# A scoping review of theories, models and frameworks used or proposed to evaluate knowledge mobilization strategies

Saliha Ziam, Sèverine Lanoue, Esther Mcsween-Cadieux, Mathieu-Joël Gervais, Julie Lane, Dina Gaid, Laura Justine Chouinard, Christian Dagenais,

Valéry Ridde, Emmanuelle Jean, et al.

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## To cite this version:

Saliha Ziam, Sèverine Lanoue, Esther Mcsween-Cadieux, Mathieu-Joël Gervais, Julie Lane, et al. A scoping review of theories, models and frameworks used or proposed to evaluate knowledge mobilization strategies. Health Research Policy and Systems, 2024, 22, pp.8. 10.1186/s12961-023-01090-7. hal-04384957

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# A scoping review of theories, models and frameworks used or proposed to evaluate knowledge mobilization strategies

Saliha Ziam, Sèverine Lanoue, Esther Mcsween-Cadieux, Mathieu-Joël Gervais, Julie Lane, Dina Gaid, Laura Justine Chouinard, Christian Dagenais,

Valéry Ridde, Emmanuelle Jean, et al.

<figure><img src="image_1.png" /></figure>

## To cite this version:

Saliha Ziam, Sèverine Lanoue, Esther Mcsween-Cadieux, Mathieu-Joël Gervais, Julie Lane, et al. A scoping review of theories, models and frameworks used or proposed to evaluate knowledge mobilization strategies. Health Research Policy and Systems, 2024, 22, pp.8. 10.1186/s12961-023-01090-7. hal-04384957

HAL Id: hal-04384957

https://hal.science/hal-04384957v1

Submitted on 15 May 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_2.png" /></figure>
RESEARCH

Open Access

<figure><img src="image_3.png" /></figure>

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# A scoping review of theories, models and frameworks used or proposed to evaluate knowledge mobilization strategies

Saliha Ziam¹* ID, Sèverine Lanoue², Esther McSween-Cadieux², Mathieu-Joël Gervais³, Julie Lane²,⁴, Dina Gaid⁵, Laura Justine Chouinard¹, Christian Dagenais⁶, Valéry Ridde⁷,⁸, Emmanuelle Jean⁹, France Charles Fleury¹⁰, Quan Nha Hong⁵ and Ollivier Prigent²

**Abstract**

**Background** Evaluating knowledge mobilization strategies (KMb) presents challenges for organizations seeking to understand their impact to improve KMb effectiveness. Moreover, the large number of theories, models, and frameworks (TMFs) available can be confusing for users. Therefore, the purpose of this scoping review was to identify and describe the characteristics of TMFs that have been used or proposed in the literature to evaluate KMb strategies.

**Methods** A scoping review methodology was used. Articles were identified through searches in electronic databases, previous reviews and reference lists of included articles. Titles, abstracts and full texts were screened in duplicate. Data were charted using a piloted data charting form. Data extracted included study characteristics, KMb characteristics, and TMFs used or proposed for KMb evaluation. An adapted version of Nilsen (Implement Sci 10:53, 2015) taxonomy and the Expert Recommendations for Implementing Change (ERIC) taxonomy (Powell et al. in Implement Sci 10:21, 2015) guided data synthesis.

**Results** Of the 4763 search results, 505 were retrieved, and 88 articles were eligible for review. These consisted of 40 theoretical articles (45.5%), 44 empirical studies (50.0%) and four protocols (4.5%). The majority were published after 2010 (n = 70, 79.5%) and were health related (n = 71, 80.7%). Half of the studied KMb strategies were implemented in only four countries: Canada, Australia, the United States and the United Kingdom (n = 42, 47.7%). One-third used existing TMFs (n = 28, 31.8%). According to the adapted Nilsen taxonomy, process models (n = 34, 38.6%) and evaluation frameworks (n = 28, 31.8%) were the two most frequent types of TMFs used or proposed to evaluate KMb. According to the ERIC taxonomy, activities to "train and educate stakeholders" (n = 46, 52.3%) were the most common, followed by activities to "develop stakeholder interrelationships" (n = 23, 26.1%). Analysis of the TMFs identified revealed relevant factors of interest for the evaluation of KMb strategies, classified into four dimensions: context, process, effects and impacts.

**Conclusions** This scoping review provides an overview of the many KMb TMFs used or proposed. The results provide insight into potential dimensions and components to be considered when assessing KMb strategies.

**Keywords** Knowledge mobilization, Knowledge translation, Theories, models, and frameworks, Evaluation, Scoping review

<footnote>*Correspondence:
Saliha Ziam
saliha.ziam@teluq.ca
Full list of author information is available at the end of the article</footnote>
RESEARCH

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# A scoping review of theories, models and frameworks used or proposed to evaluate knowledge mobilization strategies

Saliha Ziam¹* ID, Sèverine Lanoue², Esther McSween-Cadieux², Mathieu-Joël Gervais³, Julie Lane²,⁴, Dina Gaid⁵, Laura Justine Chouinard¹, Christian Dagenais⁶, Valéry Ridde⁷,⁸, Emmanuelle Jean⁹, France Charles Fleury¹⁰, Quan Nha Hong⁵ and Ollivier Prigent²

**Abstract**

**Background** Evaluating knowledge mobilization strategies (KMb) presents challenges for organizations seeking to understand their impact to improve KMb effectiveness. Moreover, the large number of theories, models, and frameworks (TMFs) available can be confusing for users. Therefore, the purpose of this scoping review was to identify and describe the characteristics of TMFs that have been used or proposed in the literature to evaluate KMb strategies.

**Methods** A scoping review methodology was used. Articles were identified through searches in electronic databases, previous reviews and reference lists of included articles. Titles, abstracts and full texts were screened in duplicate. Data were charted using a piloted data charting form. Data extracted included study characteristics, KMb characteristics, and TMFs used or proposed for KMb evaluation. An adapted version of Nilsen (Implement Sci 10:53, 2015) taxonomy and the Expert Recommendations for Implementing Change (ERIC) taxonomy (Powell et al. in Implement Sci 10:21, 2015) guided data synthesis.

**Results** Of the 4763 search results, 505 were retrieved, and 88 articles were eligible for review. These consisted of 40 theoretical articles (45.5%), 44 empirical studies (50.0%) and four protocols (4.5%). The majority were published after 2010 (n = 70, 79.5%) and were health related (n = 71, 80.7%). Half of the studied KMb strategies were implemented in only four countries: Canada, Australia, the United States and the United Kingdom (n = 42, 47.7%). One-third used existing TMFs (n = 28, 31.8%). According to the adapted Nilsen taxonomy, process models (n = 34, 38.6%) and evaluation frameworks (n = 28, 31.8%) were the two most frequent types of TMFs used or proposed to evaluate KMb. According to the ERIC taxonomy, activities to "train and educate stakeholders" (n = 46, 52.3%) were the most common, followed by activities to "develop stakeholder interrelationships" (n = 23, 26.1%). Analysis of the TMFs identified revealed relevant factors of interest for the evaluation of KMb strategies, classified into four dimensions: context, process, effects and impacts.

**Conclusions** This scoping review provides an overview of the many KMb TMFs used or proposed. The results provide insight into potential dimensions and components to be considered when assessing KMb strategies.

**Keywords** Knowledge mobilization, Knowledge translation, Theories, models, and frameworks, Evaluation, Scoping review

<footnote>*Correspondence:
Saliha Ziam
saliha.ziam@teluq.ca
Full list of author information is available at the end of the article</footnote>
## Contribution to the literature

* The evaluation of KMb strategies is a critical dimension of the KMb process that is still poorly documented and warrants researchers' attention.

* Our review identified the most common theories, models and frameworks (TMFs) proposed or used to assess KMb strategies and the main components to consider when evaluating a KMb strategy.

* By developing an integrative reference framework, this work contributes to improving organizations' capacity to evaluate their KMb initiatives.

## Background

It is widely recognized that research evidence has the potential to inform, guide, and improve practices, decisions, and policies [1]. Unfortunately, for diverse reasons, the best available evidence is still too seldom taken into account and used [2–7]. The field of research on knowledge mobilization (KMb) has been growing rapidly since the early 2000s [2, 3, 8–11]. Its purpose is to better understand how to effectively promote and support evidence use.

Knowledge mobilization is one of many terms and concepts developed over recent decades to describe processes, strategies, and actions to bridge the gap between research and practice. Other common terms often paired interchangeably with the term “knowledge” are “translation”, “transfer”, “exchange”, “sharing” and “dissemination”, among others. [12, 13]. Some are more closely linked than others to specific fields or jurisdictions. For this study, we adopted the term knowledge mobilization (KMb) because it conveys the notions of complexity and multidirectional exchanges that characterize research-to-action processes. We used it as an umbrella concept that encompasses the efforts made to translate knowledge into concrete actions and beneficial impacts on populations [1]. Moreover, the term KMb is also used by research funding agencies in Canada to emphasize the medium- and long-term effects that research knowledge or research results can have on potential users [1, 14].

KMb represents all processes from knowledge creation to action and includes all strategies implemented to facilitate these processes [14]. A KMb strategy is understood as a coordinated set of activities to support evidence use, such as dissemination activities to reach target audiences (for example, educational materials, practical guides, decision support tools) or activities to facilitate knowledge application in a specific context and support professional behaviour change (for example, community of practice, educational meetings, audits and feedback, reminders, deliberative dialogues) [15]. A KMb process

may vary in intensity, complexity or actor engagement depending on the nature of the research knowledge and the needs and preferences of evidence users [7].

KMb is considered a complex process, in that numerous factors can facilitate or hinder its implementation and subsequent evidence use. The past two decades have seen the emergence of a deeper understanding of these factors [2, 3, 16]. These may be related to the knowledge mobilized (for example, relevance, reliability, clarity, costs), the individuals involved in the KMb process (for example, openness to change, values, time available, resources), the KMB strategies (for example, fit with stakeholder needs and preferences, regular interactions, trust relationships, timing), and organizational and political contexts (for example, culture of evidence use, leadership, resources) [2, 6, 17, 18]. However, more studies are needed to understand which factors are more important in which contexts, and to evaluate the effects of KMb strategies.

On this last point, while essential, it is often very complex to study KMb impacts empirically to demonstrate the effectiveness of KMb strategies [19–21]. Partly for this reason, high-quality studies that evaluate process, mechanisms and effects of KMb strategies are still relatively rare [2, 22–25]. As a result, knowledge about the effectiveness of different KMb strategies remains limited [10, 17, 19, 23, 26–28] and their development cannot be totally evidence informed [3, 19, 20, 23, 29, 30], which may seem incompatible with the core values and principles of KMb.

The growing interest in KMb has led to an impressive proliferation of conceptual propositions, such as theories, models and frameworks (TMF) [2, 3, 9, 11, 12, 31, 32]. Many deplore the fact that these are poorly used [11, 30, 33] and insist on the need to test, refine and integrate existing ones [3, 31, 34]. Indeed, the conceptual and theoretical development of the field has outpaced its empirical development. This proliferation appears to have created confusion among certain users, such as organizations that need to evaluate their KMb strategies. Besides implementing and funding KMb strategies, knowledge organizations such as granting agencies, governments and public organizations, universities and health authorities are often required to demonstrate the impact of their strategies [21, 35, 36]. Yet this can be a significant challenge [20, 23, 29]. They may have difficulty knowing which TMFs to choose, in what context and how to use them effectively in their evaluation process [12, 37].

Indeed, the evaluation of KMb strategies is still relatively poorly documented, with respect to the phases of their development and implementation. Our aim in this scoping review is to clarify, conceptually and methodologically, this crucial dimension of the KMb process.
## Contribution to the literature

* The evaluation of KMb strategies is a critical dimension of the KMb process that is still poorly documented and warrants researchers' attention.

* Our review identified the most common theories, models and frameworks (TMFs) proposed or used to assess KMb strategies and the main components to consider when evaluating a KMb strategy.

* By developing an integrative reference framework, this work contributes to improving organizations' capacity to evaluate their KMb initiatives.

## Background

It is widely recognized that research evidence has the potential to inform, guide, and improve practices, decisions, and policies [1]. Unfortunately, for diverse reasons, the best available evidence is still too seldom taken into account and used [2–7]. The field of research on knowledge mobilization (KMb) has been growing rapidly since the early 2000s [2, 3, 8–11]. Its purpose is to better understand how to effectively promote and support evidence use.

Knowledge mobilization is one of many terms and concepts developed over recent decades to describe processes, strategies, and actions to bridge the gap between research and practice. Other common terms often paired interchangeably with the term “knowledge” are “translation”, “transfer”, “exchange”, “sharing” and “dissemination”, among others. [12, 13]. Some are more closely linked than others to specific fields or jurisdictions. For this study, we adopted the term knowledge mobilization (KMb) because it conveys the notions of complexity and multidirectional exchanges that characterize research-to-action processes. We used it as an umbrella concept that encompasses the efforts made to translate knowledge into concrete actions and beneficial impacts on populations [1]. Moreover, the term KMb is also used by research funding agencies in Canada to emphasize the medium- and long-term effects that research knowledge or research results can have on potential users [1, 14].

KMb represents all processes from knowledge creation to action and includes all strategies implemented to facilitate these processes [14]. A KMb strategy is understood as a coordinated set of activities to support evidence use, such as dissemination activities to reach target audiences (for example, educational materials, practical guides, decision support tools) or activities to facilitate knowledge application in a specific context and support professional behaviour change (for example, community of practice, educational meetings, audits and feedback, reminders, deliberative dialogues) [15]. A KMb process

may vary in intensity, complexity or actor engagement depending on the nature of the research knowledge and the needs and preferences of evidence users [7].

KMb is considered a complex process, in that numerous factors can facilitate or hinder its implementation and subsequent evidence use. The past two decades have seen the emergence of a deeper understanding of these factors [2, 3, 16]. These may be related to the knowledge mobilized (for example, relevance, reliability, clarity, costs), the individuals involved in the KMb process (for example, openness to change, values, time available, resources), the KMB strategies (for example, fit with stakeholder needs and preferences, regular interactions, trust relationships, timing), and organizational and political contexts (for example, culture of evidence use, leadership, resources) [2, 6, 17, 18]. However, more studies are needed to understand which factors are more important in which contexts, and to evaluate the effects of KMb strategies.

On this last point, while essential, it is often very complex to study KMb impacts empirically to demonstrate the effectiveness of KMb strategies [19–21]. Partly for this reason, high-quality studies that evaluate process, mechanisms and effects of KMb strategies are still relatively rare [2, 22–25]. As a result, knowledge about the effectiveness of different KMb strategies remains limited [10, 17, 19, 23, 26–28] and their development cannot be totally evidence informed [3, 19, 20, 23, 29, 30], which may seem incompatible with the core values and principles of KMb.

The growing interest in KMb has led to an impressive proliferation of conceptual propositions, such as theories, models and frameworks (TMF) [2, 3, 9, 11, 12, 31, 32]. Many deplore the fact that these are poorly used [11, 30, 33] and insist on the need to test, refine and integrate existing ones [3, 31, 34]. Indeed, the conceptual and theoretical development of the field has outpaced its empirical development. This proliferation appears to have created confusion among certain users, such as organizations that need to evaluate their KMb strategies. Besides implementing and funding KMb strategies, knowledge organizations such as granting agencies, governments and public organizations, universities and health authorities are often required to demonstrate the impact of their strategies [21, 35, 36]. Yet this can be a significant challenge [20, 23, 29]. They may have difficulty knowing which TMFs to choose, in what context and how to use them effectively in their evaluation process [12, 37].

Indeed, the evaluation of KMb strategies is still relatively poorly documented, with respect to the phases of their development and implementation. Our aim in this scoping review is to clarify, conceptually and methodologically, this crucial dimension of the KMb process.
This would help organizations gain access to evidence-
based, operational and easy-to-use evaluation toolkits for
assessing the impacts of their KMb strategies.

Objectives

To survey the available knowledge on evaluation prac-
tices for KMb strategies, we conducted a scoping review.
According to Munn et al. [38], a scoping review is indi-
cated to identify the types of available evidence and
knowledge gaps, to clarify concepts in the literature and
to identify key characteristics or factors related to a con-
cept. This review methodology also allows for the inclu-
sion of a diversity of publications, regardless of their
nature or research design, to produce the most compre-
hensive evidence mapping possible [39]. The objective of
the scoping review was to identify and describe the char-
acteristics of theories, models and frameworks (TMFs)
used or proposed to evaluate KMb strategies. The spe-
cific research questions were:

(1) What TMFs to evaluate KMb strategies exist in the literature?

(2) What KMb strategies do they evaluate (that is types of KMb objectives, activities, target audiences)?

(3) What dimensions and components are included in these TMFs?

Methods

This scoping review was conducted based on the five
steps outlined by Arksey and O'Malley [39]: (1) formu-
lating the research questions; (2) identifying relevant
studies; (3) selecting relevant studies; (4) extracting and
charting data; and (5) analysing, collating, summariz-
ing and presenting the data. Throughout the process,
researchers and knowledge users (KMb practitioners)
were involved in decisions regarding the research ques-
tion, search strategy, selection criteria for studies and
categories for data charting. We followed the Preferred
Reporting Items for Systematic reviews and Meta-Analy-
ses extension for Scoping Reviews (PRISMA-ScR) guide-
lines [40]. No protocol was registered for this review.

Search strategy and information sources

The search strategy was developed, piloted and refined
in consultation with our team's librarian. Search terms
included controlled vocabulary and keywords related to
three main concepts: (1) knowledge mobilization (for
example [knowledge or evidence or research] and trans-
fer, translation, diffusion, dissemination, mobilization,
implementation science, exchange, sharing, use, uptake,
evidence-based practice, research-based evidence),
(2) evaluation (for example, evaluat*, measur*, impact,
outcome, assess, apprais*, indicator) and (3) TMF (for

example, framework*, model*, method*, guide*, theor*).
See Additional file 1 for the search terms and strategies
used in the electronic searches.

The following databases were searched from January 2000 to August 2023: MEDLINE (Ovid), PsycInfo (Ovid), ERIC (ProQuest), Sociological Abstracts (ProQuest), Dissertations & Theses (Proquest), Érudit and Cairn. These databases were chosen to identify relevant references in the health, education and social fields. Several search strategies were tested by the librarian to optimize the retrieval of citations known to the investigators and to increase the likelihood that all relevant studies would be retrieved. We also searched reference lists of included articles and previous systematic reviews [11, 12, 15, 41].

Eligibility criteria

A publication was considered eligible if it (1) presented or
used a theory, model, or framework (TMF), (2) described
dimensions or specific components to consider in the
evaluation of KMb strategies, (3) presented or discussed
KMb strategies or activities (any initiatives to improve
evidence use), and (4) proposed outcomes that might
result directly or indirectly from the KMb strategies.
Studies were excluded from analysis if they (1) presented
a TMF to assess the impact of research without mention-
ing KMb strategies or an intervention not related to KMb
and (2) presented evaluation dimensions or components
that could not be generalized. We considered publica-
tions in English or French. All types of articles and study
designs were eligible, including study protocols.

Study selection

The results of the literature search were imported into
Covidence, which the review team used for screening.
After duplicate articles were removed, the titles and
abstracts were screened independently by two of the
three reviewers (EMC, MJG, GL). Publications identi-
fied as potentially relevant were retrieved in full text and
screened independently by three reviewers (EMC, MJG,
GL). Discrepancies regarding the inclusion of any publi-
cation were resolved through discussion and consensus
among reviewers. The principal investigator (SZ) vali-
dated the final selection of articles.

Data synthesis

A data charting form was developed in Microsoft
Excel and piloted by the research team. Data extracted
included study characteristics (authors, authors' country
of affiliation, year, journal, discipline, article type, study
setting, study aim), KMb strategies of interest, KMb
objectives, KMb target audiences and TMFs used or pro-
posed for KMb evaluation (existing or new TMF, specific
dimensions or components of TMF and so on). Data
This would help organizations gain access to evidence-
based, operational and easy-to-use evaluation toolkits for
assessing the impacts of their KMb strategies.

Objectives

To survey the available knowledge on evaluation prac-
tices for KMb strategies, we conducted a scoping review.
According to Munn et al. [38], a scoping review is indi-
cated to identify the types of available evidence and
knowledge gaps, to clarify concepts in the literature and
to identify key characteristics or factors related to a con-
cept. This review methodology also allows for the inclu-
sion of a diversity of publications, regardless of their
nature or research design, to produce the most compre-
hensive evidence mapping possible [39]. The objective of
the scoping review was to identify and describe the char-
acteristics of theories, models and frameworks (TMFs)
used or proposed to evaluate KMb strategies. The spe-
cific research questions were:

(1) What TMFs to evaluate KMb strategies exist in the literature?

(2) What KMb strategies do they evaluate (that is types of KMb objectives, activities, target audiences)?

(3) What dimensions and components are included in these TMFs?

Methods

This scoping review was conducted based on the five
steps outlined by Arksey and O'Malley [39]: (1) formu-
lating the research questions; (2) identifying relevant
studies; (3) selecting relevant studies; (4) extracting and
charting data; and (5) analysing, collating, summariz-
ing and presenting the data. Throughout the process,
researchers and knowledge users (KMb practitioners)
were involved in decisions regarding the research ques-
tion, search strategy, selection criteria for studies and
categories for data charting. We followed the Preferred
Reporting Items for Systematic reviews and Meta-Analy-
ses extension for Scoping Reviews (PRISMA-ScR) guide-
lines [40]. No protocol was registered for this review.

