Integrated evidence-based medical policy for seafarers: a novel risk stratification framework for high-risk and circumpolar zones

Abstract

Maritime medical fitness is vital for safety in high-risk and medically isolated environments, yet current international policies remain inconsistent, opaque, and weakly evidence-based. This paper presents the Integrated EBM–Policy Framework (IEPF), a three-tier model integrating systematic clinical evidence appraisal, a maritime-specific risk stratification matrix, and adaptive regulatory feedback. Developed via a mixed-methods study of 112 maritime health professionals across nine jurisdictions, the IEPF increases clarity, defensibility, and international harmonization of fitness-to-embark decisions, especially for cardiovascular and mental health risks. It reduces unnecessary exclusions and strengthens applicability in circumpolar and remote operations, positioning IEPF as a scalable benchmark for global maritime health governance and high-risk occupational policy.

Introduction

As global trade and critical infrastructure increasingly rely on maritime transport, the health and operational readiness of seafarers have become central to international occupational safety and supply chain resilience [1]. Seafaring remains one of the most physically and psychologically demanding professions, particularly in remote and medically isolated regions such as the Arctic and other circumpolar zones [2]. Workers are routinely exposed to prolonged isolation, extreme environmental conditions, limited access to medical care, and cumulative physical and mental stressors. These challenges heighten the need for accurate, transparent, and defensible medical fitness assessments that protect both individual health and broader maritime operational integrity [3].

International regulatory instruments–such as the Maritime Labor Convention and guidelines from the International Maritime Organization (IMO) and International Labor Organization (ILO)—seek to safeguard seafarer health [4]. However, a persistent gap exists between these frameworks and the complex realities of medical risk in high–latitude and remote maritime contexts [5]. Many current regulations rely on static disqualifying conditions or broadly defined fitness criteria, with limited capacity to address dynamic, prognosis–based risks in environments where evacuation is delayed and on–site medical resources are minimal [6]. This has led to jurisdictional inconsistencies, legal ambiguity, and variable protection for maritime workers–especially those operating in medically underserved regions.

A central challenge is the lack of structured, evidence–based approaches to evaluating medical fitness in maritime deployment [7]. While Evidence–Based Medicine (EBM) is well established in clinical care, its systematic application within maritime regulatory practice–particularly in remote settings–remains limited [8]. This absence of a structured framework results in several major issues. First, current international policies often rely on static disqualifying conditions or broadly defined fitness criteria, lacking the capacity to address dynamic, prognosis–based risks in environments with minimal on–site medical resources and delayed evacuation. Second, this approach leads to a lack of standardization across jurisdictions, as physicians are left to rely on subjective, ad hoc specialist input without structured decision support tools [9]. Finally, the absence of systematic EBM integration into maritime health governance results in limited transparency, consistency, and adaptability in current regulatory models. These issues underscore the need for a new framework that institutionalizes EBM within maritime governance to enhance clarity, consistency, and defensibility.

This paper introduces the Integrated EBM–Policy Framework (IEPF), a novel three–tiered model that connects structured clinical evidence appraisal, maritime–specific risk stratification, and dynamic policy integration. The IEPF addresses existing gaps by operationalizing EBM into a flexible governance architecture, improving the clarity, consistency, and legal defensibility of medical fitness assessments. It is particularly applicable to high–risk conditions such as cardiovascular disease and mental health disorders–both of which are increasingly prevalent in seafaring populations and disproportionately challenging to manage in circumpolar and offshore environments [10].

The IEPF also contributes to broader debates in implementation science and health systems governance by demonstrating how clinical evidence can be institutionalized within occupational regulatory ecosystems. It supports global calls for adaptive, data–driven policymaking in sectors where medical decision–making occurs under conditions of uncertainty, isolation, and high operational risk [11].

The primary purpose of this study is to develop and validate this novel three–tiered model. This is achieved through three specific aims: (i) to design a layered framework that systematically combines structured clinical evidence appraisal, a maritime–specific risk stratification matrix, and a dynamic regulatory feedback mechanism; (ii) to evaluate the framework's operational effectiveness through a mixed–methods study involving expert input from maritime health professionals and validation via real–world case analyzes; and (iii) to assess the IEPF’s potential to reduce unnecessary exclusions and improve the clarity, consistency, and defensibility of fitness–to–embark decisions, especially for high–risk conditions in medically isolated and circumpolar zones.

The paper proceeds as follows: Section 2 reviews limitations in current maritime medical regulation; Section 3 details the IEPF’s development and methodology; Section 4 presents key findings; Section 5 discusses policy implications; and Section 6 concludes this study.

Literature review

The complexities of the maritime environment

Maritime occupations are characterized by exposure to complex and often extreme conditions, particularly in remote or circumpolar regions where operational, medical, and environmental challenges intersect [12]. Seafarers face prolonged isolation, limited onboard medical infrastructure, and exposure to variable climatic and geographic risks [13]. These conditions amplify both physical and psychological health vulnerabilities, placing increased strain on conventional medical evaluation protocols and raising the stakes for accurate, context–specific fitness assessments [14].

The risk landscape varies significantly across vessel types and deployment zones. Long–haul commercial voyages require high levels of medical self–sufficiency, while coastal operations introduce port–specific hazards such as infectious disease exposure and accident risk [15]. In polar or sub–Arctic settings, additional threats such as hypothermia, ice–related injuries, and evacuation delays compound the complexity of risk. These environmental constraints necessitate health governance models that integrate not only individual clinical risk but also operational feasibility and environmental exposure [16].

Importantly, maritime personnel extend beyond traditional seafarers to include researchers, fisheries observers, and technical workers aboard offshore or polar vessels [17]. These groups often operate under general occupational health standards that may not account for maritime–specific risks–creating a regulatory blind spot in health protection, especially in circumpolar zones [18]. The absence of tailored guidance for these roles raises concerns about equity, safety, and legal liability.

Crew size, voyage duration, and vessel function further influence health outcomes. Smaller crews on large vessels, for example, can increase workload and injury risk due to fewer redundancies [19]. Jurisdictional inconsistencies in applying international medical standards–such as the MLC–further exacerbate risks, leading to variable access to care, delays in medical evacuation, and uneven regulatory enforcement across regions [20].

Despite growing recognition of these operational health challenges, few frameworks systematically translate this complexity into medical risk assessment or policy. This gap underscores the need for structured, evidence–based models that reflect the realities of maritime and circumpolar deployment environments.

