State-Trait Assessment of Resilience Scale

Abstract

The State-Trait Assessment of Resilience Scale (STARS) is an advanced psychological instrument developed by Samantha Lock, Clare S. Rees, and Brody Heritage in 2019 to evaluate human adaptability under stress. Rooted in modern psychological metatheory and psychometric item response theory (IRT), the scale reconceptualizes psychological resilience by addressing a foundational flaw in historical assessment: the conflation of stable, baseline personal attributes with dynamic, transient emotional adaptations. Comprising an initial pool of 28 items balanced across two distinct subscales—Trait Resilience (14 items) and State Resilience (14 items)—the instrument employs an authentic 7-point Likert scale to capture respondents’ self-appraised coping capabilities.

Unlike conventional instruments grounded solely in Classical Test Theory (CTT), the STARS was evaluated using David Andrich’s Rating Scale Formulation of the Rasch model. This parameterization permits interval-level measurement calibration, confirms category threshold orderliness across the 7-point scale, and establishes unidimensionality within each latent dimension. Validation conducted in an Australian adult cohort (N = 274; mean age = 28.33 years) confirmed rigorous construct, convergent, and discriminant validity across established psychological markers, including negative affect, perceived stress, and five-factor personality dimensions. By disentangling distal personal tendencies from proximal shifts brought on by acute environmental stressors, the STARS provides researchers and clinicians with an empirically calibrated diagnostic framework for monitoring occupational burnout, evaluating cognitive-behavioral resilience training, and exploring longitudinal adaptation.

Keywords

resilience, state-trait resilience, psychological assessment, psychometrics, Rasch analysis, Item Response Theory, coping capacity, stress appraisal, adaptation, occupational health, scale validation

Authors

The State-Trait Assessment of Resilience Scale was conceptualized, constructed, and psychometrically validated by researchers based in Western Australia:

• Samantha Lock — School of Psychology, Curtin University, Perth, Western Australia.
• Clare S. Rees — School of Psychology, Curtin University, Perth, Western Australia. Dr. Rees is an internationally recognized clinical psychologist and academic specializing in cognitive-behavioral therapy, perfectionism, anxiety disorders, and resilience mechanisms across clinical and non-clinical populations.
• Brody Heritage — Discipline of Psychology, College of Science, Health, Engineering and Education, Murdoch University, Perth, Western Australia. Dr. Heritage specializes in quantitative methodology, psychometric modeling, occupational wellbeing, and applied structural equation and Rasch analyses (Correspondence: [email protected]).

Purpose

The primary purpose of the State-Trait Assessment of Resilience Scale (STARS) is to rectify a long-standing measurement paradox within resilience research. For decades, psychometric tools such as the Connor-Davidson Resilience Scale (CD-RISC) and the Resilience Scale for Adults (RSA) captured resilience predominantly as a static, immutable personality trait. Conversely, transactional models of stress operationalized resilience strictly as an outcome or a dynamic, fluctuating coping process. By treating resilience through a singular lens, researchers and clinicians faced severe methodological limitations: trait-exclusive scales were unresponsive to acute workplace burnout, post-traumatic reactions, or the positive impacts of short-term psychological interventions; process-only approaches failed to account for an individual’s enduring coping predispositions and temperamental stability.

The STARS resolves this theoretical division by establishing a dual-construct measurement paradigm. Developed to serve both clinical diagnostics and research inquiries, the instrument offers distinct scores for Trait Resilience (an individual’s enduring baseline capacity to rebound from adversity) and State Resilience (an individual’s immediate, context-dependent coping capacity over recent intervals). In applied organizational, healthcare, and military settings—such as medical residency programs, acute nursing units, emergency services, and corporate environments—the STARS allows professionals to identify subtle yet critical psychological discrepancies. For example, an employee presenting with exceptionally high trait resilience may simultaneously experience precipitously low state resilience, signaling acute situational overload or severe exhaustion that has temporarily depleted their baseline psychological resources.

From an evaluative standpoint, the scale provides a sensitive measurement apparatus for pre- and post-intervention studies. While traditional trait measures often show negligible change following an 8-week resilience workshop (thereby leading to erroneous conclusions of treatment inefficacy), the State subscale of the STARS possesses the requisite sensitivity to register proximal gains in coping strategies and emotional appraisal. In longitudinal research, the STARS allows developmental and social psychologists to model latent trajectories of change, charting how repeated exposures to acute stressors either degrade or fortify an individual’s distal trait reserves across the lifespan.

