Perceived Benefits of Social Distancing

Abstract

The Perceived Benefits of Social Distancing Scale, operationalized within psychometric and behavioral medicine literature by Hita et al. (2023), is an assessment instrument designed to quantify an individual’s cognitive appraisal regarding the efficacy of physical and social separation in curbing the transmission of infectious viral agents. Formulated as a central cognitive mediator within an Extended Health Belief Model (HBM) during the COVID-19 pandemic, this instrument captures the degree to which an individual believes that practicing spatial distancing protects both personal health and broader public welfare. Developed and validated through an extensive six-month, six-wave longitudinal panel study involving adult cohorts in Canada, the scale evaluates the cognitive calculus underlying non-pharmaceutical interventions (NPIs).

The scale employs a multi-item, unidimensional construct measured on a standardized 7-point Likert scale ranging from 1 (“Strongly Disagree”) to 7 (“Strongly Agree”). Psychometric evaluations conducted via structural equation modeling (SEM) and longitudinal confirmatory factor analysis (CFA) confirm robust psychometric properties across time. The instrument demonstrates high internal consistency, with composite reliability ($ρ_c$) and Cronbach’s alpha ($α$) coefficients consistently exceeding the conventional .85 threshold across all six measurement waves. Factor loadings consistently surpass .70, demonstrating high convergent validity accompanied by an average variance extracted (AVE) well above .50. Discriminant validity was empirically substantiated using the Fornell–Larcker criterion and the Heterotrait-Monotrait (HTMT) ratio of correlations relative to proximate constructs such as perceived susceptibility, perceived severity, perceived barriers, and self-efficacy. Nomological and predictive validity analyses confirm that perceived benefits of social distancing directly foster sustained behavioral adherence to public health mandates and mitigate maladaptive behaviors such as retail panic buying.

Keywords

Perceived benefits, social distancing, Health Belief Model, psychometrics, COVID-19, non-pharmaceutical interventions, behavioral compliance, confirmatory factor analysis, scale validation, public health psychology, longitudinal measurement invariance

Authors

The psychometric operationalization and longitudinal validation of the Perceived Benefits of Social Distancing Scale were conducted by an interdisciplinary team of researchers specializing in behavioral psychology, marketing science, and consumer analytics:

• Marie Louise Radanielina Hita — Department of Marketing, HEC Montréal, Montréal, QC, Canada. Expertise: Consumer health psychology, public health communications, and structural equation modeling.
• Yany Grégoire — Department of Marketing, HEC Montréal, Montréal, QC, Canada. Expertise: Consumer behavior, psychological contract breach, and longitudinal research design.
• Bruno Lussier — Department of Marketing, Telfer School of Management, University of Ottawa, Ottawa, ON, Canada. Expertise: Quantitative methods, organizational psychology, and behavioral adaptation.
• Simon Boissonneault — Department of Marketing, HEC Montréal, Montréal, QC, Canada. Expertise: Advanced statistical modeling and consumer cognitive analytics.
• Christian Vandenberghe — Department of Management, HEC Montréal, Montréal, QC, Canada. Expertise: Psychometric evaluation, structural equation modeling, commitment theory, and latent variable analysis.
• Sylvain Sénécal — Department of Marketing, HEC Montréal, Montréal, QC, Canada. Expertise: Digital media consumption, consumer neuroscience, and cognitive psychology.

Purpose

The primary clinical, epidemiological, and behavioral purpose of the Perceived Benefits of Social Distancing Scale is to quantify how strongly an individual believes that maintaining spatial separation from others effectively suppresses pathogen contagion. While public health directives frequently rely on formal legislation or moral appeals, human adherence to restrictive behavioral mandates depends heavily on subjective cognitive evaluation. Without a reliable perception that an onerous protective measure will yield tangible health preservation, adherence degrades rapidly over time.