Search strategy and information sources

The search strategy was developed, piloted and refined
in consultation with our team's librarian. Search terms
included controlled vocabulary and keywords related to
three main concepts: (1) knowledge mobilization (for
example [knowledge or evidence or research] and trans-
fer, translation, diffusion, dissemination, mobilization,
implementation science, exchange, sharing, use, uptake,
evidence-based practice, research-based evidence),
(2) evaluation (for example, evaluat*, measur*, impact,
outcome, assess, apprais*, indicator) and (3) TMF (for

example, framework*, model*, method*, guide*, theor*).
See Additional file 1 for the search terms and strategies
used in the electronic searches.

The following databases were searched from January 2000 to August 2023: MEDLINE (Ovid), PsycInfo (Ovid), ERIC (ProQuest), Sociological Abstracts (ProQuest), Dissertations & Theses (Proquest), Érudit and Cairn. These databases were chosen to identify relevant references in the health, education and social fields. Several search strategies were tested by the librarian to optimize the retrieval of citations known to the investigators and to increase the likelihood that all relevant studies would be retrieved. We also searched reference lists of included articles and previous systematic reviews [11, 12, 15, 41].

Eligibility criteria

A publication was considered eligible if it (1) presented or
used a theory, model, or framework (TMF), (2) described
dimensions or specific components to consider in the
evaluation of KMb strategies, (3) presented or discussed
KMb strategies or activities (any initiatives to improve
evidence use), and (4) proposed outcomes that might
result directly or indirectly from the KMb strategies.
Studies were excluded from analysis if they (1) presented
a TMF to assess the impact of research without mention-
ing KMb strategies or an intervention not related to KMb
and (2) presented evaluation dimensions or components
that could not be generalized. We considered publica-
tions in English or French. All types of articles and study
designs were eligible, including study protocols.

Study selection

The results of the literature search were imported into
Covidence, which the review team used for screening.
After duplicate articles were removed, the titles and
abstracts were screened independently by two of the
three reviewers (EMC, MJG, GL). Publications identi-
fied as potentially relevant were retrieved in full text and
screened independently by three reviewers (EMC, MJG,
GL). Discrepancies regarding the inclusion of any publi-
cation were resolved through discussion and consensus
among reviewers. The principal investigator (SZ) vali-
dated the final selection of articles.

Data synthesis

A data charting form was developed in Microsoft
Excel and piloted by the research team. Data extracted
included study characteristics (authors, authors' country
of affiliation, year, journal, discipline, article type, study
setting, study aim), KMb strategies of interest, KMb
objectives, KMb target audiences and TMFs used or pro-
posed for KMb evaluation (existing or new TMF, specific
dimensions or components of TMF and so on). Data
were extracted by a single reviewer (SL, JC or OP) and validated by a second reviewer (SZ). Disagreements were discussed between reviewers and resolved by consensus. No quality appraisal of included studies was conducted, as this is optional in scoping reviews and the purpose was only to describe the content of identified TMFs [42].

## Data analysis and presentation of results

Data were summarized according to study characteristics, KMb strategy characteristics (activities, objectives, target audiences), types of TMFs, and dimensions or components to consider for KMb evaluation. Disagreements during the process were discussed and resolved through consensus (SL, DG, SZ). A KMb strategy might have one or more objectives and include one or more activities. Thus, the objectives and activities of the KMb strategies extracted from the selected studies were summarized based on existing categorizations. The categorization of KMb objectives was inspired by Gervais et al. [15] and Farkas et al. [43] (Table 1).

The KMb activities were categorized according to the Expert Recommendations for Implementing Change (ERIC) taxonomy [44]. The activities were first classified according to the full taxonomy and then grouped into the nine categories proposed by Waltz et al. [45] (Table 2).

The TMFs were categorized according to the categories of theoretical approaches described by Nilsen [32]: process models, evaluation frameworks, determinant frameworks and classic theories (Table 3). The category “implementation theories” originally described by Nilsen [32] was not used because we did not identify any article that fit this category. We also added a category named “logic models” due to the nature of the identified TMFs. Logic models are often used in theory-driven evaluation approaches and are usually developed to show the links among inputs (resources), activities and outputs (outcomes and short-, medium- and long-term effects) [46].

<table><caption>**Table 1** Categories of KMb strategy objectives</caption><thead><tr><td>Category</td><td>Description</td></tr></thead><tbody><tr><td>Expose – inform</td><td>Exposure and dissemination of knowledge</td></tr><tr><td>Change attitude</td><td>Enable experience, raise awareness, change beliefs</td></tr><tr><td>Inform and influence decision-making</td><td>Support decision-makers, increase knowledge use in decision-making</td></tr><tr><td>Improve practices</td><td>Increase expertise, competence and use of knowledge</td></tr><tr><td>Foster collaboration</td><td>Build partnerships and improve communication and exchange</td></tr></tbody></table>

Adapted from Gervais et al. [15] and Farkas et al. [43]

<table><caption>**Table 2** Categories used to classify KMb activities</caption><thead><tr><td>Category</td><td>Description</td></tr></thead><tbody><tr><td>Train and educate stakeholders</td><td>Conduct ongoing training, develop educational materials</td></tr><tr><td>Develop stakeholder interrelationships</td><td>Conduct consensus discussion, develop academic partnership</td></tr><tr><td>Use evaluative and iterative strategies</td><td>Audit and provide feedback, conduct needs assessment</td></tr><tr><td>Provide interactive assistance</td><td>Facilitate, provide clinical supervision</td></tr><tr><td>Adapt and tailor to context</td><td>Tailor strategies, promote adaptability</td></tr><tr><td>Engage consumers</td><td>Involve patient and family members, use mass media</td></tr><tr><td>Change infrastructure</td><td>Change service sites, mandate change</td></tr><tr><td>Utilize financial strategies</td><td>Develop disincentives, alter allowance structure</td></tr><tr><td>Support clinicians</td><td>Create new clinical teams, develop resource-sharing agreements</td></tr></tbody></table>

Waltz et al. [45]; Powell et al. [44]

Finally, the content extracted from the TMFs was analysed using mainly an inductive method. This method allows, among other things, to develop a reference framework or a model from the emerging categories that are evident in the text data [50].

The classification of concepts is the result of multiple readings and interpretations. The concepts associated with each dimension of the framework were classified according to their meaning. Similar concepts were grouped together to form components. These grouped components were then associated with the sub-dimensions and main dimensions of the framework.

## Results

### Search results

The searches yielded 4763 articles. Of those, 4258 were excluded during the title and abstract screening. Of the 505 full-text articles, we retained 88 in our final sample. The results of the search and selection processes (PRISMA flowchart) are summarized in Fig. 1.

### Publication characteristics

Most articles were published after 2010 (n=70, 79.5%), with an average of 5 articles per year between 2010 and 2023 compared with an average of 2.1 articles per year between 2001 and 2009; there were no eligible articles from 2000. The search was conducted in August 2023, and only five articles were published in these 7 months of the year. Table 4 presents the main characteristics of the selected articles. A full list of the included articles
were extracted by a single reviewer (SL, JC or OP) and validated by a second reviewer (SZ). Disagreements were discussed between reviewers and resolved by consensus. No quality appraisal of included studies was conducted, as this is optional in scoping reviews and the purpose was only to describe the content of identified TMFs [42].

## Data analysis and presentation of results

Data were summarized according to study characteristics, KMb strategy characteristics (activities, objectives, target audiences), types of TMFs, and dimensions or components to consider for KMb evaluation. Disagreements during the process were discussed and resolved through consensus (SL, DG, SZ). A KMb strategy might have one or more objectives and include one or more activities. Thus, the objectives and activities of the KMb strategies extracted from the selected studies were summarized based on existing categorizations. The categorization of KMb objectives was inspired by Gervais et al. [15] and Farkas et al. [43] (Table 1).

The KMb activities were categorized according to the Expert Recommendations for Implementing Change (ERIC) taxonomy [44]. The activities were first classified according to the full taxonomy and then grouped into the nine categories proposed by Waltz et al. [45] (Table 2).

The TMFs were categorized according to the categories of theoretical approaches described by Nilsen [32]: process models, evaluation frameworks, determinant frameworks and classic theories (Table 3). The category “implementation theories” originally described by Nilsen [32] was not used because we did not identify any article that fit this category. We also added a category named “logic models” due to the nature of the identified TMFs. Logic models are often used in theory-driven evaluation approaches and are usually developed to show the links among inputs (resources), activities and outputs (outcomes and short-, medium- and long-term effects) [46].

<table><caption>**Table 1** Categories of KMb strategy objectives</caption><thead><tr><td>Category</td><td>Description</td></tr></thead><tbody><tr><td>Expose – inform</td><td>Exposure and dissemination of knowledge</td></tr><tr><td>Change attitude</td><td>Enable experience, raise awareness, change beliefs</td></tr><tr><td>Inform and influence decision-making</td><td>Support decision-makers, increase knowledge use in decision-making</td></tr><tr><td>Improve practices</td><td>Increase expertise, competence and use of knowledge</td></tr><tr><td>Foster collaboration</td><td>Build partnerships and improve communication and exchange</td></tr></tbody></table>

Adapted from Gervais et al. [15] and Farkas et al. [43]

<table><caption>**Table 2** Categories used to classify KMb activities</caption><thead><tr><td>Category</td><td>Description</td></tr></thead><tbody><tr><td>Train and educate stakeholders</td><td>Conduct ongoing training, develop educational materials</td></tr><tr><td>Develop stakeholder interrelationships</td><td>Conduct consensus discussion, develop academic partnership</td></tr><tr><td>Use evaluative and iterative strategies</td><td>Audit and provide feedback, conduct needs assessment</td></tr><tr><td>Provide interactive assistance</td><td>Facilitate, provide clinical supervision</td></tr><tr><td>Adapt and tailor to context</td><td>Tailor strategies, promote adaptability</td></tr><tr><td>Engage consumers</td><td>Involve patient and family members, use mass media</td></tr><tr><td>Change infrastructure</td><td>Change service sites, mandate change</td></tr><tr><td>Utilize financial strategies</td><td>Develop disincentives, alter allowance structure</td></tr><tr><td>Support clinicians</td><td>Create new clinical teams, develop resource-sharing agreements</td></tr></tbody></table>

Waltz et al. [45]; Powell et al. [44]

Finally, the content extracted from the TMFs was analysed using mainly an inductive method. This method allows, among other things, to develop a reference framework or a model from the emerging categories that are evident in the text data [50].

The classification of concepts is the result of multiple readings and interpretations. The concepts associated with each dimension of the framework were classified according to their meaning. Similar concepts were grouped together to form components. These grouped components were then associated with the sub-dimensions and main dimensions of the framework.

## Results

### Search results

The searches yielded 4763 articles. Of those, 4258 were excluded during the title and abstract screening. Of the 505 full-text articles, we retained 88 in our final sample. The results of the search and selection processes (PRISMA flowchart) are summarized in Fig. 1.

### Publication characteristics

Most articles were published after 2010 (n=70, 79.5%), with an average of 5 articles per year between 2010 and 2023 compared with an average of 2.1 articles per year between 2001 and 2009; there were no eligible articles from 2000. The search was conducted in August 2023, and only five articles were published in these 7 months of the year. Table 4 presents the main characteristics of the selected articles. A full list of the included articles
<table><caption>**Table 3** Categories used to classify the identified TMFs</caption><thead><tr><th>Category</th><th>Description and examples</th></tr></thead><tbody><tr><td>Process models</td><td>Describe steps or stages to translate evidence into action and offer practical guidance for KMb planning and execution (for example, the "Knowledge-to-Action framework" by Graham et al. [9])</td></tr><tr><td>Evaluation frameworks</td><td>Describe elements or components that could be evaluated to determine KMb implementation success (for example, "RE-ALM" by Glasgow et al. [47])</td></tr><tr><td>Determinant frameworks</td><td>Specify determinants that can act as barriers and enablers to understand or explain what influences KMb implementation and outcomes (for example, "PARISH" by Kitson et al. [48])</td></tr><tr><td>Classic theories</td><td>Theories that originate from other fields (for example, psychology sociology) and can be applied to understanding KMb processes (for example, social cognitive theories)</td></tr><tr><td>Logic models</td><td>Graphical representation of the links between inputs, activities, outputs and expected outcomes of a specific KMb strategy (for example, "CNODES knowledge translation logic model" by Sketris et al. [49])</td></tr></tbody></table>

Adapted from Nilsen [32]

<figure><img src="image_4.png" /><figcaption>**Fig. 1** PRISMA flowchart summarizing search strategy and selection results [40]</figcaption></figure>

with their main characteristics is presented in Additional file 2.

The number of theoretical and empirical articles was relatively similar. Among the theoretical articles, 19 descriptive articles (21.6%) were aimed at describing a KMb strategy, a KMb infrastructure or a TMF related to a specific programme or context; 18 articles (20.5%) synthesized knowledge to propose a TMF (new or revised); and three articles conducted systematic reviews (3.4%).

<table><caption>**Table 4** Characteristics of included articles (n = 88)</caption><tbody><tr><td>Type of article</td><td></td></tr><tr><td>Theoretical article</td><td>40 (45.5%)</td></tr><tr><td>Descriptive article</td><td>19 (21.6%)</td></tr><tr><td>Narrative review</td><td>18 (20.5%)</td></tr><tr><td>Systematic review</td><td>3 (3.4%)</td></tr><tr><td>Empirical study</td><td>44 (50.0%)</td></tr><tr><td>Protocols</td><td>4 (4.5%)</td></tr><tr><td>Field of study</td><td></td></tr><tr><td>Health</td><td>71 (80.7%)</td></tr><tr><td>Healthcare and social services</td><td>42 (47.7%)</td></tr><tr><td>Health policy and systems</td><td>22 (25.0%)</td></tr><tr><td>Continuing education for healthcare professionals</td><td>7 (8.0%)</td></tr><tr><td>General</td><td>12 (13.6%)</td></tr><tr><td>Education</td><td>5 (5.7%)</td></tr><tr><td>KMb implementation context</td><td></td></tr><tr><td>Canada</td><td>16 (18.2%)</td></tr><tr><td>Australia</td><td>9 (10.2%)</td></tr><tr><td>United States</td><td>12 (13.6%)</td></tr><tr><td>United Kingdom</td><td>5 (5.7%)</td></tr><tr><td>Europe</td><td>4 (4.5%)</td></tr><tr><td>Other*</td><td>8 (9.1%)</td></tr><tr><td>Not applicable**</td><td>34 (38.6%)</td></tr><tr><td>First authors' country of affiliation</td><td></td></tr><tr><td>Canada</td><td>31 (35.2%)</td></tr><tr><td>United States</td><td>23 (26.1%)</td></tr><tr><td>Australia</td><td>13 (14.8%)</td></tr><tr><td>United Kingdom</td><td>8 (9.1%)</td></tr><tr><td>Europe</td><td>7 (8.0%)</td></tr><tr><td>Other*</td><td>6 (6.8%)</td></tr></tbody></table>

* Countries from South America, the Caribbean, Africa, Southeast Asia, China and the Middle East

**Theoretical articles that did not implement a KMb strategy

The empirical articles category included studies with different methodological approaches (quantitative, qualitative, mixed methods). We will not report the details of
<table><caption>**Table 3** Categories used to classify the identified TMFs</caption><thead><tr><th>Category</th><th>Description and examples</th></tr></thead><tbody><tr><td>Process models</td><td>Describe steps or stages to translate evidence into action and offer practical guidance for KMb planning and execution (for example, the "Knowledge-to-Action framework" by Graham et al. [9])</td></tr><tr><td>Evaluation frameworks</td><td>Describe elements or components that could be evaluated to determine KMb implementation success (for example, "RE-ALM" by Glasgow et al. [47])</td></tr><tr><td>Determinant frameworks</td><td>Specify determinants that can act as barriers and enablers to understand or explain what influences KMb implementation and outcomes (for example, "PARISH" by Kitson et al. [48])</td></tr><tr><td>Classic theories</td><td>Theories that originate from other fields (for example, psychology sociology) and can be applied to understanding KMb processes (for example, social cognitive theories)</td></tr><tr><td>Logic models</td><td>Graphical representation of the links between inputs, activities, outputs and expected outcomes of a specific KMb strategy (for example, "CNODES knowledge translation logic model" by Sketris et al. [49])</td></tr></tbody></table>

Adapted from Nilsen [32]

<figure><img src="image_4.png" /><figcaption>**Fig. 1** PRISMA flowchart summarizing search strategy and selection results [40]</figcaption></figure>

with their main characteristics is presented in Additional file 2.

The number of theoretical and empirical articles was relatively similar. Among the theoretical articles, 19 descriptive articles (21.6%) were aimed at describing a KMb strategy, a KMb infrastructure or a TMF related to a specific programme or context; 18 articles (20.5%) synthesized knowledge to propose a TMF (new or revised); and three articles conducted systematic reviews (3.4%).

<table><caption>**Table 4** Characteristics of included articles (n = 88)</caption><tbody><tr><td>Type of article</td><td></td></tr><tr><td>Theoretical article</td><td>40 (45.5%)</td></tr><tr><td>Descriptive article</td><td>19 (21.6%)</td></tr><tr><td>Narrative review</td><td>18 (20.5%)</td></tr><tr><td>Systematic review</td><td>3 (3.4%)</td></tr><tr><td>Empirical study</td><td>44 (50.0%)</td></tr><tr><td>Protocols</td><td>4 (4.5%)</td></tr><tr><td>Field of study</td><td></td></tr><tr><td>Health</td><td>71 (80.7%)</td></tr><tr><td>Healthcare and social services</td><td>42 (47.7%)</td></tr><tr><td>Health policy and systems</td><td>22 (25.0%)</td></tr><tr><td>Continuing education for healthcare professionals</td><td>7 (8.0%)</td></tr><tr><td>General</td><td>12 (13.6%)</td></tr><tr><td>Education</td><td>5 (5.7%)</td></tr><tr><td>KMb implementation context</td><td></td></tr><tr><td>Canada</td><td>16 (18.2%)</td></tr><tr><td>Australia</td><td>9 (10.2%)</td></tr><tr><td>United States</td><td>12 (13.6%)</td></tr><tr><td>United Kingdom</td><td>5 (5.7%)</td></tr><tr><td>Europe</td><td>4 (4.5%)</td></tr><tr><td>Other*</td><td>8 (9.1%)</td></tr><tr><td>Not applicable**</td><td>34 (38.6%)</td></tr><tr><td>First authors' country of affiliation</td><td></td></tr><tr><td>Canada</td><td>31 (35.2%)</td></tr><tr><td>United States</td><td>23 (26.1%)</td></tr><tr><td>Australia</td><td>13 (14.8%)</td></tr><tr><td>United Kingdom</td><td>8 (9.1%)</td></tr><tr><td>Europe</td><td>7 (8.0%)</td></tr><tr><td>Other*</td><td>6 (6.8%)</td></tr></tbody></table>

* Countries from South America, the Caribbean, Africa, Southeast Asia, China and the Middle East

**Theoretical articles that did not implement a KMb strategy

The empirical articles category included studies with different methodological approaches (quantitative, qualitative, mixed methods). We will not report the details of
the methodologies used, as this would result in a long list with few occurrences. The empirical articles can be divided into three categories: (1) studies that evaluated a TMF related to KMb (n=16, 18.2%), (2) studies that evaluated a KMb strategy (n=21, 23.9%) and (3) studies that evaluated both a KMb strategy and a TMF (n=7, 8.0%).

Most articles were related to healthcare (n=71, 80.7%). This field of study was divided into three subdomains. The healthcare and social services articles usually described or assessed a KMb strategy targeting health professionals' practices in a variety of fields (for example, occupational therapy, dentistry, mental health, pharmacology, gerontology, nursing and so on). The health policy and systems articles usually described or assessed KMb strategies targeting decision-making processes, decision-makers or public health interventions and policies. The continuing education articles assessed training programmes for health professionals aimed at increasing knowledge and skills in a specific field. The articles in the general field described or discussed TMFs and KMb strategies that could be applied to multiple disciplines or contexts. Finally, the articles in the education field described or assessed a KMb strategy targeting education professionals.

Almost half of the articles (n=42, 47.7%) studied KMb strategies implemented in only four countries: Canada, Australia, the United States and the United Kingdom. Countries in South America, the Caribbean, Africa, Asia, the Middle East, China and Europe were underrepresented (n=8, 9.1%). The remaining 34 articles (38.6%) did not specify an implementation context and were mostly theoretical articles. Regarding the authors' countries of affiliation, Canada, the United States, Australia and the United Kingdom were again the most represented countries, featuring in 85% of the articles (n=75).

**What theories, models or frameworks exist in the literature to evaluate KMb strategies?**

Several articles proposed a new TMF (n=37, 42.0%), and some articles proposed a logic model specifically developed to evaluate their KMb strategy (n=17, 19.3%). One-third of the articles used existing TMFs (n=28, 31.8%). A few articles only referred to existing TMFs but did not use them to guide a KMb strategy evaluation (n=6, 8.5%).

The identified TMFs were then categorized according to their theoretical approaches (adapted from Nilsen, [32]) (Table 5). Five articles used or proposed more than one TMF, and three TMFs could be classified in two categories. Several articles proposed or used a process model (n=34, 38.6%) or an evaluation framework (n=28, 31.8%); these were the two most frequently identified types of TMFs. Fewer articles proposed or used a logic

model (n=17, 19.3%), a determinant framework (n=12, 13.6%) or a classic theory (n=7, 8.0%). The TMFs most often identified in the articles were the RE-AIM framework (n=5, 5.7%), the Knowledge-to-Action framework [9] (n=4, 4.5%), the Theory of Planned Behavior [51] (n=3, 3.4%) and the Expanded Outcomes framework for planning and assessing continuing medical education [52] (n=3, 3.4%). In total, we identified 87 different TMFs in the 88 articles. Only nine TMFS were retrieved in more than one article.

