- Open Access
Using Normalization Process Theory in feasibility studies and process evaluations of complex healthcare interventions: a systematic review
Implementation Science volume 13, Article number: 80 (2018)
Normalization Process Theory (NPT) identifies, characterises and explains key mechanisms that promote and inhibit the implementation, embedding and integration of new health techniques, technologies and other complex interventions. A large body of literature that employs NPT to inform feasibility studies and process evaluations of complex healthcare interventions has now emerged. The aims of this review were to review this literature; to identify and characterise the uses and limits of NPT in research on the implementation and integration of healthcare interventions; and to explore NPT’s contribution to understanding the dynamics of these processes.
A qualitative systematic review was conducted. We searched Web of Science, Scopus and Google Scholar for articles with empirical data in peer-reviewed journals that cited either key papers presenting and developing NPT, or the NPT Online Toolkit (www.normalizationprocess.org). We included in the review only articles that used NPT as the primary approach to collection, analysis or reporting of data in studies of the implementation of healthcare techniques, technologies or other interventions. A structured data extraction instrument was used, and data were analysed qualitatively.
Searches revealed 3322 citations. We show that after eliminating 2337 duplicates and broken or junk URLs, 985 were screened as titles and abstracts. Of these, 101 were excluded because they did not fit the inclusion criteria for the review. This left 884 articles for full-text screening. Of these, 754 did not fit the inclusion criteria for the review. This left 130 papers presenting results from 108 identifiable studies to be included in the review. NPT appears to provide researchers and practitioners with a conceptual vocabulary for rigorous studies of implementation processes. It identifies, characterises and explains empirically identifiable mechanisms that motivate and shape implementation processes. Taken together, these mean that analyses using NPT can effectively assist in the explanation of the success or failure of specific implementation projects. Ten percent of papers included critiques of some aspect of NPT, with those that did mainly focusing on its terminology. However, two studies critiqued NPT emphasis on agency, and one study critiqued NPT for its normative focus.
This review demonstrates that researchers found NPT useful and applied it across a wide range of interventions. It has been effectively used to aid intervention development and implementation planning as well as evaluating and understanding implementation processes themselves. In particular, NPT appears to have offered a valuable set of conceptual tools to aid understanding of implementation as a dynamic process.
Implementation theories are useful. They provide explanations for relevant phenomena, propose important research questions and frame the collection and analysis of data . These explanations are generalizable and facilitate comparative studies. Implementation researchers now have a wide range of useful theoretical tools at their disposal [2,3,4]. Normalization Process Theory (NPT) [5,6,7,8,9,10] is one of these. It identifies, characterises and explains mechanisms that have been empirically demonstrated to motivate and shape implementation processes and affect their outcomes. This paper presents a systematic review of studies of healthcare interventions informed by NPT.
What is NPT and what does it do?
NPT is a theory of implementation that focuses on what people—both individuals and groups—do rather than what they believe or intend, and it has been built up from studies of practice in many different healthcare systems. This means that it focuses attention on aspects of individual and collective behaviour shown to be important in empirical studies of implementation processes. The development of NPT first involved the iterative development of a robust generic theory of implementation [5,6,7,8,9, 11, 12]. From this, tools were developed to assist implementation practitioners and researchers [13,14,15,16] in thinking through and measuring important elements of implementation processes. In its most recent iteration, we have shown how the basic mechanisms characterised in NPT function as self-organising mechanisms in complex adaptive social systems . Theory development in NPT has been iterative, with three phases of development around practical questions.
Objects: How are components of complex interventions operationalised by their users? In the first iteration of the theory—the Normalization Process Model (NPM) [5, 6]—we identified the importance of collective action in routinely incorporating complex interventions into everyday practice. We showed how collective action was organised around interactions between users and the properties of intervention components.
Agents: What is the work of implementing a new technique, technology or organisational intervention? In the second iteration of the theory—Normalization Process Theory (NPT) [7, 8]—we characterised mechanisms (coherence, cognitive participation, collective action and reflexive monitoring) that motivate and shape implementation processes and explained their operation.
Contexts: How are structural and cognitive resources for implementation mobilised and what mechanisms lead to variations in implementation processes over time and between settings? In the most recent iteration of the theory—Extended Normalization Process Theory (ENPT) [9, 10]—we pointed to the dynamic role of implementation contexts in the mobilisation and negotiation of implementation processes.
Underpinning these practical questions is one that is fundamental to the social and behavioural sciences—and especially to behavioural economics, sociology and social psychology—which is how can we best understand the dynamics of human agency under conditions of constraint ? The important implication of this question is that well-designed, theoretically informed studies in implementation research actually offer opportunities for basic investigations in the social sciences.
The purpose of this review
A review by McEvoy et al. , published in 2014, provided a qualitative synthesis of 29 early and heterogeneous studies in which NPT was used. It drew attention to a positive response from healthcare researchers to the theory, but it also made three important critical points about the emerging NPT literature. McEvoy et al.  pointed to the ways that early studies using NPT did little work to justify the choice of theory, called for the prospective application of NPT to data analysis and collection and stressed the importance of moving beyond single stakeholder perspectives.
In the period since McEvoy et al.’s review , studies using NPT have proliferated. There are now a large number of protocols, empirical studies and reviews in which NPT plays a role. Importantly, a large number of NPT studies have now been completed by groups who are independent of the theory’s architects. It is therefore an opportune time to undertake a qualitative systematic review that will (i) identify and characterise the uses and limits of NPT in research on the implementation and integration of healthcare interventions and (ii) explore NPT’s contribution to understanding the dynamics of these processes.
Systematic citation searches
As the aim of this qualitative systematic review was to identify the uses of NPT in research on the implementation and integration of health care interventions since the publication of the first iteration of the theory in 2006, our search strategy was focused on citations. Following Kirk et al.’s review of reports of the Consolidated Framework for Implementation Research , we searched two bibliographic two databases (Scopus and Web of Science), and a search engine (Google Scholar), to search for citations of key papers that developed or expounded the main constructs of NPT [5,6,7,8,9, 11, 12], papers that developed NPT related methods or tools [13,14,15] and citations of the NPT web-enabled on-line toolkit (www.normalizationprocess.org) . Searches were conducted by AC, MG, CRM, MM and TLF. The sensitivity of the search strategy was tested against a database of studies using NPT that had been collected by three of the co-authors (CRM, TR, TF). All studies already known to use NPT at December 2015 were identified by the first round of systematic searches. Searches were initially undertaken in June 2015 and were updated in December 2015, August 2016 and March 2017. A final search was undertaken in December 2017.
Inclusion and exclusion criteria
We included the following: peer-reviewed English language journal articles reporting empirical research on the implementation of healthcare interventions, in which NPT was the primary analytic framework (applied either prospectively in study design and data collection, or retrospectively in the interpretation of already collected data) and which were undertaken in any healthcare setting. We define an empirical paper as one that contains evidence of data collection and analysis. We included studies that used any method of empirical investigation (qualitative, quantitative, and mixed methods).
We excluded the following: papers in which NPT was used as a framework for systematic reviews or meta-syntheses; papers solely on patient and caregiver experiences; papers in which NPT was not the primary analytic theory; editorials, theory and methods discussion papers; papers containing passing references to NPT; study protocols; papers describing work undertaken in settings other than healthcare; and papers published in languages other than English. We also excluded theses or dissertations, books and book chapters, conference proceedings and abstracts. We did not exclude papers on the grounds of methodological quality. We already knew that the literature ranged from student projects through to process evaluations in large and well-designed clinical trials in which NPT informed all activities from design through process evaluation and follow-up, to interpretation of trial outcomes. All studies were equally interesting to us, because we were searching for information about the way in which the theory was used rather than the summative results of NPT analyses.
Screening started with an assessment of citations and abstracts’ relevance by reviewers who had not been involved in the development of NPT (AC and MM). Reports that met eligibility criteria were obtained in full text. Full-text papers were screened by pairs of reviewers (AC with MM or CRM; MB with CRM; or CRM and TF) working independently of each other. Full-text screening consisted of identifying papers where NPT was clearly the analytic framework for an empirical study. Because no ‘one best way’ to operationalise NPT and its constructs has been prescribed, we did not apply judgments about this to screened papers. This meant that screening involved a simple Yes/No question, and references were sorted within Endnote Libraries accordingly.
We developed an extraction instrument, (see Additional file 1: Appendix 1). Data were extracted by all authors except CMM, FSM and EM. To avoid conflicts of interest, authors or co-authors of included papers were not involved in extracting data from those papers. Data were extracted on authors, year of publication, health care problem addressed, study type and methods, data collection procedures, how NPT was used in the study and whether this had been pre-specified in the study protocol. We looked for data on whether and how NPT had contributed to understanding the dynamics of the processes of implementation and integration, and for authors’ views about the limitations of NPT in terms of both its scope (what the theory explains) and application (what happens when researchers use the theory). As this was a qualitative review, we included data from both the results and discussion sections of included papers.
Coding and initial interpretation work was undertaken using the extraction instrument. To ensure consistency, CRM and TLF jointly checked coding on 75/130 of included papers, and CRM and CMM jointly checked categorisation of all included papers. The analysis aimed (i) to identify and characterise the uses and limitations of NPT in research on the implementation and integration of healthcare interventions and (ii) to explore NPT’s contribution to understanding the dynamics of these processes. Hence, we started by describing how NPT had been used and subsequently analysed the data to explore the ways that mechanisms defined by NPT have been revealed to operate. We sought to understand the relative importance of specific NPT constructs across different settings (core processes and mechanisms) and differences that seemed to apply in relation to different intervention types and healthcare systems (contingent processes and mechanisms).
Public registration of the review
PROSPERO deemed this review ineligible for public registration on the grounds that NPT was not a healthcare intervention.
Searches revealed 3322 citations. In Fig. 1, we show that after eliminating 2337 duplicates and broken or junk URLs, 985 were screened as titles and abstracts. Of these, 101 were excluded because they did not fit the inclusion criteria for the review. This left 884 articles for full-text screening. Of these, 754 did not fit the inclusion criteria for the review. This left 130 papers presenting results from 108 identifiable studies to be included in the review.
Types of studies
In this review, 130 papers reported the application of NPT in 108 identifiable studies. Included articles presented both controlled (n = 26) and uncontrolled (n = 82) studies.
In Table 1, we show that NPT was employed in 26 controlled studies—mainly complex intervention trials—and these generated 40/130 (30.8%) articles [19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58]. These included an intervention design study (n = 1), feasibility studies (n = 5), process evaluations (n = 19) and retrospective documentary analyses (n = 1), embedded in complex intervention trials. Three of these studies used mixed methods, and one  was a survey. The remainder (n = 22) all used qualitative methods.
In Table 2, we show that NPT was employed in in 82 uncontrolled studies, and these generated 90/130 (69.2%) articles [59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,112,113,114,115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134,135,136,137,138,139,140,141,142,143,144,145,146,147,148]. These included feasibility studies (n = 20) and process evaluations (n = 54), and seven were what we have called ‘field studies’ which focused on general conditions in which interventions might take place, rather than the progress of specific interventions. One study was an ethnography of a set of socio-technical practices . Qualitative methods were used in 72 studies. Of the remainder, seven were mixed methods studies, two were surveys, and one was a prospective cohort study.
What was being implemented?
