SafeQuest climate measure

1. Abstract

The SafeQuest climate measure is a specialized, 30-item psychometric instrument designed to evaluate safety climate within primary care organizations. Developed by Carl de Wet, Wendy Spence, Robert Mash, Peter Johnson, and Paul Bowie in 2010, the tool was engineered to address a critical empirical gap: while safety climate instruments were widely utilized in secondary and tertiary inpatient healthcare contexts, few validated, psychometrically robust tools existed that accommodated the complex operational, organizational, and multidisciplinary realities of general medical practice. SafeQuest assesses healthcare personnel’s shared perceptions of the organizational policies, practices, procedures, and leadership behaviors that prioritize patient safety above operational expediencies.

The instrument captures safety climate across five distinct yet interrelated latent dimensions: Workload (5 items), Communication (5 items), Leadership (6 items), Teamwork (5 items), and Safety Systems (9 items). All 30 items are administered using a 7-point Likert scale ranging from 1 (“Strongly Disagree”) to 7 (“Strongly Agree”), supplemented by an explicit “Not Applicable” option. SafeQuest is designed for completion by all members of the primary healthcare team, encompassing general practitioners, practice nurses, practice managers, administrative receptionists, and allied healthcare professionals, whether practice-based or operating within community outreach settings.

Extensive psychometric evaluations have demonstrated high reliability and validity for the instrument. SafeQuest exhibits strong internal consistency, with overall scale Cronbach’s alpha coefficients exceeding .90, and subscale coefficients consistently falling between .70 and .88 across diverse primary care samples. Exploratory and confirmatory factor analyses support its five-factor structural architecture. SafeQuest provides general practices with diagnostic capability to detect organizational vulnerabilities, benchmark performance across regional health boards, evaluate quality improvement initiatives, and proactively mitigate the root systemic causes of clinical errors before adverse events reach patients.

2. Keywords

SafeQuest, safety climate, primary care, patient safety, organizational climate, general practice, healthcare quality improvement, medical error reporting, psychometrics, clinical governance

3. Authors

The SafeQuest climate measure was conceptualized, operationalized, and psychometrically validated by a multidisciplinary team of primary care physicians, health services researchers, and medical educators in the United Kingdom and South Africa:

• Carl de Wet, MBChB, FCFP, FRACGP, PhD: General practitioner and clinical researcher. Academic affiliations include NHS Education for Scotland (NES), the Academic Unit of General Practice and Primary Care at the University of Glasgow, and Griffith University School of Medicine and Dentistry, Australia.
• Wendy Spence, BSc, MSc, PhD: Health services researcher and psychometrician specializing in organizational culture, occupational health, and workforce evaluation within healthcare environments. Associated with NHS Education for Scotland and the School of Medicine, Dentistry and Nursing at the University of Glasgow.
• Robert Mash, MBChB, FCFP, PhD: Professor of Family Medicine and Primary Care, Division of Family Medicine and Primary Care, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa. Renowned expert in primary care systems research and clinical governance.
• Peter Johnson, BSc, MSc: Medical statistician and researcher in health services methodology, affiliated with NHS Education for Scotland, providing expertise in multivariate psychometric validation, factor analysis, and measurement error modeling.
• Paul Bowie, BSc, PhD, C.ErgHF, FIES, FRCPE: Program Director (Safety and Improvement) at NHS Education for Scotland; Honorary Professor at the Institute of Health and Wellbeing, University of Glasgow. A leading international authority on human factors, clinical ergonomics, significant event analysis, and patient safety science in primary care.

4. Purpose

The primary purpose of the SafeQuest climate measure is to quantitatively capture and diagnose the shared perceptions of healthcare workers regarding the prioritization, execution, and systematic management of patient safety within primary care settings. Historically, the discipline of patient safety focused overwhelmingly on acute hospital environments, intensive care units, and surgical theaters. However, epidemiological data demonstrate that the vast majority of patient consultations occur within primary care; in countries with established universal healthcare systems, such as the United Kingdom’s National Health Service (NHS), hundreds of millions of primary care interactions transpire annually. Although catastrophic clinical errors per capita may appear lower in general practice than in surgical wards, the sheer volume of encounters means that avoidable harm, diagnostic delays, medication errors, and administrative communication failures affect substantial numbers of patients.