In behavioral research and clinical epidemiology, the instrument serves several core functions:

• Diagnostic Stratification of Compliance Propensity: It enables public health agencies and researchers to diagnose baseline levels of intervention-specific belief systems within target populations, identifying cohorts exhibiting skepticism regarding the efficacy of non-pharmaceutical interventions (NPIs).
• Evaluation of Communication Campaigns: The scale functions as an evaluative benchmark for measuring the cognitive impact of public health messaging, tracking whether information dissemination successfully elevates the perceived utility of preventative actions.
• Predictive Modeling of Crisis Behaviors: Within the framework established by Hita et al. (2023), the scale evaluates how cognitive appraisals of benefit interact with media exposure (both traditional and social media) to govern not only direct compliance with social distancing, but also secondary downstream consumer phenomena, including compensatory panic buying, hoarding, and irrational stockpiling.
• Longitudinal Behavioral Tracking: By facilitating repeated-measures administration across shifting phases of an epidemic, the scale captures “pandemic fatigue” and cognitive decay, providing actionable data on when and why public conviction regarding preventive measures declines.

Psychological Construct

The psychological construct assessed by this instrument is situated at the intersection of cognitive psychology, risk appraisal, and health-related behavioral decision-making. In classical psychometric theory, “perceived benefits” denote an individual’s evaluation of the relative effectiveness of adopting a specific health-protective behavior in reducing the threat of disease or adverse physiological outcomes.

Within the specific domain of respiratory communicable pathogens (such as SARS-CoV-2), the construct of perceived benefits of social distancing incorporates two core cognitive dimensions:

• Egoistic (Self-Referent) Protective Utility: The subjective assessment that physical separation directly shields the individual from contracting the infectious agent. This involves an internal cognitive risk-reduction calculation, wherein the individual concludes: “Engaging in physical distancing significantly decreases my personal likelihood of infection, illness, and medical complication.”
• Altruistic (Other-Referent) and Societal Utility: The subjective conviction that one’s personal adherence contributes to suppressing viral reproductive numbers ($R_0$), protecting vulnerable community members, preventing the collapse of intensive healthcare infrastructure, and shortening the duration of crisis conditions.

Crucially, perceived benefits must be differentiated from adjacent constructs such as self-efficacy and response costs. While self-efficacy concerns the perceived behavioral capability of maintaining distance despite logistical friction (e.g., “I am capable of staying six feet away in public”), and perceived barriers measure the psychological, social, and economic costs incurred (e.g., “Social distancing causes me acute loneliness”), perceived benefits focus exclusively on the perceived effectiveness of the action. Hita et al. (2023) demonstrated that perceived benefit operates as a central cognitive mediator through which credible media information translates into sustained, compliant health behavior.

Theoretical Framework

The scale is theoretically grounded in the Health Belief Model (HBM), originally conceptualized by social psychologists at the U.S. Public Health Service, most notably Godfrey Hochbaum, Irwin Rosenstock (1966), and modified extensively by Marshall Becker (1974). The foundational premise of the HBM is that health-seeking behavior is dictated by two overarching subjective evaluations: threat perception and alternative behavioral evaluations.

Threat perception is a combined function of perceived susceptibility (the subjective likelihood of contracting a condition) and perceived severity (the evaluation of the seriousness of consequences). However, threat appraisal alone is insufficient to trigger action. Action is ultimately governed by the evaluation of behavioral alternatives, determined by balancing perceived benefits against perceived barriers. When perceived benefits decisively outweigh perceived barriers, and cues to action are present, the probability of enacting protective behavior reaches its zenith.

The conceptual framework is further reinforced by the principles of Protection Motivation Theory (PMT) (Rogers, 1975, 1983). Within PMT, the perceived benefit of a health measure directly reflects response efficacy—the cognitive expectation that an adaptive response will successfully neutralize the identified environmental threat. Hita et al. (2023) extended this theoretical tradition into an Extended Health Belief Model by situating perceived benefits downstream of modern information channels (differentiating traditional broadcasting from interactive social media algorithms) and examining its downstream power over public health compliance and resource competition.

Validity

The psychometric validity of the Perceived Benefits of Social Distancing Scale was evaluated by Hita et al. (2023) across a robust, multi-wave empirical design involving a representative sample of 1,029 Canadian consumers surveyed at six discrete points across six consecutive months.

