Implementation science promotes clinical practice of guidelines: a scoping review

Abstract

Background

The standardized professional conduct of medical staff and the consistent delivery of healthcare services depend on the continuous dissemination and implementation of clinical practice guidelines. However, a notable gap exists between guidelines publication and their real-world application, highlighting the need for robust methodologies to support evidence translation. Implementation science (IS) facilitates the adoption and integration of evidence-based practices, interventions, and policies within real-world healthcare and public health contexts. This scoping review aims to clarify how IS is applied in guidelines implementation, identify study characteristics, and guide medical staff in translating guidelines recommendations into actionable clinical practices.

Methods

Six electronic databases, including PubMed, Embase, Cochrane Library, Web of Science, CINAHL, and Scopus, were searched from their inception to July 17, 2025. Studies were selected based on predefined eligibility criteria, and relevant data were extracted by two reviewers using a standardized form. Quantitative and qualitative analyses were performed to assess research scope, trends, and characteristics. The results are presented in tables, accompanied by relevant visualizations where appropriate.

Results

A total of 8, 929 studies were identified, of which 99 met the inclusion criteria and underwent data extraction and synthesis. A bar chart illustrates the temporal distribution of included studies by publication year. The most common study designs were qualitative (n = 32) and observational (n = 13). A word cloud highlights primary healthcare topics addressed, including chronic diseases healthcare, maternal and infant healthcare, nervous system disease healthcare, symptom management. Among the included studies, 66 were multi-center. Hospitals were the predominant practice setting (n = 27), followed by primary care (n = 19). Studies primarily focused on patients with specialized diseases (n = 56). The most frequent study objectives were understanding current status and investigating barriers and facilitators. Provider teams constituted the most commonly involved stakeholder group, followed by patients and families. Reporting of constituting organizations occurred in 56.6% of studies, while 78.8% reported guidelines references. Regarding implementation frameworks, 63 studies applied a single framework, 21 utilized multiple frameworks, and determinant frameworks—particularly the Consolidated Framework for Implementation Research (CFIR) and the Theoretical Domains Framework (TDF)—were the most widely applied.

Conclusion

Generally, using IS in guidelines has received considerable attention but remains unsatisfactory. There is a critical need for methodological standardization, high-quality guidelines selection and their detail disclosure, stronger collaboration among all relevant stakeholders in the application of IS in guidelines. Sustained and coordinated support can foster large-scale, high-quality, and scientifically rigorous guidelines implementation studies, thereby yielding superior implementation outcomes.

Trial registration

Open Science Frame (OSF: 10.17605/OSF.IO/Q9RWE).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-025-13317-0.

Contributions to the literature

• Delineating the characteristics and current state of the application of implementation scinece (IS) within clinical practice guidelines and classifying key features of IS research based on the attributes of the included studies, offering practical and actionable guidance for future research.

• Critically assessing the gaps in the application of IS to guidelines, exploring the underlying causes, and providing evidence-based recommendations to support improvements in the quality of guidelines implementation.

• Identifying the patterns in how IS is applied in guideline-related research and proposing innovative application strategies, intended to inform and inspire future guideline-related implementation studies.

Background

By translating complex scientific insights into clear, actionable recommendations, clinical practice guidelines (termed “guidelines” in this paper) not only standardize the professional conduct of healthcare professionals and improve the quality of medical services but also positively influence patient prognosis and recovery [1]. Adhering to high-quality guidelines could potentially prevent one-third of avoidable patient deaths and reduce healthcare costs by two-thirds [2], thereby reducing medical costs and fostering consistency in care [1]. Nonetheless, a considerable gap exists between the existence of guidelines and their actual clinical use and the translation of guideline-based evidence is delayed, with an average lag of up to 17 years from publication to application [3–7]. Currently, approximately 61% of clinical decisions align with guidelines recommendations [8], and a mere 14% of evidence translates into clinical practice, indicating a low implementation rate [9]. This shortfall can negatively affect patient care, leading to unnecessary healthcare resource use [10], missed treatment opportunities, preventable harms, and increased patient mortality and adverse events [2, 11]. Therefore, it is insufficient for guidelines to define “what constitutes optimal care” merely. Guidelines must also offer clear recommendations on “how to implement optimal care effectively,” a component known as “implementation advice”. This need aligns with a central objective of IS to ensure seamless integration and sustainable implementation of guidelines into clinical practice [12].

IS provides the methodology for adopting and integrating evidence-based practices, interventions, and policies into real-world healthcare and public health settings, thereby enabling the systematic updating of research findings and the translation of evidence into routine practice [13]. Central to IS are theories, models, and frameworks [14] (collectively termed “frameworks” in this paper [15]), which are used to guide and describe the implementation process, identify barriers and facilitators, develop implementation strategies, and evaluate their effectiveness. These practices support the advocacy for using frameworks to ensure seamless implementation of guidelines [4, 16, 17]. However, as an emerging discipline, IS faces limitations such as conceptual ambiguities, inconsistent terminology, an overabundance of frameworks with debatable application efficacy [18], and a lack of standardized formats for presenting implementation strategies. The application of such strategies in guidelines implementation remains unclearly defined.

Therefore, based on this background, we conducted a scoping review to assess the current status and effectiveness of IS in the translation of guidelines. Our aims were as follows:

1. To summarize the primary ways in which IS is applied to guidelines transformation, including key features of study design;

2. To describe the use of frameworks in the guidelines context and synthesize the methodological characteristics that correspond to their different application purposes;

3. To critically assess the impact of IS in facilitating the translation of guidelines into clinical practice.

Methods

Our scoping review was registered with the Open Science Frame (10.17605/OSF.IO/Q9RWE) and executed following the methodology proposed by Arksey and O’Malley [19]. The results were documented in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist [20], as detailed in Supplemental File 1.

