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• Volume 6, Issue 12
• A guide to systems-level, participatory, theory-informed implementation research in global health
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• http://orcid.org/0000-0002-4821-9437 Nadine Seward 1 ,
• http://orcid.org/0000-0002-7937-3226 Charlotte Hanlon 2 , 3 ,
• http://orcid.org/0000-0001-9043-8847 Saba Hinrichs-Kraples 4 ,
• Crick Lund 5 , 6 ,
• http://orcid.org/0000-0002-9021-3629 Jamie Murdoch 7 ,
• Tatiana Taylor Salisbury 5 ,
• Ruth Verhey 8 ,
• http://orcid.org/0000-0001-9365-7164 Rahul Shidhaye 9 ,
• Graham Thornicroft 5 ,
• Ricardo Araya 5 ,
• Nick Sevdalis 10
• 1 Centre for Implementation Science, Department of Health Service and Population Research , King's College London , London , UK
• 2 Institute of Psychiatry, Psychology and Neuroscience, Health Service and Population Research Department, Centre for Global Mental Health , King's College London , London , UK
• 3 Centre for Innovative Drug Development and Therapeutic Trials for Africa (CDT-Africa), College of Health Sciences , Addis Ababa University , Addis Ababa , Ethiopia
• 4 Delft University of Technology , Delft , The Netherlands
• 5 King's College London , London , UK
• 6 University of Cape Town , Rondebosch , South Africa
• 7 University of East Anglia Faculty of Medicine and Health Sciences , Norwich , UK
• 8 Research Support Centre, College of Health Sciences , University of Zimbabwe , Harare , Zimbabwe
• 9 Pravara Institute of Medical Sciences , Loni , Maharashtra , India
• 10 Health Service & Population Research Department , King's College London , London , UK
• Correspondence to Dr Nadine Seward; nadine.seward{at}kcl.ac.uk

Implementation research is a multidisciplinary field that addresses the complex phenomenon of how context influences our ability to deliver evidence-informed healthcare. There is increasing realisation of the importance of applying robust implementation research to scale-up life-saving interventions that meet health-related sustainable development goals. However, the lack of high-quality implementation research is impeding our ability to meet these targets, globally. Within implementation research, theory refers to the proposed hypothesis and/or explanation of how an intervention is expected to interact with the local context and actors to bring about change. Although there is increasing interest in applying theory to understand how and why implementation programmes work in real-world settings, global health actors still tend to favour impact evaluations conducted in controlled environments. This may, in part, be due to the relative novelty as well as methodological complexity of implementation research and the need to draw on divergent disciplines, including epidemiology, implementation science and social sciences. Because of this, implementation research is faced with a particular set of challenges about how to reconcile different ways of thinking and constructing knowledge about healthcare interventions. To help translate some of the ambiguity surrounding how divergent theoretical approaches and methods contribute to implementation research, we draw on our multidisciplinary expertise in the field, particularly in global health. We offer an overview of the different theoretical approaches and describe how they are applied to continuously select, monitor and evaluate implementation strategies throughout the different phases of implementation research. In doing so, we offer a relatively brief, user-focused guide to help global health actors implement and report on evaluation of evidence-based and scalable interventions, programmes and practices.

• health policies and all other topics
• health systems
• health systems evaluation
• public health

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Not applicable.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjgh-2021-005365

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Summary box

Despite the evidence that highlights the need for implementation research to achieve the United Nation’s Sustainable Development Goals, global health researchers often do not incorporate core implementation components in their work systematically.

This guide aims to address the lack of guidance describing how to apply a range of theoretical approaches and methods that address specific questions in the context of implementation research for global health.

In doing so, we aim to offer a relatively brief, user-focused guide to help multidisciplinary global health groups design, implement and report on evaluation of evidence-based and scalable interventions, programmes and practices.

Improving the quality of implementation research in global health cannot be achieved without decolonising the very structures global health is based on. This includes, but is not limited to, ensuring research agendas are no longer set by donors from the global North. Instead, research should be driven by people from the South—the holders of knowledge of the local needs and priorities and the context that shapes their health systems.

Introduction

In poorly resourced settings within low-income and middle-income countries (LMICs) and within some high-income countries, access to high-quality evidence-informed healthcare is severely limited. 1 2 In these settings, a range of contextual and behavioural barriers and enablers at the macrolevel, mesolevel and microlevel, influence our ability to deliver this care including sociocultural, socioeconomic, geographical, epidemiological, psychological, ethical, legal and political determinants. 3 Overcoming these barriers and leveraging the enablers to effectively implement evidence-informed practice requires a mixed-methods, theoretically informed approach involving stakeholders from all levels of the health system, including service users. This is inherently different from the approach typically applied to clinical trials, which test the effectiveness of a novel drug or therapy. 4

Implementation research is widely recognised as ‘the scientific inquiry into questions concerning implementation—the act of carrying an intervention into effect, which in health research can be policies, programmes or individual practices (collectively called interventions) ’ . 5 Although the terms ‘implementation research’ and ‘implementation science’ are used interchangeably in the literature, we use this definition as an umbrella term, under which fall various theoretical approaches and methods. As an example, we situate implementation science (eg, determinant frameworks, evaluation frameworks and implementation theories) as one approach within implementation research that studies the methods for how we bring evidence-informed care to scale.

In order to ensure healthcare interventions improve health outcomes, a central concern of implementation research is to develop, test and refine the theory of how delivery of the intervention can be optimised within complex social settings. Within implementation research, theory can refer to the proposed hypothesis and/or explanation of how an intervention is expected to interact with the local context and actors to bring about change. 6–8 Implementation research typically requires multidisciplinarity that draws on a range of theoretical approaches. The theoretical approaches applied to implementation research arise from different knowledge paradigms that view the world differently, such as positivism (reality is a set of observable events) or critical realism (reality exists separately from social actors) or relativism (reality is subject to different interpretations of how actors engage with one another and the context). 9 10 Because of this, implementation research is faced with a particular set of challenges about how to reconcile different ways of thinking and constructing knowledge about healthcare interventions. Box 1 describes how different theoretical approaches offered by different knowledge paradigms contribute to implementation research.

The contribution of theoretical approaches offered by the different knowledge paradigms to implementation research

Positivism: Views the world as observable events that can be measured. Positivists use deductive reasoning by primarily adapting quantitative methods to test hypotheses about a proposed intervention, that is grounded in previous research or proposed theories. Positivist approaches to implementation research address questions such as ‘what is the effectiveness of task-shifting in increasing access to psychological therapies?’, and ‘how does stigma influence the effectiveness of task-shifting in increasing coverage of psychological therapies?’.

Relativism: Views reality as subject to different interpretations, generating multiple realities that are constructed and shifting over time through the actions and interactions of different actors. 9 10 Relativists use inductive approach that is not driven by a hypothesis to generate a theory about a phenomenon or to test a pre-existing theory. A relativist approach to implementation research address questions such as ‘How do social processes influence a patient’s understanding and experiences of task-shifting to improve access to psychological therapies for depression’.

Critical realism: Views reality as existing independently from social actors, stratified by social structures (eg, healthcare systems, political institutions, economies) and processes (eg, political, legal, ethical and bureaucratic policies). Critical realists use both deductive (theory testing) and inductive (theory building) approaches. By framing the social world as socially structured actions and mechanisms, critical realists produce knowledge on a range of mechanisms which mediate the relationship between cause and effect within different contexts and therefore addressing questions surrounding what works for whom and under what circumstances. 9

These challenges are not unique to implementation research. Given that implementation research is about strengthening health systems to ensure access to and delivery of high-quality affordable care, it also shares close ties with Health System and Policy Research (HSPR). 5 Indeed, HSPR has been defined as ‘a discipline that seeks to understand and improve how societies organise themselves in achieving collective health goals, and how different actors interact in the policy and implementation processes to contribute to policy outcome’ . 9 Due to the increased awareness of its importance for health system strengthening, implementation research is now a rapidly expanding discipline that tests, refines and adapts different strategies to address barriers and build on enablers to bring high-quality evidence-informed practice to scale. 5

Whereas public health in LMICs addresses issues relevant to a particular community or country, 11 the focus of global health is the quest for equity, including within high-income countries as well as within LMICs. 12 As such, global health is defined by problems of delivering high-quality evidence informed care in practice, especially to the most vulnerable. Like HSPR, implementation research is a highly interdisciplinary and multidisciplinary field that address delivery problems in global health. 12

Current state of implementation research in global health

Despite the evidence that highlights the need for implementation research to achieve the United Nations Sustainable Development Goals, 13 a review addressing how these approaches and methods are being applied in LMICs suggests that researchers often do not incorporate core implementation components in their work. 14 As an example, the review found that only a very small number of articles made use of implementation models or theories. The review also found that of the studies that reported their research as implementation research, only 52% (n=415) described contextual determinants and fewer than 5% addressed objectives focused on scaling up (n=32) or sustainability (n=25). Box 2 describes characteristics of high-quality implementation research.

Key principles and concepts to support high-quality implementation research in low-income and middle-income countries (LMICs)

Capacity building: The need to build capacity to conduct high-quality implementation research in global health is greatest in resource-poor contexts within LMICs. Despite efforts to increase the numbers of researchers who are able to carry out high-quality research, numbers remain low. 74

Context: Implementing evidence-informed practices needs to account for the context—any feature of the circumstances in which an intervention is conceived, developed, implemented and evaluated. 75 With implementation research in LMICs, addressing ‘contextual equipoise’ is particularly relevant as it helps to ensure that implementation efforts account for the needs and priorities of the local population in addition to preventing the inappropriate use of randomised controlled trials that denies participants in the control arm access to treatments that is known to be effective within the local context. 76

Evidence-informed practice: Whereas evidenced-based care is considered the gold standard for effective healthcare delivery, the application of evidence into practice is referred to as evidence-informed practice. 77 This distinction is important as the application of evidence into practice encounters multiple difficulties including challenges with unstable settings with rapidly changing contexts and unintended consequences. Many healthcare practitioners therefore feel that implementing evidence-based practice, should be informed by, as opposed to based on, evidence.

Embedding research activities into existing programmes and health systems: Embedded research is carried out as an integrated and systematic part of decision making and implementation that involves the collaboration between policy-makers, implementers and communities. 33 Embedding research improves ownership and, therefore, the application of the research findings.

Evaluation in real-world settings: Most implementation research in global health is conducted in resource-constrained settings. In order to bring evidence based care to scale, it is essential that implementation research is embedded in the local health system or community, allowing research to be conducted in real-world conditions, with the types of resources, incentives and operational support they would have under routine situations. 14

Mixed-methods approach: Both quantitative and qualitative methods are required to understand how and why interventions work in real-world settings: Findings are then triangulated to conceptualise and confirm how the implementation of evidence-informed practice led to the measured impact. 14 78

Multistakeholder involvement and engagement: Collaboration and partnerships among multiple stakeholders (such as academics, implementers, users, advocates, policy-makers and donors) across various influence domains (research, programme, policy and funding) is important for any implementation research enterprise to achieve large-scale impact. 14 Ensuring involvement of stakeholders who can potentially influence implementation efforts can also help to ensure the intervention is meeting the needs and proprieties of the population it is intended on serving.

Scale-up: many effective treatments are never brought to scale which is often referred to as the ‘delivery gap’ . 79 Applying robust implementation research, can help support scale-up. 80

Systems-level approach: a systems-level approach to the design and evaluation of interventions, views a complex intervention as a system in itself, interacting with other building blocks of the underlying health system in which the intervention embeds itself, setting off reactions that may well be unexpected or unpredictable. 81

Sustainability: is the extent to which a newly implemented treatment is maintained or institutionalised within a service setting. With implementation research in LMICs, sustainability is essential as it is unethical to implement evidence-informed care that has effectively improved health outcomes in other settings, only to withdraw this treatment if it is not sustainable. 82

Theory-driven research: A theory can be defined as a set of analytical principles or statements designed to structure our observation, understanding and explanation of the world. 35 Within the field of implementation science, this research uses theory to develop a set of propositions or hypotheses about how implementation phenomena might unfold, which are subsequently testes through collection of empirical observations. Arguably, all attempts to improve healthcare and its outcomes are driven by theory 83 ; theory-driven research makes such theories explicit and allows them to be tested in practice, so that an evidence-based accumulates gradually around implementation phenomena.

Unintended consequences: With implementation research there are often outcomes that are not anticipated that can be positive or negative. 84 It is important to be mindful of, and explore whether any unintended or unanticipated consequences occur as a result of implementation efforts. Research projects should be designed to allow for the identification and effective management of unintended consequences. 85

Health systems strengthening (HSS): involves comprehensive changes to policies and regulations, organisational structures, and relationships across the health system building blocks (eg, service delivery, health workforce, health information systems, access to essential medicines, financing and leadership/governance) that motivate changes in behaviour, and/or allow more effective use of resources across multiple care platforms. 81 86 Implementation research, which applies a multidisciplinary approach to understand which interventions and implementation strategies work for whom, and how, can be usefully applied to HSS by identifying and addressing barriers and opportunities to the delivery of high-quality quality care and testing potential solutions. 5

Reasons for the above weaknesses are complex and stem beyond the novelty of some of the implementation science developments or the multidisciplinary nature of the work. Much of global health research is driven by actors in the North (ie, high-income country institutions), who decide not only what needs to be investigated or funding available, but also the methods and approaches to investigate the topic of interest. 15 Donors from the North also tend to favour short-term research programmes with measurable impact whereas implementation research and health systems strengthening require longer term investments with more uncertain outcomes, and genuine engagement with users, stakeholders and adopters of research outcomes, which is resource-intensive and time-consuming. 15 Decolonising global health, that ‘involves removing all forms of supremacy within all spaces of global health practice, within countries, between countries and at a global level’ is key to improving the quality and relevance of implementation research. 16 Although not formally defined, decolonising global health can be viewed as ‘a movement that fights against ingrained systems of dominance and power in the work to improve the health of populations’. 17 In part this can be achieved by ensuring actors in the South (ie, LMIC institutions) are the ones who take ownership of and drive implementation research within their respective contexts. 16

Addressing the need for high-quality implementation research

There have been useful guides and articles published on implementation research that aim to ensure rigour. The WHO guide to implementation research, published by the Alliance for Health Policy and Systems Research has the overall aim of improving capacity, particularly within LMICs. 5 The guide provides a broad overview of implementation research including why it is important, appropriate methods, and explanation of relevant stakeholders. 5 The Medical Research Council (MRC) of the UK has published guidance on the design and evaluation of complex interventions that has proven to be very influential. 18 More recently, the MRC has released guidance on how to adapt an evidence-informed intervention to a new context. 19 Although these guidelines review in detail the essential components to design and evaluate complex interventions, they offer little emphasis or direction on how different theoretical approaches and methods can be applied in practice throughout the different phases of implementation research to address specific research objectives.

This guide aims to address the gaps in the literature in order to provide an overview of the different theoretical approaches and methods to implementation research that can be applied to address specific research objectives, throughout the implementation process. Our guidance, including the cited literature, is based on our expertise in the following multicountry implementation research programmes: Programme for Improving Mental Health care (PRIME), 20–23 a consortium of research institutions and ministries of health in five LMICs that implemented and expanded coverage of treatment for mental health conditions in primary care and community settings; the Emerging Mental Health Systems in LMICs (EMERALD) programme 24 25 ; and a multicountry heAlth Systems StrEngThening programme guided by implementation research and implementation science in sub-Saharan Africa (ASSET). 26 27 We also have experience with participatory research including participatory learning and action (PLA) with women’s groups to improve maternal and newborn health outcomes 28 29 and human-centred design to improve perinatal mental health outcomes. 30 We aim to use our experience to offer a relatively brief, user-focused guide to help global health actors recognise the important contributions arising from the different theoretical approaches and other methods to implement and report on evaluation of evidence-based and scalable interventions, programmes and practices.

The rest of the paper is organised as follows: initially we offer an overview of the role of theory and describe how this is applied to the different phases of implementation research. We then provide an outline of how the different theoretical approaches and associated methods we present can be applied throughout the implementation research process. This is followed by a discussion of how other methods, such as engagement with stakeholders, need to be embedded within implementation research. We provide case examples for illustration of the above aspects of implementation research that are based on research we have conducted within PRIME, EMERALD and ASSET as well as other research programmes we have been involved in.

Overview of implementation research

The role of theory applied to implementation research.

Within implementation research, the question(s) being investigated will determine the theoretical approach(es) taken and how such investigations are carried out. This applies from the preimplementation phase, which focuses on stakeholder engagement and participatory methods to understand the context where an intervention will be introduced, to the codesign of interventions and implementation strategies, through to approaches adopted to evaluate implementation. This approach can help to ensure both sustainability and transferability.