Before SafeQuest, primary care organizations frequently adapted hospital-oriented safety climate instruments, such as the Safety Attitudes Questionnaire (SAQ) or the Hospital Survey on Patient Safety Culture (HSOPSC). These adaptations often demonstrated poor ecological validity. General medical practices operate under organizational architectures that differ markedly from hospital wards: they are typically small-to-medium-sized professional enterprises, often run as independent partnerships or community trusts, characterized by flat hierarchies, high administrative interdependency, direct community interfaces, and a high proportion of non-clinical staff (e.g., medical receptionists, coders, practice managers) whose daily decisions directly affect patient safety trajectories. SafeQuest was developed explicitly to address these distinct operational, structural, and cultural realities.

In clinical and organizational practice, SafeQuest serves several essential functions:

• Baseline Safety Diagnostic: It provides a baseline assessment of an organization’s safety profile, identifying hidden vulnerabilities such as chronic unmanageable workloads, reluctance to disclose errors, or dysfunctional communication channels between clinical and administrative personnel.
• Facilitating Team Reflection and Significant Event Analysis: Survey outputs are compiled into detailed feedback reports, enabling practice teams to engage in structured, non-punitive reflections during protected learning time. This aligns with systems-based root cause analysis and quality improvement frameworks.
• Evaluating Interventions: SafeQuest allows clinical governance boards, primary care trusts, and practice leaders to conduct longitudinal evaluations of organizational interventions, such as the implementation of new electronic health record systems, safety checklist integrations, or leadership training programs.
• Benchmarking and Multi-Level Governance: Health authorities can aggregate anonymized practice-level data across regional clusters to detect macro-level systemic pressures, optimize resource allocation, and target educational support to practices exhibiting high organizational vulnerability.

5. Psychological Construct

SafeQuest measures safety climate, defined within organizational psychology as the measurable, surface-level manifestation of the deeper, enduring safety culture of an organization. Whereas safety culture encompasses the deeply embedded unconscious assumptions, core values, historical norms, and underlying philosophies of an institution, safety climate captures the workforce’s collective, temporal perceptions and attitudes toward how safety is prioritized, rewarded, supported, and enacted in daily practice. SafeQuest conceptualizes safety climate in primary care as a multidimensional construct comprising five discrete operational dimensions:

1. Workload (Items 1–5)

The Workload subscale assesses staff perceptions regarding the manageable nature of clinical and administrative demands, staffing adequacy, temporal pressures, and the operational risks associated with excessive work velocity. High workloads in primary care have been empirically linked to cognitive fatigue, diagnostic oversight, administrative lapses, and physician burnout. This construct examines whether employees routinely work beyond contracted hours, whether staffing ratios are sufficient to mitigate risk, and whether staff are forced to cut corners or perform complex clinical or administrative duties without adequate formal training.

2. Communication (Items 6–10)

The Communication subscale measures the openness, clarity, efficacy, and psychological accessibility of clinical and administrative information exchanges. Crucially, within primary care, safety breakdowns frequently occur at the interface between clinical staff (physicians, nurses) and non-clinical frontline staff (receptionists, medical secretaries). This dimension quantifies the fluidity of inter-professional dialogue, the ease with which team members can solicit help without fear of ridicule, the regular occurrence of team briefings, and the perceived psychological safety required to raise critical safety concerns across hierarchical gradients.

3. Leadership (Items 11–16)

The Leadership subscale evaluates the commitment, visibility, responsiveness, and behavioral modeling of practice leaders (e.g., GP partners, executive practice managers, clinical directors) concerning patient safety. Effective leadership in patient safety entails transforming safety from an abstract policy into concrete behavioral realities. This construct gauges whether leaders actively encourage incident reporting, foster a non-punitive operational milieu, remain approachable when errors emerge, provide timely constructive feedback following adverse event investigations, and promptly allocate resources to remediate identified hazards.