Professional aptitude and the limits of existing fitness frameworks

Medical evaluations that determine fitness for maritime deployment are foundational to occupational health governance, particularly in high–risk and medically isolated environments such as those in circumpolar regions [2]. Despite their critical role, current global fitness–to–embark frameworks–primarily grounded in conventions from the IMO and ILO–remain largely qualitative, relying on static lists of disqualifying conditions rather than prognosis–based thresholds or risk models tailored to remote operational contexts [18].

Fitness decisions at sea carry significant implications for individual livelihoods, vessel safety, and legal liability. Cardiovascular diseases, for example, are the leading cause of medical evacuation globally [21]. Yet, prognostic criteria for cardiovascular fitness remain inconsistently applied, often leaving physicians to rely on discretionary judgments or highly variable specialist input–an especially fraught process in remote regions with limited follow–up care [18].

Mental health presents similar challenges. The maritime environment exacerbates psychiatric vulnerabilities through isolation, disrupted circadian rhythms, and elevated stress [22]. However, regulatory guidance often lacks operationally relevant criteria for mental health evaluations, resulting in inconsistent or overly conservative exclusions that fail to reflect the realities of circumpolar or long–haul deployments [18].

These limitations are magnified for non–seafarer personnel such as researchers, technical staff, or fisheries observers, whose embarkation is governed by general occupational health standards. These individuals may be evaluated by physicians unfamiliar with maritime constraints, leading to either unsafe clearance or unnecessary exclusion–both of which can pose safety and legal risks [14].

Existing regulatory systems often struggle to balance the need for universal standards with the context–sensitive risks of maritime work. They lack operational tools that allow physicians to adjust risk evaluations based on factors such as voyage duration, degree of medical isolation, or vessel medical capabilities [23].

This section provides a comparative analysis of widely used fitness models to highlight their limitations when evaluated against the operational needs of modern seafaring. These frameworks, while foundational, are largely static, jurisdiction–specific, and not designed for evidence–based or adaptive application.

• The UK Maritime and Coastguard Agency’s (MCA) ENG1 system offers standardized forms and disqualifying conditions but lacks granularity in prognosis–sensitive cases, particularly for cardiovascular or psychiatric recovery [24].

• The US Coast Guard Medical Manual (COMDTINST M6000.1F) depends heavily on specialist letters, offering limited integration of risk scoring or voyage–specific considerations [25].

• The European Maritime Safety Agency (EMSA) provides implementation support for the MLC (2006) across EU states, yet practices remain fragmented, and there is minimal use of dynamic risk assessment tools [26].

• National frameworks, such as those in Norway and Canada, vary in their implementation of international standards and often rely on general occupational health principles that may not fully account for the unique risks of the maritime environment.

For instance, a post–myocardial infarction seafarer may be automatically deemed unfit under conventional protocols unless cleared by a specialist–without structured guidance on voyage–specific recovery criteria. In contrast, a structured model could assess recurrence probability, onboard monitoring capacity, and recovery timelines to support a more nuanced determination such as ‘Restricted Fit’ [27].

These limitations underscore the need for frameworks that translate clinical evidence into structured, defensible decisions. A modern system must allow for operational realism, reduce subjectivity, and promote regulatory consistency across remote and high–risk maritime settings [28].

The absence of evidence–based methodologies in maritime regulation

Despite the widespread adoption of EBM across clinical disciplines, its structured application within maritime occupational health–particularly in remote and high–risk environments–remains limited and inconsistent. Where EBM is applied, it typically informs clinical care rather than regulatory decision–making, leaving maritime fitness assessments reliant on generalist interpretation or ad hoc specialist opinions. This gap is especially problematic in cases involving new treatments, ambiguous prognoses, or multifactorial conditions, where operational stakes are high [29].

This reflects a broader failure in implementation science–the field concerned with translating clinical evidence into real–world systems. Practitioners often lack the training, tools, or institutional support to embed EBM into regulatory workflows [18]. As a result, guidelines intended to enhance safety often produce inconsistent decisions, undermining both accountability and legal defensibility.

Without structured frameworks, cross–jurisdictional variability in medical decisions persists, increasing the risk of litigation and unequal protection for workers operating in medically isolated or high–latitude regions [30]. Additionally, current systems lack outcome–tracking mechanisms that would allow past cases to inform future policy, hindering adaptive governance [31].

Although recent literature supports integrating structured risk stratification and evidence appraisal into maritime health [32], no comprehensive model currently exists that links clinical research, quantified risk, and regulatory feedback in a closed–loop system. Addressing this void is essential for creating consistent, transparent, and context–sensitive maritime medical governance.

While existing literature highlights the complexities of the maritime environment, the limitations of current fitness frameworks, and the inconsistency of evidence–based methodologies in practice, a significant knowledge void remains. A comprehensive model that effectively bridges these three areas does not currently exist. Specifically, the literature reveals three critical gaps: (1) the absence of a structured framework that systematically integrates EBM into maritime policy, leaving assessments to static criteria and subjective interpretation; (2) the lack of contextual risk stratification models tailored to the unique demands of remote, high–risk, and medically isolated maritime conditions; and (3) the need for adaptive, feedback–driven regulatory systems that can evolve in response to new clinical evidence and real–world outcomes. The IEPF is proposed as a novel solution designed to fill these specific gaps, offering a replicable model for consistent, transparent, and defensible health governance in high–stakes occupational settings.

EBM risk assessment methodology

Research design and sampling considerations

To validate the IEPF, a mixed–methods study design was adopted, combining qualitative policy analysis with quantitative data collection. The study engaged 112 occupational physicians and maritime health professionals across nine jurisdictions (Norway, UK, Germany, Australia, Singapore, South Korea, the Philippines, Canada, and the Netherlands). Participants were selected through stratified purposive sampling–a method widely accepted in exploratory research where access to domain–specific expertise is essential. Stratification criteria included geographic representation, professional role (e.g. clinician, regulator, consultant), and years of experience, with the goal of maximizing diversity in perspectives across regulatory environments.

Purposive sampling was chosen over probabilistic methods due to practical limitations in accessing a globally representative population of maritime health professionals, particularly across jurisdictions with varied regulatory structures and data access barriers. Moreover, the primary aim of the study was to assess the perceived applicability, usability, and effectiveness of the IEPF among experienced stakeholders, rather than to generalize findings to the broader maritime health community. In this context, expert input was prioritized to inform the framework's refinement in its early implementation phase.