**What KMb strategies do the TMFs evaluate (activities, objectives, target audience)?**

Thirty-eight articles reported using more than one activity in their KMb strategy. According to the ERIC compilation, "Train and educate stakeholders" activities were the most common, followed by "Develop stakeholder interrelationships" and "Use evaluative and iterative strategies". Table 6 presents the various types of activities and the number of articles that referred to each.

Of the 88 articles analysed, 18 (20.4%) did not specify a KMb objective. The remaining articles proposed one or more KMb strategy objectives. Specifically, 39 (36.4%) articles had one objective, 15 (17.0%) had two, three (3.4%) had three, and 13 (14.8%) had four or five. Table 7 presents the different types of objectives and the number of times they were identified.

The target audiences for KMb strategies were clearly specified in half of the articles (n=44, 50.0%). Generally, these were empirical articles that targeted specific professionals (n=36, 40.9%) or decision-makers (n=8, 9.1%). Just under one-third of the articles identified a broad target audience (for example, professionals and managers in the health system, a health organization) (n=26, 29.5%). Finally, 18 articles (20.4%) did not specify a target audience for KMb; these were most often theoretical articles.

**What are the dimensions and components included in TMFs for evaluating KMb strategies?**

The analysis of the identified TMFs revealed many factors of interest relevant for the evaluation of KMb strategies. These specific components were induc-tively classified into four main dimensions: context, process, effects and impacts (Fig. 2). The context dimension refers to the assessment of the conditions in place when the KMb strategy is implemented. These include both the external (that is, sociopolitical, economic, environmental and cultural characteristics) and internal environments (that is, characteristics of organizations, individuals and stakeholder partnerships). These factors are understood to influence the selection and tailoring of a KMb strategy. The process dimension refers to the assessment of the planning,
the methodologies used, as this would result in a long list with few occurrences. The empirical articles can be divided into three categories: (1) studies that evaluated a TMF related to KMb (n=16, 18.2%), (2) studies that evaluated a KMb strategy (n=21, 23.9%) and (3) studies that evaluated both a KMb strategy and a TMF (n=7, 8.0%).

Most articles were related to healthcare (n=71, 80.7%). This field of study was divided into three subdomains. The healthcare and social services articles usually described or assessed a KMb strategy targeting health professionals' practices in a variety of fields (for example, occupational therapy, dentistry, mental health, pharmacology, gerontology, nursing and so on). The health policy and systems articles usually described or assessed KMb strategies targeting decision-making processes, decision-makers or public health interventions and policies. The continuing education articles assessed training programmes for health professionals aimed at increasing knowledge and skills in a specific field. The articles in the general field described or discussed TMFs and KMb strategies that could be applied to multiple disciplines or contexts. Finally, the articles in the education field described or assessed a KMb strategy targeting education professionals.

Almost half of the articles (n=42, 47.7%) studied KMb strategies implemented in only four countries: Canada, Australia, the United States and the United Kingdom. Countries in South America, the Caribbean, Africa, Asia, the Middle East, China and Europe were underrepresented (n=8, 9.1%). The remaining 34 articles (38.6%) did not specify an implementation context and were mostly theoretical articles. Regarding the authors' countries of affiliation, Canada, the United States, Australia and the United Kingdom were again the most represented countries, featuring in 85% of the articles (n=75).

**What theories, models or frameworks exist in the literature to evaluate KMb strategies?**

Several articles proposed a new TMF (n=37, 42.0%), and some articles proposed a logic model specifically developed to evaluate their KMb strategy (n=17, 19.3%). One-third of the articles used existing TMFs (n=28, 31.8%). A few articles only referred to existing TMFs but did not use them to guide a KMb strategy evaluation (n=6, 8.5%).

The identified TMFs were then categorized according to their theoretical approaches (adapted from Nilsen, [32]) (Table 5). Five articles used or proposed more than one TMF, and three TMFs could be classified in two categories. Several articles proposed or used a process model (n=34, 38.6%) or an evaluation framework (n=28, 31.8%); these were the two most frequently identified types of TMFs. Fewer articles proposed or used a logic

model (n=17, 19.3%), a determinant framework (n=12, 13.6%) or a classic theory (n=7, 8.0%). The TMFs most often identified in the articles were the RE-AIM framework (n=5, 5.7%), the Knowledge-to-Action framework [9] (n=4, 4.5%), the Theory of Planned Behavior [51] (n=3, 3.4%) and the Expanded Outcomes framework for planning and assessing continuing medical education [52] (n=3, 3.4%). In total, we identified 87 different TMFs in the 88 articles. Only nine TMFS were retrieved in more than one article.

**What KMb strategies do the TMFs evaluate (activities, objectives, target audience)?**

Thirty-eight articles reported using more than one activity in their KMb strategy. According to the ERIC compilation, "Train and educate stakeholders" activities were the most common, followed by "Develop stakeholder interrelationships" and "Use evaluative and iterative strategies". Table 6 presents the various types of activities and the number of articles that referred to each.

Of the 88 articles analysed, 18 (20.4%) did not specify a KMb objective. The remaining articles proposed one or more KMb strategy objectives. Specifically, 39 (36.4%) articles had one objective, 15 (17.0%) had two, three (3.4%) had three, and 13 (14.8%) had four or five. Table 7 presents the different types of objectives and the number of times they were identified.

The target audiences for KMb strategies were clearly specified in half of the articles (n=44, 50.0%). Generally, these were empirical articles that targeted specific professionals (n=36, 40.9%) or decision-makers (n=8, 9.1%). Just under one-third of the articles identified a broad target audience (for example, professionals and managers in the health system, a health organization) (n=26, 29.5%). Finally, 18 articles (20.4%) did not specify a target audience for KMb; these were most often theoretical articles.

**What are the dimensions and components included in TMFs for evaluating KMb strategies?**

The analysis of the identified TMFs revealed many factors of interest relevant for the evaluation of KMb strategies. These specific components were induc-tively classified into four main dimensions: context, process, effects and impacts (Fig. 2). The context dimension refers to the assessment of the conditions in place when the KMb strategy is implemented. These include both the external (that is, sociopolitical, economic, environmental and cultural characteristics) and internal environments (that is, characteristics of organizations, individuals and stakeholder partnerships). These factors are understood to influence the selection and tailoring of a KMb strategy. The process dimension refers to the assessment of the planning,
<table><caption>**Table 5** List of theories, models and frameworks identified in the selected articles</caption><thead><tr><th>Theory, model or framework (source reference)</th><th>Identified in</th></tr></thead><tbody><tr><td><strong>Process Models</strong></td><td></td></tr><tr><td>ACT SMART implementation toolkit</td><td>Tschida and Drahota 2023[53]</td></tr><tr><td>Combined analytical framework: science of using science and context matters</td><td>Langer and Weyrauch 2020 [52]</td></tr><tr><td>Simplified framework of interventions to promote and integrate evidence</td><td>Colquhoun et al. 2014 [54]</td></tr><tr><td>Conceptual framework for assessing communities of practice in health policy</td><td>Bertone et al. 2013 [55]</td></tr><tr><td>Conceptual framework for patient-mediated KT interventions</td><td>Gagliardi et al. 2011 [56]</td></tr><tr><td>Conceptual model for continuing professional development (Kern, 1998)</td><td>Sargeant et al. 2011 [57]</td></tr><tr><td>Content, context and process model of strategic change (Pettigrew and Whipp, 1992)</td><td>Stetler et al. 2007 [58]</td></tr><tr><td>Contribution mapping: the three-phase process model</td><td>Kok and Schult 2012 [59]</td></tr><tr><td>Different strategies needed at different stages in the process of change (Grol, 2002)</td><td>Dadich 2010 [60]</td></tr><tr><td>Five steps of individual learning (Moore, 2008)</td><td>Sargeant et al. 2011 [57]</td></tr><tr><td>Framework for evaluating engagement intervention processes and outcomes</td><td>Brown and Bahri 2019 [61]</td></tr><tr><td>Framework for the dissemination and utilization of research</td><td>Dobbins et al. 2002 [62]</td></tr><tr><td>Framework of guideline implementability</td><td>Gagliardi et al. 2012 [63]</td></tr><tr><td>Framework to guide complex storytelling interventions</td><td>Brooks et al. 2022[64]</td></tr><tr><td>Iowa implementation for sustainability framework</td><td>Cullen et al. 2022[65]</td></tr><tr><td>Knowledge translation planning template (KTPT) (Barwick, 2013)</td><td>Labbé et al. 2020 [66]</td></tr><tr><td>Knowledge-to-action (KTA) framework (Graham et al., 2006)</td><td>Straus et al. 2010 [67]<br>Graham et al. 2006 [9]<br>Bennett et al. 2016 [68]<br>Sargeant et al. 2011 [57]</td></tr><tr><td>Levels of use scale (Hall and Hord, 2015)</td><td>Brown and Rogers 2014 [69]</td></tr><tr><td>Operations triad model</td><td>Talbott et al. 2023[70]</td></tr><tr><td>Participatory action research cycle</td><td>Bennett et al. 2016 [68]</td></tr><tr><td>Plan-Do-Study-Act (PDSA) (Deming, 1986)</td><td>Sargeant et al. 2011 [57]</td></tr><tr><td>Population health planning knowledge-to-action model (Peirson and Rosella, 2015)</td><td>Rosella et al. 2018 [71]</td></tr><tr><td>Promotion of trauma-focused interventions informed by social cognitive theory</td><td>Couineau & Forbes, 2011 [72]</td></tr><tr><td>Six-step collaborative research utilization model</td><td>Dufault, 2004 [73]</td></tr><tr><td>Social impact framework</td><td>Beckett et al. 2018 [74]</td></tr><tr><td>Theory-based knowledge-transfer and exchange method of evaluation (KEME)</td><td>Kramer et al. 2013 [75]</td></tr><tr><td>The family systems nursing knowledge utilization model</td><td>Duhamel et al. 2015 [76]</td></tr><tr><td>The ladder of research use (Landry et al., 2003)</td><td>Brown and Rogers 2014 [69]</td></tr><tr><td>The modified pipeline model</td><td>Wimpenny et al. 2008 [77]</td></tr><tr><td>The revised conceptual framework of knowledge exchange (Ward et al., 2012)</td><td>Ward et al. 2012 [78]<br>Grooten et al. 2020 [79]</td></tr><tr><td>The updated Stetler model of research utilization</td><td>Stetler 2001 [80]</td></tr><tr><td>The 4E conceptual framework: exposure, experience, expertise and embedding</td><td>Farkas et al. 2003 [43]</td></tr><tr><td>Why, whose, what, how framework for knowledge mobilizers (Ward, 2017)</td><td>Ward 2017 [81]<br>Grooten et al. 2020 [79]</td></tr><tr><td><strong>Evaluation frameworks</strong></td><td></td></tr><tr><td>Advancing research and clinical practice through close collaboration (ARCC) model</td><td>Levin et al. 2011 [82]</td></tr><tr><td>A model of the types of community impacts of research partnerships</td><td>Currie et al. 2005 [83]</td></tr><tr><td>Communities of practice (COP) evaluation model</td><td>Richard et al. 2014 [84]</td></tr><tr><td>Conceptual framework of CLAHRCs</td><td>Rycroft-Malone et al. 2013 [85]</td></tr><tr><td>Conceptual model of factors influencing effectiveness of knowledge exchange</td><td>Gagliardi et al. 2008 [86]</td></tr><tr><td>Diabetes evaluation framework for innovative national evaluations</td><td>Paquette-Warren et al. 2016 [87]<br>Paquette-Warren et al. 2017 [88]</td></tr><tr><td>Dimensions of professional learning communities (Hord, 2009)</td><td>Abbot et al. 2018 [89]</td></tr><tr><td>Evaluation dimensions and methodologies for technology-enabled KT</td><td>Ho et al. 2004 [90]</td></tr><tr><td>Evaluation model of teachers' knowledge sharing behaviour</td><td>Yu et al. 2022[91]</td></tr><tr><td>Expanded outcomes framework for planning and assessing continuing medical education (Moore et al., 2009)</td><td>Moore et al. 2009 [52]<br>Arora et al. 2017 [92]<br>Sargeant et al. 2011 [57]</td></tr></tbody></table>
<table><caption>**Table 5** List of theories, models and frameworks identified in the selected articles</caption><thead><tr><th>Theory, model or framework (source reference)</th><th>Identified in</th></tr></thead><tbody><tr><td><strong>Process Models</strong></td><td></td></tr><tr><td>ACT SMART implementation toolkit</td><td>Tschida and Drahota 2023[53]</td></tr><tr><td>Combined analytical framework: science of using science and context matters</td><td>Langer and Weyrauch 2020 [52]</td></tr><tr><td>Simplified framework of interventions to promote and integrate evidence</td><td>Colquhoun et al. 2014 [54]</td></tr><tr><td>Conceptual framework for assessing communities of practice in health policy</td><td>Bertone et al. 2013 [55]</td></tr><tr><td>Conceptual framework for patient-mediated KT interventions</td><td>Gagliardi et al. 2011 [56]</td></tr><tr><td>Conceptual model for continuing professional development (Kern, 1998)</td><td>Sargeant et al. 2011 [57]</td></tr><tr><td>Content, context and process model of strategic change (Pettigrew and Whipp, 1992)</td><td>Stetler et al. 2007 [58]</td></tr><tr><td>Contribution mapping: the three-phase process model</td><td>Kok and Schult 2012 [59]</td></tr><tr><td>Different strategies needed at different stages in the process of change (Grol, 2002)</td><td>Dadich 2010 [60]</td></tr><tr><td>Five steps of individual learning (Moore, 2008)</td><td>Sargeant et al. 2011 [57]</td></tr><tr><td>Framework for evaluating engagement intervention processes and outcomes</td><td>Brown and Bahri 2019 [61]</td></tr><tr><td>Framework for the dissemination and utilization of research</td><td>Dobbins et al. 2002 [62]</td></tr><tr><td>Framework of guideline implementability</td><td>Gagliardi et al. 2012 [63]</td></tr><tr><td>Framework to guide complex storytelling interventions</td><td>Brooks et al. 2022[64]</td></tr><tr><td>Iowa implementation for sustainability framework</td><td>Cullen et al. 2022[65]</td></tr><tr><td>Knowledge translation planning template (KTPT) (Barwick, 2013)</td><td>Labbé et al. 2020 [66]</td></tr><tr><td>Knowledge-to-action (KTA) framework (Graham et al., 2006)</td><td>Straus et al. 2010 [67]<br>Graham et al. 2006 [9]<br>Bennett et al. 2016 [68]<br>Sargeant et al. 2011 [57]</td></tr><tr><td>Levels of use scale (Hall and Hord, 2015)</td><td>Brown and Rogers 2014 [69]</td></tr><tr><td>Operations triad model</td><td>Talbott et al. 2023[70]</td></tr><tr><td>Participatory action research cycle</td><td>Bennett et al. 2016 [68]</td></tr><tr><td>Plan-Do-Study-Act (PDSA) (Deming, 1986)</td><td>Sargeant et al. 2011 [57]</td></tr><tr><td>Population health planning knowledge-to-action model (Peirson and Rosella, 2015)</td><td>Rosella et al. 2018 [71]</td></tr><tr><td>Promotion of trauma-focused interventions informed by social cognitive theory</td><td>Couineau & Forbes, 2011 [72]</td></tr><tr><td>Six-step collaborative research utilization model</td><td>Dufault, 2004 [73]</td></tr><tr><td>Social impact framework</td><td>Beckett et al. 2018 [74]</td></tr><tr><td>Theory-based knowledge-transfer and exchange method of evaluation (KEME)</td><td>Kramer et al. 2013 [75]</td></tr><tr><td>The family systems nursing knowledge utilization model</td><td>Duhamel et al. 2015 [76]</td></tr><tr><td>The ladder of research use (Landry et al., 2003)</td><td>Brown and Rogers 2014 [69]</td></tr><tr><td>The modified pipeline model</td><td>Wimpenny et al. 2008 [77]</td></tr><tr><td>The revised conceptual framework of knowledge exchange (Ward et al., 2012)</td><td>Ward et al. 2012 [78]<br>Grooten et al. 2020 [79]</td></tr><tr><td>The updated Stetler model of research utilization</td><td>Stetler 2001 [80]</td></tr><tr><td>The 4E conceptual framework: exposure, experience, expertise and embedding</td><td>Farkas et al. 2003 [43]</td></tr><tr><td>Why, whose, what, how framework for knowledge mobilizers (Ward, 2017)</td><td>Ward 2017 [81]<br>Grooten et al. 2020 [79]</td></tr><tr><td><strong>Evaluation frameworks</strong></td><td></td></tr><tr><td>Advancing research and clinical practice through close collaboration (ARCC) model</td><td>Levin et al. 2011 [82]</td></tr><tr><td>A model of the types of community impacts of research partnerships</td><td>Currie et al. 2005 [83]</td></tr><tr><td>Communities of practice (COP) evaluation model</td><td>Richard et al. 2014 [84]</td></tr><tr><td>Conceptual framework of CLAHRCs</td><td>Rycroft-Malone et al. 2013 [85]</td></tr><tr><td>Conceptual model of factors influencing effectiveness of knowledge exchange</td><td>Gagliardi et al. 2008 [86]</td></tr><tr><td>Diabetes evaluation framework for innovative national evaluations</td><td>Paquette-Warren et al. 2016 [87]<br>Paquette-Warren et al. 2017 [88]</td></tr><tr><td>Dimensions of professional learning communities (Hord, 2009)</td><td>Abbot et al. 2018 [89]</td></tr><tr><td>Evaluation dimensions and methodologies for technology-enabled KT</td><td>Ho et al. 2004 [90]</td></tr><tr><td>Evaluation model of teachers' knowledge sharing behaviour</td><td>Yu et al. 2022[91]</td></tr><tr><td>Expanded outcomes framework for planning and assessing continuing medical education (Moore et al., 2009)</td><td>Moore et al. 2009 [52]<br>Arora et al. 2017 [92]<br>Sargeant et al. 2011 [57]</td></tr></tbody></table>
<table><caption>**Table 5 (continued)**</caption><thead><tr><th>Theory, model or framework (source reference)</th><th>Identified in</th></tr></thead><tbody><tr><td>Framework for evaluating educational outcomes (Kirkpatrick, 1967; 1996)</td><td>Sargeant et al. 2011 [57]<br>Smidt et al. 2009 [93]</td></tr><tr><td>Framework for assessing the impact of implementation of best-practice guidelines</td><td>Jeffs et al. 2013 [94]</td></tr><tr><td>Knowledge uptake and utilization tool (KUUT)</td><td>Skinner 2007 [95]</td></tr><tr><td>Knowledge translation planning template (KTPT) (Barwick, 2013)</td><td>Labbé et al. 2020 [66]</td></tr><tr><td>Measuring the impact of health research: an assessment tool</td><td>Lavis et al. 2003 [96]</td></tr><tr><td>Model of deliberative dialogues as a KTE strategy</td><td>Boyko et al. 2012 [97]</td></tr><tr><td>Modified Kirkpatrick's framework (Barr, 2005)</td><td>Sargeant et al. 2011 [57]</td></tr><tr><td>Outcomes for implementation research</td><td>Proctor et al. 2011 [98]</td></tr><tr><td>RE-AIM framework (Glasgow et al., 1999)</td><td>Gainforth et al., 2015 [99]<br>Glasgow et al. 2019 [100]<br>Shelton et al. 2020[101]<br>Bender et al. 2021[102]<br>De la Garza et al. 2023[103]</td></tr><tr><td>Types of evaluation use</td><td>Alkin and Taut 2003 [104]</td></tr><tr><td>Working conceptual model for embedded implementation research</td><td>Varallyay et al. 2020 [105]</td></tr><tr><td>Determinant frameworks</td><td></td></tr><tr><td>A model for collaborative working to facilitate KM in public health</td><td>McCabe et al. 2015 [106]</td></tr><tr><td>A simplified framework of interventions to promote and integrate evidence</td><td>Colquhoun et al. 2014 [54]</td></tr><tr><td>Conceptual model of factors influencing effectiveness of knowledge exchange</td><td>Gagliardi et al. 2008 [86]</td></tr><tr><td>IDS-based conceptual framework for translating evidence into practice, policy and public health improvements</td><td>Gonzales et al. 2012[107]</td></tr><tr><td>Joint venture model of knowledge utilization (JVMKU)</td><td>Edgar 2006 [108]</td></tr><tr><td>PARIHS framework (Kitson et al., 1998)</td><td>Stetler et al. 2011 [109]</td></tr><tr><td>Professional learning evaluation 5-level framework (Guskey, 2014)</td><td>Abbot et al. 2018 [89]</td></tr><tr><td>Theoretical domains framework (TDF) (Michie et al. 2005)</td><td>Bennett et al. 2016 [68]<br>Brennan et al. 2016 [110]</td></tr><tr><td>The knowledge translation and exchange framework for road safety</td><td>Hinchcliff et al. 2017 [111]</td></tr><tr><td>TITO framework</td><td>Ye et al. 2022[112]</td></tr><tr><td>VEDMAP (value- and evidence-based decision-making and practice)</td><td>Mfuso-Bengo et al., 2023</td></tr><tr><td>Classic theories</td><td></td></tr><tr><td>Evidence-based practice confidence (EPIS) scale (Salbach et al., 2013)</td><td>Brangan et al. 2015 [113]</td></tr><tr><td>Innovation-decision process (Rogers, 2003)</td><td>Gainforth et al. 2015 [99]</td></tr><tr><td>Social cognitive theory (Bandura, 1997)</td><td>Bonetti et al. 2009 [114]</td></tr><tr><td>Stages of change model (Prochaska and DiClemente, 1985)</td><td>Buckley et al. 2003 [115]</td></tr><tr><td>Stages of change readiness and treatment eagerness scale (Miller and Tonnigan, 1996)</td><td>Buckley et al. 2003 [115]</td></tr><tr><td>Theory of planned behavior (TPB) (Ajzen, 1991)</td><td>Boyko et al. 2011 [116]<br>Bonetti et al. 2009 [114]<br>Imani-Nasab et al. 2017 [117]</td></tr><tr><td>Two-communities theory (Caplan, 1979)</td><td>Dwan et al. 2015 [118]</td></tr><tr><td>Logic Models</td><td></td></tr><tr><td>Australian prevention partnership centre model</td><td>Haynes et al. 2020 [119]</td></tr><tr><td>Australian NSW Agency for Clinical Innovation – networks project logic framework</td><td>Haines et al. 2012<br>[120]</td></tr><tr><td>CDC science impact framework</td><td>Ko et al. 2019[121]</td></tr><tr><td>Center of Excellence for Training and Research translation's evaluation framework</td><td>Leeman et al. 2012 [122]</td></tr><tr><td>CNODES' knowledge translation logic model</td><td>Sketris et al. 2020 [49]</td></tr><tr><td>CO-OPS KTE platform's logic model and evaluation plan</td><td>Pettman et al. 2016 [123]</td></tr><tr><td>Conceptual model for building programme sustainability in public health settings</td><td>Moreland-Russell et al. 2023</td></tr><tr><td>Evidence Informed Decision Making Network of the Caribbean (EvIDENCe) initiative</td><td>Yearwood et al. 2018 [124]</td></tr><tr><td>EVIPNet Europe M&E Framework: WHO Secretariat level logic model and EVIPNet Europe M&E Framework: country team/KTP level logic model</td><td>Kuchenmüller et al. 2022</td></tr><tr><td>KT platform 4C programme theory</td><td>Thomson et al. 2019 [125]</td></tr><tr><td>Logic model of the Center of Research Excellence in Polycystic Ovary Syndrome</td><td>Garad et al., 2018 [126]</td></tr></tbody></table>
<table><caption>**Table 5** (continued)</caption><thead><tr><th>Theory, model or framework (source reference)</th><th>Identified in</th></tr></thead><tbody><tr><td>Framework for evaluating educational outcomes (Kirkpatrick, 1967; 1996)</td><td>Sargeant et al. 2011 [57]<br>Smidt et al. 2009 [93]</td></tr><tr><td>Framework for assessing the impact of implementation of best-practice guidelines</td><td>Jeffs et al. 2013 [94]</td></tr><tr><td>Knowledge uptake and utilization tool (KUUT)</td><td>Skinner 2007 [95]</td></tr><tr><td>Knowledge translation planning template (KTPT) (Barwick, 2013)</td><td>Labbé et al. 2020 [66]</td></tr><tr><td>Measuring the impact of health research: an assessment tool</td><td>Lavis et al. 2003 [96]</td></tr><tr><td>Model of deliberative dialogues as a KTE strategy</td><td>Boyko et al. 2012 [97]</td></tr><tr><td>Modified Kirkpatrick's framework (Barr, 2005)</td><td>Sargeant et al. 2011 [57]</td></tr><tr><td>Outcomes for implementation research</td><td>Proctor et al. 2011 [98]</td></tr><tr><td>RE-AIM framework (Glasgow et al., 1999)</td><td>Gainforth et al., 2015 [99]<br>Glasgow et al. 2019 [100]<br>Shelton et al. 2020[101]<br>Bender et al. 2021[102]<br>De la Garza et al. 2023[103]</td></tr><tr><td>Types of evaluation use</td><td>Alkin and Taut 2003 [104]</td></tr><tr><td>Working conceptual model for embedded implementation research</td><td>Varallyay et al. 2020 [105]</td></tr><tr><td>Determinant frameworks</td><td></td></tr><tr><td>A model for collaborative working to facilitate KM in public health</td><td>McCabe et al. 2015 [106]</td></tr><tr><td>A simplified framework of interventions to promote and integrate evidence</td><td>Colquhoun et al. 2014 [54]</td></tr><tr><td>Conceptual model of factors influencing effectiveness of knowledge exchange</td><td>Gagliardi et al. 2008 [86]</td></tr><tr><td>IDS-based conceptual framework for translating evidence into practice, policy and public health improvements</td><td>Gonzales et al. 2012[107]</td></tr><tr><td>Joint venture model of knowledge utilization (JVMKU)</td><td>Edgar 2006 [108]</td></tr><tr><td>PARIHS framework (Kitson et al., 1998)</td><td>Stetler et al. 2011 [109]</td></tr><tr><td>Professional learning evaluation 5-level framework (Guskey, 2014)</td><td>Abbot et al. 2018 [89]</td></tr><tr><td>Theoretical domains framework (TDF) (Michie et al. 2005)</td><td>Bennett et al. 2016 [68]<br>Brennan et al. 2016 [110]</td></tr><tr><td>The knowledge translation and exchange framework for road safety</td><td>Hinchcliff et al. 2017 [111]</td></tr><tr><td>TITO framework</td><td>Ye et al. 2022[112]</td></tr><tr><td>VEDMAP (value- and evidence-based decision-making and practice)</td><td>Mfuso-Bengo et al., 2023</td></tr><tr><td>Classic theories</td><td></td></tr><tr><td>Evidence-based practice confidence (EPIS) scale (Salbach et al., 2013)</td><td>Brangan et al. 2015 [113]</td></tr><tr><td>Innovation-decision process (Rogers, 2003)</td><td>Gainforth et al. 2015 [99]</td></tr><tr><td>Social cognitive theory (Bandura, 1997)</td><td>Bonetti et al. 2009 [114]</td></tr><tr><td>Stages of change model (Prochaska and DiClemente, 1985)</td><td>Buckley et al. 2003 [115]</td></tr><tr><td>Stages of change readiness and treatment eagerness scale (Miller and Tonnigan, 1996)</td><td>Buckley et al. 2003 [115]</td></tr><tr><td>Theory of planned behavior (TPB) (Ajzen, 1991)</td><td>Boyko et al. 2011 [116]<br>Bonetti et al. 2009 [114]<br>Imani-Nasab et al. 2017 [117]</td></tr><tr><td>Two-communities theory (Caplan, 1979)</td><td>Dwan et al. 2015 [118]</td></tr><tr><td>Logic Models</td><td></td></tr><tr><td>Australian prevention partnership centre model</td><td>Haynes et al. 2020 [119]</td></tr><tr><td>Australian NSW Agency for Clinical Innovation – networks project logic framework</td><td>Haines et al. 2012<br>[120]</td></tr><tr><td>CDC science impact framework</td><td>Ko et al. 2019[121]</td></tr><tr><td>Center of Excellence for Training and Research translation's evaluation framework</td><td>Leeman et al. 2012 [122]</td></tr><tr><td>CNODES' knowledge translation logic model</td><td>Sketris et al. 2020 [49]</td></tr><tr><td>CO-OPS KTE platform's logic model and evaluation plan</td><td>Pettman et al. 2016 [123]</td></tr><tr><td>Conceptual model for building programme sustainability in public health settings</td><td>Moreland-Russell et al. 2023</td></tr><tr><td>Evidence Informed Decision Making Network of the Caribbean (EvIDENCe) initiative</td><td>Yearwood et al. 2018 [124]</td></tr><tr><td>EVIPNet Europe M&E Framework: WHO Secretariat level logic model and EVIPNet Europe M&E Framework: country team/KTP level logic model</td><td>Kuchenmüller et al. 2022</td></tr><tr><td>KT platform 4C programme theory</td><td>Thomson et al. 2019 [125]</td></tr><tr><td>Logic model of the Center of Research Excellence in Polycystic Ovary Syndrome</td><td>Garad et al., 2018 [126]</td></tr></tbody></table>
<table><caption>**Table 5** (continued)</caption><thead><tr><td>Theory, model or framework (source reference)</td><td>Identified in</td></tr></thead><tbody><tr><td>Policy liaison initiative (PLI) logic model</td><td>Brennan et al., 2016 [110]</td></tr><tr><td>Programme theory of The Remote Primary Health Care Manuals</td><td>Reddy et al. 2015 [127]</td></tr><tr><td>The institute for Work and Health Research impact model</td><td>Van Eerd et al. 2021[128]</td></tr><tr><td>The logic model for the INSPIRE care model</td><td>Yip et al. 2021[129]2023–12–14 12:10:00</td></tr><tr><td>The logic model of the evidence-based practice training programme</td><td>Guo et al. 2011 [130]</td></tr><tr><td>The SEA-ORCHID logical framework</td><td>McDonald et al. 2010 [131]</td></tr></tbody></table>