4. Teamwork (Items 17–21)

The Teamwork dimension assesses social cohesion, mutual support, mutual respect, and collaborative efficacy within the practice team. Primary care relies heavily on distributed cognition, where patient care trajectories require the synchronized functioning of disparate occupational groups. This subscale measures whether staff feel valued within the collective structure, how effectively distinct professional cadres collaborate, whether colleagues actively support one another during acute operational surges or crises, and whether interpersonal conflicts and disagreements are resolved via constructive, functional mechanisms.

5. Safety Systems (Items 22–30)

The Safety Systems subscale evaluates the formal structural, procedural, and technological mechanisms embedded within the organization to detect, report, analyze, prevent, and learn from medical errors and near misses. Rather than assessing abstract safety values, this dimension scrutinizes tangible processes: the routine analysis of significant events, the presence of operational barriers that prevent error recurrence, accessibility of standardized clinical protocols, inclusion of patients as safety partners, transparency regarding near-miss disclosures, and overall confidence in the baseline safety of patient care delivery.

6. Theoretical Framework

SafeQuest is anchored in classical and contemporary organizational psychology, high-reliability theory, and socio-technical systems frameworks:

Zohar’s Safety Climate Paradigm

The foundational conceptualization of safety climate originates from the pioneering work of Dov Zohar (1980, 2010). Zohar postulated that organizations possess multiple operational goals (e.g., productivity, speed, cost efficiency, customer satisfaction, safety) that inherently compete for finite cognitive and material resources. Employees observe the objective behavioral cues, reward structures, leadership responses, and policy enactments around them to deduce the true priority order of these competing goals. The resulting shared sense-making constitutes the organization’s safety climate. SafeQuest translates Zohar’s paradigm into primary care by operationalizing the tension between throughput (workload, consultation velocity, patient volume) and systemic safety safeguards (thorough event analysis, incident reporting, protocol adherence).

James Reason’s System Safety and Just Culture Framework

SafeQuest draws heavily on James Reason’s Swiss Cheese Model of organizational accidents and his seminal distinctions between human error, active failures, and latent conditions. Reason argued that complex socio-technical systems cannot eliminate human fallibility; rather, resilient systems design defensive organizational barriers to intercept errors before they manifest as harm. Central to Reason’s theory is the requirement of an “informed culture,” which depends upon four interdependent cultural sub-elements:

• A Reporting Culture: An environment where people are prepared to report their errors, near misses, and safety observations without fear of punitive reprisal.
• A Just Culture: A collective atmosphere of trust where clear lines delineate acceptable human error from blameworthy reckless behavior.
• A Flexible Culture: The capacity of an organization to reorganize and adapt under high-tempo or high-stress operational conditions.
• A Learning Culture: The willingness and systemic capability to draw correct conclusions from safety management information systems and implement meaningful organizational reforms.

SafeQuest’s Safety Systems, Leadership, and Communication dimensions reflect these theoretical constructs by probing whether errors are treated as opportunities for systemic learning or met with silence and punitive blame.

Amy Edmondson’s Psychological Safety Theory

The interpersonal dimensions of SafeQuest—specifically within the Communication and Teamwork subscales—are informed by Amy Edmondson’s model of team psychological safety. Edmondson defines team psychological safety as a shared belief held by members of a team that the team is safe for interpersonal risk-taking. In primary care, power dynamics and professional hierarchies (e.g., senior physician partners versus junior administrative clerks) can create steep psychological barriers that inhibit individuals from speaking up when they notice an unfolding clinical error, medication discrepancy, or operational hazard. SafeQuest measures the extent to which these hierarchical gradients are flattened to ensure voice behavior and error disclosure.

7. Validity

The psychometric validity of the SafeQuest climate measure has been confirmed through rigorous empirical investigations involving diverse primary care cohorts, practice structures, and professional sub-groups.