Implementation research relies heavily on social science theories driven by the relativist paradigm of knowledge. Social science theories (eg, grand theories, such as Marxism) 31 provide abstract conceptualisations of the social world, that explain the causal relationships between a phenomenon and an outcome. 32 Social science theories can also be used to guide not only the study design, but also the analysis and understanding of the findings. Box 3 describes different theoretical approaches and other methods relevant to implementation research. Box 4 describes methods and tools that complement the theoretical approaches used within implementation research.

Theoretical approaches to implementation research

Implementation science.

Implementation determinant frameworks: The compilation of contextual barriers/enablers that are known to influence the ability to effectively implement the evidence-informed practice. Researchers use these frameworks to help identify determinants relevant to their implementation problem and the context within they work. 35

Implementation theories: A set of analytical principles or statements designed to structure our observation, understanding and explanation of the world. Implementation theories can be used to identify enablers/barriers to implementation as well as the mechanisms by which these operate. 35

Implementation process models: Describe the process of translating research into practice through different phases of research. 35

Social science theories: Drawing from the relativist knowledge paradigm, social science theories provide abstract conceptualisation of the social world that explain causal relationships between a phenomenon and an outcome. 32

Realist evaluation: A way of connecting high‐level social theory with empirically observable patterns. ‘Middle-range theories’ derived from this approach are useful in addressing complexity, including a realist evaluation that accounts for how context influences the underlying mechanisms by which implementation strategies achieve the outcomes. 84

Programme theory: Describes how a specific intervention is expected to lead to its effects and under what conditions. 87

Participatory methods: defined as the process of producing new knowledge by ‘systematic inquiry, with the collaboration of those affected by the issue being studied, for the purposes of education and taking action or effecting social change’. 53

Methodological approaches and tools for implementation research

Implementation strategies: Methods or techniques used to enhance the adoption, implementation and sustainability of a clinical programme or practice. 4 Implementation strategies are selected to overcome identified contextual barriers. Other terminologies to describe these methods include health system strengthening interventions and quality improvement strategies.

Implementation evaluation frameworks: Specify implementation outcomes that can be evaluated to determine implementation effectiveness. 35

Implementation outcomes: Defined as ‘the effects of deliberate and purposive actions to implement new treatment practices, and services and are distinct from service and patient outcomes’. 40 Implementation research uses implementation outcomes (eg, acceptability, fidelity, appropriateness) to assess how well implementation has occurred or to provide insights about how this contributes to one’s health status or other important health outcomes. Implementation strategies should be selected to target and improve specific implementation outcomes.

The Expert Recommendations for Implementing Change taxonomy: A taxonomy of implementation strategies that allows researchers to apply a common language when describing how evidence-informed interventions are being implemented. Implementation strategies are selected to overcome identified contextual and behavioural barriers. 37

Effective Practice and Organisation of Care taxonomy: A taxonomy for health system strengthening interventions, that is also similar to the taxonomies for implementation and quality improvement strategies. 39

Implementation-effectiveness hybrid trials

Trials that are designed to evaluate both implementation and effectiveness outcomes, in addition to the influence of context on the effectiveness of the intervention. 88

Literature reviews

A review of the literature is required to identify and understand the mechanisms behind (ie, theory) how contextual barriers and enablers influence the ability to effectively deliver the evidence-informed practice. 76

Reporting guidelines for implementation research

Template for Intervention Description and Replication (TIDieR) checklist: To help improve the quality of descriptions of interventions and therefore their replicability, a group of experts used the Delphi process to develop the TIDieR checklist. 89 90 It is recommended that researchers use this checklist to help improve the quality and reporting of implementation research for global health.

Getting messier with TIDieR: another checklist has also been developed that helps to address gaps the TIDieR checklist for research conducted outside of trials, such as implementation research. The additional items included in this framework include factors such as how well contextual factors influenced intervention delivery.

Phases of implementation research

Ideally, implementation research involves four phases, including: (1) preimplementation; (2) piloting; (3) implementation and evaluation; and (4) postimplementation/dissemination. The core components and methods of implementation research are applied repeatedly throughout the different phases of implementation.

The preimplementation phase is a critical phase that identifies the overall aim of the study and the main theoretical approach and subsequent methodology. 26 It is also useful at this stage to identify specific objectives that may indicate an additional theory-based approach is required. Key to this phase of research is engaging with stakeholders who are a part of the public health system to ensure that the research objectives address the needs and priorities of the local population. This helps to embed the research programme within the existing health system from the outset. 5 33 This can help to ensure local ownership of the research and, therefore, enhance the longer-term sustainability of implementation efforts. 5 33 This phase of research also requires involving stakeholders to conduct a careful assessment of the local context to understand and address contextual and behavioural barriers and/or enablers to implement evidence-informed practice. 26

At the end of the preimplementation phase, a diverse group of stakeholders meet to review the findings, select an initial set of implementation strategies, and develop an initial programme theory (based on the theoretical approach taken) that details the causal processes of how the implementation strategies are expected to achieve the desired outcomes. This process can help to ensure appropriate methods are selected and relevant information is collected throughout the implementation and evaluation phase of research. Finally, conducting an evaluation of costs associated with the implementation and scale-up of the intervention at this stage is important, among other things to secure buy-in from policy-makers. 34

The piloting phase implements and evaluates the set of implementation strategies selected to deliver the evidence-informed practice to ensure it is behaving as intended in a limited number of pilot sites. Specifically, the theoretical approaches adopted will be used to drive the appropriate methods to monitor the effectiveness of implementation strategies in overcoming the contextual determinants they were selected to address. Based on these findings, participatory approaches, such as involving stakeholders in a Theory of Change (ToC) workshop and/or focus group discussions, can be used to adapt the implementation strategies and associated programme theory.

After adjusting the initial programme theory, the implementation and evaluation phase begins an iterative process of evaluating and/or understanding the effectiveness of the set of selected implementation strategies and associated evidence-informed care, on relevant implementation and clinical outcomes. It is paramount at this stage to document and monitor the influence of context on the effectiveness of the implementation strategies on implementation outcomes. All of this is done ensuring the continual engagement of stakeholders and embedding the research into existing health systems, as initiated in the preimplementation phase of the research. For example, conducting regular feedback meetings with health service managers and practitioners to provide updates on implementation strategies and hear their comments on this process is vital.

Lastly, the postimplementation/dissemination phase involves consolidating the engagement activities with stakeholders and users that have been ongoing throughout the earlier stages and together implementing a knowledge exchange, engagement and dissemination plan.

Although we have recommended that implementation research involves four phases, in practice researchers may find themselves in situations where not all of these stages are feasible to design and deliver prospectively; hence some retrospective application of theories and methods (described below) may be necessary.

Theoretical and methodological approaches to implementation research

Implementation science uses a combination of specialist theories, models, and frameworks to evaluate the effectiveness of implementation strategies and other methods in implementing evidence-informed care on implementation outcomes. 35 Implementation science also seeks to understand how context influences the effectiveness of implementation strategies on implementation outcomes and how these dynamic changes throughout the implementation process. In what follows, we describe three key theoretical approaches to implementation science.

Determinant frameworks

Implementation science determinant frameworks offer a theoretical approach to implementation research developed to identify and account for specific contextual barriers and enablers that influence the implementation of evidence-informed practice. 35 Put simply, these frameworks are designed to answer the question: what determines the success or failure of an implementation effort? Many of these frameworks were designed by synthesising results from empirical studies of barriers and enablers to implementation success, while others were developed using existing frameworks and theories. 35 Although an investigator may take a positivist approach to use the frameworks to identify determinants, the frameworks can also be operationalised in a way more aligned with critical realism. As an example, these frameworks can be used to theorise how the identified barriers and enablers bring about change by addressing interactions across multiple domains at microlevel, mesolevel and macrolevel. 27

Applying determinant frameworks to data-collection tools (eg, focus group discussions, interviews) in the preimplementation phase of research provides an evidence-based methodology to identify and address contextual and behavioural barriers and enablers that might otherwise have been missed. Identifying determinants in this phase of research can inform the selection of implementation strategies to support delivery of the evidence-informed practice.

During the implementation and evaluation phase, determinant frameworks are also used to guide the development of data collection tools that are used to monitor and understand the influence of context on the implementation strategies in delivering the evidence-informed practice. 36 Determinant frameworks are particularly useful in explaining variation in implementation outcomes across studies. 36

Determinant frameworks typically address five main categories of factors that can influence implementation efforts: characteristics of the evidence-informed intervention that is being implemented (eg, adaptability and complexity); the external setting (eg, sociocultural, epidemiological and socioeconomic determinants); the internal setting (eg, healthcare facility); characteristics of the users and providers; and processes of implementation. Table 1 provides examples of how different determinant frameworks can be used to identify contextual determinants that influence the delivery of evidence-based care that are relevant to an LMIC setting. The frameworks included in table 1 address characteristics of determinants that are particularly relevant in LMICs, including the external context (eg, lack of resources), characteristics of the healthcare facilities (ability to provide people-centred care and lack of supplies to effectively implement the interventions), and characteristics of the users of the healthcare facilities (eg, lack of knowledge about where or when to seek care, lack of empowerment to seek care) as well as the providers (eg, lack of training in how to provide people-centred care).

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Examples of how implementation science determinant frameworks can be applied to identify contextual determinants that influence the implementation of evidence-based care

Implementation strategies

We have noted some confusion in the literature with the terminology used for implementation strategies, where in some instances they are referred to as ‘components of a complex intervention’. In implementation science terms, implementation strategies are separate from any health-focused intervention. Essentially, implementation strategies are a tool used within the discipline: they are the implementation approaches that deliver and improve the uptake of an evidence-informed practice. 35

Implementation strategies are selected to overcome identified contextual barriers (which a determinant framework and a programme theory would have identified) to deliver the evidence-informed practices identified in the preimplementation phase of research using tools such as determinant frameworks. 4 As an example, a common implementation strategy applied in implementation research for global health is task sharing using community health workers to deliver the evidence-informed care. When selecting different implementation strategies, it is useful for researchers, jointly with study stakeholders, to theorise how they expect the strategies to play out once implemented within different contexts. This theorising of context and its relationship with the intervention will be critical for informing how implementation strategies in the delivery of the evidence-informed practice are subsequently evaluated and monitored over time.

There is inconsistent labelling of implementation strategies used for implementation research. 37 This has resulted in difficulty in synthesising results across studies to understand the effectiveness of specific methods in a given context. 38 However, methods are available that can help with selecting and labelling relevant implementation strategies, including a tool developed by The Expert Recommendations for Implementing Change (ERIC) study. 37 The ERIC tool offers a compilation of implementation strategies that are known to be effective in addressing specific contextual barriers and enablers. Further, the Effective Practice and Organisation of Care taxonomy is a compilation of health system strengthening interventions. 37 39 Both taxonomies share the same objective of using a common language to label the methods (ie, implementation strategies or health system strengthening interventions) used to deliver the evidence-informed practice that will help with the generalisation of findings from one research programme to another. Table 2 describes implementation strategies commonly used for implementation research in global health.

Examples of implementation strategies (health system strengthening interventions) for implementation research in global health

Evaluation frameworks

Evaluating the effectiveness of a novel treatment requires the selection of appropriate clinical outcomes. Similarly, implementation strategies need to be evaluated to assess their effectiveness, for which appropriate outcomes need to be selected. To achieve this, implementation outcomes are selected that are supported by a social science theory, or implementation science theories or frameworks. 35 Evaluation frameworks are a tool that can be applied to assist researchers in selecting appropriate implementation outcomes to evaluate for a particular set of implementation strategies. 35

Initially, determinant frameworks are used to identify barriers and enablers to implementation, followed by selecting implementation strategies to overcome identified barriers. Implementation outcomes should be selected that capture the effectiveness of implementation strategies and contextual or behavioural determinants. As an example, if there is a lack of healthcare workers to deliver a previously evaluated care intervention (determinant) then approaches such as task shifting with community healthcare workers are used to address this issue (implementation strategies—otherwise known as the ‘intervention’). A relevant implementation outcome would therefore be coverage (ie, the proportion of the population receiving care prior to implementation compared with after implementation). Proctor et al 40 have published a taxonomy of implementation outcomes that offers a list of conceptually distinct outcomes for evaluation—including acceptability, adoption, appropriateness, feasibility, fidelity, implementation cost, penetration and sustainability. There are other useful evaluation frameworks available to help select implementation outcomes, including the reach, effectiveness, acceptability, implementation and maintenance framework. 41

It is important to evaluate a combination of relevant implementation outcomes at multiple time points throughout the implementation process. 40 It is also imperative to monitor and theorise about the influence of context on the effectiveness of the implementation strategies on implementation outcomes. Determinant frameworks can be used to guide data collection tools to assess how context influences specific implementation strategies and associated implementation outcomes. Table 3 provides examples of how implementation outcomes have been applied to implementation research in LMICs.

Examples of how implementation outcomes have been applied to implementation research to evaluate specific implementation strategies in global health

Implementation theories

Whereas social science theories explain the causal mechanisms between certain phenomena and an outcome, 32 implementation theories are a theoretical approach typically developed or adapted by researchers to specifically understand or explain certain aspects of implementation. 35 Researchers select a implementation theory to analyse the mechanisms of the implementation process that can help to explain why implementation efforts are successful (or not). How a researcher views the social world shapes how the implementation theory is applied. Typically, implementation theory emerges from different knowledge paradigms, some of which may draw on wider social theories of behaviour or incorporate wider social forces.

In the preimplementation phase, implementation theories can be applied not only to identify determinants to implementation, but also to understand the mechanisms by which the implementation strategies will deliver the evidence-informed practice. Moreover, throughout the implementation and evaluation phase, a mixed-methods design, guided by an implementation theory can be used to understand barriers/enablers to implementation as well the mechanisms by which the implementation strategies work, for whom and how. An example of how an implementation science theory has been applied in practice can be found in online supplemental file A, table 1 . Broad description of several implementation theories is offered by Nilsen. 35

Supplemental material

Realist evaluations.

Realist evaluations are theory-based evaluations based on realist philosophy 42 that are gaining popularity in global health. 43 44 Realist philosophy was designed to sit between the positivist and relativist approaches. Realism assumes that nothing works for everyone everywhere and that the effects of interventions are largely determined by context. Therefore, a realist evaluation can help to understand and evaluate the complexity surrounding implementation research by conceptualising what works, for whom and how. 42 Evaluating this complexity is useful in developing an understanding of how an intervention can be adapted to a new context and scaled up. 45

Initially, a programme theory is developed (based on previous research and knowledge) that explains how the intervention is expected to produce the intended outcomes and in what contexts this can be achieved. 42 The programme theory is then revisited and modified throughout the evaluation to arrive at a final theory. This approach is otherwise known as the Context-Mechanisms-Outcomes configuration. Here, context refers to the conditions in which an intervention is introduced (sociocultural, political, socioeconomic, ethical, epidemiological) which can occur at the microlevel, mesolevel and macrolevel. 46 A mechanism refers to how social actors reason and react to the available resources (ie, the intervention), to bring about change in a specific context. 47 Once mechanisms are activated in a specific context, they can be identified and measured through their unexpected or expected outcomes. 48 When applied to implementation research, we envisage context triggering the mechanisms due to the introduction of the implementation strategy(ies) embedded within a broader programme. An example of applying realist theory to implementation research is a study that evaluated how different contexts influenced the mechanisms responsible for divergent outcomes following the implementation of a user fee exemption policy for caesarean section at two hospitals in Benin ( online supplemental file A, table 2 ). 49

Participatory approaches within implementation research

Participatory research is underpinned by a particular view of the social world that interventions/implementation strategies are socially constructed through interactions. Indeed, participatory research draws on the paradigms of critical theory and constructivism, common to the social sciences. 50 Participatory methods involve stakeholders, including research participants (ie, patients and their carers), are essential to ensure that the voices of ‘experts by experience’ are heard and to gain local buy-in and ensure acceptability and sustainability for the longer term. 51 52 Participatory research has been defined as the process of producing new knowledge by ‘systematic inquiry, with the collaboration of those affected by the issue being studied, for the purposes of education and taking action or effecting social change’. 53

Although there are different applications of participatory research, they all share the common objective of improving social and economic conditions to effect change and to reduce the distrust of the people being studied. 53 Participatory research methods are particularly relevant to disadvantaged communities and, therefore, some communities within resource-poor settings within LMICs, which are often excluded from the planning and implementation of health interventions. The inclusion of a variety of stakeholders integral to the delivery and uptake of interventions supports the development of an intervention’s theoretical foundation unencumbered by a positivist framework. 54 These methods also support self-empowerment by removing barriers and promoting environments within which communities can increase their capacity to identify and solve their own problems. 55

Participatory action research

Participatory action research (PAR) is an example of such methodology that represents a broad family of research approaches that emphasise social change, transformation. It is a self-reflective process, involving both researchers and participants, which undertakes action based on the local context and aims to empower participants to improve health and reduce health inequities. 50 PAR is a cyclical process where action is achieved through participants identifying a problem, collecting and analysing relevant information, developing an action and reflecting on the action. The process of PAR is expected to be empowering and lead to people having increased control over their lives and communities. 50 Similar to PAR is PLA, a form of action research that is grounded in the participation of people in a local community while being facilitated through local community members instead of an external researcher. PLA enables and empowers people through problem-solving through a process of sharing, learning, action and reflection. 56

Human-centred design

Human-centred design is another participatory research approach, which allows for the meaningful engagement of key stakeholders, including the intervention’s target population, in all implementation research phases. It comprises five stages of intervention development and evaluation: (1) Empathise—identification of stakeholder perceptions, needs, goals and priorities; (2) Define—agreement of a priority challenge(s) to be addressed; (3) Ideate—development of potential interventions; (4) Prototype—refinement of interventions and (5) Test—evaluation and further refinement. Although initially used within the private sector, its potential utility within the field of global health has been identified through recent research. 57 The use of prototypes to refine an intervention and implementation process prior to pilot and trial evaluation is a key feature as this allows for initial ‘bottom-up’ identification of potential barriers to success and unintended consequences prior to large-scale research investment.

