24 laboratories, and repeated expert consultations. These specifications were subsequently refined through factorial experiments and computational modeling to ensure both theoretical validity and contextual adaptability.

Table 4 Specifications for warning sign components based on cognitive processing Optimization.

The integration strategy explicitly acknowledged the critical influence of environmental factors on the visibility and effectiveness of laboratory warning signs. To accommodate these factors, modular design templates were developed for each laboratory type, including chemical, biological, physical, and engineering contexts, in order to enable discipline-specific customization while maintaining a consistent and coherent design language. Contextual noise was analyzed using digital image-processing techniques, with the objective not only of optimizing contrast but also of maximizing the signal-to-noise ratio between warning signs and their surrounding visual environment, thereby improving hazard detectability. Equally important, a user-centered design approach was adopted. Participatory design sessions involving staff from a wide range of laboratory settings revealed substantial differences in expectations and information needs, which were shaped by varying levels of expertise, cultural background, and perceptual capability. This integrative design process, which combined international safety standards, empirical field data, and direct user input, ensured that the final design principles were both scientifically robust and practically applicable. The overall strategy is aligned with Reason’s “defense-in-depth” safety framework¹⁸, which conceptualizes warning signs as a foundational layer within a broader system of complementary safety defenses intended to prevent laboratory-related incidents.

Visual elements and information transmission optimization

The optimization of visual elements and information transmission was identified as a critical determinant of warning sign effectiveness. Building on the assessment results, the study implemented an evidence-based approach that emphasized both perceptual salience and cognitive processing efficiency. Eye-tracking analyses confirmed that systematic adjustments to visual parameters led to substantial improvements in user performance, with attention capture increasing by 37.8% and information processing speed by 42.3%. Four core dimensions—color properties, spatial layout, typographic design, and symbolic notation—were refined within an integrated framework aimed at maximizing visibility and minimizing cognitive load, rather than being treated as independent variables.

As shown in Fig. 4, color optimization was informed by colorimetric analysis and psychophysical testing, which demonstrated that contrast thresholds function in a non-linear manner. Notably, performance gains became pronounced when luminance ratios exceeded the critical value of ≥ 7:1, thereby ensuring legibility even under suboptimal laboratory lighting conditions. Spatial layout adjustments reinforced the principle of visual hierarchy by positioning hazard cues before supplementary details, aligning the information structure with the natural sequence of cognitive processing. By redistributing visual weight to emphasize hazard recognition followed by classification and precautionary actions, the redesigned layouts improved sequence coherence by 63.4% compared to baseline signage.

Fig. 4

Relationship between chromatic contrast ratio and warning sign detection distance in laboratory environments.

Typographic enhancements were targeted at improving legibility and comprehension by tailoring font attributes to functional demands across different categories of information. As summarized in Table 5, the specifications for signal words, hazard descriptions, and precautionary instructions were selected not arbitrarily, but rather to ensure that each textual element corresponded to its cognitive role—whether to capture attention, facilitate hazard identification, or guide behavioral responses. Symbol design followed the principles of standardization and semantic clarity. ISO and GHS conventions were applied wherever applicable, and laboratory-specific icons were redesigned to enhance feature distinctiveness and interpretability. Comprehension testing showed that these refinements raised accuracy to 91.3%, compared to 68.7% for the baseline symbols, thereby demonstrating the effectiveness of semantic enrichment and visual consistency. Lastly, the sequencing of information flow was guided by the C-HIP model, progressing from attention capture to hazard identification, risk description, and recommended actions. This hierarchical organization reduced cognitive processing time by 24.7% and improved compliance accuracy by 31.9%, indicating that effective warning sign design depends not only on visual salience but also on alignment with the user’s cognitive processing sequence. The typographic and symbolic specifications presented in Table 5 thus represent a combination of international standards (e.g., ISO 3864, GHS pictograms) and empirically validated parameters, derived from eye-tracking data and comprehension testing. This dual foundation ensures that the final design recommendations are both standards-compliant and evidence-driven.

