This paper is in the following e-collection/theme issue:

RCTs - Protocols/Proposals (funded, already peer-reviewed, non-eHealth) (207) Safety and Error Prevention in Health (246) Design of Processes and Workflows (199) Occupational Health and Ergonomics/Prevention at the Workplace (315) Knowledge Translation and Implementation Science (539) Ergonomics (19)

Published on in Vol 15 (2026)

This is a member publication of Bibsam Consortium

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/89185, first published .
Process Evaluation of a Structured Method for Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems (SIOHPS): Protocol for a Convergent Parallel Mixed Methods Study

Process Evaluation of a Structured Method for Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems (SIOHPS): Protocol for a Convergent Parallel Mixed Methods Study

Process Evaluation of a Structured Method for Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems (SIOHPS): Protocol for a Convergent Parallel Mixed Methods Study

Authors of this article:

Camilla Göras1, 2 Author Orcid Image ;   Ann-Sofie Ersson3, 4 Author Orcid Image ;   Therese Hellman5, 6 Author Orcid Image ;   Petronella Bjurling-Sjöberg4, 7 Author Orcid Image ;   Gunnar Bergström8, 9 Author Orcid Image ;   Robert Sarkadi Kristiansson4, 6 Author Orcid Image ;   Malin Lohela-Karlsson3, 4, 10 Author Orcid Image
Article Authors Cited by Tweetations Metrics

    Protocol

    1Department of Caring Sciences, Faculty of Health and Occupational Sciences, University of Gävle, Gävle, Sweden

    2Department of Caring Sciences, School of Health and Welfare, Dalarna University, Falun, Sweden

    3Centre for Clinical Research Västmanland, Uppsala University, Västerås, Uppsala, Sweden

    4Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden

    5Department of Medical Sciences, Uppsala University, Uppsala, Uppsala, Sweden

    6Primary Care and Health, Region Uppsala, Uppsala, Sweden

    7Centre for Clinical Research Sörmland, Uppsala University, Eskilstuna, Sweden

    8Unit of Intervention and Implementation Research for Worker Health, Karolinska Institutet, Stockholm, Sweden

    9Department of Occupational Health, Psychology and Sports Sciences, Faculty of Health and Occupational Studies, University of Gävle, Gävle, Sweden

    10School of Health, Care and Social Welfare, Mälardalen University, Västerås, Sweden

    Corresponding Author:

    Camilla Göras, PhD

    Department of Caring Sciences

    Faculty of Health and Occupational Sciences

    University of Gävle

    Kungsbäcksvägen 47

    Gävle, 80176

    Sweden

    Phone: 46 26 648468

    Email: camilla.goras@hig.se


    Background: Health care systems are increasingly challenged by demographic shifts, rising chronic illnesses, human resource constraints, and growing efficiency demands. Improving both occupational safety and health (OSH) and patient safety (PS) management has been identified as a pivotal strategy to address these challenges. However, there is a paucity of evidence-based methods that support systematic and integrated OSH and PS. In response, the Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems (SIOHPS) intervention was developed, guided by the Safer Culture Framework and the Medical Research Council (MRC) framework for complex interventions.

    Objective: This paper outlines the study protocol for a process evaluation embedded in the SIOHPS trial.

    Methods: The process evaluation will use a convergent parallel mixed methods design. The SIOHPS trial is conducted in 13 Swedish hospital settings. Guided by the Consolidated Framework for Implementation Research (CFIR), quantitative and qualitative data will be collected before, during, and after the trial through questionnaires, telephone interviews, focus group interviews (FGIs), observations, the SIOHPS digital tool, and other relevant documentation. In line with the convergent parallel mixed methods study design, the quantitative and qualitative data will be analyzed in a stepwise manner, initially independently from each other, followed by iterative triangulation.

    Results: Funding began in January 2023. The development phase was completed in early 2024, and the evaluation phase started in June 2024, with completion planned in early February 2026. Quantitative data collection for two of three clusters (baseline, 4- and 8-month follow-up) is complete, and data cleaning is underway. All qualitative data collected to date have been transcribed. Final data collection for cluster III, including the 8-month survey and FGIs, is scheduled for the end of January and early February 2026. Data analysis will begin in early 2026, with results to be disseminated through publications and conference presentations later in 2026.

    Conclusions: The process evaluation will integrate quantitative and qualitative data sources to elucidate the mechanisms through which the SIOHPS intervention influences safety culture, health care worker (HCW) health, PS, and quality of care. This comprehensive approach unpacks the “black box” of the implementation process, which will provide an in-depth nuanced picture of the intervention’s effectiveness and valuable insights into scalability and transferability across diverse health care contexts.

    Trial Registration: ClinicalTrials.gov NCT06398860; https://clinicaltrials.gov/study/NCT06398860

    International Registered Report Identifier (IRRID): DERR1-10.2196/89185

    JMIR Res Protoc 2026;15:e89185

    doi:10.2196/89185

    Keywords

    complex intervention; health care; mixed methods; occupational safety and health; patient safety; process evaluation; study protocol 


    Health care systems are increasingly challenged by demographic shifts, rising chronic illness, human resource constraints, and growing efficiency demands [1]. These challenges complicate the delivery of high-quality and safe care [2], place significant strain on the work environment of health care workers (HCWs), and threaten the sustainability of health care. Occupational safety and health (OSH) and patient safety (PS) are closely intertwined fields [3]. The COVID-19 pandemic underscored this interdependence, emphasizing that protecting HCW well-being is essential to maintaining a resilient health care system [4].

