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Entry

Visual Analogue Scale

by
Malcolm Koo
1,2,* and
Shih-Wei Yang
3,4
1
Department of Medical Research, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Dalin, Chiayi 622401, Taiwan
2
Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada
3
Department of Education, National Chiayi University, Minsyong, Chiayi 621302, Taiwan
4
Department of Styling and Cosmetology, Tainan University of Technology, Tainan City 710302, Taiwan
*
Author to whom correspondence should be addressed.
Encyclopedia 2025, 5(4), 190; https://doi.org/10.3390/encyclopedia5040190 (registering DOI)
Submission received: 21 September 2025 / Revised: 22 October 2025 / Accepted: 3 November 2025 / Published: 7 November 2025
(This article belongs to the Collection Data Science)
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Versions Notes

Definition

The Visual Analogue Scale (VAS) is a psychometric instrument used in research and clinical studies to measure the intensity of subjective experiences that cannot be objectively quantified using defined biomarkers, such as pain, fatigue, or mood. It typically consists of a 100 mm straight line with descriptive anchors at each end representing the extremes of the sensation (for example, “no pain” at one end and “the most severe pain imaginable” at the other). Respondents indicate their experience by marking a point on the line, and the distance from the lower anchor is measured and recorded as a continuous variable. VAS data can be analyzed using descriptive or inferential statistics, with the ordinal and non-linear properties of the scale requiring careful justification of the statistical methods applied.

Graphical Abstract

1. Introduction

The Visual Analogue Scale (VAS) is a widely used psychometric instrument that offers a simple yet effective method for quantifying the intensity or magnitude of subjective experiences and attitudes. First introduced in the early 20th century and refined over subsequent decades, the VAS has become indispensable for assessing phenomena that lack objective measurement, such as pain intensity [1], emotional states [2], quality of life [3], and patient satisfaction [4]. The tool’s versatility and ease of administration have established it as a standard in both clinical practice and research, facilitating evidence-based decision-making across disciplines as diverse as anesthesiology [5], palliative care [6], market research [7], and educational assessment [8]. This broad adoption reflects the VAS’s unique ability to translate subjective human experience into quantitative data suitable for scientific analysis.

2. The Visual Analogue Scale: Core Concepts

2.1. History of the Visual Analogue Scale

The conceptual origins of the visual analogue scale (VAS) can be traced to the early 20th century, particularly to the introduction of the “graphic rating scale” (GRS) by Mary H. S. Hayes and Donald G. Patterson in 1921 [9,10]. The GRS provided the theoretical foundation for visual rating approaches and is widely regarded as the precursor of the VAS. Nonetheless, Shiina (2021) claimed that the development of the GRS was a collaborative effort within the Scott Company Laboratory, rather than the work of a single investigator [11].
The VAS, as a standardized instrument for pain assessment, emerged in the mid-1960s. In 1965, physicians Issy Pilowsky and Alan S. Kaufman introduced the tool specifically for measuring pain, using a 10 cm line anchored by “No pain at all” and “As painful as it could possibly be.” Patients marked the line to indicate their perceived pain intensity [12]. The method gained rapid acceptance, with key contributions such as Robert C. Aitken’s 1969 review advocating for the use of a 100 mm line and measurement to the nearest millimeter, which played a critical role in standardizing the scale [13]. Subsequent validation studies, including the work by Donald D. Price et al. in 1983, further supported the VAS’s utility as a quantitative measure with ratio-scale properties [14]. A PubMed search using the Medical Subject Headings (MeSH) controlled vocabulary term “visual analog scale” identified over 4200 publications between 2004 and October 2025, reflecting the VAS’s status as a widely studied and useful tool.