Table 5 Typographic parameter optimization for warning sign information Categories.

Environmental integration and systematic design

The effectiveness of laboratory warning signs depends not only on their inherent design features but also on how well they are integrated into the built environment. Environmental integration aims to ensure that signs function synergistically with their physical surroundings, thereby enhancing visibility, attention capture, and information delivery across diverse laboratory conditions. To support this goal, a flexible yet consistent framework was developed that considered factors such as sign placement, lighting conditions, and workflow dynamics, enabling context-specific adaptation while maintaining system-wide visual coherence.

Analysis of 24 laboratory configurations emphasized the critical influence of spatial factors, including line of sight, viewing distance, physical obstructions, and ambient lighting variability. As shown in Fig. 5, which compares detection effectiveness across laboratory types and zone categories, visibility varied significantly across workstation types. Localized environmental conditions often played a more decisive role than overall layout, especially in areas such as storage zones and shared equipment areas. By modeling these contextual variables, optimal placement strategies were identified, resulting in a 43.2% improvement in visibility compared to conventional mounting practices. These findings highlight that environmental integration is not merely a matter of standardized positioning, but rather a systematic process of aligning sign location with user perception and task context.

Fig. 5

Analysis of Viewing Zone Effectiveness Across Laboratory Configurations. The heatmap shows detection rates of warning signs across four laboratory disciplines and four location types, measured with eye-tracking and detection tests (n = 48). Warmer colors indicate higher visibility. Results highlight strong context effects, with the lowest visibility in chemical lab shared equipment areas (62.0%) and the highest in chemical lab entrance zones (91.0%).

The design framework employed a hierarchical signage deployment strategy, ensuring that hazard communication was structured into distinct but complementary layers. This stratification enhanced both clarity and redundancy, facilitating information delivery across varying levels of user engagement. As summarized in Table 6, the system addressed both spatial and temporal aspects of laboratory operation. For example, photoluminescent materials and high-contrast schemes (≥ 9:1) improved emergency lighting performance to 87.3%, while color-coded floor markings reduced attention failure by 67.9% in high-activity zones. These specifications were derived from field observations across 24 labs, refined through consultation with safety professionals, and validated in controlled experiments described in the section Validation experiments and results analysis—thus directly linking design interventions to measurable gains in hazard recognition and procedural compliance.

Table 6 Environmental adaptation strategies for warning sign system Implementation.

The development of this comprehensive warning system was guided by the principle of contextual coherence, allowing for environmental flexibility without compromising overall consistency. A modular design architecture based on interchangeable components enabled localized adjustments to spatial constraints, such as ceiling-mounted signage in crowded laboratories, while preserving the cognitive advantages of a standardized visual language. This balance between adaptability and uniformity ensured that users across laboratories could rely on familiar visual cues, regardless of specific lab configurations.

Cross-disciplinary analysis further demonstrated that, while the core principles of environmental integration remained stable, their implementation required discipline-specific customization. For instance, chemical laboratories benefited most from storage-integrated labeling, enhancing visual continuity in frequently accessed zones (e.g., 78.0% effectiveness in Fig. 5). In contrast, engineering laboratories showed the highest gains in entrance and shared-equipment zones, where integrated signage with operational controls and QR-linked instructions raised procedural compliance by up to 78.4%, as noted in Table 6. These results underscore the importance of a dual approach: shared design principles ensure coherence, while tailored strategies ensure operational relevance across diverse laboratory environments.

Validation experiments and results analysis

The effectiveness of the optimized prototypes was assessed through a series of validation experiments designed to replicate real-world laboratory conditions. A mixed-methods evaluation framework was adopted, integrating quantitative performance metrics with qualitative user feedback to ensure both statistical rigor and experiential insight. A pre–post intervention design was employed, allowing direct comparisons between baseline signage and the optimized system, and ensuring that observed improvements could be attributed to design enhancements.

