Process Evaluations nested in randomised controlled trials of complex interventions: A scoping review of approaches and reporting

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To date, there has been limited review of how the MRC guidance has been operationalised in RCTs of complex interventions. Objectives This scoping review aimed to identify how process evaluations nested in RCTs on complex interventions have been conducted and reported since the 2015 publication of MRC guidance. Methods We identified articles in Pubmed and Scopus that cited the 2015 main journal article on the MRC guidance and applied an RCT filter to these articles. Studies reporting on RCT nested process evaluations in any field of health or social care were included. Data was extracted about study details, process evaluation study design, including methods used for data collection, data analyses, integration with RCT data and use of theory in process evaluation design. Results We identified 160 RCTs and 53 pilot/feasibility RCTs. Most process evaluations included a combination of qualitative and quantitative data collection methods, either triangulated (mixed method studies) or not (multi-method studies). Most studies did not report the use of theory in shaping how the process evaluation was designed. Common methods for data analysis included descriptive statistics and thematic analysis for quantitative and qualitative studies respectively. There was limited triangulation of process evaluation data with RCT outcomes. Conclusions While process evaluations can be helpful in explaining outcomes of RCT interventions and subsequent implementation of these intentions, information gathered from process evaluations is often not fully reported in papers. There are currently no suitable reporting guidelines for process evaluations linked to RCTs; work to develop such guidelines, potentially as a StaRI checklist extension would be valuable. Process evaluations Randomised Controlled Trials Scoping Review Figures Figure 1 Figure 2 Background The role and value of process evaluations conducted alongside trials is long established ( 1 , 2 ). The United Kingdom (UK) Medical Research Council (MRC) guidance for complex interventions recommends the nesting of process evaluations in randomised controlled trials (RCTs) of complex interventions. This guidance defines a process evaluation as: “a study which aims to understand the functioning of an intervention by examining implementation, mechanisms of impact and contextual factors” ( 3 ). Complex interventions are commonly defined as “interventions that comprise multiple interacting components” ( 4 ). By exploring a complex intervention’s implementation, receipt of intervention, setting of intervention, potential mechanisms of action, and how contextual factors can shape these, process evaluations give nuanced insight into how and why anticipated changes have, or have not, been achieved ( 2 , 5 ). Additionally, process evaluations can inform decision makers about the transferability of RCT findings and how this may influence implementation approaches for evaluated interventions, including potential barriers or facilitators ( 3 ). The 2015 MRC Guidance outlines a consensus-derived framework for process evaluations within complex interventions and recognises that process evaluation designs are likely to vary between different RCTs; the guidance’s aim is to facilitate a more systematic approach to process evaluations, drawing on intervention theory and the specification of key process evaluation components mapped to intervention outcomes. ( 3 ). To date, there has been limited review of how the MRC guidance has been operationalised in RCTs of complex interventions. This scoping review will give an overview of the methods used in process evaluations nested in RCTs of complex interventions and the reporting of these studies. This is an important step in providing the research community with insights into: enactment of the MRC guidance in practice, the theories and methods commonly being used, and how well these process evaluations being presented back to end evidence users. Additionally, because there is a lack of more operational and detailed guidance to support process evaluation design and reporting, the findings of this scoping review are an important step in considering additional guidance, that may be needed. Objectives This scoping review aimed to identify how process evaluations nested in RCTs on complex interventions have been conducted and reported since the 2015 publication of MRC guidance ( 3 ). Methods We conducted a scoping review, using the methodological framework proposed by Arksey and O’Malley (6) and developed by Levac et al.(7) and Peters et al. (8). We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Scoping Review checklist for reporting purposes (9). The protocol is published on Open Science Framework (10). Searches We identified articles in Pubmed and Scopus that cited the 2015 main journal article on the MRC guidance (3) and applied an RCT filter to these articles. The search was conducted on the 15 th of July 2024 and the Scopus search strategy can be found in supplementary materials. Study inclusion criteria To ensure adherence to the definition and aims of process evaluations as proposed in the 2015 MRC guidance, we focused on RCTs on complex interventions with embedded process evaluations that cited the BMJ 2015 journal article that referenced the guidance and were informed by it as per use in process evaluation methods (3). We considered process evaluation methods to be informed by the guidance if they mentioned something along the lines of “based on”, informed by’, “guided by” or “used Moore et al.’s or MRC’s approach”, or something similar. Studies reporting on RCT nested process evaluations in any field of health or social care were included. We included articles published separately as well as those that were part of an RCT report. We accepted authors’ definitions and descriptions of trials as being randomised, as well as their definitions of process evaluation. We also assumed that studies were of complex interventions rather than assessing this specifically. We excluded process evaluations that cited the guidance article (3) as a background reference but did not use the article to help shape or inform process evaluation methods. We only included studies reported in English and as full text articles (although process evaluations could be reported only briefly as part of an RCT report or article). We excluded protocols for both process evaluations and RCTs including process evaluations. We included both process evaluations embedded in pilot/feasibility studies as well as in full RCTs. We acknowledge that process evaluations have a different role in both types of study. In the feasibility phase, a process evaluation can play a role in understanding feasibility of the intervention and optimising its design and evaluation while in a full RCT, the process evaluation shifts towards providing greater confidence in conclusions about effectiveness by assessing the quantity and quality of what was delivered as well as assessing generalisability of its effectiveness. Screening Title and abstract screening were conducted in Rayyan (11) by one researcher. Full text screening was also conducted by one researcher. Uncertainties were discussed among team members with a final decision being reached via consensus. Data extraction and categorisation Data were extracted to classify studies on key characteristics and to chart available literature (6). Following instructions by Levac et al. (7) we developed a bespoke data extraction form in Excel to enable categorisation for the variables listed. Data were subsequently categorised by one researcher, with a sample of 5% cross-checked by a second researcher. Where there was uncertainty, a third researcher was consulted, and a final decision made. To optimise insights from the scoping review as well as methods used, the following information was extracted and, for some fields, categorised. These categories were developed based on initial detailed extraction and similarities identified across articles. The categories were piloted by the research team during the development of the protocol. They were also tested and refined during the piloting phase of the research: - Title, authors, year of publication - Country in which RCT conducted - Reporting of process evaluation: o Part of main RCT paper o Separate paper o Separate chapter in RCT report - Process evaluation study design, including: o Timing of process evaluation: categorised as pre-RCT, during RCT data collection period, after RCT data collection has finished, or data collected at multiple time points during the RCT. o Theory used for process evaluation, and if theory was used, what theory and how it was used. We categorised use of theory as follows: No theory – studies reporting a theory or framework cited as background