Identification of the research questions

Our research questions were as follows:

1. How is IS applied to guidelines transformation, and what are the key features of its study design?

2. What are the key ways frameworks are applied in guidelines development, and how do their methodological features vary based on intended purposes?

3. What are the common patterns of IS application in guidelines development and adaptation?

Eligibility criteria

Studies were included if they met the following criteria: (1) the research topic addressed “implementation science” and “implementation research,” with primary studies utilizing “clinical practice guidelines” as the principal evidence base for conducting implementation research; (2) the study content adopted “implementation science” as the overarching conceptual and theoretical frameworks and/or incorporated IS frameworks to guide the development, dissemination, and implementation of guidelines; (3) the research was published in English.

Studies were excluded if they met the following criteria: (1) mentioned “implementation science” in keywords but only applied it conceptually without practical application throughout the implementation process, such as offering limited guidance on methodology [21]; (2) were set in non-medical settings, including but not limited to schools, childcare services, and occupational health; (3) focused on evaluating IS methodologies and validating the application efficacy of frameworks within specific contexts; (4) were duplicate publications, meeting abstracts, or secondary studies such as narrative reviews, systematic reviews, meta-analyses, protocols, or case reports; (5) descriptive studies such as editorials, debates, commentaries, special reports, or opinion-based papers.

Search strategy

To ensure comprehensive coverage of peer-reviewed literature on guidelines implementation, we searched six databases selected for their complementary scope and indexing features: PubMed, Embase, Cochrane Library, Web of Science, CINAHL, and Scopus. The search period spanned from database inception to July 17, 2025, enabling a retrospective assessment of IS application in guidelines translation. Relevant MeSH terms and keywords were employed, combined with the Boolean operators “AND” and “OR”. References lists of included studies were reviewed to identify relevant articles not captured in the initial database searches. Furthermore, grey literature such as theses or dissertations, conference papers, and ongoing research, was assessed. Supplementary searches were conducted via platforms such as Google, Google Scholar, Baidu Scholar, and journals including Implementation Science and Implementation Science Communications. An information specialist was engaged to collaborate with the research team. Reference lists of included and relevant studies were cross-checked. The specifics of the search strategies are detailed in Supplementary File 2.

Study selection

The EndNote Reference Library (version X20, Clarivate Analytics) was used to import the search results. After removing duplicates, two researchers (JZ and SCL) independently screened the titles and abstracts following the predefined eligibility criteria to identify relevant studies. Subsequently, they independently read the full texts of selected articles for further screening. Any disagreements were resolved through discussion with a third researcher (ZLC) to reach consensus.

Charting the data

Data extraction was performed independently by two reviewers (JZ and SCL) using a standardized Microsoft Office Excel spreadsheets. A pilot extraction on a subset of studies was conducted to refine the extraction tool. Divergent interpretations were discussed and resolved with a third researcher (ZLC).

The following information was extracted from each eligible study: (1) basic characteristics: published year, country, institution, published journal, study registration, report specification, protocol status, and funding sources; (2) methodological characteristics: study design, healthcare topic, setting, populations, study objectives, stakeholder [22], and result presentation; (3) guidelines characteristics: performance form, quantity, location mentioned in literature, constituting organizations, guidelines references; (4) IS application: IS definition, implementation phases, frameworks quantity, frameworks purpose [23], frequency of frameworks usage, framework categories [24]. Some of this information which required further clarification and definition has been elaborated and are detailed in Supplementary File 3.

Data synthesis

The results were synthesized using a narrative synthesis approach with an aggregative analysis technique. Descriptive statistics, including frequencies and percentages, were used to summarize the data. Visual aids, such as tables, figures, bar charts, and word clouds, were also used. Word clouds were generated using the online program WordArt (https://wordart.com/create) to visualize the synthesized healthcare topics.

Results

Included studies

The literature search yielded 8, 929 publications. After removing duplicates, 3, 456 studies remained. Following abstract screening, 447 publications were selected for full-text screening. Finally, 99 studies were included following a thorough screening process (Fig. 1). Among these, two publications originated from different phases of a guidelines implementation research [25, 26]. The details of all included studies are available in Supplementary File 4, references [25–123].

Fig. 1.

PRISMA 2020 flow diagram. Acronyms: CINAHL Cumulative Index to Nursing and Alied Health Literature, IS Implementation Science. The PRISMA 2020 statement: an updated guidelines for reporting systematic reviews. BMJ 2021;372:n71 10.1136/bmj.n71

Basic characteristics of included studies

The basic characteristics of included studies are provided in Table 1. A bar chart (Fig. 2) illustrates the distribution of the included studies by publication year. Most studies were from the United States of America (n = 38), followed by Australia (n = 21), Canada (n = 9), the United Kingdom (n = 9), and Sweden (n = 5). The first authors’ institutions were predominantly universities (n = 68). Other affiliations included hospitals (n = 18) and the United States Department of Veterans Affairs (VA) (n = 7), with a total of 83 institutions represented. The studies were published in 58 journals, most frequently in Implementation Science (n = 22). A total of 17 studies reported registration platforms, and 25 studies adhered to established reporting specifications. Eighteen studies reported on the status of their research protocols, among which 10 protocols were published. 69 studies received funding support solely from policy sources, 5 studies declared no funding, and 6 studies did not report any funding sources.

Table 1.