Studies included in this review fell into seven categories. The most numerous group of studies were those concerned with service organisation and delivery (n = 29, 26.9% [23, 27, 32,33,34,35, 43,44,45,46, 58, 76, 79, 82, 84, 86, 89, 91, 92, 99, 105,106,107, 110, 115, 116, 119, 122, 127, 133,134,135,136, 140, 146, 148]). For example, in the UK, Grant et al. [34, 35] evaluated a complex intervention aimed at reducing risk in prescribing in primary care. They used NPT in ‘identifying and describing the components and sub-components of the intervention’ to understand ‘the nuances associated with collective implementation’. The next most numerous group of studies focused on the implementation of diagnostic and therapeutic interventions (n = 28, 25.9% [19, 24,25,26, 28,29,30,31, 36, 37, 47, 48, 55,56,57, 67, 69, 78, 80, 90, 95, 97, 98, 103, 104, 111, 117, 123, 126, 137, 142, 143]). For example, in the USA, Hoberg et al.  examined the implementation of a new form of group therapy for people with mental health problems, while Leon et al.  showed how provider initiated testing and counselling for HIV was successfully normalised in a South African setting. Studies of implementation of E-Health and telemedicine—including telephone advice—were also numerous (n = 21, 19.4% [21, 22, 49, 59,60,61,62, 66, 71, 73,74,75, 83, 85, 87, 88, 93, 112, 114, 118, 125, 128, 130, 145]). Here, a Norwegian team led by Wilhelmsen et al.  showed how problems of participation and action—and especially the interactional workability—of a service providing internet-based cognitive behavioural therapy led to ambivalence on the part of general practitioners about its use, to low levels of follow-up and to doctors reverting to ‘standard treatment’ . Less numerous (n = 11, 10.1%, were studies of the implementation of screening and surveillance tools [38,39,40,41,42, 53, 64, 65, 72, 77, 113, 129, 132, 139, 144]). In a feasibility study, Ahmed et al.  showed that integrating a family history questionnaire about common genetic diseases into the workflow of primary care was unlikely without significant changes to the pattern of GP-patient interactions, and these were unlikely to be supported by clinicians. Such professional factors also affected the outcome of studies of decision support and shared decisionmaking (n = 8, 7.4% [81, 96, 100, 108, 109, 120, 121, 124, 131, 147]). In this category, in the USA, Scalia et al.  compared the implementation and integration of decision support tools between two major healthcare systems. This study raised important questions about how the interactions between clinicians’ (micro-level) experiences of the workability of complex interventions and meso-level organisational processes through which reflexive monitoring mechanisms play out their effects. Some studies were also explicitly concerned with implementing change in professional roles (n = 7, 6.5% [20, 54, 63, 70, 94, 101, 138]). For example, Thomas et al. [56, 57] showed how changes in roles and workload interacted to promote the routine embedding of an intervention intended to manage incontinence in stroke patients. Finally, a small group of studies were concerned with guideline implementation (n = 4, 3.7% [50,51,52, 68, 102, 141]). Here, Vest et al.  described a study in the USA of the implementation of guidelines for the management of chronic kidney disease in primary care. They asserted that NPT could not only identify key barriers to practice but could also guide intervention choice.
Was what was being implemented evidence-based?
Studies included in this review were mainly focused on reporting the implementation of complex healthcare interventions. Most of these studies had a translational component and made some claim about the evidence underpinning interventions. This evidence was heterogeneous and included qualitative studies [120, 121], implementation appraisals , meta-ethnographies  and previous trial results [38,39,40,41]. However, the most common appeal to an evidence base in studies included in this review was through references to systematic reviews and rigorously developed clinical guidelines. Across the studies included in the review, 64/108 (59.2%) were linked to such support by their authors [149,150,151,152,153,154,155,156,157,158,159,160,161,162,163,164,165,166,167,168,169,170,171,172,173,174,175,176,177,178,179,180,181,182,183,184,185,186,187,188,189,190,191,192,193,194,195,196,197,198,199,200,201]. As Tables 1 and 2 show, systematic reviews and rigorous guidelines were cited in support of 17/26 (65.4%) controlled studies and 47/82 (57.3%) uncontrolled studies.
How did researchers justify the use of NPT?
As Tables 1 and 2 show, in 54/108 (50%) of the studies included in this review, the use of NPT appeared to have been planned in advance, and this was included in the study protocol. Amongst controlled studies, 19/26 (73%) of studies made explicit reference to including NPT in study protocols, while only 35/82 (42.7%) of uncontrolled studies did so. Not all papers offered a justification for using NPT. For the most part, authors characterised NPT as a conceptual framework that explains implementation processes and thus structures study design and data analysis. For example, Brooks et al.  justify it thus:
‘Normalisation Process Theory (NPT) has been used to consider complex interventions prior to the development of a randomised control trial to test their effectiveness (…). It has also been used in the context of mental health to explore the impact of new forms of collaborative care on the way in which professionals carry out their routines of work in primary care (…). The four constructs (coherence, cognitive participation, collective action and reflexive monitoring) permit a means of appraising factors that might ‘promote and inhibit the routine incorporation of complex interventions into everyday life’ (…). It focuses on the work that people need to do to ensure interventions become ‘normalised’. As a heuristic framework it can support the optimisation of a trial intervention at three points:
supporting intervention design
describing the context of a trial
supporting the interpretation of a trial’s results’ .
Other papers reflected in more general terms on NPT’s empirical grounding (e.g. [28, 50, 52, 67, 73,74,75, 87, 114, 122]) and its usefulness in thinking about implementation design (e.g. [27, 33, 67, 106, 147, 202, 203]).
Did NPT explain implementation outcomes?
In all but one study in the review , there was evidence that implementation outcomes could be explained by reference to the mechanisms specified by NPT. For example, Scalia et al. , state that their study
suggests that patient decision aids that are specifically designed for use in clinical encounters can be embedded in clinical settings, provided there is agreement about the need to use them, that the team members are willing to work together to make sure that such tools can be integrated in existing work patterns, and understood as making a positive overall contribution to the work that has to be performed. These considerations match the mechanisms of the NPT, which provides an explanatory framework for understanding the sustained use of these tools by the two systems examined. The motivation for the use of the Option Grid at CapitalCare was their wish to achieve success in an external quality improvement initiative. At HealthPartners, implementation efforts were motivated by a ‘champion’ physician. The nursing staff also played a pivotal role by systematically identifying eligible patients and providing those patients with the relevant encounter tool. These organizations, in different ways and to different degrees, exhibited coherence, collective action and cognitive participation that supported the sustained use of the tools. The organizational appraisal, in other words, their reflexive monitoring, was positive overall, despite concerns about readability and time pressures.
Implementing patient decision aids into clinical settings is a difficult process (…) In the UK, an implementation program known as MAking Good Decisions In Collaboration (MAGIC) highlighted the need for an organizational coherence, i.e. a widely held and agreed understanding of SDM principles in order to facilitate the implementation of patient decision aids (…). Commitment at multiple organizational levels has been recognized as an important precondition for implementation (…). This lack of commitment was noticeable at the CapitalCare sites that did not use patient encounter tools .
Differences between participant groups were characterised in 69/108 (64%) studies and between settings in 36/108 (33%) studies. For example, Clarke et al.  placed this in the wider context of levels of analysis.
‘This paper briefly considers implementation theories in respect of complex interventions and provides an overview of process evaluations to set the context for the study. We draw on Normalisation Process Theory (NPT) (…) as a conceptual lens through which to explore those features of the implementation process that were intended to secure practice change and to engage caregivers in the program. We also consider the interaction between influential macro and micro contextual factors that affected delivery by multi-disciplinary stroke unit staff and suggest that prior focus on generative mechanisms identified within NPT can be used to inform implementation processes within complex healthcare settings’ .
NPT thus characterises core elements of implementation processes and the factors that shape them, and using NPT enabled researchers to explain the ‘work’ that is involved in implementation. Implementation involves interactions between mechanisms and contexts that are highly complex and emergent. Dynamic elements of context can exercise powerful constraints on action. The sources of these constraints included system-level processes that structured behaviour (e.g. the role of fee for service payments in undermining the implementation of self-care programmes ) and micro-level conflicts within contexts (e.g. disagreements over participation and intervention legitimacy [20, 25]).
How did researchers apply the theory’s constructs?
Implementation processes in NPT are explained by the operation of social mechanisms that motivate and shape collective action. Researchers using the theory employed its constructs in four distinctive ways, irrespective of the iteration of the theory that they used. We show examples of these diagrammatically below. First of all, some researchers clearly found it helpful to see the theory as describing a linear process in time [22, 63], in which the operation of mechanisms followed sequentially from each other (Fig. 2). In these studies, sense-making was seen as a necessary precursor to participation, and a degree of cognitive participation was required before collective action—in the form of an actual implementation process—could take place. Reflexive monitoring was seen as the final stage in the implementation process. However, research reported in this review often focused on feasibility studies or on the early stages of implementation life cycles in process evaluation. This skews their analyses towards the implementation phase of studies rather than their embedding and integration in everyday practice.
As Fig. 3 shows, the focus on the ‘front end’ of studies leads to an emphasis on ‘coherence’ and sense-making work as an obligatory point of departure for implementation processes (e.g. [27, 31, 50, 52, 57, 74, 85, 108, 113, 123, 131, 203]), sometimes at the expense of other activities. Figure 4 suggests a novel analysis of the relationship between mechanisms. Holtrop et al. examined the operation of components of collective action in the restructuring of provider reimbursement. Their analysis emphasised the role of relational integration as a precondition for normalisation. In this context, the operation of one mechanism might be an obligatory point of passage for the others. Holtrop et al.  state that
‘We found that effective care management normalization required relationship development between practice providers and staff and the care manager. Since identification and referral of patients needing care management was key to care management happening at all, the practice personnel understanding and appreciating the care manager role through a relationship with the care manager was critical. This was captured well through the NPT collective action component of relational integration. We interpreted relational integration to be the professional relationship development that occurred when care manager, providers and practice staff work together and understand and appreciate each other’s roles and contribution to patient care. Although it is its own component in NPT, we found it to be more of an outcome that occurred when the other components worked well (contextual integration, skill set workability and interactional workability). (…) We found that when any of the other components were not in place, there was also a lack of development of trust around shared patient care. Since care management is a relationship rich endeavor, the lack of this relationship is a key factor in care management’s disuse’ .
Finally, as Fig. 5 shows, NPT assumes that its constituent mechanisms can operate simultaneously—but unevenly—rather than sequentially. Few studies in this review tracked the implementation of a complex intervention over its whole life. When they did, they tended to present summative rather than a formative accounts. An interesting example of a longitudinal study may be found in work by Tazzyman et al.  that depicted NPT in precisely these terms. They state that the mechanisms specified by NPT are
non-linear and interact dynamically to provide a comprehensive explanation of the implementation processes. NPT was designed to be applied flexibly, can be used at one or more points in a qualitative study, has been successfully used beyond its original field and provides a robust theoretical framework to understand the dynamics of implementation .