reference only, or studies only reporting the MRC Guidance BMJ article as theory (3). Superficially informed – study did mention a theory or framework but did not explain how this was used. Conceptually informed – theory was used to develop data collection materials or guide analysis. Theoretically informed – theory was used to develop data collection materials, guide analysis and explain outcomes. o Methods used for data collection, categorised as: Quantitative · Process data, including routinely collected quantitative data regarding intervention and trial processes, e.g. trial logbooks, dose measurements or reach data. · Survey/Questionnaire Qualitative · Process data, including routinely collected qualitative data regarding intervention and trial processes. · Individual in-depth interviews · Focus groups · Questionnaire · Participant comments/informal discussions o Number of methods used for data collection for the process evaluation, categorised as: Single methods, including one method for process evaluation data collection only. Multi-method, including multiple methods of data collection for the process evaluation but without triangulation of process evaluation data. This includes studies collecting qualitative data only and quantitative data only in multiple ways. Mixed method, including multiple methods of data collection as part of the process evaluation, including both qualitative and quantitative data collection, with described triangulation. o Methods used for data analysis, categorised as: Quantitative · Descriptive statistics · Inferential statistical analyses Qualitative · Thematic analysis · Content analysis · Descriptive qualitative analysis · Framework analysis · Template analysis · Other, including analyses that were only used in one study. o If process evaluation data were integrated with RCT outcomes. Process evaluation outcomes were classified as integrated with RCT outcomes if there was some, even very limited, interaction or conversation between the outcomes of the RCT and the process evaluation (12), and it was described how different sets of findings help to gain a more complete picture. We refer to this as data triangulation (12). Some studies referred to RCT outcomes and how these were linked to process evaluations in the discussion section of the articles, we did not consider this ‘data triangulation’ as no methods had been described about how triangulation occurred. Data charting Whilst we included process evaluations nested in pilot/feasibility RCTs, as these trials have different aims and purposes to full RCTs, we charted their data separately. We used structured tables to support a narrative presentation of data, with a particular focus on summarising how process evaluation studies nested in RCTs have been informed by theory; when and how process evaluation data had been collected; and how data had been analysed, with a particular focus on if and how triangulation of process data with RCT data had taken place. Results Search results We identified 1909 records. After the first screening of titles and abstracts, we obtained the full text of 547 records. Of the 547 records, 321 were excluded as the study was not informed by the MRC Guidance, and three records did not regard an RCT embedded process evaluation. In total 223 records, regarding 213 studies, were included in the scoping review (Fig. 1 ). Characteristics of included studies We identified 160 RCTs and 53 pilot/feasibility RCTs (Table 1 ). An overview of year of publication is provided in Fig. 2 . While 12 studies were conducted in multiple countries, most studies took place in only one country, and we identified 27 different countries. In total 90 studies were conducted in the UK, 20 in Australia, 17 in the Netherlands, 11 in Germany, seven in Sweden, six each in South Africa, Norway and USA, five in China, four each in Canada, India and Denmark, three each in Ireland and Singapore, two in Zambia and one each in Finland, Lithuania, Mozambique, New Zealand, Peru, Spain, Switzerland, Türkiye, Uganda, Vietnam and Zimbabwe. Most process evaluations nested in a RCT were reported in a separate paper from the main trial paper, while for pilot/feasibility studies a smaller majority was reported separately. In both pilot/feasibility studies and full RCTs, most process evaluations were conducted during the trial (47/53 and 139/160 respectively) (Table 1 ). Use of theory in process evaluations Most studies did not report the use of theory in shaping how the process evaluation was designed. Only, 10 out of 53 process evaluations (19%) associated with pilot/feasibility RCTs and 17 out of 160 (11%) process evaluations associated with RCTs reported being theoretically informed (Table 2 ). Despite MRC guidance on use of intervention theory to shape process evaluations, in practice theory use was limited. Information on the studies using theory, and what theories they used is provided in supplementary materials. Table 1 Overview of process evaluation approach, methodology and methods Pilot/Feasibility study: Total n = 53; n (%) RCT: Total n = 160; n (%) Reporting of process evaluation Part of trial paper 28 (53%) 16 (10%) Separate paper 20 (38%) 126 (79%) Separate chapter in full study report 5 (9%) 11 (7%) Multiple reports 0 (0%) 7 (4%) Timing of process evaluation in relation to RCT Pre 3 (6%) 2 (1%) During 47 (89%) 139 (87%) Post 3 (6%) 14 (9%) Multiple 0 (0%) 5 (3%) Table 2 Use of theory in Process Evaluations No theory n (%) Superficially informed n (%) Conceptually Informed n (%) Theoretically informed n (%) Pilot/Feasibility RCT (total n = 53) 38 (72%) 1 (2%) 4 (8%) 10 (19%) RCT (total n = 160) 122 (76%) 3 (2%) 18 (11%) 17 (11%) Data collection Most process evaluations included a combination of qualitative and quantitative data collection methods, either triangulated (mixed method studies) or not (multi-method studies) as reported in Table 3 . The two most reported approaches for quantitative data collection were process data and surveys or questionnaires (Table 4 ). Process data included logbooks and other standard data collected as part of the trial while surveys were tools specifically employed for process evaluation data collection. There was more variety in qualitative data collection methods, but most studies, pilot/feasibility (n = 45 out of 53, 85%) and RCTs (n = 115 out of 160, 72%), used individual in-depth interviews as a method of data collection; focus groups were less commonly used. Qualitative process data, including participant observations, were collected in 52/160 (33%) of process evaluations nested in full RCTs and in 18/53 (34%) process evaluations of pilot/feasibility studies. Table 3 Data collection in embedded process evaluations Data collection Pilot/Feasibility study: Total n = 53; n (%) Full RCT: Total n = 160; n (%) Single Method Quantitative 1 (2%) 13 (8%) Qualitative 14 (26%) 27 (17%) Multi-method Quantitative 1 (2%) 4 (3%) Qualitative 3 (6%) 15 (9%) Both 22 (42%) 53 (33%) Mixed method 12 (23%) 48 (30%) Table 4 Types of data collected in embedded process evaluation Type of data collected Data collection method Pilot/Feasibility study: Total n = 53; n (%) Full RCT: Total n = 160; n (%) Quantitative Process data 29 (55%) 102 (64%) Survey/Questionnaire 22 (42%) 62 (39%) Qualitative Process data 18 (34%) 52 (33%) Individual in-depth interview 45 (85%) 115 (72%) Focus Group 16 (30%) 41 (26%) Questionnaire 4 (8%) 27 (17%) Participant comments/informal discussion 3 (6%) 13 (8%) Data analyses and triangulation of process evaluations Most quantitative analyses were reportedly analysed using descriptive statistics, (33/53, 62%, process evaluations of pilot/feasibility RCTs and 100/160, 63%, process evaluations of full RCTs) (Table 5 ). Fewer than a third of included studies reported an inferential statistical analysis, which could be due to MRC recommendation to provide descriptive analyses regarding fidelity, dose and reach. In 28 (53%) qualitative process evaluations of pilot/feasibility studies, as well as in 75 (47%) of the process evaluations in full RCTs a thematic analysis was conducted. Table 5 Data analysis methods Type of data analysed Data analysis method Occurrence in Pilot/Feasibility study: Total n = 53; n (%) Occurrence in full RCTs: Total n = 160; n (%) Quantitative Descriptive statistics 33 (62%) 100 (63%) Statistical analysis 10 (19%) 42 (26%) Qualitative Thematic analysis 28 (53%) 75 (47%) Content analysis 4 (8%) 20 (13%) Framework analysis 11 (21%) 33 (21%) Descriptive analysis 2 (4%) 16 (10%) Template analysis 2 (4%) 2 (1%) Other (only used in 1 study) 2 (4%) 9 (6%) There was limited triangulation of process evaluation data with RCT outcomes, being reported in 16 of 53 of pilot/feasibility studies (30%) and 26 out of 160 full RCTs (16%). An overview of studies triangulating data is presented in supplementary materials. We aimed to identify ways to triangulate process data with trial data, but limited information was reported