Basic characteristics of included studies

Basic characteristics items	n (%)	References
Country (top 5)
USA	38 (38.4)	[27–29, 31–33, 38, 41, 42, 49, 52, 53, 59, 61–63, 69, 73, 79, 80, 82, 84, 89, 91, 96, 97, 100, 101, 103, 106–108, 110, 111, 113, 115, 122, 123]
Australia	21 (21.2)	[36, 40, 50, 51, 54, 56, 57, 60, 66, 70, 74, 76, 83, 85, 86, 95, 102, 109, 117, 118, 121]
Canada	9 (9.1)	[25, 26, 35, 44, 58, 68, 94, 114, 120]
UK	9 (9.1)	[34, 37, 46, 47, 71, 75, 77, 90, 98]
Sweden	5 (5.1)	[45, 48, 55, 93, 105]
Institution
University	68 (68.7)	[25–27, 30, 34–37, 39–42, 45–49, 51–54, 56–58, 60–62, 65, 67, 69, 72–77, 82–86, 88–90, 92–94, 96, 98–105, 111–114, 116–123]
Hospital	18 (18.2)	[33, 38, 43, 44, 64, 66, 71, 78, 80, 81, 87, 91, 95, 97, 107, 108, 110, 115]
VA	7 (7.1)	[28, 29, 31, 32, 59, 63, 79]
Company	2 (2.0)	[50, 106]
Public health	2 (2.0)	[68, 109]
Elderly care institutions	1 (1.0)	[70]
Primary healthcare	1 (1.0)	[55]
Published journal (top 5)
Implementation Science	22 (22.2)	[27–38, 40, 43, 45, 46, 49, 52, 53, 56, 59, 98]
Implementation Science Communications	6 (6.1)	[79, 80, 82, 100, 102, 105]
Nutrition & Dietetics	5 (5.1)	[51, 54, 60, 86, 95]
BMC Health Services Research	4 (4.0)	[44, 47, 62, 81]
BMJ Open	4 (4.0)	[66, 75, 85, 107]
Study registration
NR	82 (82.8)	[25–33, 35, 36, 38–42, 44, 47, 48, 50–52, 54, 55, 57, 59–62, 64, 65, 67–75, 77–79, 81–84, 86–90, 92–96, 98–115, 117–123]
ClinicalTrials.gov	8 (8.1)	[43, 49, 53, 58, 63, 80, 91, 97]
ANZCTR	4 (4.0)	[56, 66, 76, 85]
ISRCTN	4 (4.0)	[34, 37, 46,45]
OSF	1 (1.0)	[116]
Report specification
NR	74 (74.7)	[25–45, 48–50, 52–55, 59–63, 66–75, 77, 81–85, 87–89, 91–93, 95, 96, 98, 100, 101, 103–106, 108, 110, 112–114, 116, 119, 121–123]
COREQ	10 (10.1)	[57, 65, 78, 80, 86, 94, 107, 111, 117, 118]
CONSORT	5 ((5.1)	[46, 56, 58, 76, 97]
StaRI	4 (4.0)	[51, 64, 99, 109]
SRQR	3 (3.0)	[79, 102, 120]
SQUIRE	2 (2.0)	[47, 115]
STROBE	1 (1.0)	[90]
Protocol status
NR	81(81.8)	[25–41, 44, 45, 47–52, 54, 55, 57, 59–67, 70–75, 77–85, 88, 90, 92–95, 98–101, 103–107, 110–122,123]
Published	10 (10.1)	[42, 43, 46, 56, 58, 68, 76, 91, 97, 109]
Only mentioned	8 (8.1)	[53, 69, 86, 87, 89, 96, 102, 108]
Funding sources
Policy fund	69 (69.7)	[25–33, 35–38, 40–42, 45–49, 51–54, 56–59, 62–66, 68, 69, 73–75, 78–82, 85, 86, 89, 90, 92–94, 96, 97, 100, 101, 103–105, 107, 109, 111, 113–115, 117–119, 121, 123]
Policy and plant fund	9 (9.1)	[34, 39, 43, 55, 72, 76, 77, 110, 112]
NR	6 (6.1)	[61, 67, 71, 87, 95, 116]
Reporting no	5 (5.1)	[44, 50, 60, 91, 98]
Plant fund	5 (5.1)	[88, 99, 106, 108, 122]
Policy and/or plant and/or personal fund	5 (5.1)	[70, 83, 84, 102, 120]

USA the United State of America, UK the United Kingdom, VA the United States Department of Veterans Affairs, NR not reported, ANZCTR Australian New Zealand Clinical Trials Registry, ISRCTN International Standard Randomized Controlled Trial Registry, OSF Open Science Frame, COREQ Consolidated Criteria for Reporting Qualitative Research, CONSORT Consolidated Standards of Reporting Trials, StaRI Standards for Reporting Implementation Studies, SRQR Standards for Reporting Qualitative Research, SQUIRE Standards for Quality Improvement Reporting Excellence, STROBE Strengthening the Reporting of Observational Studies in Epidemiology

Fig. 2.

The number of studies related to the application of IS in guidelines translation, by year

Methodological characteristics of included studies

The methodological characteristics of included studies are presented in Table 2. The top five study designs were qualitative study (n = 32), observational study (n = 13), mixed methods study (n = 9), cluster randomized controlled trial (n = 8), and pre–post study (n = 3). The distribution of healthcare topics was visualized in the word cloud (Fig. 3), highlighting areas such as chronic diseases healthcare, maternal and infant healthcare, nervous system disease healthcare, symptom management. Collectively, there were 66 multi-center studies, with one study involving 123 centers. Hospitals (n = 27) were the most common practice settings, followed by primary care (n = 19), acute care settings (n = 12), and national/local-level settings (n = 11). Additionally, 56.6% of the studies focused on patients with specialized diseases. There were 80 researches report covering more than one objective, 27 studies aimed to understanding status and investigating and analyzing barriers and facilitators, and provider teams were the most involved stakeholders, followed by patients and families. Among them, 13 studies also tried to understand and analyze the views and attitudes of stakeholders. Besides, 51 studies presented their results in words, tables, and figures.

Table 2.

