This study was registered at ClinicalTrials.gov (NCT06398860). The process evaluation follows the Medical Research Council (MRC) framework for complex interventions [18]. A convergent parallel mixed methods design [20] is used within a hybrid type 1 effectiveness-implementation framework.

The following section briefly describes the overall design and setting of the SIOHPS project. Next, the intervention (the SIOHPS method) and its underlying theoretical assumptions are provided, visualized in a logic model (Figure 1). Thereafter, participants, the procedure, and the process evaluation are outlined, including domains of the evaluation and the theoretical rationale for studying them. Finally, the planned analysis is described.

The SIOHPS project evaluates whether a structured, integrated approach to managing OSH and PS can improve HCW health and quality of care. It follows the MRC framework for complex interventions [8], emphasizing stakeholder codesign and contextual adaptation. The project is led by a core team consisting of the principal investigator (PI); two regional project managers, responsible for coordinating units in respective regions; and an administration assistant. The core team members bring complementary research and clinical expertise from health care fields, such as OSH management, occupational health services, PS, and PS culture. An advisory board (with clinical and academic background and expertise, including OSH, PS, and safety culture; intervention and implementation research; and roles such as chief medical officer, PS coordinator, and statistician) provides ongoing guidance.

The project comprised a development phase (2023-2024); it also comprises an evaluation phase. During the development phase, the program theory, intervention components, and evaluation design were refined in accordance with O’Cathain et al [21]. This work was coproduced with key stakeholders, including managers, HCWs involved in PS tasks, safety representatives, and central organizational functions. The development phase will be reported in a separate paper.

The evaluation uses a large-scale, multidisciplinary hybrid type 1 effectiveness-implementation framework [22], with the primary focus on effectiveness and cost-effectiveness and the secondary focus on the implementation process. The effectiveness study uses a pragmatic stepped-wedge cluster-controlled trial across two Swedish regions, involving 13 hospital units with round-the-clock care. Units transition from control to intervention in three steps, with at least 4 units per step and ≥360 HCWs. The sample size was determined to ensure sufficient unit-level representation, acknowledging variation in HCW numbers across units. All participating units had to provide round-the-clock care. The study protocol for the trial is outlined in a separate paper [6], while further details of the process evaluation are outlined later. Evaluation of effectiveness and process will be conducted by two separate but collaborative teams, led by the PI and one of the regional project managers, respectively. Integrating the teams supports coherent data collection, prevents duplication of effort, minimizes participant burden, and enables meaningful integration between implementation data and process outcomes [18].

The PI holds overall responsibility for ensuring the evaluation of established study protocols. The evaluation design, including the development of data collection instruments, was carried out in close collaboration with the advisory board during the development phase. The advisory board will continue to be consulted and receive regular updates, providing feedback on interim findings and overall implementation.

The developed intervention (ie, the SIOHPS method) consists of three core components: (1) targeted education, delivered in live format or in online format provided by the research team, to build foundational knowledge and practical skills to adhere to the SIOHPS method; (2) team debriefings (also known as end-of-shift huddles or after-action reviews), which HCWs are encouraged to perform after every shift; and (3) monthly audit and feedback by management in collaboration with the support functions based on data from team debriefings (Figure 1). The components target the needs of different system levels, involving management at both organizational and group levels, support functions (including those involved in PS work and the safety representatives of the work environment), and HCWs. The method encourages an integrated OSH and PS perspective when identifying patterns and root causes and taking measures, supported by a novel digital tool to be used in team debriefings, audit, and feedback.

The SIOHPS intervention and its process evaluation is theoretically grounded in the principles of safety culture theory [7] and complemented with four additional theoretical foundations: job demand-resources theory [23], the Safety I-II approach [24], Kolb’s experiential learning theory [25], and the COM-B (capability, opportunity, motivation, and behavior) model for behavior change [26]. To help clarify causal assumptions, a logic model was developed by the core team based on the relevant literature and in collaboration with the advisory board (Figure 1).