The validation sample included 120 participants representing a range of laboratory disciplines and occupational roles, thereby ensuring generalizability to real laboratory populations. By combining eye-tracking indicators of attentional allocation with assessments of comprehension, recall, and behavioral response, the study evaluated both perceptual and cognitive-behavioral dimensions of sign effectiveness.

Participants were recruited voluntarily from four laboratory departments, with quotas used to balance experience levels (novice, intermediate, expert) and occupational roles (researcher, technician, student, and administrative staff). Random assignment to experimental conditions was implemented, and exposure orders were counterbalanced using a Latin square design to control for potential order effects. Eye-tracking data were collected using a Tobii Pro Spectrum system at 120 Hz, calibrated via a standard 9-point procedure. Participants with a tracking ratio below 80% or calibration errors exceeding 1° of visual angle were excluded from analysis. Repeated-measures ANOVA was used to analyze the data, and effect sizes were reported to ensure interpretability. Eye movement data were used to construct scan sequences across defined Areas of Interest (AOIs), including pictograms, signal words, and instructional text. Results indicated that a triangular scan trajectory emerged as the dominant pattern among participants, confirming the designed visual hierarchy.

As illustrated in Fig. 6, the optimized signage system achieved significant improvements across all four laboratory disciplines, including chemical, biological, physical, and engineering labs. Improvements were observed across four key performance metrics: visual perception, information comprehension, memory retention, and behavioral response. The chemical laboratory group achieved the highest overall improvement (67.0%), followed by biological (61.4%), physical (57.2%), and engineering laboratories (52.9%). These findings confirm not only the statistical significance of the improvements but also the robustness and generalizability of the optimization strategy across laboratory contexts.

Fig. 6

Comparative Analysis of Warning Sign Optimization Effectiveness Across Laboratory Disciplines. Bars show percentage gains of optimized signs over baseline signs in four dimensions (visual perception, comprehension, memory, behavior) across four laboratory types (n = 120, pre–post design). Significance: *** p < 0.001, ** p < 0.01, * p < 0.05.

The improvement rates in core metrics—attention capture (+ 35.9%), comprehension accuracy (+ 30.4%), and compliance behavior (+ 37.8%)—were derived directly from the validation experiments (n = 120) using a pre–post comparison design. All differences were statistically significant at p < 0.01 (repeated-measures ANOVA), with medium-to-large effect sizes (η² = 0.24–0.37). Beyond statistical significance, the results offer practical implications for laboratory safety. Faster attention capture reduces the likelihood of delayed hazard recognition, which is a known precursor to laboratory accidents. Enhanced comprehension and memory improve procedural adherence, thereby reducing the risk of unsafe practices. Higher compliance rates translate into measurable reductions in safety incidents, given the established relationship between protocol non-compliance and laboratory accidents. Overall, these results suggest that the optimized warning signs not only improve cognitive performance but also contribute to tangible improvements in safety outcomes.

In addition to quantitative results, qualitative feedback collected during post-test debriefings provided complementary insights. Participants consistently reported that the optimized signs were clearer, less mentally taxing, and more attuned to actual laboratory workflows compared to the baseline designs. Several respondents emphasized that the standardized pictograms reduced ambiguity, while the hierarchical structure of information facilitated faster hazard recognition and decision-making. These subjective impressions reinforce the quantitative findings, demonstrating that the improvements were not only statistically significant but also perceived as meaningful and actionable by users in real operational settings.

Laboratory warning sign design guidelines and applications

Warning sign design specification development

Building on foundational research in visual communication and laboratory safety management, the School of Materials Science and Engineering at Fujian University of Technology developed a comprehensive specification framework for laboratory warning signage. This framework integrates perspectives from cognitive psychology, design theory, and safety systems engineering to construct a multidimensional standard, which is guided by three key objectives: enhancing visual perception, enabling efficient information transmission, and ensuring contextual alignment to support safe behavioral responses.