Methodological characteristics of included studies

Methodological characteristics items	n (%)	References
Study design
Qualitative study	32 (32.3)	[30, 33, 36, 37, 40, 42, 47–49, 57, 59, 62, 65, 72, 74, 78, 80, 85, 87, 91, 93, 94, 102, 107, 111, 114, 117–120, 122, 123]
Observational study	13 (13.1)	[27, 29, 44, 50, 83, 89, 90, 96, 103, 106, 108, 110, 116]
Mixed methods study	9 (9.1)	[35, 38, 51, 52, 69, 79, 86, 88, 112]
Cluster randomized controlled trial	8 (8.1)	[34, 43, 45, 46, 56, 58, 76, 97]
Pre-post study	3 (3.0)	[54, 64, 104]
Interrupted time series analysis	1 (1.0)	[98]
Study with unclear reporting	13 (13.1)	[25, 26, 31, 32, 41, 60, 61, 67, 70, 71, 84, 92, 95]
Unclassified study	20 (20.2)	[28, 39, 53, 55, 63, 66, 68, 73, 75, 77, 81, 82, 99–101, 105, 109, 113, 115, 121]
Healthcare topic
Chronic diseases healthcare	13 (13.1)	[27, 30, 40, 42, 81, 82, 84, 91, 96, 113, 119, 122, 123]
Maternal and infant healthcare	11 (11.1)	[45, 50, 67, 72, 73, 75, 88, 99, 105, 118, 121]
Nervous system disease healthcare	10 (10.1)	[31, 36, 37, 56, 62, 63, 65, 66, 70, 83]
Symptom management	9 (9.1)	[58, 61, 69, 76, 78, 104, 109, 115, 120]
Psychology and mental healthcare	7 (7.1)	[28, 43, 44, 93, 97, 101, 110]
Substance abuse	7 (7.1)	[32, 49, 53, 68, 90, 98, 107]
Cancer management	6 (6.1)	[35, 77, 85, 102, 114, 116]
Lifestyle and behavior change	4 (4.0)	[46, 54, 64, 95]
Perioperative management	4 (4.0)	[34, 51, 57, 106]
Hospital infection management	3 (3.0)	[38, 59, 79]
Infectious disease management	3 (3.0)	[33, 52, 80]
Multidisciplinary treatment	3 (3.0)	[29, 41, 47]
Nursing adverse events	3 (3.0)	[39, 92, 94]
Female healthcare	2 (2.0)	[86, 87]
Orthopedics healthcare	2 (2.0)	[55, 71]
Others	12 (12.1)	[25, 26, 48, 60, 74, 89, 100, 103, 108, 111, 112, 117]
Setting
Hospitals	27 (27.3)	[34, 37, 45, 50, 51, 54, 57, 64–66, 69, 71, 72, 75, 77, 87, 104, 106–109, 113–115, 118, 119, 122]
Primary care	19 (19.2)	[41–43, 46, 49, 52, 53, 55, 68, 74, 91, 92, 99, 101, 102, 112, 120, 121, 123]
Acute care setting	12 (12.1)	[33, 39, 47, 48, 56, 62, 76, 78, 81, 94, 103, 111]
National/Local level setting	11 (11.1)	[35, 36, 58, 83–86, 90, 95, 98, 105]
VA	8 (8.1)	[27–29, 31, 38, 59, 63, 79]
Specialized disease centers/units	7 (7.1)	[44, 60, 61, 93, 96, 110, 117]
Unclear	6 (6.1)	[25, 26, 30, 32, 67, 70]
Health system	4 (4.0)	[80, 82, 88, 89]
Health/Medical centers	4 (4.0)	[40, 73, 97, 100]
Hospitals and home care service	1 (1.0)	[116]
Populations
Patients with specialized disease	56 (56.6)	[25–32, 34–42, 44, 47, 48, 54, 55, 58, 60–63, 66, 68–71, 74, 76–79, 82, 83, 89, 96, 98, 100–102, 104, 106, 109–111, 113, 114, 116, 119, 122, 123]
Public health	12 (12.1)	[33, 46, 49, 52, 53, 80, 84, 85, 91, 93, 99, 112]
Pregnant/breastfeed women	10 (10.1)	[50, 67, 72, 73, 75, 88, 90, 105, 118, 121]
Older adults with disease	7 (7.1)	[43, 51, 57, 92, 103, 107, 117]
Infants/children/adolescent with disease	5 (5.1)	[45, 64, 81, 108, 115]
Adult with disease	4 (4.0)	[56, 94, 95, 120]
Women with disease	3 (3.0)	[86, 87, 97]
Medical staffs	2 (2.0)	[59, 65]
Study objectives (top 5)
②⑦	14 (14.1)	[35, 48, 57, 62, 65, 73, 74, 83–85, 87, 94, 102, 111]
①②⑦	13 (13.1)	[36, 38, 40, 42, 59, 69, 75, 77, 78, 80, 90, 93, 96]
④⑤	10 (10.1)	[53, 56, 58, 63, 66, 76, 97, 108, 109, 115]
②	7 (7.1)	[91, 112, 114, 116–118, 123]
⑤	7 (7.1)	[29, 39, 82, 88, 89, 100, 105]
Study objectives quantity
1	19(19.2)	[27, 29, 32, 39, 41, 72, 82, 88, 89, 91, 98, 100, 105, 112, 114, 116–118, 123]
2	40 (40.4)	[35, 47–50, 53, 56–58, 61–63, 65–67, 73, 74, 76, 79, 83–87, 94, 95, 97, 101, 102, 106, 108–111, 113, 115, 119–122]
3	24 (24.2)	[28, 30, 34, 36–38, 40, 42, 55, 59, 60, 69, 70, 75, 77, 78, 80, 90, 93, 96, 99, 103, 104, 107]
4	10 (10.1)	[25, 26, 33, 43, 44, 51, 52, 64, 68, 92]
5	5 (5.1)	[31, 45, 46, 54, 71]
6	1 (1.0)	[81]
Stakeholder categories (top 5)
IV	47 (47.5)	[25, 26, 30, 31, 33, 36–39, 41, 42, 45–47, 50, 53, 57, 59, 62, 64, 74, 77–79, 81, 83–85, 87, 90–96, 103, 107, 110, 111, 113, 114, 116, 118–120, 122]
IV, V	17(17.2)	[32, 51, 54, 55, 58, 60, 61, 65, 66, 75, 76, 100, 101, 104, 117, 121, 123]
III, IV	9 (9.1)	[29, 35, 40, 49, 69, 70, 73, 99, 112]
V	8 (8.1)	[34, 56, 86, 88, 89, 97, 108, 115]
III, IV, V	6 (6.1)	[28, 43, 52, 72, 80, 102]
Stakeholder quantity
1	55 (55.6)	[25, 26, 30, 31, 33, 34, 36–39, 41, 42, 45–47, 50, 53, 56, 57, 59, 62, 64, 74, 77–79, 81, 83–97, 103, 107, 108, 110, 111, 113–116, 118–120, 122]
2	28 (28.3)	[29, 32, 35, 40, 49, 51, 54, 55, 58, 60, 61, 65, 66, 69, 70, 73, 75, 76, 99–101, 104, 106, 109, 112, 117, 121, 123]
3	9 (9.1)	[27, 28, 43, 48, 52, 63, 72, 80, 102]
4	3 (3.0)	[71, 82, 105]
5	1 (1.0)	[68]
Unclear	3 (3.0)	[44, 67, 98]
Result presentation
Words, tables, and figures	51(51.5)	[25, 27, 29, 34, 39, 43, 44, 50, 53–58, 60, 61, 63, 66–68, 70, 73, 75–77, 79, 84, 87–89, 92, 95, 97, 98, 100–103, 108–111, 113–121]
Words and tables	45 (45.5)	[26, 28, 30–33, 35, 37, 38, 40, 42, 45–49, 51, 52, 59, 62, 64, 65, 69, 72, 74, 78, 80–83, 85, 86, 90, 91, 93, 94, 96, 99, 104–107, 112–123]
Words and figures	3 (3.0)	[36, 41, 71]