Briefly, the logic model visualizes that to evaluate the implementation and sustainability of SIOHPS, it is crucial to consider fidelity, adaptation, and context, as these domains interact in dynamic ways. The fidelity-adaptation dilemma [14,16,27] highlights the tension between preserving the core components of an intervention and adapting it to the local context. Striking this balance is crucial for sustainability and effectiveness, shaped by contextual factors across system levels (micro, meso, and macro) [16]. The core components of the intervention are designed to address the theoretical mechanisms of impact (ie, enabling factors and enacting behaviors) that, based on the Safer Culture Framework, influence the safety culture in the workplace [7]. Although the enabling factors do not constitute an integral component of SIOHPS or the chain of effects, they are nevertheless considered a contextual factor that possesses the capacity to exert influence on the outcome of the intervention. Additionally, unexpected pathways and consequences, due to contextual conditions and changes, affect both short- and long-term process outcomes and intervention output.

In the short term, the expected intervention output includes enhanced HCW participation and learning, alongside improved working conditions (eg, job demand and resources) and improved safety culture. These improvements are anticipated to positively affect work engagement [28], HCW health [29,30], productivity and PS [31-33], and perceived quality of care [31], contributing to reduced sick leave and improved health care quality [33,34]. The intermediate- and long-term effects are hypothesized to be mediated by improved safety culture and psychological safety [33]. However, both short- and long-term outcomes are dependent on the implementation process. Depending on whether participants adhere to the intervention (fidelity adaptations), effects are achieved on staff-related outcomes, patient-related outcomes, and safety culture (OSH culture and PS culture). Adherence to the intervention can be explained by the COM-B model [26].

Participants will include nursing assistants, registered nurses, physicians, managers, paramedical services, and support functions, together with internal facilitators. Stakeholders at the meso level, those functions involved in OSH and PS, will also contribute as informants. All HCWs will be encouraged to take part in the intervention, but to participate in the study, they must work at least 50% full-time at the unit. Data will be collected from various participants and stakeholders throughout the project period using a range of quantitative and qualitative methods. The sample size has been determined pragmatically for various parts of the project. The number of units included and HCWs was based on a power calculation for the intervention effect. Each unit was assumed to include an average of 30 HCWs. Based on the sample size calculation, at least 12 units and 360 HCWs were required to be included in the study to achieve sufficient statistical power for further analyses. The estimate was sufficiently conservative to detect the lowest expected intervention effect. The sample size was considered a minimum requirement, with primary emphasis placed on achieving the estimated number of units, as the number of staff members varied across units. A dropout rate of less than 20% for participating units and an attendance rate of at least 70% of all HCWs have been assumed in this study. For further details, please see the effectiveness study protocol [6]. The data collection process is illustrated in a Gantt chart (Figure 2). Overviews of the explored process domains, data collection methods, and their operationalization in relation to the three core components of SIOHPS are presented in Tables 1-4 for the implementation process and Tables 5 and 6 for the mechanisms of impact.

Survey data from HCWs will be collected in parallel with the effectiveness evaluation and comprise both quantitative measures (eg, Likert-scale items) and qualitative data from open-ended questions (Tables 1-6). All HCWs who fulfill the inclusion criteria will be invited to answer the questionnaires at each of the three measurement points (baseline, 4 months, and 8 months). Additional quantitative data will be collected from the SIOHPS digital tool. Qualitative data will be collected through individual telephone interviews with managers at each health care unit at the beginning of the study (n=13) and after 4 months (n=13). Focus group interviews (FGIs) with managers, support functions, and internal facilitators will be conducted at each health care unit after 8 months (n=13).