While purposive sampling enables deep insight from relevant practitioners, it inherently limits the statistical generalizability of the findings. The authors acknowledge that the results reflect expert perspectives and operational conditions within the sampled regions and may not fully represent global maritime health practice. This limitation is particularly relevant when interpreting the quantitative outcomes (e.g. reported consistency, confidence scores, or disqualification rates), which should be viewed as indicative rather than conclusive.

To mitigate potential selection bias, the sampling frame deliberately included participants from both developed and developing maritime nations, public and private sectors, and varied levels of regulatory maturity. Nonetheless, the absence of random sampling introduces a degree of respondent bias that could influence the perceived effectiveness of the IEPF. For instance, those more interested in evidence–based policy may have been more likely to participate, skewing results favorably.

Data collection and analysis

Data were collected over a six–month period using structured online surveys (via Google Forms and LimeSurvey) and semi–structured interviews conducted via Zoom. The survey instruments were initially pilot–tested with five maritime physicians to establish face validity and further reviewed by an expert panel comprising two EBM scholars and three maritime health specialists to ensure content validity. The final survey consisted of 38 items, including 24 closed–ended questions on Likert scales (1–10) and 14 open–ended questions (see Supplementary Table S2 for survey domains and sample questions). Key domains included practitioner confidence in fitness determinations, frequency of EBM use, access to clinical evidence resources, perceived consistency across jurisdictions, and familiarity with international regulatory guidelines.

A total of 112 valid responses were received, with geographic representation from Norway (14%), UK (13%), Germany (12%), Australia (11%), Singapore (10%), South Korea (10%), the Philippines (12%), Canada (9%), and the Netherlands (9%). Participants included occupational physicians (64%), regulatory officials (21%), and maritime health consultants (15%), with an average of 13.8 years (SD = 6.4) of maritime medical experience (see Supplementary Table S3 for detailed demographics).

Quantitative data were analyzed using SPSS v28. Descriptive statistics revealed moderate overall confidence in current fitness assessments (M = 6.1, SD = 1.9), which increased significantly when practitioners used the IEPF–based framework (M = 8.7, SD = 1.3). A one–way ANOVA comparing confidence across regions produced F(8,103) = 4.87, p < 0.001. Post–hoc Tukey tests showed significant differences between EU and Asia–Pacific practitioners (p = 0.003, 95% CI [0.9, 3.2]). Chi–square analysis found that 87% of participants rated the IEPF as ‘consistently applicable across cases (see Supplementary Table S4 for detailed response distribution),’ compared to 61% for traditional models (χ² = 14.6, df = 1, p < 0.001). The reported rate of avoidable disqualifications dropped from 14.3% (n = 16) under traditional models to 4.7% (n = 5) with the IEPF, which participants attributed to improved risk stratification and clearer thresholds.

Qualitative data from 28 semi–structured interviews were analyzed using thematic analysis in NVivo, yielding a Cohen’s Kappa coefficient of 0.82, indicating strong inter–rater agreement (see Supplementary Table S5 for coding framework and raw quotes). Dominant themes included: (1) increased clarity in borderline cases (e.g. post–PCI recovery), (2) reduced reliance on non–standardized specialist opinions, and (3) enhanced defensibility of fitness decisions during regulatory audits or legal disputes (see Supplementary Table S6 for thematic codes and representative quotes).

The integrated EBM–policy framework (IEPF)

Layer 1: evidence generation and appraisal

Layer 1 of the IEPF addresses a longstanding gap in maritime occupational health by transforming conventional EBM principles into a structured, policy–oriented evidence generation model. Unlike traditional clinical EBM, which centers on individual patient care, this layer operationalizes evidence appraisal for use within regulatory environments–specifically tailored to high–risk, medically isolated occupational contexts such as seafaring. This theoretical shift positions clinical literature not merely as a decision aid, but as a regulatory instrument that underpins enforceable fitness–to–work determinations.

To implement this layer, the study followed a structured process beginning with the formulation of precise clinical questions focused on high–risk maritime conditions–namely cardiovascular diseases and mental health disorders.

To enhance transparency, we note that this literature component was a targeted evidence scan undertaken to parameterize the IEPF, rather than a standalone systematic review or meta–analysis. The objective was to identify and appraise decision–relevant evidence, not to generate exhaustive pooled estimates. The following methodological details summarize our approach: (i) Search strategy: database queries (PubMed, Cochrane, Scopus) used maritime–relevant Boolean operators and MeSH terms. (ii) Inclusion and exclusion criteria: we included human studies of adult seafarers or comparable remote/isolated occupational groups, focused on high–risk conditions relevant to maritime deployment (e.g. cardiovascular disease, seizure disorders, mood disorders, diabetes, hypertension). Eligible designs were systematic reviews, randomized controlled trials, and prospective cohort studies; we excluded non–human studies, case reports, and non–English publications prior to 2008. (iii) Appraised evidence: each retained study was evaluated using the GRADE framework. (iv) Synthesis: findings were integrated narratively to inform prognosis thresholds and monitoring requirements in maritime contexts; no quantitative meta–analysis was performed (A summary of the included studies, their GRADE appraisal, and synthesis of results is provided in Supplementary Table S1).

This approach ensures that evidence is not interpreted in clinical abstraction but is instead filtered for applicability in regulatory contexts with limited access to emergency care, prolonged isolation, and strict role–based physical and psychological demands.

By embedding this process within a structured framework, Layer 1 extends EBM beyond its traditional clinical boundary, introducing an explicit governance function to evidence appraisal.

Layer 2: risk translation via the maritime risk stratification matrix (MRSM)

Layer 2 of the IEPF introduces the Maritime Risk Stratification Matrix (MRSM), a novel analytical mechanism that bridges clinical evidence with operational maritime decision–making. Unlike standard risk matrices used in general occupational health, the MRSM is designed specifically to translate appraised medical evidence into structured, context–sensitive risk categories that inform regulatory determinations. This layer redefines risk translation as not merely clinical judgment, but as a replicable, semi–quantitative modeling process tailored to the logistical, medical, and environmental complexities of maritime deployment.

The MRSM assesses both the likelihood and severity of adverse medical outcomes and classifies seafarers as ʻfit,’ ʻrestricted fit,’ or ʻunfit’ using maritime–specific criteria. These include voyage duration, level of medical isolation, onboard treatment capacity, and emergency response feasibility–factors not typically incorporated into traditional fitness assessments. The matrix employs a weighted risk scoring algorithm built around four evidence–derived dimensions: (1) time since last clinical event, (2) likelihood of recurrence, (3) treatment complexity, and (4) onboard medical readiness. Each dimension is scored on a standardized 5-point scale, and the aggregated results determine the final risk classification.