Participatory ToC to develop a programme theory

Participatory ToC methodology is a form of participatory research, which involves key stakeholders and aims to improve the understanding of how and why a programme works through the development of a programme theory. 58 Programme theories are increasingly being used with implementation research for global health to describe how an interventions intends to bring about change and the relationships between inputs, outputs and outcomes, unintended consequences and basic assumptions. 59 The expectations of how a programme or intervention might work as articulated in a programme theory can subsequently be evaluated through a study design that includes process and outcome measures (eg, a process evaluation or hybrid trial).

The ToC process can support the development of shared goals among stakeholders and promote accountability. The initial programme theory can be strengthened by incorporating mid-range theories such as a realist evaluation to help explain causal mechanisms that are particularly relevant to the intervention. 60 Strengthening the programme theory can also be achieved by incorporating key implementation outcomes and contextual determinants selected from different implementation science frameworks. Indeed, there are methods available that can be used to help to merge implementation science methods into ToC workshops. 61 A recommended approach to developing a ToC programme theory or map involves working with stakeholders (including people with lived experience of ill health and their carers) to reach agreement as to the intended impact of an intervention; then working backwards to determine intermediate and short-term outcomes necessary to achieve the desired impact. 62 Ideally, ToC programme theories are developed and refined throughout the process of implementation.

Table 4 provides examples of participatory research. As an example, ToC workshops were used to develop a programme theory for the PRIME in Ethiopia, India, Nepal, South Africa and Uganda. 21 22 This programme theory described the hypothesised causal pathway from entry into each district site to achieving changes in treatment coverage for people living with mental, neurological and substance use disorders in that district.

Examples of participatory methods in implementation research

Engagement and knowledge exchange activities

A key outcome of implementation research is to ensure scalable, sustainable change from the original research. Ensuring implementation research is participatory, by creating opportunities involving engagement with key stakeholders, is key to achieving that change. Several other disciplines have described such processes, including ‘knowledge mobilisation’, 63 the use of ‘embedded researchers’, 64 ‘co-production’ methods between researchers and practitioners, 65 as well as studies examining how societal impact stems from research. 63 66 67 Generally these are intended to create opportunities for stakeholders to understand, adopt and sustain outcomes from research, or create opportunities for ‘productive interactions’. 68 These activities can be parts of intervention design itself (ie, in codesign or coproduction activities), and at other times they are activities occurring in parallel to the research and considered to be activities which complement the research process in facilitating its adoption and scale-up. Within the context of activities that support scale-up and adoption of research to support implementation activities, there has been extensive research conducted into how to overcome barriers in bringing research evidence closer to policy-making. 69 70 One approach developed to specifically address this barrier is the ‘policy lab’ approach. 71 Envisaged as a process for engaging evidence and policy-making and not an isolated activity, these labs serve to build a coalition through participation of diverse communities, work on the language and presentation of evidence, and engage policy-makers early to respond when windows of opportunity for changing policy emerge. 71

Further components of implementation research, beyond the scope of this guide, are specialist topic areas, such as economic evaluations, literature reviews and implementation-effectiveness hybrid study designs. We have offered an overview of these in online supplemental material B for the interested readers.

Conclusions

This guide is intended to address gaps not covered by existing publications or guidance, regarding how best to set up and conduct high-quality implementation research in global health settings. Given implementation research is a relatively novel and niche field that involves expertise of complex methodologies from specialist disciplines it is unsurprising it is still a challenge to conduct and report it consistently across studies. To alleviate the ambiguity surrounding theories, methodologies and tools applied to implementation research, we have described how different knowledge paradigms, with distinctive perspectives on reality, offer contributions that are essential for high-quality implementation research. We have provided guidance through an overview of core methods and approaches offered through the divergent knowledge paradigms and how these can be applied at different phases of research. To help conceptualise how the different approaches to implementation research are applied, figure 1 depicts core components and essential methodologies that we recommend global health researchers can apply at the different phases of their research.

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Methods and core components recommended for the different phases of implementation research. EPOC, Effective Practice and Organisation of Care; ERIC, Expert Recommendations for Implementing Change; RE-AIM, reach, effectiveness, acceptability, implementation and maintenance.

The expertise from specialist disciplines required for implementation research also emphasises the need for extensive capacity building in both high-income countries, and LMICs. Further work is also needed to ensure the approaches used for implementation research are adapted and new ones developed to suit the different contexts in LMICs and that, importantly, this is driven by actors within those countries (ie, the global South). Funders such as the National Institute of Health Research in England increasingly emphasise the importance of not only capacity building, but also community engagement and involvement as core criteria for funding. 72

High-quality evidence-informed implementation research in LMICs will be key to achieving Universal Health Coverage (UHC) with high-quality care. There are multiple reasons that help to explain the lack of high-quality implementation research in LMICs. Importantly, one cannot overlook the issues with accountability, power relations and divergent interests mainly driven by the global north, strongly informed by colonialism. 15 73 As an example, some donors struggle to align their approaches and priorities with LMIC needs and priorities and are more interested in funding programmes with short-term outcomes and known impacts. 15 This undermines programmes such as health system strengthening and implementation research that have longer term impacts, reliant on local buy-in. Improving our ability to deliver high-quality implementation research will require more effort to decolonise global health. Of particular relevance is the understanding that implementation research must be driven by communities in the global south, and non-Western researchers, as they hold the knowledge surrounding the local context and the needs and the priorities of the population. To do this successfully, a concurrent emphasis on capacity-building in within LMIC, as discussed above, is essential with leadership of research initiated and taken more commonly by local actors.

We hope this guide can help to build capacity for global health actors in both LMIC and high-income countries. We also hope our guide can help donors understand the requirements of high-quality implementation research, which may need longer-term investments with uncertain outcomes. It is our aspiration that facilitating widespread and shared understanding of the theoretical and methodological approaches needed to conduct effective, robust implementation studies in LMICs can help bring to scale life-saving interventions and achieve UHC goals.

Ethics statements

Patient consent for publication.

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• Data supplement 1
• Data supplement 2

Handling editor Seye Abimbola

Twitter @nadineseward, @sabziehin

CH, SH-K, CL, JM and TTS contributed equally.

Contributors NSew is the guarantor and responsible for the overall content of the paper; NSew drafted the paper NSev conceptualised the idea for the paper; NSew and NSev offered insights into implementation science. JM offered details around process evaluations and context. SH-K offered details surrounding policy research TTS and NSev provided details to participatory research. CH, NSew, TTS, RS, GT, RV, RA and CL provided details of implementation research in Global Health. JM, SH-K, CH, RS, GT and NSev reviewed several drafts of the manuscript;

Funding NSew, CH, Prince and NSev are funded by the National Institute of Health Research (NIHR) Global Health Research Unit on Health System Strengthening in Sub-Saharan Africa, King’s College London (GHRU 16/136/54) using UK aid from the UK Government to support global health research. Sevdalis and Thornicroft’s research is further supported by the NIHR Applied Research Collaboration South London at King’s College Hospital NHS Foundation Trust, and by the ASPIRES research programme in LMICs (Antibiotic use across Surgical Pathways-Investigating, Redesigning and Evaluating Systems), funded by the Economic and Social Research Council. Sevdalis and Thornicroft are members of King’s Improvement Science, which offers cofunding to the NIHR ARC South London and is funded by King’s Health Partners (Guy’s and St Thomas’ NHS Foundation Trust, King’s College Hospital NHS Foundation Trust, King’s College London and South London and Maudsley NHS Foundation Trust) and Guy’s and St Thomas’ Foundation. Hanlon additionally receives funding support from AMARI as part of the DELTAS Africa Initiative (DEL-15-01).

Disclaimer The views expressed here are not necessarily those of the NIHR or the Department of Health and Social Care, the NHS, the ESRC, AMARI or the DELTAS Africa Initiative.

Competing interests NSew is the director of the London Safety and Training Solutions, which offers training in patient safety, implementation solutions and human factors to healthcare organisations and the pharmaceutical industry. The other authors have no conflicts of interest to declare.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Developing a theory-informed complex intervention to improve nurse-patient therapeutic engagement employing Experience-based Co-design and the Behaviour Change Wheel: an acute mental health ward case study

Affiliations.

• 1 Florence Nightingale Faculty of Nursing, Midwifery & Palliative Care, King's College London, London, UK [email protected].
• 2 Florence Nightingale Faculty of Nursing, Midwifery & Palliative Care, King's College London, London, UK.
• 3 Independent Service User and Carer Group, London, UK.
• 4 FOR WOMEN CIC, London, UK.
• PMID: 33986066
• PMCID: PMC8126294
• DOI: 10.1136/bmjopen-2020-047114

Objectives: Our objectives were threefold: (1) describe a collaborative, theoretically driven approach to co-designing complex interventions; (2) demonstrate the implementation of this approach to share learning with others; and (3) develop a toolkit to enhance therapeutic engagement on acute mental health wards.

Design and participants: We describe a theory-driven approach to co-designing an intervention by adapting and integrating Experience-based Co-design (EBCD) with the Behaviour Change Wheel (BCW). Our case study was informed by the results of a systematic integrative review and guided by this integrated approach. We undertook 80 hours of non-participant observations, and semistructured interviews with 14 service users (7 of which were filmed), 2 carers and 12 clinicians from the same acute ward. The facilitated intervention co-design process involved two feedback workshops, one joint co-design workshop and seven small co-design team meetings. Data analysis comprised the identification of touchpoints and use of the BCW and behaviour change technique taxonomy to inform intervention development.

Setting: This study was conducted over 12 months at an acute mental health organisation in England.

Results: The co-designed Let's Talk toolkit addressed four joint service user/clinician priorities for change: (1) improve communication with withdrawn people; (2) nurses to help service users help themselves; (3) nurses to feel confident when engaging with service users; (4) improving team relations and ward culture. Intervention functions included training, education, enablement, coercion and persuasion; 14 behaviour change techniques supported these functions. We detail how we implemented our integrated co-design-behaviour change approach with service users, carers and clinicians to develop a toolkit to improve nurse-patient therapeutic engagement.

Conclusions: Our theory-driven approach enhanced both EBCD and the BCW. It introduces a robust theoretical approach to guide intervention development within the co-design process and sets out how to meaningfully involve service users and other stakeholders when designing and implementing complex interventions.

Keywords: adult psychiatry; mental health; qualitative research; quality in health care.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Publication types

• Research Support, Non-U.S. Gov't
• Behavior Therapy
• Communication
• Mental Health*

• Methodology
• Open access
• Published: 25 January 2023

A theory-informed, rapid cycle approach to identifying and adapting strategies to promote sustainability: optimizing depression treatment in primary care clinics seeking to sustain collaborative care (The Transform DepCare Study)

• Nathalie Moise   ORCID: orcid.org/0000-0002-5660-5573 1 ,
• Alejandra Paniagua-Avila 2 ,
• Jennifer Mizhquiri Barbecho 1 ,
• Luis Blanco 1 ,
• Katherine Dauber-Decker 3 ,
• Samantha Simantiris 1 ,
• Martin McElhiney 4 ,
• Maria Serafini 1 ,
• Darlene Straussman 1 ,
• Sapana R. Patel 4 , 5 ,
• Siqin Ye 1 &
• Andrea T. Duran 1  

Implementation Science Communications volume  4 , Article number:  10 ( 2023 ) Cite this article

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Few real-world examples exist of how best to select and adapt implementation strategies that promote sustainability. We used a collaborative care (CC) use case to describe a novel, theory-informed, stakeholder engaged process for operationalizing strategies for sustainability using a behavioral lens.

Informed by the Dynamic Sustainability Framework, we applied the Behaviour Change Wheel to our prior mixed methods to identify key sustainability behaviors and determinants of sustainability before specifying corresponding intervention functions, behavior change techniques, and implementation strategies that would be acceptable, equitable and promote key tenets of sustainability (i.e., continued improvement, education). Drawing on user-centered design principles, we enlisted 22 national and local stakeholders to operationalize and adapt (e.g., content, functionality, workflow) a multi-level, multi-component implementation strategy to maximally target behavioral and contextual determinants of sustainability.

After reviewing the long-term impact of early implementation strategies (i.e., external technical support, quality monitoring, and reimbursement), we identified ongoing care manager CC delivery, provider treatment optimization, and patient enrollment as key sustainability behaviors. The most acceptable, equitable, and feasible intervention functions that would facilitate ongoing improvement included environmental restructuring, education, training, modeling, persuasion, and enablement. We determined that a waiting room delivered shared decision-making and psychoeducation patient tool (DepCare), the results of which are delivered to providers, as well as ongoing problem-solving meetings/local technical assistance with care managers would be the most acceptable and equitable multi-level strategy in diverse settings seeking to sustain CC programs. Key adaptations in response to dynamic contextual factors included expanding the DepCare tool to incorporate anxiety/suicide screening, triage support, multi-modal delivery, and patient activation (vs. shared decision making) ( patient ); pairing summary reports with decisional support and yearly onboarding/motivational educational videos ( provider ); incorporating behavioral health providers into problem-solving meetings and shifting from billing support to quality improvement and triage ( system ).

We provide a roadmap for designing behavioral theory-informed, implementation strategies that promote sustainability and employing user-centered design principles to adapt strategies to changing mental health landscapes.

Peer Review reports

Contributions to the literature

This study provides a novel roadmap for leveraging behavior and implementation science as well as user-centered design principles to design and rapidly adapt theory-informed strategies for sustainability.

In addition to external support, sustaining collaborative care may require ongoing patient activation, provider decisional support/motivation, and local technical assistance/problem-solving.

User-centered design principles may help operationalize the need for continuous improvement/adaptation in the sustainability phase.

More than 100 randomized trials demonstrate that collaborative care (CC), a team-based approach to managing depression in primary care, improves access to mental healthcare; improves depression, quality of life, and productivity; and is cost-effective compared to usual care by primary care providers (PCPs) alone [ 1 , 2 , 3 ]. CC is also one of the few evidence-based interventions shown to reduce health disparities [ 4 ], with minorities experiencing better improvements in depressive symptoms, physical and/or mental functioning, and unmet treatment needs [ 5 ] as well as receipt of preferred depression treatment [ 6 ]; and reduced perceived racial discrimination [ 7 ].

CC expanded exponentially across the USA, facilitated by Patient Centered Medical Home initiatives, Accountable Care Organizations, and new reimbursement approaches as part of primary care redesign [ 8 ] and through the Centers for Medicare and Medicaid Services [ 9 ]. Several recent initiatives suggest that implementation strategies such as providing flexible funding for staff, training, monitoring, quality improvement, and external facilitation improve CC implementation [ 10 , 11 , 12 , 13 ]. Unutzer et al. (2020) recently found that external support is essential to CC implementation and real-world effectiveness [ 14 ]. However, few studies focus on how best to select, refine and adapt strategies for CC sustainability, which has been defined as “the continued use of program components and activities for the continued achievement of desirable program and population outcomes” [ 15 ]. Here, we defined CC sustainability as continued provider CC referral/treatment optimization, patient CC enrollment/attendance, and care manager delivery of registry-based, treat to target depression treatment with population-based psychiatry consultation.

In 2015, building upon years of experience implementing CC for depression, the New York State (NYS) Department of Health (DOH) and NYS Office of Mental Health (OMH) successfully implemented CC in diverse, low socioeconomic status settings using a strategy consisting of technical assistance, fee-for-quality reimbursement, and ongoing training/quality monitoring; the program has reached more than 300 primary care clinics across the state [ 16 ]. In a mixed-methods study of 32 clinics about 4 or more years post-implementation, we demonstrated that having a full-time depression care manager dedicated to CC and early success (i.e., average improvements in depressive symptoms of 50% in the initial 2 years of implementation) determined whether a clinic would sustain CC or opt-out [ 17 ]. We found that external technical assistance and financial resources resulted in long-term fidelity and clinical improvement, but that clinics seeking to sustain CC often encountered low patient, staff (e.g., depression care managers), and PCP engagement as well as limited resources (e.g., number of depression care managers), perhaps due to implementation drift (e.g., decay in fidelity to depression screening) and turnover of program champions over time [ 17 ].