<table><caption>**Table 6** Types of KMb activities identified in the articles</caption><thead><tr><td>KMb activities</td><td>Number of articles* (n=88)</td></tr></thead><tbody><tr><td>Train and educate stakeholders</td><td>46 (52.3%)</td></tr><tr><td>Develop stakeholder interrelationships</td><td>23 (26.1%)</td></tr><tr><td>Use evaluative and iterative strategies</td><td>17 (19.3%)</td></tr><tr><td>Provide interactive assistance</td><td>14 (15.9%)</td></tr><tr><td>Adapt and tailor to context</td><td>7 (8.0%)</td></tr><tr><td>Engage consumers</td><td>6 (6.8%)</td></tr><tr><td>‘Change infrastructure</td><td>4 (4.5%)</td></tr><tr><td>Utilize financial strategies</td><td>1 (1.1%)</td></tr><tr><td>Support clinicians</td><td>1 (1.1%)</td></tr></tbody></table>

*Several articles identified many different activities in their KMb strategies

<table><caption>**Table 7** Types of KMb objectives identified in the articles</caption><thead><tr><td>KMb objectives</td><td>Number of articles* (n=88)</td></tr></thead><tbody><tr><td>Expose – inform</td><td>17 (19.3%)</td></tr><tr><td>Change attitude – raise awareness</td><td>9 (10.2%)</td></tr><tr><td>Inform and influence decision-making</td><td>12 (13.6%)</td></tr><tr><td>Improve practices – increase expertise</td><td>30 (34.1%)</td></tr><tr><td>Foster collaboration</td><td>12 (13.6%)</td></tr></tbody></table>

*Some articles mentioned several objectives and others none

levels and mechanisms of implementation, as well as to the characteristics of the KMb strategy implemented. The effects dimension refers to the assessment of outcomes following the KMb strategy implementation. The potential effects vary depending on the strategy's objectives and can be either the immediate results of the KMb strategy or short-, medium- and long-term outcomes. The conceptual gradation of effects was generally represented in a similar way in the TMFs analysed, but the temporality of effects could vary. A medium-term outcome in one study could be understood as a long-term outcome in another. However, the majority of authors group these effects into three

categories (Gervais et al. 2016: p. 6): (1) short-term effects, measured by success of KMb strategy measured by success of KMb strategy (number of people reached, satisfaction, participation and so on); (2) medium-term effects linked to changes in individual attitude and the use of knowledge; and (3) the long-term effects that result from achieving the KMb objective (for example, improved practices and services, changed collective behaviour, sustainable use of knowledge).

Finally, the impacts dimension refers to the ultimate effects of KMb products or interventions on end users, as measured by the organization (Phipps et al. [36], p. 34). The evaluation of these ultimate effects can be measured by the integration of a promising practice into organizational routines, by the effects on service users or by the effects on the health and well-being of communities and society in general.

This gradation shows the importance of measuring effects at different points in time, to take account of the time they take to appear and their evolving nature (Gervais et al., 2016: p. 6).

Most of the articles presented the dimensions that should be evaluated, whereas the empirical articles presented the dimensions but also used them in practice to evaluate a KMb strategy. Only five articles (5.7%) did not mention specific dimensions that could be classified.

Table 8 presents both the number of articles that presented dimensions to be evaluated and the number of articles that evaluated them in practice. These results showed that the effects dimension was both the most often named and the most evaluated in practice. The other three dimensions (context, process, impacts), while quite often mentioned as relevant to assess, were less often evaluated in practice. For example, only five articles (5.7%) reported having assessed the impacts dimension.

As previously mentioned, the components relevant for the evaluation of KMb strategies were extracted from the identified TMFs. Table 9 presents these components, which represent the more specific factors of interest for assessing context, process, effects and impacts.
<table><caption>**Table 5** (continued)</caption><thead><tr><td>Theory, model or framework (source reference)</td><td>Identified in</td></tr></thead><tbody><tr><td>Policy liaison initiative (PLI) logic model</td><td>Brennan et al., 2016 [110]</td></tr><tr><td>Programme theory of The Remote Primary Health Care Manuals</td><td>Reddy et al. 2015 [127]</td></tr><tr><td>The institute for Work and Health Research impact model</td><td>Van Eerd et al. 2021[128]</td></tr><tr><td>The logic model for the INSPIRE care model</td><td>Yip et al. 2021[129]2023–12–14 12:10:00</td></tr><tr><td>The logic model of the evidence-based practice training programme</td><td>Guo et al. 2011 [130]</td></tr><tr><td>The SEA-ORCHID logical framework</td><td>McDonald et al. 2010 [131]</td></tr></tbody></table>

<table><caption>**Table 6** Types of KMb activities identified in the articles</caption><thead><tr><td>KMb activities</td><td>Number of articles* (n=88)</td></tr></thead><tbody><tr><td>Train and educate stakeholders</td><td>46 (52.3%)</td></tr><tr><td>Develop stakeholder interrelationships</td><td>23 (26.1%)</td></tr><tr><td>Use evaluative and iterative strategies</td><td>17 (19.3%)</td></tr><tr><td>Provide interactive assistance</td><td>14 (15.9%)</td></tr><tr><td>Adapt and tailor to context</td><td>7 (8.0%)</td></tr><tr><td>Engage consumers</td><td>6 (6.8%)</td></tr><tr><td>‘Change infrastructure</td><td>4 (4.5%)</td></tr><tr><td>Utilize financial strategies</td><td>1 (1.1%)</td></tr><tr><td>Support clinicians</td><td>1 (1.1%)</td></tr></tbody></table>

*Several articles identified many different activities in their KMb strategies

<table><caption>**Table 7** Types of KMb objectives identified in the articles</caption><thead><tr><td>KMb objectives</td><td>Number of articles* (n=88)</td></tr></thead><tbody><tr><td>Expose – inform</td><td>17 (19.3%)</td></tr><tr><td>Change attitude – raise awareness</td><td>9 (10.2%)</td></tr><tr><td>Inform and influence decision-making</td><td>12 (13.6%)</td></tr><tr><td>Improve practices – increase expertise</td><td>30 (34.1%)</td></tr><tr><td>Foster collaboration</td><td>12 (13.6%)</td></tr></tbody></table>

*Some articles mentioned several objectives and others none

levels and mechanisms of implementation, as well as to the characteristics of the KMb strategy implemented. The effects dimension refers to the assessment of outcomes following the KMb strategy implementation. The potential effects vary depending on the strategy's objectives and can be either the immediate results of the KMb strategy or short-, medium- and long-term outcomes. The conceptual gradation of effects was generally represented in a similar way in the TMFs analysed, but the temporality of effects could vary. A medium-term outcome in one study could be understood as a long-term outcome in another. However, the majority of authors group these effects into three

categories (Gervais et al. 2016: p. 6): (1) short-term effects, measured by success of KMb strategy measured by success of KMb strategy (number of people reached, satisfaction, participation and so on); (2) medium-term effects linked to changes in individual attitude and the use of knowledge; and (3) the long-term effects that result from achieving the KMb objective (for example, improved practices and services, changed collective behaviour, sustainable use of knowledge).

Finally, the impacts dimension refers to the ultimate effects of KMb products or interventions on end users, as measured by the organization (Phipps et al. [36], p. 34). The evaluation of these ultimate effects can be measured by the integration of a promising practice into organizational routines, by the effects on service users or by the effects on the health and well-being of communities and society in general.

This gradation shows the importance of measuring effects at different points in time, to take account of the time they take to appear and their evolving nature (Gervais et al., 2016: p. 6).

Most of the articles presented the dimensions that should be evaluated, whereas the empirical articles presented the dimensions but also used them in practice to evaluate a KMb strategy. Only five articles (5.7%) did not mention specific dimensions that could be classified.

Table 8 presents both the number of articles that presented dimensions to be evaluated and the number of articles that evaluated them in practice. These results showed that the effects dimension was both the most often named and the most evaluated in practice. The other three dimensions (context, process, impacts), while quite often mentioned as relevant to assess, were less often evaluated in practice. For example, only five articles (5.7%) reported having assessed the impacts dimension.

As previously mentioned, the components relevant for the evaluation of KMb strategies were extracted from the identified TMFs. Table 9 presents these components, which represent the more specific factors of interest for assessing context, process, effects and impacts.
<figure><img src="image_5.png" /><figcaption>**Fig. 2** The main evaluation dimensions that emerged from the TMFs analysed</figcaption></figure>

<table><caption>**Table 8** Number of articles that mentioned or evaluated the different dimensions</caption><thead><tr><td>Dimensions</td><td>Number of articles that mentioned the dimensions (n = 88)</td><td>Number of articles that evaluated the dimensions (n = 88)</td></tr></thead><tbody><tr><td>(1) Context</td><td>42 (47.7%)</td><td>15 (17.0%)</td></tr><tr><td>(2) Process</td><td>46 (52.3%)</td><td>16 (18.2%)</td></tr><tr><td>(3) Effects (immediate result; short-, medium- and long-term effects)</td><td>75 (85.2%)</td><td>32 (36.4%)</td></tr><tr><td>(4) Impacts (or benefits)</td><td>47 (53.4%)</td><td>5 (5.7%)</td></tr></tbody></table>

## Discussion

Although often overlooked, the evaluation of KMb strategies is an essential step in guiding organizations seeking to determine whether the expected outcomes of their initiatives are being realized. Evaluation not only allows organizations to make adjustments if the initiatives are not producing the expected results, but also helps them to justify their funding of such initiatives. Evaluation is also essential if the KMb science is to truly inform KMb practice, such that the strategies developed are based on empirical data [30]. To make KMb evaluation more feasible, evaluation must be promoted and practices improved.

This scoping review meets the first objective of our project, which was to provide an overview of reference frameworks used or proposed for evaluating KM strategies, and to propose a preliminary version of a reference framework for evaluating KM strategies. Several key findings emerged from this scoping review:

### Proliferation of theories, models and frameworks, but few frequently used

We are seeing a proliferation of TMFs in KMb and closely related fields [132, 133]. Thus, the results of this scoping review support the argument that the conceptual and theoretical development of the field is outpacing its
<figure><img src="image_5.png" /><figcaption>**Fig. 2** The main evaluation dimensions that emerged from the TMFs analysed</figcaption></figure>

<table><caption>**Table 8** Number of articles that mentioned or evaluated the different dimensions</caption><thead><tr><th>Dimensions</th><th>Number of articles that mentioned the dimensions (n = 88)</th><th>Number of articles that evaluated the dimensions (n = 88)</th></tr></thead><tbody><tr><td>(1) Context</td><td>42 (47.7%)</td><td>15 (17.0%)</td></tr><tr><td>(2) Process</td><td>46 (52.3%)</td><td>16 (18.2%)</td></tr><tr><td>(3) Effects (immediate result; short-, medium- and long-term effects)</td><td>75 (85.2%)</td><td>32 (36.4%)</td></tr><tr><td>(4) Impacts (or benefits)</td><td>47 (53.4%)</td><td>5 (5.7%)</td></tr></tbody></table>

## Discussion

Although often overlooked, the evaluation of KMb strategies is an essential step in guiding organizations seeking to determine whether the expected outcomes of their initiatives are being realized. Evaluation not only allows organizations to make adjustments if the initiatives are not producing the expected results, but also helps them to justify their funding of such initiatives. Evaluation is also essential if the KMb science is to truly inform KMb practice, such that the strategies developed are based on empirical data [30]. To make KMb evaluation more feasible, evaluation must be promoted and practices improved.