2.2. Design and Formatting

The standard pen-and-paper VAS consists of a continuous, straight line, typically 100 mm in length, which may be oriented either horizontally or vertically. Evidence regarding whether orientation affects results is mixed, with some studies reporting differences and others finding no significant effect [15,16,17,18]. In one study of 78 patients with chronic low back pain, the horizontal format demonstrated greater sensitivity and produced data that more closely approximated a normal distribution [19]. A notable exception to the horizontal convention is the EuroQol, a cross-European quality of life instrument, in which five items with three response categories are accompanied by a vertical VAS assessing self-rated health on a scale from 0 to 100 [20].
The VAS line represents a continuum between two anchor points that define the extreme limits of the sensation being measured. For pain assessment, these anchors are commonly labelled “no pain” at one end and “severe pain” or “worst possible pain” at the other. In cultures where text is traditionally read from right to left, such as Arabic- or Hebrew-speaking populations, the orientation of the scale may be reversed, with “no pain” positioned on the right and “worst possible pain” on the left [21]. In addition to reversing the orientation, researchers must ensure the anchor terms are conceptually equivalent and culturally appropriate when translated. In addition, the thickness of the line has been suggested to be 3 point (approximately 1 mm) printed in black line [22].
It is important to emphasize that the term “analogue” in the VAS inherently denotes a continuous scale, capable of capturing any value along a continuum. The design of the VAS is therefore intentionally minimalist. Intermediate verbal or numerical descriptors, as well as tick marks, should not be included along the line, as these features may lead to score clustering and end-digit preference [23]. Scales that incorporate markings on the line [24] or use emoji-based formats [25] should not be classified as true VAS (Figure 1).

2.3. Comparison with Other Rating Scales

The VAS is considered one of the four principal unidimensional scales for pain measurement, alongside the Numeric Rating Scale (NRS), the Verbal Rating Scale (VRS) (such as the Likert-type format [26]), and the Faces Pain Scale-Revised (FPS-R) [27,28]. Each of these instruments quantifies pain intensity uses different response formats: the VAS relies on a continuous line, the NRS on numeric categories (typically 0–10), the VRS on descriptive verbal anchors (e.g., “mild,” “moderate,” “severe”), and the FPS-R on facial expressions representing increasing levels of pain (Table 1). The choice of a particular instrument should be guided by the characteristics of the target population as well as the objectives of the research or clinical assessment. For example, the FPS-R is often preferred in children or individuals with communication difficulties.

3. Administration, Scoring, and Analysis

3.1. Administration, Scoring and Data Handling

The administration of a paper-based VAS typically involves presenting participants with a printed horizontal line, usually 100 mm in length, with descriptive anchors at each end (e.g., “no sensation” on the left and “the most extreme sensation” on the right). Participants are instructed to indicate the intensity of their experience by marking the line, for example: “Please mark the point on the line that best represents how intense your [symptom] is.” Respondents are asked to indicate their response with a short vertical line or an “X” at the position on the line they feel corresponds to their symptom severity.
Once the line is marked, the VAS score is obtained by measuring the distance in millimeters from the lower anchor point (zero) to the respondent’s mark. This method effectively creates a 101-point scale, with higher values reflecting greater symptom intensity. For example, a mark placed 72 mm from the left end would correspond to a VAS score of 72 on a 0–100 scale. To ensure measurement accuracy, the printed VAS line must be exactly 100 mm in length, as distortions from printing or photocopying may alter the scale. If the line deviates from 100 mm, scores should be adjusted using the following formula:
Adjusted score = (measured distance ÷ actual line length) × 100

3.2. Statistical Analysis Considerations

There has been long-standing debate about whether VAS scores should be analyzed as ratio, interval, or ordinal data. Some researchers argue that the scale is ratio-level, as it has a true zero (e.g., complete absence of pain) and allows proportional comparisons (e.g., “twice as painful”) [14]. Others contend that it is better regarded as interval-level, since equal distances on the line may not represent equal psychological differences for all respondents [29]. To directly test this assumption, Kersten et al. applied the Rasch model, which evaluates whether responses fit a probabilistic framework ensuring consistent measurement of a single underlying construct to data from 221 patients with chronic joint pain. The results showed that the VAS functions as an ordinal scale rather than a linear interval or ratio scale. In other words, raw VAS change scores may misrepresent true change, overestimating responsiveness at the extremes and underestimating it in the middle. Therefore, VAS data should either be transformed into interval-level measures using Rasch analysis or analyzed with non-parametric methods appropriate for ordinal data [30].
This distinction in scale type has important implications for statistical analysis. A simulation study of VAS data from 480 nulliparous women in labour found that neither parametric nor nonparametric tests inflated the type I error rate, but Student’s t-test and analysis of variance (ANOVA) had slightly greater statistical power [31]. However, when the assumption of normality is clearly violated, for example, in palliative care populations where pain scores are often right-skewed. In such case, nonparametric rank-based methods (e.g., Mann-Whitney U test, Wilcoxon signed-rank test) may be more appropriate. Investigators are therefore advised to test for normality, using procedures such as the Kolmogorov–Smirnov or Shapiro–Wilk test, before selecting the statistical approach.
For VAS analyses involving multiple covariates, multiple regression is required. If the assumptions of linear regression are satisfied, ordinary least squares regression can be used. When assumptions are violated, data transformations (e.g., logarithmic, square-root) may improve normality, or regression models that do not rely on distributional assumptions, such as gamma regression or quantile regression, may be applied. In a separate simulation study, Heller et al. evaluated continuous ordinal regression, which formally models VAS data as ordinal while accounting for its continuous nature. They reported that this method provided superior power to detect differences in small samples and skewed data [29,32]. However, its implementation requires the R package ordinalCont, which may limit accessibility for some researchers.