VA the United States Department of Veterans Affairs, ①understanding status, ②investigating and analyzing barriers and facilitators; ③developing and formulating implementation strategies, ④applying implementation strategies and methods, ⑤evaluating the effects of implementation, ⑥describing process of translating guidelines, ⑦understanding and analyzing the views and attitudes of stakeholders, I policy and economic environments, II organizations, III management teams, IV provider teams, V individual patients. Studies with unclear reporting were the type of study design is not explicitly stated. Unclassified studies where the type of study design were explicitly stated but does not fit into the above categories

Fig. 3.

Word clouds were generated using the online program wordart to visualize the synthesis healthcare topics (https://wordart.com/create). Different colors represent different healthcare topics, and a larger font size indicates that health topics are discussed more frequently

Characteristics of guidelines translated into clinical practice

The characteristics of guidelines translated into clinical practice are detailed in Table 3. The most common form of guidelines performance is to use a complete guideline (n = 44), followed by common recommendations of several guidelines (n = 22). 35 studies reported detail of guidelines in background and methods in literature. 28 studies mentioned guidelines were application in their but lack of guidelines information. 56.6% studies reported constituting organizations, and 78.8% reported guidelines references.

Table 3.

Characteristics of guidelines translated into clinical practice

Guidelines characteristics items	n (%)	References
Guidelines performance form
A complete guideline	44 (44.4)	[25–28, 32, 38–40, 42, 44, 45, 50, 51, 53, 67, 69–76, 78, 80–82, 85, 86, 88–90, 93, 95, 96, 99, 105, 110–114, 117, 119, 123]
Common recommendations of several guideline	22 (22.2)	[37, 41, 43, 55, 56, 59–61, 77, 79, 84, 94, 100, 101, 104, 106, 108, 109, 111, 116, 120, 121]
Recommendations of a guideline	16 (16.2)	[33, 34, 36, 46, 57, 58, 64, 66, 97, 98, 102, 103, 107, 115, 118, 122]
Several guidelines	13 (13.1)	[29, 31, 35, 48, 52, 54, 62, 65, 68, 83, 87, 91, 92]
Lack of implementation details	4 (4.1)	[30, 47, 49, 63]
Guidelines quantity
1	62 (62.6)	[25–28, 32–34, 36, 38–40, 42, 44–46, 50, 51, 53, 57, 58, 64, 66–76, 78, 80–82, 85, 86, 88–90, 92, 93, 95–99, 102, 103, 105, 107, 110, 112–115, 117–119, 122, 123]
2	7 (7.1)	[35, 37, 48, 54, 77, 101, 121]
3	9 (9.1)	[29, 55, 59, 61, 65, 79, 84, 94, 106]
4	6 (6.1)	[31, 41, 91, 108, 109, 111]
≥ 5	3 (3.0)	[43, 60, 87]
NR	12 (12.1)	[30, 47, 49, 52, 56, 62, 63, 83, 100, 104, 116, 120]
Location mentioned in literature
Background and methods	35 (35.4)	[29, 32, 35, 36, 38–40, 42, 46, 48, 53, 54, 60, 68–70, 72, 78, 82, 85, 86, 90, 92, 93, 95, 96, 98, 99, 108, 110, 112, 113, 117, 118, 123]
Background but unclear in methods	28 (28.3)	[30, 31, 33, 34, 37, 43, 51, 56, 58, 59, 61, 66, 73–75, 77, 79, 91, 94, 102, 103, 106, 107, 109, 111, 116, 121, 122]
Methods	18 (18.2)	[27, 28, 41, 45, 50, 55, 57, 64, 67, 71, 76, 80, 81, 88, 89, 97, 101, 105]
NR	9 (9.1)	[47, 49, 52, 62, 63, 83, 100, 104, 120]
Results	5 (5.1)	[25, 26, 44, 65, 87]
Background and results	4 (4.0)	[84, 114, 115, 119]
Reported constituting organizations or not
Y	56 (56.6)	[25–29, 31–33, 35, 36, 38–42, 44–46, 48, 59, 64, 65, 67, 69, 71–79, 81, 84–92, 95, 98, 101, 106, 108, 110, 112, 113, 115, 117–119, 123]
NR	43 (43.4)	[30, 34, 37, 43, 47, 49–58, 60, 63, 66–68, 70, 80, 82, 83, 93, 94, 96, 97, 99, 100, 102, 105, 107, 109, 111, 114, 116, 120–122]
Reported guidelines references or not
Y	78 (78.8)	[25, 26, 29, 31–42, 44, 46, 48, 50, 53, 54, 57–61, 64–70, 72–79, 81, 82, 84–86, 88–99, 101–103, 105–119, 121–123]
NR	21 (21.2)	[27, 28, 30, 43, 45, 47, 49, 51, 52, 55, 56, 62, 63, 71, 80, 83, 87, 100, 104, 116, 120]

