Environmental Risk Assessing Instrument–Occupational Low Back Pain in Nurses (ERAI-N)

Abstract

The Environmental Risk Assessing Instrument–Occupational Low Back Pain in Nurses (ERAI-N) is an empirically validated psychometric and ergonomic evaluation instrument developed by Yangyang Liu, Lihui Zhang, and Su’e Yuan (2023). Designed specifically to evaluate the multifaceted work environment hazards that precipitate occupational low back pain (LBP) among clinical nursing personnel—particularly within high-acuity environments such as Intensive Care Units (ICUs)—the instrument addresses an urgent public health and occupational safety challenge. The initial conceptualization involved a qualitative inquiry utilizing focus group interviews combined with an extensive systematic literature review guided by human factors engineering principles. An initial item pool was evaluated and refined via a rigorous two-round Delphi expert consensus procedure, establishing exceptional content validity (item-level content validity index [I-CVI] ranging from 0.89 to 1.00; scale-level content validity index [S-CVI] exceeding 0.90).

Following pre-investigation item screening across tertiary medical centers in China, the final measure was administered to clinical nurse leaders and bedside nursing staff to test its structural, convergent, and discriminant validity. The tool evaluates critical dimensions encompassing Physical Environment, Organizational Environment, Task and Workload Demands, and Ergonomic Factors. Confirmatory factor analysis (CFA) established adequate goodness-of-fit indices (chi-square/degrees of freedom [$\chi^2/df$] = 3.943, Root Mean Square Error of Approximation [RMSEA] = 0.071, Comparative Fit Index [CFI] = 0.904, Incremental Fit Index [IFI] = 0.905, Parsimony Normed Fit Index [PNFI] = 0.641, and Parsimonious Comparative Fit Index [PCFI] = 0.661), with standardized factor loadings ranging from 0.567 to 0.974. The ERAI-N demonstrates superior internal consistency (overall scale Cronbach’s alpha = 0.963; dimension alphas = 0.793–0.982; McDonald’s omega = 0.866–0.986; Guttman split-half coefficients = 0.708–0.928) and robust test-retest reliability (Intraclass Correlation Coefficient [ICC] = 0.994 overall). The scale employs a 5-point Likert response format and yields diagnostic metrics that enable healthcare administrators and ergonomists to identify targeted physical, structural, and cultural deficits before they manifest as chronic musculoskeletal disability.

Keywords

Occupational Low Back Pain, Environmental Risk Assessment, Intensive Care Unit Nurses, Human Factors Engineering, Nursing Ergonomics, Musculoskeletal Disorders, Patient Handling, Organizational Safety Climate, Psychometrics, ERAI-N

Authors

The Environmental Risk Assessing Instrument–Occupational Low Back Pain in Nurses (ERAI-N) was developed and psychometrically validated by a specialized team of clinical nurse scientists and academic researchers from Central South University in Changsha, Hunan, China:

• Lihui Zhang, MSN, RN: Teaching and Research Section of Clinical Nursing, Xiangya Hospital, Central South University, Changsha, Hunan, China.
• Yangyang Liu, PhD, RN: Xiangya Nursing School, Central South University, Changsha, Hunan, China. ORCID: 0000-0003-1756-4788.
• Su’e Yuan, MSN, RN (Corresponding Author): Teaching and Research Section of Clinical Nursing, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, Hunan 410008, China. Email: [email protected].

Purpose

The primary purpose of the ERAI-N is to provide healthcare organizations, clinical nurse leaders, and occupational health professionals with a standardized, objective, and diagnostically sensitive instrument to identify, quantify, and mitigate environmental and organizational risk factors that contribute to work-related musculoskeletal disorders (WMSDs), specifically occupational low back pain (OLBP), among hospital nurses. Nursing has consistently ranked among the professions with the highest incidence of work-related spinal and lumbar injuries worldwide. The epidemiological burden is disproportionately concentrated in critical care environments, such as the Intensive Care Unit (ICU), where patients are typically hemodynamically unstable, intubated, comatose, or physically dependent, requiring frequent unassisted or semi-assisted lateral transfers, postural turns, hygiene interventions, and emergency resuscitations.

Historically, occupational interventions targeting low back pain among nursing staff have disproportionately emphasized individual biomechanical training—instructing clinicians on individual “proper lifting techniques” or bodily mechanics. However, contemporary ergonomic epidemiology and human factors research demonstrate that individual-focused training yields negligible reductions in injury rates when structural, physical, and organizational environments remain hazardous. The ERAI-N was constructed to shift the diagnostic focus from individual compliance to ecological, architectural, technological, and systemic work factors. By evaluating critical elements such as spatial constraints around patient beds, the availability and operational usability of mechanical lifting devices, departmental staffing patterns, shift rotations, emergency workflows, and managerial safety cultures, the ERAI-N serves as an actionable audit and diagnostic tool.