3.3. Transparent Reporting of VAS Outcomes

When reporting the use of a VAS in research, several key elements should be addressed to ensure clarity, transparency, and reproducibility. First, the instrument must be fully described, including the anchor text (e.g., “no pain” to “worst pain imaginable”), the length of the line (e.g., 100 mm), and its orientation (horizontal or vertical). Second, authors should also specify whether the assessment was conducted using paper-based VAS or electronic VAS (eVAS), as mode of administration can affect data quality and feasibility. If eVAS was used, details regarding the software platform, device type, and validation against the paper version should be provided. Third, the choice of statistical methods must be explicitly stated and justified, with an indication of whether underlying assumptions were formally tested and met.
In addition, handling of missing or incomplete VAS data should be clearly described, as this can significantly affect study conclusions. For example, some participants may place more than one mark on the line, requiring investigators to prespecify whether the mean of the two values, the first mark, or the mark closest to an anchor will be used. Others may position the mark above or below the line rather than directly on it, in which case the perpendicular projection to the line may be applied, or the response may be considered invalid. Occasionally, participants may place the mark beyond the extremes of the line (e.g., outside the 0–100 mm range), and investigators must specify whether such responses will be truncated at the nearest valid value or excluded from the analysis. Similarly, if a cross mark is thicker than one millimeter, the central point of the marking should be used to minimize measurement error and ensure consistency across participants. Furthermore, when participants omit a response altogether, strategies for handling missing data (e.g., complete case analysis, imputation methods) should be stated. Explicitly defining these procedures ensures transparency, reduces risk of bias, and allows replication and comparison across studies using the VAS.

4. Psychometric Properties of the Visual Analogue Scale

4.1. Reliability

Reliability refers to the consistency and stability of a measure over time and across conditions. For the VAS, this is most commonly assessed using test–retest reliability, which examines whether the scale yields similar results when administered repeatedly to stable respondents.
The VAS has generally shown good to excellent test–retest reliability. In a study of 121 patients with osteoarthritic knee pain, it demonstrated excellent reliability, with an intraclass correlation coefficient (ICC) of 0.97 [33]. Likewise, in a large cohort of 733 patients with low back pain, reliability was moderate to good, with ICC values ranging from 0.68 to 0.89 depending on recall period (20 min vs. 24 h) and pain duration (acute vs. chronic) [34]. Patient characteristics may influence reliability; for example, among 92 patients with rheumatoid arthritis, reliability was significantly higher in literate participants (r = 0.90) than in illiterate participants (r = 0.71), suggesting that comprehension affects the consistency of responses [35].

4.2. Validity

Validity addresses the fundamental question of whether a scale truly measures the construct it is intended to assess. Because subjective experiences such as pain lack an objective “gold standard,” the validity of the VAS cannot be evaluated through criterion validity but must instead rely on construct validity.
Construct validity is supported through both convergent and discriminant validity. Convergent validity is demonstrated when the VAS correlates strongly with other instruments measuring similar constructs. For example, a psychological-physical pain VAS showed moderate correlations with depression, hopelessness, and physical pain (r = 0.43–0.67) [36]. Similarly, a generalized anxiety VAS (GA-VAS) correlated significantly with established anxiety measures, including the Hamilton Rating Scale for Anxiety (r = 0.60) and the Hospital Anxiety and Depression Scale-Anxiety subscale (r = 0.74) [37]. Discriminant validity is established when the VAS shows weak or non-significant correlations with conceptually different constructs. For instance, the GA-VAS correlated strongly with the mental health subscale of the 36-Item Short Form Health Survey (SF-36) (r = 0.68) but much lower with its physical function subscale (r = 0.24), indicating that it measured anxiety rather than general physical distress [37]. Likewise, in 378 patients with advanced cancer, a VAS for goals of care showed no significant correlation with a physical symptom burden scale (r = 0.06), further demonstrating discriminant validity [38].