Validation of the MRSM was achieved by comparing its predictive classifications to anonymized medical evacuation data from participating jurisdictions. The anonymized medical evacuation data used for validation consisted of aggregated case records from national maritime health authorities and participating clinics. These records included de–identified information on the medical condition leading to evacuation, patient demographics, voyage type, and evacuation outcome. No personal identifiers were retained, and the data were standardized across jurisdictions to allow consistent comparison with MRSM classifications. This ensured that validation was based on real–world operational outcomes while fully maintaining confidentiality.

A chi–square test demonstrated statistically significant alignment (χ² = 23.7, df = 4, p < 0.01) between MRSM–derived classifications and real–world outcomes. While promising, further validation through psychometric analysis and longitudinal benchmarking remains a priority for future research.

Layer 3: regulatory integration and feedback loop

Layer 3 of the IEPF advances maritime health governance by embedding clinical risk assessment into a dynamic, policy–responsive regulatory cycle. By a dynamic, policy–responsive regulatory cycle, we refer to a process in which medical fitness decisions are not fixed in static guidelines but are continually refined based on new clinical evidence and operational outcomes. This means that aggregated case data, trends in medical evacuation, and practitioner feedback are fed back into the regulatory system, allowing authorities to adapt criteria, thresholds, and protocols in real time. Unlike traditional systems that isolate medical decision–making from policy refinement, this layer introduces a feedback mechanism that enables maritime regulations to evolve in real time based on frontline data and emerging clinical evidence. Central to this process is a digital health database prototype developed and piloted during the study ʻThe digital health database prototype is a cloud–based platform designed to capture structured medical fitness evaluations, MRSM scores, voyage characteristics, and follow–up outcomes. It allows practitioners to input case data securely, and regulators to analyze anonymized aggregate patterns across multiple jurisdictions. Key features include role–based access, encrypted data storage, and automated analytics that generate trend reports and inter–rater consistency metrics.’, which supports structured input of fitness evaluations, anonymized tracking of medical outcomes, and analytical tools for identifying regulatory trends. This prototype–built on a modular, cloud–based architecture–includes role–based access, encrypted data transmission, and anonymized storage compliant with international data protection standards. Users input MRSM scores, diagnostic information, and voyage–specific variables, and the system aggregates these to support regulatory decision–making and longitudinal outcome monitoring.

Piloted among 18 physicians across five jurisdictions, the prototype enabled automated visualizations of fitness classification trends and inter–rater agreement. To evaluate the practicality of the database, we employed the System Usability Score (SUS), a widely used and validated questionnaire–based metric that provides a global view of user satisfaction with digital systems. The SUS yields a score between 0 and 100, where higher values indicate stronger usability and acceptance. This measure is commonly applied in health informatics and human–computer interaction research to benchmark system design and functionality. Early user feedback highlighted the system’s operational feasibility, with SUS of 82.5 and a 94% task completion rate during structured case testing.

Load testing confirmed stable performance for up to 500 concurrent records, and participants reported improved confidence in defensible fitness determinations when referencing historical case patterns. However, the system remains in its proof–of–concept stage. It has not yet been deployed at scale, lacks integration with national maritime health registries, and awaits independent cybersecurity auditing and a privacy impact assessment. Despite these limitations, it demonstrates strong potential as a scalable tool for policy adaptation.

This layer closes the loop between evidence generation (Layer 1), risk translation (Layer 2), and governance enforcement, transforming policy from a static rulebook into a living framework. It reframes fitness–to–work decisions as iterative, evidence–driven processes and introduces adaptive regulation into maritime health–a field traditionally constrained by static guidelines.

Analysis

Case study analysis

To evaluate the real–world applicability, operational robustness, and regulatory relevance of the IEPF, ten anonymized medical fitness–to–embark cases were analyzed across a range of maritime roles and jurisdictions. These cases, selected for their clinical ambiguity and policy sensitivity, represent common yet high–impact medical conditions encountered in seafaring contexts. Each was evaluated using the IEPF's three–tiered methodology: evidence appraisal (Layer 1)¹, operational risk stratification via the MRSM (Layer 2), and regulatory adaptation through policy feedback (Layer 3).

Among the most illustrative cases is that of a 47-year–old offshore engineer from Norway recovering from a recent myocardial infarction treated with percutaneous coronary intervention (PCI). Despite a cardiologist’s general clearance, uncertainty persisted regarding recurrence risk and the implications of long–term antiplatelet therapy. A targeted literature search conducted under Layer 1 indicated that the highest risk of restenosis occurs within the first 6–12 months post–intervention, declining thereafter to <5% annually, supported by high–grade evidence [33,34]. The MRSM score yielded a ‘Restricted Fit’ classification, contingent upon completion of a stable 12-month recovery, onboard monitoring capabilities, and reduced exposure to injury during antiplatelet therapy. This classification informed updated internal protocols governing post–cardiac cases in offshore environments.

A second case involved a 39-year–old Australian fisheries observer with a history of major depressive disorder, stable under pharmacological treatment. Conventional maritime medical guidance lacked specific prognostic criteria for such conditions, leading to variable and often overly cautious outcomes. Using the IEPF, clinicians reviewed moderate–quality evidence suggesting that stable depressive conditions can be safely managed in isolated environments with appropriate monitoring and telehealth access. The MRSM designated the case as ʻFit with Monitoring,’ triggering the development of structured protocols that included mandatory pre–departure psychiatric evaluation, scheduled teleconsultations, and onboard mental health monitoring protocols.

Other cases further demonstrate the framework’s adaptability across a spectrum of conditions. For example, a cargo officer with uncontrolled type 2 diabetes was designated ʻUnfit’ due to the high risk of acute complications in remote environments. Conversely, a bipolar II disorder case–well–managed under supervision–was cleared as ʻRestricted Fit’ with voyage duration limitations. A tugboat engineer with severe hypertension was permitted to embark under strict monitoring conditions, while a visually impaired dredging crew member with monocular vision was found unfit due to safety–critical visual requirements.

Obesity–related risks were addressed in the case of an offshore catering officer with a BMI of 39, classified as ʻFit with Monitoring’ and prompting the development of weight–related role restrictions. Similarly, a ferry first mate with a seizure–free history of epilepsy was granted full clearance based on seizure–free duration thresholds, and a marine biologist on anticoagulants was deemed ʻRestricted Fit’ due to bleeding risks. Lastly, an electrician with generalized anxiety disorder was cleared under supportive conditions including digital mental health interventions.