The NYS findings suggest that strategies designed for early implementation may not be sufficient for sustainability, particularly in diverse settings with the most to gain from the model. There is a recent focus on sustainability as a dynamic concept, recognizing that the implementation of evidence-based interventions will likely evolve over time, due to complex and changing real-world healthcare settings and systems [ 18 , 19 ]. The Dynamic Sustainability Framework (DSF) argues for the continuous refinement and improvement of interventions during the sustainability phase, through learning and evaluation, problem solving and ongoing adaptations to interventions to enhance fit between interventions, practice settings/contexts and ecological systems over time [ 19 ]. Few guides exist for operationalizing this dynamic process, particularly the additions/revisions to initial implementation strategies that are essential to this process. In addition, the DSF does not explicitly acknowledge the ways in which sustainability often requires sustained behavior change at multiple levels (e.g., continued CC enrollment/attendance by patients). We posit that behavior change theory and user-centered design principles may be helpful tools for operationalizing the dynamic sustainability process.

The NYS DOH/OMH initiative for implementing CC for depression provides a unique, rare opportunity to identify how best to develop, adapt and test strategies for sustainability in real world settings. This paper provides a roadmap for designing and adapting behavioral theory-informed strategies for sustainability, drawing from the DSF, Behaviour Change Wheel (BCW) [ 20 ], Expert Recommendations for Implementing Change (ERIC) [ 21 ], and user-centered design principles [ 22 , 23 , 24 ]. To our knowledge, this is one of the first studies to describe the design of a multi-level, theory-informed, adaptable implementation strategy for settings seeking to sustain CC programs.

Synopsis of our prior work on implementing CC

Based on our prior mixed methods analyses [ 17 ], we determined that NYS OMH’s ongoing implementation and scale-up strategies (i.e., external technical assistance, quality monitoring, reimbursement) optimized CC uptake, quality/fidelity, clinical improvement/psychiatry consultation rates, acceptability, and perceived costs but that referral/enrollment rates (which are directly tied to billing and thus care manager hiring/retention) diminished significantly over time despite stable depression screen positive rates. We surmised that care manager, patient, and provider engagement were key to sustainability, which would require strategies that not only addressed changing local contextual factors (like problem-solving/adaptation) but also promoted ongoing multi-level behavior change.

Informed by the DSF, our development of implementation strategies to enhance CC sustainability consisted of the following phases: (1) a mixed methods approach to specify determinants of and strategies for sustainability based on the multi-step BCW [ 20 ] and ERIC [ 21 ]; and (2) a rapid cycle adaption phase, drawing from user-centered design principles [ 22 , 23 , 24 ], that involved multidisciplinary stakeholders in operationalizing and refining a multi-level implementation strategy for sustainability to maximize fit between the intervention/CC, strategy and context over time (Fig.  1 ).

Roadmap for theory-informed approach to identifying and adapting strategies for sustainability

Theoretical frameworks used to develop implementation strategies that promote CC sustainability

Theoretical underpinnings of our approach centers around the DSF ( process framework ), particularly the need for ongoing optimization, improvement, evaluation/feedback, stakeholder involvement, and organizational learning as well as a strong fit between the program and implementation setting, all of which we argue require sustained behavior change on the parts of multiple stakeholders.

For Phase 1 , we used the BCW (Additional File 1 ), which can be applied to individual behavior (e.g., patient-level smoking cessation) and multi-level (system, provider, patient) behavior change in clinical settings [ 20 ], as well as implementation strategy development [ 25 , 26 ]. The multi-step BCW first requires identifying and specifying a primary behavior and posits that changing behavior requires increasing capability, opportunity, and/or motivation for a behavior (COM-B Model) ( determinant framework ) by removing barriers and/or augmenting facilitators to that target behavior. The BCW involves (1) understanding the behavior, (2) identifying intervention options, and (3) identifying related content and implementation options [ 20 ]. Informed by the DSF, we sought to apply the BCW to understand behaviors integral to sustainability while identifying implementation strategies informed by both behavioral theory and dynamic sustainability tenets. We further characterized strategies according to ERIC [ 21 ] and targeted Proctor’s implementation outcome [ 27 ] ( outcome framework ) in order to facilitate standardized reporting across implementation science studies [ 21 , 28 ].

For Phase 2 , we aimed to operationalize a key tenet of DSF (i.e., adaptation to maximize the fit between CC, implementation strategies, and context over time) by using stakeholder engaged, rapid cycle process . We leveraged user-centered design principles, an approach to product development that grounds the process in data collected from end users at the individual and settings level; this process draws from a clear identification of the end users and their needs, prototyping/rapid iteration, simplification of existing procedures and exploiting natural constraints [ 22 , 24 , 29 ]. We specified behavioral (COM-B model) and contextual (DSF) factors driving adaptations. Here, we describe iterations made by the advisory board, intervention development team, and creative team and will describe patient-level usability testing, cognitive interviews, and heuristics evaluation separately (Fig.  2 ) [ 30 ].

Rapid cycle, stakeholder engaged adaption of strategies for sustainability

We developed the multi-level implementation strategy for sustaining CC in a large academic primary care clinic in the Ambulatory Care Network (ACN) at New York Presbyterian Hospital in upper Manhattan serving low socioeconomic and diverse communities of Washington Heights, Inwood, Harlem, and the Southwest Bronx. Implementation is currently occurring in separate demographically similar ACN clinics in the sustainability phase of the NYS OMH CC Initiative (i.e., receiving external technical assistance/quality monitoring and fee-for-quality reimbursement for Medicaid patients) as well as integrated care settings not receiving external implementation strategies.

Phase 1: specify multi-level determinants of and strategies for CC sustainability

Step 1 methods: use mixed methods to understand multi-level sustainability behaviors and determinants.

Overall, our work was informed by three previously published mixed-methods studies on sustainability of CC, including (1) descriptive analyses of CC sustainability including long-term fidelity, improvement, enrollment, caseloads, and psychiatric consultation rates as well as 30 semi-structured interviews with PCPs, care managers, psychiatrists and administrators at clinics that sustained or opted out of CC across in NYS [ 17 ]; (2) three focus groups and four one-on-one interviews with historically marginalized patients ( n = 12) referred to CC programs in the sustainability phase (both enrollees and no-shows) [ 31 ]; and (3) 10 interviews with CC experts from diverse settings across the USA focused on determinants of patient engagement in mature (i.e., at least 1 year after implementation initiation) CC programs [ 32 ].

First, we defined the problem in behavioral terms and selected and specified target behaviors at every level (patient, provider, and system). Drawing from our previously published qualitative interviews with key stakeholders on barriers to CC sustainability (above) [ 17 , 31 , 32 ], two authors (NM, MAPA) classified themes highlighted in the publications by level (patient-, provider- or system-level) and COM-B construct. For example, we deemed the ‘lack of PCP time and competing demands’ theme to be a provider-level “opportunity” barrier. There were no major disagreements. We resolved any differences by consensus discussion, with researchers referring to original manuscripts to reassess context of the codes when categorizations were unclear.

Step 2 methods: identify intervention functions, behavior change techniques and strategies that promote sustainability

After coding the COM-B categories, our clinician implementation scientists on our research team (NM, MAPA) followed the BCW to map the above COM-B barriers to corresponding intervention functions (i.e., nine broad categories by which an intervention can change behavior, e.g., education, training, persuasion), policy categories (i.e., seven policies representing types of decisions made by authorities that help to support and enact interventions), and behavior change techniques (i.e., a standardized language for describing the active ingredients in behavior change interventions via which intervention functions and policy categories are delivered (Additional File 2 ). As several interventions, policies, and behavior change techniques may map to each COM-B construct, the BCW recommends applying the affordability, practicality, effectiveness, acceptability, side effects, and equity (APEASE) criteria to narrow-down intervention components to those that are affordable (within an acceptable budget for patients, mental health and primary care providers, and administrators after/not withstanding development costs), practical (can be delivered as designed), efficacious (effectiveness and cost-effective related to designed objectives in real world context), acceptable (judged appropriate by relevant stakeholders), safe (no unwanted side effects), and equitable (does not increase disparities) [ 20 ].

Informed by DSF, we selected intervention functions, policy categories, and behavior change techniques that met all APEASE criteria (agreed upon by both coders) in the sustainability phase . We then reviewed and prioritized implementation components that aligned with core DSF tenets, particularly those not otherwise delivered within ongoing external implementation strategies. For example, incentivization (or the expectation of reward for patients enrolling in CC) was an intervention function that would be acceptable, effective, and equitable but did not align with continuous improvement/problem-solving DSF tenets nor was it affordable in the sustainability phase (i.e., OMH already provided fiscal reimbursement to care managers in sustainability phase and OMH/local settings would be unable to also incentivize patients). As another example, several enablement-related behavior change techniques met all APEASE criteria, but problem-solving particularly adhered to DSF principles. Differences were resolved through consensus discussion.

Given calls for shared language and conceptual clarity around implementation strategies, we also mapped behavior change techniques to implementation strategies from the ERIC project [ 21 , 33 ], again prioritizing those strategies that met key DSF tenets. While all strategies met all APEASE criteria (i.e., would ongoing provider education be acceptable to stakeholders?), we also specified the dose, mode of delivery and predominant Proctor implementation outcome targeted (would this educational strategy improve CC acceptability?) for each strategy component [ 28 ].

Phase 2: rapid cycle adaptation of an implementation strategy to promote sustainability

Step 3 methods: engage multi-disciplinary stakeholders and end-users in rapid cycle, iterative, user-centered design process to operationalize and refine strategy components.

After initial implementation strategy selection described above, we conducted sequential group and one-on-one meetings with multidisciplinary teams of stakeholders (Fig.  2 ) from January 2018 to May 2021 (~ 30 months to account for COVID-19 disruptions): (1) a creative team led by our creative director of developers and experts in user experience who create journey maps of patient and system/provider experiences with CC/mental health optimization and operationalize/develop patient and PCP facing materials; (2) an intervention development team of historically marginalized patient stakeholders, care managers, and PCP stakeholders who ensured strategies fit to rapidly shifting contextual factors in diverse, low socioeconomic settings; (3) an advisory board of experts in behavior change and patient activation/experience to refine the strategy; and finally, (4) which will be described separately, depression care managers, PCPs and historically marginalized patients for user testing patient-facing interventions to maximize the usability, safety, feasibility, and sustainability of our multi-level strategy.

For intervention team stakeholders, we used snowball sampling to identify CC champions in the ACN clinics. We identified advisory board members from literature reviews on behavioral, user experience and shared decision-making experts. Stakeholders were invited by email to serve in an advisory role for our study. While the cycle initiated with creative team members and ended with patient/provider user testing, intervention development, and advisory board meetings were in no apparent order; team members could meet multiple times in a row (as a group or one-on-one) based on need/mandate/availability. Meetings were held in-person with remote stakeholders calling in via teleconference prior to COVID-19 and via zoom/video calls post-COVID-19. Patients and providers who underwent in-person user-testing (described separately) were consented and the protocol was approved by the Columbia University Irving Medical Center Institutional Review Board.

The core team of staff and implementation science researchers recorded and transcribed meeting notes, identified themes, and arrived at consensus to guide strategy prototype refinements when technically and logistically feasible. We rapidly reviewed meeting notes for usability themes (i.e., content, usability, usefulness, understandability/functionality, visibility, workflow, navigation, content) based on key user-centered design principles [ 34 , 35 , 36 ]. We specified whether strategy adaptations were done to maximally target behavioral determinants of sustainability (informed by the BCW/COM-B Model [i.e., motivation , opportunity, and/or capability ]) and/or contextual factors (informed by DSF [i.e., ecologic system : other practice settings, policy, regulation, population characteristics; practice setting : staffing, info systems, organizational culture, training, supervision]). Because strategy adaptations are often in response to intervention adaptations, we also tracked adaptations to the CC program itself overtime based on input from key stakeholders during meetings (again specifying driving behavioral and contextual factors driving CC adaptations).

Step 4 methods: map strategy materials back to behavior change techniques and finalize strategy components

The creative team met after each cycle to refine educational materials before presenting prototypes to the advisory board and intervention team members for feedback, consensus, and adaptation. We conducted three iterative adaptation cycles. At the end of the last cycle, we ensured the mode of delivery/behavior change techniques fit the contextual considerations of the telemedicine/post-COVID-19 era (e.g., we expanded the mode of delivery from iPads in waiting rooms to include home delivery via personal phone, computer, or tablet). An external expert trained in the BCW with no prior knowledge of our intervention then coded our final multi-level implementation strategy components (e.g., shared decision-making tool, PCP marketing videos) for behavior change techniques to ensure that behavioral components determined in Phase 1 were well represented in our final materials.

In our final advisory board meeting, we administered the brief feasibility and appropriateness of intervention measures [ 37 ] informed by Proctor’s implementation outcomes to ensure the feasibility and appropriateness/fit of our multi-level implementation strategy. We used descriptive analyses of our quantitative implementation outcomes to report percentages for categorical variables and means for continuous variables.

Step 1 results: understand multi-level sustainability behaviors and determinants

Sustainability behaviors.

We identified sustained engagement in CC by care managers/psychiatrists (system-level), depression treatment optimization/referrals (provider-level), and treatment initiation/persistence (patient-level/primary sustainability behavior given reimbursement link) as essential behaviors for collaborative/integrated care sustainability in diverse settings (Additional File 3 ). We combined system and provider-level constructs given marked overlap in interviews and themes.

Determinants of sustainability behaviors

Determinants of sustainability behaviors are presented in Table 1 . Key capability constructs included lack of patient awareness of depression treatment options and provider CC knowledge/training (i.e., indications for referral) and error-prone referral processes (e.g., inappropriate referral of patients with serious mental illness). From an opportunity perspective, competing initiatives, limited resources/complex psychosocial needs, complex workflows as well as PCP and care manager time/schedules/workloads were key provider/system level barriers, while stigma, accessibility, convenience, and quality of mental care were key patient-level barriers. Key provider/system level motivation barriers related to ongoing PCP engagement, lack of PCP-care manager teamwork/communication, and infeasible warm handoffs while patients faced fear of treatment side effects and concerns around treatment efficacy (e.g., due to prior treatment failure). Experts also noted unaddressed patient-level concerns and the need for tailoring (e.g., for Spanish speaking participants) in the sustainability phase.

Step 2 results: intervention functions, behavior change techniques and strategies that promote sustainability

Intervention function behavior change techniques and eric strategies for sustainability.

Tables 2 and 3 describe the operationalized patient and provider/system-targeted multi-component implementation strategy with the final list (see below for adaptations) of corresponding behavior change techniques, targeted COM-B constructs, intervention functions (corresponding DSF tenet), mode of delivery/actors and implementation outcomes targeted [ 27 ] (e.g., CC fidelity, acceptability, sustainability).

Key intervention functions for promoting ongoing behavior change that met all APEASE criteria and would support continuous learning/improvement (DSF) included environmental restructuring, education, training, modeling, persuasion, education, and enablement. W e determined that the most feasible multi-level strategy (with corresponding behavior change techniques and ERIC strategies) for promoting sustainable behavior change would center around a patient-level video-assisted electronic shared decision making (eSDM) web application to provide culturally targeted psychoeducation, motivational messaging from care managers and patients with lived experiences, and treatment preference matching/automated shared decision making preliminarily delivered in the waiting room to patients with elevated depressive symptoms prior to primary care visits to ensure equitable access to technology ( prompts/cues, information about consequences, credible source, verbal persuasion, and restructuring the environment; develop/distribute educational materials, model/simulate change, change physical structure and equipment ) (Table 2 ).

At the provider/system level, a preliminary strategy would involve yearly mental health/CC general medicine grand rounds as well as in-person delivery of DepCare tool summary reports to PCPs/care managers on treatment preferences/barriers in the waiting room at the time of a visit to support patient-provider communication, triage, and referrals ( prompts/cues and information about consequences; ongoing training, educational meetings, remind clinicians, audit and provide feedback ). Initially, no system-level strategy was planned but based on care manager meetings it became clear we would need local (as opposed to external NYS delivered) problem- solving meetings with researchers, care managers and PCPs to discuss contextual factors key to CC sustainability (e.g., billing education/support, cultural tailoring) ( problem-solving; provide local technical assistance, implementation meetings, learning collaborative ).

Step 3 Results. Rapid Cycle user design process to operationalize and refine strategy components

Stakeholder characteristics are described in Additional File 4 . Table 4 describes adaptations to the strategy components by the creative team ( n  = 4), intervention development team ( n  = 7), and advisory board ( n  = 11) categorized by usability/workflow themes and DSF/COM-B constructs targeted. We further describe ongoing CC adaptations and contextual factors.