Tazzyman et al.  explored the processes that underpinned revalidation of medical practitioners in a qualitative study of senior decision-makers undertaken at three time points (2011, 2013 and 2015). They characterised respondents in their study in NPT terms as ‘sense-makers’ and then explored the process of implementing and embedding of revalidation as a broad policy initiative. They state that their contribution
has been to extend the use of NPT to explore the implementation of a broad and complex policy, with wide ranging implications for an entire profession, and the wider healthcare system. Much previous work using NPT in healthcare has addressed the implementation of micro level interventions. This expanded application of NPT has highlighted a number of factors which seem to have affected the implementation of revalidation. The four dimensions of the framework (see Table 3) had an intuitive relevance and provided a useful explanatory framework for understanding the implementation of revalidation. There is scope to apply NPT more widely to complex social interventions and policy initiatives at the organisational and system level in future .
More usually, longitudinal studies using NPT were process evaluations embedded in large complex intervention trials. As we have noted above and elsewhere , these permitted a more structured analysis of implementation processes and their motivating mechanisms over time [29,30,31, 38,39,40,41, 43,44,45,46, 50,51,52].
How did researchers integrate NPT into their research methods?
Researchers used two main strategies to translate the constructs of NPT into practically useful analytic tools. Some used deductive strategies that relied on framework or directed content [204, 205] analyses and in which interpretation of data was structured prospectively by the theory. These approaches often took the form of relating data to matrices of varying degrees of complexity. In Table 3, we show how Alverbratt et al.  have created a detailed matrix in which they reinterpret and operationalise all constructs and sub-constructs of NPT. This partly replicates the way that these were originally characterised in May and Finch’s account of NPT . This approach defines and sets out all of the constituent elements of the work that drives implementation processes and permits data collection and coding using framework, or directed, content analysis . The approach taken by Alverbratt et al. focuses on translating the content of the theory into practical research questions in a very precise way. Others focused on the main constructs of the theory prospectively, but within a more flexible framework. In Table 4, we show how Røsstad et al.  set out a matrix that links theory constructs to a description of data collected and in Table 5, we show how Nordmark et al. offer an even simpler data matrix, in which core constructs are linked to data collection opportunities . Tazzyman et al.  used an analytic approach included both deductive and inductive elements.
A coding framework was developed using the four domains and sub-domains of NPT by using an adapted version of the NoMAD instrument (part omitted), which was developed to assess implementation processes (Normalization Measure Development is an instrument designed for assessing the implementation of complex interventions). The adapted NoMaD instrument was applied to the transcripts by coding evidence of the sub-domains in Dedoose . Following coding, two members of the research team (AT and JF) analysed the data across the three interview stages, using the constant comparative method, in order to understand changes and continuities over time. The inductive method of constant comparison analysis involved searching within individual transcripts, making comparison between transcripts within the same cohort, and comparing transcripts from different cohorts for conceptual similarities and differences. This method was combined with the deductive approach of using the four domains on NPT as a framework for the analysis.
Tazzyman et al.’s hybrid approach enabled them to develop a theory-led analysis, without needing to force data into a rigid theoretical framework. However, many studies took a more straightforward inductive approach to data collection and analysis. When studies collected and analysed qualitative data inductively—in the light of NPT—rather than deductively using framework approaches, there was less pressure on them to interpret their qualitative data within an inflexible coding framework. For example, in Table 6, we show how Bamford et al.  described the ways that their inductively generated data categories mapped on to NPT constructs. This group of papers includes a group of highly illuminating studies across the life course of complex intervention trials. Bamford et al.’s  process evaluation of the CAREDEM trial, and Kennedy et al.’s [43,44,45,46] account of the WISE trial explain how structural factors militated against processes of cognitive participation. In their longitudinal accounts of the MOVE [38,39,40,41] and STEPPING-UP [29,30,31] Trials, Hooker et al. and Furler et al. show how mechanisms of coherence, cognitive participation and collective action interact to support the embedding of complex interventions in practice. Importantly, these studies also showed that the intervention remained in play once the trials themselves had concluded.
How did users’ criticise NPT
Critique of NPT as a theory was rare amongst the papers included in this review. However, it was not absent. For example, Clarke et al.  criticised an over-emphasis on agency at the expense of implementation contexts in NPT.
‘While May et al (…) acknowledge that the NPT generative mechanisms are in dynamic interaction with local contexts and external drivers, the framework primarily addresses the mechanisms. Indeed, the theory tends to place undue emphasis on individual and collective agency without explicitly locating this within, and as shaped by, the organisational and relational context in which implementation occurs’ .
Segrott et al.  take this further. They point to what they perceive as a focus on the agency of those involved in implementation, as opposed to those who experience the effects of that agency.
‘ENPT places considerable emphasis on the notion of implementation as an expression of agency. However, the agents in question appear to be mainly conceptualised as professional practitioners (e.g. nurses), rather than the participants who receive interventions. There is scope to consider further how the key constructs of ENPT can be applied to understand how participant (and non-participant) agency may shape whether interventions become integrated and embedded within delivery systems’ 
Beyond this, Alharbi et al.  criticised NPT for presenting a normative model of implementation that paid insufficient attention to idealised temporal aspects of implementation, a point echoed by Alverbratt et al. . Critique was more often about the interaction between theory and method. Some articles (9/108) observed that NPT constructs overlapped, that the technical vocabulary of the theory was difficult and that as a result coding qualitative data was difficult [39, 44, 48, 59, 64, 67, 82, 99, 207]. Problems of this nature seemed less evident when researchers used a more inductive approach to qualitative data analysis (e.g. [25, 26, 38,39,40,41]) than they did when authors employed a framework approach (e.g. [39, 99]).
Key results of the review
In this review, we identified 108 discrete studies of complex healthcare interventions and related implementation processes. These studies were reported in 130 journal articles published after 2008. In papers included in this review, researchers collected and analysed their data in ways that effectively provided a basis (i) for intervention design and implementation planning and (ii) for understanding the dynamics of implementation, embedding and integration. Three key results of the review are as follows:
NPT appears to accurately depict important elements of implementation processes, and the constructs of the theory can be applied in a stable and consistent way within and between studies.
NPT has provided conceptual tools for a large body of feasibility studies and process evaluations of complex healthcare interventions. It has successfully explained the outcome of such intervention studies.
NPT can be applied flexibly and can be understood and mobilised by researchers and practitioners with diverse professional backgrounds, working across a variety of healthcare settings.
The use of NPT has coalesced around two main types of study: feasibility studies and process evaluations. However, unlike McEvoy et al.’s  review of NPT studies, we found that authors were justifying their choice of theory, and NPT was more frequently embedded in study protocols and thus being operationalised prospectively. However, concerns raised by McEvoy et al. about the lack of prospective application do not just apply to NPT. For example, Kirk et al.  point to the problem of low levels of prospective use of the CFIR  and PARIHS  frameworks. They point to the additional problem of lack of integration of theory into implementation research. Against this background, our review suggests that—although some authors have experienced difficulty with NPT’s technical vocabulary—users of NPT appear to be able to operationalise its concepts in consistent, stable ways to inform their work, and we can see evidence of theoretical integration in four kinds of studies.
Studies that used NPT constructs as sensitising devices to form questions about implementation processes, and then related their conclusions back to the predictions of the theory (e.g. Grant et al. [34, 35]).
Studies that collected and analysed data inductively in the light of NPT and then developed an analysis of the ways that different mechanisms work to motivate and shape implementation processes. The major papers by Clarke et al. [34, 35] and Hooker et al. [38,39,40,41] are important examples of such work. So too are Kennedy et al.’s accounts of the WISE trial [43,44,45,46].
Studies that treated qualitative data deductively and used prescheduled coding matrices for framework or directed content analysis. Nordmark et al.’s work  offers an example of the way that this approach to theory driven analysis can be handled without ‘fitting’ or ‘shoehorning’ data in a rigid way (see MacFarlane and O’Reilly-de Brún  on techniques to manage this problem in qualitative research).
These different approaches to mobilising theory suggest that NPT’s users have developed flexible explanatory strategies, and we have pointed to some of these in Figs. 2, 3, 4 and 5. In earlier papers [5,6,7,8,9, 11, 12], we have argued that theories are conceptual toolkits that can be used flexibly to deal with practical problems. This means that there is no definitive ‘right way’ to employ NPT. It can be used on its own or in combination with other theories in ways that are locally defined to solve problems in intervention design and evaluation.
Limitations of this review
This review contributes to the literature on the incorporation of theory in implementation research, the benefits of this incorporation and the problems that can arise as a result. There are, of course, limitations to the review. Searches were undertaken in two databases, so it is possible that some studies were missed. It is questionable whether this would have altered the main findings and conclusions. Because Google Scholar is a search engine, and not a database, results of searches using it were not stable. Searches on Google Scholar also identified multiple versions of the same reference (e.g. versions of the published paper on publisher’s websites, records on institutional repositories, versions on personal websites and on academic social media sites such as Academia.edu and ResearchGate.Com). Sorting these involved significant additional work. It did however identify about 20 papers that would not otherwise have been included in the review. One paper was brought to our attention before appearing in any databases; however, subsequent updated searches did identify this paper. Equally, we excluded studies published in languages other than English, although there is some evidence that this is unlikely to be a major limitation .
We deliberately followed a two-step approach to data analysis, first identifying and characterising the use of NPT in implementation research, and then exploring the contribution made by NPT to understanding the dynamics of the processes of implementation and integration, and the limitations of its use. The characterisation is likely to be replicable by another team, but it is possible that a different group of researchers, with different backgrounds and different prior experience of NPT, would reach different conclusions. We have maximised the robustness of our findings by following a transparent process for analysis, including NPT-naïve researchers in the team, and holding frequent discussions amongst the team during the analysis. Finally, we made a deliberate decision to focus solely on the health care literature, and in light of this decision, our findings only apply to research on implementation in health care.
Next steps for NPT development and empirical research
Most papers in the review used the elaboration of NPT published by May et al. [7, 8] in 2009. More recent iterations of the theory have focused on (a) the important role that social structural and social cognitive features of context play in mobilisation for implementation  and (b) the ways in which implementation processes demand that their participants negotiate with other actors and elements in the context in which they are set . In these papers, we have already gone some way to answering the critique of Clarke et al.  on the relationship between agency and context. The critique offered by Segrott et al. , however, focused on the experiences of different groups of actors in implementation processes. They saw NPT as primarily being about the agency of professionals, rather than the experiences of patients and other participants in implementation processes. NPT both can be, and is, applied to those groups. We have developed theory in this area to explore the relationship between the implementation of complex interventions and burden of treatment (e.g. [212,213,214,215]), and there is now a discrete body of primary research literature (e.g. [216,217,218,219,220]) and systematic reviews (e.g. [221,222,223]) that utilises these theoretical perspectives to understand patient and caregiver experience.
NPT has developed iteratively. Future work to develop it will explore variations in the ways that NPT mechanisms motivate and shape implementation processes across and between settings, and between micro, meso and macro levels of activity. This will engender a comprehensive ‘whole system’ approach to understanding implementation processes. Future empirical research will also help us to explore and test the hypothesis that collective action mechanisms operate cumulatively and that some mechanisms are more significant than others in determining implementation process outcomes. Rigorous quantitative research will assist in this, but until recently, there has been no robust instrument through which quantitative investigations of NPT mechanisms could be done. However, the NoMAD instrument is now available to perform this task . This will make possible both large-scale and comparative quantitative and mixed methods studies that will provide important insights into the role of NPT mechanisms and the form and direction of implementation processes. This should lead to rigorous statistical models of NPT mechanisms at work and so to new insights about implementation processes. Finally, despite attempts to make NPT more user friendly through the development of explanatory toolkits, some users have difficulty with its technical vocabulary. NPT training packages are now coming on stream that will help to solve this problem .