These ten cases, summarized in the table below, showcase how IEPF facilitates granular, evidence–informed decisions while advancing adaptive maritime health governance (Table 1).

Table 1.

Summary of case study evaluations using the IEPF framework.

Case	Maritime role	Condition	Evidence base (GRADE)	MRSM score	Fit classification	Key risk factors	Policy/protocol outcome
1	Offshore Engineer (Norway)	Post–PCI (MI)	High	7.2	Restricted fit	Restenosis, bleeding risk	Introduced post–PCI recovery and monitoring protocols
2	Fisheries Observer (Australia)	Major depressive disorder	Moderate	5.9	Fit with monitoring	Isolation, relapse risk	Mandatory psych evaluation and telehealth support
3	Cargo Officer (Singapore)	Type 2 diabetes (uncontrolled)	High	8.1	Unfit	Hypoglycemia, medical inaccessibility	Updated exclusion criteria based on HbA1c
4	Research Navigator (UK)	Bipolar II disorder (Stable)	Moderate	6.0	Restricted fit	Mood instability risk	30-day voyage limit; quarterly psychiatric review
5	Tugboat Engineer (Germany)	Hypertension (SBP > 160)	High	6.5	Restricted fit	Stroke, medication non–compliance	Onboard BP logging; conditional clearance
6	Dredging Crew (Philippines)	Monocular vision	Moderate	7.9	Unfit	Depth perception, navigation risk	Revised visual acuity standards
7	Catering Officer (Netherlands)	Obesity (BMI = 39)	Moderate	6.2	Fit with monitoring	Cardiometabolic risk, mobility	Role restrictions and health monitoring
8	Ferry First Mate (South Korea)	Seizure Disorder (2 + yrs seizure–free)	High	5.4	Fit	Seizure recurrence	Clearance after 2 years seizure–free
9	Marine Biologist (Canada)	Anticoagulant use (DVT)	High	6.7	Restricted fit	Bleeding risk, trauma	Safety measures for anticoagulant users onboard
10	Junior Electrician (Australia)	Generalized anxiety disorder	Moderate	4.8	Fit with monitoring	Stress–induced episodes	CBT access, periodic reassessments

To contextualize these outcomes, we compared the IEPF–derived decisions with how similar cases would likely be assessed under three leading regulatory systems:

• The UK Maritime and Coastguard Agency (MCA) ENG1 Medical Guidelines

• The US Coast Guard Medical Manual (COMDTINST M6000.1F)

• The European Maritime Safety Agency (EMSA) Certification Guidelines

This comparative assessment is summarized below (Table 2).

Table 2.

Compares the IEPF–derived decisions with how similar cases would likely be assessed under three regulatory systems.

Case	Likely outcome under existing frameworks	IEPF classification	Observed difference
1 (Post–PCI MI)	Likely temporary unfit pending non–specific specialist opinion (MCA, USCG)	Restricted fit	More nuanced, time–and capability–sensitive clearance
2 (Depression)	Frequently unfit or restricted due to lack of psychiatric criteria (EMSA, USCG)	Fit with monitoring	Conditional inclusion instead of exclusion
3 (Uncontrolled diabetes)	Typically unfit (consistent across all systems)	Unfit	No difference
4 (Stable bipolar II)	Often unfit or subject to broad restrictions (USCG, MCA)	Restricted fit	Voyage–limited inclusion supported by prognosis data
5 (Severe hypertension)	Clearance may depend on specialist letter; no structured tool	Restricted fit	MRSM–supported decision with conditional onboard protocols
6 (Monocular vision)	Unfit (consistent across all)	Unfit	No difference
7 (Obesity)	Case–by–case; inconsistent outcomes (EMSA)	Fit with monitoring	Role–specific monitoring introduced
8 (Seizure disorder)	Clearance after 2–5 years seizure–free (aligned with USCG/MCA)	Fit	Alignment with stricter frameworks
9 (Anticoagulant use)	Often unfit without clear policy exception (MCA, EMSA)	Restricted fit	Conditional clearance with enhanced safety measures
10 (Anxiety disorder)	High variability; often deemed unfit without evidence base	Fit with monitoring	Mental health protocols introduced for safe inclusion

Of the ten IEPF–evaluated cases, five would likely have resulted in overly cautious exclusion or inconsistent outcomes under conventional frameworks. By introducing structured evidence appraisal, maritime–specific risk scoring, and policy feedback loops, the IEPF offers a significant improvement in decision quality and adaptability.

A comprehensive analysis: epidemiological evidence and the case for regulatory adaptation in maritime medical governance

An integrated analysis of recent maritime health datasets reveals both the strengths and critical vulnerabilities in current seafarer medical fitness evaluation systems, particularly in the context of a rapidly evolving risk landscape. Drawing upon data from EMSA’s Seafarers Statistics in the EU—2022 [35], and MCA’s ENG1 Annual Medical Report and Summary 2023 [36], this section offers a synthesis of workforce demographics and health outcomes that directly inform the development and operational relevance of the IEPF. These findings underscore the imperative for dynamic, evidence–based regulatory models capable of addressing emerging health challenges with precision, consistency, and global applicability.

The EMSA dataset highlights a stable yet aging maritime workforce within the European Union. As of 2022, over 171,000 masters and officers held valid Certificates of Competency (CoCs), with an additional 117,000 endorsements issued for non–EU seafarers (see Figure 1). While this suggests strong institutional continuity and capacity within the sector, a closer examination of age distribution reveals a significant concentration of certified officers aged 45 and above–indicating a workforce that is increasingly susceptible to age–related chronic conditions such as cardiovascular disease, type 2 diabetes, and sensory impairments. These conditions directly impact the risk profile of deployed personnel, raising urgent questions about the adequacy of current fitness–to–work models that rely heavily on static exclusion criteria or clinician discretion.

Figure 1.

Age distribution of masters and officers holding valid CoCs based on [35].

As the proportion of older seafarers increases, regulatory mechanisms must evolve accordingly [37]. Within the IEPF, this demographic trend activates Layer 2—the MRSM–to ensure that age–associated risks are quantitatively incorporated into risk scores. For example, the probability of adverse cardiac events or medication–related complications increases with age, particularly in high–isolation deployments, necessitating structured tools that move beyond binary fit/unfit classifications and toward nuanced categories such as ʻRestricted Fit’ or ʻFit with Monitoring’ [38].