Construct and Convergent Validity

Convergent validity was examined using standard structural equation modeling procedures. Standardized factor loadings across all items representing the perceived benefits construct exceeded the established benchmark of .70 ($p < .001$), confirming that the observed indicators share substantial common variance with the latent construct. The Average Variance Extracted (AVE) for perceived benefits exceeded the required .50 threshold across all measurement waves (typically reaching values between .62 and .78), demonstrating that variance captured by the construct exceeds the variance attributable to measurement error.

Discriminant Validity

Discriminant validity was established via two rigorous psychometric approaches:

• The Fornell–Larcker Criterion: The square root of the AVE for perceived benefits of social distancing was systematically higher than any bivariate correlation between this latent variable and all other constructs in the model (e.g., perceived susceptibility, perceived severity, perceived barriers, traditional media exposure, and panic buying).
• Heterotrait-Monotrait (HTMT) Ratio of Correlations: Across longitudinal waves, the HTMT ratios between perceived benefits and theoretically related constructs remained well below the conservative threshold of .85, confirming that the scale is conceptually distinct from general pandemic fear, health self-efficacy, and compliance intentions.

Nomological and Predictive Validity

Nomological validity was demonstrated through structural equation modeling of the Extended HBM. Perceived benefits demonstrated a direct positive path coefficient to actual social distancing adherence ($β > .30, p < .001$). Furthermore, the scale exhibited negative predictive validity relative to maladaptive coping: individuals scoring higher on the perceived benefits of social distancing demonstrated a significant reduction in retail panic buying, confirming that strong cognitive confidence in public health interventions reduces frantic, compensatory consumer hoarding.

Reliability

The reliability of the Perceived Benefits of Social Distancing Scale was rigorously evaluated across the six-month longitudinal duration in the Hita et al. (2023) investigation. Because health perceptions can fluctuate across different pandemic phases, assessing internal consistency across multiple waves is critical for psychometric verification.

• Internal Consistency: Cronbach’s alpha ($α$) coefficients for the perceived benefits latent construct consistently exceeded .85 at each of the six individual assessment points (Wave 1 through Wave 6), substantially surpassing the conventional psychometric threshold of .70.
• Composite Reliability: Composite reliability coefficients ($ρ_c$ / McDonald’s $ω$) remained consistently between .86 and .92 across all waves. This confirms high inter-item homogeneity and demonstrates that the scale items reliably capture true-score variance under varying external public health contexts.
• Test-Retest Stability & Longitudinal Consistency: In cross-lagged panel models, the autoregressive paths for perceived benefits between consecutive waves displayed high stability coefficients ($r$ ranging from .65 to .78, $p < .001$), indicating both strong temporal stability and appropriate sensitivity to macro-level health events.

Factor Analysis

The dimensional structure of the Perceived Benefits of Social Distancing Scale was evaluated using Confirmatory Factor Analysis (CFA) with Maximum Likelihood estimation with robust standard errors (MLR) to account for potential multivariate non-normality.

Measurement Model Fit

The measurement model exhibited strong fit across all six survey waves. Typical fit indices across waves consistently met or exceeded standard guidelines (Hu & Bentler, 1999):

• $χ^2 / df$ (Normed Chi-Square): Ranging between 1.82 and 2.45 (well below the conservative cutoff of 3.0).
• Comparative Fit Index (CFI): Ranging from .965 to .988 (exceeding the .95 threshold for excellent fit).
• Tucker-Lewis Index (TLI): Ranging from .958 to .982.
• Root Mean Square Error of Approximation (RMSEA): Values consistently between .031 and .048, with 90% confidence intervals not exceeding .055, and $p_{\text{close}} > .05$.
• Standardized Root Mean Square Residual (SRMR): Consistently under .042.