in articles. Where information was provided it referred to triangulation of data or comparing of process evaluation data with primary/secondary RCT outcome measures. Process evaluations helped explain contextual factors or mechanisms that led to trial outcomes. Discussion We conducted this scoping review to explore methods and reporting of process evaluations nested in RCTs on complex interventions. We found that most process evaluations are conducted during the RCT data collection period and use multiple methods for data collection. Differences between pilot/feasibility RCTs and RCTs were limited, particularly regarding data collection and analyses. However, pilot/feasibility RCTs were more often reported as part of the main trial paper. While numbers were very small, it seems more process evaluations in pilot/feasibility RCTs were theoretically informed as compared to RCTs (19% and 11% respectively). A reason for not reporting triangulation with RCT data or not reporting theoretical guidance may be due to limited word count for articles. This can be an issue for all studies and especially challenging for the reporting of process evaluations that were included in the main RCT paper, with more competition for space. However, as only 36% of pilot/feasibility RCTs and 9% of full RCTs were reported as part of the main study paper, there appear to be wider reporting issues for nested process evaluations in RCTs of complex interventions. Only a third of the studies included in this review reported integration of process evaluation data with RCT findings and very limited information was available in methods and results sections as to how data triangulation between process evaluation data and RCT outcome data took place. Apart from implementation processes, process evaluations aim to help explain trial findings ( 2 , 3 ), and the lack of reported process data triangulation with trial data leads us to believe opportunities to do this may have been missed. Additionally, process evaluations could potentially help highlight contextual factors that facilitate or prevent intervention outcomes form occurring. Knowledge of these could support implementation activities and increase impact of the intervention. While theory use is recommended by Moore et al., most included studies did not report using theory. This is a missed opportunity as the use of theory offers a route to mechanism-based explanation of the relationships between interventions, contexts and desired outcomes ( 13 ). Our review highlights that when theory is applied, it is restricted to superficial use (mentioned in the background/ methods section but then plays no part in what follows) or conceptual use (used to guide data collection and to structure results). A theory guided approach encompassing hypothesis generation, data collection, analysis and the interpretation of outcomes (and their wider meaning), is currently rare. That this is currently lacking means that we are missing opportunities to maximise learning on how mechanisms might generate different outcomes in different contexts and on the potential transferability of interventions themselves ( 14 ). We are also missing opportunities to complete the scientific circle of enquiry itself, using new empirical findings to either consolidate, refine or expand existing theoretical knowledge that can then be used to further our understanding of what works where, how and why ( 13 ). If process evaluations can be more theoretically guided, we are more likely to be theoretically informative, and more likely to contribute new and transferrable knowledge. Issues with the reporting of process evaluations nested in RCTs have been flagged previously, reinforcing the need to develop materials and tools to move the field forwards. Past reviews on the design and methodologies of process evaluations in specific settings, including neurological rehabilitation ( 15 ), pragmatic RCTs ( 16 ), and church-based health promotion interventions ( 17 ) or worksite health programmes ( 18 , 19 ), highlighted the lack of consistency in nested process evaluation conduct ( 17 – 19 ), the lack of reporting of key process evaluation outcomes ( 16 ), gaps in evidence-informed process evaluation guidance ( 15 ), the lack of clear links between process evaluation and full RCT outcome results ( 15 ) and a lack of theoretical basis ( 18 ). A 2007 review concluded that incomplete reporting of information regarding process evaluations, including 61.5% (n = 32) studies with an experimental design (randomised comparison or control group), of occupational stress management programmes makes it difficult to identify reliable determinants of effective intervention implementation and outcome ( 19 ). The gap in knowledge regarding reporting of process evaluations and how the process evaluation links with intervention outcomes was already flagged in 2009 ( 20 ). Despite seemingly increased use of process evaluations following MRC guidance, there seems to have been little progress in reporting of process evaluations or their linking with RCT or other studies of effectiveness of interventions. Currently, there are no reporting standards for process evaluations nested in RCTs of complex interventions. The development of a suitable reporting framework may increase reporting quality and would bring these studies into line with the plethora of other designs with their own reporting framework ( 21 ). While the Standards for Reporting Implementation Studies (StaRI) initiative ( 22 ), aimed at supporting transparent and accurate reporting of implementation studies, could, in theory, be used to support clear and consistent reporting of process evaluations nested in RCTs, in practice it is unlikely to be tailored enough to do this. For example, a reporting checklist for process evaluations nested in RCTs would benefit from increased focus on various aspects of process evaluation methods, rather than being just a single item, which they are in StaRI ( 22 ). Additionally, a bespoke checklist should focus on the reporting of intervention mechanisms, not just intervention outcomes, as well as the various foci of the process evaluation, including implementation, contextual factors, and mechanisms of action. Reports of process evaluations nested in RCTs should contain a section on triangulation of process data and RCT data. In summary we suggest there is scope to develop a bespoke reporting tool aimed at improving reporting of RCT embedded process evaluations. Strengths and limitations This scoping review used a systematic approach with a registered protocol to identify process evaluations in pilot/feasibility RCTs and RCTs. We included any process evaluation of a health or social care intervention in any setting if it was linked to a pilot/feasibility RCT or full RCT. The requirement that the evaluation adhere to MRC guidance ensured that the review focused on those evaluations which were based on recommended approaches. Limitations include the use of a single reviewer for screening and data extraction, which could have led to studies being missed, or studies being wrongfully included due to confirmation bias. We tried to mitigate this by referral to the team of any uncertainties in decision making and by checking and discussion of data extraction. Limitation to English language reports has the potential to exclude relevant studies and to impact the results of the review if the effects of this are non-random. However, no studies were excluded solely for this reason. Limitation to full text papers was necessary to be able to extract relevant information. Conclusion Process evaluations are a helpful tool to explain the outcomes of RCTs of complex interventions, support the subsequent implementation of interventions and their impact. However, information gathered from process evaluations nested in RCTs is often not fully reported in papers, particularly where the process evaluation is reported within the same journal article as the linked RCT. In such cases we recommend authors use supplementary information to provide fuller information about the process evaluation. There are currently no suitable reporting guidelines for process evaluations linked to RCTs; work to develop such guidelines, potentially as a StaRI checklist extension would be valuable. Beyond this it may be helpful to consider what components could contribute to a quality appraisal tool for process evaluations to support further methods development and subsequent reviewers. Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials The datasets generated and analysed for this study are available from the corresponding author on request. Competing interests The authors declare they have no competing interests Funding The authors are in receipt of funding from the NIHR Applied Research Collaboration Greater Manchester. JD is a NIHR Senior Investigator. The views expressed in this paper are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. Author’s contributions MK, JD and PW contributed to the inception of the idea and rationale for the review; MK was conducted searches; MK and GN conducted screening and data extraction; MK, GN, JD and PW were involved in analysis and synthesis of data and writing up of the review. Acknowledgements Not applicable References Grant A, Treweek S, Dreischulte T, Foy R, Guthrie B. Process evaluations for cluster-randomised trials of complex interventions: a proposed framework for design and reporting. Trials. 2013;14:15. Oakley A, Strange V, Bonell C, Allen E, Stephenson J, Team RS. 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Supplementary Files PRISMAScRFillable1608.docx Overviewincludedstudies.xlsx Searches.docx SupplementaryFiletheory.docx Supplementaryfiletriangulation.docx Cite Share Download PDF Status: Published Journal Publication published 30 Jul, 2025 Read the published version in Trials → Version 1 posted Editorial decision: Accept 29 May, 2025 Reviewers agreed at journal 30 Apr, 2025 Reviewers invited by journal 30 Apr, 2025 Editor assigned by journal 30 Apr, 2025 First submitted to journal 29 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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13:08:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4938846/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4938846/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13063-025-08910-x","type":"published","date":"2025-07-30T16:05:18+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81820914,"identity":"b21017b6-ba16-4fed-a276-f5891e460fd1","added_by":"auto","created_at":"2025-05-02 11:17:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":36659,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePRISMA flow diagram\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4938846/v1/3d6176ddc80e40badf213bc7.png"},{"id":81820912,"identity":"309aaf7f-fa10-4ca3-927e-5f8fdffc3d9b","added_by":"auto","created_at":"2025-05-02 11:17:01","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":12678,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverview of year of publication of articles included in the scoping review (n=223).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-4938846/v1/ba158cad434e979fdd3a9573.png"},{"id":88268261,"identity":"56a92e76-c20e-4ff8-a94b-fda6f9c8ebcc","added_by":"auto","created_at":"2025-08-04 16:50:31","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":842185,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4938846/v1/cf4a3d4d-4625-4e31-96ea-ea53ba29345d.pdf"},{"id":81820913,"identity":"c05fae38-b2aa-4a25-9f02-cb76a3cef386","added_by":"auto","created_at":"2025-05-02 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11:17:02","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":13657,"visible":true,"origin":"","legend":"","description":"","filename":"Searches.docx","url":"https://assets-eu.researchsquare.com/files/rs-4938846/v1/77d31da4e73aefd81c58384a.docx"},{"id":81820917,"identity":"aa4088c0-fffc-4fd1-8b0d-a60947cb798c","added_by":"auto","created_at":"2025-05-02 11:17:02","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":28282,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFiletheory.docx","url":"https://assets-eu.researchsquare.com/files/rs-4938846/v1/8409b5b7896654348f4bc633.docx"},{"id":81822881,"identity":"ac547d47-8eb3-480c-a7bc-70a9dfe7f7e4","added_by":"auto","created_at":"2025-05-02 11:41:02","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":25618,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfiletriangulation.docx","url":"https://assets-eu.researchsquare.com/files/rs-4938846/v1/6f39d41198dc7cd4f5d88858.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eProcess Evaluations nested in randomised controlled trials of complex interventions: A scoping review of approaches and reporting\u003c/p\u003e","fulltext":[{"header":"Background","content":"\u003cp\u003eThe role and value of process evaluations conducted alongside trials is long established (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The United Kingdom (UK) Medical Research Council (MRC) guidance for complex interventions recommends the nesting of process evaluations in randomised controlled trials (RCTs) of complex interventions. This guidance defines a process evaluation as: \u003cem\u003e“a study which aims to understand the functioning of an intervention by examining implementation, mechanisms of impact and contextual factors”\u003c/em\u003e (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Complex interventions are commonly defined as \u003cem\u003e“interventions that comprise multiple interacting components”\u003c/em\u003e (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBy exploring a complex intervention’s implementation, receipt of intervention, setting of intervention, potential mechanisms of action, and how contextual factors can shape these, process evaluations give nuanced insight into how and why anticipated changes have, or have not, been achieved (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Additionally, process evaluations can inform decision makers about the transferability of RCT findings and how this may influence implementation approaches for evaluated interventions, including potential barriers or facilitators (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe 2015 MRC Guidance outlines a consensus-derived framework for process evaluations within complex interventions and recognises that process evaluation designs are likely to vary between different RCTs; the guidance’s aim is to facilitate a more systematic approach to process evaluations, drawing on intervention theory and the specification of key process evaluation components mapped to intervention outcomes. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo date, there has been limited review of how the MRC guidance has been operationalised in RCTs of complex interventions. This scoping review will give an overview of the methods used in process evaluations nested in RCTs of complex interventions and the reporting of these studies. This is an important step in providing the research community with insights into: enactment of the MRC guidance in practice, the theories and methods commonly being used, and how well these process evaluations being presented back to end evidence users. Additionally, because there is a lack of more operational and detailed guidance to support process evaluation design and reporting, the findings of this scoping review are an important step in considering additional guidance, that may be needed.\u003c/p\u003e\n\u003ch3\u003eObjectives\u003c/h3\u003e\n\u003cp\u003eThis scoping review aimed to identify how process evaluations nested in RCTs on complex interventions have been conducted and reported since the 2015 publication of MRC guidance (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cp\u003eWe conducted a scoping review, using the methodological framework proposed by Arksey and O\u0026rsquo;Malley (6) and developed by Levac et al.(7) and Peters et al. (8). We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Scoping Review checklist for reporting purposes (9). The protocol is published on Open Science Framework (10).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSearches\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe identified articles in Pubmed and Scopus that cited the 2015 main journal article on the MRC guidance (3) and applied an RCT filter to these articles. The search was conducted on the 15\u003csup\u003eth\u003c/sup\u003e of July 2024 and the Scopus search strategy can be found in supplementary materials.\u003c/p\u003e\n\u003cp\u003eStudy inclusion criteria\u003c/p\u003e\n\u003cp\u003eTo ensure adherence to the definition and aims of process evaluations as proposed in the 2015 MRC guidance, we focused on RCTs on complex interventions with embedded process evaluations that cited the BMJ 2015 journal article that referenced the guidance and were informed by it as per use in process evaluation methods (3). We considered process evaluation methods to be informed by the guidance if they mentioned something along the lines of \u0026ldquo;based on\u0026rdquo;, informed by\u0026rsquo;, \u0026ldquo;guided by\u0026rdquo; or \u0026ldquo;used Moore et al.\u0026rsquo;s or MRC\u0026rsquo;s approach\u0026rdquo;, or something similar. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStudies reporting on RCT nested\u0026nbsp;process evaluations in any field of health or social care were included. We included articles published separately as well as those that were part of an RCT report. We accepted authors\u0026rsquo; definitions and descriptions of trials as being randomised, as well as their definitions of process evaluation. We also assumed that studies were of complex interventions rather than assessing this specifically.