Further illuminating the complexity of medical fitness governance is the MCA's 2023 ENG1 dataset, which comprises 52,770 medical assessments. Of these, approximately 91% resulted in unrestricted certification, while 9% were either restricted, temporarily unfit, or permanently unfit. Table 3 summarizes the distribution of these decisions across fitness categories:

Table 3.

Summary of approved doctors’ decisions based on [36].

Fitness category	Number of assessments	Percentage
Fully fit (unrestricted)	47,020	89.1%
Temporarily unfit	2,370	4.5%
Permanently unfit	1,110	2.1%
Fit with restrictions	2,270	4.3%
Total	52,770	100%

This breakdown reveals that while the majority of seafarers pass fitness evaluations, a non–negligible minority face restrictions or disqualification–outcomes with direct implications for employment, legal liability, and vessel safety. Critically, the ENG1 report identifies endocrine disorders, notably obesity and diabetes, as now surpassing cardiovascular disease as the leading cause of fitness restrictions. This marks a paradigm shift in seafarer health risk and signals a policy lag in current regulatory guidance, which remains more closely aligned with legacy concerns around cardiac function and sensory impairments.

Mental health concerns also represent a growing area of regulatory stress. A notable rise in mood disorders–primarily depressive and anxiety–related conditions–was observed in the 2023 dataset, often resulting in temporary disqualification or conditional clearance. Yet, existing maritime regulations continue to lack detailed prognosis–based criteria for these conditions, leading to variability in decision–making and, at times, overly cautious or inconsistently applied exclusions. The IEPF responds to this gap through its evidence appraisal mechanism (Layer 1), which synthesizes current psychiatric literature to produce tailored, prognosis–sensitive guidelines. This is further operationalized through MRSM scores that incorporate psychological stability, relapse history, and availability of remote mental health interventions such as telemedicine and cognitive–behavioral therapy (CBT).

In addition to chronic disease prevalence, sensory impairments continue to play a central role in disqualifications. The MCA data reports extremely low pass rates (only 2%) in supplementary Color Assessment and Diagnosis (CAD) testing, reflecting the operational hazards posed by color vision deficiencies, particularly in navigation and emergency response. Under conventional binary frameworks, this leads to automatic exclusion. However, the IEPF introduces the capacity to apply context–specific thresholds based on actual role demands, redundancy protocols, and technological mitigations–allowing for more equitable and operationally sound decisions.

The combined implications of these findings are manifold. First, they expose a fundamental mismatch between evolving epidemiological realities and existing regulatory instruments. While traditional models rely on disqualifying conditions and subjective interpretations, the IEPF establishes an adaptive architecture that allows medical risk assessments to evolve in tandem with population health trends. Second, these data support the need for Layer 3 of the IEPF–the policy feedback mechanism–through which regulators can continuously refine fitness criteria based on aggregate outcomes, case learnings, and frontline practitioner input. For example, a sustained increase in diabetes–related disqualifications could trigger the development of a new evidence–based protocol for glycemic control thresholds and onboard monitoring requirements.

Results and discussion

Discussion

The implementation of the IEPF marks a substantial shift in the landscape of maritime occupational health governance, introducing a structured, evidence–driven alternative to historically discretionary and inconsistent medical fitness evaluations. The empirical results from this study demonstrate that embedding evidence–based methodologies into maritime policy leads to significant improvements in both clinical precision and regulatory coherence. Notably, inter–rater consistency among physicians increased from 61% to 87% (p < 0.001), and the rate of avoidable disqualifications dropped by over two–thirds (from 14.3% to 4.7%, p = 0.002) (see Supplementary Table S7 for full statistical summary)². These outcomes reflect not only statistical improvements, but also a fundamental recalibration of how medical risk is conceptualized and managed within the high–stakes, medically isolated maritime environment.

On a theoretical level, the IEPF represents a significant contribution to the literature on evidence–based regulation, occupational health frameworks, and adaptive governance. It moves beyond existing fragmented applications of EBM by embedding clinical reasoning directly into fitness–to–embark decisions and maritime governance, thus offering a new model for evidence–regulation translation applicable across other high–risk occupations. The framework's ability to operationalize EBM within a regulatory structure that is both adaptive and domain–specific fills a critical gap in implementation science–the field concerned with translating clinical evidence into real–world systems.

The IEPF’s influence on day–to–day maritime health governance is profound. MRSM, in particular, empowers practitioners to make more granular and defensible decisions. For example, a clinician is no longer limited to a simple ʻfit’ or ʻunfit’ determination for a seafarer with a complex condition like well–managed diabetes. This approach enhances operational realism, allowing qualified seafarers to remain employed under safe conditions, reducing unnecessary exclusions and protecting their livelihoods. The framework also provides a clear, documented audit trail, which is crucial for legal defensibility and regulatory oversight, particularly in cases involving medical evacuations or incidents at sea.

Traditional maritime health assessments, grounded in static exclusion criteria and subjective judgment, have struggled to keep pace with the growing complexity of seafarer health profiles and operational risk environments [39]. In contrast, the IEPF introduces a layered architecture that operationalizes clinical evidence into defensible regulatory outcomes. Its middle tier–the MRSM–functions as a semi–quantitative tool that translates prognosis data into role–specific classifications (e.g. ʻFit with Monitoring,’ ʻRestricted Fit’), thereby eliminating the false dichotomy of binary clearance models. This nuance is particularly impactful in cases involving cardiovascular recovery, psychiatric stabilization, or chronic disease management, where one–size–fits–all exclusions often fail to reflect true fitness or risk.

The benefits of this structured approach are illustrated through real–world case studies analyzed in the study. For instance, a fisheries observer with stabilized major depressive disorder was appropriately classified as fit for duty under defined monitoring protocols, a decision that would likely have resulted in unwarranted exclusion under traditional guidelines due to insufficient regulatory clarity. Likewise, post–PCI cardiac patients were assessed with greater accuracy by integrating time–bound recurrence data, onboard medical capabilities, and pharmacological risk–all factors that conventional assessments neglect. These outcomes demonstrate the IEPF’s capacity to align medical realism with operational safety, enhancing both personnel inclusion and hazard mitigation.

However, despite these promising results, the findings must be interpreted with caution due to several key limitations. First, the study’s reliance on purposive sampling of expert participants introduces selection bias, as individuals already supportive of evidence–based approaches may have been more likely to participate. While the data offer rich insight into cross–jurisdictional practice, they may not fully represent the views or conditions of the global maritime medical community. This limitation constrains the generalizability of outcomes and highlights the need for broader, randomized, and representative studies. In addition, the literature appraisal conducted for this study was a targeted evidence scan rather than a full systematic review. This approach may limit comprehensiveness, yet it was deliberately chosen because the objective was framework development and parameterization of the IEPF, rather than exhaustive evidence synthesis or meta–analysis.