The performance of the SIOHPS method during team debriefings will be examined through nonparticipating observations conducted twice at each unit, after 1 and 4 months, respectively (n=at least 1 observation per data collection, yielding a minimum of 26 observations in total). The observations will be conducted by a single researcher and will not audio- or video-recorded in order to minimize potential inhibitory effects on team behavior. The observations will be documented contemporaneously in a template, and reflexive field notes will be documented after each observation. The observation protocol comprises two parts: intervention fidelity and psychological safety. The intervention fidelity part will be based on the SIOHPS method used during team debriefings. The psychological safety part will be based on O’Donovan et al’s work [35], with adjustments to fit debriefings under a short duration with possible interruptions. The observer will be one of the researchers (author ASE), who is well informed about the intervention and the study. Additionally, the observer will be trained in pilot observations, in which the observer and the PI independently will rate the same team debriefings. These will be discussed to ensure consistency in interpretation. The protocol will be refined accordingly, followed by additional pilot observations to further train the observer and to ensure that the protocol functions according to its purpose.

Documentation in logbooks will occur iteratively during the different phases, as described in the MRC framework [18]. Additionally, qualitative data will be gathered through face-to-face interactions, telephone calls, video conferences and informal observations, and continuous process notes documented in connection with every contact with participating units.

All data will be stored pseudonymized, with only the date and time of the interviews documented, and will be analyzed solely at the group level.

The process evaluation will explore the implementation process, including fidelity, adaptations, context and process outcomes (short and long term), and mechanisms of impact [18], with theoretical assumptions based on the logic model (Figure 1). An overview of explored process domains, data collection, and operationalization in relation to the three core components of SIOHPS is presented in Tables 1-6.

Mechanisms of impact refer to the processes through which interventions produce change. For SIOHPS, these mechanisms are explored from a theoretical perspective, with enabling factors from the Safer Culture Framework. The Safer Culture Framework [7] and the COM-B model [26] informed the operationalization of the mechanisms of impact and guided data collection through questionnaires, telephone interviews, and FGIs (Tables 5 and 6).

At the organizational level, management commitment and prioritization of safety and investment in safety competencies are expected to foster an environment conducive to effective implementation and sustained impact by enhancing fidelity, promoting safety culture, motivating HCWs, and enabling capacity building. On a group level, cohesion and psychological safety facilitate open communication, engagement, and collective learning through trust, key processes for cultural change, and long-term sustainability. At the individual level, commitment, prioritization of safety, and perceived control are assumed to be drivers of sustained engagement.

Together, these enabling factors influence enacting behaviors, such as communication, teamwork, incident reporting, and ownership of safety practices, thereby activating mechanisms for lasting improvements in OSH culture [7]. SIOHPS is designed to reinforce these processes by promoting effective communication and regular incident reporting.

Contextual factors and organizational changes may also generate unanticipated pathways influencing short- and long-term outcomes, reflecting the dynamic interplay between external demands, internal dynamics, and organizational structures.

In line with the MRC framework [18], qualitative findings will be integrated with quantitative measures of process variables and short- and long-term outcomes, particularly where these are expected to influence the SIOHPS intervention’s effectiveness and functionality. All analyses will be explorative and framed by the underlying logic model (Figure 1). Aligned with a developmental evaluation approach, the analysis will remain open to emergent findings and local contextual adaptations, supported by continuous learning [38]. This will enable the study to capture how the intervention functions in practice and to identify refinements for future large-scale implementation [8,39].

The project was approved by the Swedish Ethics Review Authority (IDs 2023-02402-01 and 2024-01407-02). Informed consent was collected from the participants before data collection. Project datasets will be stored in secure storage for research data provided by Region Västmanland. Members of the Systematic and Integrated Occupational Health and Patient Safety (SIOHPS) project core team will be given access to the cleaned datasets. To ensure confidentiality, all data forms and data files will be pseudonymized, and project team members will be blinded to any identifying participant information. The code key will be stored separately. Access to the code key will be restricted to researchers in the core research team.

This protocol outlines the process evaluation embedded in the SIOHPS trial, an effectiveness-implementation hybrid type 1 study assessing an integrated approach to systematic OSH and PS management. Conducting a process evaluation alongside the trial is essential to clarify how the intervention is delivered, how contextual factors influence implementation, and how through them change is generated [18,44]. Because the hybrid type 1 design primarily targets effectiveness [22], fidelity focuses on intervention fidelity, including fidelity of delivery and participant adherence [36] instead of implementation fidelity. The logic model (Figure 1) will guide the analytical process [18] and support examination of how fidelity, adaptations, and contextual conditions interact across system levels.

