Beyond the Surface of Capacity Building: A Mixed-Methods Study of the Core Functions and Forms of Dissemination and Implementation Science Consultations

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Stadnick, Gregory A. Aarons, Lauren Brookman-Frazee, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6559185/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Aug, 2025 Read the published version in Implementation Science Communications → Version 1 posted 5 You are reading this latest preprint version Abstract Background: The number of Dissemination and Implementation Science (DIS) capacity building programs is increasing worldwide. These programs aim to enhance diverse DIS skills through a variety of activities. Our team’s systematic review of DIS programs determined that DIS consultations were offered across 67% of programs, yet their specific roles in capacity development were not well defined. This mixed methods study aimed to identify and categorize the functions and forms of consultation activities across three DIS capacity building programs at the University of California San Diego that varied in content focus and infrastructure and then to map findings onto DIS competencies. Methods: Consultation notes from the three programs were extracted for content analysis to identify discussion topics, DIS guidance provided, and resources shared. Generative artificial intelligence (ChatGPT Plus) facilitated content analyses with multiple rounds of validation from program consultants to refine and finalize themes. Themes were categorized into consultation functions and forms. Forms were mapped onto DIS competencies and a gap analysis was conducted to identify areas for improvement. Program metrics were used to further contextualize findings. Results: A total of 108 consultation notes were analyzed across the three programs. The most common types of support requested related to grant proposals (54%) and ongoing D&I projects (25%). Consultation discussion topics most frequently involved applying implementation science principles (55%) grant development (31%), guidance centered on DIS methods (47%), and study/project design (37%). Consultation guidance was most often aligned with intermediate-level DIS competencies (58%), primarily in the design and analysis and practice-based considerations domains. Conclusions: These findings highlight the nature of DIS consultation services, particularly among those seeking support for grant proposals and ongoing implementation projects. Consultations primarily addressed intermediate-level competencies within the domains of design, analysis, and practice-based implementation strategies, indicating a clear opportunity to strengthen support for both foundational and advanced skill development. These results suggest the need for scalable consultation frameworks, improved tracking systems, and tiered training resources to optimize the reach and impact of DIS capacity-building efforts. Dissemination Implementation Capacity Building Consultation Figures Figure 1 Contributions to the literature Despite the widespread use of consultation in Dissemination and Implementation Science (DIS) capacity-building programs, little is known about what actually happens during these consultations. This study identifies the core functions (topics discussed) and forms (guidance provided) of DIS consultations across three DIS capacity-building programs. By mapping consultation activities onto established DIS competencies, this work provides a new method for evaluating how consultations support capacity-building efforts. Findings highlight opportunities to better align consultation services with foundational DIS competencies, helping to shape future training and consultation models. 1. Background Interest in Dissemination and Implementation Science (DIS) and its applications continues to grow, with a variety of efforts emerging to support its advancement ( 1 , 2 ). DIS capacity building programs enhance DIS skills and competencies through education and training, funding opportunities, consultation, technical assistance, and mentorship ( 3 – 12 ). Notable programs include the Implementation Research Institute (IRI), which provides intensive training in mental health DIS through a two-year program of didactic sessions, mentored research, and concept paper development ( 13 – 15 ); the Mentored Training for Dissemination and Implementation Research in Cancer (MT-DIRC), targeting postdoctoral researchers with mentorship and project-based learning ( 16 ); the Knowledge Translation Summer Institute (KTSI) in Canada, offering short-term, intensive training on implementation frameworks and stakeholder engagement ( 17 ); and the Training in Dissemination and Implementation Research in Health (TIDIRH), providing foundational training for health researchers in conducting D&I studies ( 9 , 18 ). These initiatives reflect a growing ecosystem of DIS training that varies in format (e.g., workshops, fellowships, graduate-level courses etc.), audience, and disciplinary focus ( 7 ). Programs are grounded in DIS competencies, which guide development, assessment, and strengthening of DIS skills ( 19 , 20 ). In 2015, Padek and colleagues developed 43-core DIS competencies, organized by level of expertise (i.e., beginner, intermediate, and advanced) and across four domains: ( 1 ) Definition, Background, and Rationale; ( 2 ) Theory and Approaches; ( 3 ) Design and Analysis; and ( 4 ) Practice-Based Considerations. Hubeschmann et al. (2022) later expanded these with 10 new competencies aimed at advancing rapid and inclusive DIS research. Grounding capacity-building efforts in these competencies enables rigorous standards and measurable benchmarks for DIS training and workforce development. Our team conducted a systematic review of DIS capacity building programs, identifying 165 programs domestically and globally, and found that DIS consultations made up 67% of capacity building activities ( 12 ). This highlights the central role of consultation as a strategy for providing tailored guidance, problem-solving, and real-time support to navigate foundational and complex DIS challenges. Despite their prevalence, little is known about how consultation activities contribute to DIS capacity building nor how they align with DIS competencies. Understanding DIS consultation content and methods is crucial for identifying best practices and developing evidence-based guidelines ( 21 , 22 ). Without such knowledge, evaluating, refining, and optimizing consultations remains challenging. Building on prior work ( 7 , 12 , 21 ), this study examines consultation activities at three DIS capacity building programs housed at the University of California, San Diego (UCSD): ( 1 ) a DIS program within a clinical and translational science center (NIH UL1TR001442); ( 2 ) an HIV implementation science program (NIAID P30-AI036214 CFAR Supplement); and ( 3 ) a center focused on team-based implementation strategies in children’s mental health (NIMH P50MH126231). Using consultation notes and program metrics, we aim to identify the core functions (topics) and forms (guidance provided) of DIS consultations, assess their alignment with DIS competencies, and propose best practices to enhance their effectiveness. 2. Methods 2.1 Study Context: Overview of the Three DIS Capacity Building Programs UCSD currently houses three DIS capacity building programs that served as data sources for this study. The Altman Clinical and Translational Research Institute Dissemination and Implementation Science Center (DISC) – Established in 2020 through the Clinical and Translational Science Award program (NIH Grant UL1TR001442), offers DIS training, technical assistance, and research support through expert consultations tailored to diverse stakeholders. San Diego Center for AIDS Research Implementation Science Hub (SD CFAR IS Hub) – Funded by the National Institute of Allergy and Infectious Diseases (NIAID P30-AI036214 CFAR Supplement) and established in 2020, its one of 10 regional IS Hubs that supports Ending the HIV Epidemic (EHE) research through DIS training, mentoring, and technical assistance. Implementation Science and Team Effectiveness in Practice (IN STEP) Children’s Mental Health Research Center – Established in 2022 through a National Institute of Mental Health (NIMH) ALACRITY P50 award (P50MH126231), IN STEP develops and tests team-based implementation strategies to improve children's mental health services across systems and provides consultation in team effectiveness, implementation science, and children’s mental health services research. Though operating independently, these programs collaborate by sharing resources and consultants, co-hosting events, and referring consultation requests, offering a unique context for examining DIS consultation activities. Across programs, 23 consultants (20 PhD/MD-level, three Master’s-level Certified Implementation Support Specialists) offer expertise across DIS, public health, HIV/AIDS, gender and sexual minority health, team-effectiveness research, children’s mental health, leadership, policy, and organizational psychology disciplines (DISC n = 11; IS Hub n = 8; IN STEP n = 11). Seven consultants work across the three programs, fostering cross-program synergy. Consultation mechanisms were conceptualized using the Core Functions and Forms framework, which distinguishes between an intervention’s essential purposes (core functions) and strategies used to achieve them (forms) ( 23 , 24 ). In the context of this study, this framework offers a structured lens through which to examine how various consultation activities contribute to DIS capacity building ( 25 ). 