Poverty-Related Stress Scale

1. Abstract

The Poverty-Related Stress Scale (PRSS) is an advanced, multidimensional psychometric instrument developed by Brianna Allen, Jeffrey Klibert, and Llewellyn E. van Zyl (2023) designed to quantify the multifaceted, chronic, and toxic stress experienced by adults living in impoverished, economically marginalized, and resource-deprived environments. Historically, psychological assessment and public health epidemiology have assessed socioeconomic hardship primarily through unidimensional objective markers (e.g., federal poverty thresholds, household income) or restricted subjective metrics that isolate financial strain while disregarding the broader physical, interpersonal, and environmental disruptions endemic to socioeconomic disadvantage. The PRSS addresses this long-standing operational limitation by conceptualizing poverty-related stress as a hierarchical, multifaceted construct encompassing 15 items distributed across three distinct yet interrelated sub-domains: Noise Disturbance (5 items), Housing Dysfunction (6 items), and Financial Distress (4 items). Evaluated on a 4-point Likert response scale ranging from 1 (Never) to 4 (Always), the instrument allows respondents to self-report the occurrence and psychological burden of contextual stressors experienced within their domestic, community, and economic spheres.

Psychometrically, the PRSS was validated through a rigorous multi-study, longitudinal research design across independent adult community samples within the United States (Study 1: N = 206; Study 2: N = 400; Study 3: N = 470 at Time 1 and N = 219 at Time 2). Utilizing Exploratory Structural Equation Modeling (ESEM) and bifactor-ESEM frameworks, the authors demonstrated that a hierarchical structure—comprising an overarching global poverty-related stress factor alongside three well-differentiated specific factors—exhibited superior fit compared to traditional, overly restrictive independent-clusters Confirmatory Factor Analysis (CFA) configurations. The scale demonstrated high internal consistency across all dimensions, robust longitudinal measurement invariance, and compelling convergent, concurrent, and prospective predictive validity. Specifically, PRSS scores predicted significant longitudinal variance in elevated internalizing symptomatology (major depression and generalized anxiety) and corresponding decrements in psychological flourishing over time. The PRSS constitutes a vital psychometric asset for clinical researchers, psychiatric epidemiologists, and community health practitioners seeking to isolate the exact psychosocial mechanisms linking structural inequality to psychiatric morbidity.

2. Keywords

Poverty-Related Stress Scale, socioeconomic status, psychological stress, psychometrics, exploratory structural equation modeling, housing instability, environmental noise, financial distress, depression, anxiety, flourishing, social causation theory, health disparities.

3. Authors

The Poverty-Related Stress Scale was conceptualized, operationalized, and psychometrically validated by a collaborative team of behavioral scientists, clinical psychologists, and quantitative methodologists:

• Brianna Allen — Department of Psychology, Georgia Southern University, Statesboro, Georgia, United States.
• Jeffrey Klibert, Ph.D. (Corresponding Author) — Professor of Psychology, Department of Psychology, Georgia Southern University, Statesboro, Georgia, United States. Email: [email protected].
• Llewellyn E. van Zyl, Ph.D. — Department of Human Resource Management, University of Twente, Enschede, Netherlands; Optentia Research Focus Area, North-West University, Vanderbijlpark, South Africa; and Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven, Netherlands.

4. Purpose

The primary purpose of the Poverty-Related Stress Scale (PRSS) is to deliver a theoretically grounded, adult-normed, and psychometrically robust measurement tool capable of evaluating the toxic, cumulative, and multidimensional stressors inherent to poverty. For decades, behavioral health literature has acknowledged the deleterious impact of low socioeconomic status (SES) on mental health and physical morbidity. However, measurement instruments historically employed in this literature suffered from three systemic flaws. First, research frequently substituted proxy objective markers—such as income-to-needs ratios or parental educational attainment—for the actual subjective experience of stress. While objective indices identify socioeconomic classification, they fail to illuminate how individuals perceive, navigate, and internalize the chronic adversity of their daily environments. Second, existing subjective hardship scales (e.g., the Economic Hardship Questionnaire) focused almost exclusively on monetary scarcity and consumption restrictions, effectively omitting the non-monetary physical and environmental hazards that characterize low-income living environments. Third, earlier stress inventories were predominantly normed on children and adolescents within the purview of pediatric family stress models, leaving a distinct clinical and empirical void regarding how adults directly bear the chronic psychological burdens of poverty.

