Climate Change Skepticism Questionnaire (CCS-Q)

Abstract

The Climate Change Skepticism Questionnaire (CCS-Q), formulated by Janna A. de Graaf, F. Marijn Stok, John B. F. de Wit, and Michèlle Bal (2023), is a psychometrically validated, 12-item self-report instrument constructed to capture nuanced variations in public doubt regarding anthropogenic global climate change. Designed to overcome the methodological constraints, conceptual conflations, and psychometric ambiguities present in earlier assessment inventories, the CCS-Q operationalizes climate skepticism as a multifaceted psychological construct. The instrument was developed under the rigorous, three-phase construct validation methodology articulated by Flake, Pek, and Hehman (2017), synthesizing theoretical foundations from pioneering taxonomies of environmental skepticism (Ding et al., 2011; Poortinga et al., 2011; Rahmstorf, 2004). The questionnaire measures four distinct, correlated dimensions: trend skepticism (doubt concerning whether the climate is warming), attribution skepticism (doubt regarding the anthropogenic etiology of climatic alterations), impact skepticism (doubt regarding the severity, speed, and negative consequences of climate change), and response skepticism (doubt concerning the feasibility, efficacy, and meaningfulness of collective or individual mitigation efforts).

Administered via a 7-point Likert response format ranging from 1 (strongly disagree) to 7 (strongly agree), the CCS-Q yields both dimension-specific facet scores and an overarching composite skepticism index. During psychometric evaluation across multiple adult cohorts, the four-factor structural model demonstrated adequate goodness-of-fit via confirmatory factor analysis (CFA: CFI = .94, NFI = .93, SRMR = .04) and robust cross-sample replication (CFI = .92, NFI = .90, SRMR = .05). The instrument exhibits robust internal consistency across all subscales and the total composite scale (α ≥ .70), alongside excellent one-week test-retest stability (all temporal correlation coefficients r > .78). Criterion, convergent, and predictive validities are substantiated by negative associations with pro-environmental behavioral intentions, policy acceptance, and institutional trust, paired with positive correlations with general science skepticism and dispositional psychological reactance. The CCS-Q serves as an essential, high-precision psychometric tool for environmental psychologists, behavioral economists, climate communicators, and policy evaluators aiming to untangle the cognitive and ideological architecture of climate skepticism.

Keywords

Climate Change Skepticism Questionnaire, CCS-Q, trend skepticism, attribution skepticism, impact skepticism, response skepticism, environmental psychometrics, climate change beliefs, climate policy acceptance, dispositional reactance, public understanding of science, environmental psychology

Authors

The Climate Change Skepticism Questionnaire was developed and validated by a collaborative research team based in the Department of Interdisciplinary Social Science at Utrecht University, Netherlands:

• Janna A. de Graaf, Ph.D. — Department of Interdisciplinary Social Science, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht, Netherlands. ORCID: 0000-0002-6690-9482. Email: [email protected].
• F. Marijn Stok, Ph.D. — Department of Interdisciplinary Social Science, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht, Netherlands.
• John B. F. de Wit, Ph.D. — Department of Interdisciplinary Social Science, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht, Netherlands.
• Michèlle Bal, Ph.D. — Department of Interdisciplinary Social Science, Faculty of Social and Behavioural Sciences, Utrecht University, Utrecht, Netherlands.

Corresponding Address: Dr. Janna A. de Graaf, Faculty of Social and Behavioural Sciences, Utrecht University, Heidelberglaan 1, 3584 CS Utrecht, The Netherlands. Email: [email protected].

Purpose

The anthropogenic transformation of Earth’s climate system represents an existential challenge demanding unprecedented societal, institutional, and individual behavioral adaptation. Despite overwhelming consensus across the global scientific community (Intergovernmental Panel on Climate Change [IPCC]), widespread skepticism, doubt, and ambivalence continue to permeate public discourse. Prior to the development of the Climate Change Skepticism Questionnaire (CCS-Q), empirical investigations in environmental psychology and political science were constrained by significant psychometric limitations. Extant instruments frequently treated skepticism as a unidimensional, monolithic construct, conflated ideological denial with genuine epistemic uncertainty, relied on single-item indicators lacking documented reliability, or utilized unvalidated ad-hoc scales that failed standard construct validation criteria.

The overarching purpose of the CCS-Q is to provide an empirically grounded, structurally robust, and psychometrically validated instrument that captures the multi-faceted nature of climate change skepticism. By deconstructing doubt into four distinct cognitive components—trend, attribution, impact, and response skepticism—the scale enables researchers and practitioners to pinpoint the precise psychological mechanisms driving disengagement, policy resistance, or inaction.