A mixed methods design [41] is appropriate for capturing the complexity of the SIOHPS intervention. Quantitative process data collected at multiple time points will describe implementation patterns and indicators of sustainability, while qualitative data will be gathered iteratively throughout implementation. This reflects the intervention’s complexity and the dynamic nature of its implementation context. Multiple mixed methods will support meaningful data integration and accommodate emerging contextual changes. Coproduction with stakeholders will help ensure that diverse perspectives are presented.

Implementation of complex interventions often occurs in organizational environments characterized by imbalances between job demands and available resources [23]. Consistent with previous research, factors such as organizational readiness [45], leadership engagement [46], and traditional separation of systematic OSH management and PS work are likely to influence the implementation of SIOHPS.

Organizational interventions aimed at strengthening PS culture have shown positive effects on HCW working conditions and health [47], yet few are designed to support systematic OSH management or reinforce OSH culture. Despite the interdependence between OSH and PS, a recent scoping review did not identify interventions targeting improvements in both safety cultures simultaneously (M Lohela-Karlsson, Associate Professor, unpublished data, January 2026). This gap likely reflects longstanding organizational silos within health care. Within SIOHPS, the work processes are integrated, which is essential for influencing both PS culture and OSH culture, thereby supporting the interventions primary long-term outcomes. Such organizational integration introduces additional complexity, as the intervention interacts dynamically with local structures, workflows, and contextual conditions. This aligns with contemporary perspectives emphasizing the need to embrace complexity in the design and evaluation of organizational interventions [48], reinforcing the importance of a rigorous process evaluation.

Balancing fidelity and adaptation [49] are particularly relevant in complex interventions. Achieving fidelity, while allowing contextually appropriate adaptations, requires preserving core components while tailoring implementation to local needs. This process evaluation will examine how this balance is negotiated across units and regions. Although specific implementation strategies are not tested, mapping contextual factors at micro and meso levels, together with documentation of barriers and facilitators, will support a nuanced understanding of how SIOHPS is enacted in practice.

With the Safer Culture Framework, encompassing enabling factors and enacting behaviors, this evaluation adopts a theory-informed lens that strengthens understanding of integrated OSH and PS management interventions. This approach positions key factors for safety culture as the key unifying mechanism connecting the two fields and influences how integrated interventions produce change. The SIOHPS evaluation therefore offers a theoretically grounded example of how mechanisms of impact operate across organizational, group, and individual levels, thereby advancing the understanding of mechanisms of change [50].

A strength of this process evaluation is the use of a logic model to guide data collection and analysis. This facilitates systematic assessment of fidelity, adaptations, contextual conditions, and mechanisms of impact and supports iterative refinement of theoretical assumptions. The mixed methods design and longitudinal data collection allow for the examination of temporal patterns and triangulation of findings across diverse data sources. Coproduction provides valuable insights into multiple perspectives on the implementation process.

The process evaluation also has potential limitations. Achieving adequate response rates in web-based surveys remains challenging [51] and will require close monitoring and active involvement of first-line managers and internal facilitators. The round-the-clock operational context of participating units might limit opportunities to convene support functions and internal facilitators for focus groups. The complexity of the SIOHPS intervention and the substantial volume of data collected also present analytical challenges. To mitigate these issues, analytic procedures will be anchored in the logic model and supported by iterative triangulation across methods.

This process evaluation is designed to illuminate how SIOHPS is implemented across diverse real-world settings and to identify the mechanisms through which it generates both short- and long-term outcomes. Through contextual mapping, exploration of barriers and facilitators, and examination of fidelity and adaptations, the evaluation is expected to generate insights that can inform future refinements of the SIOHPS intervention and guide the selection of appropriate implementation strategies for broader scale-up. The mixed methods approach, combined with iterative engagement with stakeholders, will enhance the robustness and transferability of findings and contribute to advancing knowledge on integrated complex organizational interventions, such as OSH and PS interventions.