4.3. Responsiveness

Responsiveness refers to the ability of an instrument to detect clinically important changes over time, even when those changes are small. For the VAS, this property is critical because it is widely used in clinical trials to evaluate treatment efficacy and in clinical practice to monitor symptom progression.
Responsiveness of the VAS is commonly quantified using effect size or standardized response mean. The minimal clinically important difference (MCID), the smallest change in score perceived as meaningful by patients, has been estimated at 12 mm (95% confidence interval 9–15 mm) on the 100 mm scale [39]. A systematic review of 66 empirical studies including over 31,000 patients reported a median absolute MCID of 23 mm (interquartile range 12–39), though estimates varied by baseline pain level, the operational definition of meaningful relief, and clinical condition [40]. Importantly, measurement error must also be taken into account, as some studies have shown that the smallest detectable change on the VAS can approach or exceed typical MCID thresholds, underscoring the need for caution when interpreting small changes in score [41].

5. Limitations and Challenges of the Visual Analogue Scale

Although the VAS is simple, imposes a low respondent burden, is freely available, and is sensitive to small changes in subjective states, it has several limitations. One of the most widely reported challenges is its usability in specific populations. Children and patients with cognitive or physical impairments may find it difficult to place a precise mark on the line, resulting in unreliable responses. For example, patients with reduced manual dexterity, visual impairments, or post-stroke aphasia may struggle with accurate completion [42]. One study reported that VAS-anxiety was a valid tool to assess perioperative anxiety in children 7 year and older [43]. Moreover, Kremer et al. studied 56 patients with chronic pain patients and found higher failure rate of 11% with the VAS compared with adjective (0%) or numerical rating scales (2%) in older individuals. The mean age of failures on the VAS was 75.3 years, which is significantly greater than the mean age of 54.4 years of successful patients, suggesting that declines in abstract thinking with age contribute to the difficulty [44].
In addition to completion challenges, the VAS has psychometric limitations. The scale lacks a standardized theoretical framework, and anchor descriptors such as “worst pain imaginable” may be interpreted inconsistently across individuals or cultural groups, introducing context and anchor bias [45]. Furthermore, subtle perceptual or motor tendencies in healthy people, such as pseudoneglect, a natural attentional bias towards the left side of space which leads to a directional bias making individuals to place marks slightly to the left of the intended position [46]. This phenomenon can create systematic error, particularly in horizontal formats.
Although the VAS is designed as a continuous measure, it still represents a finite response space bounded by two anchors, which introduces certain methodological constraints similar to those seen in categorical rating scales. This limitation may lead to ceiling or floor effects, reducing sensitivity when responses cluster near the extremes of the scale [47]. Furthermore, psychophysical research indicates that VAS scores can be influenced by stimulus amplitude, spacing, and frequency, reflecting adaptation-level shifts and context-dependent perception [48]. For example, repeated exposure to pain stimuli or analgesic interventions may alter participants’ internal reference frames, leading to “response spreading,” in which marks are distributed more broadly across the line without corresponding changes in perceived intensity [14,49]. Therefore, careful interpretation of VAS data is warranted, as apparent score changes may sometimes reflect perceptual recalibration rather than genuine clinical improvement.
Cross-cultural differences further affect the psychometric performance of the VAS. Variations in language, literacy, and cultural conceptualizations of pain or emotion can influence how respondents interpret anchor descriptors and utilize the scale. Studies have shown that cultural adaptation and validation are essential to ensure conceptual equivalence and maintain reliability across diverse populations [50]. Without proper cross-cultural validation, differences in interpretation may compromise comparability of results between cultural groups [51,52].
Practical limitations also persist. The paper-based VAS requires manual measurement with a ruler, which increases administrative workload and introduces the risk of data entry errors, and it cannot be administered verbally or over the telephone. Electronic VAS (eVAS) formats address some of these issues but require access to digital devices as well as validation evidence for their psychometric properties [53]. Furthermore, commonly used online survey platforms such as Google Forms do not currently support true VAS items, offering only discrete 10-point rating scales (https://docs.google.com/forms/, (accessed on 10 October 2025)). In addition, careful justification of statistical methods is essential when analyzing VAS data. Researchers must decide whether to treat VAS scores as interval or ordinal data, justify the use of parametric versus non-parametric tests, and consider the potential for non-normal distributions and measurement error. In addition, careful justification of statistical methods is essential when analyzing VAS data. Researchers must decide whether to treat VAS scores as interval or ordinal data, justify the use of parametric versus non-parametric tests, and consider the potential for non-normal distributions and measurement error. These constraints should be carefully considered when determining whether the VAS is suitable for a particular study.