CC program adaptations and key contextual factors

Strategy delivery was affected by competing initiatives (e.g., iPad delivered social determinants of health screening in waiting rooms), transition to EPIC Systems Corporation electronic health record (which disrupted referral and registry processes), care manager turnover, expanded CC reimbursement for anxiety not just depression, and transition to remote/hybrid CC delivery during COVID-19, which improved show rates but increased inappropriate referrals of severe cases. Few factors were addressed by external technical assistance provided by state officials.

Patient-level strategy adaptation

The initial (version 1) DepCare prototype consisted of depression screening (with the validated Patient Health Questionnaire (PHQ)-9), a depression “score report” (describing the meaning of their score), a treatment preference and barriers checklists, care manager motivational video, and assessment of patient’s interest in seeing a care manager and starting a medication. The tool was available in English and Spanish and took 10 to 15 min to complete based on digital literacy. Details of the iterative user-centered design process of the DepCare prototype with patients and providers as well as version-by-version adaptations will be described separately. Key adaptations included (1) personalizing based on patients’ depression severity/treatment history; (2) incorporation of suicide/anxiety screening; (3) strengthening triage functionality and connection to content hub/treatment resources to address care manager capacity concerns; (4) transition from treatment decisional support to education/patient activation to reduce no-show rates ( motivation, capability) to triage/personalization/treatment optimization to address inappropriate referrals ( opportunity ); (5) reduced waiting room delivery, portal/multi-modal delivery [including paper versions to address literacy] ( opportunity/practice setting , capacity, motivation ); and (6) addition of patient video/story to facilitate cultural tailoring and activation ( capability, motivation ).

Provider-level strategy adaptation

The preliminary strategy included an in-person PCP summary report of patient preferences and yearly in-person general CC education. The PCP educational strategy transitioned to email-delivered short video/newsletters on CC indications and feedback on provider treatment optimization rates . Summary reports were delivered via EPIC/email and expanded to include care managers to better prepare for visits, triage, and avoid inappropriate referrals. We created an EPIC Systems Corporation smart phrase i.e., “dot phrases,” that allow commonly used chunks of text to easily be inserted into patient notes”).

System level strategy adaptation

Finally, we expanded the ongoing problem-solving meetings (focused on billing, cultural tailoring with local care managers) to include behavioral health providers across the institution to address local barriers and quality improvement (e.g., creating and disseminating quality improvement videos for medical assistant administered depression screening).

Step 4 results: confirm behavior change techniques and finalize strategy

Confirm behavior change techniques in final materials.

An external BCW expert reviewed all final adapted materials. The combination of the brochure and DepCare tool appropriately represented all the initially mapped behavior change techniques, except for restructuring of the physical environment, which was an inherent component of how the tool would be delivered. The external BCW expert mapped all behavior change techniques to the provider marketing video, except for demonstration of the behavior and add objects to the environment . We refined the provider video to better demonstrate how a provider would refer to CC and strengthened descriptions of how the summary report and smart phrase as additions to the environment. The expert appropriately identified most behavior change techniques related to the quarterly implementation team meetings, except for feedback on the behavior, action planning, and credible source . We removed action planning given lack of feasibility and opted to better differentiate behaviors (e.g., screening/referrals) from outcomes of behaviors (e.g., clinic-level depression symptom burden) during meetings/newsletters. We further engaged care managers/clinic administrators to lead meetings and send newsletters as credible sources. If proven effective in our ongoing trial, links to all materials will be made widely available.

Final implementation strategy for CC sustainability

The final multi-level implementation strategy is presented in Table 5 . The patient-level centers around implementation team/staff-delivered (email/text/in-person based on patient preference) DepCare tool (IR CU19184), which includes enhanced depression and anxiety screening, diagnosis recognition support, patient activation, personalized psychoeducation, patient/care manager videos promoting patient treatment engagement, personalized medication selection support and link to external treatment. The provider-level strategy includes administrator-delivered email of educational/motivational video on CC and optimal management of depression and comorbid anxiety, invitations to problem-solving/technical assistance meetings, and automatically generated DepCare tool decisional support on individual patient treatment preferences delivered to both the provider and care managers. The clinic-level strategy includes quality improvement support and education around valid depression screening as well as local technical support/problem solving for mental health staff/providers co-lead with implementation team members. In the last advisory board meeting ( n  = 4) prior to launch, the mean appropriateness of the intervention based on the validated scale was 4.56 and the mean feasibility was 4.36.

Using CC sustainability as a use case, we apply the DSF, BCW, and user-centered design principles to provide a multi-step roadmap for designing implementation strategies that promote sustainability, which involves identifying key “ sustainability behaviors ” and their barriers, selecting behavioral theory-informed strategies for sustainability, and finally operationalizing and adapting these strategies using rapid cycle, multi-stakeholder processes (Fig.  1 ). We provide a framework for incorporating more behavioral science into sustainability efforts. We go on to demonstrate how user-centered design principles can be used to operationalize and adapt implementation strategies to address fluctuations in contextual factors. For this use case, we found that a multi-level, multi-component strategy centered around an electronic automated shared decision-making, triage and referral tool (DepCare), provider education/activation/decision support and ongoing problem-solving meetings would be the most acceptable and equitable strategy for supporting multi-level behaviors and facilitating continued improvement/training processes.

Our study adds to the sustainability literature in several ways. First, experts have conceptualized sustainability as a dynamic construct that allows adaptation in response to contextual influences and organizational/implementer/intervention characteristics, calling for more research to identify and evaluate planned strategies to support sustainability in real world settings [ 18 ]. A recent systematic review of strategies that promote sustainability found few studies that employed a conceptual framework to guide in strategy development and highlighted key sustainability barriers (i.e., limited funding/resources) and facilitators (i.e., need for adaptation/alignment and funding) [ 38 ]. Our study, informed by DSF, answers calls for theory-informed, real world sustainability evaluation studies and proposes methods for operationalizing and tracking continued adaptations/improvements/evaluations not just of EBIs but strategies themselves via user-centered design principles. Experts have increasingly remarked on the need to consider user-centered design for improving the fit between evidence-based practices and implementation context and that the two fields can be complementary [ 22 ]. However, there are few use cases for integrating the two disciplines, particularly as it relates to sustainability. We posit that user-centered design may also be one method for facilitating ongoing adaptations, refinements, and improvements of implementation strategies integral to sustainability [ 19 ]. Integral to the process of sustainability is stakeholder engagement [ 18 ], and we describe ways in which stakeholders should be involved not only in understanding successes and failures of early implementation strategies but in developing, refining, and delivering strategies for sustainability.

Second, we propose a multi-step process for operationalizing the DSF to incorporate behavior change theory more explicitly to ongoing quality improvement/adaptation processes. In illustrative applications of the DSF, Chambers et al. note that care management is “influenced by drivers at patient, provider, organization and system levels”, requiring coordination among multiple stakeholders and continued assessment of fit over time, [ 19 ] all of which we posit necessitates sustained multi-level behavior change. Implementation experts recommend choosing frameworks that fit sustainability needs [ 39 ] and not every sustainability effort will warrant a behavioral lens. We identified ongoing behavior change as a key component of CC sustainability, which will require strategies that address both local contextual factors and behavioral constructs (i.e., capability, opportunity, motivation) of several CC end users. The BCW has been extensively used to design behavioral interventions and develop implementation strategies [ 26 , 33 , 40 ]. To our knowledge, we are among the first to apply a sustainability lens to the BCW by prioritizing behavior change techniques and implementation strategies that are not just acceptable/equitable/feasible but adhere to tenets of dynamic sustainability (i.e., continued education/improvement). Systematically incorporating behavior change techniques like feedback of behavior, prompts/cues, and problem solving may improve the efficiency and effectiveness of dynamic sustainability processes. We also demonstrate the ways in which usability and behavioral factors (in addition to ecological and local contextual factors) may drive adaptations to both interventions and strategies.

Finally, our proposed roadmap is adaptable. A recent mixed methods study also found that several elements of the Consolidated Framework for Implementation Research (CFIR) (e.g., ongoing coalitions, networks and partnerships, infrastructure and capacity to support sustainability, community need for programs, ongoing evaluation of performance and outcomes) are integral to the sustainability of evidence-based mental health and behavioral interventions [ 41 ]. Other use cases may find that incorporating CFIR constructs is warranted during Phase 1 of our roadmap. We posit that attention is also needed to maximally support optimal behaviors and thus long-term fidelity. Nonetheless, further work is needed to rigorously validate conceptual and methodological aspects of sustainability [ 18 ], including our behavioral approach. Future work will establish whether our strategy resulted in improved sustainability indices, including treatment optimization rates in settings seeking to sustain CC (both those with and without external implementation strategy support). Our ongoing work will also elucidate the utility of adapting our DepCare strategy to other implementation use cases (i.e., depression screening and treatment in heart disease patients) [ 42 ].

Overall, extensive research on CC implementation concludes that external support is essential for real-world effectiveness [ 14 ]. Centralized (policy-level) strategies for CC implementation (i.e., external technical assistance, reimbursement, quality monitoring) often focus on care manager behavior and CC quality/fidelity/implementation processes [ 16 ]. While these strategies inherently improve some sustainability indices, the premise of our study is that sustainability will also require ongoing behavior change, including continued care manager delivery of CC but also provider referral/optimization and patient treatment initiation/persistence. For example, late adopting CC patients may have more treatment-resistant, complex, comorbid mental health conditions. Researchers have also long demonstrated suboptimal mental health engagement/competency/optimization by providers [ 43 , 44 ], further impacting implementation outcomes [ 45 , 46 , 47 , 48 ]. Strategies not attuned to local contextual factors and related multi-level behavior change may lose ground in the sustainability phase. Our theory-informed, multi-level approach to targeting behaviors key to sustainability suggests the need for ongoing problem-solving meetings, patient activation/educational tools (that also target contextual factors by triaging patients, saving providers time, and connecting to treatment) and ongoing provider-level decisional support/education to support multi-level engagement.

There were several limitations to our study. Despite our incorporation of DSF tenets, our use of the multi-step BCW (which is often more static than dynamic) may have failed to identify key contextual determinants of and adaptative strategies for sustainability [ 38 , 41 ]. We also focused on adapting the strategy itself while tracking adaptations to CC in response to contextual factors. Sustainability may require more intensive adaptations to EBIs themselves. Relatedly, ERIC strategies and the BCW have yet to be tested or validated for sustainability. Instead, our roadmap should be interpreted as an adjunctive process for incorporating more behavioral science into sustainability efforts. Since study completion, newer frameworks for tracking adaptations of interventions and strategies have also emerged, which may have allowed us to better operationalize our process [ 49 ]. While our adaptation process innovatively utilized user-centered design procedures and multiple stakeholders to adapt (not just track adaptations), this was an intensive process and may not be replicable. In all, it took 30 months to complete due to the COVID-19 pandemic. In addition, the adaptation of the implementation strategy occurred in experimental (vs. real time) settings within a subset of individuals, which did not allow us to evaluate the effects of each strategy adaptation on validated sustainability measures (other than usability and perceived feasibility). Finally, we did not consider development costs when deciding on strategy components, though concluded that a freely available web application had the most potential to be sustainably delivered (e.g., sent to all patients on waiting/screen positive lists by care managers/care coordinators while other strategy components were already delivered by the healthcare system (e.g., problem-solving meetings, provider education). Nonetheless, an inherent consideration within implementation science is that strategies (including those that promote sustainability) need to themselves be sustained.

Our study provides a rigorous, multi-step process for applying behavioral science, implementation science, and user center design to select and adapt implementation strategies to fit dynamic local contexts and sustain interventions. Our strategy is currently being tested in settings with collaborative/integrated care, during which we will track further adaptations to both the strategy and evidence-based intervention and assess the effects of our multi-level strategy on treatment optimization in clinics seeking to sustain CC. This study has marked implications to developing, adapting, and testing strategies that specifically promote sustainability in a broad range of populations and settings.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Ambulatory Care Network

Behaviour Change Wheel

Collaborative Care

Consolidated Framework for Implementation Research

Capability, Opportunity, Motivation – Behavior Model

Coronavirus disease 2019

Dynamic Sustainability Framework

Expert Recommendations for Implementation Change

New York State Department of Health

New York State Office of Mental Health

Patient Health Questionnaire

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Acknowledgements

This work was supported by funds from the Agency for Health and Research Quality (R01HS025198). AHRQ had no role in the design and conduct of the study, including the collection, management, analysis, interpretation of the data, preparation, review, or approval of the manuscript, and decision to submit the manuscript for publication.

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Nathalie Moise, Jennifer Mizhquiri Barbecho, Luis Blanco, Samantha Simantiris, Maria Serafini, Darlene Straussman, Siqin Ye & Andrea T. Duran

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NM secured funding, analyzed data, drafted the manuscript, and supervised the manuscript. APA analyzed data and drafted sections of the manuscript. LB oversaw intervention development and adaptation. JMB oversaw data collection, interpreted data, intervention development, and adaptation. KDB analyzed data and provided critical revision of the manuscript. SF collected data. MM contributed to intervention development and adaptation. MS collected and analyzed data. DS collected data. SP provided critical revision of manuscript. SY oversaw the collection of data and critical revision of the manuscript. AD supervised data collection, critical revision, and interpretation of data. All authors read and approved the final manuscript.

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Supplementary Information

Additional file 1..

The behavior Change Wheel.

Additional file 2.

Definitions of Intervention Functions and Policy Categories: The Behavioral Chance Wheel.

Additional file 3.

Using the Behaviour Change Wheel to operationalizing multi-level behaviors around sustaining collaborative care.

Additional file 4.

Expert Stakeholder Characteristics.

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Moise, N., Paniagua-Avila, A., Barbecho, J.M. et al. A theory-informed, rapid cycle approach to identifying and adapting strategies to promote sustainability: optimizing depression treatment in primary care clinics seeking to sustain collaborative care (The Transform DepCare Study). Implement Sci Commun 4 , 10 (2023). https://doi.org/10.1186/s43058-022-00383-2

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Developing theory-informed behaviour change interventions to implement evidence into practice: a systematic approach using the Theoretical Domains Framework

• Simon D French 1 , 2 ,
• Sally E Green 1 ,
• Denise A O’Connor 1 ,
• Joanne E McKenzie 1 ,
• Jill J Francis 3 ,
• Susan Michie 4 ,
• Rachelle Buchbinder 1 , 5 , 9 ,
• Peter Schattner 6 ,
• Neil Spike 6 &
• Jeremy M Grimshaw 7 , 8  

Implementation Science volume  7 , Article number:  38 ( 2012 ) Cite this article

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There is little systematic operational guidance about how best to develop complex interventions to reduce the gap between practice and evidence. This article is one in a Series of articles documenting the development and use of the Theoretical Domains Framework (TDF) to advance the science of implementation research.

The intervention was developed considering three main components: theory, evidence, and practical issues. We used a four-step approach, consisting of guiding questions, to direct the choice of the most appropriate components of an implementation intervention: Who needs to do what, differently? Using a theoretical framework, which barriers and enablers need to be addressed? Which intervention components (behaviour change techniques and mode(s) of delivery) could overcome the modifiable barriers and enhance the enablers? And how can behaviour change be measured and understood?

A complex implementation intervention was designed that aimed to improve acute low back pain management in primary care. We used the TDF to identify the barriers and enablers to the uptake of evidence into practice and to guide the choice of intervention components. These components were then combined into a cohesive intervention. The intervention was delivered via two facilitated interactive small group workshops. We also produced a DVD to distribute to all participants in the intervention group. We chose outcome measures in order to assess the mediating mechanisms of behaviour change.

Conclusions

We have illustrated a four-step systematic method for developing an intervention designed to change clinical practice based on a theoretical framework. The method of development provides a systematic framework that could be used by others developing complex implementation interventions. While this framework should be iteratively adjusted and refined to suit other contexts and settings, we believe that the four-step process should be maintained as the primary framework to guide researchers through a comprehensive intervention development process.

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Many resources have been directed toward improving the quality and safety of health care, but major problems persist [ 1 ]. Implementation interventions are interventions designed to change clinical practice behaviour and improve the uptake of evidence into practice. To date, implementation interventions have had limited and varied effects [ 2 ]. This may be due, in part, to a lack of explicit rationale for the intervention choice and the use of inappropriate methods to design the interventions [ 3 – 5 ].

The design of implementation interventions requires a systematic approach with a strong rationale for design and explicit reporting of the intervention development process [ 6 – 8 ]. One option is to use theory to inform the design of implementation interventions [ 3 , 9 ]. The UK Medical Research Council’s (MRC) guidance for developing complex interventions informed by theory [ 10 – 13 ] is useful as a general approach to designing an implementation intervention, but it does not provide detailed guidance about how to achieve this.