    Integrated OSH and PS management, to simultaneously prevent adverse outcomes in both fields, has been raised as having potential for addressing the challenges in a resource-effective manner [4,5]. However, evidence-based methods integrating OSH and PS are lacking (M Lohela-Karlsson, Associate Professor, unpublished data, January 2026), highlighting the need for the development and evaluation of such methods. In response, a theoretically grounded project was launched to develop and evaluate a structured method for OSH and PS management, called Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems (SIOHPS). To evaluate the SIOHPS intervention, a large-scale multidisciplinary trial has been performed [6].

    From a theoretical perspective [7], effective integration of OSH and PS requires addressing organizational factors that support a culture of safety across multiple system levels. This complexity needs to be considered in intervention development and evaluation, preferably codesigning it with key stakeholders and addressing the needs of different system levels. However, the efficiency of complex interventions, defined by multiple interacting components, diverse outcomes, and system-level impact [8], depends not only on the intervention itself, but also on the implementation process [9,10] and sustained enactment [11].

    The viability of an intervention depends on implementation outcomes, that is, stakeholders’ satisfaction with the intervention (acceptability); its fit and relevance to the context, problem, and users (appropriateness); the extent to which it can be successfully deployed (feasibility); and the financial impact and resources required for the implementation effort (implementation cost) [8]. Additionally, the extent to which an intervention is implemented as intended (fidelity) by its developers is critical for internal validity and for understanding intervention effectiveness [12]. Context-sensitive adaptations of an intervention’s design or delivery (adaptations) may be needed, while preferably preserving its core components [13]. Once viewed as a threat to fidelity, adaptations are currently considered vital for aligning complex interventions with real-world contexts and enhancing implementation outcomes [14]. Similarly, the extent to which an implemented intervention is sustained over time (sustainability) has been seen as a final implementation outcome [15], while being contemporary viewed as a dynamic, adaptive process that ensures continued use of an intervention in response to evolving needs [10]. Implementation outcomes are also shaped by the process through which interventions produce change, that is, enabling factors, enacting behaviors, and eventual unexpected pathways and consequences (mechanisms of impact) [7]. Hence, facilitators and barriers in the organizational, cultural, and structural environment in which an intervention is implemented (contextual conditions) [16,17] can provide valuable insights into intervention effectiveness [18].

    Implementation processes of complex interventions are often referred to as the “black box,” insinuating a lack of transparency that undermines reliable interpretation of outcomes and eventual scalability across health care settings. Additionally, despite growing interest, few studies address sustained interventions, probably due to varied definitions of sustainability and challenges in adapting interventions across contexts [19]. Addressing questions beyond the scope of effectiveness studies, process evaluations unpack the “black box” of the implementation process, with the purpose to understand how and why interventions succeed or fail. Such understanding can be used to assess whether interventions are viable and what adaptations and implementation strategies might be suitable in eventual future implementation across diverse contexts [18]. This paper outlines the study protocol for a process evaluation embedded in the SIOHPS trial [6].

    The overall aim of this process evaluation is to understand how the SIOHPS intervention is delivered and adhered to in practice, how context influences implementation, and the mechanisms through which it produces change.

    The specific aims of the process evaluation of the SIOHPS intervention are to:

    • Describe the content, frequency and dose, duration, and coverage (fidelity), as well as adaptations for contextual fit.
    • Explore the contextual factors that facilitate or hinder the implementation of the intervention.
    • Describe and compare short- and long-term outcomes between settings in relation to the implementation process.
    • Identify variables (mechanisms of impact) that may influence or contribute to the development of the intervention outputs.

    Study Design

    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.

    ‎
    Figure 1. Logic model illustrating the interrelationship between the process evaluation components: contextual factors; the implementation process and mechanisms of impact (coloured boxes); and the theoretical foundation, core components of the intervention, and expected intervention outputs (grey boxes). COM-B: capability, opportunity, motivation, and behavior.

    The SIOHPS Project

    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 SIOHPS Intervention

    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.

    Theoretical Assumptions

    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 and Procedure

    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.

    ‎
    Figure 2. Gantt chart illustrating data collection during the process evaluation phase, visualized in relation to the process evaluation components in accordance with the logic model. The boxes represent the type of data collected, the timing, and the month from intervention start when each data collection activity was conducted. C: cluster (C1-C3); HCW: health care worker; m: month (1=1 month, 4=4 months, 8=8 months); Pl: project logbook; SIOHPS: Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems.
    Table 1. Overview of the “fidelity” process domain, data collection, and operationalization in relation to the three core components for exploration of the SIOHPSa implementation.
    Dimension, core component, and data sourcesData collection methods (number of planned data collections, where relevant)OperationalizationData type
    Content and targeted education

    		First-line managers and support functionsFGIsb (n=13)Experience of the targeted educationQualitative
    Content and team debriefings