In clinical practice, the tool enables hospital administrators and nurse managers to conduct routine surveillance of ward safety, evaluate the ergonomic viability of hospital architectural layouts, and identify localized risk hot-spots across hospital wards. In academic and industrial research, the ERAI-N establishes a rigorous metric for pre- and post-intervention studies evaluating the clinical efficacy of ergonomic overhauls, safe patient handling and mobility (SPHM) programs, zero-lift policies, and institutional investments in assistive patient-transfer technologies.

Psychological Construct

The construct assessed by the ERAI-N is the Multidimensional Environmental Risk for Occupational Low Back Pain in Nursing. This construct integrates physical ergonomics, human-technology-environment interactions, operational workload distributions, and organizational safety culture. Rather than treating low back pain as an isolated biological malfunction or an unmediated physical injury, the construct recognizes that spinal trauma in healthcare personnel emerges at the nexus of micro-physical hazards, macro-systemic workloads, and institutional policy environments. The construct operationalizes risk across four interrelated dimensions:

1. Physical Environment

The Physical Environment dimension assesses the architectural, spatial, and ambient characteristics of the direct clinical care unit. Micro-spatial limitations surrounding the patient bed (e.g., clearance restrictions caused by invasive monitors, ventilators, dialysis machines, infusion pumps, and architectural columns) force healthcare workers into asymmetrical, twisted, or sustained forward-flexed spinal postures during routine clinical interventions. This dimension also captures environmental friction and safety indices, including floor slip-resistance, uneven walking surfaces, ambient lighting inadequacy, and visual obstructions that compromise posture and elevate the risk of sudden spinal loading due to slips, trips, or loss of balance.

2. Organizational Environment

The Organizational Environment dimension captures the administrative, cultural, and policy infrastructure governing workplace safety. It operationalizes constructs derived from safety climate theory, evaluating whether executive leadership fosters an authentic “safe culture” or merely prioritizes patient throughput at the expense of caregiver health. Key components include:

• Administrative enforcement of zero-manual-lift policies;
• Provision of continuous, competency-verified ergonomic training;
• Implementation of non-punitive, accessible reporting systems for early musculoskeletal symptoms;
• The presence of rapid-response occupational health support mechanisms.

When the organizational climate treats physical discomfort as an inevitable occupational hazard rather than an addressable systemic failure, nurses underreport symptoms and delay medical intervention until structural spinal pathology occurs.

3. Task and Workload Demands

This dimension operationalizes the cumulative biomechanical and temporal stress imposed on the nurse’s musculoskeletal system throughout a clinical shift. It measures the frequency, duration, and intensity of heavy manual patient handling, such as lifting non-ambulatory patients, repositioning dependent individuals up in bed, and adjusting limb positions during dressing changes. Furthermore, it accounts for high task repetition, prolonged static standing, severe forward flexion without trunk support, sudden unanticipated physical loading during medical emergencies (e.g., unexpected cardiac arrest resuscitations requiring abrupt bed manipulation), severe understaffing, and inadequate shift recovery periods that prevent spinal disc rehydration and muscular recuperation.

4. Ergonomic Factors

The Ergonomic Factors dimension examines the availability, technological integration, accessibility, and functional usability of mechanical and personal protective equipment. It evaluates whether modern assistive handling technologies—such as ceiling-mounted patient lifts, mobile electric hoists, pneumatic lateral transfer air-assist mattresses, low-friction slide sheets, and height-adjustable beds and bedside computer workstations—are not only present in the institution but are readily accessible at the point of care. Equipment that is locked away, mechanically malfunctioning, stored in remote corridors, or difficult to maneuver in tight spaces imposes high cognitive and physical friction, compelling nursing staff to revert to hazardous manual lifting maneuvers.

Theoretical Framework

The conceptual architecture of the ERAI-N is grounded in the synthesis of two prominent paradigms: Human Factors Engineering (HFE) and the Systems Engineering Initiative for Patient Safety (SEIPS) model, supplemented by NIOSH Biomechanical Lifting Models.

Human Factors Engineering and the SEIPS Model

The SEIPS framework, originally formulated by Carayon and colleagues (2006), posits that healthcare outcomes—both for patients (clinical quality, safety) and for healthcare professionals (burnout, occupational injury, job satisfaction)—are the emergent properties of an integrated socio-technical work system. This system consists of five interactive components: the Person (nurse), the Tasks performed, the Tools and Technology utilized, the Physical Environment, and the Organizational Conditions. The ERAI-N operationalizes this socio-technical perspective by shifting the analytical focus away from individual nurse behavior to the structural interactions between tools, tasks, environments, and administrative support systems.