Multiple theories and frameworks of individual and organisational behaviour change exist, and often these theories have conceptually overlapping constructs [ 14 – 16 ]. Only a few of these theories have been tested in robust research in healthcare settings. There is currently no systematic basis for determining which among the various theories available predicts behaviour or behaviour change most precisely [ 17 ], or which is best suited to underpin implementation research [ 16 , 18 ]. Theories that have been used in previous implementation research include PRECEDE (Predisposing, Reinforcing, and Enabling Constructs in Educational Diagnosis and Evaluation), diffusion of innovations, information overload, and social marketing [ 5 ].

This article is one in a Series of articles documenting the development and use of the Theoretical Domains Framework (TDF) to advance the science of implementation research. The TDF was developed using an expert consensus process and validation to identify psychological and organisational theory relevant to health practitioner clinical behaviour change [ 19 ]. A set of 12 domains covering the main factors influencing practitioner clinical behaviour and behaviour change were identified: knowledge; skills; social/professional role and identity; beliefs about capabilities; beliefs about consequences; motivation and goals; memory, attention and decision processes; environmental context and resources; social influences; emotion; behavioural regulation; and nature of the behaviours. Relative to previously accepted, often implicit, models for developing interventions (for example, need to raise awareness, to provide information, to educate, need for an opinion leader or champion), these 12 domains provide an extensive framework that has greater coverage of potential barriers to change, and thus implies a greater range of potential intervention components.

Although improved health care can be facilitated at different levels of the health system, one important approach is to support individual health professionals to modify their clinical behaviour in response to evidence-based guidance [ 15 ]. The focus on this level is because much of health care is delivered in the context of an encounter between a health professional and a patient, making healthcare professional clinical behaviours an important proximal determinant of the quality of care that patients receive.

Development of implementation interventions can draw on theory, evidence, and practical issues in the following ways. Theory can be used to understand the factors that might influence the clinical behaviour change being targeted, to underpin possible techniques that could be used to change clinical behaviour [ 19 ], and to clarify how such techniques might work. Evidence can inform which clinical behaviours should be changed, and which potential behaviour change techniques and modes of delivery are likely to be effective. Practical issues then determine which behaviour change techniques are feasible with available resources, and which are likely to be acceptable in the relevant setting and to the targeted health professional group.

This paper outlines a method for developing an implementation intervention, drawing on the guidance from the UK MRC framework [ 10 – 12 ], and building on previously published methods for theory-informed intervention development [ 20 , 21 ]. We discuss how we used this method for developing an implementation intervention using the example of a recently developed intervention that we tested in the IMPLEMENT cluster randomised trial [ 22 ].

A method for developing implementation interventions to change clinical behaviour

We used a four-step approach, consisting of guiding questions to direct the choice of the most appropriate components of an implementation intervention (Table 1 ). The four steps represent: identifying the problem (who needs to do what, differently?); assessing the problem (using a theoretical framework, which barriers and enablers need to be addressed?); forming possible solutions (which intervention components could overcome the modifiable barriers and enhance the enablers?); and evaluating the selected intervention (how can behaviour change be measured and understood?).

Step 1. Who needs to do what, differently?

We selected the target clinical behaviours to be addressed, based on documented evidence-practice gaps. We specified the target behaviours in detail by asking the following questions: What is the clinical behaviour (or series of linked behaviours) that you will try to change? Who performs the behaviour(s)? And when and where do they perform the behaviour(s)?

Step 2. Using a theoretical framework, which barriers and enablers need to be addressed?

We chose a theoretical framework that we considered was most likely to inform the pathways of behaviour change. We used qualitative methods, underpinned by this theoretical framework, to identify the barriers and enablers to the pathways of change that were likely to influence the target clinical behaviours.

Step 3. Which intervention components (behaviour change techniques and mode(s) of delivery) could overcome the modifiable barriers and enhance the enablers?

Informed by our chosen theoretical framework, and empirical evidence about effectiveness of behaviour change techniques, we identified techniques to overcome the barriers and enhance the enablers. We first established the content of the intervention (what will actually be delivered), then we identified possible modes of delivery (how each chosen technique would be delivered) [ 23 ]. We based the final selection of behaviour change techniques and mode of delivery on what we considered was locally relevant, likely to be feasible, and could be implemented as a cohesive intervention.

Step 4. How can behaviour change be measured and understood?

We determined in advance the outcome measures for behaviour change and which mediators of change could be measured to evaluate the proposed pathways of change [ 24 ]. We based the selection of outcome measures on the availability of reliable and valid measures that were feasible to use.

The resultant IMPLEMENT intervention was delivered via two facilitated interactive small group workshops that were a combination of didactic lectures and small group discussions and activities. We also produced a DVD to distribute to all general practitioners (GPs) in the intervention group with the primary purpose of providing the material to those who could not attend the workshops. This alternative mode of delivering the same intervention content included film footage from the workshops and electronic resources related to acute low back pain management.

The target behaviours for the IMPLEMENT intervention arose from two recommendations from the Australian evidence-based clinical practice guideline for acute low back pain [ 25 ]. The first target behaviour was to restrict the ordering of plain film x-rays to situations in which fracture is suspected because plain film x-rays are rarely helpful in the management of acute low back pain and are potentially harmful. The second target behaviour was to advise patients with acute non-specific low back pain to remain active because this reduces pain and disability.

We chose these target behaviours because they had strong supporting evidence, were potentially modifiable at a practitioner level, and were clinical behaviours to be performed by the GP during a clinical interaction early in the course of management of acute low back pain.

To develop the IMPLEMENT intervention, we used the TDF [ 19 ] to identify the barriers and enablers to the target behaviours and to guide the choice of intervention components. Barriers to, and enablers of, the two target behaviours were identified in a qualitative study consisting of focus group interviews with 42 GPs in Victoria, Australia [ 26 ]. Each focus group was led by a trained facilitator who investigated the reasons GPs gave for practising, or not, in a manner consistent with the guideline recommendations. Questions were designed to explore the domains from the TDF for each of the two behaviours. Key domains were identified that described the specific barriers and enablers at a theoretical level, which then allowed us to access relevant evidence of likely effective behaviour change techniques.

For the IMPLEMENT trial, our selection of behaviour change techniques was informed by a matrix that mapped behaviour change techniques to the theoretical domains, based on expert consensus about effectiveness for behaviour change [ 27 ]. We used the experience of the research team including clinicians and clinician educators, together with feedback from clinical colleagues on potential intervention approaches, to determine which behaviour change techniques and modes of delivery to select.

We chose the delivery mode of facilitated workshops because interactive education is familiar, acceptable, and feasible for GPs, and there is evidence that interventions delivered using this mode of delivery may change professional practice [ 28 ]. Also, this delivery mode could be linked to the requirements for Continuing Professional Development points for GPs in Australia. Finally, the intervention was assessed by the clinical members of the research team who checked that the proposed content was likely to be regarded by participants as relevant and helpful to their practice.

Table 2 provides details of the intervention development process of the IMPLEMENT intervention. The columns indicate how we linked specified barriers and enablers to theoretical domains and then identified behaviour change techniques and modes of delivery. For example, one identified barrier was lack of skill: some GPs reported that they lacked the communication skills to reassure patients that a plain film x-ray is unnecessary. We mapped this barrier to the domains ‘skills’ and ‘beliefs about capabilities’. It was considered that these domains were best addressed by using the behaviour change technique ‘rehearsal’ [ 27 ]. We delivered this in the facilitated workshop in a small group activity, where the GP took a clinical history with a trained simulated patient who repeatedly requested an x-ray, and the GP was asked to explain to the patient that a plain film x-ray was unnecessary, followed by a group discussion of the issues the GPs faced during the activity.

Detailed documentation of the full content of the IMPLEMENT facilitated workshops is available in the Additional file 1 .

Table 3 outlines the constructs we planned to measure in the IMPLEMENT trial, describing outcomes measured to assess the causal pathway (mediating mechanisms of behaviour change), the practitioner outcomes and the patient outcomes.

We have illustrated a four-step method for developing an intervention designed to change clinical behaviour based on a theoretical framework. We have demonstrated the use of this method in a case study of designing the IMPLEMENT intervention, an intervention designed to improve the management of low back pain in general practice [ 22 ].

Many researchers who assess barriers and enablers for implementation problem assessment do not do this within a theoretical framework and are therefore limited to pragmatic, rather than theoretically informed, solutions [ 37 ]. The use of our method when designing implementation interventions allows the use of theory and empirical research, along with the results of mixed methods research, to decide upon intervention components and to build a complex intervention. This will allow for further exploration of the associations between intervention components and intervention effects [ 38 ]. We also encourage researchers involved in developing implementation interventions to better document and report their own development process thus generating a body of knowledge about explicit methods for developing these interventions.

Strengths of this method

The main strength of this four-step method is that it can be used as a guide for implementation intervention developers through a systematic method of moving from target behaviours, to theoretical domains, to behaviour changes techniques, and finally a full implementation intervention. By basing implementation interventions on a theoretical approach to behaviour change and linking this to relevant and effective behaviour change techniques, researchers can make explicit, and thus investigate, the hypothesised mechanisms of change. We propose a streamlined approach moving directly from identified theoretical domains relevant to the implementation problem to behaviour change techniques.

Multiple theories and frameworks of individual and organisational behaviour change exist [ 14 – 16 ], and choosing an appropriate theory for designing implementation interventions is challenging [ 16 – 18 ]. Setting predetermined criteria for selection of theories may assist, for example, including consideration of the evidence base for the theory, the relevance to the setting, and perceived usefulness of the theory. Also, using a broadly based theoretical framework for behaviour change, rather than a single theory, may allow a more comprehensive examination of potential barriers and enablers, and possible mechanisms linking them to the target clinical behaviour. The TDF is arguably the most comprehensive framework for designing implementation interventions as it offers broad coverage of potential change pathways; however other theoretical frameworks, or specific theories, could be used.

There are many potential delivery modes in the clinical setting for most behaviour change techniques [ 27 ], including educational meetings, educational detailing, reminder systems, and audit and feedback [ 39 ]. We suggest the choice of the delivery mode is guided by local context and what is acceptable and feasible in the target group.

Potential limitations of this method

There is subjectivity in this proposed process of designing implementation interventions of combining research evidence, matrix mapping, and feasibility information. Further empirical work is required to test the method in different contexts and examine the links between theoretical assessment and behaviour change techniques. There are alternative ways of operationalising this method. For example, in other studies the TDF has been used to identify key domains followed by predictive theory-based surveys to check whether the domains regarded as ‘key’ actually do predict clinical practice [ 40 ]. Another approach has been to use the TDF to identify specific theories of behaviour change to inform the intervention [ 40 – 42 ]. Documentation and careful reporting of the development process of implementation interventions will further this field.

In IMPLEMENT, barriers and enablers were assessed by conducting focus groups with GPs. Hence, the intervention developed was directed at the individual clinician. However, in broader application of the TDF, although data may be gathered at an individual level, theory is not restricted to the individual level and may address organisational determinants of behaviour change, such as the included domains Environmental context and resources, Professional role and identity, and Social influences which address issues beyond the individual clinician.

This method of intervention development requires considerable time and resources. Developing the IMPLEMENT intervention involved time of a PhD student (SDF), his supervisors (SEG and RB), and input from the rest of the research team via teleconferences and email correspondence over 12 months. During this time we were also developing the method itself, adding to the time needed. Full detail of the resources required to develop the IMPLEMENT intervention will be reported in a separate economic evaluation publication.

The resources required could be seen as a necessary component of the development of complex behaviour change implementation interventions [ 12 ]. Resources to enable this will depend on funding models allocating sufficient funds for the intervention development component of research studies and to require this as a component of guideline development and implementation initiatives. Currently, many funding bodies expect that, at the time at which funding applications are submitted, the intervention protocol for complex interventions is already well formulated [ 43 ]. This contrasts with, for example, pharmacologic interventions, for which it is accepted that a decade or two of basic research is required before an intervention is ready for trialling. The publication of the new guidance for the MRC framework [ 12 ], along with applications of the framework which demonstrate the resource intensive nature of this work, will hopefully facilitate increased funding for this important activity, increasing the likelihood that interventions will be fit for evaluation in trials, and will therefore better utilise research investments.

We have illustrated a four-step systematic method for developing an intervention designed to change clinician behaviour based on a theoretical framework. We propose a streamlined approach moving directly from identified theoretical domains relevant to the implementation problem to behaviour change techniques. This method is a conceptual aid, rather than a rigid prescription; it may be iteratively adjusted and refined to suit other contexts and settings. The process outlined here can be used by researchers and quality improvement practitioners to guide a comprehensive intervention development process.

By basing implementation interventions on a theoretical approach to behaviour change and linking this to relevant and effective behaviour change techniques, researchers can make explicit, and thus investigate, the hypothesised mechanisms of change. We have argued that using such a method can facilitate the development of theory-informed implementation interventions. Finally, appropriate reporting of the processes used to develop the interventions, and of the components of the intervention, is necessary.

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The IMPLEMENT trial was funded by the Australian National Health and Medical Research Council (NHMRC) by way of a Primary Health Care Project Grant (334060). The NHMRC has had no involvement in the study design, preparation of the manuscript, or the decision to submit the manuscript. SF is supported by a NHMRC Primary Health Care Fellowship (567071). DOC is supported by a NHMRC Public Health Fellowship (606726). JF has 50% of her time funded by the Chief Scientist Office of the Scottish Government Health Directorate. JG holds a Canada Research Chair in Health Knowledge Transfer and Uptake. We thank Professor Martin Eccles, Co-Editor-in-Chief of Implementation Science, for his comprehensive editorial advice and suggestions during the peer review process.

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Simon D French, Sally E Green, Denise A O’Connor, Joanne E McKenzie & Rachelle Buchbinder

Primary Care Research Unit, University of Melbourne, 200 Berkeley St, Carlton, Victoria, 3010, Australia

Simon D French

Health Services Research Unit, Health Sciences Building, University of Aberdeen, Aberdeen, AB25 2ZD, Scotland, UK

Jill J Francis

Centre for Outcomes Research and Effectiveness, Department of Clinical, Educational and Health Psychology, University College London, WC1E 7HB, London, UK

Susan Michie

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Rachelle Buchbinder

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Peter Schattner & Neil Spike

Clinical Epidemiology Program, Ottawa Health Research Institute, Ottawa, Canada

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Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Level 6, The Alfred Centre, 99 Commercial Road, Melbourne, Victoria, Australia, 3004

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Denise O’Connor and Susan Michie are Associate Editors for Implementation Science and Sally Green and Jeremy Grimshaw are members of the editorial board. All decisions on this manuscript were made by another editor. All other authors declare that they have no competing interests.

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SF wrote the first draft of this manuscript with comments from SG, RB, SM, and JG, and then the remaining authors. All authors contributed to the ideas in this paper and SF acts as guarantor. All authors read and approved the final manuscript.

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French, S.D., Green, S.E., O’Connor, D.A. et al. Developing theory-informed behaviour change interventions to implement evidence into practice: a systematic approach using the Theoretical Domains Framework. Implementation Sci 7 , 38 (2012). https://doi.org/10.1186/1748-5908-7-38

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DOI : https://doi.org/10.1186/1748-5908-7-38

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• Volume 11, Issue 5
• Developing a theory-informed complex intervention to improve nurse–patient therapeutic engagement employing Experience-based Co-design and the Behaviour Change Wheel: an acute mental health ward case study
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• http://orcid.org/0000-0002-0448-006X Sarah McAllister 1 ,
• Alan Simpson 1 ,
• Vicki Tsianakas 1 ,
• Nick Canham 2 ,
• Vittoria De Meo 2 , 3 ,
• Cady Stone 2 ,
• http://orcid.org/0000-0001-8781-6675 Glenn Robert 1
• 1 Florence Nightingale Faculty of Nursing, Midwifery & Palliative Care , King's College London , London , UK
• 2 Independent Service User and Carer Group , London , UK
• 3 FOR WOMEN CIC , London , UK
• Correspondence to Sarah McAllister; Sarah.McAllister{at}kcl.ac.uk

Objectives Our objectives were threefold: (1) describe a collaborative, theoretically driven approach to co-designing complex interventions; (2) demonstrate the implementation of this approach to share learning with others; and (3) develop a toolkit to enhance therapeutic engagement on acute mental health wards.

Design and participants We describe a theory-driven approach to co-designing an intervention by adapting and integrating Experience-based Co-design (EBCD) with the Behaviour Change Wheel (BCW). Our case study was informed by the results of a systematic integrative review and guided by this integrated approach. We undertook 80 hours of non-participant observations, and semistructured interviews with 14 service users (7 of which were filmed), 2 carers and 12 clinicians from the same acute ward. The facilitated intervention co-design process involved two feedback workshops, one joint co-design workshop and seven small co-design team meetings. Data analysis comprised the identification of touchpoints and use of the BCW and behaviour change technique taxonomy to inform intervention development.