From a clinical and applied healthcare standpoint, the PRSS serves to bridge these structural and diagnostic voids. Chronic poverty constitutes a primary driver of health disparities, consistently predicting disproportionate rates of major depressive disorder, generalized anxiety disorder, substance misuse, and chronic somatic conditions mediated by prolonged allostatic load. By differentiating poverty-related stress into granular, modifiable domains—including acute community and domestic acoustic pollution, structural shelter decay and instability, and acute economic deprivation—the PRSS enables mental health clinicians, social workers, and primary care providers to map the precise environmental etiologies undermining an individual’s psychological well-being. Rather than treating depressive or anxious symptomatology in a contextual vacuum, clinicians utilizing the PRSS can identify whether therapeutic non-compliance, cognitive fatigue, or emotional dysregulation stem from severe domestic crowding, neighborhood violence, chronic sleep disruption due to environmental decibels, or immediate threats of homelessness and eviction.

From a research and public policy vantage point, the instrument empowers investigators to rigorously evaluate the efficacy of targeted anti-poverty interventions, universal basic income trials, community noise abatement legislation, and subsidized housing initiatives. By offering an outcome metric sensitive to psychosocial fluctuations over time, the PRSS allows epidemiologists and policy analysts to ascertain which specific socio-structural interventions yield the most profound reductions in stress-induced psychiatric vulnerabilities, thereby informing evidence-based structural reforms.

5. Psychological Construct

The psychological construct operationalized by the PRSS is poverty-related stress, defined as the ongoing, cumulative, and context-specific psychological strain generated by exposure to systemic resource deprivation, physical environmental degradation, and socioeconomic marginalization. Unlike acute, episodic life events (e.g., the death of a relative or sudden divorce) or generalized perceived stress, poverty-related stress is structural, chronic, and unremitting. It directly impairs executive functioning, depletes self-regulatory cognitive reserves, and disrupts biological homeostasis. Within the PRSS, this overarching construct is modeled as a hierarchical phenomenon comprising three distinct first-order sub-constructs:

Noise Disturbance

The Noise Disturbance dimension (Items 1–5) captures the pervasive psychological strain, sleep fragmentation, cognitive disruption, and chronic irritability caused by intrusive acoustic pollution occurring both within and outside the home. In impoverished and structurally underfunded neighborhoods, residential units are frequently situated adjacent to major transportation arteries, industrial complexes, highway corridors, or construction zones, compounded by elevated community violence and unaddressed neighborhood commotion. Concurrently, high-density occupancy—characterized by multiple family units sharing cramped interior living quarters—amplifies internal domestic volume, including crying infants, loud family members, and shared electronic appliances. This continuous acoustic overload prevents home environments from serving as psychological refuges or restorative niches. Sustained exposure to uncontrolled noise triggers persistent sympathetic nervous system arousal, sleep architecture breakdown, and chronic cognitive fatigue, driving feelings of frustration and domestic alienation.

Housing Dysfunction

The Housing Dysfunction dimension (Items 6–11) evaluates stress originating from physical structural hazards, residential instability, domestic crowding, and extreme resource desperation. Low-income housing units are systematically prone to deferred maintenance, leading to severe structural degradation, water intrusions, mold infestations, inadequate insulation, and municipal condemnation threats. Furthermore, the persistent vulnerability to formal eviction or displacement forces individuals into unstable shelter arrangements, such as residing in homeless shelters, automobiles, churches, or couch-surfing in overcrowded apartments. Crucially, the PRSS captures the extreme coping behaviors precipitated by severe housing and subsistence deprivation, such as reliance on soup kitchens, scavenging garbage bins, and experiencing interpersonal estrangement due to the incarceration of loved ones. This sub-construct captures the profound loss of physical security, biological safety, and domestic dignity that directly challenges fundamental survival needs.