    		HCWscDirect observations (≥26)Adherence to the protocolQuantitative

    		HCWsDirect observations (≥26)Interruptions and the causes of observed interruptionsQuantitative, qualitative

    		First-line managers and support functionsFGIs (n=13)Experience of structured team debriefingsQualitative
    Content, and audit and feedback

    		First-line managers and support functionsFGIs (n=13)Experience of audit and feedbackQualitative
    Duration and team debriefings

    		HCWsDirect observations (≥26)Duration of structured team debriefingsQuantitative
    Duration, and audit and feedback

    		First-line managersDocumentation and FGIs (n=13)Experience of audit and feedbackQualitative

    		HCWsQuestionnaires (n=2)Perception of regular feedbackQuantitative
    Frequency and dose, and targeted education

    		HCWsQuestionnaires (n=2)Participation in targeted education and in what formatQuantitative

    		First-line managers and support functionsDocumentation and FGIsParticipation in targeted education and in what formatQuantitative, qualitative
    Frequency and dose, and team debriefings

    		SIOHPS digital toolAll HCWsNumber of reported estimates, including distribution by work shiftQuantitative

    		HCWsQuestionnaires (n=2)Participation in structured team debriefings in the past 4 monthsQuantitative
    Frequency and dose, and audit and feedback

    		First-line managers and support functionsFGIs (n=13)Experience of conducted audit and feedbackQualitative

    		HCWsQuestionnaires (n=2)Perception of regular feedback on reported data in the SIOHPS digital toolQuantitative
    Coverage (reach) and targeted education

    		First-line managers and support functionsDocumentation/logbookParticipation in targeted education and in what formatQualitative
    Coverage (reach) and team debriefings

    		First-line managers and support functionsFGIs (n=13)Presence during team debriefingsQualitative

    		HCWsDirect observations (≥26) and questionnaires (n=2)Participating professionals during structured team debriefingsQuantitative, qualitative
    Coverage (reach), and audit and feedback

    		First-line managers and support functionsFGIsProviding audit and feedbackQualitative

    		HCWsQuestionnaires (n=2)Perception of regular feedback on reported data in the SIOHPS digital toolQuantitative

    aSIOHPS: Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems.

    bFGI: focus group interview.

    cHCW: health care worker.

    Table 2. Overview of the “adaptations” process domain, data collection, and operationalization in relation to the three core components for exploration of the SIOHPSa implementation.
    Core components and data sourceData collection methods (number of planned data collections, where relevant)OperationalizationData type
    Targeted education

    		First-line managersDocumentation in a logbookContextual adaptations of education sessionsQualitative
    Targeted education and team debriefings

    		HCWsbDirect observations with memos (≥26)Adaptations from the original protocol and as intended by developersQualitative

    		HCWA follow-up question postobservation (≥26)Experiences of adaptation needs, the cause, and adaptations implementedQualitative

    aSIOHPS: Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems.

    bHCW: health care worker.

    Table 3. Overview of the “context” process domain, data collection, and operationalization in relation to the three core components for exploration of the SIOHPSa implementation.
    Core components and data sourcesData collection methods (number of planned data collections, where relevant)OperationalizationData type
    Targeted education, team debriefings, and audit and feedback

    		Central support functions working within the area of PSb or the work environment and first-line managersTelephone interviews (n=13+4)Mapping of factors at micro and meso levels with a potential impact on the conditions for systematic quality and safety work related to the work environment and PSQuantitative, qualitative

    		First-line managersTelephone interviews (n=13)Experience of organizational/contextual changesQualitative

    		First-line managers and support functionsFGIsc (n=13)Experience of barriers and facilitatorsQualitative

    		LogbookDocumentationContextual changes over timeQualitative

    aSIOHPS: Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems.

    bPS: patient safety.

    cFGI: focus group interview.

    Table 4. Overview of the “short- and long-term outcomes” process domain, data collection, and operationalization in relation to the three core components for exploration of the SIOHPSa implementation.
    Dimension, core components, and data sourcesData collection methods (number of planned data collections, where relevant)OperationalizationData type
    Acceptability, appropriateness, and feasibility (short term); team debriefings

    		HCWsbQuestionnaires (n=2)Perception of the SIOHPS digital toolQuantitative
    Acceptability, appropriateness, and feasibility (short term); targeted education, team debriefings, and audit and feedback

    		First-line managers and support functionsFGIsc (n=13)Experience of the SIOHPS methodQualitative
    Sustainability (long term); team debriefings

    		HCWsQuestionnaires (n=2)Perception of motivational factors involvement, communication, psychological safety, and consequencesQuantitative

    		HCWsQuestionnaires (n=2)Perception of intervention complexity, compatibility, and advantages of the methodQuantitative
    Sustainability (long term); audit and feedback

    		First-line managers and support functionsFGIs (n=13)Experiences of intervention complexity and advantages of the methodQualitative
    Sustainability (long term); targeted education, team debriefings, and audit and feedback

    		HCWsQuestionnaires (n=2)Perception of management commitmentQuantitative

    		First-line managersFGIs (n=13)Experience of support from head of departmentQualitative

    		First-line managers and support functionsFGIs (n=13)Experience of preconditions and goalsQualitative
    Sustainability (long term); team debriefings, and audit and feedback

    		First-line managers and support functionsFGIs (n=13)Experience of internal and external supportQualitative

    aSIOHPS: Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems.

    bHCW: health care worker.

    cFGI: focus group interview.