Normalization Process Theory appears to offer its users a coherent and stable set of explanations of implementation processes. It characterises the mechanisms that motivate and shape these processes and so can be used to aid intervention development and implementation planning as well as evaluating and understanding implementation processes themselves. In particular, NPT appears to have offered a valuable set of conceptual tools to understand the dynamics of implementation within clinical trials. In the future, it will be important to connect collective action much more closely to context in implementation studies. Equally, it will be important to develop longitudinal and genuinely mixed methods studies. These will help us understand not only the dynamics of implementation but also variations in implementation, embedding and long-term integration and sustainability over time and between settings.
American College of Physicians
American Psychiatric Association
Collaborative cARE for people with DEMentia in primary care (trial acronym)
Capability + Opportunity + Motivation → Behaviour Change Model
Chronic obstructive pulmonary disease
Proprietary qualitative analysis software
Daily life dialogue assessment
Discharge planning process
Extended Normalization Process Theory
Food standards agency (England and Wales)
Inter-collegiate stroke working party (UK)
Improving maternal and child health nurse care for vulnerable mothers (trial acronym)
National Institute of Health and Care Excellence
Normalisation of complex interventions—measure development
Normalization Process Model
Normalization Process Theory
Promoting action on research implementation in health services
Patient trajectory for Home-dwelling elders
Theory based change in practice systems and roles of health professionals in the primary care diabetes team (trial acronym)
Whole system informing self-management engagement (trial acronym)
Davidoff F, Dixon-Woods M, Leviton L, Michie S. Demystifying theory and its use in improvement. BMJ Qual Saf. 2015; https://doi.org/10.1136/bmjqs-2014-003627.
Tabak RG, Khoong EC, Chambers DA, Brownson RC. Bridging research and practice: models for dissemination and implementation research. Am J Prev Med. 2012;43(3):337–50.
Nilsen P. Making sense of implementation theories, models and frameworks. Implement Sci. 2015;10:53.
Skolarus TA, Lehmann T, Tabak RG, Harris J, Lecy J, Sales AE. Assessing citation networks for dissemination and implementation research frameworks. Implement Sci. 2017;12(1):97.
May C. A rational model for assessing and evaluating complex interventions in health care. BMC Health Serv Res. 2006;6(86):1–11.
May C, Finch T, Mair F, Ballini L, Dowrick C, Eccles M, Gask L, MacFarlane A, Murray E, Rapley T, et al. Understanding the implementation of complex interventions in health care: the normalization process model. BMC Health Serv Res. 2007;7:148.
May C, Finch T. Implementation, embedding, and integration: an outline of normalization process theory. Sociology. 2009;43(3):535–54.
May C, Mair FS, Finch T, MacFarlane A, Dowrick C, Treweek S, Rapley T, Ballini L, Ong BN, Rogers A, et al. Development of a theory of implementation and integration: normalization process theory. Implement Sci. 2009:4(29).
May C. Towards a general theory of implementation. Implement Sci. 2013;8(1):18.
May CR, Johnson M, Finch T. Implementation, context and complexity. Implement Sci. 2016;11(1):141.
May CR, Mair FS, Dowrick CF, Finch TL. Process evaluation for complex interventions in primary care: understanding trials using the normalization process model. BMC Fam Pract. 2007;8
May C. Agency and implementation: understanding the embedding of healthcare innovations in practice. Soc Sci Med. 2013;78(0):26–33.
Murray E, Treweek S, Pope C, MacFarlane A, Ballini L, Dowrick C, Finch T, Kennedy A, Mair F, O'Donnell C, et al. Normalisation process theory: a framework for developing, evaluating and implementing complex interventions. BMC Med. 2010;8(1):63.
Finch TL, Rapley T, Girling M, Mair FS, Murray E, Treweek S, McColl E, Steen IN, May CR. Improving the normalization of complex interventions: measure development based on normalization process theory (NoMAD): study protocol. Implement Sci. 2013;8
Finch T, Mair F, O'Donnell C, Murray E, May C. From theory to ‘measurement’ in complex interventions: methodological lessons from the development of an e-health normalisation instrument. BMC Med Res Methodol. 2012;12(1):69.
May C, Finch T, Ballini L, MacFarlane A, Mair F, Murray E, Treweek S, Rapley T. Evaluating complex interventions and health technologies using normalization process theory: development of a simplified approach and web-enabled toolkit. BMC Health Serv Res. 2011;11(1):245.
McEvoy R, Ballini L, Maltoni S, ODonnell C, Mair F, MacFarlane A. A qualitative systematic review of studies using the normalization process theory to research implementation processes. Implement Sci. 2014;9(1):2.
Kirk MA, Kelley C, Yankey N, Birken SA, Abadie B, Damschroder L. A systematic review of the use of the consolidated framework for implementation research. Implement Sci. 2016;11:72.
Ballinger C, Taylor A, Loudon D, Macdonald AS. Rehabilitation professionals’ perceptions of the use of new visualisation software tools with people with stroke. Disability Rehab Assist Technol. 2016;11(2):139–49.
Bamford C, Poole M, Brittain K, Chew-Graham C, Fox C, Iliffe S, Manthorpe J, Robinson L, Team C. Understanding the challenges to implementing case management for people with dementia in primary care in England: a qualitative study using normalization process theory. BMC Health Serv Res. 2014;14(1):549.
Blakeman T, Protheroe J, Chew-Graham C, Rogers A, Kennedy A. Understanding the management of early-stage chronic kidney disease in primary care: a qualitative study. Br J Gen Pract. 2012;62(597):e233–42.
Blickem C, Kennedy A, Jariwala P, Morris R, Bowen R, Vassilev I, Brooks H, Blakeman T, Rogers A. Aligning everyday life priorities with people's self-management support networks: an exploration of the work and implementation of a needs-led telephone support system. BMC Health Serv Res. 2014;14(1):262.
Brooks H, Sanders C, Lovell K, Fraser C, Rogers A. Re-inventing care planning in mental health: stakeholder accounts of the imagined implementation of a user/carer involved intervention. BMC Health Serv Res. 2015;15(1):490.
Buckingham S, Kendall M, Ferguson S, MacNee W, Sheikh A, White P, Worth A, Boyd K, Murray SA, Pinnock H. HELPing older people with very severe chronic obstructive pulmonary disease (HELP-COPD): mixed-method feasibility pilot randomised controlled trial of a novel intervention. Prim Care Resp Med. 2015;25:15020.
Clarke DJ, Hawkins R, Sadler E, Harding G, McKevitt C, Godfrey M, Dickerson J, Farrin AJ, Kalra L, Smithard D, et al. Introducing structured caregiver training in stroke care: findings from the TRACS process evaluation study. BMJ Open. 2014;4(4):e004473.
Clarke DJ, Godfrey M, Hawkins R, Sadler E, Harding G, Forster A, McKevitt C, Dickerson J, Farrin A. Implementing a training intervention to support caregivers after stroke: a process evaluation examining the initiation and embedding of programme change. Implement Sci. 2013;8(1):96.
Coupe N, Anderson E, Gask L, Sykes P, Richards DA, Chew-Graham C. Facilitating professional liaison in collaborative care for depression in UK primary care; a qualitative study utilising normalisation process theory. BMC Fam Pract. 2014;15(1):78.
Finch TL, Bamford C, Deary V, Sabin N, Parry SW. Making sense of a cognitive behavioural therapy intervention for fear of falling: qualitative study of intervention development. BMC Health Serv Res. 2014;14(1):436.
Furler J, O'Neal D, Speight J, Manski-Nankervis JA, Gorelik A, Holmes-Truscott E, Ginnivan L, Young D, Best J, Patterson E, et al. Supporting insulin initiation in type 2 diabetes in primary care: results of the stepping up pragmatic cluster randomised controlled clinical trial. BMJ. 2017;356:j783.
Furler J, Blackberry I, Manski-Nankervis J-A, O’Neal D, Best J, Young D. Optimizing care and outcomes for people with type 2 diabetes—lessons from a translational research program on insulin initiation in general practice. Front Med. 2015;1:60.
Furler JS, Blackberry ID, Walker C, Manski-Nankervis JA, Anderson J, O'Neal D, Young D, Best J. Stepping up: a nurse-led model of care for insulin initiation for people with type 2 diabetes. Fam Pract. 2014;31(3):349–56.
Gabbay MB, Ring A, Byng R, Anderson P, Taylor RS, Matthews C, Harris T, Berry V, Byrne P, Carter E, et al. Debt counselling for depression in primary care: an adaptive randomised controlled pilot trial (DeCoDer study). Health Technol Assess. 2017;21(35):1.
Gask L, Bower P, Lovell K, Escott D, Archer J, Gilbody S, Lankshear A, Simpson A, Richards D. What work has to be done to implement collaborative care for depression? Process evaluation of a trial utilizing the Normalization Process Model. Implement Sci. 2010;5(15):5908–5.
Grant A, Dreischulte T, Guthrie B. Process evaluation of the data-driven quality improvement in primary care (DQIP) trial: active and less active ingredients of a multi-component complex intervention to reduce high-risk primary care prescribing. Implement Sci. 2017;12(1):4.
Grant A, Dreischulte T, Guthrie B. Process evaluation of the Data-Driven Quality Improvement in Primary Care (DQIP) trial: case study evaluation of adoption and maintenance of a complex intervention to reduce high-risk primary care prescribing. BMJ Open. 2017;7(3):e015281.
Godfrey M, Smith J, Green J, Cheater F, Inouye SK, Young JB. Developing and implementing an integrated delirium prevention system of care: a theory driven, participatory research study. BMC Health Serv Res. 2013;13(1):341.
Hind D, Parkin J, Whitworth V, Rex S, Young T, Hampson L, Sheehan J, Maguire C, Cantrill H, Scott E, et al. Aquatic therapy for children with Duchenne muscular dystrophy: a pilot feasibility randomised controlled trial and mixed-methods process evaluation. Health Technol Assess. 2017;21(27):1.
Hooker L, Taft A. Using theory to design, implement and evaluate sustained nurse domestic violence screening and supportive care. J Res Nurs. 2016;21(5–6):432–42.
Hooker L, Small R, Humphreys C, Hegarty K, Taft A. Applying normalization process theory to understand implementation of a family violence screening and care model in maternal and child health nursing practice: a mixed method process evaluation of a randomised controlled trial. Implement Sci. 2015;10(1):39.
Hooker L, Small R, Taft A. Understanding sustained domestic violence identification in maternal and child health nurse care: process evaluation from a 2-year follow-up of the MOVE trial. J Adv Nurs. 2016;72(3):533-44.
Taft AJ, Hooker L, Humphreys C, Hegarty K, Walter R, Adams C, Agius P, Small R. Maternal and child health nurse screening and care for mothers experiencing domestic violence (MOVE): a cluster randomised trial. BMC Med. 2015;13(1):150.
Hooker L, Small R, Taft A. Understanding sustained domestic violence identification in maternal and child health nurse care: process evaluation from a 2-year follow-up of the MOVE trial. J Adv Nurs. 2016;72(3):533–44.