Financial Distress

The Financial Distress dimension (Items 12–15) measures the psychological toll of chronic economic shortfall, consumption restrictions, and the perpetual inability to secure material necessities through conventional monetary channels. Beyond the mathematical calculation of income versus expenses, this construct captures the existential and interpersonal weight of monetary deprivation. It assesses the psychological anguish of relinquishing long-term aspirational goals, personal hopes, and educational dreams merely to secure basic biological sustenance (food, warmth, and shelter). Additionally, it addresses the anticipatory anxiety surrounding acute mobility constraints—specifically the inability to finance sudden emergency relocations—and the relational strain and conflict injected into marital and familial dynamics as a consequence of unyielding fiscal pressure.

6. Theoretical Framework

The Poverty-Related Stress Scale is grounded in a triad of foundational paradigms within developmental psychopathology, medical sociology, and stress physiology: the Social Causation Hypothesis, the Family Stress Model, and Bronfenbrenner’s Bioecological Systems Theory.

Social Causation Hypothesis

The conceptual bedrock of the PRSS rests upon the Social Causation Hypothesis, formulated and refined by researchers such as Wadsworth and Achenbach (2005) and Aneshensel (1992). In direct contrast to social selection (drift) theory—which posits that genetic or neurodevelopmental liabilities cause individuals to drift downward into lower socioeconomic strata—social causation asserts that the structural realities of poverty exert a direct, causal, and toxic effect on the genesis of psychopathology. Living in low-SES strata exposes individuals to a disproportionate clustering of chronic environmental, social, and economic adversities. These continuous stressors exhaust neuroendocrine stress systems (such as the hypothalamic-pituitary-adrenal axis), diminish psychological resilience, and inevitably trigger internalizing pathologies such as clinical depression and generalized anxiety disorders.

The Family Stress Model

The operationalization of the PRSS is heavily indebted to the seminal Family Stress Model pioneered by Conger et al. (1994) and subsequently expanded within the Adaptation to Poverty-Related Stress Model by Wadsworth, Compas, and colleagues (2005, 2011). This framework posits that objective economic adversity does not impact psychological functioning in isolation; rather, it cascades through intermediate ecological processes. Severe financial hardship initiates acute economic pressure, which subsequently triggers parental emotional distress, housing destabilization, and destructive interpersonal dynamics. In turn, these environmental disruptions permeate the immediate living space, degrading family cohesion and overwhelming adaptive coping mechanisms. The PRSS directly integrates these intermediate ecological stressors—such as relational conflict, housing eviction risks, and interpersonal avoidance—into its structural taxonomy.

Bioecological Systems and Conservation of Resources Theories

The incorporation of physical environmental hazards (noise and structural decay) aligns with Urie Bronfenbrenner‘s Bioecological Systems Theory (1979). Bronfenbrenner emphasized that human development and psychological stability are intimately dictated by the proximal microsystem—the physical environment with which the individual maintains direct, daily contact. When the physical microsystem is marked by continuous acoustic chaos and structural hazards, the environment ceases to provide the physical predictability necessary for cognitive rest and emotional regulation. Complementing this, Stevan Hobfoll’s Conservation of Resources (COR) theory explains how poverty forces individuals into rapid resource depletion spirals. When scarce psychological and material resources must be perpetually expended to mitigate noise and ward off housing loss, individuals lack the surplus energy required to invest in positive psychological functioning, ultimately eroding psychological flourishing.

7. Validity

The psychometric validity of the PRSS was established through a series of empirical investigations designed to evaluate construct, convergent, discriminant, concurrent, and longitudinal predictive validity across distinct adult community cohorts in the United States.

Construct and Structural Validity

Construct validity was validated through rigorous structural equation modeling frameworks. Dimensional analyses confirmed that the 15 items loaded robustly onto their respective theoretical factors: Noise Disturbance (5 items), Housing Dysfunction (6 items), and Financial Distress (4 items). The scale’s construct validity is anchored in its ability to isolate unique variance contributed by physical environmental stressors (noise and housing) that had been omitted from legacy economic hardship inventories, confirming that poverty-related stress cannot be reduced to a unidimensional economic parameter.