NR not reported, Y yes

Patterns of IS application in guidelines

The patterns of IS application in guidelines are provided in Table 4. Notably, 83.9% studies did not provide a clear IS definition, 13 studies have provided the sources of IS definitions, and Eccles & Mittman’s study [13] is the most frequently cited. 18 studies clarified implementation phases. A total of 63 studies used one kind of framework, 21 studies used multiple frameworks. 15 studies did not use any framework. Additional, The determinant frameworks was the most widely applied in included studies, among which the Consolidated Framework for Implementation Research (CFIR) (n = 32) was the most common, followed by the Theoretical Domains Framework (TDF) (n = 24).

Table 4.

Patterns of implementation science application in guidelines

IS application	n (%)	References
IS definition
NR	83 (83.9)	[25–50, 52–65, 67–70, 72–93, 95–99, 104, 105, 108–110, 112, 114, 115, 117, 118, 120, 121]
Custom in text	3 (3.0)	[66, 102, 111]
Reference	13 (13.1)	[51, 71, 94, 100, 101, 103, 106, 107, 113, 116, 119, 122, 123]
(Eccles & Mittman, 2006) [13]	5 (-)	[44, 87]
(Nilsen, 2015) [24]	2 (-)	[64, 87]
(Bauer et al., 2015) [124]	3 (-)	[93, 96, 100]
(Carpenter & Pinnock, 2017) [125]	1 (-)	[96]
(Koczwara et al., 2018) [126]	1 (-)	[94]
(Livet et al., 2018) [127]	1 (-)	[106]
(Rapport et al., 2018) [128]	1 (-)	[109]
(Bauer et al., 2020) [3]	1 (-)	[99]
(Proctor et al., 2022) [129]	1 (-)	[93]
Clarity of implementation phases
Y	18 (18.2)	[28, 31, 41, 44, 52, 55, 67, 68, 70, 71, 75, 81, 92, 101, 107, 113, 120, 121]
N	81 (81.8)	[25–27, 29, 30, 32–40, 42, 43, 45–51, 53, 54, 56–66, 69, 72–74, 76–80, 82–91, 93–100, 102–106, 108–112, 114–119, 122, 123]
Frameworks quantity
1	63 (63.6)	[25–28, 30, 31, 34, 36–42, 45, 47–49, 51, 53, 55–58, 61–65, 69, 70, 72–91, 93, 94, 96, 102–105, 110, 116, 117, 120, 123]
2	13 (13.1)	TDF + BCW [50, 54], TDF + COM-B [68, 122], IM + MRC frameworks [92], CFIR + Proctor et al. [99], RE-AIM + ERIC [100], BCW + ERIC [101], CFIR + TDF [104], CFIR + ERIC [97, 114], Helfrich et al.+ facilitation strategies consistent with IS [115]
3	7 (7.1)	CFIR + TDF + BCW [52], KTA + TDF + BCW [60], TDF + BCW + French et al. [66], TDF + COM-B + BCW [107, 121], CFIR + TDF + ERIC [112, 119]
4	1 (1.0)	KTA + TDF + COM-B + RE-AIM [109]
NR	15 (15.2)	[29, 32, 33, 35, 43, 44, 46, 59, 67, 71, 95, 98, 106, 108, 113]
Frameworks purpose
①	15 (-)	[25, 26, 51, 55, 60, 63, 64, 70, 73, 88, 92, 97, 99, 103, 104]
②	19 (-)	[50, 52, 54, 58, 60, 66, 68, 76, 81, 92, 93, 97, 100, 101, 107, 109, 112, 119, 122]
③	11 (-)	[36, 40, 48, 49, 65, 69, 72, 74, 75, 94, 102]
④	18 (-)	[37, 47, 50, 52, 60, 78, 86, 90, 91, 107, 109–111, 117–119, 122, 123]
⑤	9 (-)	[38, 61, 80, 83–85, 87, 96, 120]
⑥	10 (-)	[45, 53, 82, 89, 92, 99, 100, 109, 112, 114]
⑦	4 (-)	[41, 68, 115, 116]
⑧	3 (-)	[30, 42, 111]
⑨	8 (-)	[34, 39, 54, 56, 57, 77, 79, 105]
Frequency of frameworks usage
Process models
KTA	8 (-)	[25, 26, 60, 72, 76, 88, 104, 109]
Determinant frameworks
CFIR	32 (-)	[39, 41, 47–49, 52, 61, 63, 65, 69, 73, 75, 79, 80, 83, 85–87, 91, 93, 96, 97, 99, 103, 110–112, 114, 116, 117, 119, 123]
TDF	24 (-)	[36, 37, 40, 50, 52, 54, 56, 58, 60, 66, 68, 74, 77, 81, 90, 107, 109, 111, 112, 118–122]
iPARIHS	5 (-)	[51, 57, 64, 94, 105]
PARIHS	3 (-)	[34, 38, 45]
Grol et al. [130]	2 (-)	[30, 55]
Classic theories	0 (-)
Implementation theories
COM-B	6 (-)	[68, 107, 109, 118, 121, 122]
NPT	2 (-)	[42, 70]
Evaluation frameworks
RE-AIM	6 (-)	[53, 82, 84, 89, 100, 109]
Proctor et al. [131]	1 (-)	[99]
Others
BCW	8 (-)	[50, 52, 54, 60, 66, 101, 107, 121]
ERIC	6 (-)	[97, 100, 101, 112, 114, 119]