Content and Face Validity

The initial development phase incorporated comprehensive literature reviews, theoretical mapping against established human factors frameworks, and iterative expert panel consensus reviews. Content validity was established via focus groups and qualitative cognitive debriefing sessions involving general practitioners, practice managers, practice nurses, administrative receptionists, and academic experts in primary care quality improvement. Items were refined to ensure ecological relevance to general practice, clear comprehension across both clinical and non-clinical roles, and unambiguous wording.

Construct and Factorial Validity

Construct validity was formally established by de Wet et al. (2010) through exploratory factor analysis (EFA) and subsequent confirmatory testing. Across validation studies in general practices across Scotland (spanning single-handed rural practices to large multi-partner urban health centers), the empirical data converged around the hypothesized five-factor structure (Workload, Communication, Leadership, Teamwork, Safety Systems). The five-factor model demonstrated superior fit compared to single-factor or competing structural models, confirming that safety climate in primary care is inherently multidimensional.

Convergent and Discriminant Validity

Convergent validity has been established by demonstrating moderate-to-strong correlations between SafeQuest dimension scores and external measures of organizational functioning, such as the Manchester Patient Safety Assessment Framework (MaPSAF), burnout inventories, and clinical governance audit ratings. Discriminant validity is evidenced by the scale’s capacity to detect statistically significant variations across distinct professional subgroups within the same practice. Research consistently demonstrates that general practitioners, practice nurses, and administrative receptionists perceive the safety climate differently. Administrative staff frequently report lower scores on communication and psychological safety, while clinical staff report significantly higher workload strain, reflecting known sociotechnical gradients within medical practices.

Known-Groups and Criterion-Related Validity

SafeQuest demonstrates strong known-groups validity, successfully differentiating between practices recognized for robust quality improvement infrastructures and those undergoing clinical governance remediation or experiencing high staff turnover. Longitudinal studies have further indicated that practices with higher baseline SafeQuest composite scores display greater engagement with formal Significant Event Analyses (SEAs), more comprehensive near-miss reporting rates, and enhanced compliance with national clinical safety guidelines.

8. Reliability

The SafeQuest climate measure exhibits high reliability across diverse clinical settings and organizational contexts. The instrument’s internal consistency, stability, and aggregation indices have been thoroughly documented in the peer-reviewed psychometric literature.

Internal Consistency

In the primary validation study by de Wet et al. (2010), involving 535 primary care staff members across 30 general practices, the total 30-item SafeQuest instrument demonstrated excellent overall internal consistency, with a global Cronbach’s alpha ($lpha$) exceeding .90. The individual subscales demonstrated strong reliability coefficients, well above the traditional psychometric benchmark of .70 for organizational diagnostic instruments:

• Workload: $\alpha = .77 – .82$
• Communication: $\alpha = .78 – .84$
• Leadership: $\alpha = .84 – .88$
• Teamwork: $\alpha = .80 – .85$
• Safety Systems: $\alpha = .82 – .88$

Subsequent independent validation studies evaluating SafeQuest within international healthcare systems (such as adaptation studies conducted in South Africa and Australia) have confirmed stable alpha coefficients, with subscale reliabilities consistently falling within the .74 to .89 range across disparate primary care environments.

Test-Retest Reliability and Stability

Test-retest reliability assessments conducted across stable primary care practices (over intervals of four to eight weeks in the absence of major organizational restructuring or crisis events) have demonstrated high intraclass correlation coefficients (ICCs), typically ranging from .75 to .86 across the five subscales. This indicates that while the tool remains sensitive to longitudinal changes resulting from safety interventions, it provides a stable and reliable measure of organizational climate under baseline operating conditions.

Aggregation Statistics and Within-Group Agreement

Because SafeQuest measures a shared group-level property (organizational safety climate) via individual-level responses, psychometric researchers routinely calculate within-group agreement and reliability indices to justify aggregating individual survey responses to the practice level. Studies employing SafeQuest demonstrate high within-group agreement ($r_{wg}$ values consistently exceeding the .70 threshold) and robust intraclass correlation coefficients (ICC[1] and ICC[2]), confirming that variance between different general practices is significantly greater than variance within practice teams, thereby empirically justifying practice-level aggregation.