Convergent and Concurrent Validity

Concurrent validity was established by evaluating the bivariate and latent correlations between the PRSS (and its subscales) and validated measures of adult behavioral health, psychiatric distress, and psychological well-being. Across validation samples, the PRSS demonstrated statistically significant, positive convergent associations with standardized inventories measuring:

• Major Depression: Demonstrating strong positive correlations with standardized depressive symptom inventories (e.g., Burns Depression Checklist, PHQ-9), validating the social causation premise that poverty-related stressors serve as primary antecedents to depressive affect, anhedonia, and cognitive despair.
• Generalized Anxiety: Demonstrating statistically significant positive correlations with clinical anxiety scales, indicating that chronic environmental unpredictability, housing eviction threats, and financial volatility fuel hyperarousal and persistent somatic worry.
• Psychological Flourishing: Exhibiting significant, moderate-to-strong negative correlations with measures of psychological flourishing and positive psychological functioning (e.g., Flourishing Scale). High PRSS scores reliably correspond with diminished meaning in life, impaired personal growth, and degraded subjective well-being.

Predictive and Longitudinal Validity

A critical psychometric hallmark of the PRSS is its longitudinal predictive validity, evaluated in Study 3 using a prospective panel design (Time 1: N = 470; Time 2: N = 219). Latent regression analyses demonstrated that baseline poverty-related stress accounted for significant unique variance in internalizing psychiatric symptoms (depression and anxiety) and psychological flourishing measured months later, even after controlling for baseline symptom severity. This prospective predictive power confirms that the PRSS captures active, etiologic stressors that prospectively degrade mental health over time.

Discriminant Validity

Discriminant validity was verified across ESEM models, where the three first-order factors demonstrated sufficient conceptual and statistical independence. Average variance extracted (AVE) estimates and moderate inter-factor correlations (typically ranging from .35 to .65) confirmed that while Noise Disturbance, Housing Dysfunction, and Financial Distress share common variance under an overarching poverty-stress umbrella, they represent non-redundant, distinct facets of socioeconomic adversity.

8. Reliability

The PRSS has demonstrated high internal consistency, composite reliability, and measurement stability across diverse empirical cohorts.

Internal Consistency

Throughout scale development and cross-validation studies, the total scale and its subscales have consistently yielded strong internal consistency estimates exceeding recommended psychometric standards (Cronbach’s α ≥ .80; McDonald’s ω ≥ .80):

• Full Scale (15 items): Cronbach’s alpha coefficients routinely range from .87 to .92, indicating minimal measurement error in capturing overarching poverty-related stress.
• Noise Disturbance Subscale (5 items): Cronbach’s alpha ranges from .84 to .89 across validation samples, demonstrating tight item-homogeneity regarding acoustic disruptions.
• Housing Dysfunction Subscale (6 items): Cronbach’s alpha ranges from .79 to .85, reflecting strong internal consistency despite capturing diverse manifestations of housing distress (e.g., eviction, crowding, condemnation).
• Financial Distress Subscale (4 items): Cronbach’s alpha ranges from .82 to .88, confirming the reliable capture of economic strain and consumption sacrifice.

Temporal Stability and Longitudinal Invariance

To ensure that the PRSS reliably assesses stable environmental stress rather than transient state-dependent mood fluctuations, longitudinal invariance was formally evaluated across Time 1 and Time 2 in Study 3. Using longitudinal structural equation modeling, the authors tested hierarchical levels of invariance:

• Configural Invariance: Established that the overall factor structure remained identical across temporal assessment waves.
• Metric (Weak) Invariance: Verified that factor loadings were invariant across time (ΔCFI < .01, ΔRMSEA < .015), indicating that participants attributed identical psychological meaning to the scale items longitudinally.
• Scalar (Strong) Invariance: Confirmed that item intercepts remained stable across measurement intervals, demonstrating that changes in PRSS scores over time reflect true developmental changes in poverty-related stress rather than measurement drift or instrumentation artifacts.

9. Factor Analysis

The latent architecture of the PRSS was resolved through advanced factor analytic methodology, progressing from initial exploratory phases to comprehensive latent structural comparisons.