This scoping review meets the first objective of our project, which was to provide an overview of reference frameworks used or proposed for evaluating KM strategies, and to propose a preliminary version of a reference framework for evaluating KM strategies. Several key findings emerged from this scoping review:

### Proliferation of theories, models and frameworks, but few frequently used

We are seeing a proliferation of TMFs in KMb and closely related fields [132, 133]. Thus, the results of this scoping review support the argument that the conceptual and theoretical development of the field is outpacing its
<table><caption>**Table 9** Dimensions, subdimensions and components for evaluating KMb strategies</caption><thead><tr><th>Dimensions</th><th>Subdimensions</th><th>Components</th></tr></thead><tbody><tr><td rowspan="10">(1) Context</td><td>External context</td><td>Supportive external environment<br>Response to needs<br>Accessibility to knowledge<br>Priority given to knowledge</td></tr><tr><td>Internal context – organization</td><td>Structural characteristics<br>Organizational culture<br>Available resources<br>Networks and communications<br>Implementation climate<br>Leadership</td></tr><tr><td>Internal context – individuals (target population)</td><td>Personal characteristics<br>Attitudes (for example, receptivity, motivation)<br>Beliefs (for example, perceived value and utility)<br>Knowledge and skills (pre-strategy objective assessment)<br>Perceived knowledge and skills (pre-strategy)</td></tr><tr><td>Internal context – partnership and collaboration</td><td>Functioning of the partnership or collaboration<br>Perceived quality of the partnership or collaboration<br>Characteristics of the group of partners or collaborators</td></tr><tr><td>Planification</td><td>Presence of a KMb plan (intervention logic)<br>Presence of an evaluation plan for the KMb strategy</td></tr><tr><td>KMb strategy</td><td>Characteristics of the strategy (for example, types of activities)<br>Characteristics of the content (for example, knowledge quality)<br>Characteristics of those responsible for the KMb strategy</td></tr><tr><td>Implementation</td><td>Level of participation<br>Reason (motivation) for participation<br>Participants' attitudes and commitment<br>Implementation fidelity<br>Adaptation of the KMb strategy<br>Implementation and evaluation follow-up</td></tr><tr><td>Immediate results</td><td>Participants' satisfaction<br>Perceived learning<br>Objective learning<br>Sense of competence (self-efficacy)<br>Change in beliefs and attitudes<br>Intention to use knowledge</td></tr><tr><td>Short- to medium-term effect of evidence use</td><td>Knowledge adoption<br>Knowledge appropriation<br>Knowledge application<br>Decision-making support using acquired knowledge<br>Intent to maintain knowledge use<br>Collaboration development</td></tr><tr><td>Medium- to long-term effect of evidence use</td><td>Effectiveness of knowledge use<br>Development of competence<br>Individual behaviour change<br>Collective behaviour change<br>Organizational change<br>Sustained knowledge use<br>Updating (adaptation) of knowledge through practice<br>Improved practices and services<br>Sharing of acquired expertise<br>Maintenance of the collaboration</td></tr><tr><td rowspan="3">(2) Process</td><td>Impacts or benefits of evidence use</td><td>Impacts on people receiving services<br>Impacts on professionals<br>Impacts on organizations, policies or systems<br>Impacts on the community or population</td></tr><tr><td>Immediate results</td><td>Participants' satisfaction<br>Perceived learning<br>Objective learning<br>Sense of competence (self-efficacy)<br>Change in beliefs and attitudes<br>Intention to use knowledge</td></tr><tr><td>Short- to medium-term effect of evidence use</td><td>Knowledge adoption<br>Knowledge appropriation<br>Knowledge application<br>Decision-making support using acquired knowledge<br>Intent to maintain knowledge use<br>Collaboration development</td></tr><tr><td rowspan="5">(3) Effects</td><td>Immediate results</td><td>Participants' satisfaction<br>Perceived learning<br>Objective learning<br>Sense of competence (self-efficacy)<br>Change in beliefs and attitudes<br>Intention to use knowledge</td></tr><tr><td>Short- to medium-term effect of evidence use</td><td>Knowledge adoption<br>Knowledge appropriation<br>Knowledge application<br>Decision-making support using acquired knowledge<br>Intent to maintain knowledge use<br>Collaboration development</td></tr><tr><td>Medium- to long-term effect of evidence use</td><td>Effectiveness of knowledge use<br>Development of competence<br>Individual behaviour change<br>Collective behaviour change<br>Organizational change<br>Sustained knowledge use<br>Updating (adaptation) of knowledge through practice<br>Improved practices and services<br>Sharing of acquired expertise<br>Maintenance of the collaboration</td></tr><tr><td>Immediate results</td><td>Participants' satisfaction<br>Perceived learning<br>Objective learning<br>Sense of competence (self-efficacy)<br>Change in beliefs and attitudes<br>Intention to use knowledge</td></tr><tr><td>Short- to medium-term effect of evidence use</td><td>Knowledge adoption<br>Knowledge appropriation<br>Knowledge application<br>Decision-making support using acquired knowledge<br>Intent to maintain knowledge use<br>Collaboration development</td></tr><tr><td rowspan="3">(4) Impacts</td><td>Immediate results</td><td>Participants' satisfaction<br>Perceived learning<br>Objective learning<br>Sense of competence (self-efficacy)<br>Change in beliefs and attitudes<br>Intention to use knowledge</td></tr><tr><td>Short- to medium-term effect of evidence use</td><td>Knowledge adoption<br>Knowledge appropriation<br>Knowledge application<br>Decision-making support using acquired knowledge<br>Intent to maintain knowledge use<br>Collaboration development</td></tr><tr><td>Medium- to long-term effect of evidence use</td><td>Effectiveness of knowledge use<br>Development of competence<br>Individual behaviour change<br>Collective behaviour change<br>Organizational change<br>Sustained knowledge use<br>Updating (adaptation) of knowledge through practice<br>Improved practices and services<br>Sharing of acquired expertise<br>Maintenance of the collaboration</td></tr></tbody></table>
<table><caption>**Table 9** Dimensions, subdimensions and components for evaluating KMb strategies</caption><thead><tr><th>Dimensions</th><th>Subdimensions</th><th>Components</th></tr></thead><tbody><tr><td rowspan="10">(1) Context</td><td>External context</td><td>Supportive external environment<br>Response to needs<br>Accessibility to knowledge<br>Priority given to knowledge</td></tr><tr><td>Internal context – organization</td><td>Structural characteristics<br>Organizational culture<br>Available resources<br>Networks and communications<br>Implementation climate<br>Leadership</td></tr><tr><td>Internal context – individuals (target population)</td><td>Personal characteristics<br>Attitudes (for example, receptivity, motivation)<br>Beliefs (for example, perceived value and utility)<br>Knowledge and skills (pre-strategy objective assessment)<br>Perceived knowledge and skills (pre-strategy)</td></tr><tr><td>Internal context – partnership and collaboration</td><td>Functioning of the partnership or collaboration<br>Perceived quality of the partnership or collaboration<br>Characteristics of the group of partners or collaborators</td></tr><tr><td>Planification</td><td>Presence of a KMb plan (intervention logic)<br>Presence of an evaluation plan for the KMb strategy</td></tr><tr><td>KMb strategy</td><td>Characteristics of the strategy (for example, types of activities)<br>Characteristics of the content (for example, knowledge quality)<br>Characteristics of those responsible for the KMb strategy</td></tr><tr><td>Implementation</td><td>Level of participation<br>Reason (motivation) for participation<br>Participants' attitudes and commitment<br>Implementation fidelity<br>Adaptation of the KMb strategy<br>Implementation and evaluation follow-up</td></tr><tr><td>Immediate results</td><td>Participants' satisfaction<br>Perceived learning<br>Objective learning<br>Sense of competence (self-efficacy)<br>Change in beliefs and attitudes<br>Intention to use knowledge</td></tr><tr><td>Short- to medium-term effect of evidence use</td><td>Knowledge adoption<br>Knowledge appropriation<br>Knowledge application<br>Decision-making support using acquired knowledge<br>Intent to maintain knowledge use<br>Collaboration development</td></tr><tr><td>Medium- to long-term effect of evidence use</td><td>Effectiveness of knowledge use<br>Development of competence<br>Individual behaviour change<br>Collective behaviour change<br>Organizational change<br>Sustained knowledge use<br>Updating (adaptation) of knowledge through practice<br>Improved practices and services<br>Sharing of acquired expertise<br>Maintenance of the collaboration</td></tr><tr><td rowspan="4">(2) Process</td><td>Impacts or benefits of evidence use</td><td>Impacts on people receiving services<br>Impacts on professionals<br>Impacts on organizations, policies or systems<br>Impacts on the community or population</td></tr><tr><td>Immediate results</td><td>Participants' satisfaction<br>Perceived learning<br>Objective learning<br>Sense of competence (self-efficacy)<br>Change in beliefs and attitudes<br>Intention to use knowledge</td></tr><tr><td>Short- to medium-term effect of evidence use</td><td>Knowledge adoption<br>Knowledge appropriation<br>Knowledge application<br>Decision-making support using acquired knowledge<br>Intent to maintain knowledge use<br>Collaboration development</td></tr><tr><td>Medium- to long-term effect of evidence use</td><td>Effectiveness of knowledge use<br>Development of competence<br>Individual behaviour change<br>Collective behaviour change<br>Organizational change<br>Sustained knowledge use<br>Updating (adaptation) of knowledge through practice<br>Improved practices and services<br>Sharing of acquired expertise<br>Maintenance of the collaboration</td></tr><tr><td rowspan="4">(3) Effects</td><td>Immediate results</td><td>Participants' satisfaction<br>Perceived learning<br>Objective learning<br>Sense of competence (self-efficacy)<br>Change in beliefs and attitudes<br>Intention to use knowledge</td></tr><tr><td>Short- to medium-term effect of evidence use</td><td>Knowledge adoption<br>Knowledge appropriation<br>Knowledge application<br>Decision-making support using acquired knowledge<br>Intent to maintain knowledge use<br>Collaboration development</td></tr><tr><td>Medium- to long-term effect of evidence use</td><td>Effectiveness of knowledge use<br>Development of competence<br>Individual behaviour change<br>Collective behaviour change<br>Organizational change<br>Sustained knowledge use<br>Updating (adaptation) of knowledge through practice<br>Improved practices and services<br>Sharing of acquired expertise<br>Maintenance of the collaboration</td></tr><tr><td>Immediate results</td><td>Participants' satisfaction<br>Perceived learning<br>Objective learning<br>Sense of competence (self-efficacy)<br>Change in beliefs and attitudes<br>Intention to use knowledge</td></tr><tr><td rowspan="4">(4) Impacts</td><td>Impacts or benefits of evidence use</td><td>Impacts on people receiving services<br>Impacts on professionals<br>Impacts on organizations, policies or systems<br>Impacts on the community or population</td></tr><tr><td>Immediate results</td><td>Participants' satisfaction<br>Perceived learning<br>Objective learning<br>Sense of competence (self-efficacy)<br>Change in beliefs and attitudes<br>Intention to use knowledge</td></tr><tr><td>Short- to medium-term effect of evidence use</td><td>Knowledge adoption<br>Knowledge appropriation<br>Knowledge application<br>Decision-making support using acquired knowledge<br>Intent to maintain knowledge use<br>Collaboration development</td></tr><tr><td>Medium- to long-term effect of evidence use</td><td>Effectiveness of knowledge use<br>Development of competence<br>Individual behaviour change<br>Collective behaviour change<br>Organizational change<br>Sustained knowledge use<br>Updating (adaptation) of knowledge through practice<br>Improved practices and services<br>Sharing of acquired expertise<br>Maintenance of the collaboration</td></tr></tbody></table>
empirical development. Most of the reviewed articles (42.0%) proposed a new TMF rather than using existing ones. Furthermore, we identified relatively few empirical studies (50.0%) that focused on the evaluation of KMb strategies. Consequently, the TMFs used were poorly consolidated, which does not provide a solid empirical foundation to guide the evaluation of KMb strategies. Also, not all the TMFs proposed in the articles were specifically developed for evaluation; some were focused on KMb implementation processes. These may still provide elements to consider for evaluation, although they were not designed to propose specific indicators.

A scoping review published in 2018 identified 596 studies using 159 different KMb TMFs, 95 of which had been used only once [11]. Many authors reported that these are rarely reused and validated [11, 30, 33] and that it is important to test, refine and integrate existing ones [3, 31, 34, 133]. A clear, collective and consistent use of existing TMFs is recommended and necessary to advance KMb science and closely related fields [12, 31]. The systematic review by Strifler et al. [11] highlights the diversity of available TMFs and the difficulty users may experience when choosing TMFs to guide their KMb initiatives or evaluation process. Future work should focus on the development of tools to better support users of TMFs, especially those working in organizations. By consolidating a large number of TMFs, the results of this scoping review contribute to these efforts.

## The importance of improving evaluation practices for complex multifaceted KMb strategies

Another noteworthy finding was the emphasis on the evaluation of strategies focused on education and professional training for practice improvement (52.3%). Relatively few of the reviewed articles looked at, for example, the evaluation of KMb strategies aimed at informing or influencing decision-making (13.6%), or KMb strategies targeting decision-makers (9.1%). These results reaffirm the importance of conducting more large-scale evaluations of complex and multifaceted KMb strategies. These involve a greater degree of interaction and engagement, are composed of networks of multiple actors, mobilize diverse sources of knowledge and have simultaneous multilevel objectives [19, 134].

The fact that some KMb strategies are complex interventions implemented in complex contexts [134] presents a significant and recurring challenge to their evaluation. Methodological designs, approaches and tools are often ill-suited to capture the short-, medium- and long-term outcomes of KMb strategies, as well as to identify the mechanisms by which these outcomes were produced in a specific context. It is also difficult to link concrete changes in practice and decision-making to tangible

longer-term impacts at the population level. Moreover, these impacts can take years to be achieved [36] and can be influenced by several other factors in addition to KMb efforts [2, 19, 24]. Comprehensive, dynamic and flexible evaluation approaches [135-137] using mixed methods [20] appear necessary to understand why, for whom, how, when and in what context KMb strategies achieve their objectives [2, 21, 25]. For instance, realist evaluation, which belongs to theory-based evaluation, may be an approach that addresses issues of causality without sacrificing complexity [134, 138, 139]. This evaluation approach aims to identify the underlying generative mechanisms that can explain how the outcomes were generated and what characteristics of the context affected, or not, those mechanisms. This approach is used to test and refine theory about how interventions with a similar logic of action actually work [139].

## Large heterogeneity of methodologies used in empirical studies

Despite the growth of the KMb field, a recurring issue is the relatively limited number of high-quality studies that evaluate KMb outcomes and impacts. This observation is shared by many of the authors of our scoping articles [2, 22-25]. Only a limited number of empirical articles met the selection criteria (n=44/88) in this scoping review. Synthesizing these studies is challenging due to the diversity of research designs used and the large number of potential evaluation components identified. In addition, most of the identified studies used TMFs and measurement tools that were not validated [20, 29] and that were specifically developed for their study [16, 25, 140]. Moreover, these studies did not describe the methods used to justify their choice of evaluation dimensions and components [25], which greatly hinders the ability to draw inferences and develop generalizable theories through replication in similar studies [110, 140-143]. The lack of a widely used evaluation approach across the field is therefore an important issue [16, 20] also highlighted by this scoping review.

Our aim in this review was not to identify specific indicators or measurement tools (for example, questionnaires) for assessing KMb strategies, but rather to describe dimensions and component of TMFs used for KMb evaluation. However, a recent scoping review [144] looked at measurement tools and revealed that only two general potential tools have been identified to assess KMb activities in any sector or organization: the *Level of Knowledge Use Survey* (LOKUS) [145] and the *Knowledge Uptake and Utilization Tool* (KUUT) [95]. The authors also assert the importance of developing standardized tools and evaluation processes to facilitate comparison of KMb activities' outcomes across organizations [144].
empirical development. Most of the reviewed articles (42.0%) proposed a new TMF rather than using existing ones. Furthermore, we identified relatively few empirical studies (50.0%) that focused on the evaluation of KMb strategies. Consequently, the TMFs used were poorly consolidated, which does not provide a solid empirical foundation to guide the evaluation of KMb strategies. Also, not all the TMFs proposed in the articles were specifically developed for evaluation; some were focused on KMb implementation processes. These may still provide elements to consider for evaluation, although they were not designed to propose specific indicators.

A scoping review published in 2018 identified 596 studies using 159 different KMb TMFs, 95 of which had been used only once [11]. Many authors reported that these are rarely reused and validated [11, 30, 33] and that it is important to test, refine and integrate existing ones [3, 31, 34, 133]. A clear, collective and consistent use of existing TMFs is recommended and necessary to advance KMb science and closely related fields [12, 31]. The systematic review by Strifler et al. [11] highlights the diversity of available TMFs and the difficulty users may experience when choosing TMFs to guide their KMb initiatives or evaluation process. Future work should focus on the development of tools to better support users of TMFs, especially those working in organizations. By consolidating a large number of TMFs, the results of this scoping review contribute to these efforts.

## The importance of improving evaluation practices for complex multifaceted KMb strategies

Another noteworthy finding was the emphasis on the evaluation of strategies focused on education and professional training for practice improvement (52.3%). Relatively few of the reviewed articles looked at, for example, the evaluation of KMb strategies aimed at informing or influencing decision-making (13.6%), or KMb strategies targeting decision-makers (9.1%). These results reaffirm the importance of conducting more large-scale evaluations of complex and multifaceted KMb strategies. These involve a greater degree of interaction and engagement, are composed of networks of multiple actors, mobilize diverse sources of knowledge and have simultaneous multilevel objectives [19, 134].

The fact that some KMb strategies are complex interventions implemented in complex contexts [134] presents a significant and recurring challenge to their evaluation. Methodological designs, approaches and tools are often ill-suited to capture the short-, medium- and long-term outcomes of KMb strategies, as well as to identify the mechanisms by which these outcomes were produced in a specific context. It is also difficult to link concrete changes in practice and decision-making to tangible

longer-term impacts at the population level. Moreover, these impacts can take years to be achieved [36] and can be influenced by several other factors in addition to KMb efforts [2, 19, 24]. Comprehensive, dynamic and flexible evaluation approaches [135-137] using mixed methods [20] appear necessary to understand why, for whom, how, when and in what context KMb strategies achieve their objectives [2, 21, 25]. For instance, realist evaluation, which belongs to theory-based evaluation, may be an approach that addresses issues of causality without sacrificing complexity [134, 138, 139]. This evaluation approach aims to identify the underlying generative mechanisms that can explain how the outcomes were generated and what characteristics of the context affected, or not, those mechanisms. This approach is used to test and refine theory about how interventions with a similar logic of action actually work [139].

## Large heterogeneity of methodologies used in empirical studies

Despite the growth of the KMb field, a recurring issue is the relatively limited number of high-quality studies that evaluate KMb outcomes and impacts. This observation is shared by many of the authors of our scoping articles [2, 22-25]. Only a limited number of empirical articles met the selection criteria (n=44/88) in this scoping review. Synthesizing these studies is challenging due to the diversity of research designs used and the large number of potential evaluation components identified. In addition, most of the identified studies used TMFs and measurement tools that were not validated [20, 29] and that were specifically developed for their study [16, 25, 140]. Moreover, these studies did not describe the methods used to justify their choice of evaluation dimensions and components [25], which greatly hinders the ability to draw inferences and develop generalizable theories through replication in similar studies [110, 140-143]. The lack of a widely used evaluation approach across the field is therefore an important issue [16, 20] also highlighted by this scoping review.

Our aim in this review was not to identify specific indicators or measurement tools (for example, questionnaires) for assessing KMb strategies, but rather to describe dimensions and component of TMFs used for KMb evaluation. However, a recent scoping review [144] looked at measurement tools and revealed that only two general potential tools have been identified to assess KMb activities in any sector or organization: the *Level of Knowledge Use Survey* (LOKUS) [145] and the *Knowledge Uptake and Utilization Tool* (KUUT) [95]. The authors also assert the importance of developing standardized tools and evaluation processes to facilitate comparison of KMb activities' outcomes across organizations [144].
## Lack of description and reporting of KMb strategies and evaluation

Another important finding from this review was the sparsity of descriptions of KMb strategies in the published articles. In general, the authors provided little information on the operationalization of their KMb strategies (for example, objectives, target audiences, details of activities implemented, implementation context, expected effects). The KMb strategy objectives and the implemented activities should be carefully selected and empirically, theoretically or pragmatically justified before the evaluation components and specific indicators can be determined [146].

To improve consistency in the field and to contribute to the development of KMb science, many authors reported the need to better describe and report KMb strategies and their context [8, 54, 146-150]. KMb strategies are often inconsistently labelled across studies, poorly described and rarely justified theoretically [146, 150, 151]. It was not possible in this scoping review to associate the evaluation components to be used with the objectives and types of KMb strategies, as too much information was missing in the articles. Over the past 10 years, several guidelines have been proposed to improve the reporting of interventions such as KMb strategies: the “Workgroup for Intervention Development and Evaluation Research (WIDER) recommendations checklist” [147], the “Standards for Reporting Implementation Studies (StaRI)” [150] and the “Template for Intervention Description and Replication (TIDieR)” [152]. These guidelines should be used more often to enhance the reporting of KMb strategies and help advance the field [153].

## Implications for future research

This scoping review provides an overview of potential factors of interest for assessing the context, process, effects and impacts of a KMb strategy. It also proposes a preliminary inventory of potential dimensions and components to consider when planning the evaluation of a KMb strategy. Given the broad spectrum of factors of interest identified across studies, not all of them can be assessed in every context. Rather, they should be targeted according to the objectives of the evaluation, the nature of the KMb strategy and the resources available to conduct the evaluation. Thus, this inventory should not be understood as a prescriptive, normative and exhaustive framework, but rather as a toolbox to identify the most relevant factors to include in the evaluation of a given KMB strategy, and to address a need often expressed by organizations wishing to evaluate their KMb efforts.

Additional work is needed to validate and operationalize these dimensions, to identify relevant measurement tools related to the different components and to see how

this inventory could support KMb evaluation practices in organizations.

This scoping review is the first stage of a larger research project aimed at improving organizations' capacity to evaluate their KMb initiatives by developing an integrative, interdisciplinary and easy-to-use reference framework. In the second phase of the project, the relevance and clarity of the evaluation dimensions identified in the scoping review will be validated through a Delphi study with KMb specialists and researchers. The enriched framework will then be pilot tested in two organizations carrying out and evaluating KMb strategies, to adapt the framework to their needs and to further clarify how the dimensions can be measured in practice. In this third phase, guidance will be provided to help organizations adopt the framework and its support kit. The aim of the project is to go beyond proposing a theoretical framework, and to help build organizations' capacity to evaluate KT strategies by proposing tools adapted to their realities.

## Review limitations

Some limitations of this scoping review should be acknowledged. First, given the numerous different terms used to describe and conceptualize the science of using evidence, it is possible that our search strategy did not capture all relevant publications. However, to limit this risk, we manually searched the reference lists of the selected articles. Second, the literature search was limited to articles published in English or French, and the articles were mostly from high-income countries (for example, North America); therefore, the application of the identified concepts in this scoping review to other contexts should be further explored.

In addition, the search strategy focused on scientific publications to assess progress made in the field of knowledge mobilization strategy evaluation. The grey literature was not examined. It should be considered in future research to complete the overview of evaluation needs in the field of knowledge mobilization.

Finally, the paucity of information in the articles sometimes made it difficult to classify the TMFs according to the taxonomies [32, 44], which may have led to possible misinterpretation. However, to limit the risk of errors, the categorization was performed by two reviewers and validated by a third in cases of uncertainty.