    Table 5. Overview of the “enabling factors” process domain, data collection, and operationalization in relation to the three core components for exploration of the mechanisms of impact.
    System level and factorsData sourceData collection methods (number of planned data collections, where relevant)OperationalizationData type
    Organizational level

    		Management commitment and prioritization of safetyFirst-line managers and support functionsFGIsa (n=13)Experiences of SIOHPSbQualitative

    		Resources for safetyFirst-line managers and support functionsFGIs (n=13)Experiences of SIOHPSQualitative
    Group level

    		CohesionHCWscQuestionnairePerceptions of communication and participationQuantitative

    		Psychological safetyHCWsQuestionnairePerceptions of psychological safetyQuantitative
    Individual level

    		Individual commitment and prioritization of safetyHCWsQuestionnairePerceptions of work engagementQuantitative

    		Sense of controlHCWsQuestionnairePerceptions of resourcesQuantitative

    aFGI: focus group interview.

    bSIOHPS: Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems.

    cHCW: health care worker.

    Table 6. Overview of the “enacting factors” process domain, data collection, and operationalization in relation to the three core components for exploration of the mechanisms of impact.
    FactorsData sourceData collection methods (number of planned data collections, where relevant)OperationalizationData type
    Teamwork climateHCWsaQuestionnairePerceptions of quality of collaboration between team membersQuantitative
    CommunicationHCWsQuestionnairePerceptions of communicationQuantitative
    Incident reportingIncident-reporting system—bFrequency of reported incidentsQuantitative
    Unexpected pathways and consequences

    		Contextual conditions and changesFirst-line managersTelephone interviews (n=13)Experienced contextual conditions and changesQualitative

    		Contextual conditions and changesFirst-line managersFGIsc (n=13)Barriers and facilitatorsQualitative

    aHCW: health care worker.

    bNot applicable.

    cFGI: focus group interview.

    Process Evaluation

    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.

    Implementation Process

    The implementation process describes how the intervention is delivered and adhered to in practice [18]. During this process, particular attention will be given to intervention fidelity, adaptations, and contextual conditions, as these factors are expected to influence both short- and long-term outcomes. Short-term outcomes, including acceptability, appropriateness, and feasibility, are primarily assumed to impact the intervention output and also sustainability of the intervention.

    Fidelity

    Given that SIOHPS is evaluated using an effectiveness-implementation hybrid design, fidelity will be assessed primarily as intervention fidelity, including fidelity of delivery and participant adherence. Fidelity of delivery refers to the interventionists’ actions and reflects the quality, consistency, and alignment of delivered activities in relation to the intervention protocol. Participant adherence captures the extent to which participants engage with the intervention as intended [36]. This part will be explored across four dimensions (content, coverage, frequency and dose, and duration [10]) related to the three core components of SIOHPS using multiple data sources.

    Content will be explored through participants’ experiences of education, information, and support provided for systematic management, complemented by observations of adherence to protocol, interruptions, and the causes of interruptions during team debriefings. Experience of the content in team debriefings and the audit and feedback process will also be examined.

    The duration of team debriefings will be observed, and the approximate time spent preparing presentation materials for audit and feedback sessions during workplace meetings will be obtained from the FGIs.

    Frequency and dose will be assessed through participation in the targeted education, including the delivery format. Additional information includes the frequency and distribution of team debriefings across work shifts and patterns of participation over time. The audit and feedback component will be examined by assessing the regularity of feedback provided through the SIOHPS digital tool and through routine workplace meetings or other communication channels.

    Coverage will be evaluated by documenting participation in education (live or online), presence during team debriefings, and the professional groups represented. Materials used when presenting audit and feedback results in workplace meetings will be collected as part of the documentation. Participants will also be surveyed regarding the regularity of feedback received based on reports in the SIOHPS digital tool.

    Adaptations

    To explore adaptations, information on participation in targeted education and the format will be collected as these are essential for contextual fit. In addition, experiences regarding the need for adaptations, their underlying causes, and the specific adaptations implemented will also be explored.

    Context

    The context domain will be guided by the Consolidated Framework for Implementation Research (CFIR) [37]. Prior to the start of the intervention, a comprehensive mapping of contextual factors in participating regions and units will be conducted through telephone interviews. A follow-up after 4 months will be performed to identify any organizational changes that could influence the implementation of SIOHPS. In addition, barriers and facilitators will be explored following completion of the intervention. Contextual changes during the study period will be continuously documented in the project logbook.

    Short- and Long-Term Outcomes

    During the implementation process, fidelity, adaptation, and contextual factors are expected to influence short-term outcomes, such as acceptability, appropriateness, and feasibility, which, in turn, are expected to mediate long-term outcomes, such as sustainability.

    Acceptability, appropriateness, and feasibility of the SIOHPS digital tool will be assessed by examining perceptions of its complexity, compatibility, and perceived advantages. Experiences of the SIOHPS method as a whole will also be explored.

    To examine long-term sustainability, motivational factors, such as involvement, will be assessed. Perceptions of management commitment will also be collected, and experiences of organizational support, prerequisites, and goals will be explored.