6. Current and Future Developments

A current development for the VAS is its digital transformation. The traditional pen-and-paper scale is being replaced by electronic VAS (eVAS) deployed on smartphones and computers [53]. This shift allows for the immediate, error-free capture of patient-reported data, eliminating the need for manual measurement and transcription. The integration of eVAS into clinical trial software enables real-time monitoring of patient symptoms, providing clinicians with longitudinal data that can reveal trends in pain, fatigue, or mood over time. Furthermore, the application of the VAS has broadened far beyond its original use in pain assessment to become a staple tool for measuring subjective experiences in fields like psychology, sleep medicine, and quality of life research [54].
Looking ahead, the future of the VAS lies in its integration with other emerging technologies to create a more holistic picture of a patient’s condition. We can expect to see VAS prompts integrated into mobile technology, allowing for ecological momentary assessment (EMA) that can capture a person’s feelings or symptoms in their natural environment at various points throughout the day. This frequently collected subjective data can then be correlated with objective biometric data (e.g., heart rate, activity levels, sleep patterns) collected by the same device [55,56]. Furthermore, artificial intelligence (AI) and machine learning models can be applied to these combined datasets to identify complex patterns, predict symptom flare-ups, and personalize interventions, transforming the simple VAS line into a powerful input for predictive health analytics [57].

7. Conclusions

The VAS, which originated from early graphic rating methods, remains a valuable instrument in both clinical practice and research. Its key strengths include ease of use, sensitivity to change, and adaptability across diverse fields. These features have supported its widespread use in measuring subjective experiences. Beyond pain assessment, the VAS has also been adapted to evaluate a variety of psychological and emotional constructs, including anxiety, mood, fatigue, and overall well-being. This versatility illustrates its capacity to quantify subjective experiences that extend beyond physical sensations.
Despite its advantages, the VAS presents several limitations. These include challenges in administration among specific populations and ongoing debates regarding its psychometric classification and the most appropriate statistical methods for data analysis. Effective application of the scale requires a thorough understanding of both its conceptual basis and practical constraints. Transparent reporting and carefully justified analytical strategies are essential to ensure validity and reproducibility.
Ongoing developments are redefining the role of the VAS within digital health systems. The transition to electronic formats enables real-time data capture, minimizes manual error, and facilitates integration into mobile health platforms. When paired with biometric data and analyzed using advanced computational tools such as machine learning, VAS responses can inform personalized care and reinforce the patient-centred focus of modern healthcare.

Author Contributions

Conceptualization, M.K. and S.-W.Y.; writing—original draft preparation, M.K. and S.-W.Y.; writing—review and editing, M.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AIArtificial Intelligence
ANOVAAnalysis of Variance
EMAEcological Momentary Assessment
FPS-RFaces Pain Scale–Revised
GA-VASGeneralized Anxiety Visual Analogue Scale
GRSGraphic Rating Scale
MCIDMinimal Clinically Important Difference
MESHMedical Subject Headings
NRSNumeric Rating Scale
SF-3636-Item Short Form Health Survey
VASVisual Analogue Scale
VRSVerbal Rating Scale

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Encyclopedia 05 00190 g001
Figure 1. Example of a visual analogue scale for pain measurement, with the scale shown in black text and its component descriptions in blue text.
Figure 1. Example of a visual analogue scale for pain measurement, with the scale shown in black text and its component descriptions in blue text.
Encyclopedia 05 00190 g001
Table 1. Comparison of four common unidimensional rating scale for pain assessment.
Table 1. Comparison of four common unidimensional rating scale for pain assessment.
FeatureVisual Analogue Scale (VAS)Numeric Rating Scale (NRS)Verbal Rating Scale
(VRS)		Faces Pain Scale-Revised (FPS-R)
Format100 mm line without numerical markers0–10 or 0–11 numerical scaleDiscrete verbal descriptors (e.g., “no pain” to “worst pain”)Series of facial expressions
Measurement TypeContinuous (ratio scale)Discrete (interval scale)Ordinal scaleOrdinal scale
ScoringMillimeter measurement from left end (0–100 mm)Numeric score from 0 (no pain) to 10 (worst pain)Predefined categories converted to numeric equivalentsScore of 0, 2, 4, 6, 8, or 10
AdvantagesHigh sensitivity; ratio scale propertiesSimple; widely usedEasy for patients with cognitive or literacy challengesCulturally neutral; suitable for young children
LimitationsRequires understanding of scaleLess sensitive to small changesLimited sensitivity; fewer response optionsLess precise; not suitable for adults
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