9. Factor Analysis

The latent structural architecture of SafeQuest was determined through systematic factor analytic procedures conducted during its development and psychometric refinement phases.

Exploratory Factor Analysis (EFA)

During the initial development of the instrument, an exploratory factor analysis using principal axis factoring with oblique rotation (Promax and Oblimin) was conducted on the initial item pool. Oblique rotation was selected because theoretical dimensions of safety climate (such as leadership behavior, teamwork, and communication) were hypothesized to correlate naturally in real-world organizations. The EFA yielded a distinct, conceptually coherent five-factor solution corresponding to the five operationalized dimensions:

• Factor 1 (Safety Systems): Accounted for the largest proportion of total variance, with salient factor loadings ranging from .48 to .78 across items evaluating significant event audits, error recurrences, protocol availability, and systemic learning.
• Factor 2 (Leadership): Items assessing managerial approachability, proactive encouragement of incident reporting, and prompt resolution of safety concerns loaded cleanly on this factor (loadings from .52 to .83).
• Factor 3 (Teamwork): Captured shared mutual support, professional collaboration, value within the team, and constructive resolution of disagreements (loadings from .46 to .79).
• Factor 4 (Workload): Comprised items relating to staffing adequacy, overtime hours, operational pressure, and task complexity outstripping training (loadings from .50 to .81).
• Factor 5 (Communication): Included items regarding inter-professional clinical/non-clinical dialogue, accessibility of advice, and psychological safety in raising concerns (loadings from .44 to .76).

Confirmatory Factor Analysis (CFA)

Subsequent confirmatory factor analyses on independent validation cohorts confirmed the structural integrity of the 30-item five-factor model. The five-factor specification achieved acceptable to good goodness-of-fit indices:

• Comparative Fit Index (CFI): $ge .92$, indicating robust model fit relative to the null baseline model.
• Tucker-Lewis Index (TLI): $ge .91$, verifying satisfactory structural specification across multi-item constructs.
• Root Mean Square Error of Approximation (RMSEA): $le .055$ (with 90% confidence intervals bounded between .045 and .064), demonstrating low residual error.
• Standardized Root Mean Square Residual (SRMR): $le .058$, corroborating model parsimony.

Alternative models, including a unidimensional model (forcing all 30 items onto a single omnibus safety climate factor) and three-factor models, demonstrated significantly degraded fit indices, establishing that SafeQuest’s five-factor latent structure is both psychometrically optimal and theoretically justified.

10. Instrument / Measurement Tool

• Instrument Name: SafeQuest climate measure (commonly referred to as SafeQuest)
• Authors: Carl de Wet, Wendy Spence, Robert Mash, Peter Johnson, and Paul Bowie
• Construct Measured: Organizational safety climate in primary healthcare settings
• Target Population: Multidisciplinary primary care teams, including general practitioners, practice nurses, healthcare assistants, practice managers, medical receptionists, administrative personnel, and attached community healthcare staff
• Format & Length: 30 self-report items grouped into 5 subscales
• Subscale Breakdown:
  • Workload: Items 1 to 5 (5 items)
  • Communication: Items 6 to 10 (5 items)
  • Leadership: Items 11 to 16 (6 items)
  • Teamwork: Items 17 to 21 (5 items)
  • Safety Systems: Items 22 to 30 (9 items)
• Response Scale: 7-point Likert scale: 1 = Strongly Disagree, 2 = Disagree, 3 = Slightly Disagree, 4 = Neutral, 5 = Slightly Agree, 6 = Agree, 7 = Strongly Agree (with a ‘Not Applicable’ option)
• Administration Time: Approximately 10–15 minutes
• Administration Method: Electronic survey platform (hf.gpsafetyclimate.com) or standardized paper-and-pencil questionnaire
• Scoring and Scoring Rules:
  • SafeQuest comprises five safety climate dimensions: Workload (items 1–5), Communication (items 6–10), Leadership (items 11–16), Teamwork (items 17–21), and Safety Systems (items 22–30).
  • Reverse Scoring: Negatively worded items (e.g., items 2, 4, 5, 10, 22) are reverse-scored prior to calculating dimension and composite safety climate scores. On the 1–7 scale, reverse scoring follows the transformation: $Score_{reversed} = 8 – Score_{original}$ (i.e., $1 \rightarrow 7$, $2 \rightarrow 6$, $3 \rightarrow 5$, $4 \rightarrow 4$, $5 \rightarrow 3$, $6 \rightarrow 2$, $7 \rightarrow 1$).
  • Subscale Scores: Calculated by computing the arithmetic mean of all non-missing, reverse-adjusted items within each respective subscale. Scores range from 1.0 to 7.0, where higher scores represent a more positive, resilient, and proactive safety climate.
  • Composite Score: An overall safety climate score can be calculated as the unweighted mean across all 30 items (or the mean of the five subscale scores).
  • Missing Data / Not Applicable: “Not Applicable” responses are treated as missing data and excluded from subscale and composite mean calculations. Practice-level aggregation requires a minimum response rate (typically $ge 60%$) to ensure representative organizational validity.