2.2 Study Design This study employed a multi-stepped mixed-methods approach: Data Compilation – Consultation notes were compiled into a database for qualitative coding and analysis. Program metrics (e.g., consultee role, department, experience level) were integrated to enrich interpretation. Integration of Program Metrics –Metrics were synthesized with content analysis findings to contextualize consultation activities. Content Analysis Using Generative Artificial Intelligence (AI) – A three-step process combined manual coding with validation using a Large Language Model (LLM) (ChatGPT) ( 26 ) to systematically identify and categorize consultation core functions (i.e., topics discussed), forms (i.e., types of guidance provided), and resources shared. Results served as the foundation for competency mapping and gap analysis. Competency Mapping – Consultation forms were mapped onto updated DIS competencies ( 21 ). Gap Analysis – Analysis identified competency areas addressed and gaps in consultation support ( 27 ). 2.3 Data Compilation Program coordinators reviewed and added consultation notes to the database, excluding entries lacking sufficient detail. Specifically, consultation notes with a single vague sentence, offering no insight into the discussion content, topics covered, or type of guidance provided during the session. In such cases, these notes did not allow for reliable coding or interpretation and were therefore omitted from the dataset to ensure the integrity and depth of the analysis. 2.4 Integration of Program Metrics Program metrics across the three programs (e.g., consulting program, type of consultation, consultee role/title, consultee affiliation, consultation follow up data) were synthesized, providing contextual depth to the content analysis. Consultee and consultation request data were collected through each program’s consultation request system. DISC and IN STEP offer consultation services to a broader audience and capture a range of requested support types. In contrast, the IS Hub provided consultations exclusively to pre-funded projects under the EHE initiative and did not collect comparable support request data due to its consultation scope. 2.5 Content Analysis The content analysis was completed using three consecutive steps: Step one – Manual Coding , two trained coders manually assigned consultation functions, forms, and resource types using an iteratively refined codebook. Consultation function codes were initially developed using predefined topic areas listed on each program’s consultation request, where consultees select discussion topics. However, several of these predefined categories were broad and lacked specificity (e.g., DIS methods, designing and evaluating implementation strategies, program design etc.). To enhance analytical clarity, consultation notes were reviewed to identify more granular discussion points and targeted sub-codes under these broader themes and finalized by the larger study team. For example, the broad category of “adaptations” was refined to reflect more specific subtopics such as “adaptation of DIS models,” “intervention tailoring,” and “modification of implementation strategies”. Discrepancies were addressed through discussion and escalation to the larger study team for review and decision-making. The full list of codes is provided in Additional file 1. Codes for consultation forms and resources shared were generated based on observed content in the notes rather than a predefined list. As with function codes, these were iteratively reviewed and validated by the larger study team to ensure consistency and accuracy. For example, the coding team discussed with the larger study team how to distinguish between “connect with co-investigator” and “identified mentor” when reviewing consultation notes. It was agreed that “connect with co-investigator” would be reserved for projects not associated with K or other career development awards, whereas “identified mentor” would be used exclusively for consultations involving mentorship support tied to early-career development mechanisms (e.g., K awards). In another instance, the broad code “guidance on sustainability” was reviewed and refined to “guidance on sustainability methods”, better reflecting the type of technical support offered (i.e., applying DIS theories, models, and frameworks to sustainability planning and evaluation, methods to address sustainability barriers, identifying adaptations for sustainability etc.). Step two - Familiarize ChatGPT to Data , using ChatGPT as a tool to facilitate the content analysis, the coding team familiarized ChatGPT to the database, conducting iterative checks to ensure accurate data. ChatGPT was provided with key background information related to the consultation notes (e.g., “ these notes are from DIS consultations…” ); total number of notes in the database; and a copy of the codebook to use as a reference. It was prompted to summarize the dataset and the coding team used their existing knowledge of the data to question any inconsistencies until an accurate summary was produced. For example, ChatGPT initially miscalculated the number of consultation notes due to formatting errors in the coded entries. Specifically, it misinterpreted commas as delimiters for separate notes rather than as separators between multiple codes within a single entry. To correct this, the team issued a refinement prompt clarifying the structure of the database: “Note: Each row in the dataset represents one individual consultation note. Within each row, codes are separated by commas but do not indicate separate consultation entries. Do not count comma-separated codes as separate notes. Instead, use the row count to determine the total number of consultation notes in the dataset.”. This clarification enabled ChatGPT to correctly compute the total number of consultations and to produce accurate frequency counts of individual codes. The refinement prompt strategy was used throughout the analysis to ensure consistency between the model’s interpretation and the database structure. This iterative process helped mitigate the risks of hallucinations and response degradation, as noted in other AI-supported qualitative analysis research ( 28 , 29 ). Step three – AI Assisted Thematic Synthesis , the coding team developed a structured prompt framework to guide the model’s thematic synthesis ( 29 ), which included prompting ChatGPT to: ( 1 ) analyze the database using the codebook to organize content into overarching categories and ( 2 ) summarize the frequency of each code within those categories. To begin, ChatGPT was given explicit instructions to analyze the full list of consultation codes (categorized by consultation function, form, and resources shared) and group them into higher-level content buckets. For example, the coding team provided the following instruction: “ Using the codebook, group the consultation forms into broader thematic categories. For each category, include the name, a short label, and a list of the individual codes it contains. Then provide the frequency of each code based on the number of times it appears in the dataset. Ensure the categories are mutually exclusive.” Using ChatGPT’s interactive design, the coding team asked follow-up questions to gather additional detailed and validate responses. If the coding team was unsure about ChatGPT’s categorization, they would escalate it to the larger study team for review and feedback. For example, the overarching category of “implementation science application” was initially called “implementation strategies & feedback”. However, this overarching theme did not capture all of the other items in the category. The larger study team advised the coding team to have ChatGPT update the name of the overarching category to better capture the application of implementation science principles, not just implementation strategies. The coding team proceeded to instruct ChatGPT to avoid overlapping categories and to suggest revised category names if existing labels were too narrow or broad: “Review the content within the ‘implementation strategies & feedback’ category. Some codes in this group pertain to broader applications of DIS (e.g., implementation outcomes, team science/team effectiveness, dissemination strategies). Propose a more inclusive label for this category that better reflects these elements.”. Then, ChatGPT was prompted to quantify the data by summarizing how many times each code appeared in the dataset: “ For each category, list the number of times each individual code appears, and then sum the total number of codes within that category. Output the results in a table format ”. The iterative approach allowed the team to not only leverage the model’s capacity for thematic synthesis but also maintain oversight and analytic accuracy throughout the content analysis process ( 29 , 30 ). 2.6 Competency Mapping Consultation forms, representing actionable guidance, were mapped to DIS competencies ( 21 ) by linking each form to its most relevant domain (e.g., Theory, Design and Analysis, Practice-Based Considerations). For each form, the study team identified the most closely related competency based on its primary focus. Forms addressing theoretical or conceptual issues were mapped to competencies in Section A (Definition, Background, and Rationale) or Section B (Theory and Approaches). Forms related to methodology and study design were mapped to Section C (Design and Analysis), while those emphasizing community engagement or practical applications were assigned to Section D (Practice-Based Considerations). Forms that did not align with a specific competency were categorized under broader DIS competencies and noted accordingly. Multiple rounds of validation occurred with the study team to ensure the accuracy of the competency mapping. 