As illustrated in Fig. 7, the design specification adopts a hierarchical layout that prioritizes essential information within the central visual field and promotes a triangular scanning trajectory. This structure facilitates rapid hazard identification, accurate risk differentiation, and clear behavioral cues, collectively reducing cognitive demands during high-risk situations. To balance standardization with adaptability, the framework incorporates consistent conventions in color use, symbol language, and typographic structure, while allowing for scenario-based adjustments to address specific laboratory environments.

Fig. 7

Example of laboratory warning sign design.

The framework highlights four interdependent design elements: color system, symbol system, information structure, and environmental adaptability, as summarized in Table 7. The color system follows universally recognized safety codes to support cross-cultural consistency and facilitate rapid hazard recognition. The symbol system is based on ISO and GHS standards, which enhance semantic clarity and increase recognition accuracy. The information structure is organized in line with cognitive processing principles, guiding user attention from the level of hazard to the recommended protective actions in a sequence that reflects natural information uptake. Environmental adaptability ensures that these components remain effective under varying laboratory conditions by reinforcing both perceptual accessibility and contextual relevance.

Table 7 Core elements of laboratory warning sign design Specifications.

Empirical evidence demonstrates that warning systems designed according to established standards significantly improve both comprehension and compliance. Within this framework, the application at the School of Materials Science and Engineering, Fujian University of Technology, resulted in a 37.8% increase in hazard perception accuracy and a 42.3% improvement in procedural compliance. These outcomes show that evidence-based specifications can lead to measurable gains in safety communication, providing practical guidance for laboratory management and empirical support for the broader application of standardized and adaptable design principles.

Warning sign system implementation and application case study

The implementation of the optimized warning sign framework at the School of Materials Science and Engineering, Fujian University of Technology serves as a pilot demonstration of how evidence-based design can improve laboratory safety communication. A phased and iterative process consisting of initial testing, refinement, piloting, and full-scale rollout with continuous evaluation ensured that improvements were both data-informed and contextually appropriate. Baseline assessments revealed notable deficiencies, with comprehension rates at 68.4% and compliance at 61.7%. Following implementation, performance increased significantly across all key indicators (Table 8). In particular, hazard identification accuracy improved by 42.3%, and compliance behaviors rose by 37.8%, confirming the technical efficacy of the optimized system and demonstrating its causal contribution to safer behavioral outcomes.

Table 8 Comparative performance of warning sign systems before and after Optimization.

Figure 8 illustrates the improvements in attentional distribution. The optimized warning signs focused visual attention on critical areas and reduced total processing time, enabling faster and more accurate hazard detection. A key feature of the implementation was the contextual adaptation of the general framework to address discipline-specific risks. In materials science laboratories, tailored modules were developed to reflect hazards such as high-temperature equipment, nanomaterials, and specialized chemical processes, while maintaining a unified visual language. The system also demonstrated adaptability in interdisciplinary environments shared with chemical and electronic engineering laboratories, indicating that a coherent yet flexible framework can accommodate diverse hazard profiles across scientific domains.

Fig. 8

Comparison of Visual Attention Patterns on Laboratory Warning Signs. Heat maps show fixation density from eye-tracking data (n = 48 participants).

The Fujian University of Technology case represents an early-stage application that illustrates the scalability and transferability of evidence-based approaches to laboratory safety communication. Rather than focusing on institutional achievements, it highlights the importance of stakeholder participation, phased implementation, and ongoing evaluation as components of sustainable organizational practice. Equally important, the iterative process underscores the need for adaptive mechanisms such as the inclusion of new user groups and the integration of emerging technologies, which help to ensure continued effectiveness. Beyond the institutional setting, these findings have broader implications. They suggest that standardized yet flexible communication frameworks could inform the development of national or international guidelines, while also drawing attention to adoption barriers in resource-limited contexts. Viewed in this light, the case serves not as a conclusion but as an example of how localized implementation can inform broader policy development and cross-institutional scalability.