Psychological Construct

The STARS conceptualizes psychological resilience not merely as the absence of psychopathology following exposure to trauma, but as an active, self-appraised psychological capability to navigate, withstand, and adaptively recover from stress, adversity, and disruptive life changes. The construct is operationalized across two structural dimensions:

1. Trait Resilience

Trait Resilience is defined as a distal, deeply embedded, and relatively enduring personality disposition that characterizes an individual’s generalized belief in their ability to overcome adversity across time and varied life domains. It reflects crystallized cognitive schemas, stable self-efficacy expectations, and entrenched emotional regulation tendencies. Individuals characterized by high trait resilience approach unforeseen hurdles with an internalized conviction that setbacks are temporary, surmountable, and instrumental for self-growth. This subscale measures an individual’s chronic cognitive-affective architecture, which buffers the psychological system against the long-term wear of chronic life stressors.

2. State Resilience

State Resilience represents a proximal, dynamic, and transient psychological condition that fluctuates according to immediate contextual demands, recent life events, cumulative daily hassles, and momentary internal energy reserves. Even if a person possesses an inherently robust trait baseline, their state resilience may become compromised when faced with a sudden barrage of stressors, acute sleep deprivation, personal loss, or systemic organizational strain. Conversely, state resilience can surge when temporary protective resources—such as supportive social interactions, structured coping regimens, or transient reductions in workload—are introduced. Items within this subscale gauge an individual’s current capacity to mobilize affective stability, mental flexibility, and problem-focused coping under present conditions.

By measuring both dimensions along parallel conceptual axes, the STARS maps the dynamic tension between enduring psychological resources and the ongoing friction of immediate environmental demands. This dual conceptualization reflects contemporary meta-theoretical perspectives, which posit that human adaptation is an ongoing dialogue between constitutional endurance and situational elasticity.

Theoretical Framework

The theoretical architecture of the STARS is grounded in three converging paradigms within contemporary clinical, personality, and psychometric science:

The State-Trait Paradigm

The primary theoretical foundation is derived from the classic state-trait dichotomy introduced by Charles Spielberger in his groundbreaking work on anxiety (STAI). Spielberger posited that affective states cannot be fully comprehended without distinguishing between an individual’s baseline, enduring disposition to experience a given affective reaction (trait) and the actual, momentary intensity of that reaction in a specific situation (state). Lock, Rees, and Heritage extended this metatheoretical framework to the domain of positive psychological coping, arguing that resilience exhibits the exact same ontological bifurcation: individuals possess both a latent, trait-like propensity to bounce back and a state-level appraisal of their real-time coping functioning.

Cognitive Appraisal and Transactional Coping Metatheory

The second pillar rests upon the Transactional Model of Stress and Coping pioneered by Richard Lazarus and Susan Folkman (1984), alongside Albert Bandura’s (1977) Self-Efficacy Theory. In this framework, resilience is not viewed as an objective asset that one either holds or lacks; rather, it is an emergent property of cognitive appraisal. When faced with an environmental stressor, individuals execute primary appraisals (evaluating threat, challenge, or harm) and secondary appraisals (evaluating the availability and efficacy of personal coping resources). The STARS explicitly measures this self-appraised coping efficacy, capturing whether individuals evaluate their internal psychological resources as sufficient to neutralize present challenges.

Modern Latent Trait Measurement Theory

Historically, psychological scales were constructed under the assumptions of Classical Test Theory, which implicitly assumes that raw Likert sum scores represent true linear intervals and that measurement error is uniform across all respondents. The STARS departs decisively from this paradigm by anchoring its scale construction in Item Response Theory, specifically Georg Rasch’s mathematical model for ordered polytomous categories (Andrich, 1978). This modern psychometric framework stipulates that the probability of an individual endorsing a particular category on a resilience item is a logistic function of the distance between the person’s latent coping capacity ($ heta$) and the item’s location/difficulty ($eta$). By utilizing this framework, the authors established that the STARS functions as an interval-level metric capable of tracking non-linear psychological adaptations across clinical thresholds.

Validity

The construct validity of the State-Trait Assessment of Resilience Scale was established through a series of empirical investigations designed to delineate its place within the broader nomological network of psychological well-being, stress physiology, and personality organization.

Convergent and Concurrent Validity

To evaluate convergent validity, Lock, Rees, and Heritage (2019) correlated the STARS subscales with well-established psychometric instruments across an Australian adult cohort (N = 274). The subscales demonstrated robust, statistically significant correlations with benchmark measures of resilience and psychological adjustment:

• Established Resilience Measures: The Trait subscale correlated strongly and positively with the 10-item Connor-Davidson Resilience Scale (CD-RISC-10; Campbell-Sills & Stein, 2007) and the Resilience Scale for Adults (RSA; Friborg et al., 2003), confirming that it measures the core theoretical construct of self-perceived adaptability.
• Affective States: Both subscales were evaluated against the Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988). As theoretically hypothesized, Trait and State Resilience displayed moderate-to-strong positive correlations with Positive Affect, indicating that resilient individuals maintain an optimistic, proactive emotional stance.