From an applied perspective, the CCS-Q serves several critical functions across research, clinical-educational, and policy-making domains:

• Targeted Climate Communication: Communication interventions often fail because they target the wrong cognitive barrier. An individual who acknowledges global warming trends and human attribution but doubts the efficacy of mitigation policies (response skepticism) requires an entirely different intervention strategy than an individual who rejects the foundational temperature data (trend skepticism). The CCS-Q allows communicators to diagnose audience profiles and tailor messaging accordingly.
• Behavioral and Policy Modeling: The instrument facilitates structural equation modeling to disentangle which specific forms of skepticism exert the strongest direct and indirect effects on pro-environmental behaviors, support for carbon pricing, renewable energy investments, and regulatory compliance.
• Longitudinal and Cross-National Monitoring: With its brief 12-item architecture and verified test-retest reliability, the CCS-Q provides an efficient tool for longitudinal tracking of shifting public attitudes in response to extreme weather events, political campaigns, economic fluctuations, or educational curricula.
• Theoretical Integration: The questionnaire bridges environmental psychometrics with broader psychological frameworks, including motivated reasoning, system justification theory, and psychological reactance, elucidating how ideological beliefs intersect with scientific comprehension.

Psychological Construct

The construct assessed by the CCS-Q is climate change skepticism (CCS), defined as subjective doubt, disbelief, or rejection regarding the mainstream scientific consensus concerning global warming and anthropogenic environmental degradation. Rather than conceptualizing skepticism as an all-or-nothing cognitive state, the construct represents a multidimensional spectrum of epistemic and motivational beliefs. The CCS-Q delineates four distinct yet inter-correlated sub-constructs:

1. Trend Skepticism

Trend skepticism involves doubt or outright denial regarding the empirical reality of global climate change. Individuals endorsing trend skepticism question whether Earth’s climate is actually undergoing a warming trajectory or exhibiting systematic, unprecedented shifts. Epistemologically, trend skepticism challenges observational and paleoclimatic temperature datasets, dismissing reported warming patterns as measurement errors, statistical artifacts, or natural short-term weather variability. In the CCS-Q, trend skepticism is characterized by uncertainty regarding whether global warming is actively occurring and broad skepticism regarding the veracity of climate scientists’ claims.

2. Attribution Skepticism

Attribution skepticism refers to beliefs that dismiss or minimize the anthropogenic etiology of observed climatic changes. An individual exhibiting attribution skepticism may concede that global temperatures are rising, but firmly rejects the scientific conclusion that greenhouse gas emissions from human industrial activity, deforestation, and fossil fuel combustion are the principal driving mechanisms. Instead, climate change is attributed entirely or predominantly to natural biogeochemical cycles, solar irradiance variations, or volcanic activity. Within the CCS-Q, attribution skepticism captures cognitive resistance to human culpability and the belief that ongoing climatic shifts are merely organic, natural planetary fluctuations.

3. Impact Skepticism

Impact skepticism represents the conviction that the adverse consequences, threats, and prospective risks associated with climate change are benign, manageable, or grossly exaggerated by researchers and the media. Even when trend and human attribution are acknowledged, impact skeptics minimize the severity of projected ecological and societal disruptions—such as sea-level rise, biodiversity loss, extreme meteorological events, and agricultural displacement. In the CCS-Q, impact skepticism reflects downplaying the seriousness of climate change, viewing public warnings as sensationalist, and lacking personal or collective concern regarding ecological outcomes.

4. Response Skepticism

Response skepticism is an action-oriented dimension that reflects profound doubt regarding the efficacy, utility, feasibility, and fairness of mitigation or adaptation initiatives. Individuals high in response skepticism perceive human efforts to combat climate change as fundamentally futile, economically wasteful, or technologically impotent. This dimension embodies a sense of collective fatalism (“there is nothing we can do that will meaningfully alter planetary outcomes”) alongside the belief that proactive sustainability interventions constitute an unproductive expenditure of resources. In the CCS-Q, response skepticism operationalizes feelings of helplessness, policy cynicism, and perceived mitigation inefficacy.

Theoretical Framework

The conceptual architecture of the CCS-Q is anchored in environmental sociology, cognitive science, and social psychology. Its primary structural foundation derives from the theoretical taxonomy formulated by oceanographer and climate scientist Stefan Rahmstorf (2004), who categorized public climate skepticism into trend, attribution, and impact skepticism. This tripartite model was subsequently refined, expanded, and operationalized empirically within social science by researchers such as Poortinga et al. (2011), Ding et al. (2011), and Capstick and Pidgeon (2014), who demonstrated that skepticism regarding societal and policy responses (response skepticism) constitutes an independent, functionally critical facet of public resistance.