Setting This study was conducted over 12 months at an acute mental health organisation in England.

Results The co-designed Let’s Talk toolkit addressed four joint service user/clinician priorities for change: (1) improve communication with withdrawn people; (2) nurses to help service users help themselves; (3) nurses to feel confident when engaging with service users; (4) improving team relations and ward culture. Intervention functions included training, education, enablement, coercion and persuasion; 14 behaviour change techniques supported these functions. We detail how we implemented our integrated co-design-behaviour change approach with service users, carers and clinicians to develop a toolkit to improve nurse–patient therapeutic engagement.

Conclusions Our theory-driven approach enhanced both EBCD and the BCW. It introduces a robust theoretical approach to guide intervention development within the co-design process and sets out how to meaningfully involve service users and other stakeholders when designing and implementing complex interventions.

• quality in health care
• mental health
• adult psychiatry
• qualitative research

Data availability statement

Data are available upon reasonable request. All data relevant to the study are included in the article or uploaded as supplementary information. All data generated or analysed during this study are included in this published article and its accompanying supplemental information files.

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/ .

https://doi.org/10.1136/bmjopen-2020-047114

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Strengths and limitations of this study

To our knowledge, our study is the first to combine and implement a new theory-driven co-design-behaviour change process with service users, carers and clinicians in a mental health setting.

Our intervention development process was highly collaborative, with service users, carers and clinicians working together in equal and active partnership.

Our process provided a systematic and replicable system for reporting the behavioural mechanisms of action behind our complex intervention toolkit.

Although our process was highly collaborative, it was conducted at just one National Health Service site, which represents a possible limitation.

Nurse–patient therapeutic engagement can broadly be described as the use of verbal and non-verbal interchange to improve a service user’s mental health. 1 2 Lack of high-quality engagement on acute mental health wards is strongly associated with increased rates of self-harm, violence, aggression, absconding and poor perceptions of inpatient care. 3 4 Engagement may initiate and enhance the therapeutic relationship, 5 which arguably has the greatest impact on treatment outcomes, over and above the specific interventions provided. 6 7 However, nurses report high levels of acuity, reduced workforce, competing administrative duties and the nebulous nature of engagement as reasons for not engaging with service users. 8–10 These factors also have a negative impact on nurses’ job satisfaction, 11 increasing the likelihood of burn-out and leaving the profession prematurely.

Reports from service users suggest that wards are experienced as devoid from warm, respectful therapeutic interactions. 12 Pharmacological treatments are prioritised over collaborative clinician–patient engagement, which leaves service users feeling stigmatised and alienated from their care team. 13 14 Despite a recognition of the importance of collaborative care planning by clinicians, service users were often not involved in this process and felt as if they had no say in the trajectory of their care. 15 Policymakers, researchers and patient advocacy groups globally have emphasised the importance of engagement in practice. 16–18 However, lack of quality engagement is a long-standing, complex problem 19 20 and few nursing interventions to improve engagement are reported in the literature.

One such intervention, predominantly implemented in the UK, is protected engagement time (PET). During PET, nurses devote a specified amount of time to regular engagement sessions with service users. 21 22 PET originates from the refocusing model, which was a comprehensive series of interventions to improve inpatient services and reduce work strain on staff. 23 24 The refocus model brought about improvements to the quality of care, staff sickness and costs, rates of absconding and self-harm. 23 Following this, PET was adopted as a stand-alone intervention by mainstream policy (eg, ref 25 ), which resulted in its top-down implementation in many mental health services across England. Subsequent evaluations on both adult and older adult mental health wards found that while PET attempts to address nurses’ opportunities to engage, it does not account for wider considerations about what is done within the engagement sessions. 26–28 This may be because PET was intended to be used alongside other interventions, and its use as a stand-alone intervention stemmed from an atheoretical, common sense approach to implementation.

In response to PET’s limitations, a Swedish study developed the Time to Talk (TT) intervention. 29 TT is a form of PET, theoretically informed by two studies of everyday life on acute wards 30 31 and the Tidal Model—a holistic model of nursing care that promotes the exploration of service users’ own narratives. 32 In a qualitative evaluation of TT, 33 service users reported that clinicians were more engaged after TT was implemented; however, their quantitative evaluation found no improvement in the quality of engagement as measured through the Caring Professional Scale. 34 This mirrors evaluations of PET. 26 27 Although PET and TT address nurses’ opportunities to engage, they may not compensate for wider deficiencies in service provision such as poor supervision, clinical skills and personal motivations, 26 28 and neither were collaboratively developed with input from service users, carers and clinicians.

To better understand and enhance nurse–patient engagement in practice we previously conducted a systematic integrative review to develop a conceptual model of engagement. 35 For high-quality engagement to occur, the model suggests that nurses must employ techniques that encompass five ‘Principles of Engagement’: (1) understand the person and their illness; (2) facilitate growth; (3) therapeutic use of self; (4) choose the right approach and; (5) emotional versus restrictive containment. The model drew on behaviour change theory 36 to show that engagement is broadly influenced by both the service users' and nurses’ capability, opportunity and motivation to engage. To address the limitations of previous interventions, we propose a collaborative, theory-driven approach to co-designing a complex intervention to improve the amount and quality of engagement on acute mental health wards. To do so, we have drawn from our model of engagement described above and adapted and integrated two existing approaches: Experience-based Co-design (EBCD) 37 38 and the Behaviour Change Wheel (BCW). 36

EBCD is a form of participatory action research which draws on user-centred design and user experience to improve healthcare services. 37 The structured EBCD process, detailed in a freely available online toolkit, 39 aims to meaningfully engage service users, carers and clinicians throughout a co-design process using observations, interviews and facilitated workshops. The BCW and accompanying behaviour change technique taxonomy version 1 (BCTTv1) has amalgamated 19 behaviour change theories to create a framework that guides intervention development. 36 It follows three phases: (1) understand the behaviour; (2) identify intervention options; and (3) identify intervention content. At its core, the model suggests that capability, opportunity and motivation interact to create behaviours (COM-B). 40 The Theoretical Domains Framework (TDF) 41 is aligned in the model to the COM-B components and both are linked to nine intervention functions. The BCTTv1 is a taxonomy of 93 behaviour change techniques (BCTs). These 93 BCTs can be matched to the intervention functions to identify suitable BCTs, which make up the active ingredients of an intervention. 42 43 Figure 1 maps the BCW phases, methods and tools to the phases, methods and tools of EBCD and provides a theory-driven basis for the co-design of behaviour change interventions.

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Integrated codesign-behaviour change model. APEASE, affordability, practicability, effectiveness/cost-effectiveness, acceptability, side effects/safety and equity; BCT, behaviour change technique; BCTTv1, behaviour change technique taxonomy version 1; BCW, behaviour change wheel; COM-B, capability, opportunity and motivation interact to create behaviours; EBCD, experience-based co-design; PPI, patient and public involvement; TDF, theoretical domains framework.

Healthcare research and policy now recognise the importance of both co-designing interventions and using a robust theory to guide intervention development, 44 45 but to date very few studies report on how to co-design complex healthcare interventions using a theory-driven approach. Currently, there are no published studies that develop interventions using EBCD informed by the BCW. In response, we demonstrate the implementation of a theory-driven co-design-behaviour change process ( figure 1 ) that was used to develop a complex intervention toolkit for promoting nurse–patient engagement on acute mental health wards.

Describe a collaborative, theoretically driven approach to co-designing complex interventions.

Demonstrate the implementation of this process to share learning with others.

Develop a toolkit to enhance therapeutic engagement on acute mental health wards.

This case study was guided by the UK Medical Research Council complex intervention framework 46 and was theoretically driven by the content illustrated in figure 1 . The co-design process is reported in accordance with guidance for reporting intervention development studies in health research 47 ( online supplemental file 1 ). Participants gave written consent prior to being interviewed and again at the start of each co-design workshop. Posters that explained the purpose of the ward observations were displayed in common areas on the ward. Participation in observations was on an opt-out basis, to which nobody opted out.

Supplemental material

The study was conducted with service users, carers and clinicians from one inner-London National Health Service (NHS) Foundation Trust in England, where the lead author had previously conducted exploratory work. 5 The intervention ward has 18 beds and treats adults 18–64 experiencing an acute phase of severe mental illness. The ward is laid out along a corridor, with the nursing station and reception area at one end of the ward, the service user bedrooms running along both sides of the corridor and the service user lounge and day area at the opposite end of the ward to the nursing station. Service users are predominantly detained under the Mental Health Act. 48 The ward consists of a multidisciplinary team of 20 clinicians, including 8 registered mental health nurses (RMNs), 7 healthcare assistants (HCAs), a peer support worker, an activities coordinator, an occupational therapist, a psychologist and a consultant psychiatrist. The nursing team works shift patterns from 07:30 to 21:30 or from 21:00 to 08:00 and all RMNs and HCAs are involved in direct patient care including care planning, one-to-one interactions and close and hourly observations. The RMNs are responsible for medication rounds. The ward provides timetabled daily activities run by the activities coordinator, and service users attend weekly ward rounds led by the consultant psychiatrist and an RMN. This project began in April 2018 and complemented other organisational improvement work to reimplement PET.

Participants

The co-design team was recruited through:

A convenience sample of service users and carers via: (1) face-to-face contact and posters at community mental health teams (CMHTs) and (2) face-to-face contact and email at service user advocacy groups connected to the participating NHS organisation.

A whole population sample of clinicians on the participating ward were invited to take part via presentations, posters, email and face-to-face meetings.

SM screened all potential participants, specifically looking for those who had, or had cared for somebody who had at least one inpatient admission at the organisation but was not currently experiencing a relapse. Eligible individuals were then guided through a written informed consent procedure. Figure 2 shows the recruitment process by type of participant and workshop attendance through the EBCD process. A total of 35 members were recruited to the co-design team including 15 service users, 2 carers, 10 RMNs, 4 HCAs, 3 psychological therapy clinicians and 1 student nurse. Just over half of the codesign team were female (54%) and just under half were from a black, Asian, and minority ethnic background (49%). Participants’ ages ranged from 18 to 64 years. Service users had a variety of mental illnesses, including psychotic disorders such as schizophrenia and bipolar affective disorder (71%), personality disorder (7%), anxiety (7%) and eating disorder (7%).

Recruitment process by type of participant and workshop attendance. EBCD, experience-based codesign.

Data collection and analysis

Data collection methods and processes were aligned to the EBCD phases and BCW stages contained in figure 1 and informed by the aforementioned integrative review 35 these included non-participant observations and semistructured interviews to gather service user, carer and clinician experiences, and feedback and co-design workshops to facilitate development of the engagement toolkit.

Non-participant observations and semistructured interviews

SM (a mental health nurse, previously unknown to the study participants and trained in the application of the EBCD and BCW approach) conducted 80 hours of non-participant observations on the acute ward between the hours of 07:30 and 15:00 or 13:30 and 21:30, Monday through Sunday. Observations were performed in 15 minute intervals, beginning with the first nurse encountered and continued until all nursing staff had been observed. Field notes were guided by Tyson and colleagues 49 and documented patterns of nurse–patient behaviour, nurse–patient dynamics, tone of voice, body language, potential influences on engagement and general ward atmosphere.

SM also interviewed 14 service users, 2 carers and 12 clinicians on a one-to-one basis at a location of their choice including university premises, offices at CMHTs or by telephone. All interviews were audio recorded and seven service user interviews were filmed in keeping with the EBCD approach. Interviews lasted between 30 and 80 min. A topic guide was followed, informed by our review, 35 the non-participant observations and the COM-B/TDF domains. 41 42 Interviews addressed participants’ experiences of engagement, barriers and facilitators to engagement, and clarified assumptions made from the observations.

Full details of the non-participant observations and semistructured interviews, including the inductive analysis of data to identify ‘touchpoints’ (emotionally significant points) of importance to the co-design team, are reported in a separate paper. 50 A secondary deductive analysis of interview data, which is reported in this paper, was also undertaken to identify barriers to engagement. Deductive codes were based on the COM-B and TDF components of the BCW which were used as an a priori framework to analyse and thematically organise interview data. SM independently coded and themed the data using this framework. Extracts from both the filmed and audio-recorded interviews were also edited into a trigger film that was used to stimulate discussion at the feedback and co-design workshops.

Feedback and codesign workshops

Touchpoints and themes were shared at separate service user/carer and clinician feedback workshops and at a joint co-design team workshop. This ensured validity of the analysis, facilitated the joint selection of target behaviours based on the touchpoints and allowed intervention options and content to be agreed. Seven co-design team meetings were also established to work on specific priority areas. Consensus was reached through facilitated discussions and consensus building exercises including emotional mapping 37 and affinity grouping. 51

Input was also sought throughout the co-design process from two mental health patient and public involvement (PPI) groups based at the participating organisation. An advisory group consisted of a service user representative, one clinician and clinical academic experts in (A) the EBCD methodology and (B) therapeutic engagement, respectively. The service user representative cofacilitated the feedback workshops with SM who also facilitated the joint co-design and co-design team workshops with the assistance of another nurse researcher trained in the BCW approach. Three co-design team members wrote reflective accounts of their experiences of the co-design process and are coauthors of this paper.

Patient and public involvement

Service users and carers were at the heart of this research, being involved from conception, through execution and dissemination of this work.

Here we present our theory-driven approach to co-designing the Let’s Talk complex intervention toolkit. Our findings are organised under the three stages (and eight constituent steps) of the BCW guide, as shown in figure 1 .

Stage 1: understanding the behaviours

Step 1: define the problem in behavioural terms.

Through previous research, 5 our integrative review 35 and initial discussions with our PPI, advisory groups and the clinical service lead, modern matron and divisional medical director at the NHS organisation, the behavioural problem was defined as the absence of high-quality nurse–patient therapeutic engagement on acute mental health wards, that is, not using the Principles of Engagement identified in our review.

Step 2: select target behaviour(s)

In keeping with the EBCD methodology, it was important to understand how service users and staff typically experienced engagement prior to the identification of relevant areas for behavioural change. Through observations and semistructured interviews, the research team identified 28 touchpoints. Some examples of touchpoints were (1) I was left on my own and ignored; (2) my care was robotic; and (3) as a nursing team we need to create better bonds with service users (full results found in ref 50).

To ensure credibility, the touchpoints were discussed during two facilitated feedback workshops—one for service users and one for clinicians. In an emotional mapping exercise, participants were encouraged to identify improvement priorities based on their touchpoints and assign associated behaviours (see online supplemental file 2 for breakdown of touchpoints into improvement priorities and associated behaviours). Participants then ranked their improvement priorities in a dot voting exercise and chose four priorities to take forward to the joint workshop ( table 1 ). The service user and clinician priorities were as follows.

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Service user and clinician priorities for change

At the joint workshop, facilitated discussion encouraged participants to consider the potential impact, likelihood of change, spillover effect and ease of measurement of all the improvement priorities and associated behaviours. An affinity grouping exercise was conducted and through this, four shared improvement priorities were identified and agreed:

Improve communication with withdrawn people.

Nurses to help service users help themselves.

Increasing nurses’ confidence when interacting with service users.

Improve team relations and ward culture.

Step 3: specify target behaviour(s)

EBCD focuses on identifying participants’ improvement priorities as a way of bringing about change that is meaningful to service users, carers and clinicians. 39 We used the BCW to examine each of the four joint improvement priorities. At the joint workshop, the co-design team formed into smaller groups with equal numbers of service users and clinicians. Each group completed a written exercise where they examined the joint priorities and associated behaviours in terms of who needs to perform the behaviour, what the person needs to do differently to achieve change and when, where and with whom they will do it ( table 2 ). (See online supplemental file 3 for example of written exercise.)

Specification of behaviours for joint improvement priorities

Step 4: identify what needs to change

From our review and semistructured interviews with service users, carers and clinicians, the research team identified 26 barriers to engagement and mapped them to the COM-B/TDF domains. The barriers were discussed with participants at the feedback workshops to ensure credibility. At the joint workshop participants matched the barriers to their four joint improvement priorities. The barriers related to each COM-B component are discussed below, with the corresponding TDF domains presented in parentheses.