2.7 Gap Analysis The gap analysis was conducted by comparing the DIS competencies from Hubeschmann et al. (2022) with the DIS competencies mapped to the identified consultation forms. Competencies were categorized across the four competency domains. The number and percentage of competencies covered in each domain were used to assess gaps in coverage across consultation forms. 2.8 Consultation Outcomes The DISC and IN STEP programs collect post-consultation outcome data from the consultees through brief surveys (DISC via JotForm and IN STEP via Qualtrics) sent approximately six months after the initial consultation. Since the IS Hub exclusively supports ongoing funded EHE projects, comparable follow-up mechanisms were not in place and therefore excluded from this analysis. 3. Results At the time of analysis, the three programs conducted a total of 302 consultations: The DISC completed 238 consultations (2019–2024), the IS Hub completed 33 consultations (2021–2024), and IN STEP completed 31 consultations (2022–2024). Average monthly consultation rates were calculated based on annual volumes for each program, not total divided by years in operation: DISC averaged 4.1/month, IS Hub 3.6/month, and IN STEP 2/month. Not all consultations had associated notes. Of the 302 consultation meetings, 121 consultation notes were identified, and 108 included in the analysis after excluding entries with insufficient detail (e.g., one-sentence notes lacking content). These comprised of 46 from DISC, 38 from IS Hub, and 24 from IN STEP. 3.1 Program Metrics Consultee demographics Consultations were requested by a diverse group of consultees with overlapping roles: Assistant Professors (n = 86, 26%), Professors (n = 62, 18%), Associate Professors (n = 55, 16%), Postdoctoral Trainees (n = 35, 10%), Graduate Students (n = 26, 8%), and Clinicians/Healthcare Providers (n = 22, 7%). Disciplines included Medicine (n = 137, 43%), Public Health (n = 68, 21%), Psychiatry (n = 48, 15%), and Psychology (n = 27, 9%). DISC and IN STEP also collected data on consultee affiliations: most were from academic institutions (n = 261, 87%), followed by healthcare systems (n = 18, 6%), and community agencies (n = 12, 4%). (See Table 1 ). Table 1 Program Metrics by Program Roles/Titles a Overall (N = 336) DISC (n = 235) IS Hub (n = 42) IN STEP (n = 59) Professor D, IS, IN 62 18% 50 21% 6 14% 6 10% Associate Professor D, IS, IN 55 16% 31 13% 16 38% 8 14% Assistant Professor D, IS, IN 86 26% 61 26% 10 24% 15 25% Adjunct Professor IS 3 1% - - 2 5% - - Postdoctoral Trainee D, IN 35 10% 22 9% - - 13 22% Graduate Student D, IN 26 8% 25 11% - - 1 2% Clinician/Healthcare Provider D, IN 22 7% 15 6% - - 6 10% Project/Research Scientist D, IS, IN 15 4% 7 3% 1 2% 6 10% Non-faculty Researcher D 2 1% 2 1% N/A - - - Research Staff D, IN 10 3% 6 3% N/A - 4 7% Director IS 3 1% - - 3 7% - - Other (Associate Dean etc.) D, IS 14 4% 14 6% - - - - Degrees a Overall (N = 117) DISC IS Hub (n = 40) IN STEP (n = 77) PhD/DrPH IS, IN 37 32% - - 28 70% 9 12% ScD IS 1 1% - - 1 3% - - DrPH IS 2 2% - - 2 5% - - MD/DO IS, IN 48 41% - - 8 20% 40 52% MPH/MSPH IS, IN 8 7% - - - - 8 10% MA/MS IN 11 9% - - 1 3% 10 13% BA/BS/BSN IN 10 9% - - - - 10 13% Departments a Overall (N = 317) DISC (n = 275) IS Hub (n = 42) IN STEP Medicine (Includes all sub-specialties) D, IS 137 43% 124 45% 13 31% - - Public Health D, IS 68 21% 58 21% 10 24% - - Psychiatry D, IS 48 15% 45 16% 3 7% - - Psychology D, IS 27 9% 22 8% 5 12% - - Global Health IS 3 1% - - 3 7% - - Nursing D 5 2% 3 1% 2 5% - - Social Work D, IS 8 3% 7 3% 1 2% - - Other (Health Systems, Anthropology, Medical Social Sciences etc.) D, IS 21 7% 16 6% 5 12% - - Experience Levels a Overall (N = 333) DISC 1 (n = 193) IS Hub IN STEP (n = 48) Novice D, IN 147 44% 122 63% - - 25 52% Advanced Beginner D, IN 104 31% 91 47% - - 13 27% Intermediate D, IN 54 16% 46 24% - - 8 17% Advanced D, IN 28 8% 26 13% - - 2 4% 1 Aggregate of two separate measures of DIS experience Affiliations a Overall (N = 301) DISC (n = 207) IS Hub IN STEP (n = 74) Academic Institutions D, IN 261 87% 204 90% - - 57 77% Healthcare Systems D, IN 18 6% 14 6% - - 4 5% Community Agency (e.g., Federally qualified health center) D, IN 12 4% 9 4% - - 3 4% County Department (e.g., health, education etc.) IN 2 1% - - - - 2 3% Other (Private organization etc.) IN 8 3% - - - - 8 11% Note : a Available metrics by program: D = DISC, IS = IS Hub, and IN = IN STEP Additionally, through the DISC and IN STEP consultation requests, consultees are able to self-disclose their experience levels with DIS (DISC-only) and team effectiveness research (TER) (IN STEP-only). DISC consultees reported varying DIS experience: 63% (n = 122) identified as novices (e.g., no prior engagement with DIS activities or frameworks), 47% (n = 91) as advanced beginners (e.g., having participated in some DIS training, contributed to a DIS project, or used DIS frameworks once or twice), 24% (n = 46) as intermediate (e.g. having engaged in DIS activities and applied frameworks multiple times, they had not led a DIS-focused project or proposal), and 13% (n = 26) as advanced (e.g., having led grants or projects with DIS as a central research focus or incorporated DIS frameworks as a core part of study design). Similarly, among IN STEP consultees, 52% (n = 25) identified as novices (e.g., no prior engagement with TER activities or frameworks), 27% (n = 13) as advanced beginners (e.g., having participated in TER training or contributed to a TER project), 17% (n = 8) as intermediate (e.g., having engaged in TER activities, but not led a TER-focused project or proposal), and 4% (n = 2) as advanced (e.g., having led grants or projects with TER as a central research focus). Type of support requested Across 302 consultation requests, 329 distinct support types were reported (requests could include multiple types). Most commonly was support related to grant proposals (n = 177, 54%) and ongoing D&I projects (n = 82, 25%). Additional requests included D&I mentoring and career development (n = 44, 13%), support on publications (n = 17, 5%), general program inquires (n = 4, 1%), other support (e.g., dissertation support) (n = 3, 1%), and Ongoing TER research project (n = 2, 1%). 3.2 Content Analysis: Consultation Functions & Forms Consultation Functions A total of 370 topic observations were identified across 108 consultation notes (multiple topics per note). The most common functions included implementation science applications (e.g., implementation strategies; applying DIS theories, models, and frameworks; adaptations etc.) (n = 201, 55%) and grant development (e.g., study design; metrics & measures; identifying a co-investigator etc.) (n = 113, 31%), while topics on analytical methods and evaluation (e.g., data analysis; qualitative/quantitative methods support etc.) (n = 31, 8%) and professional development and training (e.g., publications, discussion of program services, general DIS education etc.) (n = 25, 7%) were also present. (See Table 2 ). Table 2 Content Analysis Results Topic Discussed (Consultation Functions) Frequency (N = 370) Percentage (%) Implementation Science Application 201 54% Implementation Strategies 29 8% Models & Frameworks 28 8% Community and/or Stakeholder Engagement 27 7% Implementation Outcomes 23 6% Implementation Determinants 23 6% Implementation Outcomes Crosswalk 16 4% Sustainability 12 3% Adaptations 12 3% Team Science/Team Effectiveness 11 3% Program Design 7 2% Dissemination Strategies 5 1% Team mechanisms 5 1% Intervention Selection 3 1% Grant Development 113 31% Study Design 63 17% Metrics & Measures 23 6% Seeking co-investigator 12 3% Funding opportunities 9 2% Future grant proposal 6 2% Analytical Methods and Evaluation Support 31 8% Data Analysis 13 4% Qualitative methods support 13 4% Program Evaluation 4 1% Quantitative methods support 1 0.1% Professional Development and Training 25 7% Publication/Presentation 9 2% General D&I education 8 2% Seeking mentor 5 1% Career Development 3 1% Types of DIS Guidance Provided (Consultation Forms) Frequency (N = 262) Percentage (%) Dissemination & Implementation Concepts and Methods 124 47% Guidance on selecting, applying, evaluating, and adapting implementation and/or dissemination strategies 29 11% Guidance on identifying and addressing implementation determinants 21 8% Use of DIS tools (e.g., implementation logic model; implementation outcomes crosswalk) 17 7% Guidance on team science methods 12 5% Guidance on sustainability methods 9 3% Provided general D&I education (e.g., discussion of D&I topics and concepts, directing towards educational resources) 9 3% Identify dissemination avenues (e.g., conference presentations) 1 0.40% Provide guidance on intervention selection 1 0.40% Guidance on selecting and applying D&I theories, models, frameworks 24 9% Adapting D&I theories, models, and frameworks 1 0.40% Study & Project Guidance 96 37% Guidance on study design 56 21% Feedback on grant 15 6% Connect with DIS co-investigator 10 4% Potential funding opportunities 5 2% Provide feedback on program 5 2% Feedback on manuscript 3 1% Feedback on presentation 2 1% Community/Stakeholder Engagement Strategies 28 11% Conceptualizing and/or operationalizing stakeholder engagement methods 21 8% Guidance on community-engagement methods 5 2% Disseminating findings to community and/or stakeholders 1 0.40% Evaluating community/stakeholder engagement 1 0.40% Mentorship/Career Development 14 5% Establishing co-investigator/mentorship 6 2% General Career Development (e.g., submitting a K award etc.) 5 2% Identify DIS mentor 3 1% Types of Resources Shared Frequency (N = 113) Percentage (%) Relevant readings (e.g. journal articles, policy brief, grant RFA etc.) 51 45% Web resource (e.g. D&I models, webtools) 25 22% Connect with content expert 19 17% Education and training opportunities (e.g. workshop information, fellowship opportunities etc.) 14 12% Offer program support (e.g. Letter of Support, data analysis and interpretation) 2 2% Consultation Forms We documented 262 instances of DIS guidance, categorized as consultation forms (not mutually exclusive). The most frequent consultation form was guidance on DIS concepts and methods (n = 124, 47%) (e.g., selecting, applying, evaluating, and adapting implementation strategies, identifying and addressing implementation determinants etc.), followed by study and project guidance (n = 96, 37%) (e.g., feedback on study design, grant proposals, and making connections with DIS co-investigators). Additional forms included community/stakeholder engagement strategies (n = 28, 11%) (e.g., conceptualizing and operationalizing community/stakeholder methods) and mentorship/career development (n = 14, 5%) (e.g., agreeing to be listed as a mentor on career development award). (See Table 2 ). Types of Resources Shared Among 109 documented resources, 45% (n = 51) were relevant readings (e.g., journal articles, grant examples), 22% (n = 25) were DIS-related webtools (e.g., the D&I Models in Health Webtool), 17% (n = 19) were connections to content experts, and 12% (n = 14) were educational resources. Letters of support were shared in two consultations (2%). (See Table 2 ). 