11. Permissions & Fee and Test Year

The SafeQuest climate measure was developed and published in 2010 under the auspices of NHS Education for Scotland (NES) in collaboration with academic partners. The instrument was deliberately created as an open-access, public health resource to support clinical governance, educational improvement, and patient safety enhancement across primary medical services.

Primary care practices, researchers, and health boards have the option to register free of charge at the designated electronic platform (hf.gpsafetyclimate.com). This secure web portal permits general practice teams to distribute and complete the survey electronically among staff members. In addition, an automated, tailored safety climate report can be generated for participating practice teams, illustrating subscale score distributions, comparisons across clinical versus non-clinical staff categories, and benchmarking against regional or national norms.

For independent academic research, quality improvement projects, or non-commercial healthcare evaluations, SafeQuest is made available free of charge, subject to standard academic attribution of the original validation paper (de Wet et al., 2010). Commercial entities or organizations seeking commercial exploitation of the instrument or proprietary software integration should direct licensing inquiries to NHS Education for Scotland.

12. References

The following references provide the empirical, methodological, and theoretical basis for the SafeQuest climate measure and its application in primary care environments:

• Bowie, P., Ferguson, J., & de Wet, C. (2012). Safety climate in primary care: Understanding the perceptions of practice teams. British Journal of General Practice, 62(600), e472-e478. https://doi.org/10.3399/bjgp12X652328
• de Wet, C., Spence, W., Mash, R., Johnson, P., & Bowie, P. (2010). The development and psychometric evaluation of a safety climate measure for primary care. Quality & Safety in Health Care, 19(6), 578–584. https://doi.org/10.1136/qshc.2009.034529
• de Wet, C., Johnson, P., Mash, R., McConnachie, A., & Bowie, P. (2011). Measuring perceptions of safety climate in primary care: A cross-sectional study. Journal of Evaluation in Clinical Practice, 18(1), 135-142. https://doi.org/10.1111/j.1365-2753.2010.01548.x
• Edmondson, A. (1999). Psychological safety and learning behavior in work teams. Administrative Science Quarterly, 44(2), 350-383. https://doi.org/10.2307/2666999
• Reason, J. (1997). Managing the risks of organizational accidents. Ashgate Publishing.
• Reason, J. (2000). Human error: Models and management. BMJ, 320(7237), 768-770. https://doi.org/10.1136/bmj.320.7237.768
• Zohar, D. (1980). Safety climate in industrial organizations: Theoretical and applied implications. Journal of Applied Psychology, 65(1), 96-102. https://doi.org/10.1037/0021-9010.65.1.96
• Zohar, D. (2010). Thirty years of safety climate research: Reflections and future directions. Accident Analysis & Prevention, 42(5), 1517-1522. https://doi.org/10.1016/j.aap.2009.12.019

13. Items of the Scale