    Mechanisms of Impact

    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.

    Data Management and Analysis

    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].

    Quantitative Data

    For all quantitative data (Tables 1-6), analyses will include descriptive and comparative statistics to summarize and explore patterns in process and outcome domains across measurement points and settings. Descriptive analyses will be used to explore intervention delivery (eg, coverage, frequency and dose, duration, and adaptations), while comparative analyses will be applied to examine associations and potential relationships between process variables, contextual factors, and short- and long-term outcomes. Depending on data type, distributions, and study-specific requirements, appropriate parametric and nonparametric tests will be conducted using established statistical software, such as R (R Foundation for Statistical Computing), IBM SPSS, or equivalent.

    Qualitative Data

    For all qualitative data (Tables 1-6), an inductive-deductive approach will be applied guided by a thematic analysis outlined by Braun and Clarke [40], using NVivo software. Interviews will be audio-recorded and transcribed verbatim. Data analysis will follow an iterative process, allowing insights from initial telephone interviews, surveys, nonparticipant observations, and FGIs to inform subsequent data collection. The analysis process will follow a customary process, including repeated reading, coding, and categorizing, with gradually increasing abstraction. The final abstraction level will be determined based on the depth of data and the requirement of the different specific study aims.

    Triangulation

    In line with the convergent parallel mixed methods study design, all data will be analyzed in a stepwise manner. Initially, quantitative and qualitative data will be analyzed independently from each other, followed by iterative triangulation according to Creswell and Plano-Clark [41]. The breadth and complexity of the data, combined with data collection before, during, and after the intervention phase, means that different parts of the quantitative and qualitative results will be merged in multiple combinations to meet each specific aim. The formulation of the study aims reflects different analytic logics (convergent, exploratory, and explanatory) across aims, which will guide the integration of quantitative and qualitative findings, without altering the overall convergent design. Based on each aim, integration will occur through systematic comparison and complementary quantitative and qualitative results to inform understanding of observed outcomes. The different combinations of quantitative and qualitative data used in triangulation are outlined in Tables 1-6 for each process domain. Integration will be achieved through merging quantitative and qualitative results using complementary strategies, including joint displays, side-by-side comparisons, narrative weaving by aim, and matrix mapping of integrated findings to components of the underlying logic model, following the typology described by Fetters et al [42]. The logic model will further serve as a theoretical framework to guide the interpretation of interrelationships between contextual factors, implementation processes, mechanisms of impact, and intervention outputs (Figure 1). This strategy aims to strengthen the trustworthiness [43] of the process evaluation and to evaluate and refine the underlying logic model in alignment with the empirical results.

    Ethical Considerations

    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.


    Research funding for the project began in January 2023. The development phase was completed in the beginning of 2024, including refinement of the program theory, intervention components, and evaluation design in close collaboration with key stakeholders. The evaluation phase started in June 2024, with completion planned in early February 2026. The effectiveness trial protocol has been published, and description of the development phase is currently in preparation. Quantitative data collection for two of three clusters (baseline, 4- and 8-month follow-up) is complete, and data cleaning of these datasets is in progress. Interim feedback has been provided to participating units in clusters I and II. All qualitative material collected to date (contextual mapping and FGIs) has been fully transcribed. Planning for the final data collection for cluster III is underway and scheduled for the end of January and early February 2026, including the 8-month follow-up survey and FGIs. Data analysis will start in February-March 2026. Results will be disseminated through publications and conference presentations starting in 2026.


    Summary

    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.

    Comparison With Prior Work

    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].

    Strengths and Limitations

    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.

    Conclusion

    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.

    Acknowledgments

    The Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems (SIOHPS) research group is grateful for the contributions of the research assistants involved in the project. We extend our thanks specifically to Ellen Arbman Hansing, the current research assistant, for her efforts in participating during the focus group interviews and supporting the project during all phases of the process evaluation.

    The SIOHPS project has received funding from the Swedish Research Council for Health, Working Life and Welfare (FORTE) for the data collection part of the process evaluation (diary number 2022-00404) and Region Västmanland internal research funds (diary number LTV-1003601). This was peer-reviewed, and now is developed with further details. The funder will play no role in the conceptualization, design, data collection, analysis, decision to publish, or preparation of the manuscript.

    Data Availability

    The Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems (SIOHPS) project group will be open for collaboration with other researchers, and data will be shared, provided that a research plan is submitted to the project group and aligns with the ethical approval.