3.3 Competency Mapping & Gap Analysis Competency Mapping Of the total 54 DIS competencies ( 21 ), 25 were mapped to the consultation forms. Eleven forms aligned with multiple competencies, which were recorded in secondary columns (see Table 3 ). Sub-forms were also captured (e.g., “Use of DIS tools” was broken down into guidance on logic models and outcomes crosswalks). Notably, of the two uncategorized competencies reported by Huebschmann and colleagues (2022), we were able to map one, “Apply theory and strategies from team science to promote team effectiveness in D&I research”, onto the consultation form “Guidance on team science methods”. Table 3 DIS Competencies Mapped Consultation Form Primary Secondary Competency Section Competency Competency Level Competency Section Competency Competency Level 1. Guidance on selecting, applying, evaluating, and adapting implementation and/or dissemination strategies Section D: Practice-Based Considerations Identify and develop sustainable partnerships for D&I research. Intermediate Section D: Practice-Based Considerations Use evidence to evaluate and adapt D&I strategies for specific populations, settings, contexts, resources, and/or capacities. Advanced 1a. Guidance on evaluation methods Section C: Design and Analysis Identify and measure outcomes that matter to stakeholders, adopters, and implementers. Intermediate Section C: Design and Analysis Identify common D&I measures and analytic strategies relevant to your research question(s). Beginner 1b. Guidance on documenting and evaluating adaptations Section D: Practice-Based Considerations Describe how adaptations will be documented throughout the D&I research project. Intermediate Section D: Practice-Based Considerations Explain how to maintain fidelity of original interventions during the adaptation process. Intermediate 2. Guidance on identifying and addressing implementation determinants Section A: Definition, Background, and Rationale Formulate methods to address barriers and facilitators of D&I research. Intermediate - - - 3. Use of DIS tools (e.g., implementation logic model; implementation outcomes crosswalk) Not explicitly mapped, but aligns with broader guidance competencies (e.g., Section B: Theory and Approaches; Section C: Design and Analysis). Expanded to include sub-forms that were able to be mapped onto individual competencies. 3a. Guidance on completing/refining implementation outcomes crosswalk Section B: Theory and Approaches Characterize process models that support iterative cycles of implementation and adaptation based on learning. - Section C: Design and Analysis Develop and assess processes and outcomes that support iterative cycles of implementation and bidirectional flow of information (e.g., learning health systems). Advanced 3b. Guidance on developing implementation logic model for projects Section B: Theory and Approaches Describe a process for designing for dissemination (planning for adoption, implementation, and sustainability during the intervention development stage). Intermediate - - - 4. Guidance on team science methods Section B: Theory and Approaches Apply theory and strategies from team science to promote team effectiveness in D&I research. Beginner - - - 5. Guidance on sustainability methods Section C: Design and Analysis Effectively integrate the concepts of sustainability/sustainment and the rationale behind them in D&I study design. Intermediate Section C: Design and Analysis Evaluate and refine innovative scale-up and spread methods (e.g., technical assistance, interactive systems, novel incentives, and 'pull' strategies). Advanced 6. Provided general D&I education (e.g., discussion of D&I topics and concepts, directing towards educational resources) Section A: Definition, Background, and Rationale Define and communicate dissemination and implementation (D&I) research terminology. Beginner - - - 7. Identify dissemination avenues (e.g., conference presentations) Not explicitly mapped to competencies but aligns with broader guidance competencies (e.g., Section D: Practice-Based Considerations). 8. Provide guidance on intervention selection Section A: Definition, Background, and Rationale Determine which evidence-based interventions are worth disseminating and implementing. Intermediate - - - 9. Guidance on selecting and applying D&I theories, models, frameworks Section B: Theory and Approaches Identify appropriate conceptual models, frameworks, or program logic for D&I change. Intermediate Section B: Theory and Approaches Describe a process for designing for dissemination (planning for adoption, implementation, and sustainability during the intervention development stage). Intermediate 10. Adapting D&I theories, models, and frameworks Section D: Practice-Based Considerations Describe how adaptations will be documented throughout the D&I research project. Intermediate - - - 11. Guidance on study design Section C: Design and Analysis Identify and articulate the trade-offs between a variety of different study designs for D&I research. Intermediate Section C: Design and Analysis Operationalize hybrid effectiveness-implementation designs when appropriate to accelerate the implementation of evidence-based interventions in real-world settings. Advanced 11a. Guidance on selecting, measuring, and determining implementation outcomes Section C: Design and Analysis Identify common D&I measures and analytic strategies relevant to your research question(s). Beginner Section C: Design and Analysis Identify and measure outcomes that matter to stakeholders, adopters, and implementers. Intermediate 11b. Review and provide feedback on measures Section C: Design and Analysis Describe gaps in D&I measurement and critically evaluate how to fill them. Advanced - - - 11c. Guidance on data collection, analysis, and interpretation Section C: Design and Analysis Describe the application and integration of mixed-method (quantitative and qualitative) approaches in D&I research. Intermediate Section C: Design and Analysis Apply common D&I measures and analytic strategies relevant for your research question(s) within your model/framework. Intermediate 12. Feedback on grant Not explicitly mapped to competencies but aligns with broader guidance competencies (e.g., Section C: Design and Analysis & Section D: Practice-Based Considerations). 13. Connect with DIS co-investigator Section D: Practice-Based Considerations Identify and develop sustainable partnerships for D&I research. Intermediate - - - 14. Potential funding opportunities Indirectly aligns with sustainability and equity strategies in partnerships (e.g., Section D: Practice-Based Considerations). 15. Provide feedback on program Not explicitly mapped to competencies but aligns with broader guidance competencies (e.g., Section C: Design and Analysis; Section D: Practice-Based Considerations). 16. Feedback on manuscript Not explicitly mapped to competencies but aligns with broader guidance competencies (e.g., Section C: Design and Analysis; Section D: Practice-Based Considerations). 17. Feedback on presentation Not explicitly mapped to competencies but aligns with broader guidance competencies (e.g., Section C: Design and Analysis; Section D: Practice-Based Considerations). 18. Conceptualizing and/or operationalizing stakeholder engagement methods Section D: Practice-Based Considerations Integrate strategies within D&I research to facilitate meaningful stakeholder engagement (e.g., shared power, shared decision-making, co-learning). Beginner Section D: Practice-Based Considerations Describe the appropriate process for eliciting input from community-based practitioners for adapting an intervention. Intermediate 19. Guidance on community-engagement methods Section D: Practice-Based Considerations Integrate strategies within D&I research to facilitate meaningful stakeholder engagement (e.g., shared power, shared decision-making, co-learning). Beginner Section D: Practice-Based Considerations Summarize the importance of ethically and culturally competent clinical and community-based research in D&I science. Intermediate 20. Disseminating findings to community and/or stakeholders Not explicitly mapped to competencies but aligns with broader guidance competencies (e.g., Section C: Design and Analysis; Section D: Practice-Based Considerations). 