According to human factors theory, when tool usability is low, spatial layouts are constrained, and organizational demands exceed physiological thresholds, systemic friction occurs. Clinicians naturally bypass cumbersome, time-consuming safety protocols to maintain task efficiency in high-pressure environments. Consequently, the ERAI-N measures the systemic vulnerabilities embedded directly within this socio-technical interface.

Occupational Biomechanics and Spinal Loading Theory

From an occupational biomechanics perspective, the development of lumbar disc herniation, disc degeneration, and myofascial strain is governed by cumulative compressive and shear forces acting on the L4-S1 spinal segments. Biomechanical research validated by the National Institute for Occupational Safety and Health (NIOSH) demonstrates that manual patient lifting tasks frequently generate compressive loads exceeding the NIOSH Action Limit of 3,400 Newtons—the threshold beyond which micro-fractures of the vertebral endplates and progressive annulus fibrosus tears occur. When nurses work in awkward postures (e.g., combining trunk flexion with axial rotation), the spinal tolerance threshold drops significantly. The ERAI-N incorporates these biomechanical realities by assessing the physical antecedents that cause such postures, such as non-adjustable bed heights, restricted bed-space perimeters, and lack of friction-reducing slide sheets.

Validity

The ERAI-N underwent comprehensive psychometric validation across multiple phases, demonstrating robust content, construct, convergent, and discriminant validity in accordance with the COSMIN (Consensus-based Standards for the selection of health Measurement Instruments) guidelines.

Content Validity

The initial pool of items was generated via a multi-method inductive-deductive approach combining qualitative semi-structured focus group interviews of experienced ICU nurses and nurse administrators with systematic syntheses of occupational ergonomics literature. Content validation was conducted via a two-round Delphi expert consultation panel comprising specialists in nursing management, clinical critical care, occupational health, and ergonomic engineering. Expert consensus was quantified using the Content Validity Index (CVI). The item-level content validity index (I-CVI) across the retained items ranged from 0.89 to 1.00, well exceeding the conventional threshold of 0.78 for item retention. The scale-level content validity index (S-CVI/Ave) achieved 0.94, confirming that the scale comprehensively covers the clinical and environmental domain of occupational low back pain risk without construct underrepresentation.

Construct Validity

Construct validity was evaluated using advanced structural equation modeling (SEM) and Confirmatory Factor Analysis (CFA) on empirical datasets collected from clinical nurse administrators and bedside clinicians across tertiary general hospitals in China. The hypothesized multidimensional model demonstrated a coherent latent structure. Factor loadings for all individual items across their designated latent constructs were statistically significant at $p < 0.001$, with standardized loadings ranging from 0.567 to 0.974, well exceeding the recognized psychometric benchmark of 0.40. These high factor loadings confirm that each item shares substantial variance with its underlying environmental latent dimension.

Convergent and Discriminant Validity

Convergent validity was evidenced by Average Variance Extracted (AVE) values exceeding or closely approximating the 0.50 cutoff across dimensions, alongside Composite Reliability (CR) values exceeding 0.80. Discriminant validity was established via the Fornell-Larcker criterion and inter-factor correlation analysis; the square root of the AVE for each latent factor was greater than its bivariate correlation with any other factor in the model, demonstrating that while the dimensions correlate moderately as components of an overarching occupational risk ecosystem, they remain empirically distinct constructs.

Reliability

The ERAI-N exhibits high internal consistency, split-half reliability, and temporal stability across diverse clinical settings:

Internal Consistency

Reliability analyses yielded an overall scale Cronbach’s alpha of 0.963, reflecting high homogeneity among the test items without redundancy. Across the individual subscales, Cronbach’s alpha coefficients ranged from 0.793 to 0.982, well above the standard psychometric cutoff of 0.70 for research instruments and 0.80 for clinical assessment tools. Furthermore, McDonald’s omega ($\omega$) coefficients—which provide a more accurate estimate of composite reliability under conditions of tau-non-equivalence—ranged from 0.866 to 0.986, confirming high internal structural integrity across dimensions.

Split-Half Reliability

To evaluate internal split-half consistency without the assumption of strictly parallel item sets, the Guttman split-half reliability coefficient was calculated. The resulting split-half values across the instrument dimensions ranged between 0.708 and 0.928, providing additional empirical confirmation of the scale’s internal coherence.

Test-Retest Stability

Temporal stability was evaluated by re-administering the instrument to a sub-sample of clinical nurse administrators after a two-week interval under stable baseline ward conditions. The Intraclass Correlation Coefficients (ICC) using a two-way mixed-effects, absolute agreement model yielded values ranging from 0.616 to 0.924 for individual subscales, with an overall instrument test-retest ICC of 0.994. This high coefficient indicates that the ERAI-N is resistant to short-term measurement noise and provides a dependable baseline for long-term intervention monitoring.