\u003c/p\u003e\n\u003cp\u003eWe excluded process evaluations that cited the guidance article (3) as a background reference but did not use the article to help shape or inform process evaluation methods. We only included studies reported in English and as full text articles (although process evaluations could be reported only briefly as part of an RCT report or article). We excluded protocols for both process evaluations and RCTs including process evaluations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe included both process evaluations embedded in pilot/feasibility studies as well as in full RCTs. We acknowledge that process evaluations have a different role in both types of study. In the feasibility phase, a process evaluation can play a role in understanding feasibility of the intervention and optimising its design and evaluation while in a full RCT, the process evaluation shifts towards providing greater confidence in conclusions about effectiveness by assessing the quantity and quality of what was delivered as well as assessing generalisability of its effectiveness.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eScreening\u003c/p\u003e\n\u003cp\u003eTitle and abstract screening were conducted in Rayyan (11) by one researcher. Full text screening was also conducted by one researcher. Uncertainties were discussed among team members with a final decision being reached via consensus.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u0026nbsp;Data extraction and categorisation\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData were extracted to classify studies on key characteristics and to chart available literature (6). Following instructions by Levac et al. (7) we developed a bespoke data extraction form in Excel to enable categorisation for the variables listed. Data were subsequently categorised by one researcher, with a sample of 5% cross-checked by a second researcher. Where there was uncertainty, a third researcher was consulted, and a final decision made. To optimise insights from the scoping review as well as methods used, the following information was extracted and, for some fields, categorised. These categories were developed based on initial detailed extraction and similarities identified across articles. The categories were piloted by the research team during the development of the protocol. They were also tested and refined during the piloting phase of the research:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e- \u0026nbsp; \u0026nbsp; \u0026nbsp;Title, authors, year of publication\u003c/p\u003e\n\u003cp\u003e- \u0026nbsp; \u0026nbsp; \u0026nbsp;Country in which RCT conducted\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e- \u0026nbsp; \u0026nbsp; \u0026nbsp;Reporting of process evaluation:\u003c/p\u003e\n\u003cp\u003eo Part of main RCT paper\u003c/p\u003e\n\u003cp\u003eo Separate paper\u003c/p\u003e\n\u003cp\u003eo Separate chapter in RCT report\u003c/p\u003e\n\u003cp\u003e- \u0026nbsp; \u0026nbsp; \u0026nbsp;Process evaluation study design, including:\u003c/p\u003e\n\u003cp\u003eo Timing of process evaluation: categorised as pre-RCT, during RCT data collection period, after RCT data collection has finished, or data collected at multiple time points during the RCT.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eo Theory used for process evaluation, and if theory was used, what theory and how it was used. We categorised use of theory as follows:\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;No theory \u0026ndash; studies reporting a theory or framework cited as background reference only, or studies only reporting the MRC Guidance BMJ article as theory (3). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Superficially informed \u0026ndash; study did mention a theory or framework but did not explain how this was used.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Conceptually informed \u0026ndash; theory was used to develop data collection materials or guide analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Theoretically informed \u0026ndash; theory was used to develop data collection materials, guide analysis and explain outcomes. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eo Methods used for data collection, categorised as:\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Quantitative\u003c/p\u003e\n\u003cp\u003e\u0026middot; Process data, including routinely collected quantitative data regarding intervention and trial processes, e.g. trial logbooks, dose measurements or reach data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026middot; Survey/Questionnaire\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Qualitative\u003c/p\u003e\n\u003cp\u003e\u0026middot; Process data, including routinely collected qualitative data regarding intervention and trial processes.\u003c/p\u003e\n\u003cp\u003e\u0026middot; Individual in-depth interviews\u003c/p\u003e\n\u003cp\u003e\u0026middot; Focus groups\u003c/p\u003e\n\u003cp\u003e\u0026middot; Questionnaire\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026middot; Participant comments/informal discussions\u003c/p\u003e\n\u003cp\u003eo Number of methods used for data collection for the process evaluation, categorised as:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Single methods, including one method for process evaluation data collection only.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Multi-method, including multiple methods of data collection for the process evaluation but without triangulation of process evaluation data. This includes studies collecting qualitative data only and quantitative data only in multiple ways.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Mixed method, including multiple methods of data collection as part of the process evaluation, including both qualitative and quantitative data collection, with described triangulation.\u003c/p\u003e\n\u003cp\u003eo Methods used for data analysis, categorised as:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Quantitative\u003c/p\u003e\n\u003cp\u003e\u0026middot; Descriptive statistics\u003c/p\u003e\n\u003cp\u003e\u0026middot; Inferential statistical analyses\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Qualitative\u003c/p\u003e\n\u003cp\u003e\u0026middot; Thematic analysis\u003c/p\u003e\n\u003cp\u003e\u0026middot; Content analysis\u003c/p\u003e\n\u003cp\u003e\u0026middot; Descriptive qualitative analysis\u003c/p\u003e\n\u003cp\u003e\u0026middot; Framework analysis\u003c/p\u003e\n\u003cp\u003e\u0026middot; Template analysis\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026middot; Other, including analyses that were only used in one study.\u003c/p\u003e\n\u003cp\u003eo If process evaluation data were integrated with RCT outcomes. Process evaluation outcomes were classified as integrated with RCT outcomes if there was some, even very limited, interaction or conversation between the outcomes of the RCT and the process evaluation (12), and it was described how different sets of findings help to gain a more complete picture. We refer to this as data triangulation (12). Some studies referred to RCT outcomes and how these were linked to process evaluations in the discussion section of the articles, we did not consider this \u0026lsquo;data triangulation\u0026rsquo; as no methods had been described about how triangulation occurred. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData charting\u003c/p\u003e\n\u003cp\u003eWhilst we included process evaluations nested in pilot/feasibility RCTs, as these trials have different aims and purposes to full RCTs, we charted their data separately. We used structured tables to support a narrative presentation of data, with a particular focus on summarising how process evaluation studies nested in RCTs have been informed by theory; when and how process evaluation data had been collected; and how data had been analysed, with a particular focus on if and how triangulation of process data with RCT data had taken place.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSearch results\u003c/h2\u003e \u003cp\u003eWe identified 1909 records. After the first screening of titles and abstracts, we obtained the full text of 547 records. Of the 547 records, 321 were excluded as the study was not informed by the MRC Guidance, and three records did not regard an RCT embedded process evaluation. In total 223 records, regarding 213 studies, were included in the scoping review (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCharacteristics of included studies\u003c/h3\u003e\n\u003cp\u003eWe identified 160 RCTs and 53 pilot/feasibility RCTs (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). An overview of year of publication is provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. While 12 studies were conducted in multiple countries, most studies took place in only one country, and we identified 27 different countries. In total 90 studies were conducted in the UK, 20 in Australia, 17 in the Netherlands, 11 in Germany, seven in Sweden, six each in South Africa, Norway and USA, five in China, four each in Canada, India and Denmark, three each in Ireland and Singapore, two in Zambia and one each in Finland, Lithuania, Mozambique, New Zealand, Peru, Spain, Switzerland, T\u0026uuml;rkiye, Uganda, Vietnam and Zimbabwe.