21. Evaluating community/stakeholder engagement Section D: Practice-Based Considerations Integrate strategies within D&I research to facilitate meaningful stakeholder engagement (e.g., shared power, shared decision-making, co-learning). Beginner - - - 22. Establishing co-investigator/mentorship Section A: Definition, Background, and Rationale Describe the range of expertise needed to conduct D&I research (e.g., mixed-methods experience, economic, organizational, policy, clinical). Intermediate - - - 23. General Career Development (e.g., submitting a K award etc.) Not explicitly mapped to competencies but aligns with broader guidance competencies (e.g., Section C: Design and Analysis; Section D: Practice-Based Considerations). 24. Identify DIS mentor Section D: Practice-Based Considerations Identify and develop sustainable partnerships for D&I research. Intermediate - - - Gap Analysis Among the 24 mapped competencies with defined expertise levels, most were Intermediate (n = 14, 58%), followed by Beginner (n = 5, 21%) and Advanced (n = 5, 21%). Most frequently observed competencies came from Section C: Design and Analysis (n = 10, 63%) and Section D: Practice-Based Considerations (n = 7, 44%). For example, “Guidance on study design” mapped to “Identify and articulate the trade-offs between a variety of different study designs for D&I research” (Section C, Intermediate). “Guidance on stakeholder engagement” mapped to “Identify and develop sustainable partnerships for D&I research” (Section D, Intermediate). Fewer competencies were observed in Section A: Definition, Background, and Rationale (n = 4, 36%) and Section B: Theory and Approaches (n = 3, 33%). (see Table 4 ). Table 4 DIS Competency Gap Analysis Competency Sections (N = 54) Competencies Observed (N = 25, 46%) Competencies not observed (N = 29, 52%) Specific Competencies Observed (n = 4) Level Specific Competencies Not Observed (n = 7) Level Section A: Definition, Background, and Rationale (N = 11) Formulate methods to address barriers and facilitators of D&I research. Intermediate Examine the importance of rapid research to advance D&I science concepts and directions. Beginner Determine which evidence-based interventions are worth disseminating and implementing. Intermediate Define what is and what is not D&I research. Beginner Define and communicate dissemination and implementation (D&I) research terminology. Beginner Differentiate between D&I research and other related areas, such as efficacy research and effectiveness research. Beginner Describe the range of expertise needed to conduct D&I research (e.g., mixed-methods experience, economic, organizational, policy, clinical) Beginner Identify the potential impact of disseminating, implementing, and sustaining effective interventions, including assessments of equity and representativeness. Intermediate Assess, describe, and quantify (where possible) the context for effective D&I (setting characteristics, culture, capacity, and readiness). Intermediate Identify existing gaps in D&I research. Intermediate Identify the potential impact of scaling down (aka de-implementing) an ineffective but often used intervention. Intermediate Specific Competencies Observed (n = 3) Level Specific Competencies Not Observed (n = 6) Level Section B: Theory and Approaches (N = 9) Identify appropriate conceptual models, frameworks, or program logic for D&I change. Intermediate Describe a range of D&I strategies, models, and frameworks. Beginner Design strategies to address the multi-level influences of health inequities as it relates to the implementation of an evidence-based intervention. Intermediate Describe a process for designing for dissemination (planning for adoption, implementation, and sustainability during the intervention development stage). Intermediate Describe the relationships between various organizational dimensions (e.g., climate, culture) and D&I research. Intermediate Explain how knowledge from disciplines outside of health (e.g., business, marketing, and engineering) can help inform further transdisciplinary efforts in D&I research. Intermediate Characterize process models that support iterative cycles of implementation and adaptation based on learning. Intermediate Identify and articulate the interplay between policy and organizational processes in D&I. Intermediate Identify core elements (effective ingredients) of effective interventions, and recognize risks of making modifications to these. Intermediate Specific Competencies Observed (n = 10) Level Specific Competencies Not Observed (n = 6) Level Section C: Design and Analysis (N = 16) Identify and articulate the trade-offs between a variety of different study designs for D&I research. Intermediate Describe the core components of external validity and their relevance to D&I research. Beginner Describe the application and integration of mixed-method (quantitative and qualitative) approaches in D&I research. Intermediate Identify common D&I measures and analytic strategies relevant to your research question(s). Beginner Identify possible methods to address external validity in study design reporting and implementation. Intermediate Apply common D&I measures and analytic strategies relevant for your research question(s) within your model/framework. Intermediate List the potential roles of mediators and moderators in a D&I study. Intermediate Identify and measure outcomes that matter to stakeholders, adopters, and implementers. Intermediate Operationalize hybrid effectiveness-implementation designs when appropriate to accelerate the implementation of evidence-based interventions in real-world settings. Advanced Effectively explain and incorporate concepts of de-adoption and de-implementation into D&I study design. Advanced Describe gaps in D&I measurement and critically evaluate how to fill them. Advanced Evaluate and refine innovative scale-up and spread methods (e.g., technical assistance, interactive systems, novel incentives, and 'pull' strategies). Advanced Effectively integrate the concepts of sustainability/sustainment and the rationale behind them in D&I study design. Intermediate Describe how to frame and analyze the context of D&I as a complex system with interacting parts. Intermediate Develop and assess processes and outcomes that support iterative cycles of implementation and bidirectional flow of information (e.g., learning health systems). Advanced Incorporate methods of economic evaluation (e.g., implementation costs, cost-effectiveness) in D&I study design. Advanced Specific Competencies Observed (n = 7) Level Specific Competencies Not Observed (n = 9) Level Section D: Practice-Based Considerations (N = 16) Identify and develop sustainable partnerships for D&I research. Intermediate Describe the importance of incorporating the perspectives of different stakeholder groups (e.g., patient/family, employers, payers, healthcare settings, public organizations, community, and policy makers). Beginner Describe how adaptations will be documented throughout the D&I research project. Intermediate Describe the concept and measurement of fidelity. Beginner Summarize the importance of ethically and culturally competent clinical and community-based research in D&I science. Beginner Articulate the strengths and weaknesses of participatory research in D&I research. Beginner Integrate strategies within D&I research to facilitate meaningful stakeholder engagement (e.g., shared power, shared decision-making, co-learning). Beginner Determine when engagement in participatory research is appropriate with D&I research. Intermediate Use evidence to evaluate and adapt D&I strategies for specific populations, settings, contexts, resources, and/or capacities. Advanced Identify and apply techniques for stakeholder analysis and engagement when implementing evidence-based practices. Intermediate Identify a process for adapting an intervention and implementation strategy prior to and during implementation. Intermediate Explain how to maintain fidelity of original interventions during the adaptation process. Intermediate Identify sites to participate in D&I studies, and negotiate or provide incentives to secure their involvement. Intermediate Describe the appropriate process for eliciting input from community-based practitioners for adapting an intervention. Intermediate Describe how to measure successful partnerships for D&I research. Intermediate Develop strategies to promote equity in resource distribution across all external research partners, including community partners or other external organizations and the researcher’s institution. Intermediate Specific Competencies Observed (n = 1) Level Specific Competencies Not Observed (n = 1) Level Not Categorized (N = 2) Apply theory and strategies from team science to promote team effectiveness in D&I research. N/A Apply systems science and systems modeling approaches in D&I research. N/A 3.4 Consultation Follow Up Data Consultation Satisfaction Of the 223 DISC consultation follow up surveys collected, 77 had completed satisfaction questions. Consultees rated their consultation experience using a 5-point Likert scale (1 = Strongly Disagree to 5 = Strongly Agree). Responses were highly positive: 100% agree consultants actively listened (n = 77), 93.4% (n = 71) strongly agreed the consultation was useful, and 90.9% (n = 70) strongly agreed the meeting was timely and that they would recommend the service. Somewhat lower agreement (84.4%, n = 65) was seen for post-meeting collaboration follow-through (See Table 5 ). One consultee shared: “DISC consultation helped me establish my first connection with a DISC expert, from which a mentor-mentee relationship was developed (and still is). Through this relationship I was able to tailor my K01 proposal with strong Implementation Science focus. The proposal was completed and submitted”. Table 5 DISC Consultation