Future research should therefore expand the sample size using probabilistic or respondent–driven sampling methods to improve external validity. Large–scale, multi–year studies involving randomized participants and additional stakeholder groups–including shipowners, crewmembers, and regulators–would strengthen the empirical foundation for broader adoption. In addition, longitudinal studies tracking health and operational outcomes following IEPF implementation could provide stronger evidence of its effectiveness across diverse operational settings.

Second, while the IEPF demonstrates operational promise, its implementation requires significant infrastructural, institutional, and cultural shifts that may not be feasible in all jurisdictions. In particular, Layer 3—the feedback mechanism built on a digital health database–faces real–world obstacles such as data privacy concerns, cybersecurity risks, and cross–border legal discrepancies. Many lower–resourced maritime nations may lack the IT infrastructure or trained personnel needed to deploy such a system at scale, potentially limiting equitable adoption.

Third, although the IEPF enhances consistency and transparency, it may risk introducing excessive rigidity if applied too mechanistically. Medical assessments often require case–by–case clinical judgment, and an overreliance on structured matrices could inadvertently marginalize nuanced individual considerations [40]. There is also a danger that reliance on algorithmic scoring may foster misplaced confidence in borderline cases, especially where evidence quality is moderate or evolving [41].

Finally, stakeholder resistance–particularly among practitioners accustomed to flexible, discretionary models–may present a barrier to adoption. Training, cultural change, and policy alignment efforts will be essential to avoid fragmentation or tokenistic implementation.

Despite these limitations, the policy implications remain compelling. The IEPF's findings extend beyond practical application to contribute to broader theoretical discussions on adaptive health governance and implementation science. By embedding a feedback loop in Layer 3, the framework transforms maritime policy from a static rulebook into a dynamic, learning–oriented system. This model demonstrates how clinical evidence can be institutionalized to drive continuous policy refinement, a concept that is highly relevant to other high–risk, isolated occupational sectors, such as polar research or offshore energy. It challenges traditional top–down regulatory models by integrating frontline practitioner data into policy–making, fostering a more responsive and scientifically grounded regulatory environment. The IEPF thus provides a blueprint for how to bridge the gap between abstract clinical research and enforceable, context–sensitive regulatory policy.

To fully validate and institutionalize the IEPF, a clear future research agenda is essential. Future studies should aim for large–scale empirical validation using probabilistic or respondent–driven sampling methods to improve external validity and statistical generalizability of the framework's findings. It would also be highly beneficial to incorporate additional stakeholder groups, such as shipowners, crewmembers, and regulators, to gain a more comprehensive understanding of the framework’s impact across the maritime ecosystem. Furthermore, a long–term, multi–year study tracking health and operational outcomes following IEPF implementation could provide stronger evidence of its effectiveness in reducing medical incidents and improving overall seafarer safety across diverse operational settings. Such longitudinal research would enable the continuous recalibration of policy thresholds in response to new evidence, ensuring the sustainability and scientific integrity of the model.

From a doctrinal standpoint, the IEPF provides a structured response to the long–standing ambiguity that characterizes maritime health governance under international law. The Maritime Labor Convention, 2006, often described as the ʻseafarers' bill of rights,’ requires states to ensure that all seafarers possess valid medical certificates as a condition of employment. Yet the MLC is drafted in broad terms, leaving the content of ʻfitness’ largely to national interpretation [24,26]. This results in divergent outcomes that threaten both equal treatment of seafarers and the principle of legal certainty. Similarly, the International Convention on Standards of Training, Certification and Watchkeeping for Seafarers (STCW, 1978, as amended) and the International Convention for the Safety of Life at Sea (SOLAS, 1974, as amended) impose obligations relating to the competence and safety of crews, but their health provisions remain ancillary, addressing medical carriage requirements and training rather than uniform medical standards. The United Nations Convention on the Law of the Sea (UNCLOS, 1982) indirectly reinforces these obligations by imposing flag–state duties to ensure safety at sea, yet it too lacks detailed guidance on medical risk governance. The International Health Regulations (IHR, 2005), binding on all WHO member states, add another dimension by requiring states to prevent cross–border health risks, including those transmitted by maritime workers. Collectively, these instruments illustrate a doctrinal patchwork: they establish duties of care without prescribing a systematic evidentiary framework for implementing them.

Comparative practice underscores these limitations. The UK’s ENG1 regime under the MLC framework emphasizes uniformity but is grounded in exclusion lists and clinical discretion [24]. The US Coast Guard’s COMDTINST M6000.1F incorporates specialist reports but lacks structured risk stratification [25]. EMSA guidelines promote consistency within the EU but remain fragmented in application due to subsidiarity and the absence of binding secondary legislation [26]. Nordic jurisdictions, such as Norway, integrate prognosis–sensitive tools but stop short of codifying them into law, leaving outcomes vulnerable to inconsistency [27]. This comparative picture reveals a systemic gap: while all regimes aspire to balance individual rights with vessel safety, none provide a doctrinally anchored mechanism that operationalizes EBM within enforceable legal standards.

The IEPF directly addresses this lacuna by transforming medical evidence into a governance instrument that can be harmonized with existing treaty obligations. Its three–tiered architecture enhances the MLC’s requirement of medical certification by providing objective, transparent, and prognosis–sensitive benchmarks for determining fitness. It supplements STCW’s focus on crew competence by ensuring that medical assessments reflect operational realities such as voyage duration and medical isolation. By integrating a feedback loop, it advances SOLAS’s goal of continuous safety improvement through adaptive regulatory learning. It also reinforces UNCLOS duties of the flag state by supplying an evidentiary basis for compliance with ʻdue diligence’ in ensuring safe manning. Finally, by incorporating public–health monitoring and data feedback, the framework aligns with IHR obligations for states to maintain capacities to detect and respond to health risks aboard ships.

In doctrinal terms, therefore, the IEPF bridges the persistent gap between soft guidance and hard obligations. It transforms vague treaty duties into operational standards that can withstand judicial and administrative scrutiny, particularly in disputes concerning wrongful disqualification, crew claims under labor law, or state responsibility in cases of medical evacuation failures. By integrating international conventions with evidence–based protocols, the framework not only enhances occupational safety but also secures greater compliance with fundamental principles of non–discrimination, proportionality, and accountability. In comparative terms, it represents a middle path between rigid exclusionary lists and ad hoc discretion, offering a replicable model that brings coherence to the fragmented field of maritime medical law.