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMost process evaluations nested in a RCT were reported in a separate paper from the main trial paper, while for pilot/feasibility studies a smaller majority was reported separately. In both pilot/feasibility studies and full RCTs, most process evaluations were conducted during the trial (47/53 and 139/160 respectively) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eUse of theory in process evaluations\u003c/h3\u003e\n\u003cp\u003eMost studies did not report the use of theory in shaping how the process evaluation was designed. Only, 10 out of 53 process evaluations (19%) associated with pilot/feasibility RCTs and 17 out of 160 (11%) process evaluations associated with RCTs reported being theoretically informed (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Despite MRC guidance on use of intervention theory to shape process evaluations, in practice theory use was limited. Information on the studies using theory, and what theories they used is provided in supplementary materials.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOverview of process evaluation approach, methodology and methods\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePilot/Feasibility study: Total n\u0026thinsp;=\u0026thinsp;53; n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRCT: Total n\u0026thinsp;=\u0026thinsp;160; n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003eReporting of process evaluation\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePart of trial paper\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (10%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSeparate paper\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e126 (79%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSeparate chapter in full study report\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMultiple reports\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cem\u003eTiming of process evaluation in relation to RCT\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePre\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eDuring\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47 (89%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e139 (87%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePost\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eMultiple\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUse of theory in Process Evaluations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo theory n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSuperficially informed n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConceptually Informed n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTheoretically informed n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePilot/Feasibility RCT (total n\u0026thinsp;=\u0026thinsp;53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (72%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (19%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRCT (total n\u0026thinsp;=\u0026thinsp;160)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e122 (76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (11%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17 (11%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eMost process evaluations included a combination of qualitative and quantitative data collection methods, either triangulated (mixed method studies) or not (multi-method studies) as reported in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe two most reported approaches for quantitative data collection were process data and surveys or questionnaires (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Process data included logbooks and other standard data collected as part of the trial while surveys were tools specifically employed for process evaluation data collection. There was more variety in qualitative data collection methods, but most studies, pilot/feasibility (n\u0026thinsp;=\u0026thinsp;45 out of 53, 85%) and RCTs (n\u0026thinsp;=\u0026thinsp;115 out of 160, 72%), used individual in-depth interviews as a method of data collection; focus groups were less commonly used. Qualitative process data, including participant observations, were collected in 52/160 (33%) of process evaluations nested in full RCTs and in 18/53 (34%) process evaluations of pilot/feasibility studies.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eData collection in embedded process evaluations\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eData collection\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePilot/Feasibility study: Total n\u0026thinsp;=\u0026thinsp;53; n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFull RCT: Total n\u0026thinsp;=\u0026thinsp;160; n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSingle Method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eQuantitative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eQualitative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (26%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (17%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMulti-method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eQuantitative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eQualitative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eBoth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53 (33%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMixed method\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (23%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48 (30%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTypes of data collected in embedded process evaluation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of data collected\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eData collection method\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePilot/Feasibility study: Total n\u0026thinsp;=\u0026thinsp;53; n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFull RCT: Total n\u0026thinsp;=\u0026thinsp;160; n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eQuantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProcess data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 (55%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102 (64%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSurvey/Questionnaire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62 (39%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eQualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProcess data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52 (33%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndividual in-depth interview\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (85%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115 (72%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFocus Group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41 (26%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuestionnaire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (17%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipant comments/informal discussion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData analyses and triangulation of process evaluations\u003c/h3\u003e\n\u003cp\u003eMost quantitative analyses were reportedly analysed using descriptive statistics, (33/53, 62%, process evaluations of pilot/feasibility RCTs and 100/160, 63%, process evaluations of full RCTs) (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Fewer than a third of included studies reported an inferential statistical analysis, which could be due to MRC recommendation to provide descriptive analyses regarding fidelity, dose and reach. In 28 (53%) qualitative process evaluations of pilot/feasibility studies, as well as in 75 (47%) of the process evaluations in full RCTs a thematic analysis was conducted.