Satisfaction Ratings Strongly Disagree Somewhat Disagree Neither Agree/Disagree Somewhat Agree Strongly Agree The consultation meeting was scheduled in a timely manner. - 1 (1.3%) 1 (1.3%) 5 (6.5%) 70 (90.9%) My immediate needs were addressed during this first consultation. - 1 (1.3%) - 9 (11.8%) 66 (86.8%) The consultation meeting was useful. - - - 5 (6.6%) 71 (93.4%) The consultant addressed my questions clearly and completely. - - 1 (1.3%) 5 (6.6%) 70 (92.1%) I understand my steps or action items. - - 1 (1.7%) 7 (11.5%) 53 (86.9%) There is a clear continuation plan to keep my work moving forward. - - 3 (3.9%) 12 (15.6%) 62 (80.5%) Resources or tools mentioned during the consultation were shared afterwards. - - 1 (1.3%) 7 (9.2%) 68 (89.5%) The consultation improved my understanding of D&I frameworks and models. - - - 6 (12.0%) 44 (88.0%) The consultant actively listened to my questions and description. - - - - 75 (100.0%) Connections and/or collaborations offered during the meeting were shared afterwards. - - 6 (7.8%) 6 (7.8%) 65 (84.4%) I would recommend the DISC consultation service to my colleagues. - - - 7 (9.1%) 70 (90.9%) The consultation improved my ability to apply D&I frameworks and models. - - - 8 (16.7%) 40 (83.3%) Note. Participants rated each item on a 5-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). D&I = Dissemination and Implementation. Data presented as a frequency. For IN STEP, there were a total of 13 follow up surveys collected. All respondents selected the highest possible score across satisfaction with the consultation service (“Extremely satisfied”), perceived value of the consultation (“Very valuable”), and likelihood to recommend the service (“Extremely likely”). Due to uniformity in responses, these data are summarized narratively. Project Outcomes DISC and IN STEP also collected data on project status. Six non-mutually exclusive categories were shared across the two programs: Grant Proposal Submitted (34.1%, n = 15), Grant Submission-In Progress (25.0%, n = 11), Other (15.9%, n = 7), Grant Funded (13.6%, n = 6), Paper Submission-In Progress (6.8%, n = 3), and Paper Submitted (4.5%, n = 2). (See Fig. 1 .) 4. Discussion This study expands our understanding of DIS consultations by examining core functions and forms of consultations across three DIS capacity-building programs. While several formal DIS training programs have evaluated educational activities (e.g., coursework, seminars, mentoring), less is known about the consultation services embedded within these programs ( 3 – 5 , 9 , 13 – 15 , 15 , 20 , 31 ). Given that consultations represent approximately 67% of DIS capacity-building activities ( 12 ), this study fills a critical gap by detailing consultation content, guidance forms, and alignment with DIS competencies ( 20 ). These findings contribute to a more nuanced understanding of consultations as a central DIS capacity-building mechanism. Program metrics showed that most consultees were faculty at academic institutions (ranging from early-career to senior investigators) or clinicians/healthcare professionals working in healthcare systems, often identifying as novices. Consultation largely supported ongoing DIS projects and grant proposals. Notably, the IS Hub’s focus on Ending the HIV Epidemic projects likely contributed to its higher proportion of project-based consultations. Follow up data from DISC and IN STEP consultations indicated high levels of satisfaction, with strong ratings across satisfaction dimensions. Project outcomes suggested early signs of consultation impact: 34.1% of DISC and IN STEP consultees reported grant proposal submissions, and 13.6% reported funded grants following consultation. These findings reinforce consultations’ potential value not only for education but also for advancing tangible research outputs ( 32 ). Content analysis systematically identified consultation functions (topics discussed), forms (guidance provided), and resources shared ( 23 – 25 ). Implementation science applications and grant development emerged as the most common functions; DIS methods guidance and study/project support were the most frequent forms. Shared resources included relevant readings, DIS web tools, expert connections, and educational opportunities. Although letters of support were infrequently shared during sessions, they remain a resource offered by these programs outside of the consultation service and not explicitly captured through consultation notes. Mapping consultation forms to DIS competencies allowed objective evaluation of how these consultations align with DIS training standards ( 7 , 19 – 21 , 33 ). The gap analysis showed concentration in competencies related to Design and Analysis and Practice-Based Considerations, with fewer consultations addressing foundational theory and background. Additionally, consultations were predominantly aligned with intermediate-level competencies, with fewer consultations mapping onto beginner- and advanced-level competencies. Applying the Core Functions and Forms framework to consultations helped to clarify their role among DIS capacity building efforts ( 23 – 25 ) and offers a framework for evaluation ( 2 , 33 ). Identifying gaps in consultation coverage presents an opportunity to enhance training and foundational DIS skill development. 4.1 Limitations Despite generating valuable insights, this study has limitations. First, while the three programs share administrative resources and commonalities, their distinct structures and processes complicated data synthesis. Developing systematic methods to track project outcomes across programs could improve data comparability and capture long-term impacts. Second, consultation notes varied in detail, limiting the ability to fully capture consultation nuances. Future efforts could involve recording consultations and using AI tools to generate transcripts and meeting summaries to enhance the quality and comprehensiveness of consultation records. This approach could reduce the burden of manual note-taking, ensure consistency, and provide valuable resources for training future consultants. However, AI-generated transcripts and notes must be validated by program coordinators to mitigate inaccuracies. This is because AI transcription tools may struggle with specialized terminology, multiple speakers, or poor audio quality, potentially resulting in incomplete or misleading data ( 29 , 34 , 35 ). Third, although ChatGPT supported the content analysis (organizing codes, summarizing frequencies, proposing categories), all outputs were reviewed and refined by the study team. Clarification were often needed to avoid misclassification due to database formatting or code ambiguities. While this validation minimized AI biases, reliance on AI tools still poses risks of oversimplification or contextual misinterpretation ( 29 , 30 ). Future research should continue to explore best practices for integrating generative AI tools into qualitative and mixed methods research, including structured prompts, validation strategies, and mitigation of AI limitations. 4.2 Implications for Future Research and Practice Findings suggest several practical strategies for optimizing DIS consultation services. First, improving consultation tracking and standardization could enhance program evaluation and demonstrate impact. Pre/post surveys, qualitative interviews, and periodic follow ups would provide richer insights into consultation contributions to skill-building and project outcomes. Second, the gap analysis identified lower coverage of competencies related to Definition, Background, and Rationale and Theory and Approaches. Since these domains serve as the foundation for DIS, consultation services could intentionally integrate theoretical and background content into sessions (e.g., onboarding modules for newcomers) or complementary training activities appropriate across career stages and experience levels ( 2 , 3 ). Third, formalizing resource-sharing practices, such as curated repositories of recommended readings and webtools, could streamline consultations ( 36 ). Expanding mentorship networks and expert connections would also strengthen capacity-building efforts ( 37 ). Finally, these results can inform the development of standardized DIS consultation frameworks that can be adapted and scaled across different institutions ( 2 ). Shared consultation protocols, structured resource sharing, and standardized evaluation indicators would strengthen individual programs and foster a broader DIS infrastructure. 5. Conclusion This study provides foundational insights into DIS consultations, clarifying their functions and forms within capacity-building efforts. By improving consultation tracking, standardizing processes, and tailoring services across skill levels, programs can further enhance DIS training and workforce development. Future research should explore longitudinal consultation outcomes, examine the relationship between guidance types and project success, and refine scalable consultation models to maximize DIS capacity-building impact. Abbreviations Dissemination and implementation science (DIS); Implementation Research Institute (IRI); Mentored Training for Dissemination and Implementation Research in Cancer (MT-DIRC); Knowledge Translation Summer Institute (KTSI); Training in Dissemination and Implementation Research in Health (TIDIRH); Dissemination and Implementation Science Center (DISC); San Diego Center for AIDS Research Implementation Science Hub (SD CFAR IS Hub); Implementation Science and Team Effectiveness in Practice (IN STEP); National Institutes of Health (NIH); National Institute of Mental Health (NIMH); National Institute of Allergy and Infectious Diseases (NIAID); Artificial Intelligence (AI); Large Language Models (LLMs); Ending HIV Epidemic (EHE); Team effectiveness research (TER); Dissemination and implementation (D&I) Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request [KS]. The datasets presented in this article are not readily available because the project is still ongoing. Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding Funding for this work was supported by: The University of California San Diego Altman Clinical and Translational Research Institute Dissemination and Implementation Science Center (DISC) (UL1 TR001442); University of California San Diego ImplementatioN Science and Team Effectiveness in Practice (IN STEP) Children’s Mental Health Research Center (P50MH126231); and the San Diego Center for AIDS Research Implementation Science Hub (P30-AI036214 CFAR Supplement). Author contributions KS & BR contributed by designing the study. KS contributed by leading the data analysis and interpretation. KS, IB, KC, CV, CG, LC, ZD, & AB contributed by collecting and synthesizing consultation data. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6559185","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":453795605,"identity":"c50cbed5-1463-4f16-910f-c8eea1744bc6","order_by":0,"name":"Kera Swanson","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIiWNgGAWjYBACCTiLvQdIFDAkgDk8DAyMDQS18JwBEgYGpGiRyCFSi+Ts9mcSP3fUyZlLvj344IfBnzwGieTHH94w2MhuOIBdi7TMGTPJ3jOHjS1n5yUb9hgYFDNIpJlJzmFIM8alRU4ih+0Gb9uBxA23c8wkeAwMEhuAIsw8DIcTcWtJf3bzb1td4oabZ8x//oFoYf7Mw/AfpxZpiQSz27xtzIkbbvCYMUNtYZDmYTiAU4vkjBzz37Jth40NzuQYS8sYGCe28TwD+sUg2XgmDi0SN9IfG75tq5MzOH7G8OObCrnEfnZQiFXYyfbh0IIJ2MCkAbHKR8EoGAWjYBRgAwAlV1t7y99CPAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0001-9744-127X","institution":"University of California San Diego","correspondingAuthor":true,"prefix":"","firstName":"Kera","middleName":"","lastName":"Swanson","suffix":""},{"id":453795606,"identity":"03e45cc1-7a90-48fd-909f-29f713b7840d","order_by":1,"name":"Nicole A. Stadnick","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Nicole","middleName":"A.","lastName":"Stadnick","suffix":""},{"id":453795607,"identity":"f95c7a89-87a4-4b2f-98dc-e680e73856d4","order_by":2,"name":"Gregory A. Aarons","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Gregory","middleName":"A.","lastName":"Aarons","suffix":""},{"id":453795608,"identity":"d5ab1e16-0143-4586-af5a-8d712c69a3e1","order_by":3,"name":"Lauren Brookman-Frazee","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Lauren","middleName":"","lastName":"Brookman-Frazee","suffix":""},{"id":453795609,"identity":"48e113e4-2bfd-4ff9-9d98-1717be953a7c","order_by":4,"name":"Isaac Bouchard","email":"","orcid":"","institution":"California State University Northridge","correspondingAuthor":false,"prefix":"","firstName":"Isaac","middleName":"","lastName":"Bouchard","suffix":""},{"id":453795610,"identity":"fb7e0918-1ebc-44e0-8247-4ee827a71494","order_by":5,"name":"Zeying Du","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Zeying","middleName":"","lastName":"Du","suffix":""},{"id":453795611,"identity":"915a1202-b024-4acd-aa0d-1f64a697b022","order_by":6,"name":"Anna Brubaker","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Brubaker","suffix":""},{"id":453795612,"identity":"2e1ab77d-db7d-434b-8653-c255ce695dc3","order_by":7,"name":"Carrie Geremia","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Carrie","middleName":"","lastName":"Geremia","suffix":""},{"id":453795613,"identity":"e0f08f16-7fe7-4e42-831c-eec4761032f1","order_by":8,"name":"Kelli Cain","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Kelli","middleName":"","lastName":"Cain","suffix":""},{"id":453795614,"identity":"ae47df03-abb4-4c7f-aab4-372e9b85f264","order_by":9,"name":"Lilliana Conradi","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Lilliana","middleName":"","lastName":"Conradi","suffix":""},{"id":453795615,"identity":"a82e2874-b272-4f84-826d-2b88e4186d00","order_by":10,"name":"Marisa Sklar","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Marisa","middleName":"","lastName":"Sklar","suffix":""},{"id":453795616,"identity":"fa2194ca-0761-4bce-ace5-91e6d645395b","order_by":11,"name":"Clare Viglione","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Clare","middleName":"","lastName":"Viglione","suffix":""},{"id":453795617,"identity":"0160797b-1b28-46ef-a3a1-c726d932aeab","order_by":12,"name":"Borsika Rabin","email":"","orcid":"","institution":"University of California San Diego","correspondingAuthor":false,"prefix":"","firstName":"Borsika","middleName":"","lastName":"Rabin","suffix":""}],"badges":[],"createdAt":"2025-04-29 19:40:51","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6559185/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6559185/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s43058-025-00775-0","type":"published","date":"2025-08-18T16:29:24+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82595544,"identity":"eb68b703-c798-499a-932c-9b02e95cdd1b","added_by":"auto","created_at":"2025-05-13 08:41:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":10648,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eDISC and IN STEP Consultation Outcomes – Project Status\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote: \u003c/em\u003ePercentages represent the proportion of respondents within each program (DISC: n=33; IN STEP: n=11) who reported each outcome. Raw values are not shown due to different sample sizes across programs.\u003c/p\u003e","description":"","filename":"Onlinedrawingimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6559185/v1/8f900fe1626282f058277acb.png"},{"id":89847266,"identity":"7d78c256-eb11-422f-ad6c-d4f16c39f863","added_by":"auto","created_at":"2025-08-25 16:42:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2504746,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6559185/v1/b02160bf-fdb9-49ed-a11e-eb82dc405bbc.pdf"},{"id":82595551,"identity":"8556d379-b681-470c-82ab-b77ae0381a48","added_by":"auto","created_at":"2025-05-13 08:41:08","extension":"docx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":31450,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6559185/v1/c99b9f4192467a43482c8c0a.docx"}],"financialInterests":"","formattedTitle":"Beyond the Surface of Capacity Building: A Mixed-Methods Study of the Core Functions and Forms of Dissemination and Implementation Science Consultations","fulltext":[{"header":"Contributions to the literature","content":"\u003cul type=\"disc\"\u003e\n \u003cli\u003eDespite the widespread use of consultation in\u0026nbsp;Dissemination and Implementation Science (DIS)\u0026nbsp;capacity-building programs, little is known about what actually happens during these consultations.\u003c/li\u003e\n \u003cli\u003eThis study identifies the core functions (topics discussed) and forms (guidance provided) of DIS consultations across three DIS capacity-building programs.\u003c/li\u003e\n \u003cli\u003eBy mapping consultation activities onto established DIS competencies, this work provides a new method for evaluating how consultations support capacity-building efforts.\u003c/li\u003e\n \u003cli\u003eFindings highlight opportunities to better align consultation services with foundational DIS competencies, helping to shape future training and consultation models.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Background","content":"\u003cp\u003eInterest in Dissemination and Implementation Science (DIS) and its applications continues to grow, with a variety of efforts emerging to support its advancement (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). DIS capacity building programs enhance DIS skills and competencies through education and training, funding opportunities, consultation, technical assistance, and mentorship (\u003cspan additionalcitationids=\"CR4 CR5 CR6 CR7 CR8 CR9 CR10 CR11\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNotable programs include the Implementation Research Institute (IRI), which provides intensive training in mental health DIS through a two-year program of didactic sessions, mentored research, and concept paper development (\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e); the Mentored Training for Dissemination and Implementation Research in Cancer (MT-DIRC), targeting postdoctoral researchers with mentorship and project-based learning (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e); the Knowledge Translation Summer Institute (KTSI) in Canada, offering short-term, intensive training on implementation frameworks and stakeholder engagement (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e); and the Training in Dissemination and Implementation Research in Health (TIDIRH), providing foundational training for health researchers in conducting D\u0026amp;I studies (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). These initiatives reflect a growing ecosystem of DIS training that varies in format (e.g., workshops, fellowships, graduate-level courses etc.), audience, and disciplinary focus (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Programs are grounded in DIS competencies, which guide development, assessment, and strengthening of DIS skills (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn 2015, Padek and colleagues developed 43-core DIS competencies, organized by level of expertise (i.e., beginner, intermediate, and advanced) and across four domains: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) Definition, Background, and Rationale; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) Theory and Approaches; (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) Design and Analysis; and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) Practice-Based Considerations. Hubeschmann et al. (2022) later expanded these with 10 new competencies aimed at advancing rapid and inclusive DIS research. Grounding capacity-building efforts in these competencies enables rigorous standards and measurable benchmarks for DIS training and workforce development.