Discriminant and Divergent Validity

To ensure that the STARS does not merely reflect generalized distress or overlapping personality constructs, divergent validity analyses were conducted against measures of stress and Big Five personality domains:

• Perceived Stress: The subscales demonstrated substantial inverse correlations with the Perceived Stress Scale (PSS; Cohen, Kamarck, & Mermelstein, 1983). Critically, State Resilience exhibited a significantly stronger negative correlation with immediate perceived stress than Trait Resilience did, confirming that the State subscale is uniquely attuned to acute, proximal strain.
• Five-Factor Personality Domains: Divergent patterns were established using the Ten-Item Personality Inventory (TIPI; Gosling et al., 2003). Trait Resilience showed strong positive associations with Emotional Stability (low Neuroticism) and moderate positive correlations with Extraversion and Conscientiousness. Importantly, the correlations were not high enough to indicate construct redundancy (all r values < .70), demonstrating that resilience constitutes a distinct, self-appraised regulatory capability separate from broad personality traits.

Reliability

The psychometric evaluation of the STARS moved beyond the traditional reliance on Cronbach’s coefficient alpha, incorporating advanced IRT-based indices of reliability and precision:

Rasch Person and Item Reliability

Within the Rasch measurement model, reliability is conceptualized through Person Separation Reliability and Item Separation Reliability. These statistics evaluate how reliably the scale discriminates between persons along the latent trait continuum and how securely the item hierarchy is replicated across different samples:

• Person Separation Reliability: The Rasch person reliability coefficients for both the Trait and State subscales were found to be exceptionally high (exceeding .85), establishing that the items effectively separate individuals into discrete strata of coping capacity ranging from severe depletion to optimal flourishing.
• Item Separation Reliability: The item separation indices approached near-unity (> .95), indicating that the item difficulty hierarchy is robust and invariant across the sample, confirming structural stability.

Measurement Precision Across the Continuum

Classical Test Theory assumes that measurement error is uniform across all score levels. In contrast, the Item Information Functions (IIF) and Test Information Functions (TIF) calculated for the STARS demonstrated that both the State and Trait subscales achieve maximum measurement precision in the middle-to-low ranges of the resilience continuum ($ heta$ between -2.5 and +1.0 logits). This psychometric property is particularly advantageous for clinical diagnostics and occupational health screening, where the primary objective is to accurately identify and differentiate individuals suffering from depleted coping resources or acute psychological exhaustion.

Factor Analysis

Rather than relying solely on linear Confirmatory Factor Analysis (CFA), the structural validity of the STARS was evaluated using David Andrich’s Rating Scale formulation of the Rasch model. This approach tests the foundational axioms of additive conjoint measurement, verifying whether the observational data meet the requirements for objective, interval-level scaling.

Unidimensionality and Local Independence

A central requirement of the Rasch model is unidimensionality—the condition that all items within a subscale measure a single latent construct without substantial multidimensional noise. The authors performed a Principal Components Analysis of Rasch Residuals (PCARR) independently on both the Trait and State item sets:

• The primary Rasch dimension accounted for the vast majority of the total variance in observed responses.
• The eigenvalues of the first contrast in the residuals were well below the standard 2.0 threshold, demonstrating that no systematic secondary dimension was present within either subscale.
• Local item independence was confirmed by examining Yen’s $Q_3$ residual correlation statistics (Christensen, Makransky, & Horton, 2017), ensuring that items were not artificially linked by overlapping wording or shared superficial content.

Item Fit Statistics

Item quality was assessed using Mean-Square (MNSQ) infit and outfit statistics, which detect underfit (unpredictable, noisy responses) and overfit (redundant, deterministic responses):

• All retained items satisfied the conventional quality control criteria, with infit and outfit MNSQ statistics falling comfortably within the accepted psychometric boundaries of 0.60 to 1.40.
• Standardized $z$-values confirmed that the items conformed closely to theoretical Rasch model expectations, validating the distinct structural integrity of the 14-item Trait and 14-item State subscales.

Rating Scale Category Functioning

The developers evaluated the functioning of the 7-point Likert response scale to ensure that each category represented a distinct, ordered level of resilience. In accordance with Linacre’s (2002) criteria for rating scale optimization, the analysis confirmed that:

• Response frequencies across all 7 categories formed smooth, unimodal distributions without underutilized options.
• Average person ability measures monotonically increased with each step up the rating scale.
• Category transition thresholds (step calibrations) advanced monotonically without threshold disordering, confirming that respondents reliably distinguished between adjacent response options.