Results: integrated EBM–policy paradigm

This study introduces the IEPF as both a novel operational solution and a conceptual advancement in maritime occupational health governance. While EBM has been sporadically applied in clinical maritime settings, its structured and policy–level integration into international maritime regulation remains underdeveloped. The IEPF fills this critical void by offering more than a practical toolkit–it represents a new regulatory paradigm that systematically links clinical evidence to policy decision–making, with global applicability across high–risk, logistically isolated occupations.

The IEPF’s innovation lies not only in its practical utility but in its theoretical architecture. Its three interdependent layers–clinical evidence appraisal, risk quantification, and dynamic policy integration–transform fragmented medical assessments into a unified governance mechanism. Unlike traditional maritime medical guidelines, often limited to listing disqualifying conditions or relying on practitioner discretion, the IEPF establishes a replicable, evidence–informed structure that converts appraised medical data into enforceable, transparent policy outcomes. This framework positions EBM as a regulatory engine, integrating adaptive feedback loops that enable real–time policy recalibration based on field outcomes.

Layer 1 anchors policy recommendations in robust science using validated tools such as GRADE and CONSORT. Layer 2—the MRSM–translates evidence into context–sensitive operational classifications (ʻfit,’ ʻrestricted fit,’ ʻunfit’). Layer 3 institutionalizes a feedback loop through a digital health database, creating a closed system for longitudinal monitoring, threshold refinement, and evolving regulatory alignment.

To validate the IEPF, the study employed a mixed–methods research approach. Data were collected from 112 maritime physicians across nine jurisdictions (Norway, the UK, Germany, Australia, Singapore, South Korea, the Philippines, Canada, and the Netherlands) via structured online surveys and semi–structured interviews conducted over six months. Quantitative data were analyzed using SPSS v28 (descriptive statistics, chi–square tests, and ANOVA), while qualitative responses underwent thematic analysis to identify implementation barriers, practical benefits, and systemic insights.

The following statistically significant results highlight the effectiveness of the IEPF compared to traditional assessment models (Table 4):

Table 4.

Results of survey about effectiveness of the IEPF compared to traditional assessment models.

Outcome metric	Traditional method	IEPF–based method	Statistical significance (p)
Evaluation consistency across physicians	61% agreement	87% agreement	p < 0.001
Rate of avoidable disqualification	14.3%	4.7%	p = 0.002
Physician confidence in decision–making	Avg. 6.1/10	Avg. 8.7/10	p < 0.001
Time taken per evaluation (avg.)	24 minutes	31 minutes	N/A (expected increase due to rigor)

Although the IEPF modestly increases evaluation time, this is viewed as an acceptable trade–off for gains in decision clarity, consistency, legal defensibility, and stakeholder trust.

Furthermore, institutional engagement demonstrated strong support for the IEPF’s adoption. By formalizing a systems–based approach to medical risk governance, the IEPF facilitates not only compliance but also proactive regulatory innovation.

Importantly, the IEPF demonstrates cross–sector applicability beyond traditional seafaring roles. Its relevance extends to offshore energy personnel, polar research teams, fisheries observers, and naval operations–underscoring its versatility in supporting fitness–to–work decisions in any high–risk, medically isolated setting. This positions the IEPF not merely as a maritime health tool, but as a generalizable model for evidence–based occupational governance in extreme environments.

To institutionalize the framework globally, the study proposes the development of an international maritime occupational health registry using standardized IEPF templates. This registry would facilitate continuous case tracking, longitudinal health monitoring, and ongoing recalibration of policy thresholds in response to new evidence–ensuring sustainability, adaptability, and scientific integrity in maritime medical governance.

Conclusion

This study proposes a foundational shift in maritime occupational health governance by embedding EBM within a novel, three–tiered framework–the IEPF. Moving beyond reactive or descriptive approaches, the IEPF institutionalizes clinical evidence through structured appraisal, maritime–specific risk stratification, and dynamic policy feedback. In doing so, it addresses persistent inconsistencies in medical fitness evaluations and establishes a replicable model for managing health risks in high–stakes, medically isolated environments–particularly relevant to circumpolar and remote maritime regions.

Empirical findings highlight the IEPF’s ability to improve decision consistency, reduce unjustified disqualifications, and enhance the legal defensibility of fitness–to–embark assessments. By translating clinical thresholds into operational risk categories, the framework offers a science–driven alternative to discretionary models that often fail to accommodate context–specific demands. Its adaptability across jurisdictions and capacity to respond to changing risk profiles make it especially well–suited for remote deployments where medical support is limited and evacuation is delayed.

The IEPF also contributes to broader discussions in implementation science and adaptive health governance. It demonstrates how structured evidence can be embedded into regulatory systems, bridging the gap between clinical research and policy in sectors where health outcomes and operational safety are tightly linked.

However, successful implementation requires addressing practical challenges, including training, infrastructure limitations, data governance, and stakeholder resistance. The digital feedback component, while innovative, also raises ethical and legal considerations–especially regarding cross–border data protection and system interoperability.

To realize its full potential, the IEPF will require coordinated investment in capacity building, technological development, and international cooperation. The study calls on regulatory bodies–particularly the IMO and ILO–to explore adoption and scaling of this framework to strengthen maritime health governance globally.

Ultimately, the IEPF provides a robust foundation for future–proofing occupational health policy in an era of growing complexity, geographic dispersion, and medical uncertainty.

Supplementary Material

Supplementary material

Supplementary Table S1. Summary of Literature Review Process and Key Evidence (GRADE-based appraisal).

Supplemental Material

Supplemental data for this article can be accessed at https://doi.org/10.1080/22423982.2025.2576341.

Author contributions

Conceptualization, A.H.A. and M.A.A.; methodology, A.H.A. and M.A.A.; software, M.A.A.; validation, A.H.A.; formal analysis, A.H.A. and M.A.A.; investigation, A.H.A. and M.A.A.; resources, A.H.A. and M.A.A.; data curation, A.H.A. and M.A.A.; writing–original draft preparation, A.H.A. and M.A.A.; writing–review and editing, A.H.A.; visualization, A.H.A. and M.A.A., All authors have read and agreed to the published version of the manuscript.

Disclosure statement

The authors report there are no competing interests to declare.

Funding

This research received no external funding.

Data availability statement

The datasets generated and analyzed during the current study are not publicly available as per our ethical approvals, to protect the confidentiality of study participants. Corresponding author can be contacted if someone wants to access the data from this study.