Kennedy A, Rogers A, Bowen R, Lee V, Blakeman T, Gardner C, Morris R, Protheroe J, Chew-Graham C. Implementing, embedding and integrating self-management support tools for people with long-term conditions in primary care nursing: a qualitative study. Int J Nurs Stud. 2014;51(8):1103–13.
Kennedy A, Rogers A, Chew-Graham C, Blakeman T, Bowen R, Gardner C, Lee V, Morris R, Protheroe J. Implementation of a self-management support approach (WISE) across a health system: a process evaluation explaining what did and did not work for organisations, clinicians and patients. Implement Sci. 2014;9(1):129.
Kennedy A, Bower P, Reeves D, Blakeman T, Bowen R, Chew-Graham C, Eden M, Fullwood C, Gaffney H, Gardner C, et al. Implementation of self management support for long term conditions in routine primary care settings: cluster randomised controlled trial. BMJ. 2013;346:f2882.
Kennedy A, Chew-Graham C, Blakeman T, Bowen A, Gardner C, Protheroe J, Rogers A, Gask L. Delivering the WISE (Whole Systems Informing Self-Management Engagement) training package in primary care: learning from formative evaluation. Implement Sci. 2010;5(1):7.
Khowaja AR, Qureshi RN, Sawchuck D, Oladapo OT, Adetoro OO, Orenuga EA, Bellad M, Mallapur A, Charantimath U, Sevene E, et al. The feasibility of community level interventions for pre-eclampsia in South Asia and Sub-Saharan Africa: a mixed-methods design. Reprod Health. 2016;13(Suppl 1):56.
Leon N, Lewin S, Mathews C. Implementing a provider-initiated testing and counselling (PITC) intervention in Cape town, South Africa: a process evaluation using the normalisation process model. Implement Sci. 2013;8(1):97.
Mair FS, Hiscock J, Beaton SC. Understanding factors that inhibit or promote the utilization of telecare in chronic lung disease. Chronic Illness. 2008;4(2):110–7.
Morden A, Ong BN, Brooks L, Jinks C, Porcheret M, Edwards JJ, Dziedzic KS. Introducing evidence through research “push” using theory and qualitative methods. Qual Health Res. 2015;25:1560–75.
Morden A, Brooks L, Jinks C, Porcheret M, Ong BN, Dziedzic K. Research “push”, long term-change, and general practice. J Health Org Manage. 2015;29(7):798–821.
Ong BN, Morden A, Brooks L, Porcheret M, Edwards JJ, Sanders T, Jinks C, Dziedzic K. Changing policy and practice: making sense of national guidelines for osteoarthritis. Soc Sci Med. 2014;106:101–9.
Ricketts EJ, Francischetto EOC, Wallace LM, Hogan A, McNulty CAM. Tools to overcome potential barriers to chlamydia screening in general practice: qualitative evaluation of the implementation of a complex intervention. BMC Fam Pract. 2016;17
Speed C, Heaven B, Adamson A, Bond J, Corbett S, Lake A, May C, Vanoli A, McMeekin P, Moynihan P. LIFELAX–diet and LIFEstyle versus LAXatives in the management of chronic constipation in older people: randomised controlled trial. Health Technol Assess. 2010;14(52):1–251.
Sturgiss EA, Elmitt N, Haesler E, van Weel C, Douglas K. Feasibility and acceptability of a physician-delivered weight management programme. Fam Pract. 2017;34(1):43–8.
French B, Thomas LH, Harrison J, Burton CR, Forshaw D, Booth J, Britt D, Cheater FM, Roe B, Watkins CL. Implementing a systematic voiding program for patients with urinary incontinence after stroke. Qual Health Res. 2016;26(10):1393–408.
Thomas LH, French B, Burton CR, Sutton C, Forshaw D, Dickinson H, Leathley MJ, Britt D, Roe B, Cheater FM, et al. Evaluating a systematic voiding programme for patients with urinary incontinence after stroke in secondary care using soft systems analysis and Normalisation Process Theory: findings from the ICONS case study phase. Int J Nurs Stud. 2014;51(10):1308–20.
Willis K, Small R, Brown S. Using documents to investigate links between implementation and sustainability in a complex community intervention: the PRISM study. Soc Sci Med. 2012;75(7):1222–9.
Aarts JW, Faber MJ, Cohlen BJ, Van Oers A, Nelen WL, Kremer JA. Lessons learned from the implementation of an online infertility community into an IVF clinic’s daily practice. Hum Fertil. 2015;(0):1–10.
Devlin AM, McGee-Lennon M, O’Donnell CA, Bouamrane M-M, Agbakoba R, O’Connor S, Grieve E, Finch T, Wyke S, Watson N, et al. Delivering digital health and well-being at scale: lessons learned during the implementation of the Dallas program in the United Kingdom. J Am Med Inform Assoc. 2015;23:ocv097.
Agbakoba R, McGee-Lennon M, Bouamrane M-M, Watson N, Mair FS. Implementation factors affecting the large-scale deployment of digital health and well-being technologies: a qualitative study of the initial phases of the ‘Living-It-Up’ programme. Health Informat J. 2016;22(4):867-77.
Lennon MR, Bouamrane MM, Devlin AM, O'Connor S, O'Donnell C, Chetty U, Agbakoba R, Bikker A, Grieve E, Finch T, et al. Readiness for delivering digital health at scale: lessons from a longitudinal qualitative evaluation of a national digital health innovation program in the United Kingdom. J Med Internet Res. 2017;16;19(2):e42.
Alharbi TS, Carlström E, Ekman I, Olsson L-E. Implementation of person-centred care: management perspective. J Hosp Admin. 2014;3(3):107.
Ahmed S, Hayward J, Ahmed M. Primary care professionals’ perceptions of using a short family history questionnaire. Fam Pract. 2016;33:cmw080.
Alverbratt C, Carlström E, Åström S, Kauffeldt A, Berlin J. The process of implementing a new working method-a project towards change in a Swedish psychiatric clinic. J Hosp Admin. 2014;3(6):174.
Ariens LFM, Schussler-Raymakers FML, Frima C, Flinterman A, Hamminga E, Arents BWM, Bruijnzeel-Koomen CAFM, Marjolein SDBW, Os-Medendorp HV. Barriers and facilitators to eHealth use in daily practice: perspectives of patients and professionals in dermatology. J Med Internet Res. 2017;19(9):e300.
Atkins S, Lewin S, Ringsberg KC, Thorson A. Provider experiences of the implementation of a new tuberculosis treatment programme: a qualitative study using the normalisation process model. BMC Health Serv Res. 2011;11
Bamford C, Heaven B, May C, Moynihan P. Implementing nutrition guidelines for older people in residential care homes: a qualitative study using normalization process theory. Implement Sci. 2012;7(1):106.
Basu AP, Pearse JE, Baggaley J, Watson RM, Rapley T. Participatory design in the development of an early therapy intervention for perinatal stroke. BMC Pediatr. 2017;17:33.
Bayliss K, Riste L, Band R, Peters S, Wearden A, Lovell K, Fisher L, Chew-Graham CA. Implementing resources to support the diagnosis and management of chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) in primary care: a qualitative study. BMC Fam Pract. 2016;17:66.
Bee P, Lovell K, Airnes Z, Pruszynska A. Embedding telephone therapy in statutory mental health services: a qualitative, theory-driven analysis. BMC Psychiatry. 2016;16(1):56.
Bocoum FY, Tarnagda G, Bationo F, Savadogo JR, Nacro S, Kouanda S, Zarowsky C. Introducing onsite antenatal syphilis screening in Burkina Faso: implementation and evaluation of a feasibility intervention tailored to a local context. BMC Health Serv Res. 2017;17:378.
Bouamrane M-M, Mair FS. A study of clinical and information management processes in the surgical pre-assessment clinic—the experience of the Dumfries & Galloway royal infirmary preoperative clinic. BMC Med Inf Dec Making. 2014;14(1):22.
Bouamrane MM, Mair FS. A qualitative evaluation of general practitioners’ views on protocol-driven eReferral in Scotland. BMC Med Inform Decis Mak. 2014;14(1):30.
Bouamrane MM, Mair FS. Implementation of an integrated preoperative care pathway and regional electronic clinical portal for preoperative assessment. BMC Med Inform Decis Mak. 2014;14(1):93.
Bridges J, May C, Fuller A, Griffiths P, Wigley W, Gould L, Barker H, Libberton P. Optimising impact and sustainability: a qualitative process evaluation of a complex intervention targeted at compassionate care. BMJ Qual Saf. 2017;26:970-7.
Chiang PP, Glance D, Walker J, Walter F, Emery J. Implementing a QCancer risk tool into general practice consultations: an exploratory study using simulated consultations with Australian general practitioners. Br J Cancer. 2015;112:S77–83.
Conn LG, McKenzie M, Pearsall EA, McLeod RS. Successful implementation of an enhanced recovery after surgery programme for elective colorectal surgery: a process evaluation of champions’ experiences. Implement Sci. 2015;10(1):99.
Desveaux L, Mitchell J, Shaw J, Ivers N. Understanding the impact of accreditation on quality in healthcare: a grounded theory approach. Int J Qual Health Care. 2017;29:1–7.
Dickinson C, Gibson G, Gotts Z, Stobbart L, Robinson L. Cognitive stimulation therapy in dementia care: exploring the views and experiences of service providers on the barriers and facilitators to implementation in practice using Normalization Process Theory. Int Psychogeriatr. 2017;29(11):1869–78.
Dikomitis L, Green T, Macleod U. Embedding electronic decision-support tools for suspected cancer in primary care: a qualitative study of GPs’ experiences. Prim Health Care Res Dev. 2015;16(06):548–55.
Drew S, Judge A, May C, Farmer A, Cooper C, Javaid MK, Gooberman-Hill R. Implementation of secondary fracture prevention services after hip fracture: a qualitative study using extended Normalization Process Theory. Implement Sci. 2015;10(1):57.
Dugdale S, Elison S, Davies G, Ward J, Dalton M. A qualitative study investigating the continued adoption of breaking free online across a national substance misuse organisation: theoretical conceptualisation of staff perceptions. J Behav Health Serv Res. 2017;44(1):89–101.
Ehrlich C, Kendall E, John WS. How does care coordination provided by registered nurses “fit” within the organisational processes and professional relationships in the general practice context? Collegian. 2013;20(3):127–35.
Finch T. Teledermatology for chronic disease management: coherence and normalization. Chronic illness. 2008;4(2):127–34.
Franx G, Oud M, de Lange J, Wensing M, Grol R. Implementing a stepped-care approach in primary care: results of a qualitative study. Implement Sci. 2012;7(1):8.
French B, Day E, Watkins C, McLoughlin A, Fitzgerald J, Leathley M, Davies P, Emsley H, Ford G, Jenkinson D, et al. The challenges of implementing a telestroke network: a systematic review and case study. BMC Med Inf Dec Making. 2013;13(1):125.
Gibson J, Lightbody E, McLoughlin A, McAdam J, Gibson A, Day E, Fitzgerald J, May C, Price C, Emsley H, et al. ‘It was like he was in the room with us’: patients’ and carers’ perspectives of telemedicine in acute stroke. Health Expect. 2016;19(1):98–111.