## Conclusions

Given the increasing demand from organizations for the evaluation of KMb strategies, along with the poorly consolidated KMb research field, a scoping review was needed to identify the range, nature and extent of the
## Lack of description and reporting of KMb strategies and evaluation

Another important finding from this review was the sparsity of descriptions of KMb strategies in the published articles. In general, the authors provided little information on the operationalization of their KMb strategies (for example, objectives, target audiences, details of activities implemented, implementation context, expected effects). The KMb strategy objectives and the implemented activities should be carefully selected and empirically, theoretically or pragmatically justified before the evaluation components and specific indicators can be determined [146].

To improve consistency in the field and to contribute to the development of KMb science, many authors reported the need to better describe and report KMb strategies and their context [8, 54, 146-150]. KMb strategies are often inconsistently labelled across studies, poorly described and rarely justified theoretically [146, 150, 151]. It was not possible in this scoping review to associate the evaluation components to be used with the objectives and types of KMb strategies, as too much information was missing in the articles. Over the past 10 years, several guidelines have been proposed to improve the reporting of interventions such as KMb strategies: the “Workgroup for Intervention Development and Evaluation Research (WIDER) recommendations checklist” [147], the “Standards for Reporting Implementation Studies (StaRI)” [150] and the “Template for Intervention Description and Replication (TIDieR)” [152]. These guidelines should be used more often to enhance the reporting of KMb strategies and help advance the field [153].

## Implications for future research

This scoping review provides an overview of potential factors of interest for assessing the context, process, effects and impacts of a KMb strategy. It also proposes a preliminary inventory of potential dimensions and components to consider when planning the evaluation of a KMb strategy. Given the broad spectrum of factors of interest identified across studies, not all of them can be assessed in every context. Rather, they should be targeted according to the objectives of the evaluation, the nature of the KMb strategy and the resources available to conduct the evaluation. Thus, this inventory should not be understood as a prescriptive, normative and exhaustive framework, but rather as a toolbox to identify the most relevant factors to include in the evaluation of a given KMb strategy, and to address a need often expressed by organizations wishing to evaluate their KMb efforts.

Additional work is needed to validate and operationalize these dimensions, to identify relevant measurement tools related to the different components and to see how

this inventory could support KMb evaluation practices in organizations.

This scoping review is the first stage of a larger research project aimed at improving organizations' capacity to evaluate their KMb initiatives by developing an integrative, interdisciplinary and easy-to-use reference framework. In the second phase of the project, the relevance and clarity of the evaluation dimensions identified in the scoping review will be validated through a Delphi study with KMb specialists and researchers. The enriched framework will then be pilot tested in two organizations carrying out and evaluating KMb strategies, to adapt the framework to their needs and to further clarify how the dimensions can be measured in practice. In this third phase, guidance will be provided to help organizations adopt the framework and its support kit. The aim of the project is to go beyond proposing a theoretical framework, and to help build organizations' capacity to evaluate KT strategies by proposing tools adapted to their realities.

## Review limitations

Some limitations of this scoping review should be acknowledged. First, given the numerous different terms used to describe and conceptualize the science of using evidence, it is possible that our search strategy did not capture all relevant publications. However, to limit this risk, we manually searched the reference lists of the selected articles. Second, the literature search was limited to articles published in English or French, and the articles were mostly from high-income countries (for example, North America); therefore, the application of the identified concepts in this scoping review to other contexts should be further explored.

In addition, the search strategy focused on scientific publications to assess progress made in the field of knowledge mobilization strategy evaluation. The grey literature was not examined. It should be considered in future research to complete the overview of evaluation needs in the field of knowledge mobilization.

Finally, the paucity of information in the articles sometimes made it difficult to classify the TMFs according to the taxonomies [32, 44], which may have led to possible misinterpretation. However, to limit the risk of errors, the categorization was performed by two reviewers and validated by a third in cases of uncertainty.

## Conclusions

Given the increasing demand from organizations for the evaluation of KMb strategies, along with the poorly consolidated KMb research field, a scoping review was needed to identify the range, nature and extent of the
literature. This scoping review enabled us to synthesize the breadth of the literature, provide an overview of the many theories, models and frameworks used, and identify and categorize the potential dimensions and components to consider when evaluating KMb initiatives. This scoping review is part of a larger research project, in which the next steps will be to validate the integrative framework and develop a support kit to facilitate its use by organizations involved in KMb.

**Abbreviations**

KMb Knowledge mobilization

TMFs Theories, models, and frameworks

**Supplementary Information**

The online version contains supplementary material available at https://doi.org/10.1186/s12961-023-01090-7.

Additional file 1. Keywords and search strategy.

Additional file 2. Summary of included articles.

**Acknowledgements**

We wish to thank Julie Desnoyers for designing and implementing the search strategy, Gabrielle Legendre for her contribution in the screening phase and Karine Souffez and Caroline Tessier for their input during the project.

**Author contributions**

SZ, MJG, EMC, JL, CD, EJ, KS, VR and CT were involved in developing and designing the scoping review. EMC, MJG and GL (collaborator) screened articles in duplicate. SL, DG, LIC and OP extracted data from the included articles. SL and DG synthesized the data. SL, SZ and EMC drafted the manuscript. SZ led the project, supervised and assisted the research team at every stage, and secured the funding. All authors provided substantive feedback and approved the manuscript prior to submission.

**Funding**

This project was supported by an Insight Grant from the Social Sciences and Humanities Research Council of Canada (SSHRC) and by the Équipe RENARD (FRQ-SC). The funding bodies had no role in the conduct of this scoping review.

**Availability of data and materials**

The dataset supporting the conclusions of this article is included within the article and its additional files.

**Declarations**

**Ethics approval and consent to participate**

Not applicable.

**Consent for publication**

Not applicable.

**Competing interests**

The authors declare that they have no competing interests.

**Author details**

Received: 16 June 2023 Accepted: 7 December 2023

Published online: 10 January 2024

**References**

1. Social Sciences and Humanities Research Council. Guidelines for Effective Knowledge Mobilization. 2019. https://www.sshrc-crsh.gc.ca/funding-financement/policies-politiques/knowledge_mobilisation-mobilisation_des_connaissances-eng.aspx Accessed 28 Dec 2022.

2. Boaz A, Davies H, Fraser A, Nutley S. What works now? evidence-informed policy and practice. Bristol: Policy press; 2019.

3. Curran JA, Grimshaw JM, Hayden JA, Campbell B. Knowledge translation research: the science of moving research into policy and practice. J Contin Educ Heal Prof. 2011;31(3):174–80.

4. Global Commission on Evidence. The Evidence Commission report: A wake-up call and path forward for decision-makers, evidence intermediaries, and impact-oriented evidence producers. McMaster University; 2022 p. 144. https://www.mcmasterforum.org/networks/evidence-commission/report/english

5. Morris ZS, Wooding S, Grant J. The answer is 17 years, what is the question: understanding time lags in translational research. J R Soc Med. 2011;104(12):510–20.

6. Orton L, Lloyd-Williams F, Taylor-Robinson D, O'Flaherty M, Capewell S. The use of research evidence in public health decision making processes: systematic review. PLoS ONE. 2011;6(7):e21704.

7. Straus SE, Tetroe J, Graham ID, editors. Knowledge translation in health care: moving from evidence to practice. 2nd ed. Chichester, West Sussex; Hoboken, NJ: Wiley/BMJ Books; 2013, 406

8. Barwick M, Dubrowski R, Petricca K. Knowledge translation: The rise of implementation. 2020; https://ktdrr.org/products/kt-implementation/KT-Implementation-508.pdf

9. Graham ID, Logan J, Harrison MB, Straus SE, Tetroe J, Caswell W, et al. Lost in knowledge translation: time for a map? J Continuing Educ Health Professions. 2006;26(1):13–24.

10. Grimshaw JM, Eccles MP, Lavis JN, Hill SJ, Squires JE. Knowledge translation of research findings. Implement Sci. 2012;7(1):50.

11. Strifler L, Cardoso R, McGowan J, Cogo E, Nincic V, Khan PA, et al. Scoping review identifies significant number of knowledge translation theories, models, and frameworks with limited use. J Clin Epidemiol. 2018;100:92–102.

12. Esmail R, Hanson HM, Holroyd-Leduc J, Brown S, Strifler L, Straus SE, et al. A scoping review of full-spectrum knowledge translation theories, models, and frameworks. Implement Sci. 2020;15(1):11.

13. McKibbon KA, Lokker C, Wilczynski NL, Ciliska D, Dobbins M, Davis DA, et al. A cross-sectional study of the number and frequency of terms used to refer to knowledge translation in a body of health literature in 2006: a Tower of Babel? Implement Sci. 2010;5(1):16.

14. Fonds de recherche du Québec. Stratégie de mobilisation des connaissances 2014–2017. 2014. https://frq.gouv.qc.ca/en/mobilization-of-knowledge/. Accessed 28 Dec 2022.

15. Gervais MJ, Souffez K, Ziam S. Quel impact avons-nous ? Vers l'élaboration d'un cadre pour rendre visibles les retombées du transfert des connaissances. TUC Revue francophone de recherche sur le transfert et l'utilisation des connaissances. 2016;1(2):21.

16. Williams NJ, Beidas RS. Annual research review: the state of implementation science in child psychology and psychiatry: a review and suggestions to advance the field. J Child Psychol Psychiatr. 2019;60(4):430–50.

17. Mitton C, Adair CE, Mckenzie E, Patten SB, Perry BW. Knowledge transfer and exchange: review and synthesis of the literature. Milbank Q. 2007;85(4):729–68.

<footnote n="1">¹School of Business Administration, Université TÉLUQ, Montreal, Canada.</footnote>

<footnote n="2">²Department of School and Social Adaptation Studies, Faculty of Education, Université de Sherbrooke, Sherbrooke, Canada. ³Department of Psychology, Université du Québec à Montréal, Montreal, Canada. ⁴Centre RBC d'expertise Universitaire en Santé Mentale, Université de Sherbrooke, Sherbrooke, Canada. ⁵School of Rehabilitation, Faculty of Medicine, Université de Montréal, Montreal, Canada. ⁶Department of Psychology, Université de Montréal, Montreal, Canada. ⁷Université Paris Cité, IRD (Institute for Research on Sustainable Development, CEPED, Paris, France). ⁸Institute of Health and Development (ISED), Cheikh Anta Diop University, Dakar, Senegal. ⁹Public Health Intelligence and Knowledge Translation Division, Public Health Agency of Canada, Ottawa, Canada. ¹⁰Coordinator of the Interregional Consortium of Knowledge in Health and Social Services (InterS4), Rimouski, Canada.</footnote>
literature. This scoping review enabled us to synthesize the breadth of the literature, provide an overview of the many theories, models and frameworks used, and identify and categorize the potential dimensions and components to consider when evaluating KMb initiatives. This scoping review is part of a larger research project, in which the next steps will be to validate the integrative framework and develop a support kit to facilitate its use by organizations involved in KMb.

### Abbreviations

KMb Knowledge mobilization

TMFs Theories, models, and frameworks

### Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s12961-023-01090-7.

**Additional file 1.** Keywords and search strategy.

**Additional file 2.** Summary of included articles.

### Acknowledgements

We wish to thank Julie Desnoyers for designing and implementing the search strategy, Gabrielle Legendre for her contribution in the screening phase and Karine Souffez and Caroline Tessier for their input during the project.

### Author contributions

SZ, MJG, EMC, JL, CD, EJ, KS, VR and CT were involved in developing and designing the scoping review. EMC, MJG and GL (collaborator) screened articles in duplicate. SL, DG, LJC and OP extracted data from the included articles. SL and DG synthesized the data. SL, SZ and EMC drafted the manuscript. SZ led the project, supervised and assisted the research team at every stage, and secured the funding. All authors provided substantive feedback and approved the manuscript prior to submission.

### Funding

This project was supported by an Insight Grant from the Social Sciences and Humanities Research Council of Canada (SSHRC) and by the Équipe RENARD (FRQ-SC). The funding bodies had no role in the conduct of this scoping review.

### Availability of data and materials

The dataset supporting the conclusions of this article is included within the article and its additional files.

### Declarations

#### Ethics approval and consent to participate

Not applicable.

#### Consent for publication

Not applicable.

#### Competing interests

The authors declare that they have no competing interests.

#### Author details

Received: 16 June 2023 Accepted: 7 December 2023

Published online: 10 January 2024

### References

1. Social Sciences and Humanities Research Council. Guidelines for Effective Knowledge Mobilization. 2019. https://www.sshrc-crsh.gc.ca/funding-financement/policies-politiques/knowledge_mobilisation-mobilisation_des_connaissances-eng.aspx Accessed 28 Dec 2022.

2. Boaz A, Davies H, Fraser A, Nutley S. What works now? evidence-informed policy and practice. Bristol: Policy press; 2019.

3. Curran JA, Grimshaw JM, Hayden JA, Campbell B. Knowledge translation research: the science of moving research into policy and practice. J Contin Educ Heal Prof. 2011;31(3):174-80.

4. Global Commission on Evidence. The Evidence Commission report: A wake-up call and path forward for decision-makers, evidence intermediaries, and impact-oriented evidence producers. McMaster University; 2022 p. 144. https://www.mcmasterforum.org/networks/evidence-commission/report/english

5. Morris ZS, Wooding S, Grant J. The answer is 17 years, what is the question: understanding time lags in translational research. J R Soc Med. 2011;104(12):510-20.

6. Orton L, Lloyd-Williams F, Taylor-Robinson D, O'Flaherty M, Capewell S. The use of research evidence in public health decision making processes: systematic review. PLoS ONE. 2011;6(7):e21704.

7. Straus SE, Tetroe J, Graham ID, editors. Knowledge translation in health care: moving from evidence to practice. 2nd ed. Chichester, West Sussex; Hoboken, NJ: Wiley/BMJ Books; 2013, 406

8. Barwick M, Dubrowski R, Petricca K. Knowledge translation: The rise of implementation. 2020; https://ktdrr.org/products/kt-implementation/KT-Implementation-508.pdf

9. Graham ID, Logan J, Harrison MB, Straus SE, Tetroe J, Caswell W, et al. Lost in knowledge translation: time for a map? J Continuing Educ Health Professions. 2006;26(1):13-24.

10. Grimshaw JM, Eccles MP, Lavis JN, Hill SJ, Squires JE. Knowledge translation of research findings. Implement Sci. 2012;7(1):50.

11. Strifler L, Cardoso R, McGowan J, Cogo E, Nincic V, Khan PA, et al. Scoping review identifies significant number of knowledge translation theories, models, and frameworks with limited use. J Clin Epidemiol. 2018;100:92-102.

12. Esmail R, Hanson HM, Holroyd-Leduc J, Brown S, Strifler L, Straus SE, et al. A scoping review of full-spectrum knowledge translation theories, models, and frameworks. Implement Sci. 2020;15(1):11.

13. McKibbon KA, Lokker C, Wilczynski NL, Ciliska D, Dobbins M, Davis DA, et al. A cross-sectional study of the number and frequency of terms used to refer to knowledge translation in a body of health literature in 2006: a Tower of Babel? Implement Sci. 2010;5(1):16.

14. Fonds de recherche du Québec. Stratégie de mobilisation des connaissances 2014-2017. 2014. https://frq.gouv.qc.ca/en/mobilization-of-knowledge/. Accessed 28 Dec 2022.

15. Gervais MJ, Souffez K, Ziam S. Quel impact avons-nous ? Vers l'élaboration d'un cadre pour rendre visibles les retombées du transfert des connaissances. TUC Revue francophone de recherche sur le transfert et l'utilisation des connaissances. 2016;1(2):21.

16. Williams NJ, Beidas RS. Annual research review: the state of implementation science in child psychology and psychiatry: a review and suggestions to advance the field. J Child Psychol Psychiatr. 2019;60(4):430-50.

17. Mitton C, Adair CE, Mckenzie E, Patten SB, Perry BW. Knowledge transfer and exchange: review and synthesis of the literature. Milbank Q. 2007;85(4):729-68.

<footnote n="1">¹School of Business Administration, Université TÉLUQ, Montreal, Canada.</footnote>

<footnote n="2">²Department of School and Social Adaptation Studies, Faculty of Education, Université de Sherbrooke, Sherbrooke, Canada. ³Department of Psychology, Université du Québec à Montréal, Montreal, Canada. ⁴Centre RBC d'expertise Universitaire en Santé Mentale, Université de Sherbrooke, Sherbrooke, Canada. ⁵School of Rehabilitation, Faculty of Medicine, Université de Montréal, Montreal, Canada. ⁶Department of Psychology, Université de Montréal, Montreal, Canada. ⁷Université Paris Cité, IRD (Institute for Research on Sustainable Development, CEPED, Paris, France). ⁸Institute of Health and Development (ISED), Cheikh Anta Diop University, Dakar, Senegal. ⁹Public Health Intelligence and Knowledge Translation Division, Public Health Agency of Canada, Ottawa, Canada. ¹⁰Coordinator of the Interregional Consortium of Knowledge in Health and Social Services (InterS4), Rimouski, Canada.</footnote>
18. Oliver K, Innvar S, Lorenc T, Woodman J, Thomas J. A systematic review of barriers to and facilitators of the use of evidence by policymakers. BMC Health Serv Res. 2014;14(1):2.

19. Fazey I, Bunse L, Msika J, Pinke M, Preedy K, Evely AC, et al. Evaluat-
ing knowledge exchange in interdisciplinary and multi-stakeholder
research. Glob Environ Chang. 2014;25:204–20.

20. Gervais MJ, Marion C, Dagenais C, Chiocchio F, Houlfort N. Dealing with the complexity of evaluating knowledge transfer strategies: guiding principles for developing valid instruments. Res Eval. 2016;25(1):62–9.

21. Reed MS, Bryce R, Machen R. Pathways to policy impact: a new approach for planning and evidencing research impact. Evid policy. 2018;14(3):431–58.

22. Kim C, Wilcher R, Petruney T, Krueger K, Wynne L, Zan T. A research utilisation framework for informing global health and development policies and programmes. Health Res Policy Sys. 2018;16(1):9.

23. Langer L, Tripney J, Gough D University of London, Social Science Research Unit, Evidence for Policy and Practice Information and Co-ordinating Centre. The science of using science: researching the use of research evidence in decision-making. 2016.

24. Rajić A, Young I, McEwen SA. Improving the utilization of research knowledge in agri-food public health: a mixed-method review of knowledge translation and transfer. Foodborne Pathog Dis. 2013;10(5):397–412.

25. Scarlett J, Forsberg BC, Biermann O, Kuchenmüller T, El-Khatib Z. Indica-
tors to evaluate organisational knowledge brokers: a scoping review.
Health Res Policy Syst. 2020;18(1):93.

26. Bornbaum CC, Kornas K, Peirson L, Rosella LC. Exploring the function and effectiveness of knowledge brokers as facilitators of knowledge translation in health-related settings: a systematic review and thematic analysis. Implement Sci. 2015;10(1):162.

27. Sarkies MN, Bowles KA, Skinner EH, Haas R, Lane H, Haines TP. The effectiveness of research implementation strategies for promoting evidence-informed policy and management decisions in healthcare: a systematic review. Implement Sci. 2017;12(1):132.

28. Scott SD, Albrecht L, O'Leary K, Ball GD, Hartling L, Hofmeyer A, et al. Systematic review of knowledge translation strategies in the allied health professions. Implement Sci. 2012;7(1):70.

29. Dagenais C, Malo M, Robert É, Ouimet M, Berthelette D, Ridde V. Knowledge transfer on complex social interventions in public health: a scoping study. PLoS ONE. 2013;8(12):e80233.

30. Davies HT, Powell AE, Nutley SM. Mobilising knowledge to improve UK health care: learning from other countries and other sectors – a multimethod mapping study. Health Serv Deliv Res. 2015;3(27):1–190.

31. Damschroder LJ. Clarity out of chaos: use of theory in implementation research. Psychiatry Res. 2020;283: 112461.

32. Nilsen P. Making sense of implementation theories, models and frame-
works. Implement Sci. 2015;10(1):53.

33. Ellen ME, Panisset U, Araujo de Carvalho I, Goodwin J, Beard J. A knowledge translation framework on ageing and health. Health Policy. 2017;121(3):282–91.

34. Wensing M, Bosch M, Grol R. Developing and selecting interventions for translating knowledge to action. CMAJ. 2010;182(2):E85-.

35. Bennet A, Bennet D, Fafard K, Fonda M, Lomond T, Messier L, et al. Knowledge mobilization in the social sciences and humanities: moving from research to action. Frost: MQI Press; 2007.

36. Phipps D, Cummins J, Pepler D, Craig W, Cardinal S. The Co-produced Pathway to Impact Describes Knowledge Mobilization Processes. JCES. 2016;9(1). https://jces.ua.edu/articles/258. Accessed 17 Nov 2022.

37. Birken SA, Rohweder CL, Powell BJ, Shea CM, Scott J, Leeman J, et al. T-CaST: an implementation theory comparison and selection tool. Implement Sci. 2018;13(1):143.

38. Munn Z, Peters MDJ, Stern C, Tufanaru C, McArthur A, Aromataris E. Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Med Res Methodol. 2018;18(1):143.

39. Arksey H, O'Malley L. Scoping studies: towards a methodological frame-
work. Int J Soc Res Methodol. 2005;8(1):19–32.

40. Tricco AC, Lillie E, Zarin W, O'Brien KK, Colquhoun H, Levac D, et al.
PRISMA extension for scoping reviews (PRISMA-ScR): checklist and
explanation. Ann Intern Med. 2018;169(7):467–73.