    Authors' Contributions

    CG is the principal investigator (PI) of the process evaluation; is leading the design, analysis, and interpretation of the process evaluation; and has contributed to the development of the intervention. She wrote the first draft of the study protocol for the process evaluation and will participate in the analysis and interpretation of the data. ASE and CG are the project managers of the trial, overseeing all activities and are responsible for the implementation. ASE is responsible for managing participating workplaces at Region Västmanland. She contributed to the development of the intervention and lead the development of the supporting Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems (SIOHPS) digital tool used in the intervention. CG is responsible for managing participating workplaces at Region Dalarna. MLK is the PI of the SIOHPS project. She is also leading the design of the effectiveness and economic evaluation. As a PI for the general project, she holds overall responsibility for the evaluation of the SIOHPS project, ensuring that both effectiveness and process evaluations are conducted in line with the established plan. All data collections are conducted by ASE, CG, and a research assistant, with support from MLK. MLK, ASE, and CG are the core team of the research project. TH, GB, PBS, and RSK are research associates of the project, acting as an advisory board to the core team, contributing to the study design, logic model, and interpretation of data; together with MLK and ASE, they have critically revised the protocol draft for important intellectual content. All authors have approved the final version of the manuscript and have agreed to be accountable for all aspects of the work. The authors declare the use of generative artificial intelligence (GAI) in the research and writing process. According to Generative AI Delegation Taxonomy (GAIDeT) 2025, the following tasks were delegated to a GAI tool (ChatGPT 5.2) under full human supervision: editing, proofreading, and translation. Responsibility for the final manuscript lies entirely with the authors. GAI tools are not listed as authors and do not bear responsibility for the final outcomes. CG used a GAI tool to clarify wording, translate text, and check grammar in sentences and sections. Additionally, CG sought assistance in shortening extended passages, while preserving nuances and the essence of the content and maintaining an academic tone.

    Conflicts of Interest

    None declared.

    Multimedia Appendix 1

    Peer-review report from the Swedish Research Council for Health, Working Life and Welfare (FORTE).