Foss C, Ruud Knutsen IA, Havrevold Henni S, Myrstad H. The challenges associated with implementing new practice. Norwegian J Clin Nurs Sykepleien Forskning. 2017;e59483.
Foster M, Burridge L, Donald M, Zhang J, Jackson C. The work of local healthcare innovation: a qualitative study of GP-led integrated diabetes care in primary health care organization, structure and delivery of healthcare. BMC Health Serv Res. 2016;16(11).
Gould DJ, Hale R, Waters E, Allen D. Promoting health workers’ ownership of infection prevention and control: using normalization process theory as an interpretive framework. J Hosp Infect. 2016;94(4):373–80.
Gunn JM, Palmer VJ, Dowrick CF, Herrman HE, Griffiths FE, Kokanovic R, Blashki GA, Hegarty KL, Johnson CL, Potiriadis M, et al. Embedding effective depression care: using theory for primary care organisational and systems change. Implement Sci. 2010;5(1):62.
Hall A, Wilson CB, Stanmore E, Todd C. Implementing monitoring technologies in care homes for people with dementia: a qualitative exploration using normalization process theory. Int J Nurs Stud. 2017;72:60–70.
Hall A, Finch T, Kolehmainen N, James D. Implementing a video-based intervention to empower staff members in an autism care organization: a qualitative study. BMC Health Serv Res. 2016;16:608.
Hazell CM, Strauss C, Hayward M, Cavanagh K. Understanding clinician attitudes towards implementation of guided self-help cognitive behaviour therapy for those who hear distressing voices: using factor analysis to test normalisation process theory. BMC Health Serv Res. 2017;17(1):507.
Henderson EJ, Rubin GP. The utility of an online diagnostic decision support system (Isabel) in general practice: a process evaluation. JRSM Short Rep. 2013;4(5):31.
Herbert G, Sutton E, Burden S, Lewis S, Thomas S, Ness A, Atkinson C. Healthcare professionals' views of the enhanced recovery after surgery programme: a qualitative investigation. BMC Health Serv Res. 2017;17(1):617.
Hoberg AA, Vickers KS, Ericksen J, Bauer G, Kung S, Stone R, Williams M, Moore MJ, Frye MA. Feasibility evaluation of an interpersonal and social rhythm therapy group delivery model. Arch Psychiatr Nurs. 2013;27(6):271–7.
Holtrop JS, Potworowski G, Fitzpatrick L, Kowalk A, Green LA. Effect of care management program structure on implementation: a normalization process theory analysis. BMC Health Serv Res. 2016;16(1):386.
Kanagasundaram NS, Bevan MT, Sims AJ, Heed A, Price DA, Sheerin NS. Computerized clinical decision support for the early recognition and management of acute kidney injury: a qualitative evaluation of end-user experience. Clin Kidney J. 2016;9(1):57–62.
Kulnik ST, Postges H, Brimicombe L, Hammond J, Jones F. Implementing an interprofessional model of self-management support across a community workforce: a mixed-methods evaluation study. J Int Care. 2017;31(1):75–84.
Johnson M, Leaf AA, Pearson F, Clark H, Dimitrov B, Pope C, May CR. Successfully implementing and embedding guidelines to improve the nutrition and growth of preterm infants in neonatal intensive care: a prospective interventional study. BMJ Open. 2017;7:e017727.
Jones CH, Glogowska M, Locock L, Lasserson DS. Embedding new technologies in practice—a normalization process theory study of point of care testing. BMC Health Serv Res. 2016;16(1):591.
Jones F, Bailey N. How can we train stroke practitioners about patient self-management? Description and evaluation of a pathway wide training programme. Eur J Per Centered Healthcare. 2013;1(1):246–54.
Leggat SG, Balding C. A qualitative study on the implementation of quality systems in Australian hospitals. Health Serv Manag Res. 2017;30(3):179–86.
Lhussier M, Forster N, Eaton S, Carr SM. Care planning for long term conditions in primary care: indicators of embeddedness. Eur J Per Centered Healthcare. 2015;3(1):59–64.
Ling T, Brereton L, Conklin A, Newbould J, Roland M. Barriers and facilitators to integrating care: experiences from the English integrated care pilots. Int J Integr Care. 2012;12
Lloyd A, Joseph-Williams N, Edwards A, Rix A, Elwyn G. Patchy ‘coherence’: using normalization process theory to evaluate a multi-faceted shared decision making implementation program (MAGIC). Implement Sci. 2013;8(1):102.
Joseph-Williams N, Lloyd A, Edwards A, Stobbart L, Tomson D, Macphail S, Dodd C, Brain K, Elwyn G, Thomson R. Implementing shared decision making in the NHS: lessons from the MAGIC programme. Bmj. 2017;357:j1744.
Lowrie R, Johansson L, Forsyth P, Bryce SL, McKellar S, Fitzgerald N. Experiences of a community pharmacy service to support adherence and self-management in chronic heart failure. Int J Clin Pharm. 2014;36(1):154–62.
Martindale A-M, Elvey R, Howard SJ, McCorkindale S, Sinha S, Blakeman T. Understanding the implementation of ‘sick day guidance’ to prevent acute kidney injury across a primary care setting in England: a qualitative evaluation. BMJ Open. 2017;7(11):e017241.
May CR, Finch TL, Cornford J, Exley C, Gately C, Kirk S, Jenkings KN, Osbourne J, Robinson AL, Rogers A. Integrating telecare for chronic disease management in the community: what needs to be done? BMC Health Serv Res. 2011;11(1):131.
Morton A, Wigley W. Beyond ‘train and hope’: identifying factors that affect implementation of the promotional guide in practice. J Health Visiting. 2014;2(12):670–80.
Murray E, Burns J, May C, Finch T, O'Donnell C, Wallace P, Mair F. Why is it difficult to implement e-health initiatives? A qualitative study. Implement Sci. 2011;6(1):6.
Newton MS, McLachlan HL, Forster DA, Willis KF. Understanding the ‘work’ of caseload midwives: a mixed-methods exploration of two caseload midwifery models in Victoria. Australia: Women and Birth. 2016;29(3):223.
Nordmark S, Zingmark K, Lindberg I. Process evaluation of discharge planning implementation in healthcare using normalization process theory. BMC Med Inf Dec Making. 2016;16:48.
O’Donnell A, Kaner E. Are brief alcohol interventions adequately embedded in UK primary care? A qualitative study utilising normalisation process theory. Int J Environ Res Public Health. 2017;14(4):350.
Owens C, Charles N. Implementation of a text-messaging intervention for adolescents who self-harm (TeenTEXT): a feasibility study using normalisation process theory. Child Adolescent Psychiat Mental Health. 2016;10(1):14.
Polus BI, Paterson C, Van Rotterdam J, Vindigni D. Embedding chiropractic in indigenous health care organisations: applying the normalisation process model. BMC Health Serv Res. 2012;12(1):429.
Turnbull J, Prichard J, Halford S, Pope C, Salisbury C. Reconfiguring the emergency and urgent care workforce: mixed methods study of skills and the everyday work of non-clinical call-handlers in the NHS. J Health Serv Res Policy. 2012;17(4):233–40.
Pope C, Halford S, Turnbull J, Prichard J, Calestani M, May C.
Røsstad T, Garåsen H, Steinsbekk A, Håland E, Kristoffersen L, Grimsmo A. Implementing a care pathway for elderly patients, a comparative qualitative process evaluation in primary care. BMC Health Serv Res. 2015;15(1):86.
Sanders T, Foster NE, Ong BN. Perceptions of general practitioners towards the use of a new system for treating back pain: a qualitative interview study. BMC Med. 2011;9:49.
Scalia P, Elwyn G, Durand MA. “Provoking conversations”: case studies of organizations where Option Grid™ decision AIDS have become 'normalized'. BMC Med Inf Dec Making. 2017;17(1):124.
Scantlebury A, Sheard L, Watt I, Cairns P, Wright J, Adamson J. Exploring the implementation of an electronic record into a maternity unit: a qualitative study using normalisation process theory. BMC Med Inf Dec Making. 2017;17(1):1–10.
Segrott J, Murphy S, Rothwell H, Scourfield J, Foxcroft D, Gillespie D, Holliday J, Hood K, Hurlow C, Morgan-Trimmer S, et al. An application of extended normalisation process theory in a randomised controlled trial of a complex social intervention: process evaluation of the strengthening families programme (10–14) in Wales, UK. SSM Pop Health. 2017;3:255–65.
Shemeili SA, Klein S, Strath A, Fares S, Stewart D. An exploration of health professionals’ experiences of medicines management in elderly, hospitalised patients in Abu Dhabi. Int J Clin Pharm. 2016;38(1):107–18.
Shulver W, Killington M, Crotty M. ‘Massive potential’ or ‘safety risk’? Health worker views on telehealth in the care of older people and implications for successful normalization. BMC Med Inf Dec Making. 2016;16(1):131.
Spangaro J, Poulos RG, Zwi AB. Pandora doesn’t live here anymore: normalization of screening for intimate partner violence in Australian antenatal, mental health, and substance abuse services. Violence Victims. 2011;26(1):130–44.
Stevenson F. The use of electronic patient records for medical research: conflicts and contradictions. BMC Health Serv Res. 2015;15(1):124.
Tarzia L, Fetherstonhaugh D, Bauer M, Beattie E, Nay R. “We have to work within the system!”: staff perceptions of organizational barriers to decision making for older adults with dementia in Australian aged care facilities. Res Gerontol Nurs. 2015;8:1–7.
Temple-Smith M, Pirotta M, Kneebone J, McNamee K, Fairley C, Bilardi J, Hocking J. A missed opportunity lessons learnt from a chlamydia testing observation study in general practice. Aust Fam Physician. 2012;41(6):413–6.
Teunissen E, Gravenhorst K, Dowrick C, Van Weel-Baumgarten E, Van Den Driessen MF, De Brún T, Burns N, Lionis C, Mair FS, O'Donnell C, et al. Implementing guidelines and training initiatives to improve cross-cultural communication in primary care consultations: a qualitative participatory European study. Int J Equity Health. 2017;16(1):32.
de Brun T, De-Brun MO, van Weel-Baumgarten E, van Weel C, Dowrick C, Lionis C, O'Donnell CA, Burns N, Mair FS, Saridaki A et al: Guidelines and training initiatives that support communication in cross-cultural primary-care settings: appraising their implementability using normalization process theory. Fam Pract 2015, 32(4):420–425.
Lionis C, Papadakaki M, Saridaki A, Dowrick C, O'Donnell CA, Mair FS, Van Den Muijsenbergh M, Burns N, De Brún T, O'Reilly De Brún M, et al. Engaging migrants and other stakeholders to improve communication in cross-cultural consultation in primary care: a theoretically informed participatory study. BMJ Open. 2016;6(7):e010822.
Papadakaki M, Lionis C, Saridaki A, Dowrick C, de Brun T, O'Reilly-de Brun M, O'Donnell CA, Burns N, van Weel-Baumgarten E, van den Muijsenbergh M et al: Exploring barriers to primary care for migrants in Greece in times of austerity: perspectives of service providers. Eur J Gen Pract 2017, 23(1):128–134.
Thomas K, Bendtsen P, Krevers B. Towards implementing coordinated healthy lifestyle promotion in primary care: a mixed method study. Int J Integr Care. 2015;18(3):312-24.