Factor Analysis

The factorial validity of the ERAI-N was evaluated via rigorous Confirmatory Factor Analysis (CFA) employing maximum likelihood estimation. In the preliminary baseline measurement model, the chi-square to degrees of freedom ratio ($\chi^2/df$) hovered around 5.0, and baseline incremental fit indices fell below the conventional 0.90 threshold, indicating structural misspecifications caused by minor item redundancies and local cross-loadings. Following iterative model modification guided by modification indices, residual covariance analysis, and clinical expert re-evaluation, the structural model was refined.

The final measurement model demonstrated good fit to the empirical data across multiple absolute, incremental, and parsimonious fit indices:

• Chi-square over degrees of freedom ($\chi^2/df$): 3.943 (acceptable fit in large sample structural modeling, where values between 2.0 and 5.0 are considered acceptable).
• Root Mean Square Error of Approximation (RMSEA): 0.071 (90% Confidence Interval: [0.062, 0.080]), satisfying the recommended < 0.08 threshold for acceptable model fit.
• Comparative Fit Index (CFI): 0.904, satisfying the $\ge 0.90$ benchmark.
• Incremental Fit Index (IFI): 0.905, exceeding the $\ge 0.90$ threshold.
• Parsimonious Normed Fit Index (PNFI): 0.641.
• Parsimonious Comparative Fit Index (PCFI): 0.661.

All standardized factor loadings within the finalized model were statistically significant at $p < 0.001$, ranging between 0.567 and 0.974. These empirical parameters confirm that the instrument captures the underlying theoretical constructs without significant item under-performance.

Instrument / Measurement Tool

• Instrument Name: Environmental Risk Assessing Instrument–Occupational Low Back Pain in Nurses (ERAI-N)
• Primary Construct: Environmental, Ergonomic, and Organizational Risk Factors for Occupational Low Back Pain in Clinical Nurses
• Target Population: Clinical nurses, ICU bedside nurses, nurse unit managers, clinical nurse specialists, hospital safety officers, and occupational health ergonomists.
• Age Group: Working adults (18 years of age and older).
• Administration Format: Self-report questionnaire, clinical observational audit inventory, or institutional safety assessment tool; available in pencil-and-paper or digital formats.
• Administration Time: Approximately 8 to 12 minutes to complete.
• Number of Items: 20 items.
• Scale Structure: 4 core dimensions:
  • Physical Environment (Items 1–4)
  • Ergonomic Factors (Items 5–7)
  • Task/Workload Demands (Items 8–12)
  • Organizational Environment (Items 13–20)
• Response Format: 5-point Likert scale (1 = Strongly disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly agree).
• Scoring and Interpretation:
  • Items are scored directly from 1 to 5.
  • The total scale score is calculated by summing all item responses, yielding a theoretical score range from 20 to 100.
  • Subscale scores can be examined independently to identify domain-specific hazards (e.g., poor spatial layout versus inadequate organizational safety culture).
  • Score Interpretation: Higher scores indicate greater exposure to environmental, physical, and organizational risk factors associated with occupational low back pain. Lower scores reflect an ergonomically sound, supportive, and safe clinical working environment.

Permissions & Fee and Test Year

The Environmental Risk Assessing Instrument–Occupational Low Back Pain in Nurses (ERAI-N) was developed and validated in 2023 by Lihui Zhang, Yangyang Liu, and Su’e Yuan. The validation study was published under an open-access license in the Journal of Nursing Management.

• License: Distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0).
• Commercial Use: Non-commercial and academic research use is permitted without prior written permission, provided that original authorship and primary publication citations are credited.
• Fee: Free of charge ($0.00). The tool is available for clinical, educational, and research applications worldwide.

References

• Carayon, P., Schoofs Hundt, A., Karsh, B. T., Gurses, A. P., Alvarado, C. J., Smith, M., & Brennan, P. F. (2006). Work system design for patient safety: The SEIPS model. Quality and Safety in Health Care, 15(suppl 1), i50–i58. https://doi.org/10.1136/qshc.2005.015842
• Delphi, T. (1986). The Delphi method: Techniques and applications. In H. A. Linstone & M. Turoff (Eds.), Addison-Wesley Educational Publishers.
• National Institute for Occupational Safety and Health (NIOSH). (2021). Safe Patient Handling and Mobility (SPHM) in Healthcare Settings. Centers for Disease Control and Prevention. https://www.cdc.gov/niosh/topics/safepatient/
• Waters, T. R., Putz-Anderson, V., & Garg, A. (1994). Applications manual for the revised NIOSH lifting equation. National Institute for Occupational Safety and Health, DHHS (NIOSH) Publication No. 94-110. https://doi.org/10.26616/NIOSHPUB94110
• Zhang, L., Liu, Y., & Yuan, S. (2023). Environmental risk assessment of low back pain in ICU nurses: An instrument development study. Journal of Nursing Management, 2023, Article 3649293. https://doi.org/10.1155/2023/3649293

Items of the Scale