41. Moullin JC, Sabater-Hernandez D, Fernandez-Llimos F, Benrimo Sl. A systematic review of implementation frameworks of innovations in healthcare and resulting generic implementation framework. Health Res Policy Syst. 2015;13(101170481):16.

42. Pham MT, Rajić A, Greig JD, Sargeant JM, Papadopoulos A, McEwen SA. A scoping review of scoping reviews: advancing the approach and enhancing the consistency. Res Synthesis Methods. 2014;5(4):371–85.

43. Farkas M, Jette AM, Tennstedt S, Haley SM, Quinn V. Knowledge dis-
semination and utilization in gerontology: an organizing framework.
Gerontologist. 2003;43:47–56.

44. Powell BJ, Waltz TJ, Chinman MJ, Damschroder LJ, Smith JL, Matthieu MM, et al. A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project. Implement Sci. 2015;10(1):21.

45. Waltz TJ, Powell BJ, Matthieu MM, Damschroder LJ, Chinman MJ, Smith JL, et al. Use of concept mapping to characterize relationships among implementation strategies and assess their feasibility and importance: results from the Expert Recommendations for Implementing Change (ERIC) study. Implement Sci. 2015;10(1):109.

46. Smith JD, Li DH, Rafferty MR. The implementation research logic model: a method for planning, executing, reporting, and synthesizing imple-
mentation projects. Implement Sci. 2020;15(1):84.

47. Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. 1999;89(9):1322-7.

48. Kitson A, Harvey G, McCormack B. Enabling the implementation of evidence based practice: a conceptual framework. Qual Health Care. 1998;7:149–58.

49. Sketris IS, Carter N, Traynor RL, Watts D, Kelly K, following contributing members of the CNODES Knowledge Translation Team: Pierre Ernst JG Brenda Hemmelgarn, Colleen Metge, Michael Paterson, Robert Platt W and Gary Teare. Building a framework for the evaluation of knowledge translation for the Canadian Network for Observational Drug Effect Studies. Pharmacoepidemiol Drug Saf. 2020;29 Suppl 1(d0r, 9208369):8–25.

50. Thomas DR. A general inductive approach for analyzing qualitative evaluation data. Am J Eval. 2006;27(2):237-46.

51. Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50(2):179-211.

52. Moore DE, Green JS, Gallis HA. Achieving desired results and improved outcomes: integrating planning and assessment throughout learning activities. J Contin Educ Health Prof. 2009;29(1):1–15.

53. Tschida JE, Drahota A. Fidelity to the ACT SMART Toolkit: an instru-
mental case study of implementation strategy fidelity. Implement Sci
Commun. 2023;4(1):52.

54. Colquhoun H, Leeman J, Michie S, Lokker C, Bragge P, Hempel S, et al. Towards a common terminology: a simplified framework of interventions to promote and integrate evidence into health practices, systems, and policies. Implement Sci. 2014;9(1):781.

55. Bertone MP, Meessen B, Clarysse G, Hercot D, Kelley A, Kafando Y, et al. Assessing communities of practice in health policy: a conceptual framework as a first step towards empirical research. Health Res Policy Sys. 2013;11(1):39.

56. Gagliardi AR, Legare F, Brouwers MC, Webster F, Wiljer D, Badley E, et al. Protocol: developing a conceptual framework of patient mediated knowledge translation, systematic review using a realist approach. Implement Sci. 2011;6(101258411):25.

57. Sargeant J, Borduas F, Sales A, Klein D, Lynn B, Stenerson H. CPD and KT: models used and opportunities for synergy. J Contin Educ Heal Prof. 2011;31(3):167–73.

58. Stetler CB, Ritchie J, Rycroft-Malone J, Schultz A, Charns M. Improv-
ing quality of care through routine, successful implementation of
evidence-based practice at the bedside: an organizational case study
protocol using the Pettigrew and Whipp model of strategic change.
Implement Sci. 2007;2(101258411):3.

59. Kok MO, Schuit AJ. Contribution mapping: a method for mapping the contribution of research to enhance its impact. Health Res Policy Syst. 2012;10(101170481):21.

60. Dadich A. From bench to bedside: methods that help clinicians use evidence-based practice. Aust Psychol. 2010;45(3):197-211.
18. Oliver K, Innvar S, Lorenc T, Woodman J, Thomas J. A systematic review of barriers to and facilitators of the use of evidence by policymakers. BMC Health Serv Res. 2014;14(1):2.

19. Fazey I, Bunse L, Msika J, Pinke M, Preedy K, Evely AC, et al. Evaluat-
ing knowledge exchange in interdisciplinary and multi-stakeholder
research. Glob Environ Chang. 2014;25:204–20.

20. Gervais MJ, Marion C, Dagenais C, Chiocchio F, Houlfort N. Dealing with the complexity of evaluating knowledge transfer strategies: guiding principles for developing valid instruments. Res Eval. 2016;25(1):62–9.

21. Reed MS, Bryce R, Machen R. Pathways to policy impact: a new approach for planning and evidencing research impact. Evid policy. 2018;14(3):431–58.

22. Kim C, Wilcher R, Petruney T, Krueger K, Wynne L, Zan T. A research utilisation framework for informing global health and development policies and programmes. Health Res Policy Sys. 2018;16(1):9.

23. Langer L, Tripney J, Gough D University of London, Social Science Research Unit, Evidence for Policy and Practice Information and Co-ordinating Centre. The science of using science: researching the use of research evidence in decision-making. 2016.

24. Rajić A, Young I, McEwen SA. Improving the utilization of research knowledge in agri-food public health: a mixed-method review of knowledge translation and transfer. Foodborne Pathog Dis. 2013;10(5):397–412.

25. Scarlett J, Forsberg BC, Biermann O, Kuchenmüller T, El-Khatib Z. Indica-
tors to evaluate organisational knowledge brokers: a scoping review.
Health Res Policy Syst. 2020;18(1):93.

26. Bornbaum CC, Kornas K, Peirson L, Rosella LC. Exploring the function and effectiveness of knowledge brokers as facilitators of knowledge translation in health-related settings: a systematic review and thematic analysis. Implement Sci. 2015;10(1):162.

27. Sarkies MN, Bowles KA, Skinner EH, Haas R, Lane H, Haines TP. The effectiveness of research implementation strategies for promoting evidence-informed policy and management decisions in healthcare: a systematic review. Implement Sci. 2017;12(1):132.

28. Scott SD, Albrecht L, O'Leary K, Ball GD, Hartling L, Hofmeyer A, et al. Systematic review of knowledge translation strategies in the allied health professions. Implement Sci. 2012;7(1):70.

29. Dagenais C, Malo M, Robert É, Ouimet M, Berthelette D, Ridde V. Knowledge transfer on complex social interventions in public health: a scoping study. PLoS ONE. 2013;8(12):e80233.

30. Davies HT, Powell AE, Nutley SM. Mobilising knowledge to improve UK health care: learning from other countries and other sectors – a multimethod mapping study. Health Serv Deliv Res. 2015;3(27):1–190.

31. Damschroder LJ. Clarity out of chaos: use of theory in implementation research. Psychiatry Res. 2020;283: 112461.

32. Nilsen P. Making sense of implementation theories, models and frame-
works. Implement Sci. 2015;10(1):53.

33. Ellen ME, Panisset U, Araujo de Carvalho I, Goodwin J, Beard J. A knowledge translation framework on ageing and health. Health Policy. 2017;121(3):282–91.

34. Wensing M, Bosch M, Grol R. Developing and selecting interventions for translating knowledge to action. CMAJ. 2010;182(2):E85–8.

35. Bennet A, Bennet D, Fafard K, Fonda M, Lomond T, Messier L, et al. Knowledge mobilization in the social sciences and humanities: moving from research to action. Frost: MQI Press; 2007.

36. Phipps D, Cummins J, Pepler D, Craig W, Cardinal S. The Co-produced Pathway to Impact Describes Knowledge Mobilization Processes. JCES. 2016;9(1). https://jces.ua.edu/articles/258. Accessed 17 Nov 2022.

37. Birken SA, Rohweder CL, Powell BJ, Shea CM, Scott J, Leeman J, et al. T-CaST: an implementation theory comparison and selection tool. Implement Sci. 2018;13(1):143.

38. Munn Z, Peters MDJ, Stern C, Tufanaru C, McArthur A, Aromataris E. Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Med Res Methodol. 2018;18(1):143.

39. Arksey H, O'Malley L. Scoping studies: towards a methodological frame-
work. Int J Soc Res Methodol. 2005;8(1):19–32.

40. Tricco AC, Lillie E, Zarin W, O'Brien KK, Colquhoun H, Levac D, et al. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med. 2018;169(7):467–73.

41. Moullin JC, Sabater-Hernandez D, Fernandez-Llimos F, Benrimo Sl. A systematic review of implementation frameworks of innovations in healthcare and resulting generic implementation framework. Health Res Policy Syst. 2015;13(101170481):16.

42. Pham MT, Rajić A, Greig JD, Sargeant JM, Papadopoulos A, McEwen SA. A scoping review of scoping reviews: advancing the approach and enhancing the consistency. Res Synthesis Methods. 2014;5(4):371–85.

43. Farkas M, Jette AM, Tennstedt S, Haley SM, Quinn V. Knowledge dis-semination and utilization in gerontology: an organizing framework. Gerontologist. 2003;43:47–56.

44. Powell BJ, Waltz TJ, Chinman MJ, Damschroder LJ, Smith JL, Matthieu MM, et al. A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project. Implement Sci. 2015;10(1):21.

45. Waltz TJ, Powell BJ, Matthieu MM, Damschroder LJ, Chinman MJ, Smith JL, et al. Use of concept mapping to characterize relationships among implementation strategies and assess their feasibility and importance: results from the Expert Recommendations for Implementing Change (ERIC) study. Implement Sci. 2015;10(1):109.

46. Smith JD, Li DH, Rafferty MR. The implementation research logic model: a method for planning, executing, reporting, and synthesizing imple-
mentation projects. Implement Sci. 2020;15(1):84.

47. Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. 1999;89(9):1322–7.

48. Kitson A, Harvey G, McCormack B. Enabling the implementation of evidence based practice: a conceptual framework. Qual Health Care. 1998;7:149–58.

49. Sketris IS, Carter N, Traynor RL, Watts D, Kelly K, following contributing members of the CNODES Knowledge Translation Team: Pierre Ernst JG Brenda Hemmelgarn, Colleen Metge, Michael Paterson, Robert Platt W and Gary Teare. Building a framework for the evaluation of knowledge translation for the Canadian Network for Observational Drug Effect Studies. Pharmacoepidemiol Drug Saf. 2020;29 Suppl 1(d0r, 9208369):8–25.

50. Thomas DR. A general inductive approach for analyzing qualitative evaluation data. Am J Eval. 2006;27(2):237–46.

51. Ajzen I. The theory of planned behavior. Organ Behav Hum Decis Process. 1991;50(2):179–211.

52. Moore DE, Green JS, Gallis HA. Achieving desired results and improved outcomes: integrating planning and assessment throughout learning activities. J Contin Educ Health Prof. 2009;29(1):1–15.

53. Tschida JE, Drahota A. Fidelity to the ACT SMART Toolkit: an instru-
mental case study of implementation strategy fidelity. Implement Sci
Commun. 2023;4(1):52.

54. Colquhoun H, Leeman J, Michie S, Lokker C, Bragge P, Hempel S, et al. Towards a common terminology: a simplified framework of interven-
tions to promote and integrate evidence into health practices, systems,
and policies. Implement Sci. 2014;9(1):781.

55. Bertone MP, Meessen B, Clarysse G, Hercot D, Kelley A, Kafando Y, et al. Assessing communities of practice in health policy: a conceptual framework as a first step towards empirical research. Health Res Policy Sys. 2013;11(1):39.

56. Gagliardi AR, Legare F, Brouwers MC, Webster F, Wiljer D, Badley E, et al. Protocol: developing a conceptual framework of patient mediated knowledge translation, systematic review using a realist approach. Implement Sci. 2011;6(101258411):25.

57. Sargeant J, Borduas F, Sales A, Klein D, Lynn B, Stenerson H. CPD and KT: models used and opportunities for synergy. J Contin Educ Heal Prof. 2011;31(3):167–73.

58. Stetler CB, Ritchie J, Rycroft-Malone J, Schultz A, Charns M. Improv-
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59. Kok MO, Schuit AJ. Contribution mapping: a method for mapping the contribution of research to enhance its impact. Health Res Policy Syst. 2012;10(101170481):21.

60. Dadich A. From bench to bedside: methods that help clinicians use evidence-based practice. Aust Psychol. 2010;45(3):197–211.
61. Brown P, Bahri P. Engagement of patients and healthcare professionals in regulatory pharmacovigilance: establishing a conceptual and methodological framework. Eur J Clin Pharmacol. 2019;75(9):1181-92.

62. Dobbins M, Ciliska D, Cockerill R, Barnsley J, DiCenso A. A framework for the dissemination and utilization of research for health-care policy and practice. Worldviews Evid Based Nurs Presents Arch Online J Knowl Synthesis Nurs. 2002;9(1):149-60.

63. Gagliardi AR, Brouwers MC, Bhattacharyya OK. The guideline implementability research and application network (GIRAnet): an international collaborative to support knowledge exchange: study protocol. Implement Sci. 2012;7(101258411):26.

64. Brooks SP, Zimmermann GL, Lang M, Scott SD, Thomson D, Wilkes G, et al. A framework to guide storytelling as a knowledge translation intervention for health-promoting behaviour change. Implement sci commun. 2022;3(1):35.

65. Cullen L, Hanrahan K, Edmonds SW, Reisinger HS, Wagner M. Iowa implementation for sustainability framework. Implement Sci. 2022;17(1):1.

66. Labbé D, Mahmood A, Miller WC, Mortenson WB. Examining the impact of knowledge mobilization strategies to inform urban stakeholders on accessibility: a mixed-methods study. Int J Environ Res Public Health. 2020;17(5):1561.

67. Straus SE, Tetroe J, Graham ID, Zwarenstein M, Bhattacharyya O, Shepperd S. Monitoring use of knowledge and evaluating outcomes. Can Med Assoc J. 2010;182(2):E94-8.

68. Bennett S, Whitehead M, Eames S, Fleming J, Low S, Caldwell E. Building capacity for knowledge translation in occupational therapy: learning through participatory action research. BMC Med Educ. 2016;16(1):257.

69. Brown C, Rogers S. Measuring the effectiveness of knowledge creation as a means of facilitating evidence-informed practice in early years settings in one London Borough. Lond Rev Educ. 2014;12(3):245-60.

70. Talbott E, De Los RA, Kearns DM, Mancilla-Martinez J, Wang M. Evidence-based assessment in special education research: advancing the use of evidence in assessment tools and empirical processes. Except Child. 2023;89(4):467-87.

71. Rosella LC, Bornbaum C, Kornas K, Lebenbaum M, Peirson L, Francoo R, et al. Evaluating the process and outcomes of a knowledge translation approach to supporting use of the Diabetes Population Risk Tool (DPoRT) in public health practice. Canadian J Program Eval. 2018;33(1):21-48.

72. Couineau AL, Forbes D. Using predictive models of behavior change to promote evidence-based treatment for PTSD. Psychol Trauma Theory Res Pract Policy. 2011;3(3):266-75.

73. Dufault M. Testing a collaborative research utilization model to translate best practices in pain management. Worldviews Evid Based Nurs. 2004;1:526-32.

74. Beckett K, Farr M, Kothari A, Wye L, le May A. Embracing complexity and uncertainty to create impact: exploring the processes and transformative potential of co-produced research through development of a social impact model. Health Res Policy Syst. 2018;16(1):118.

75. Kramer DM, Wells RP, Carlan N, Aversa T, Bigelow PP, Dixon SM, et al. Did you have an impact? A theory-based method for planning and evaluating knowledge-transfer and exchange activities in occupational health and safety. Int J Occup Saf Ergon. 2013;19(1):41-62.

76. Duhamel F, Dupuis F, Turcotte A, Martinez AM, Goudreau J. Integrating the illness beliefs model in clinical practice: a family systems nursing knowledge utilization model. J FAM NURS. 2015;21(2):322-48.

77. Wimpenny P, Johnson N, Walter I, Wilkinson JE. Tracing and identifying the impact of evidence-use of a modified pipeline model. Worldviews Evid Based Nurs. 2008;5(1):3-12.

78. Ward V, Smith S, House A, Hamer S. Exploring knowledge exchange: a useful framework for practice and policy. Soc Sci Med. 2012;74(3):297-304.

79. Grooten L, Vrijhoef HJM, Alhambra-Borras T, Whitehouse D, Devroey D. The transfer of knowledge on integrated care among five European regions: a qualitative multi-method study. BMC Health Serv Res. 2020;20(1):11.

80. Stetler CB. Updating the Stetler Model of research utilization to facilitate evidence-based practice. Nurs Outlook. 2001;49(6):272-9.

81. Ward V. Why, whose, what and how? A framework for knowledge mobilisers. Evid Policy J Res Debate Pract. 2017;13(3):477-97.

82. Levin RF, Fineout-Overholt E, Melnyk BM, Barnes M, Vetter MJ. Fostering evidence-based practice to improve nurse and cost outcomes in a community health setting: a pilot test of the advancing research and clinical practice through close collaboration model. Nurs Adm Q. 2011;35(1):21-33.

83. Currie M, King G, Rosenbaum P, Law M, Kertoy M, Specht J. A model of impacts of research partnerships in health and social services. Eval Program Plann. 2005;28(4):400-12.

84. Richard L, Chiocchio F, Essiembre H, Tremblay MC, Lamy G, Champagne F, et al. Communities of practice as a professional and organizational development strategy in local public health organizations in Quebec, Canada: an evaluation model. Healthc Policy. 2014;9(3):26-39.

85. Rycroft-Malone J, Wilkinson J, Burton CR, Harvey G, McCormack B, Graham I, et al. Collaborative action around implementation in collaborations for leadership in applied health research and care: towards a programme theory. J Health Serv Res Policy. 2013;18(3 Suppl):13-26.

86. Gagliardi AR, Fraser N, Wright FC, Lemieux-Charles L, Davis D. Fostering knowledge exchange between researchers and decision-makers: exploring the effectiveness of a mixed-methods approach. Health Policy. 2008;86(1):53-63.

87. Paquette-Warren J, Harris SB, Naqshbandi Hayward M, Tompkins JW. Case study of evaluations that go beyond clinical outcomes to assess quality improvement diabetes programmes using the Diabetes Evaluation Framework for Innovative National Evaluations (DEFINE). J Eval Clin Pract. 2016;22(5):644-52.

88. Paquette-Warren J, Tyler M, Fournie M, Harris SB. The diabetes evaluation framework for innovative national evaluations (DEFINE): construct and content validation using a modified Delphi method. Can J diabetes. 2017;41(3):281-96.

89. Abbot ML, Lee KK, Rossiter MJ. Evaluating the effectiveness and functionality of professional learning communities in adult ESL Programs. TESL Canada J. 2018;35(2):1-25.

90. Ho K, Bloch R, Gondocz T, Laprise R, Perrier L, Ryan D, et al. Technology-enabled knowledge translation: frameworks to promote research and practice. J Contin Educ Heal Prof. 2004;24(2):90-9.

91. Yu X, Hu D, Li N, Xiao Y. Comprehensive evaluation on teachers' knowledge sharing behavior based on the improved TOPSIS method. Comput Intell Neurosci. 2022;2022(101279357):2563210.

92. Arora S, Kalishman SG, Thornton KA, Komaromy MS, Katzman JG, Struminger BB, et al. Project ECHO: a telementoring network model for continuing professional development. J Contin Educ Health Prof. 2017;37(4):239-44.

93. Smidt A, Balandin S, Sigafoos J, Reed VA. The Kirkpatrick model: a useful tool for evaluating training outcomes. J Intellect Dev Disabil. 2009;34(3):266-74.

94. Jeffs L, Sidani S, Rose D, Espin S, Smith O, Martin K, et al. Using theory and evidence to drive measurement of patient, nurse and organizational outcomes of professional nursing practice. Int J Nurs Pract. 2013;19(2):141-8.

95. Skinner K. Developing a tool to measure knowledge exchange outcomes. Can J Program Eval. 2007;22(1):49-75.

96. Lavis J, Ross S, McLeod C, Gildiner A. Measuring the impact of health research. J Health Serv Res Policy. 2003;8(3):165-70.

97. Boyko JA, Lavis JN, Abelson J, Dobbins M, Carter N. Deliberative dialogues as a mechanism for knowledge translation and exchange in health systems decision-making. Soc Sci Med. 2012;75(11):1938-45.

98. Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, et al. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health. 2011;38(2):65-76.

99. Gainforth HL, Latimer-Cheung AE, Athanasopoulos P, Martin Ginis KA. Examining the feasibility and effectiveness of a community-based organization implementing an event-based knowledge mobilization initiative to promote physical activity guidelines for people with spinal cord injury among support personnel. Health Promot Pract. 2015;16(1):55-62.

100. Glasgow RE, Harden SM, Gaglio B, Rabin B, Smith ML, Porter GC, et al. RE-AIM planning and evaluation framework: adapting to new science and practice with a 20-year review. Front Public Health. 2019. https://doi.org/10.3389/fpubh.2019.00064.
61. Brown P, Bahri P. Engagement of patients and healthcare professionals in regulatory pharmacovigilance: establishing a conceptual and methodological framework. Eur J Clin Pharmacol. 2019;75(9):1181-92.

62. Dobbins M, Ciliska D, Cockerill R, Barnsley J, DiCenso A. A framework for the dissemination and utilization of research for health-care policy and practice. Worldviews Evid Based Nurs Presents Arch Online J Knowl Synthesis Nurs. 2002;9(1):149-60.