Promotion strategies and practical value

The sustained effectiveness of enhanced laboratory warning systems depends not only on technical design but also on strategic organizational measures that promote user acceptance and long-term adherence. Drawing on the implementation experience at the School of Materials Science and Engineering, Fujian University of Technology, we developed a comprehensive promotional framework that integrates stakeholder engagement, multi-channel communication alignment, and institutional support mechanisms. This approach aligns with Lehto’s¹⁹ observation that technical competence in warning design must be complemented by organizational institutionalization to achieve meaningful safety improvements.

The framework consists of four interrelated components: awareness cultivation, competency development, organizational embedding, and iterative enhancement, as summarized in Table 9. Each component incorporates targeted strategies and measurable outcomes, enabling systematic evaluation of effectiveness. By embedding promotional efforts into institutional routines, the framework repositions system adoption from a one-time intervention to an ongoing trajectory of organizational learning. The most pronounced effects were observed in research laboratories with complex hazard profiles, highlighting the necessity of comprehensive promotional systems for sustaining safety communication in high-risk environments.

Table 9 Multi-dimensional promotion framework for laboratory warning sign Systems.

The benefits of optimized warning systems extend beyond immediate safety gains to encompass broader institutional advancements. As shown in Fig. 9, longitudinal analysis indicates that widespread adoption yields measurable returns not only through reductions in incident frequency and associated costs but also through improvements in operational efficiency and strengthened regulatory alignment. Especially in interdisciplinary research settings, contextually tailored systems proved highly effective in supporting diverse user groups navigating complex hazard environments with varying levels of expertise.

Empirical evidence from varied laboratory contexts further confirms the framework’s applicability to high-risk processes such as nanomaterial synthesis and high-temperature operations. Consistent with Lehto’s¹⁹ insight that “the effectiveness of warning signs rests not with the inherent design quality, but with the organizational frameworks that enable their implementation and maintenance,” our findings reinforce the critical role of institutionalization and compliance practices. Regular deployment across laboratory settings enhanced functional efficiency, demonstrating that sustained effectiveness derives from systematic organizational integration rather than design in isolation.

Fig. 9

Return on Investment Analysis of Warning Sign System Implementation. Analysis based on implementation data from the School of Materials Science and Engineering, Fujian University of Technology (n = 24 laboratories).

Conclusions and future prospects

This study has developed a comprehensive framework for evaluating and optimizing laboratory warning sign systems by integrating theoretical concepts with empirical evidence. The strategy addresses key limitations of conventional safety communication by examining how visual design, information structure, contextual conditions, and user factors jointly shape communication effectiveness. Results demonstrate that optimized systems substantially enhance safety communication across laboratory settings, with significant improvements in attention capture (35.9%), comprehension accuracy (30.4%), and compliance behavior (37.8%). These outcomes affirm the value of evidence-informed design strategies in overcoming the deficiencies of traditional warning practices and provide a more rigorous scientific basis for future safety communication interventions.

While improvements in visual hierarchy reduced processing errors, the cognitive burden of information density remains a critical challenge in high-stakes environments. The trade-off between sufficiency and overload can be interpreted through theories of visual attention, working memory, cognitive load, and dual processing. Prior studies show that effective hazard communication depends on selective attention²⁰, is constrained by limited working memory²¹, and can be undermined by cognitive overload²². Dual-process theory additionally posits that well-designed signage should support both rapid, intuitive recognition (System 1) and deliberate comprehension of detailed instructions (System 2)²³. The hierarchical structuring adopted in this study reflects these principles by ensuring that critical hazards are processed first, while supplementary details remain accessible as resources permit.

Beyond statistical improvements, the observed gains carry clear safety implications. By accelerating attention capture, strengthening comprehension and memory, and increasing compliance behaviors, the optimized system directly targets major causal factors in laboratory incidents, such as delayed hazard recognition and procedural non-compliance. Taken together, these outcomes suggest that optimized warning systems not only enhance cognitive processing but also translate into demonstrable reductions in accident likelihood and operational risk.