To ground the instrument within established measurement theory, de Graaf et al. (2023) implemented the rigorous construct validation framework established by Flake, Pek, and Hehman (2017). This framework mandates three distinct methodological phases:

1. Substantive Phase: Comprehensive conceptual definition, review of extant literature, generation of an initial item pool (16 items derived from validated sources including Christensen & Knezek, 2015; Feinberg & Willer, 2011; Leiserowitz et al., 2013; Poortinga et al., 2011; Steg et al., 2005), cognitive debriefing, language simplification to an intermediate reading level, and removal of redundant phrasing yielding a 12-item instrument.
2. Structural Phase: Quantitative evaluation of the dimensional structure using confirmatory factor modeling, item-factor loadings, and testing for local independence and latent distinctiveness.
3. External Phase: Systematic examination of how the latent dimensions correlate with external criteria, theoretical correlates, and real-world outcomes (nomological network evaluation).

Underpinning the manifestation of these four skeptical dimensions are several prominent psychological theories:

• Motivated Reasoning and Cultural Cognition: Individuals interpret scientific evidence through the lens of prior values, political ideology, and social identity (Kahan et al., 2011). Skepticism does not simply reflect an information deficit; rather, it functions as a protective cognitive mechanism shielding individuals from identity-threatening scientific conclusions.
• System Justification Theory: Formulated by Jost et al. (2004), this theory posits that individuals possess an inherent motivation to defend, bolster, and justify existing socioeconomic and industrial arrangements. Acknowledging anthropogenic climate change implies that modern industrial-capitalist systems are fundamentally flawed; consequently, individuals activate trend, attribution, and impact skepticism to preserve psychological equilibrium and justify the status quo.
• Psychological Reactance Theory: Conceptualized by Jack Brehm (1966), reactance occurs when individuals perceive behavioral freedoms to be threatened or curtailed. Climate mitigation policies (e.g., carbon taxes, regulatory appliance prohibitions, meat consumption constraints) impose direct behavioral boundaries. Skepticism—especially response and impact skepticism—acts as an ideological defense mechanism allowing individuals to rationalize non-compliance and neutralize feelings of externally imposed behavioral control.

Validity

The construct validity of the CCS-Q has been rigorously established across multiple independent adult samples through comprehensive convergent, discriminant, and predictive criterion-related analyses (de Graaf et al., 2023).

Convergent and Discriminant Validity

To assess convergent validity within a nomological network, the four dimensions of the CCS-Q were evaluated alongside established psychological measures of environmental motivation, political orientation, institutional trust, general science skepticism, and dispositional reactance:

• Sustainable Behavioral Intentions and Motivation: All four CCS-Q dimensions displayed statistically significant, robust negative correlations with self-reported intentions to engage in sustainable behaviors (e.g., energy conservation, dietary alterations) and general autonomous motivation toward environmental stewardship.
• Institutional Trust: Strong inverse relationships emerged between all skepticism subscales and trust in governmental, scientific, and regulatory institutions, indicating that climate skepticism is intrinsically linked to broader socio-epistemic alienation.
• General Climate Science Skepticism: Strong positive correlations were observed between the CCS-Q dimensions and independent, general scales measuring distrust of scientific institutions and scientific consensus, substantiating the convergence of the instrument on the target latent construct.
• Dispositional Reactance: Significant positive associations were identified between CCS-Q dimensions and trait psychological reactance, supporting the theoretical proposition that skeptical attitudes serve to deflect perceived threats to personal autonomy.

Predictive and Criterion Validity

Predictive validity was verified using multiple and hierarchical linear regression analyses testing whether the CCS-Q accounts for variance in environmental policy acceptance and personal behavior beyond standard socio-demographic covariates (such as age, gender, education, and political orientation). The composite CCS-Q score demonstrated profound predictive power across several key behavioral and political criteria:

• Sustainable Intentions: Composite CCS significantly and negatively predicted intentions to adopt pro-environmental actions, F(5, 526) = 37.00, p < .001, accounting for 26% of the variance (R² = .26).
• Fossil Fuel Taxation Policy: Acceptance of policy measures aimed at increasing taxes on fossil fuels was strongly and negatively predicted by composite skepticism, F(5, 505) = 39.48, p < .001, R² = .28.
• Renewable Energy Subsidization: Support for utilizing national tax revenues to finance wind and solar power generation infrastructure was significantly undermined by skepticism, F(5, 506) = 36.04, p < .001, R² = .26.
• Regulatory Appliance Bans: Policy acceptance regarding legally prohibiting energy-inefficient household appliances was negatively predicted by the CCS-Q, F(5, 507) = 17.41, p < .001, R² = .15.