Participants agreed that nurses often had limited knowledge and inadequate training in therapeutic engagement techniques (skills and knowledge):

Although I’ve been doing this for almost five years it’s like sometimes with certain patients you just don’t know what to say…I wish there could be some training to understand that stuff.—RMN6

Nurses also felt that the very nature of having a mental health problem could make it difficult to engage, and while service users agreed that their mental illness and medication effects could negatively impact engagement (memory/attention/decision process), they were able to describe helpful engagement techniques that nurses could employ, even with the most acutely unwell people. This further highlighted the need to improve nurses’ engagement skills:

Sometimes you have a lot more patients who are unwell or sometimes they’re less unwell, so engagement fluctuates week on week from that point of view.—RMN2

Opportunity

It was felt that there needed to be a cultural shift on the ward and within the organisation so that nurse–patient engagement activities were supported and valued in the same way as other tasks such as hourly observations or administrative duties (social influences):

It was a numbers game, everyone’s taking handover, another one’s doing checks, some are on break…in an ideal world allocate friendly HCAs just to sit with patients.—SU7

There was unanimous agreement that lack of resources negatively impacted on nurses’ ability to engage therapeutically:

The problem for me lies on the number of staff, that is not enough…—C1

This created an untherapeutic ward environment where ‘ professionals would run around like mad rabbits not giving any attention to the patients ’.—SU2 (environmental contexts and resources)

Nurses felt that they could not always trust all members of their team to carry out the job in the right way. This created a feeling of helplessness for some nurses, which deterred them from engaging therapeutically (beliefs about capabilities):

I became very aware that when there is an incident, I’m left on my own…I stopped trusting the team…I couldn’t rely, therefore I needed to take a step back from the patients.—HCA2

Service users were also deterred from approaching nurses for engagement because they felt nurses often did not understand their problems or would punish them if they asked for therapeutic engagement too often (beliefs about consequences):

I kept myself to myself because even when I asked for simplest of things I was made to wait for ages so I would get frustrated, but if I showed frustration no doubt that would be on my notes and I would get set back.—SU4

As well as issues of trust, the ward staff felt as though their team were transient, with many long-standing nurses leaving to work elsewhere. This led to a lack of shared responsibility. Therapeutic engagement could easily ‘ fall through the cracks ’—HCA1, and when poor-quality engagement was witnessed, it was rarely followed up by a senior member of the team. This made some nurses feel they could not be bothered to engage:

I mean to put it blunt; I know it sounds really bad…I can’t be bothered.—RMN5

There was also a blurring of professional roles, where although nurses knew they should engage, they left it to other professionals such as the occupational therapist or activities coordinator:

I can completely understand why nurses want separate roles because they would say you don’t do our job so why should we do yours, but I do take people out on escorts and I do blur the boundaries there.—PT1.

When asked to give examples of nurse–patient engagement, many service users spoke about engagement with professionals other than nurses. This shows both the lack of engagement from nurses and the difficulty service users have in delineating between the nursing role and the role of other health professionals (social/professional identity).

There was a general sense from nurses that therapeutic engagement ‘ didn’t always help people ’—RMN8 (optimism). This led some nurses to feel anxious about engaging therapeutically, particularly when they felt they did not have the required skills. When this was coupled with feelings of frustration at the perceived lack of managerial support, nurses reported feeling drained, burnt out and demotivated (emotions):

One of the biggest problems is the management style which on paper, yes, it seems to be doing everything right, but in practice they have a very poor relationship with their staff and that does impact on performance…I just feel like no one cares about you, so why give up your time?—RMN3

Stage 2: identify intervention options

Step 5: identify intervention functions.

PPI and advisory group meetings highlighted that some of the terminology used to describe intervention functions would not be suitable to use with our participants. Words such as ‘coercion’ can have negative connotations to mental health service users. Instead, practical examples that captured the essence of each intervention function were provided to participants at the joint co-design workshop. In a written exercise they were encouraged to use these examples to think about intervention functions that could address their four joint improvement priorities. Where possible we modelled these examples on illustrations from interviews with service users, carers and clinicians. Where this was not possible, we developed examples from the BCW book 36 ( table 3 ).

Practical examples of behaviour change wheel functions given to co-design team

Participants identified five intervention functions that were relevant to bringing about the desired change. These were (1) training; (2) education; (3) enablement; (4) coercion; and (5) persuasion. Through discussions with senior management, the research team also identified restriction as a relevant function. The links between the COM-B/TDF domains and the intervention functions are shown in table 4 .

The behaviour change intervention co-design process and components of the resulting Let’s Talk intervention toolkit

Step 6: identify policy categories

The BCW includes policy categories which may help to support the delivery of an intervention. Through discussion with senior management, the research team identified communication/marketing, guidelines and social planning as potentially relevant to facilitating our intervention. As such, the Principles of Engagement described in the introduction of this paper were included within Trust policy on therapeutic engagement and observations, and these principles will be directly linked with other components of the intervention, such as a training film described below.

Stage 3: identifying intervention content and implementation options

Steps 7 and 8: identify bcts and mode of delivery.

Rather than provide participants with a long list of BCTs, the written exercise at the joint workshop encouraged them to design intervention strategies they thought relevant to each of the four priorities and its influencing factors. The research team retrospectively assigned BCTs to the participants’ examples and selected further BCTs and intervention strategies not identified during the joint workshop. These were the basis for the development of the first intervention prototype.

The prototype was further refined through an iterative process of email exchanges, telephone calls, a PPI meeting, seven small co-design team meetings and finally presentation of the work at an organisation-wide acute care forum. As per the BCW guide, 36 the affordability, practicability, effectiveness/cost-effectiveness, acceptability, side effects/safety and equity (APEASE) criteria were used in an adapted form (see online supplemental file 4 ) to stimulate discussion and ideas. These criteria ultimately informed the choice of intervention strategies for each improvement priority.

Fourteen BCTs were considered relevant to the Let’s Talk intervention toolkit. Table 4 shows the link between each phase of the behaviour change intervention design process, the 14 BCTs and the intervention strategies and modes of delivery which resulted from the co-design process.

The Let’s Talk toolkit consisted of four main components, linked to the co-design team’s four joint improvement priorities:

A 30 minute training film for nurses, delivered by service users and carers to be shown to nurses at the start of the intervention. Service users and carers discuss good and bad engagement techniques and personal accounts of their experiences of engagement while an inpatient, structured by our model of engagement.

An illustrated workbook called My Conversation Companion which includes guided exercises that nurses and service users can do together to help structure therapeutic conversations.

Signs attached to the outside of service users’ bedroom doors to enable them to indicate, with a sliding panel, whether they would like engagement time or not. The signs are linked to the hourly nursing observation record, where each hour nurses will be required to record if a service user has requested engagement and if that request has been fulfilled. ‘Missed engagement’ will be handed over at each nursing shift with the expectation that it is fulfilled that day. Observation records will be audited each month and feedback given to the nursing team. Additionally, an illustrated sign on the inside of service users’ doors will encourage service users to use the signs if they want to engage.

Changes to nurses’ daily routines, for example, during handover, time will be made to check in with the nursing team and offer additional support to any team member that needs it that day. Additionally, quarterly facilitated workshops will bring clinicians and service users together to discuss, reflect and improve practice.

While conducting this work, the organisation was simultaneously discussing the potential addition of one extra staff member per shift. Our co-design team felt this would be beneficial to improving therapeutic engagement; however, a decision on this is yet to be made. Through discussions with the chief nurse, assistant director of nursing and divisional medical director and presentation of the work at an acute care forum it was agreed that the Let’s Talk intervention would support the relaunched implementation of PET within the organisation. Discussion with participants revealed that they supported this and considered some form of PET essential to support nurses to use Let’s Talk in practice. See online supplemental files 5 and 6 for the toolkit.

The delivery of high-quality nurse–patient therapeutic engagement is a complex issue that requires input from service users, carers, clinicians and researchers alike. Interventions to improve engagement must be multifaceted and encompass service users, carers and clinicians’ capabilities, opportunities and motivations to engage. We used the methodical and evidence-based framework of the BCW to guide intervention development within a co-design process. This enhanced the process by supporting its ‘intrinsically desirable qualities’ 52 with a robust theoretical underpinning that facilitated a full analysis of existing barriers and behaviours among its principal stakeholders. Although Larkin and colleagues 53 suggest that it may be unrealistic to expect co-design participants to generate solutions to long-standing problems within a short space of time, supporting participants’ ideas with a systematic and methodical theory of behaviour change may help mitigate that limitation.

Recent literature encourages a systematic, comprehensive and transparent approach to intervention development. 40 However, many behaviour change interventions are poorly defined and do not use consistent language to describe their mechanisms of action 54 55 making it difficult to pinpoint what did and did not work, which also reduces the ability to compare such interventions. 41 The BCW enabled us to identify, understand and describe the mechanisms of action behind Let’s Talk which is likely to both improve its effectiveness 56 and enable us to review and refine intervention targets after preliminary testing. It also emphasised the importance of addressing nurses’ capability, opportunity and motivation to engage. Previous interventions such as PET focus predominantly on the opportunities nurses have to engage, but do not consider whether a nurse may be capable or motivated to engage. This may explain why evaluations of PET have not shown improvements in the quality of engagement. 57 To our knowledge, this is the first intervention aimed at improving engagement to be developed and presented in this comprehensive, systematic and transparent manner.

Although systematic, the BCW approach may be considered somewhat prescriptive. This can clash with the underlying principles of co-production and co-design, which demand democratic, innovative and creative techniques. 58 59 The concept of co-production in mental health was not commonplace even 5 years ago. 60 Traditionally, professional knowledge had a higher status than service users’ lived experiential knowledge. 61 62 Despite some notable exceptions (eg, ref 63 64 ), service user participation in research was, and often still is, tokenistic, with participants having little influence over defining the problems or required changes. 62 65 It was essential that our process acknowledged, explored and addressed these power differentials so as not to reinforce these entrenched ideals.

Academic language and terminology can preserve power differentials and compromise user and clinician participation. 66 67 People who suffer from mental health problems experience effects that can negatively impact cognition and concentration, often exacerbated by medications. 68 The use of overly technical language may disproportionally affect people from this group and may lead to exclusion and disempowerment, 69 which mirror some of the alienating experiences faced while an inpatient on acute wards (eg, ref 70 ). While the COM-B model uses relatively simple terminology, 40 the language used to describe the intervention functions was particularly problematic. Intervention functions such as ‘coercion’ and ‘restriction’ may have triggered difficult emotions for some of our participants. These words describe negative ward experiences, for example, when clinicians coerce service users into taking medication, 71 or when liberties are restricted due to treatment under the Mental Health Act 1983. 48 This was also true of the clinicians who participated in our study. Suggesting that they lacked ‘skills’ or ‘knowledge’ was likely to alienate them from the process and make them feel devalued.

To ensure fidelity to the underlying principles of co-design we therefore tailored the BCW approach to the needs of the co-design team. The research team found that providing practical examples of each intervention function, using language from the service users, carers and clinicians’ interviews, was a suitable way of adhering to the principles of co-design and using evidence-based theory in a non-alienating, confirmatory way. Although APEASE criteria were not considered to contain triggering terminology, some of the language was overly technical which also risked alienating co-design team members. The research team therefore translated the APEASE criteria into more accessible language. Furthermore, the co-design team were encouraged to design their own intervention content based on the behavioural analysis. The research team retrospectively assigned BCTs and confirmed these with the co-design team. This adhered to the underlying principles of co-design by foregrounding service user experience (rather than privileging academic knowledge over experiential knowledge), while also creating an intervention that could be clearly and methodically described through evidence-based theory and language.

Reflective accounts from three of our co-design team support the steps taken by the research team to ensure an inclusive, participatory process. While the potential for experiential reflections to trigger difficult emotions was anticipated, team members’ expressed anxieties were soon ‘ quashed ’ by a ‘ safe and secure ’ environment in which members ‘ never felt pressured or judged ’. This allowed the service users, carers and clinicians ‘ to support each other on an equal basis and share a common goal ’. The opportunity to share personal experiences emerged as an important dynamic across the three reflective accounts. It was variously described as ‘ a privilege ’, and an ‘ incredibly moving ’ and ‘ powerful ’ experience that allowed their expert knowledge to be used ‘ to implement new models of care and improve quality standards ’ that ‘ would make a real difference ’. Consequently, these co-design team members described an ‘ enjoyable ’ and ‘ rewarding ’ process that engendered feelings of pride and empowerment. One member referred to it as a ‘ life changing ’ event that promoted self- esteem and self-awareness, and another reported the development of reflective skills. Notable also was the wider outreach and consultation that members undertook through liaison with professional colleagues, service users and carers in various institutional and community arenas, which mirrored their experience of the co-design process. This allowed stakeholders to express any concerns, ask questions and provide feedback. In turn, this led to ‘ product refinements to make the workbook more accessible and easier to read ’. As well as personal impact, these team members described interpersonal benefits including ‘ feeling (more) engaged with mental health professionals ’ and managing to ‘ engage in some really good work ’ with patients. They were also optimistic about the likely impact of this work moving forward. They sensed that service users and clinicians were ‘ inspired ’ by their work and believed the workbook would have ‘ a ripple effect…and help create a cultural change within the organisation ’. Each of the reflective accounts is provided in full in online supplemental file 7 .

Beresford 72 argues that front-line clinicians can also be a marginalised group whose voices are often excluded. It is also vital to consider the needs of the service provider while embarking on participatory work. 73 We implemented several facilitative measures such as providing backfill money so clinicians could attend the feedback and joint workshops and offered flexibility with participation in the small co-design teamwork, for example, emailing instead of face-to-face meetings and piggybacking staff meetings. However, enabling clinicians to participate equally was challenging. Unfortunately, organisational structures such as shift patterns and staffing levels impacted on clinicians’ ability to fully participate. Regular staff meetings or reflective practice groups were also not in place. When given the opportunity to participate, clinicians were motivated, and meaningful participation was possible during the feedback and joint workshops. However, without organisational support structures to provide clinicians time to undertake the ongoing co-design work, much of the prototyping and iterative development of the intervention components were undertaken by the service users. This is a common issue evident in co-design studies in both mental health and general settings. 74 There is a need for healthcare organisations to reconfigure their services so clinicians can meaningfully participate in such endeavours and encourage a sense of joint ownership over the work.

Although the process was highly collaborative and involved service users, carers and clinicians to varying degrees, it was conducted at just one NHS site, which represents a possible limitation. Transferability of our processes to other settings cannot be guaranteed. However, to our knowledge, this is the first time the BCW has been translated for use with participants who have mental health problems and used within an integrated co-design-behaviour change process. This new and novel approach will require further testing to ascertain whether it is suitable and translatable to other intervention development processes. Given that participants were a self-selecting, motivated sample of clinicians, service users and carers, their views may not be representative of all patients and clinicians in the organisation. During the final stage of co-designing Let’s Talk the global COVID-19 pandemic took place. We continued our co-design activities remotely; however, a planned quasiexperimental pretest/post-test using a structured observational tool 49 had to be postponed. The tool examines the amount, type (eg, interactive, individual, verbal, non-verbal or solitary) and quality (eg, positive feedback, praise, smile, ignoring, reprimand, discouragement, neutral behaviours) of nurse–patient interactions. 49 Pretest data on one control and one intervention ward were collected in April to June 2019 and we plan to collect post-test data when we are able to do so and publish the results of this study.

Conclusions

This paper has described the implementation of a new theory-driven co-design-behaviour change approach used to develop the Let’s Talk intervention toolkit. It offers tools that others may use, or adapt as necessary, to implement the approach in their settings. It also describes the behavioural mechanisms behind the Let’s Talk intervention toolkit to improve the amount and quality of nurse–patient therapeutic engagement on acute mental health wards. Our paper makes a timely and novel contribution to further both participatory methods and behaviour change theory. The approach enhances EBCD by introducing a robust behavioural change theory to help guide the development of a complex intervention. In turn, our participatory approach also enhances the BCW by setting out a practical guide on how to meaningfully involve service users and other stakeholders when designing complex implementation interventions.

Ethics statements

Patient consent for publication.

Not required.

Ethics approval

Ethical approval for the study was obtained from the London Fulham Research Ethics Committee (reference: 18/LO/2193).

Acknowledgments

The authors thank all the service users, carers and clinicians who gave their time to the codesign process. The authors also thank Iain Ryrie, publication coach at King’s College London, for his assistance with early drafts of this paper. And, finally, thank you to Soak Digital for designing figure 1, Peter Moorey for his illustrations as part of the Let’s Talk toolkit and Ioanna Xenophontes and Sarah Combes for cofacilitating the EBCD workshops.

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Supplementary materials

Supplementary data.

This web only file has been produced by the BMJ Publishing Group from an electronic file supplied by the author(s) and has not been edited for content.

• Data supplement 1
• Data supplement 2
• Data supplement 3
• Data supplement 4
• Data supplement 5
• Data supplement 6
• Data supplement 7

Twitter @SarahMc_RMN, @cityalan, @gbrgsy

Contributors SM conceived the study, secured the research funding, facilitated the codesign process, analysed the data, contributed to designing intervention components and wrote the manuscript. GR, AS and VT participated in the design and coordination of the study, contributed to the analysis and helped draft the manuscript. NC, VDM and CS participated in the codesign process, contributed to designing intervention components and wrote reflective accounts for the manuscript. All authors read and approved the final manuscript.

Funding This report is independent research supported by the National Institute for Health Research (HEE/NIHR ICA Programme Clinical Doctoral Research Fellowship, Ms Sarah McAllister, ICA‐CDRF2017‐03‐034). The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research, or the Department of Health and Social Care.

Disclaimer The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health and Social Care.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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