    PDF File (Adobe PDF File), 43 KB
    1. Page B, Irving D, Amalberti R, Vincent C. Health services under pressure: a scoping review and development of a taxonomy of adaptive strategies. BMJ Qual Saf. Oct 18, 2024;33(11):738-747. [FREE Full text] [CrossRef] [Medline]
    2. National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Health Care Services, Board on Global Health, Committee on Improving the Quality of Health Care Globally. Crossing the Global Quality Chasm: Improving Health Care Worldwide. Washington, DC. National Academies Press; 2018.
    3. Welp A, Manser T. Integrating teamwork, clinician occupational well-being and patient safety - development of a conceptual framework based on a systematic review. BMC Health Serv Res. Jul 19, 2016;16(1):281. [FREE Full text] [CrossRef] [Medline]
    4. Nathan Ezie K, Amekpor F, Scott G, Andigema AS, Musa S, Takoutsing B, et al. Healthcare workers’ safety; a necessity for a robust health system. Ann Glob Health. 2023;89(1):57. [FREE Full text] [CrossRef] [Medline]
    5. Keller S, Jelsma JGM, Tschan F, Sevdalis N, Löllgen RM, Creutzfeldt J, et al. Behavioral sciences applied to acute care teams: a research agenda for the years ahead by a European research network. BMC Health Serv Res. Jan 13, 2024;24(1):71. [FREE Full text] [CrossRef] [Medline]
    6. Lohela-Karlsson M, Ersson A, Hellman T, Condén Mellgren E, Bergström G, Bjurling-Sjöberg P, et al. Effectiveness- and cost effectiveness of a structured method for systematic and integrated occupational safety and health and patient safety management systems (SIOHPS) - a study protocol for a pragmatic stepped wedge cluster randomised controlled trial. BMC Health Serv Res. Oct 22, 2025;25(1):1391. [FREE Full text] [CrossRef] [Medline]
    7. Kilcullen MP, Bisbey TM, Ottosen MJ, Tsao K, Salas E, Thomas EJ. The Safer Culture Framework: an application to healthcare based on a multi-industry review of safety culture literature. Hum Factors. Feb 22, 2022;64(1):207-227. [FREE Full text] [CrossRef] [Medline]
    8. Skivington K, Matthews L, Simpson SA, Craig P, Baird J, Blazeby JM, et al. A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance. BMJ. Sep 30, 2021;374:n2061. [FREE Full text] [CrossRef] [Medline]
    9. Nilsen P, Kirk JW, Gunnarsson KU, Thomas K. Tempering implementation optimism: distinguishing between efficacy and effectiveness in implementation research. Implement Sci Commun. Aug 23, 2025;6(1):90. [FREE Full text] [CrossRef] [Medline]
    10. Nilsen P, Birken SA. Handbook on Implementation Science. Cheltenham, UK. Edward Elgar; 2020.
    11. Nilsson K, Bååthe F, Andersson AE, Wikström E, Sandoff M. Experiences from implementing value-based healthcare at a Swedish University Hospital - a longitudinal interview study. BMC Health Serv Res. Feb 28, 2017;17(1):169. [FREE Full text] [CrossRef] [Medline]
    12. Proctor EK, Bunger AC, Lengnick-Hall R, Gerke DR, Martin JK, Phillips RJ, et al. Ten years of implementation outcomes research: a scoping review. Implement Sci. Jul 25, 2023;18(1):31. [FREE Full text] [CrossRef] [Medline]
    13. Stirman SW, Gamarra J, Bartlett B, Calloway A, Gutner C. Empirical examinations of modifications and adaptations to evidence-based psychotherapies: methodologies, impact, and future directions. Clin Psychol (New York). Dec 2017;24(4):396-420. [FREE Full text] [CrossRef] [Medline]
    14. Moore JE, Bumbarger BK, Cooper BR. Examining adaptations of evidence-based programs in natural contexts. J Prim Prev. Jun 19, 2013;34(3):147-161. [FREE Full text] [CrossRef] [Medline]
    15. Proctor E, Luke D, Calhoun A, McMillen C, Brownson R, McCrary S, et al. Sustainability of evidence-based healthcare: research agenda, methodological advances, and infrastructure support. Implement Sci. Jun 11, 2015;10(1):88. [FREE Full text] [CrossRef] [Medline]
    16. Chambers DA, Glasgow RE, Stange KC. The dynamic sustainability framework: addressing the paradox of sustainment amid ongoing change. Implement Sci. Oct 02, 2013;8(1):117. [FREE Full text] [CrossRef] [Medline]
    17. Kitson A, Harvey G, McCormack B. Enabling the implementation of evidence based practice: a conceptual framework. Qual Health Care. Sep 01, 1998;7(3):149-158. [FREE Full text] [CrossRef] [Medline]
    18. Moore GF, Audrey S, Barker M, Bond L, Bonell C, Hardeman W, et al. Process evaluation of complex interventions: Medical Research Council guidance. BMJ. Mar 19, 2015;350:h1258. [FREE Full text] [CrossRef] [Medline]
    19. Wiltsey Stirman S, Kimberly J, Cook N, Calloway A, Castro F, Charns M. The sustainability of new programs and innovations: a review of the empirical literature and recommendations for future research. Implement Sci. Mar 14, 2012;7(1):17. [FREE Full text] [CrossRef] [Medline]
    20. Steinmetz-Wood M, Pluye P, Ross NA. The planning and reporting of mixed methods studies on the built environment and health. Prev Med. Sep 2019;126:105752. [FREE Full text] [CrossRef] [Medline]
    21. O'Cathain A, Croot L, Duncan E, Rousseau N, Sworn K, Turner KM, et al. Guidance on how to develop complex interventions to improve health and healthcare. BMJ Open. Aug 15, 2019;9(8):e029954. [FREE Full text] [CrossRef] [Medline]
    22. Landes SJ, McBain SA, Curran GM. Reprint of: an introduction to effectiveness-implementation hybrid designs. Psychiatry Res. Jan 2020;283:112630. [FREE Full text] [CrossRef] [Medline]
    23. Bakker AB, Demerouti E, Sanz-Vergel A. Job demands–resources theory: ten years later. Annu Rev Organ Psychol Organ Behav. Jan 23, 2023;10(1):25-53. [FREE Full text] [CrossRef]
    24. Aven T. A risk science perspective on the discussion concerning Safety I, Safety II and Safety III. Reliab Eng Syst Saf. Jan 2022;217:108077. [FREE Full text] [CrossRef]
    25. Kolb D. Experiential Learning: Experience as the Source of Learning and Development. NJ. Prentice-Hall; 1984.
    26. Michie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci. Apr 23, 2011;6(1):42. [FREE Full text] [CrossRef] [Medline]
    27. Stirman SW, Miller CJ, Toder K, Calloway A. Development of a framework and coding system for modifications and adaptations of evidence-based interventions. Implement Sci. Jun 10, 2013;8(1):65. [FREE Full text] [CrossRef] [Medline]
    28. Platania S, Morando M, Caruso A, Scuderi VE. The effect of psychosocial safety climate on engagement and psychological distress: a multilevel study on the healthcare sector. Safety. Sep 02, 2022;8(3):62. [FREE Full text] [CrossRef]