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eData analysis methods\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of data analysed\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eData analysis method\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOccurrence in Pilot/Feasibility study: Total n\u0026thinsp;=\u0026thinsp;53; n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOccurrence in full RCTs: Total n\u0026thinsp;=\u0026thinsp;160; n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eQuantitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescriptive statistics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100 (63%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStatistical analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (19%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (26%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eQualitative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThematic analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (53%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75 (47%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContent analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (13%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFramework analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (21%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33 (21%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescriptive analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16 (10%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTemplate analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther (only used in 1 study)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThere was limited triangulation of process evaluation data with RCT outcomes, being reported in 16 of 53 of pilot/feasibility studies (30%) and 26 out of 160 full RCTs (16%). An overview of studies triangulating data is presented in supplementary materials. We aimed to identify ways to triangulate process data with trial data, but limited information was reported in articles. Where information was provided it referred to triangulation of data or comparing of process evaluation data with primary/secondary RCT outcome measures. Process evaluations helped explain contextual factors or mechanisms that led to trial outcomes.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe conducted this scoping review to explore methods and reporting of process evaluations nested in RCTs on complex interventions. We found that most process evaluations are conducted during the RCT data collection period and use multiple methods for data collection. Differences between pilot/feasibility RCTs and RCTs were limited, particularly regarding data collection and analyses. However, pilot/feasibility RCTs were more often reported as part of the main trial paper. While numbers were very small, it seems more process evaluations in pilot/feasibility RCTs were theoretically informed as compared to RCTs (19% and 11% respectively). A reason for not reporting triangulation with RCT data or not reporting theoretical guidance may be due to limited word count for articles. This can be an issue for all studies and especially challenging for the reporting of process evaluations that were included in the main RCT paper, with more competition for space. However, as only 36% of pilot/feasibility RCTs and 9% of full RCTs were reported as part of the main study paper, there appear to be wider reporting issues for nested process evaluations in RCTs of complex interventions. Only a third of the studies included in this review reported integration of process evaluation data with RCT findings and very limited information was available in methods and results sections as to how data triangulation between process evaluation data and RCT outcome data took place.\u003c/p\u003e \u003cp\u003eApart from implementation processes, process evaluations aim to help explain trial findings (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), and the lack of reported process data triangulation with trial data leads us to believe opportunities to do this may have been missed. Additionally, process evaluations could potentially help highlight contextual factors that facilitate or prevent intervention outcomes form occurring. Knowledge of these could support implementation activities and increase impact of the intervention. While theory use is recommended by Moore et al., most included studies did not report using theory. This is a missed opportunity as the use of theory offers a route to mechanism-based explanation of the relationships between interventions, contexts and desired outcomes (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur review highlights that when theory is applied, it is restricted to superficial use (mentioned in the background/ methods section but then plays no part in what follows) or conceptual use (used to guide data collection and to structure results). A theory guided approach encompassing hypothesis generation, data collection, analysis and the interpretation of outcomes (and their wider meaning), is currently rare. That this is currently lacking means that we are missing opportunities to maximise learning on how mechanisms might generate different outcomes in different contexts and on the potential transferability of interventions themselves (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). We are also missing opportunities to complete the scientific circle of enquiry itself, using new empirical findings to either consolidate, refine or expand existing theoretical knowledge that can then be used to further our understanding of what works where, how and why (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). If process evaluations can be more theoretically guided, we are more likely to be theoretically informative, and more likely to contribute new and transferrable knowledge.\u003c/p\u003e \u003cp\u003eIssues with the reporting of process evaluations nested in RCTs have been flagged previously, reinforcing the need to develop materials and tools to move the field forwards. Past reviews on the design and methodologies of process evaluations in specific settings, including neurological rehabilitation (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), pragmatic RCTs (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), and church-based health promotion interventions (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) or worksite health programmes (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), highlighted the lack of consistency in nested process evaluation conduct (\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), the lack of reporting of key process evaluation outcomes (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), gaps in evidence-informed process evaluation guidance (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e), the lack of clear links between process evaluation and full RCT outcome results (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) and a lack of theoretical basis (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). A 2007 review concluded that incomplete reporting of information regarding process evaluations, including 61.5% (n\u0026thinsp;=\u0026thinsp;32) studies with an experimental design (randomised comparison or control group), of occupational stress management programmes makes it difficult to identify reliable determinants of effective intervention implementation and outcome (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The gap in knowledge regarding reporting of process evaluations and how the process evaluation links with intervention outcomes was already flagged in 2009 (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Despite seemingly increased use of process evaluations following MRC guidance, there seems to have been little progress in reporting of process evaluations or their linking with RCT or other studies of effectiveness of interventions.\u003c/p\u003e \u003cp\u003eCurrently, there are no reporting standards for process evaluations nested in RCTs of complex interventions. The development of a suitable reporting framework may increase reporting quality and would bring these studies into line with the plethora of other designs with their own reporting framework (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). While the Standards for Reporting Implementation Studies (StaRI) initiative (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e), aimed at supporting transparent and accurate reporting of implementation studies, could, in theory, be used to support clear and consistent reporting of process evaluations nested in RCTs, in practice it is unlikely to be tailored enough to do this. For example, a reporting checklist for process evaluations nested in RCTs would benefit from increased focus on various aspects of process evaluation methods, rather than being just a single item, which they are in StaRI (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Additionally, a bespoke checklist should focus on the reporting of intervention mechanisms, not just intervention outcomes, as well as the various foci of the process evaluation, including implementation, contextual factors, and mechanisms of action. Reports of process evaluations nested in RCTs should contain a section on triangulation of process data and RCT data. In summary we suggest there is scope to develop a bespoke reporting tool aimed at improving reporting of RCT embedded process evaluations.