IS Implementation Science, NR not reported, Y yes, N no, TDF Theoretical Domains Frameworks, BCW Behavior Change Wheel, COM-B Capacity-Opportunities-Motivation-Behaviour, IM Intervention Mapping, MRC United Kingdom Medical Research Council, CFIR Consolidated Frameworks for Implementation Research, RE-AIM Reach, Effectiveness, Adoption, Implementation, Maintenance, ERIC Expert Recommendations for Implementing Change, KTA Knowledge-to-Action, iPARIHS integrated-Promoting Action on Research Implementation in Health Services, PARIHS Promoting Action on Research Implementation in Health Services, NPT Normalization Process Theory, ①to guide the entire study design (including implementation progress/planning), ②to guide implementation intervention (including the selection of implementation strategies), ③to inform data/content collection/analysis/interpretation, ④to assess difficulties and identify barriers and/or facilitators of implementation, ⑤to guide interviews/surveys, ⑥to frame an evaluation, ⑦as theoretical/conceptual guidance, ⑧to enhance conceptual clarity, ⑨multiple purposes

Discussion

Our findings indicate that IS in guidelines is advancing, offering clinicians enhanced approaches for evidence translation. However, its impact on guidelines implementation hinges on the scientific rigor and judicious application of IS principles. The included studies were mainly conducted in universities and hospitals, were mostly government-funded, and spanned a broad range of healthcare areas. Consequently, the research designs presented were complex and varied, which may expand the options and possibilities for the clinical translation of guidelines. Frameworks were most commonly used to guide the design of implementation interventions or the overall study design, followed by their use in barrier/facilitator assessment. However, considerations related to research feasibility likely biased participant selection toward clinicians and patients, resulting in the underrepresentation of other stakeholders. Some studies lacked scientific rigor in their design. The disclosure of details such as the implementation process and the strategies for guidelines adoption was limited.

Implementation science: creating new gaps while bridging the evidence-practice chasm

We discover that most implementation studies were unregistered, potentially owing to the complexity of IS study designs and the absence of appropriate registration platforms. Additionally, protocols and detailed disclosures were frequently absent. Although reporting practices have exhibited modest improvement, compliance with StaRI (Standards for Reporting Implementation Studies, promulgated by Carpenter et al. in 2017 [125]) guidelines remains poor. Many researchers appeared uncertain about the required disclosures in guideline-focused implementation research, with some studies failing to articulate the definition of IS. New challenges have emerged. Notably, knowledge of IS remains largely confined to the scientific research domain. This concern is supported by studies reporting that medical staff often feel unprepared to engage with or apply IS concepts, expressing low confidence in their capacity to assimilate the knowledge [124, 131]. Consequently, IS remains largely confined to academia, often becoming a shelved theoretical construct rather than translating into clinical utility [132–134]. Compounding this issue is the existence of over a hundred distinct theories within IS research. Mastering these methodologies remains challenging because of inconsistent terminologies, varying operational definitions, and divergent validation criteria across theories.

Low-quality guidelines implementation: an inherent resource waste

A notable gap identified in our study was the lack of detailed descriptions concerning the specific characteristics of the guidelines used. Clinical studies often rely on guidelines as a central theoretical foundation in their introductions. However, these studies often fail to disclose critical attributes and application specifics of the guidelines within their methodology designs, such as the developers, references, and correspondents. This omission raises an important question: How should guidelines be translated into implementation research? Currently, there is no accepted standard. Our findings demonstrated that 44.4% of the included studies focused on implementing a single, complete guideline. However, it has become common for studies to adopt selected recommendations from one or more guidelines, especially when multiple sources endorse similar actions. A possible explanation for this trend lies in differences in researchers’ viewpoints and objectives. Guidelines developers and government bodies are typically concerned with promoting the dissemination and implementation of full guidelines and obtaining feedback from stakeholders to inform ongoing updates. In contrast, healthcare professionals and patients and their families are often more focused on specific clinical problems, seeking evidence-based solutions that can be applied in the real world. Therefore, the deconstruction and integration of guidelines recommendations is commonly observed, particularly in the development of Computerized Decision Support System [135]. However, researchers seeking to replicate or adapt successful implementation strategies may encounter confusion and barriers when essential details about the guidelines are not disclosed. More importantly, the use of low-quality guidelines can result in wasted resources and undermine the effectiveness and impact of guidelines implementation. Therefore, we recommend that implementation studies document and appraise the detailed attributes of the guidelines they employ.

Enhancing the scientific rigor of implementation study designs in guidelines development

In this scoping review, one-third of the included studies lacked clear or well-defined study designs. While the use of complex research designs may reflect an effort to align guidelines implementation with the realities of clinical practice, which is consistent with the central goals of IS, we emphasize the need for a more precise definition of research design types. A stepwise research approach can help clarify the implementation pathway. This includes identifying barriers and facilitators, guiding the translation of evidence into practice, identifying critical elements of change, specifying implementation strategies, and evaluating implementation outcomes. Nevertheless, consistency in defining study designs is essential. Without it, secondary research is hindered: Shared features are difficult to extract, evidence synthesis becomes challenging, quality assessment is weakened, and the overall progression of IS is impeded.