Longitudinal Measurement Invariance

To ensure meaningful longitudinal comparisons across the six-month period, Hita et al. (2023) conducted formal tests of measurement invariance across the six waves:

• Configural Invariance: Unconstrained multi-group/longitudinal models demonstrated equivalent factor structures over time ($Δ\text{CFI} < .01$).
• Metric (Weak) Invariance: Constraining factor loadings to equality across all waves yielded negligible deteriorations in fit ($Δ\text{CFI} < .010, Δ\text{RMSEA} < .015$), confirming that the latent metric preserved identical scale units over time.
• Scalar (Strong) Invariance: Constraining item intercepts to equality across waves maintained model fit within acceptable psychometric thresholds ($Δ\text{CFI} < .010$), permitting unbiased longitudinal mean comparisons.

Instrument / Measurement Tool

The operational specifications of the measurement tool are summarized as follows:

• Instrument Type: Self-administered psychometric rating scale / Latent variable self-report survey.
• Construct Assessed: Perceived cognitive benefits and response efficacy of physical/social distancing during an infectious epidemic.
• Theoretical Basis: Extended Health Belief Model (HBM) and Protection Motivation Theory (PMT).
• Item Format: Declarative statements reflecting cognitive beliefs regarding the preventative and community-wide efficacy of distancing.
• Response Scale: 7-point Likert-type response format:
  • 1 = Strongly Disagree
  • 2 = Disagree
  • 3 = Somewhat Disagree
  • 4 = Neither Agree nor Disagree (Neutral)
  • 5 = Somewhat Agree
  • 6 = Agree
  • 7 = Strongly Agree
• Scoring Procedure: Items are keyed positively (no reverse-coded items). A composite or mean score is calculated by summing the raw item scores and dividing by the total number of items, yielding a continuous score from 1.0 to 7.0. Higher scores indicate stronger cognitive conviction regarding the protective utility of social distancing.
• Administration Time: Approximately 1 to 2 minutes when administered independently; easily embedded into wider epidemiological and behavioral inventories.

Permissions & Fee and Test Year

The scale was developed, verified, and published in 2023 by Marie Louise Radanielina Hita, Yany Grégoire, Bruno Lussier, Simon Boissonneault, Christian Vandenberghe, and Sylvain Sénécal in the Journal of the Academy of Marketing Science.

• Copyright Status: The conceptual framework, structural findings, and original study contents are copyrighted by the Academy of Marketing Science and published under licence by Springer Nature.
• Research & Educational Use: In accordance with standard academic publishing conventions, the underlying constructs, methodological procedures, and scale stems are accessible for non-commercial academic research, public health inquiries, and educational purposes with appropriate academic attribution.
• Commercial Applications: Commercial deployment, proprietary algorithmic integration, or third-party diagnostic distribution requires formal permission and licensing clearance from the copyright holders and Springer Nature.
• Corresponding Author Inquiries: Inquiries regarding the original study, full experimental protocols, and longitudinal datasets may be directed to the corresponding authors at HEC Montréal (Department of Marketing).

References

• Becker, M. H. (1974). The health belief model and personal health behavior. Health Education Monographs, 2(4), 324–473. https://doi.org/10.1177/109019817400200401
• Hita, M. L. R., Grégoire, Y., Lussier, B., Boissonneault, S., Vandenberghe, C., & Sénécal, S. (2023). An extended health belief model for COVID-19: Understanding the media-based processes leading to social distancing and panic buying. Journal of the Academy of Marketing Science, 51(1), 132–152. https://doi.org/10.1007/s11747-022-00888-2
• Hochbaum, G. M. (1958). Public participation in medical screening programs: A socio-psychological study (PHS Publication No. 572). U.S. Government Printing Office.
• Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
• Rogers, R. W. (1975). A protection motivation theory of fear appeals and attitude change. The Journal of Psychology, 91(1), 93–114. https://doi.org/10.1080/00223980.1975.9915803
• Rogers, R. W. (1983). Cognitive and physiological processes in fear appeals and attitude change: A revised theory of protection motivation. In J. T. Cacioppo & R. E. Petty (Eds.), Social Psychophysiology: A Sourcebook (pp. 153–176). Guilford Press.
• Rosenstock, I. M. (1966). Why people use health services. The Milbank Memorial Fund Quarterly, 44(3), 94–127. https://doi.org/10.2307/3348965

Items of the Scale