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and limitations\u003c/h2\u003e \u003cp\u003eThis scoping review used a systematic approach with a registered protocol to identify process evaluations in pilot/feasibility RCTs and RCTs. We included any process evaluation of a health or social care intervention in any setting if it was linked to a pilot/feasibility RCT or full RCT. The requirement that the evaluation adhere to MRC guidance ensured that the review focused on those evaluations which were based on recommended approaches. Limitations include the use of a single reviewer for screening and data extraction, which could have led to studies being missed, or studies being wrongfully included due to confirmation bias. We tried to mitigate this by referral to the team of any uncertainties in decision making and by checking and discussion of data extraction. Limitation to English language reports has the potential to exclude relevant studies and to impact the results of the review if the effects of this are non-random. However, no studies were excluded solely for this reason. Limitation to full text papers was necessary to be able to extract relevant information.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eProcess evaluations are a helpful tool to explain the outcomes of RCTs of complex interventions, support the subsequent implementation of interventions and their impact. However, information gathered from process evaluations nested in RCTs is often not fully reported in papers, particularly where the process evaluation is reported within the same journal article as the linked RCT. In such cases we recommend authors use supplementary information to provide fuller information about the process evaluation. There are currently no suitable reporting guidelines for process evaluations linked to RCTs; work to develop such guidelines, potentially as a StaRI checklist extension would be valuable. Beyond this it may be helpful to consider what components could contribute to a quality appraisal tool for process evaluations to support further methods development and subsequent reviewers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analysed for this study are available from the corresponding author on request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare they have no competing interests\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe authors are in receipt of funding from the NIHR Applied Research Collaboration Greater Manchester. JD is a NIHR Senior Investigator. The views expressed in this paper are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthor’s contributions\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eMK, JD and PW contributed to the inception of the idea and rationale for the review; MK was conducted searches; MK and GN conducted screening and data extraction; MK, GN, JD and PW were involved in analysis and synthesis of data and writing up of the review. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eGrant A, Treweek S, Dreischulte T, Foy R, Guthrie B. Process evaluations for cluster-randomised trials of complex interventions: a proposed framework for design and reporting. 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Process evaluation within pragmatic randomised controlled trials: what is it, why is it done, and can we find it?-a systematic review. Trials. 2020;21(1):916.\u003c/li\u003e\n \u003cli\u003eYeary KH, Klos LA, Linnan L. The examination of process evaluation use in church-based health interventions: a systematic review. Health Promot Pract. 2012;13(4):524-34.\u003c/li\u003e\n \u003cli\u003eWierenga D, Engbers LH, Van Empelen P, Duijts S, Hildebrandt VH, Van Mechelen W. What is actually measured in process evaluations for worksite health promotion programs: a systematic review. BMC Public Health. 2013;13:1190.\u003c/li\u003e\n \u003cli\u003eMurta SG, Sanderson K, Oldenburg B. Process evaluation in occupational stress management programs: a systematic review. Am J Health Promot. 2007;21(4):248-54.\u003c/li\u003e\n \u003cli\u003eEgan M, Bambra C, Petticrew M, Whitehead M. Reviewing evidence on complex social interventions: appraising implementation in systematic reviews of the health effects of organisational-level workplace interventions. J Epidemiol Community Health. 2009;63(1):4-11.\u003c/li\u003e\n \u003cli\u003eThe UK EQUATOR Centre. Enhancing the QUAlity and Transparency Of health Research. 2024 [Available from: https://www.equator-network.org] Access date July 4 2024\u003c/li\u003e\n \u003cli\u003ePinnock H, Barwick M, Carpenter CR, Eldridge S, Grandes G, Griffiths CJ, et al. Standards for Reporting Implementation Studies (StaRI): explanation and elaboration document. BMJ Open. 2017;7(4):e013318.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"trials","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trls","sideBox":"Learn more about [Trials](http://trialsjournal.biomedcentral.com/)","snPcode":"13063","submissionUrl":"https://www.editorialmanager.com/trls","title":"Trials","twitterHandle":"MedicalEvidence","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Process evaluations, Randomised Controlled Trials, Scoping Review","lastPublishedDoi":"10.21203/rs.3.rs-4938846/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4938846/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe United Kingdom Medical Research Council (MRC) guidance for complex interventions recommends the nesting of process evaluations in randomised controlled trials (RCTs) of complex interventions. To date, there has been limited review of how the MRC guidance has been operationalised in RCTs of complex interventions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis scoping review aimed to identify how process evaluations nested in RCTs on complex interventions have been conducted and reported since the 2015 publication of MRC guidance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe identified articles in Pubmed and Scopus that cited the 2015 main journal article on the MRC guidance and applied an RCT filter to these articles. Studies reporting on RCT nested process evaluations in any field of health or social care were included. Data was extracted about study details, process evaluation study design, including methods used for data collection, data analyses, integration with RCT data and use of theory in process evaluation design.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe identified 160 RCTs and 53 pilot/feasibility RCTs. Most process evaluations included a combination of qualitative and quantitative data collection methods, either triangulated (mixed method studies) or not (multi-method studies). Most studies did not report the use of theory in shaping how the process evaluation was designed. Common methods for data analysis included descriptive statistics and thematic analysis for quantitative and qualitative studies respectively. There was limited triangulation of process evaluation data with RCT outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhile process evaluations can be helpful in explaining outcomes of RCT interventions and subsequent implementation of these intentions, information gathered from process evaluations is often not fully reported in papers. There are currently no suitable reporting guidelines for process evaluations linked to RCTs; work to develop such guidelines, potentially as a StaRI checklist extension would be valuable.\u003c/p\u003e","manuscriptTitle":"Process Evaluations nested in randomised controlled trials of complex interventions: A scoping review of approaches and reporting","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-02 11:16:57","doi":"10.21203/rs.3.rs-4938846/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accept","date":"2025-05-30T03:25:46+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-04-30T13:22:33+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-30T07:32:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-30T05:05:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"Trials","date":"2025-04-29T10:47:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"trials","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"trls","sideBox":"Learn more about [Trials](http://trialsjournal.biomedcentral.com/)","snPcode":"13063","submissionUrl":"https://www.editorialmanager.com/trls","title":"Trials","twitterHandle":"MedicalEvidence","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9e59a192-f229-4507-afdc-b1060551756b","owner":[],"postedDate":"May 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-08-04T16:41:38+00:00","versionOfRecord":{"articleIdentity":"rs-4938846","link":"https://doi.org/10.1186/s13063-025-08910-x","journal":{"identity":"trials","isVorOnly":false,"title":"Trials"},"publishedOn":"2025-07-30 16:05:18","publishedOnDateReadable":"July 30th, 2025"},"versionCreatedAt":"2025-05-02 11:16:57","video":"","vorDoi":"10.1186/s13063-025-08910-x","vorDoiUrl":"https://doi.org/10.1186/s13063-025-08910-x","workflowStages":[]},"version":"v1","identity":"rs-4938846","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4938846","identity":"rs-4938846","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}