Sample Characteristics and Analytic Workflow

Factorial validation was conducted across three distinct empirical samples:

• Study 1 (Exploratory Phase, N = 206): Conducted with low-income adult community participants to explore initial latent dimensionality and refine candidate items using exploratory factor analysis.
• Study 2 (Structural Confirmation, N = 400): Administered to a larger, diverse adult sample to rigorously contrast competing structural models (unidimensional CFA, independent 3-factor CFA, higher-order CFA, and ESEM).
• Study 3 (Longitudinal Invariance, N = 470 at T1, N = 219 at T2): Designed to verify structural replication and test longitudinal measurement invariance over time.

Superiority of Exploratory Structural Equation Modeling (ESEM)

A critical methodological finding was the empirical superiority of Exploratory Structural Equation Modeling (ESEM) over traditional Confirmatory Factor Analysis (CFA). Traditional CFA relies on the “independent cluster model” (ICM-CFA), which forces all non-target item cross-loadings to exactly zero. In complex, ecologically intertwined psychosocial phenomena like poverty, items naturally share peripheral substantive variance. Imposing zero-loading restrictions in ICM-CFA resulted in inflated inter-factor correlations (often exceeding .80) and suboptimal model fit.

When modeled via hierarchical ESEM using target rotation (Mplus), the PRSS achieved exceptional fit to the data: Comparative Fit Index (CFI) > .96, Tucker-Lewis Index (TLI) > .94, Root Mean Square Error of Approximation (RMSEA) < .05, and Standardized Root Mean Square Residual (SRMR) < .04. In this hierarchical ESEM framework, all 15 items loaded strongly onto their designated primary factors (standardized loadings generally ranging between .55 and .88) while maintaining minimal, theoretically justifiable cross-loadings. This confirmed the presence of a general, overarching poverty-related stress factor alongside three well-defined first-order dimensions: Noise Disturbance, Housing Dysfunction, and Financial Distress.

10. Instrument / Measurement Tool

The Poverty-Related Stress Scale is standardized as a self-administered, adult-normed psychological questionnaire. The instrument specifications are summarized below:

• Test Type: Standardized self-report psychometric rating scale.
• Format: Pen-and-paper or computerized digital administration (compatible with Qualtrics, REDCap, and online psychological testing platforms).
• Target Population: Adults (aged 18 and older) within general community and low-income populations.
• Item Count: 15 items total.
• Subscale Breakdown:
  • Noise Disturbance: 5 items (Items 1 through 5)
  • Housing Dysfunction: 6 items (Items 6 through 11)
  • Financial Distress: 4 items (Items 12 through 15)
• Authentic Response Scale: 4-point Likert scale:
  • 1 = Never
  • 2 = Sometimes
  • 3 = Often
  • 4 = Always
• Scoring Formula and Instructions:
  • Subscale Scores: Calculated by summing or averaging the responses to the items within each respective subscale (Noise Disturbance: Items 1–5; Housing Dysfunction: Items 6–11; Financial Distress: Items 12–15).
  • Total Score: Calculated by summing responses across all 15 items (score range: 15 to 60). Alternatively, an overall mean score can be computed (score range: 1.00 to 4.00).
  • Reverse Scoring: There are no reverse-scored items on this scale.
  • Interpretation: Higher total and subscale scores indicate higher levels of experienced poverty-related stress, environmental disruption, and socioeconomic strain.
• Administration Time: Approximately 3 to 5 minutes.

11. Permissions & Fee and Test Year

The Poverty-Related Stress Scale was formally developed and published in 2023 by Brianna Allen, Jeffrey Klibert, and Llewellyn E. van Zyl. The seminal validation study was published in the peer-reviewed journal Depression and Anxiety (Volume 2023, Article ID 6659030, https://doi.org/10.1155/2023/6659030).

Licensing and Accessibility: The scale was published under an Open Access framework governed by the Creative Commons Attribution License (CC BY 4.0). Under this license, researchers, clinicians, educators, and public health entities are permitted to copy, reproduce, distribute, and administer the instrument free of charge for non-commercial or academic research purposes, provided that proper scholarly attribution is credited to the original authors and journal publication. Commercial distribution, proprietary integration into commercial software platforms, or modification for commercial re-use requires formal permission from the corresponding author (Dr. Jeffrey Klibert at [email protected]).