Tierney E, O'Sullivan M, Hickey L, Hannigan A, May C, Cullen W, Kennedy N, Kineen L, MacFarlane A. Do primary care professionals agree about progress with implementation of primary care teams: results from a cross sectional study. BMC Fam Pract. 2016;17:163.
Toye CRA. Normalisation process theory and the implementation of resident assessment instrument–home care in Saskatchewan, Canada: a qualitative study. Home Health Care Manage Pract. 2016;28(3):161–9.
Trietsch J, van Steenkiste B, Hobma S, Frericks A, Grol R, Metsemakers J, van der Weijden T. The challenge of transferring an implementation strategy from academia to the field: a process evaluation of local quality improvement collaboratives in Dutch primary care using the normalization process theory. J Eval Clin Pract. 2014;20(6):1162–71.
Vest BM, York TRM, Sand J, Fox CH, Kahn LS. Chronic kidney disease guideline implementation in primary care: a qualitative report from the TRANSLATE CKD study. J Am Board Fam Med. 2015;28(5):624–31.
Volker N, Williams LT, Davey RC, Cochrane T, Clancy T. Implementation of cardiovascular disease prevention in primary health care: enhancing understanding using normalisation process theory. BMC Fam Pract. 2017;18(1):28.
Webster LAD, Ekers D, Chew-Graham CA. Feasibility of training practice nurses to deliver a psychosocial intervention within a collaborative care framework for people with depression and long-term conditions. BMC Nurs. 2016;15:71.
Walker JG, Bickerstaffe A, Hewabandu N, Maddumarachchi S, Dowty JG, Jenkins M, Pirotta M, Walter FM, Emery JD. The CRISP colorectal cancer risk prediction tool: an exploratory study using simulated consultations in Australian primary care. BMC Med Inf Dec Making. 2017;17(1):1–11.
Wilhelmsen M, Høifødt RS, Kolstrup N, Waterloo K, Eisemann M, Chenhall R, Risør MB. Norwegian general practitioners’ perspectives on implementation of a guided web-based cognitive behavioral therapy for depression: a qualitative study. J Med Internet Res. 2014;16(9):e208.
Wilkes S, Rubin G. Process evaluation of infertility management in primary care: has open access HSG been normalized? Prim Health Care Res Dev. 2009;10(04):290–8.
Green T, Martins T, Hamilton W, Rubin G, Elliott K, Macleod U. Exploring GPs’ experiences of using diagnostic tools for cancer: a qualitative study in primary care. Fam Pract. 2014;32:cmu081.
Tazzyman A, Ferguson J, Hillier C, Boyd A, Tredinnick-Rowe J, Archer J, de Bere SR, Walshe K. The implementation of medical revalidation: an assessment using normalisation process theory. BMC Health Serv Res. 2017;17(1):749.
Lohse KR, Hilderman CG, Cheung KL, Tatla S, Van der Loos HF. Virtual reality therapy for adults post-stroke: a systematic review and meta-analysis exploring virtual environments and commercial games in therapy. PLoS One. 2014;9(3):e93318.
Tam-Tham H, Cepoiu-Martin M, Ronksley PE, Maxwell CJ, Hemmelgarn BR. Dementia case management and risk of long-term care placement: a systematic review and meta-analysis. Int J Geriatr Psychiat. 2013;28(9):889–902.
NICE. Chronic kidney disease. Early identification and management of chronic kidney disease in adults in primary and secondary care (CG73). London: National Institute for Health and Clinical Excellence; 2008.
Crawford MJ, Rutter D, Manley C, Weaver T, Bhui K, Fulop N, Tyrer P. Systematic review of involving patients in the planning and development of health care. BMJ. 2002;325(7375):1263.
Giacomini M, De Jean D, Simeonov D, Smith A. Experiences of living and dying with COPD: a systematic review and synthesis of the qualitative empirical literature. Ont Health Technol Assess Ser. 2012;12(13):1–47.
Brereton L, Carroll C, Barnston S. Interventions for adult family carers of people who have had a stroke: a systematic review. Clin Rehabil. 2007;21(10):867–84.
Gunn J, Diggens J, Hegarty K, Blashki G. A systematic review of complex system interventions designed to increase recovery from depression in primary care. BMC Health Serv Res. 2006;6:88.
Zijlstra GA, van Haastregt JC, van Rossum E, van Eijk JT, Yardley L, Kempen GI. Interventions to reduce fear of falling in community-living older people: a systematic review. J Am Geriatr Soc. 2007;55(4):603–15.
NICE. Delirium: diagnosis, prevention and management (CG103). Manchester: National Institute for Clinical Excellence; 2010.
Howard RL, Avery AJ, Slavenburg S, Royal S, Pipe G, Lucassen P, Pirmohamed M. Which drugs cause preventable admissions to hospital? A systematic review. Br J Clin Pharmacol. 2007;63(2):136–47.
Zwar N, Harris M, Griffiths R, Roland M, Denis S, Powell-Davies G, Hassan I. A systematic review of chronic disease management. Canberra: Australian Primary Care Research Institute; 2006.
WHO. WHO recommendations for prevention and treatment of pre-eclampsia and eclampsia. Geneva: World Health Organization; 2011.
Obermeyer CM, Osborn M. The utilization of testing and counseling for HIV: a review of the social and behavioral evidence. Am J Public Health. 2007;97(10):1762–74.
Hensen B, Baggaley R, Wong VJ, Grabbe KL, Shaffer N, Lo YR, Hargreaves J. Universal voluntary HIV testing in antenatal care settings: a review of the contribution of provider-initiated testing & counselling. Tropical Med Int Health. 2012;17(1):59–70.
Chou R, Huffman LH, Fu R, Smits AK, Korthuis PT, Force USPST. Screening for HIV: a review of the evidence for the U.S. Preventive Services Task Force. Ann Intern Med. 2005;143(1):55–73.
Pare G, Jaana M, Sicotte C. Systematic review of home telemonitoring for chronic diseases: the evidence base. J Am Med Inform Assoc. 2007;14(3):269–77.
NICE. Osteoarthritis: national clinical guideline for care and management in adults (CG59). London: National Institue for Health and Care Excellence; 2008.
Party I-CSW. National clinical guideline for stroke. London: Royal College of Physicians; 2012.
Black AD, Car J, Pagliari C, Anandan C, Cresswell K, Bokun T, McKinstry B, Procter R, Majeed A, Sheikh A. The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS Med. 2011;8(1):e1000387.
Mair F, May C, O'Donnell C, Finch T, Sullivan F, Murray E. Factors that promote or inhibit the implementation of e-health systems: an explanatory systematic review. Bull World Health Organ. 2012;90:357–64.
Reid GT, Walter FM, Brisbane JM, Emery JD. Family history questionnaires designed for clinical use: a systematic review. Public Health Gen. 2009;12(2):73–83.
Munro SA, Lewin SA, Smith HJ, Engel ME, Fretheim A, Volmink J. Patient adherence to tuberculosis treatment: a systematic review of qualitative research. PLoS Med. 2007;4(7):e238.
FSA. Guidance on food served to older people in residential care. London: Food Standards Agency; 2007.
NICE. Chronic fatigue syndrome/myalgic encephalitis (or encalopathy): diagnosis and management of CFS/ME in adults and children (CG53). London: National Institute of Clinical Excellence; 2007.
Cresswell K, Sheikh A. Organizational issues in the implementation and adoption of health information technology innovations: an interpretative review. Int J Med Inform. 2013;82(5):e73–86.
McDonald KM, Matesic B, Contopoulos-Ioannidis DG, Lonhart J, Schmidt E, Pineda N, Ioannidis JP. Patient safety strategies targeted at diagnostic errors: a systematic review. Ann Intern Med. 2013;158(5 Pt 2):381–9.
Eskicioglu C, Forbes SS, Aarts MA, Okrainec A, McLeod RS. Enhanced recovery after surgery (ERAS) programs for patients having colorectal surgery: a meta-analysis of randomized trials. J Gastrointest Surg. 2009;13(12):2321–9.
NICE. Falls in older people: assessing risk and prevention (CG161). Manchester: National Institute for Clinical Excellence; 2013.
NICE. Osteoporosis: secondary prevention including strontium ranelate (TA161). Manchester: National Institue of Clinical Excellence; 2008.
NICE: Depression: the treatment and management of depression in adults (CG90). Manchester: National Institute of Clinical Excellence; 2009.
Deshpande A, Khoja S, McKibbon A, Rizo C, Jadad A. Telehealth for acute stroke management (Telestroke): systematic review and environment scan (technology overview 37). Ottowa: Canadian Agency for Drugs and Technologies in Health; 2008.
Greenhalgh T, Robert G, Macfarlane F, Bate P, Kyriakidou O. Diffusion of innovations in service organizations: systematic review and recommendations. Milbank Q. 2004;82(4):581–629.
NICE. Referral guidelines for suspected cancer. London: National Institute for Health and Clinical Excellence; 2005.
Garg AX, Adhikari NK, McDonald H, Rosas-Arellano MP, Devereaux PJ, Beyene J, Sam J, Haynes RB. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA. 2005;293(10):1223–38.
NICE. Acute kidney injury: prevention, detection and management of acute kidney injury up to the point of renal replacement therapy (CG169). Manchester: National Institute of Health and Care Excellence; 2013.
Coulter A, Entwistle VA, Eccles A, Ryan S, Shepperd S, Perera R. Personalised care planning for adults with chronic or long-term health conditions. Cochrane Database Syst Rev. 2015;3:CD010523.
O'Connor AM, Stacey D, Rovner D, Holmes-Rovner M, Tetroe J, Llewellyn-Thomas H, Entwistle V, Rostom A, Fiset V, Barry M, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev. 2001;3:CD001431.
NICE. Chronic heart failure: management of chronic heart failure in adults in primary and secondary care. London: National Institute of Health and Care Excellence; 2008.
Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E, Morton SC, Shekelle PG. Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med. 2006;144(10):742–52.
Sandall J, Soltani H, Gates S, Shennan A, Devane D. Midwife-led continuity models versus other models of care for childbearing women. Cochrane Database Syst Rev. 2013;8:CD004667.
Shepperd S, McClaran J, Phillips C, Lannin N, Clemson L, McCluskey A, Cameron I, Barras S. Discharge planning from hospital to home. Cochrane Database Syst Rev. 2010;1(Issue 1):CD000313.
Ougrin D, Tranah T, Stahl D, Moran P, Asarnow JR. Therapeutic interventions for suicide attempts and self-harm in adolescents: systematic review and meta-analysis. J Am Acad Child Adolesc Psychiatry. 2015;54(2):97–107. e102
Mistiaen P, Francke AL, Poot E. Interventions aimed at reducing problems in adult patients discharged from hospital to home: a systematic meta-review. BMC Health Serv Res. 2007;7:47.
Boonstra A, Broekhuis M. Barriers to the acceptance of electronic medical records by physicians from systematic review to taxonomy and interventions. BMC Health Serv Res. 2010;10:231.
Petrie J, Bunn F, Byrne G. Parenting programmes for preventing tobacco, alcohol or drugs misuse in children <18: a systematic review. Health Educ Res. 2007;22(2):177–91.