Crucially, these predictive effects remained statistically significant after controlling for ideological self-placement and educational background, confirming that the CCS-Q captures unique explanatory variance that cannot be reduced merely to political partisanship or general cognitive ability.

Reliability

The psychometric reliability of the CCS-Q has been demonstrated across parameters of internal consistency and temporal stability.

Internal Consistency

Internal consistency was assessed across multiple Dutch community and general population samples using Cronbach’s alpha (α). In alignment with psychometric standards (Nunnally & Bernstein, 1994), values of α ≥ .70 reflect acceptable to good internal reliability:

• Subscale Reliabilities: All four subscales—Trend Skepticism, Attribution Skepticism, Impact Skepticism, and Response Skepticism—demonstrated internal consistency coefficients meeting or exceeding the α = .70 threshold.
• Composite Scale Reliability: The total 12-item composite scale consistently demonstrated high internal reliability, with Cronbach’s alpha coefficients exceeding .85 across validation studies.

Temporal Stability (Test-Retest Reliability)

To establish that the CCS-Q measures enduring cognitive attitudes rather than fleeting situational states, test-retest reliability was evaluated across a one-week interval. The stability coefficients for all four distinct dimensions as well as the total composite scale were robust:

• All subscale test-retest correlations yielded coefficients of r > .78 (p < .001).
• The composite score demonstrated exceptional stability (r > .80), indicating high replicability across repeated administrations in stable environmental conditions without intervening experimental manipulations.

Factor Analysis

The structural dimensionality of the CCS-Q was evaluated using Confirmatory Factor Analysis (CFA), testing the theoretical four-factor model against plausible alternative specifications (e.g., a unidimensional one-factor model and hierarchical models).

Primary Sample Confirmatory Factor Analysis

In the primary validation sample comprising Dutch adults recruited online, CFA was estimated using robust maximum likelihood estimators. The hypothesized four-factor model (Trend, Attribution, Impact, and Response Skepticism) yielded satisfactory-to-good goodness-of-fit indices:

• Comparative Fit Index (CFI): 0.94 (exceeding standard acceptable thresholds of ≥ .90 and approaching the conservative .95 cutoff proposed by Hu & Bentler, 1999).
• Normed Fit Index (NFI): 0.93 (indicating excellent fit relative to the null baseline model).
• Standardized Root Mean Square Residual (SRMR): 0.04 (well below the conventional .08 threshold for well-fitting structural models).

All 12 items loaded strongly and significantly on their respective hypothesized latent factors, with standardized factor loadings typically exceeding .60, confirming that each item functions as a strong observable indicator of its target dimension. Inter-factor correlations among the four subscales were positive, moderate-to-strong, and statistically significant, confirming that while the facets share common variance within the broader climate skepticism domain, they remain empirically distinct constructs.

Replication Confirmatory Factor Analysis

To ensure structural stability and mitigate the risk of sample-specific capitalization on chance, a second CFA was conducted on an entirely independent validation sample of Dutch adults. The four-factor architecture replicated successfully with strong fit parameters:

• Comparative Fit Index (CFI): 0.92
• Normed Fit Index (NFI): 0.90
• Standardized Root Mean Square Residual (SRMR): 0.05

Model comparison tests demonstrated that the four-factor model was statistically superior to a unidimensional model, which exhibited poor fit, confirming the multidimensional nature of climate change skepticism.

Instrument / Measurement Tool

Below is the structured technical specification of the Climate Change Skepticism Questionnaire:

• Test Name: Climate Change Skepticism Questionnaire (CCS-Q)
• Authors: Janna A. de Graaf, F. Marijn Stok, John B. F. de Wit, & Michèlle Bal (2023)
• Construct Measured: Multidimensional Climate Change Skepticism (Trend, Attribution, Impact, and Response Skepticism)
• Test Type: Psychometric Self-Report Questionnaire / Attitudinal Inventory
• Administration Method: Electronic (online survey platforms, computer-assisted web interviewing) or pen-and-paper self-administration
• Target Population: General adult population (aged 18 years and older), encompassing young adults (18–29), thirties (30–39), middle age (40–64), and older adults (65+) across all gender identities
• Languages Available: Dutch (original validation language) and English
• Item Count: 12 items total (3 items per subscale)
• Response Scale: 7-point Likert scale ranging from 1 (strongly disagree / totally disagree) to 7 (strongly agree / totally agree)
• Subscale Allocation:
  • Trend Skepticism: Items 1, 7 (R), 11
  • Attribution Skepticism: Items 2, 6 (R), 9
  • Impact Skepticism: Items 3 (R), 5, 12 (R)
  • Response Skepticism: Items 4, 8, 10
• Scoring Guidelines:
  • Four items are negatively phrased and must be reverse-scored prior to computation: Item 3, Item 6, Item 7, and Item 12. Reverse scoring on a 1-to-7 scale is executed via the formula: Score_Reversed = 8 - Score_Original.
  • Subscale scores are calculated by averaging the response values of the three corresponding items.
  • A global Composite Climate Change Skepticism score is derived by computing the mean of all 12 items (after reverse scoring).
  • Higher scores on individual subscales and the composite index indicate greater levels of climate change skepticism.