    29. Cheng H, Yang H, Ding Y, Wang B. Nurses' mental health and patient safety: an extension of the Job Demands-Resources model. J Nurs Manag. Apr 25, 2020;28(3):653-663. [FREE Full text] [CrossRef] [Medline]
    30. Wang J, Wu C, Tsai Y, Weng S, Hsu Y. The effects of safety climate on psychosocial factors: an empirical study in healthcare workplaces. J Patient Saf. May 3, 2021;18(2):e528-e533. [FREE Full text] [CrossRef] [Medline]
    31. Lake E, Sanders J, Duan R, Riman K, Schoenauer K, Chen Y. A meta-analysis of the associations between the nurse work environment in hospitals and 4 sets of outcomes. Med Care. May 2019;57(5):353-361. [FREE Full text] [CrossRef] [Medline]
    32. Sturm H, Rieger MA, Martus P, Ueding E, Wagner A, Holderried M, et al. WorkSafeMed Consortium. Do perceived working conditions and patient safety culture correlate with objective workload and patient outcomes: a cross-sectional explorative study from a German university hospital. PLoS One. Jan 4, 2019;14(1):e0209487. [FREE Full text] [CrossRef] [Medline]
    33. O'Connor DB, Hall LH, Johnson J. Job strain, burnout, wellbeing and patient safety in healthcare professionals. In: Montgomery A, van der Doef M, Panagopoulou E, Leiter MP, editors. Connecting Healthcare Worker Well-Being, Patient Safety and Organisational Change. Aligning Perspectives on Health, Safety and Well-Being. Cham. Springer; 2020:11-23.
    34. Teoh K, Hassard J. Linking organisational factors and patient care: does healthcare workers’ well-being matter? In: Montgomery A, van der Doef M, Panagopoulou E, Leiter MP, editors. Connecting Healthcare Worker Well-Being, Patient Safety and Organisational Change. Aligning Perspectives on Health, Safety and Well-Being. Cham. Springer; 2020:41-57.
    35. O'Donovan R, McAuliffe E. Exploring psychological safety in healthcare teams to inform the development of interventions: combining observational, survey and interview data. BMC Health Serv Res. Aug 31, 2020;20(1):810. [FREE Full text] [CrossRef] [Medline]
    36. Páez A, Nunan D, McCulloch P, Beard D. The influence of intervention fidelity on treatment effect estimates in clinical trials of complex interventions: a metaepidemiological study. J Clin Epidemiol. Jan 2025;177:111610. [FREE Full text] [CrossRef] [Medline]
    37. Damschroder LJ, Reardon CM, Widerquist MAO, Lowery J. The updated Consolidated Framework for Implementation Research based on user feedback. Implement Sci. Oct 29, 2022;17(1):75. [FREE Full text] [CrossRef] [Medline]
    38. Patton MQ. What is essential in developmental evaluation? On integrity, fidelity, adultery, abstinence, impotence, long-term commitment, integrity, and sensitivity in implementing evaluation models. Am J Eval. Mar 22, 2016;37(2):250-265. [FREE Full text] [CrossRef]
    39. Skivington K, Craig N, Craig P, Rycroft-Malone J, Matthews L, Simpson SA, et al. Introducing the revised framework for developing and evaluating complex interventions: a challenge and a resource for nursing research. Int J Nurs Stud. Jun 2024;154:104748. [FREE Full text] [CrossRef] [Medline]
    40. Braun V, Clarke V. Thematic Analysis: A Practical Guide. Los Angeles. SAGE; 2022.
    41. Creswell JW, Plano Clark VL. Designing and Conducting Mixed Methods Research. Los Angeles. SAGE; 2017.
    42. Fetters MD, Curry LA, Creswell JW. Achieving integration in mixed methods designs-principles and practices. Health Serv Res. Dec 2013;48(6 Pt 2):2134-2156. [FREE Full text] [CrossRef] [Medline]
    43. Lincoln YS, Guba EG. Naturalistic Inquiry. Beverly Hills, CA. SAGE; Jun 1985.
    44. French C, Pinnock H, Forbes G, Skene I, Taylor SJC. Process evaluation within pragmatic randomised controlled trials: what is it, why is it done, and can we find it?-a systematic review. Trials. Nov 09, 2020;21(1):916. [FREE Full text] [CrossRef] [Medline]
    45. Weiner BJ, Clary AS, Klaman SL, Turner K, Alishahi-Tabriz A. Organizational readiness for change: what we know, what we think we know, and what we need to know. In: Albers B, Shlonsky A, Mildon R, editors. Implementation Science 3.0. Cham. Springer; 2020:101-144.
    46. Karanika-Murray M, Gkiontsi D, Baguley T. Engaging leaders at two hierarchical levels in organizational health interventions: insights from the intervention team. Int J Workplace Health Manag. Sep 25, 2018;11(4):210-227. [FREE Full text] [CrossRef]
    47. Finn M, Walsh A, Rafter N, Mellon L, Chong HY, Naji A, et al. Effect of interventions to improve safety culture on healthcare workers in hospital settings: a systematic review of the international literature. BMJ Open Qual. May 07, 2024;13(2):e002506. [FREE Full text] [CrossRef] [Medline]
    48. von Thiele Schwarz U, Sørensen O, Tafvelin S, Roczniewska M. Complexity embraced: a new perspective on the evaluation of organisational interventions. Work Stress. May 08, 2024;38(4):373-379. [FREE Full text] [CrossRef]
    49. von Thiele Schwarz U, Aarons GA, Hasson H. The value equation: three complementary propositions for reconciling fidelity and adaptation in evidence-based practice implementation. BMC Health Serv Res. Nov 21, 2019;19(1):868. [FREE Full text] [CrossRef] [Medline]
    50. Lewis C, Klasnja P, Powell B, Lyon A, Tuzzio L, Jones S, et al. From classification to causality: advancing understanding of mechanisms of change in implementation science. Front Public Health. 2018;6:136. [FREE Full text] [CrossRef] [Medline]
    51. Shiyab W, Ferguson C, Rolls K, Halcomb E. Solutions to address low response rates in online surveys. Eur J Cardiovasc Nurs. May 25, 2023;22(4):441-444. [FREE Full text] [CrossRef] [Medline]

    ‎
    FGI: focus group interview
    HCW: health care worker
    MRC: Medical Research Council
    OSH: occupational safety and health
    PI: principal investigator
    PS: patient safety
    SIOHPS: Systematic and Integrated Occupational Safety and Health and Patient Safety Management Systems

    Edited by J Sarvestan; The proposal for this study was peer-reviewed by: the Swedish Research Council for Health, Working Life and Welfare (FORTE). See the Multimedia Appendix for the peer-review report; submitted 08.Dec.2025; accepted 09.Jan.2026; published 27.Jan.2026.

    Copyright

    ©Camilla Göras, Ann-Sofie Ersson, Therese Hellman, Petronella Bjurling-Sjöberg, Gunnar Bergström, Robert Sarkadi Kristiansson, Malin Lohela-Karlsson. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 27.Jan.2026.

    This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be included.