The methodological framework developed here advances the analysis of safety communication in laboratory contexts. By integrating insights from cognitive psychology, visual communication design, and human factors engineering, it provides a multidimensional perspective that surpasses single-discipline approaches. As Yuan and Zhang²⁴ argue, effective systems must balance standardization with contextual adaptation to reflect the diversity of laboratory environments. Our findings support this view, showing that warning signs should be systematically adapted to laboratory type while upholding core design integrity. The proposed optimization methodology thus offers a structured means of combining the cognitive benefits of uniformity with the practical flexibility of contextual modification.

Application of the C-HIP model yielded valuable insights into cognitive processing in complex laboratory contexts. By assessing effectiveness across the full processing chain, including attention capture and maintenance as well as comprehension, motivation, and behavioral response, the study identified key determinants of signage effectiveness. Notably, optimized signs elicited a distinctive “triangle scanning pattern” that began with the pictogram, followed by the signal word and then the instructional text. This sequence reflects a logically structured flow of information aligned with cognitive processing, thereby improving hazard detection and appropriate behavioral response. These findings are consistent with Gopang et al.²⁵, who showed that effective hazard communication depends not only on visibility but also on the intentional coordination of visual components with user cognition.

Looking ahead, the integration of digital technologies holds significant promise for the advancement of laboratory warning systems. Computer-aided design tools already enable rapid prototyping and iterative testing²⁶. Future research should extend this trajectory by developing adaptive systems that respond dynamically to hazard conditions, user profiles, and environmental contexts. Potential approaches include digital displays, augmented reality, and sensor-based technologies that deliver real-time, context-sensitive alerts. These innovations are especially relevant for laboratories with frequently changing hazard profiles, where static signage may be insufficient. Recent studies on digital signage and real-time hazard communication support this direction, underscoring the potential of dynamic, sensor-driven systems to enhance safety messaging^27,28.

Emerging digital technologies in adjacent domains further illustrate the value of instrumented, user-centered optimization. Eye-tracking studies of syntax comprehension and code reading reveal how fixation duration, scan paths, and regressions can diagnose cognitive bottlenecks and inform design refinement^29,30. Similarly, mobile learning applications such as phlebotomy training tools (mStikk) and pregnancy-related mHealth platforms demonstrate how lightweight, context-aware interfaces reinforce procedural compliance^31,32,33. These examples highlight two promising extensions: (i) gaze-informed interface calibration to fine-tune visual hierarchy and information load, and (ii) mobile micro-interventions (e.g., QR-linked checklists) that reinforce safety behaviors at the point of use, especially in resource-constrained settings.

This work is subject to several limitations. First, it focused primarily on academic laboratories, which may limit generalizability to industrial contexts with different user populations and operational demands. Second, although participants represented diverse experience levels, the study did not fully account for linguistic and cultural variation in hazard communication. Symbols and messages may be interpreted differently across user groups, and multilingual environments pose additional challenges. Future research should therefore incorporate cross-cultural testing and multilingual evaluations to determine whether standardized designs achieve universal clarity or require culturally specific adjustments. As Kimball³⁴ emphasized, the effectiveness of visual design varies across cultures, underscoring the importance of tailoring systems to heterogeneous audiences. Additional research should also explore the framework’s extension to diverse laboratory domains and technological applications.

In conclusion, this study advances the evidence base for improving laboratory warning systems by integrating theoretical insights with empirical validation. The proposed framework, which combines comprehensive evaluation, design optimization, and coordinated implementation strategies, offers a robust foundation for enhancing laboratory safety communication. As laboratories and research institutions become increasingly complex and globalized, these methods provide scalable and adaptable solutions to emerging safety challenges, with the potential to reduce accidents, injuries, and material losses through more effective communication of hazards and protective procedures.