Permissions & Fee and Test Year

The Climate Change Skepticism Questionnaire was officially published in 2023 in the Journal of Environmental Psychology. The instrument is made available under the Creative Commons Attribution 4.0 International (CC BY 4.0) license.

• Research & Educational Use: Free of charge. Researchers, students, and educators are permitted to share, copy, adapt, and administer the instrument for academic, non-commercial, and teaching purposes, provided appropriate scholarly credit is attributed to the original authors (de Graaf et al., 2023).
• Commercial Use: Commercial application is governed by the underlying journal publication terms and standard institutional guidelines. Inquiries regarding commercial implementations should be directed to the corresponding author or the journal publisher.
• Licensing Web Link: Creative Commons CC BY 4.0 License

References

• Brehm, J. W. (1966). A theory of psychological reactance. Academic Press.
• Capstick, S. B., & Pidgeon, N. F. (2014). What is climate change scepticism? Examination of the concept using a mixed methods study of the UK public. Global Environmental Change, 24, 389–401. https://doi.org/10.1016/j.gloenvcha.2013.08.012
• Christensen, R., & Knezek, G. (2015). The climate change attitude survey: Measuring middle school student beliefs and intentions to enact positive environmental change. International Journal of Environmental and Science Education, 10(5), 773–788.
• de Graaf, J. A., Stok, F. M., de Wit, J. B. F., & Bal, M. (2023). The climate change skepticism questionnaire: Validation of a measure to assess doubts regarding climate change. Journal of Environmental Psychology, 89, 102068. https://doi.org/10.1016/j.jenvp.2023.102068
• Ding, D., Maibach, E. W., Zhao, X., Roser-Renouf, C., & Leiserowitz, A. (2011). Support for climate policy and societal action are linked to perceptions about scientific consensus. Nature Climate Change, 1(9), 462–466. https://doi.org/10.1038/nclimate1295
• Feinberg, M., & Willer, R. (2011). Apocalypse soon? Dire messages reduce belief in global warming by contradicting just-world beliefs. Psychological Science, 22(1), 34–38. https://doi.org/10.1177/0956797610391911
• Flake, J. K., Pek, J., & Hehman, E. (2017). Construct validation in social and personality psychological research: Current practice and recommendations. Social Psychological and Personality Science, 8(4), 370–378. https://doi.org/10.1177/1948550617693063
• 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
• Jost, J. T., Banaji, M. R., & Nosek, B. A. (2004). A decade of system justification theory: Accumulated evidence of conscious and unconscious bolstering of the status quo. Political Psychology, 25(6), 881–919. https://doi.org/10.1111/j.1467-9221.2004.00402.x
• Kahan, D. M., Jenkins-Smith, H., & Braman, D. (2011). Cultural cognition of scientific consensus. Journal of Risk Research, 14(2), 147–174. https://doi.org/10.1080/13669877.2010.511246
• Leiserowitz, A., Maibach, E., Roser-Renouf, C., Feinberg, G., & Howe, P. (2013). Climate change in the American mind: Americans’ global warming beliefs and attitudes in April 2013. Yale University and George Mason University. New Haven, CT: Yale Project on Climate Change Communication.
• Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
• Poortinga, W., Spence, A., Whitmarsh, L., Capstick, S., & Pidgeon, N. F. (2011). Uncertain climate: An investigation into public scepticism about anthropogenic climate change. Global Environmental Change, 21(3), 1015–1024. https://doi.org/10.1016/j.gloenvcha.2011.03.001
• Rahmstorf, S. (2004). The climate sceptics. In Weather Catastrophes and Climate Change (pp. 76–83). Munich Re.
• Steg, L., Dreijerink, L., & Abrahamse, W. (2005). Factors influencing the acceptability of energy policies: A test of VBN theory. Journal of Environmental Psychology, 25(4), 415–425. https://doi.org/10.1016/j.jenvp.2005.08.003

13. Items of the Scale (Questionnaire)