Seeking broad-spectrum support to leverage resources for effective guidelines implementation

The effectiveness of guidelines recommendations in specific clinical settings depends on their congruence with the preferences and priorities of stakeholders [136]. This scoping review identified medical staff as the primary stakeholders, followed by patients and families. This hierarchy likely reflects clinicians’ capacity to provide direct feedback through their expertise, knowledge, skills, behaviors, and cognition, alongside greater accessibility. Meanwhile, the increased emphasis on patients and families aligns with the fundamental principles of IS and evidence-based medicine, which prioritize patient engagement. However, such emphasis alone proves insufficient to drive guidelines implementation. Research must ensure the adequate representation of all relevant stakeholders to uphold the principles of equity and comprehensiveness [137, 138]. Our findings indicate that sustained and strategic support can foster large-scale, high-quality, and scientifically rigorous guidelines implementation studies, yielding superior implementation outcomes. A supportive organizational culture and robust leadership with top-down commitment are essential, as they not only signal substantial policy and financial commitment but also ensure that healthcare providers are equipped with the necessary resources, knowledge, and skills [139].

There is still a long way to go to apply frameworks in guidelines

In the included studies, 17 frameworks were identified. Among them, the CFIR, TDF were most utilized. They were predominantly applied to guide the entire implementation research design, including implementation progress/planning, barrier and/or facilitator assessment, data/content collection/analysis/interpretation, and evaluation structuring. This finding partially agrees with the results of Birken et al. [23], who also reported primarily for identifying key constructs that could serve as barriers or facilitators, guiding data collection, augmenting conceptual clarity, and directing implementation planning. Although multiple frameworks have been developed and advocated—corroborating the findings of Tinkle et al. [140] and Kirk et al. [141]—the lack of standardized selection criteria and application protocols contributes to their underutilization and suboptimal application [133, 134, 142, 143]. This results in inefficient resource allocation, methodological flaws, erroneous conclusions, and compromised grant review rigor [18].

Strengths and limitations

Existing research has not provided a comprehensive synthesis of the application and characteristics of IS within guidelines. While previous studies have examined the trends in guidelines implementation [4], our study is the first to explore this intricate process further, revealing additional patterns and highlighting opportunities for bridging the gap between guidelines development and practice. Our study has some limitations: (1) some relevant IS studies related to guidelines implementation might have been inadvertently excluded. This may be due to our restriction to English-language literature and the exclusion of studies with ambiguous definitions of IS, indistinct research design characteristics, and unclear IS theory features. (2) the lack of standardized terminology and structural consistency across IS literature posed a challenge for data extraction and synthesis. Uniform language is essential to ensure clear communication, comparability of results, and replication. Although we categorized and defined key concepts to mitigate this issue, the subjective interpretation involved in feature induction might have introduced biases during data extraction. (3) there remains a notable deficiency in the in-depth analysis of implementation outcomes. The lack of focus on implementation outcomes hinders the progress of IS. Although Proctor et al. [131] introduced the concept of “implementation outcomes” in 2011, distinguishing them from service system and clinical treatment outcomes, the conceptualization and assessment of implementation success remain an unresolved conundrum in implementation research [124, 131]. (4) numerous methodologically diverse studies prevented quality assessment and further evidence synthesis due to comprehensive inclusion requirements for characterizing IS guidelines implementation. These limitations should be acknowledged when interpreting our findings. (5) by focusing on peer-reviewed literature for objective evidence synthesis, our review might have excluded relevant grey literature, including institutional implementation plans and evaluation reports, and non-indexed studies. We recommend that future research undertake systematic reviews and meta-analyses with a clear emphasis on evaluating implementation outcomes, tailored to specific research designs. Additionally, the inclusion of gray literature and non-indexed studies may provide additional insights into guidelines implementation.

Conclusion

The evolution of IS within guidelines demonstrates a promising trajectory. Nonetheless, challenges remain, including the lack of scientific rigor in research designs, non-standardized research reporting practices, limited application of IS frameworks, variable quality of the guidelines selected and and their detail disclosure, and an insufficient focus on equitable stakeholder engagement. There is a pressing need for methodological standardization and the active collaboration of all relevant stakeholders. Moving forward, the field of guidelines implementation must prioritize high-quality, evidence-based research to strengthen theoretical underpinnings and provide data support. This will help bridge the gap between IS and the practical enactment of guidelines.

Abbreviations

ANZCTR

Australian New Zealand Clinical Trials Registry

BCW

Behavior Change Wheel

CFIR

Consolidated Framework for Implementation Research

CINAHL

Cumulative Index to Nursing and Alied Health Literature

COM-B

Capacity-Opportunities-Motivation-Behaviour

CONSORT

Consolidated Standards of Reporting Trials

COREQ

Consolidated Criteria for Reporting Qualitative Research

ERIC

Expert Recommendations for Implementing Change

IM

Intervention Mapping

iPARIHS

integrated-Promoting Action on Research Implementation in Health Services

IS

Implementation Science

ISRCTN

International Standard Randomized Controlled Trial Registry

KTA

Knowledge-to-Action

MRC

United Kingdom Medical Research Council

NPT

Normalization Process Theory

NR

Not Reported

OSF

Open Science Frame

PARIHS

Promoting Action on Research Implementation in Health Services

PRISMA-ScR

Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews

RE-AIM

Reach, Effectiveness, Adoption, Implementation, Maintenance

SRQR

Standards for Reporting Qualitative Research

StaRI

Standards for Reporting Implementation Studies

STROBE

Strengthening the Reporting of Observational Studies in Epidemiology

TDF

Theoretical Domains Framework

USA

the United State of America

UK

the United Kingdom

VA

the United States Department of Veterans Affairs

Authors’ contributions

JZ and ZLC conceived the idea and the protocol for this study. JZ and SCL conducted the literature search and data extraction. JZ, XYX and SCL conducted the data collection with advice and consensus gathering from ZLC. ZLC and YB assessed the quality of the studies. JZ, XYX and SCL performed the analysis and synthesis of the results with advice and consensus gathering from ZLC, YB. JZ drafted the manuscript. All the authors revised and approved the submitted version.

Funding

No funding was received to support this scoping review.

Data availability

No datasets were generated or analysed during the current study.

Declarations

Competing interests

The authors declare no competing interests.