12. References

• Allen, B., Klibert, J., & van Zyl, L. E. (2023). Poverty-Related Stress Scale. Depression and Anxiety, 2023, Article ID 6659030. https://doi.org/10.1155/2023/6659030
• American Psychological Association. (2017). Stress and health disparities: Contexts, mechanisms, and interventions among racial/ethnic minority and low-socioeconomic status populations. American Psychological Association.
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• Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. Harvard University Press. https://doi.org/10.4159/9780674028845
• Burns, D. D. (1989). The Feeling Good Handbook. William Morrow and Company.
• Conger, R. D., Ge, X., Elder, G. H., Lorenz, F. O., & Simons, R. L. (1994). Economic stress, coercive family process, and developmental problems of adolescents. Child Development, 65(2), 541–561. https://doi.org/10.2307/1131401
• Cooper, S., Lund, C., & Kakuma, R. (2012). The measurement of poverty in psychiatric epidemiology in LMICs: Critical review and recommendations. Social Psychiatry and Psychiatric Epidemiology, 47(9), 1499–1516. https://doi.org/10.1007/s00127-011-0457-6
• Gallo, L. C., & Matthews, K. A. (2003). Understanding the association between socioeconomic status and physical health: Do negative emotions play a role? Psychological Bulletin, 129(1), 10–51. https://doi.org/10.1037/0033-2909.129.1.10
• Long, K., & Renbarger, R. (2023). Persistence of poverty: How measures of socioeconomic status have changed over time. Educational Researcher, 52(3), 144–154. https://doi.org/10.3102/0013189X221141409
• Mayo, C., Pham, H., Patallo, B., Joos, C., & Wadsworth, M. (2022). Coping with poverty-related stress: A narrative review. Developmental Review, 64, Article 101024. https://doi.org/10.1016/j.dr.2022.101024
• McDonald, A., Thompson, A., Perzow, S., Joos, C., & Wadsworth, M. (2020). The protective roles of ethnic identity, social support, and coping on depression in low-income parents: A test of the adaptation to poverty-related stress model. Journal of Consulting and Clinical Psychology, 88(6), 504–515. https://doi.org/10.1037/ccp0000477
• Morin, A. J. S. (2020). Modern factor analytic techniques: Bifactor models, exploratory structural equation modeling (ESEM) and bifactor-ESEM. In Handbook of Quantitative Methods for Educational Research (pp. 1044–1076). Wiley. https://doi.org/10.1002/9781119568124.ch51
• Santiago, C. D., Wadsworth, M. E., & Stump, J. (2011). Socioeconomic status, neighborhood disadvantage, and poverty-related stress: Prospective effects on psychological syndromes among diverse low-income families. Journal of Economic Psychology, 32(2), 218–230. https://doi.org/10.1016/j.joep.2009.10.008
• United States Census Bureau. (2022). Poverty in the United States: 2021 (Current Population Reports, P60-277). U.S. Government Printing Office.
• Wadsworth, M. E., & Achenbach, T. M. (2005). Explaining the link between low socioeconomic status and psychopathology: Testing two mechanisms of the social causation hypothesis. Journal of Consulting and Clinical Psychology, 73(6), 1146–1153. https://doi.org/10.1037/0022-006X.73.6.1146
• Wadsworth, M. E., & Berger, L. E. (2006). Adolescents coping with poverty-related family stress: Prospective predictors of coping and psychological symptoms. Journal of Youth and Adolescence, 35(1), 54–67. https://doi.org/10.1007/s10964-005-9022-5
• Wadsworth, M. E., Raviv, T., Compas, B. E., & Connor-Smith, J. K. (2005). Parent and adolescent responses to poverty-related stress: Tests of mediated and moderated coping models. Journal of Child and Family Studies, 14(2), 283–298. https://doi.org/10.1007/s10826-005-5056-2
• Wadsworth, M. E., Raviv, T., Santiago, C. D., & Etter, E. M. (2011). Testing the adaptation to poverty-related stress model: Predicting psychopathology symptoms in families facing economic hardship. Journal of Clinical Child & Adolescent Psychology, 40(4), 646–657. https://doi.org/10.1080/15374416.2011.581622
• Wagle, U. (2018). Rethinking poverty: Definition and measurement. International Social Science Journal, 68(227-228), 183–193. https://doi.org/10.1111/issj.12192

13. Items of the Scale