Renders CM, Valk GD, Griffin S, Wagner EH, Eijk JT, Assendelft WJ. Interventions to improve the management of diabetes mellitus in primary care, outpatient and community settings. Cochrane Database Syst Rev. 2001;1:CD001481.
Flodgren G, Parmelli E, Doumit G, Gattellari M, O'Brien MA, Grimshaw J, Eccles MP. Local opinion leaders: effects on professional practice and health care outcomes. Cochrane Database Syst Rev. 2011;8:CD000125.
Bower P, Gilbody S, Richards D, Fletcher J, Sutton A. Collaborative care for depression in primary care. Making sense of a complex intervention: systematic review and meta-regression. Br J Psychiatry. 2006;189:484–93.
Arnold SR, Straus SE. Interventions to improve antibiotic prescribing practices in ambulatory care. Cochrane Database Syst Rev. 2005;4:CD003539.
Fink HA, Ishani A, Taylor BC, Greer NL, MacDonald R, Rossini D, Sadiq S, Lankireddy S, Kane RL, Wilt TJ. Screening for, monitoring, and treatment of chronic kidney disease stages 1 to 3: a systematic review for the U.S. Preventive Services Task Force and for an American College of Physicians Clinical Practice Guideline. Ann Intern Med. 2012;156(8):570–81.
NICE. Depression in adults with a chronic physical health problem (CG91). Manchester: National Institute for Health and Clinical Excellence; 2009.
Farrand P, Woodford J. Impact of support on the effectiveness of written cognitive behavioural self-help: a systematic review and meta-analysis of randomised controlled trials. Clin Psychol Rev. 2013;33(1):182–95.
Waller R, Gilbody S. Barriers to the uptake of computerized cognitive behavioural therapy: a systematic review of the quantitative and qualitative evidence. Psychol Med. 2009;39(5):705–12.
Gask L, Rogers A, Campbell S, Sheaff R. Beyond the limits of clinical governance? The case of mental health in English primary care. BMC Health Serv Res. 2008;8(1):63.
Gitlin LN, Harris LF, McCoy MC, Hess E, Hauck WW. Delivery characteristics, acceptability, and depression outcomes of a home-based depression intervention for older African Americans: the get busy get better program. The Gerontologist. 2015;56:gnv117.
Hsieh H-F, Shannon SE. Three approaches to qualitative content analysis. Qual Health Res. 2005;15(9):1277–88.
Ritchie J, Spencer L. Qualitative data analysis for applied policy research. In: Bryman A, Burgess R, editors. Analysing qualitative data. London: Routledge; 1994. p. 173–94.
Dedoose. Dedoose version 4.5, web application for managing, analyzing, and presenting qualitative and mixed method research data. Los Angeles: SocioCultural Research Consultants, LLC; 2013. http://www.dedoose.com
de Brún T, de-Brún MOR, van Weel-Baumgarten E, van Weel C, Dowrick C, Lionis C, O’Donnell CA, Burns N, Mair FS, Saridaki A, et al. Guidelines and training initiatives that support communication in cross-cultural primary-care settings: appraising their implementability using normalization process theory. Fam Pract. 2015;32(4):420–5.
Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009;4
Rycroft-Malone J. The PARIHS framework—a framework for guiding the implementation of evidence-based practice. J Nurs Care Qual. 2004;19(4):297–304.
MacFarlane A, O'Reilly-de Brún M. Using a theory-driven conceptual framework in qualitative health research. Qual Health Res. 2012;22(5):607-18.
Morrison A, Polisena J, Husereau D, Moulton K, Clark M, Fiander M, Mierzwinski-Urban M, Clifford T, Hutton B, Rabb D. The effect of English-language restriction on systematic review-based meta-analyses: a systematic review of empirical studies. Int J Technol Assess. 2012;28(2):138–44.
Gallacher K, May C, Montori V, Mair F. Assessing treatment burden in chronic heart failure patients. Heart. 2010;96(s1):A37–8.
May C. Retheorizing the clinical encounter. In: Scambler G, Scambler S, editors. Assaults on the lifeworld: new directions in the sociology of chronic and disabling conditions. London: Routledge; 2010.
Shippee ND, Shah ND, May CR, Mair FS, Montori VM. Cumulative complexity: a functional, patient-centered model of patient complexity can improve research and practice. J Clin Epidemiol. 2012;65(10):1041–51.
May C, Eton DT, Boehmer KR, Gallacher K, Hunt K, MacDonald S, Mair FS, May CM, Montori VM, Richardson A, et al. Rethinking the patient: using burden of treatment theory to understand the changing dynamics of illness. BMC Health Serv Res. 2014;14(1):281.
Burridge LH, Foster MM, Donald M, Zhang J, Russell AW, Jackson CL. Making sense of change: patients’ views of diabetes and GP-led integrated diabetes care. Health Expect. 2016;19(1):74–86.
Gallacher K, May CR, Montori VM, Mair FS. Understanding patients’ experiences of treatment burden in chronic heart failure using normalization process theory. Annal Fam Med. 2011;9(3):235–43.
McNaughton RJ, Shucksmith J. Reasons for (non)compliance with intervention following identification of ‘high-risk’ status in the NHS health check programme. Journal of Public Health. 2015;37(2):218–25.
Tiedje K, Boehm D, Montori VM. Factors that lessen the burden of treatment in complex patients with chronic conditions: a qualitative study. Patient Preference Adherence. 2014;8:339–51.
Tiedje K, Shippee ND, Johnson AM, Flynn PM, Finnie DM, Liesinger JT, May CR, Olson ME, Ridgeway JL, Shah ND, et al. ‘They leave at least believing they had a part in the discussion’: understanding decision aid use and patient-clinician decision-making through qualitative research. Patient Educ Couns. 2013;93(1):86–94.
May CR, Cummings A, Myall M, Harvey J, Pope C, Griffiths P, Roderick P, Arber M, Boehmer K, Mair FS, et al. Experiences of long-term life-limiting conditions among patients and carers: what can we learn from a meta-review of systematic reviews of qualitative studies of chronic heart failure, chronic obstructive pulmonary disease and chronic kidney disease? BMJ Open. 2016;6(10):e011694.
Sav A, King MA, Whitty JA, Kendall E, McMillan SS, Kelly F, Hunter B, Wheeler AJ. Burden of treatment for chronic illness: a concept analysis and review of the literature. Health Expect. 2015;18(3):312-24.
Demain S, Gonçalves A-C, Areia C, Oliveira R, Marcos AJ, Marques A, Parmar R, Hunt K. Living with, managing and minimising treatment burden in long term conditions: a systematic review of qualitative research. PLoS One. 2015;10(5):e0125457.
Finch TL, Girling M, May CR, Mair FS, Murray E, Treweek S, Steen IN, McColl EM, Dickinson C, Rapley T: NoMAD: implementation measure based on normalization process theory. Retrieved from http://wwwnormalizationprocessorg (12 April 2016) 2015.
O'Donnell CA, Mair FS, Dowrick C, MOR-d B, Td B, Burns N, Lionis C, Saridaki A, Papadakaki M, MvD M, et al. Supporting the use of theory in cross-country health services research: a participatory qualitative approach using normalisation process theory as an example. BMJ Open. 2017;7(8):e014289.
Murray E, May C, Mair F. Development and formative evaluation of the e-Health Implementation Toolkit (e-HIT). Bmc Med Inf Dec Making. 2010;10(1):61.
Muller I, Yardley L. Telephone-delivered cognitive behavioural therapy: a systematic review and meta-analysis. J Telemed Telecare. 2011;17(4):177–84.
Mohr DC, Ho J, Duffecy J, Reifler D, Sokol L, Burns MN, Jin L, Siddique J. Effect of telephone-administered vs face-to-face cognitive behavioral therapy on adherence to therapy and depression outcomes among primary care patients a randomized trial. Jama J Am Med Assoc. 2012;307(21):2278–85.
Bridges J, Flatley M, Meyer J. Older people’s and relatives’ experiences in acute care settings: systematic review and synthesis of qualitative studies. Int J Nurs Stud. 2010;47(1):89–107.
Greenfield D, Braithwaite J. Health sector accreditation research: a systematic review. Int J Qual Health Care. 2008;20(3):172–83.
Kousoulis AA, Patelarou E, Shea S, Foss C, Knutsen IAR, Todorova E, Roukova P, Portillo MC, Pumar-Mendez MJ, Mujika A, et al. Diabetes self-management arrangements in Europe: a realist review to facilitate a project implemented in six countries. BMC Health Serv Res. 2014;14:453.
Khosravi P, Ghapanchi AH. Investigating the effectiveness of technologies applied to assist seniors: a systematic literature review. Int J Med Inform. 2016;85(1):17–26.
NICE. Psychosis and schizophrenia in adults: prevention and management [CG178]. London: National Institute for Health and Care Excellence; 2014.
APA. Practice guideline for the treatment of patients with bipolar disorder (2nd edition). Arlington: American Psychiatric Association; 2002.
Johnson MJ, May CR. Promoting professional behaviour change in healthcare: what interventions work, and why? A theory-led overview of systematic reviews. BMJ Open. 2015;5(9):e008592.
Elwyn G, Legare F, Edwards A, van der Weijden T, May C. Arduous implementation: does the normalisation process model explain why it is so difficult to embed decision support technologies in routine clinical practice. Implement Sci. 2008;3:57.
Elwyn G, Scholl I, Tietbohl C, Mann M, Edwards AGK, Clay C, Legare F, van der Weijden T, Lewis CL, Wexler RM, et al. “Many miles to go ... ”: a systematic review of the implementation of patient decision support interventions into routine clinical practice. BMC Med Inf Dec Making. 2013:13.
Feder G, Ramsay J, Dunne D, Rose M, Arsene C, Norman R, Kuntze S, Spencer A, Bacchus L, Hague G, et al. How far does screening women for domestic (partner) violence in different health-care settings meet criteria for a screening programme? Systematic reviews of nine UK National Screening Committee criteria. Health Technol Assess. 2009;13(16):1–113. iii-iv, xi-xiii, 137-347
We thank Professor Anne MacFarlane for her helpful comments on an earlier version of the manuscript.
CRM, MB, AC and MM were supported by the National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care (NIHR CLAHRC) Wessex, which is a partnership between Wessex NHS organisations and partners and the University of Southampton. TLF, MG, FSM, EM, and TR were supported by the Economic and Social Research Council, Grant ES-062-23-3274. EM is also supported by the NIHR School of Primary Care Research. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR, the Department of Health or the Economic and Social Research Council. Funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. CMM’s contribution was supported in part by Macmillan Cancer Support through core funding of the Macmillan Survivorship Research Group at the University of Southampton.
During the period in which this work was undertaken, CRM was a member of staff in the Faculty of Health Sciences, University of Southampton, UK. With Prof Alison Richardson, he jointly led the Patient Experience and Organisational Behaviour Research Programme of NIHR CLARHC Wessex.
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CRM and TLF are the lead architects of NPT. FSM, EM and TR all played leading roles in the development and empirical application of NPT.
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May, C.R., Cummings, A., Girling, M. et al. Using Normalization Process Theory in feasibility studies and process evaluations of complex healthcare interventions: a systematic review. Implementation Sci 13, 80 (2018). https://doi.org/10.1186/s13012-018-0758-1
- Normalization Process Theory
- Complex interventions
- Implementation research
- Process evaluation
- Systematic review