63. Gagliardi AR, Brouwers MC, Bhattacharyya OK. The guideline implementability research and application network (GIRAnet): an international collaborative to support knowledge exchange: study protocol. Implement Sci. 2012;7(101258411):26.

64. Brooks SP, Zimmermann GL, Lang M, Scott SD, Thomson D, Wilkes G, et al. A framework to guide storytelling as a knowledge translation intervention for health-promoting behaviour change. Implement sci commun. 2022;3(1):35.

65. Cullen L, Hanrahan K, Edmonds SW, Reisinger HS, Wagner M. Iowa implementation for sustainability framework. Implement Sci. 2022;17(1):1.

66. Labbé D, Mahmood A, Miller WC, Mortenson WB. Examining the impact of knowledge mobilization strategies to inform urban stakeholders on accessibility: a mixed-methods study. Int J Environ Res Public Health. 2020;17(5):1561.

67. Straus SE, Tetroe J, Graham ID, Zwarenstein M, Bhattacharyya O, Shepperd S. Monitoring use of knowledge and evaluating outcomes. Can Med Assoc J. 2010;182(2):E94-8.

68. Bennett S, Whitehead M, Eames S, Fleming J, Low S, Caldwell E. Building capacity for knowledge translation in occupational therapy: learning through participatory action research. BMC Med Educ. 2016;16(1):257.

69. Brown C, Rogers S. Measuring the effectiveness of knowledge creation as a means of facilitating evidence-informed practice in early years settings in one London Borough. Lond Rev Educ. 2014;12(3):245-60.

70. Talbott E, De Los RA, Kearns DM, Mancilla-Martinez J, Wang M. Evidence-based assessment in special education research: advancing the use of evidence in assessment tools and empirical processes. Except Child. 2023;89(4):467-87.

71. Rosella LC, Bornbaum C, Kornas K, Lebenbaum M, Peirson L, Fransoo R, et al. Evaluating the process and outcomes of a knowledge translation approach to supporting use of the Diabetes Population Risk Tool (DPoRT) in public health practice. Canadian J Program Eval. 2018;33(1):21-48.

72. Couineau AL, Forbes D. Using predictive models of behavior change to promote evidence-based treatment for PTSD. Psychol Trauma Theory Res Pract Policy. 2011;3(3):266-75.

73. Dufault M. Testing a collaborative research utilization model to translate best practices in pain management. Worldviews Evid Based Nurs. 2004;1:526-32.

74. Beckett K, Farr M, Kothari A, Wye L, le May A. Embracing complexity and uncertainty to create impact: exploring the processes and transformative potential of co-produced research through development of a social impact model. Health Res Policy Syst. 2018;16(1):118.

75. Kramer DM, Wells RP, Carlan N, Aversa T, Bigelow PP, Dixon SM, et al. Did you have an impact? A theory-based method for planning and evaluating knowledge-transfer and exchange activities in occupational health and safety. Int J Occup Saf Ergon. 2013;19(1):41-62.

76. Duhamel F, Dupuis F, Turcotte A, Martinez AM, Goudreau J. Integrating the illness beliefs model in clinical practice: a family systems nursing knowledge utilization model. J FAM NURS. 2015;21(2):322-48.

77. Wimpenny P, Johnson N, Walter I, Wilkinson JE. Tracing and identifying the impact of evidence-use of a modified pipeline model. Worldviews Evid Based Nurs. 2008;5(1):3-12.

78. Ward V, Smith S, House A, Hamer S. Exploring knowledge exchange: a useful framework for practice and policy. Soc Sci Med. 2012;74(3):297-304.

79. Grooten L, Vrijhoef HJM, Alhambra-Borras T, Whitehouse D, Devroey D. The transfer of knowledge on integrated care among five European regions: a qualitative multi-method study. BMC Health Serv Res. 2020;20(1):11.

80. Stetler CB. Updating the Stetler Model of research utilization to facilitate evidence-based practice. Nurs Outlook. 2001;49(6):272-9.

81. Ward V. Why, whose, what and how? A framework for knowledge mobilisers. Evid Policy J Res Debate Pract. 2017;13(3):477-97.

82. Levin RF, Fineout-Overholt E, Melnyk BM, Barnes M, Vetter MJ. Fostering evidence-based practice to improve nurse and cost outcomes in a community health setting: a pilot test of the advancing research and clinical practice through close collaboration model. Nurs Adm Q. 2011;35(1):21-33.

83. Currie M, King G, Rosenbaum P, Law M, Kertoy M, Specht J. A model of impacts of research partnerships in health and social services. Eval Program Plann. 2005;28(4):400-12.

84. Richard L, Chiocchio F, Essiembre H, Tremblay MC, Lamy G, Champagne F, et al. Communities of practice as a professional and organizational development strategy in local public health organizations in Quebec, Canada: an evaluation model. Healthc Policy. 2014;9(3):26-39.

85. Rycroft-Malone J, Wilkinson J, Burton CR, Harvey G, McCormack B, Graham I, et al. Collaborative action around implementation in collaborations for leadership in applied health research and care: towards a programme theory. J Health Serv Res Policy. 2013;18(3 Suppl):13-26.

86. Gagliardi AR, Fraser N, Wright FC, Lemieux-Charles L, Davis D. Fostering knowledge exchange between researchers and decision-makers: exploring the effectiveness of a mixed-methods approach. Health Policy. 2008;86(1):53-63.

87. Paquette-Warren J, Harris SB, Naqshbandi Hayward M, Tompkins JW. Case study of evaluations that go beyond clinical outcomes to assess quality improvement diabetes programmes using the Diabetes Evaluation Framework for Innovative National Evaluations (DEFINE). J Eval Clin Pract. 2016;22(5):644-52.

88. Paquette-Warren J, Tyler M, Fournie M, Harris SB. The diabetes evaluation framework for innovative national evaluations (DEFINE): construct and content validation using a modified Delphi method. Can J diabetes. 2017;41(3):281-96.

89. Abbot ML, Lee KK, Rossiter MJ. Evaluating the effectiveness and functionality of professional learning communities in adult ESL Programs. TESL Canada J. 2018;35(2):1-25.

90. Ho K, Bloch R, Gondocz T, Laprise R, Perrier L, Ryan D, et al. Technology-enabled knowledge translation: frameworks to promote research and practice. J Contin Educ Heal Prof. 2004;24(2):90-9.

91. Yu X, Hu D, Li N, Xiao Y. Comprehensive evaluation on teachers' knowledge sharing behavior based on the improved TOPSIS method. Comput Intell Neurosci. 2022;2022(101279357):2563210.

92. Arora S, Kalishman SG, Thornton KA, Komaromy MS, Katzman JG, Struminger BB, et al. Project ECHO: a telementoring network model for continuing professional development. J Contin Educ Health Prof. 2017;37(4):239-44.

93. Smidt A, Balandin S, Sigafoos J, Reed VA. The Kirkpatrick model: a useful tool for evaluating training outcomes. J Intellect Dev Disabil. 2009;34(3):266-74.

94. Jeffs L, Sidani S, Rose D, Espin S, Smith O, Martin K, et al. Using theory and evidence to drive measurement of patient, nurse and organizational outcomes of professional nursing practice. Int J Nurs Pract. 2013;19(2):141-8.

95. Skinner K. Developing a tool to measure knowledge exchange outcomes. Can J Program Eval. 2007;22(1):49-75.

96. Lavis J, Ross S, McLeod C, Gildiner A. Measuring the impact of health research. J Health Serv Res Policy. 2003;8(3):165-70.

97. Boyko JA, Lavis JN, Abelson J, Dobbins M, Carter N. Deliberative dialogues as a mechanism for knowledge translation and exchange in health systems decision-making. Soc Sci Med. 2012;75(11):1938-45.

98. Proctor E, Silmere H, Raghavan R, Hovmand P, Aarons G, Bunger A, et al. Outcomes for implementation research: conceptual distinctions, measurement challenges, and research agenda. Adm Policy Ment Health. 2011;38(2):65-76.

99. Gainforth HL, Latimer-Cheung AE, Athanasopoulos P, Martin Ginis KA. Examining the feasibility and effectiveness of a community-based organization implementing an event-based knowledge mobilization initiative to promote physical activity guidelines for people with spinal cord injury among support personnel. Health Promot Pract. 2015;16(1):55-62.

100. Glasgow RE, Harden SM, Gaglio B, Rabin B, Smith ML, Porter GC, et al. RE-AIM planning and evaluation framework: adapting to new science and practice with a 20-year review. Front Public Health. 2019. https://doi.org/10.3389/fpubh.2019.00064.
101. Shelton RC, Chambers DA, Glasgow RE. An extension of RE-AIM to enhance sustainability: addressing dynamic context and promoting health equity over time. Front Public Health. 2020;8(101616579):134.

102. Bender BG, Simmons B, Konkoly N, Liu AH. The asthma toolkit boot-camp to improve rural primary care for pediatric asthma. J Allergy Clin Immunol Pract. 2021;9(8):3091-3097.e1.

103. de la Garza Iga FJ, Mejía Alvarez M, Cockcroft JD, Rabin J, Cordon A, Elias Rodas DM, et al. Using the project ECHO TM model to teach mental health topics in rural Guatemala: an implementation science-guided evaluation. Int J Soc Psychiatry. 2023;69(8):2031-41.

104. Alkin M, Taut S. Unbundling evaluation use. Stud Educ Eval. 2003;29(1):1-12.

105. Varallyay NI, Langlois EV, Tran N, Elias V, Reveiz L. Health system decision-makers at the helm of implementation research: development of a framework to evaluate the processes and effectiveness of embedded approaches. Health Res Policy Syst. 2020;18(1):64.

106. McCabe KE, Wallace A, Crosland A. A model for collaborative working to facilitate knowledge mobilisation in public health. Evid Policy. 2015;11(4):559-76.

107. Gonzales R, Handley MA, Ackerman S, O'Sullivan PS. A framework for training health professionals in implementation and dissemination science. Acad Med. 2012;87(3):271-8.

108. Edgar L, Herbert R, Lambert S, MacDonald JA, Dubois S, Latimer M. The joint venture model of knowledge utilization: a guide for change in nursing. Nurs Leadersh. 2006;9(2):41-55.

109. Stetler CB, Damschroder LJ, Helfrich CD, Hagedorn HJ. A Guide for applying a revised version of the PARIHS framework for implementation. Implement Sci. 2011;6(101258411):99.

110. Brennan SE, Cumpston M, Misso ML, McDonald S, Murphy MJ, Green SE. Design and formative evaluation of the policy liaison initiative: a long-term knowledge translation strategy to encourage and support the use of cochrane systematic reviews for informing. Evid Policy. 2016;12(1):25-52.

111. Hinchcliff R, Senserrick T, Travaglia J, Greenfield D, Ivers R. The enhanced knowledge translation and exchange framework for road safety: a brief report on its development and potential impacts. Inj Prev. 2017;23(2):114-7.

112. Ye J, Woods D, Bannon J, Bilaver L, Kricke G, McHugh M, et al. Identifying contextual factors and strategies for practice facilitation in primary care quality improvement using an informatics-driven model: framework development and mixed methods case study. JMIR Hum Factors. 2022;9(2):e32174.

113. Brangan J, Quinn S, Spirtos M. Impact of an evidence-based practice course on occupational therapist's confidence levels and goals. Occup Ther Health Care. 2015;29(1):27-38.

114. Bonetti D, Johnston M, Pitts NB, Deery C, Ricketts I, Tilley C, et al. Knowledge may not be the best target for strategies to influence evidence-based practice: using psychological models to understand RCT effects. Int J Behav Med. 2009;16(3):287-93.

115. Buckley LL, Goering P, Parikh SV, Butterill D, Foo EKH. Applying a "stages of change" model to enhance a traditional evaluation of a research transfer course. J Eval Clin Pract. 2003;9(4):385-90.

116. Boyko JA, Davis JN, Dobbins M, Souza ML. Reliability of a tool for measuring theory of planned behaviour constructs for use in evaluating research use in policymaking. Health Res Policy Syst. 2011;24(9):29.

117. Imani-Nasab MH, Yazdizadeh B, Salehi M, Seyedin H, Majdzadeh R. Validity and reliability of the Evidence Utilisation in Policymaking Measurement Tool (EUPMT). Health Res Policy Syst. 2017;15(1):66.

118. Dwan KM, McInnes P, Mazumdar S. Measuring the success of facilitated engagement between knowledge producers and users: a validated scale. Evid Policy. 2015;11(2):239-52.

119. Haynes A, Rowbotham S, Grunseit A, Bohn-Goldbaum E, Slaytor E, Wilson A, et al. Knowledge mobilisation in practice: an evaluation of the Australian Prevention Partnership Centre. Health Res Policy Sys. 2020;18(1):13.

120. Haines M, Brown B, Craig J, D'Este C, Elliott E, Klineberg E, et al. Determinants of successful clinical networks: the conceptual framework and study protocol. Implement Sci. 2012;7(101258411):16.

121. Ko LK, Jang SH, Friedman DB, Glanz K, Leeman J, Hannon PA, et al. An application of the science impact framework to the cancer prevention

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123. Pettman TL, Armstrong R, Waters E, Allender S, Love P, Gill T, et al. Evaluation of a knowledge translation and exchange platform to advance non-communicable disease prevention. Evid Policy. 2016;12(1):109-26.

124. Yearwood AC. Applying a logical theory of change for strengthening research uptake in policy: a case study of the Evidence Informed Decision Making Network of the Caribbean. Rev Panam Salud Publica. 2018;42: e91.

125. Thomson D, Brooks S, Nuspl M, Hartling L. Programme theory development and formative evaluation of a provincial knowledge translation unit. Health Res Policy Syst. 2019;17(1):40.

126. Garad R, Kozica-Olenski S, Teede HJ. Evaluation of a center of research excellence in polycystic ovary syndrome as a large-scale collaborative research translation initiative, including evaluating translation of guideline impact. Semin Reprod Med. 2018;36(1):42-9.

127. Reddy S, Wakerman J, Westhorp G, Herring S. Evaluating impact of clinical guidelines using a realist evaluation framework. J Eval Clin Pract. 2015;21(6):1114-20.

128. Van Eerd D, Moser C, Saunders R. A research impact model for work and health. Am J Ind Med. 2021;64(1):3-12.

129. Yip O, Huber E, Stenz S, Zullig LL, Zeller A, De Geest SM, et al. A contextual analysis and logic model for integrated care for frail older adults living at home: The INSPIRE Project. Int J Integr Care. 2021;21(2):9.

130. Guo R, Bain BA, Willer J. Application of a logic model to an evidence-based practice training program for speech-language pathologists and audiologists. J Allied Health. 2011;40(1):e23-8.

131. McDonald S, Turner T, Chamberlain C, Lumbiganon P, Thinkham-rop J, Festin MR, et al. Building capacity for evidence generation, synthesis and implementation to improve the care of mothers and babies in South East Asia: methods and design of the SEA-ORCHID Project using a logical framework approach. BMC Med Res Methodol. 2010;10(100968545):61.

132. 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.

133. Wensing M, Grol R. Knowledge translation in health: how implementation science could contribute more. BMC Med. 2019;17(1):88.

134. Kreindler SA. Advancing the evaluation of integrated knowledge translation. Health Res Policy Sys. 2018;16(1):104.

135. Best A, Holmes B. Systems thinking, knowledge and action: towards better models and methods. Evid Policy. 2010;6(2):145-59.

136. van Mil HGJ, Foegeding EA, Windhab EJ, Perrot N, van der Linden E. A complex system approach to address world challenges in food and agriculture. Trends Food Sci Technol. 2014;40(1):20-32.

137. Wehrens R. Beyond two communities – from research utilization and knowledge translation to co-production? Public Health. 2014;128(6):545-51.

138. Ridde V, Pérez D, Robert E. Using implementation science theories and frameworks in global health. BMJ Glob Health. 2020;5(4): e002269.

139. Salter KL, Kothari A. Using realist evaluation to open the black box of knowledge translation: a state-of-the-art review. Implement Sci. 2014;9(1):115.

140. Van Eerd D, Cole D, Keown K, Irvin E, Kramer D, Gibson B, et al. Report on knowledge transfer and exchange practices: A systematic review of the quality and types of instruments used to assess KTE implementation and impact. Toronto: Institute for Work & Health; 2011 p. 130. https://www.iwh.on.ca/sites/iwh/files/iwh/reports/iwh_sys review_kte evaluation tools_2011_rev.pdf

141. Dobbins M, Robeson P, Ciliska D, Hanna S, Cameron R, O'Mara L, et al. A description of a knowledge broker role implemented as part of a randomized controlled trial evaluating three knowledge translation strategies. Implement Sci. 2009;4(1):23.

142. Rychetnik L, Bauman A, Laws R, King L, Rissel C, Nutbeam D, et al. Translating research for evidence-based public health: key concepts and future directions. J Epidemiol Community Health. 2012;66(12):1187-92.
101. Shelton RC, Chambers DA, Glasgow RE. An extension of RE-AIM to enhance sustainability: addressing dynamic context and promoting health equity over time. Front Public Health. 2020;8(101616579):134.

102. Bender BG, Simmons B, Konkoly N, Liu AH. The asthma toolkit boot-camp to improve rural primary care for pediatric asthma. J Allergy Clin Immunol Pract. 2021;9(8):3091-3097.e1.

103. de la Garza Iga FJ, Mejía Alvarez M, Cockcroft JD, Rabin J, Cordon A, Elias Rodas DM, et al. Using the project ECHO TM model to teach mental health topics in rural Guatemala: an implementation science-guided evaluation. Int J Soc Psychiatry. 2023;69(8):2031-41.

104. Alkin M, Taut S. Unbundling evaluation use. Stud Educ Eval. 2003;29(1):1-12.

105. Varallyay NI, Langlois EV, Tran N, Elias V, Reveiz L. Health system decision-makers at the helm of implementation research: development of a framework to evaluate the processes and effectiveness of embedded approaches. Health Res Policy Syst. 2020;18(1):64.

106. McCabe KE, Wallace A, Crosland A. A model for collaborative working to facilitate knowledge mobilisation in public health. Evid Policy. 2015;11(4):559-76.

107. Gonzales R, Handley MA, Ackerman S, O'Sullivan PS. A framework for training health professionals in implementation and dissemination science. Acad Med. 2012;87(3):271-8.

108. Edgar L, Herbert R, Lambert S, MacDonald JA, Dubois S, Latimer M. The joint venture model of knowledge utilization: a guide for change in nursing. Nurs Leadersh. 2006;9(2):41-55.

109. Stetler CB, Damschroder LJ, Helfrich CD, Hagedorn HJ. A Guide for applying a revised version of the PARIHS framework for implementation. Implement Sci. 2011;6(101258411):99.

110. Brennan SE, Cumpston M, Misso ML, McDonald S, Murphy MJ, Green SE. Design and formative evaluation of the policy liaison initiative: a long-term knowledge translation strategy to encourage and support the use of cochrane systematic reviews for informing. Evid Policy. 2016;12(1):25-52.

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143. Weiner BJ, Lewis CC, Stanick C, Powell BJ, Dorsey CN, Clary AS, et al. Psychometric assessment of three newly developed implementation outcome measures. Implement Sci. 2017;12(1):108.

144. Bhawra J, Skinner K. Examination of tools associated with the evaluation of knowledge uptake and utilization: a scoping review. Eval Program Plann. 2020;83: 101875.

145. Lane JP, Stone VI, Nobrega A, Tomita M. Level Of Knowledge Use Survey (LOKUS): a validated instrument for tracking knowledge uptake and use. Stud Health Technol Inform. 2015;217:106–10.

146. Proctor EK, Powell BJ, McMillen JC. Implementation strategies: recommendations for specifying and reporting. Implement Sci. 2013;8(1):139.

147. Albrecht L, Archibald M, Arseneau D, Scott SD. Development of a checklist to assess the quality of reporting of knowledge translation interventions using the Workgroup for Intervention Development and Evaluation Research (WIDER) recommendations. Implement Sci. 2013;8(1):52.

148. Bragge P, Grimshaw JM, Lokker C, Colquhoun H, Albrecht L, Baron J, et al. AIMD - a validated, simplified framework of interventions to promote and integrate evidence into health practices, systems, and policies. BMC Med Res Methodol. 2017;17(1):38.

149. Kastner M, Makarski J, Hayden L, Lai Y, Chan J, Treister V, et al. Improving KT tools and products: development and evaluation of a framework for creating optimized, Knowledge-activated Tools (KaT). Implement Sci Commun. 2020;1(1):47.

150. Pinnock H, Barwick M, Carpenter CR, Eldridge S, Grandes G, Griffiths C.J, et al. Standards for Reporting Implementation Studies (StaRI) Statement. BMJ. 2017;6(356): i6795.

151. Lokker C, McKibbon KA, Colquhoun H, Hempel S. A scoping review of classification schemes of interventions to promote and integrate evidence into practice in healthcare. Implement Sci. 2015;10(1):27.

152. Hoffmann TC, Glasziou PP, Boutron I, Milne R, Perera R, Moher D, et al. Better reporting of interventions: template for intervention description and replication (TIDieR) checklist and guide. BMJ. 2014;3(348): g1687.

153. Wilson PM, Sales A, Wensing M, Aarons GA, Flottorp S, Glidewell L, et al. Enhancing the reporting of implementation research. Implement Sci. 2017;12(1):13.

**Publisher's Note**

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Ready to submit your research? Choose BMC and benefit from:

* fast, convenient online submission

* thorough peer review by experienced researchers in your field

* rapid publication on acceptance

* support for research data, including large and complex data types

* gold Open Access which fosters wider collaboration and increased citations

* maximum visibility for your research: over 100M website views per year

At BMC, research is always in progress.

Learn more biomedcentral.com/submissions

<figure><img src="image_6.png" /></figure>