Instrument / Measurement Tool

• Test Name: State-Trait Assessment of Resilience Scale (STARS)
• Test Type: Dual-construct self-report psychological questionnaire
• Primary Dimensions / Subscales:
  • Trait Resilience Subscale: 14 items assessing an enduring, distal baseline capacity to recover from adversity over time.
  • State Resilience Subscale: 14 items evaluating a transient, proximal coping capacity in response to recent events and immediate challenges.
• Total Item Count: 28 items (initial validated pool)
• Target Population: Adults (validated in general and working community populations aged 18 and older; baseline cohort mean age = 28.33 years, SD = 10.59)
• Administration Format: Standardized self-administered survey (available via secure computer-assisted web administration or traditional pen-and-paper protocols)
• Response Scale: Authentic 7-point Likert scale, ranging across ordered gradations of agreement/frequency calibrated through Rasch threshold analysis
• Completion Time: Approximately 6 to 10 minutes for the full 28-item battery
• Scoring Methodology:
  • Subscales are scored independently to preserve the theoretical distinction between baseline trait and momentary state resilience; items should not be collapsed into an undifferentiated global score.
  • Raw subscale scores can be derived by summing the items (after reversing any negatively worded items), producing separate Trait and State scores.
  • In advanced clinical or research settings, raw scores are converted to interval-level Rasch logit measures using author-provided calibration tables, eliminating non-linear ordinal distortion.

Permissions & Fee and Test Year

The State-Trait Assessment of Resilience Scale was officially published in 2019 in the peer-reviewed journal Australian Psychologist by authors Samantha Lock, Clare S. Rees, and Brody Heritage. The psychometric property rights, theoretical specifications, and initial validation data are governed by standard academic copyright agreements through the publisher (Wiley / Australian Psychological Society / Taylor & Francis).

The scale was developed as an academic instrument intended for psychological research, clinical diagnostics, and organizational well-being assessments. While the conceptual architecture, validation statistics, and psychometric models are published in the open scientific literature, the complete, calibrated item inventory remains under copyright to ensure standardized usage and item integrity. Academic researchers, non-profit institutions, and practicing psychologists wishing to administer the STARS for empirical studies or clinical practice must contact the corresponding author, Dr. Brody Heritage, or the School of Psychology at Curtin University to request the full scale inventory, administration manual, and formal authorization. Commercial entities and external consulting firms must obtain appropriate licensing agreements prior to corporate deployment.

References

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• Bond, T., & Fox, C. M. (2015). Applying the Rasch model: Fundamental measurement in the human sciences (3rd ed.). Routledge. https://doi.org/10.4324/9781315814698
• Campbell-Sills, L., & Stein, M. B. (2007). Psychometric analysis and refinement of the Connor-Davidson Resilience Scale (CD-RISC): Validation of a 10-item measure of resilience. Journal of Traumatic Stress, 20(6), 1019–1028. https://doi.org/10.1002/jts.20271
• Christensen, K. B., Makransky, G., & Horton, M. (2017). Critical values for Yen’s $Q_3$: Identification of local dependence in the Rasch model using residual correlations. Applied Psychological Measurement, 41(3), 178–194. https://doi.org/10.1177/0146621616677520
• Cohen, S., Kamarck, T., & Mermelstein, R. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24(4), 385–396. https://doi.org/10.2307/2136404
• Connor, K. M., & Davidson, J. R. (2003). Development of a new resilience scale: The Connor-Davidson Resilience Scale (CD-RISC). Depression and Anxiety, 18(2), 76–82. https://doi.org/10.1002/da.10113
• Friborg, O., Hjemdal, O., Rosenvinge, J. H., & Martinussen, M. (2003). A new rating scale for adult resilience: What are the central protective resources behind healthy adjustment? International Journal of Methods in Psychiatric Research, 12(2), 65–76. https://doi.org/10.1002/mpr.143
• Gosling, S. D., Rentfrow, P. J., & Swann, W. B., Jr. (2003). A very brief measure of the Big-Five personality domains. Journal of Research in Personality, 37(6), 504–528. https://doi.org/10.1016/S0092-6566(03)00046-1
• Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal, and coping. Springer Publishing Company.
• Linacre, J. M. (2002). Optimizing rating scale category effectiveness. Journal of Applied Measurement, 3(1), 85–106.
• Lock, S., Rees, C. S., & Heritage, B. (2019). Development and psychometric evaluation of the State-Trait Assessment of Resilience Scale. Australian Psychologist, 55(1), 10–25. https://doi.org/10.1111/ap.12434
• Spielberger, C. D. (1983). State-Trait Anxiety Inventory for Adults: Manual and test form. Consulting Psychologists Press.
• Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS scales. Journal of Personality and Social Psychology, 54(6), 1063–1070. https://doi.org/10.1037/0022-3514.54.6.1063
• Wright, B. D., & Masters, G. N. (1982). Rating scale analysis. MESA Press.

Items of the Scale