\u003c/p\u003e \u003cp\u003eOur team conducted a systematic review of DIS capacity building programs, identifying 165 programs domestically and globally, and found that DIS consultations made up 67% of capacity building activities (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). This highlights the central role of consultation as a strategy for providing tailored guidance, problem-solving, and real-time support to navigate foundational and complex DIS challenges. Despite their prevalence, little is known about how consultation activities contribute to DIS capacity building nor how they align with DIS competencies.\u003c/p\u003e \u003cp\u003eUnderstanding DIS consultation content and methods is crucial for identifying best practices and developing evidence-based guidelines (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Without such knowledge, evaluating, refining, and optimizing consultations remains challenging. Building on prior work (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), this study examines consultation activities at three DIS capacity building programs housed at the University of California, San Diego (UCSD): (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) a DIS program within a clinical and translational science center (NIH UL1TR001442); (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) an HIV implementation science program (NIAID P30-AI036214 CFAR Supplement); and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) a center focused on team-based implementation strategies in children\u0026rsquo;s mental health (NIMH P50MH126231). Using consultation notes and program metrics, we aim to identify the core functions (topics) and forms (guidance provided) of DIS consultations, assess their alignment with DIS competencies, and propose best practices to enhance their effectiveness.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Context: Overview of the Three DIS Capacity Building Programs\u003c/h2\u003e \u003cp\u003eUCSD currently houses three DIS capacity building programs that served as data sources for this study.\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eThe Altman Clinical and Translational Research Institute Dissemination and Implementation Science Center (DISC)\u003c/em\u003e \u0026ndash; Established in 2020 through the Clinical and Translational Science Award program (NIH Grant UL1TR001442), offers DIS training, technical assistance, and research support through expert consultations tailored to diverse stakeholders.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eSan Diego Center for AIDS Research Implementation Science Hub (SD CFAR IS Hub)\u003c/em\u003e \u0026ndash; Funded by the National Institute of Allergy and Infectious Diseases (NIAID P30-AI036214 CFAR Supplement) and established in 2020, its one of 10 regional IS Hubs that supports Ending the HIV Epidemic (EHE) research through DIS training, mentoring, and technical assistance.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eImplementation Science and Team Effectiveness in Practice (IN STEP) Children\u0026rsquo;s Mental Health Research Center\u003c/em\u003e \u0026ndash; Established in 2022 through a National Institute of Mental Health (NIMH) ALACRITY P50 award (P50MH126231), IN STEP develops and tests team-based implementation strategies to improve children's mental health services across systems and provides consultation in team effectiveness, implementation science, and children\u0026rsquo;s mental health services research.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThough operating independently, these programs collaborate by sharing resources and consultants, co-hosting events, and referring consultation requests, offering a unique context for examining DIS consultation activities.\u003c/p\u003e \u003cp\u003eAcross programs, 23 consultants (20 PhD/MD-level, three Master\u0026rsquo;s-level Certified Implementation Support Specialists) offer expertise across DIS, public health, HIV/AIDS, gender and sexual minority health, team-effectiveness research, children\u0026rsquo;s mental health, leadership, policy, and organizational psychology disciplines (DISC n\u0026thinsp;=\u0026thinsp;11; IS Hub n\u0026thinsp;=\u0026thinsp;8; IN STEP n\u0026thinsp;=\u0026thinsp;11). Seven consultants work across the three programs, fostering cross-program synergy.\u003c/p\u003e \u003cp\u003eConsultation mechanisms were conceptualized using the Core Functions and Forms framework, which distinguishes between an intervention\u0026rsquo;s essential purposes (core functions) and strategies used to achieve them (forms) (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). In the context of this study, this framework offers a structured lens through which to examine how various consultation activities contribute to DIS capacity building (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study Design\u003c/h2\u003e \u003cp\u003eThis study employed a multi-stepped mixed-methods approach:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eData Compilation\u003c/em\u003e \u0026ndash; Consultation notes were compiled into a database for qualitative coding and analysis. Program metrics (e.g., consultee role, department, experience level) were integrated to enrich interpretation.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eIntegration of Program Metrics\u003c/em\u003e \u0026ndash;Metrics were synthesized with content analysis findings to contextualize consultation activities.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eContent Analysis Using Generative Artificial Intelligence (AI)\u003c/em\u003e \u0026ndash; A three-step process combined manual coding with validation using a Large Language Model (LLM) (ChatGPT) (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) to systematically identify and categorize consultation core functions (i.e., topics discussed), forms (i.e., types of guidance provided), and resources shared. Results served as the foundation for competency mapping and gap analysis.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eCompetency Mapping\u003c/em\u003e \u0026ndash; Consultation forms were mapped onto updated DIS competencies (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eGap Analysis\u003c/em\u003e \u0026ndash; Analysis identified competency areas addressed and gaps in consultation support (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data Compilation\u003c/h2\u003e \u003cp\u003eProgram coordinators reviewed and added consultation notes to the database, excluding entries lacking sufficient detail. Specifically, consultation notes with a single vague sentence, offering no insight into the discussion content, topics covered, or type of guidance provided during the session. In such cases, these notes did not allow for reliable coding or interpretation and were therefore omitted from the dataset to ensure the integrity and depth of the analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Integration of Program Metrics\u003c/h2\u003e \u003cp\u003eProgram metrics across the three programs (e.g., consulting program, type of consultation, consultee role/title, consultee affiliation, consultation follow up data) were synthesized, providing contextual depth to the content analysis.\u003c/p\u003e \u003cp\u003eConsultee and consultation request data were collected through each program\u0026rsquo;s consultation request system. DISC and IN STEP offer consultation services to a broader audience and capture a range of requested support types. In contrast, the IS Hub provided consultations exclusively to pre-funded projects under the EHE initiative and did not collect comparable support request data due to its consultation scope.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Content Analysis\u003c/h2\u003e \u003cp\u003eThe content analysis was completed using three consecutive steps:\u003c/p\u003e \u003cp\u003e \u003cb\u003eStep one \u0026ndash; Manual Coding\u003c/b\u003e, two trained coders manually assigned consultation functions, forms, and resource types using an iteratively refined codebook. Consultation function codes were initially developed using predefined topic areas listed on each program\u0026rsquo;s consultation request, where consultees select discussion topics. However, several of these predefined categories were broad and lacked specificity (e.g., DIS methods, designing and evaluating implementation strategies, program design etc.). To enhance analytical clarity, consultation notes were reviewed to identify more granular discussion points and targeted sub-codes under these broader themes and finalized by the larger study team. For example, the broad category of \u0026ldquo;adaptations\u0026rdquo; was refined to reflect more specific subtopics such as \u0026ldquo;adaptation of DIS models,\u0026rdquo; \u0026ldquo;intervention tailoring,\u0026rdquo; and \u0026ldquo;modification of implementation strategies\u0026rdquo;. Discrepancies were addressed through discussion and escalation to the larger study team for review and decision-making. The full list of codes is provided in Additional file 1.\u003c/p\u003e \u003cp\u003eCodes for consultation forms and resources shared were generated based on observed content in the notes rather than a predefined list. As with function codes, these were iteratively reviewed and validated by the larger study team to ensure consistency and accuracy. For example, the coding team discussed with the larger study team how to distinguish between \u0026ldquo;connect with co-investigator\u0026rdquo; and \u0026ldquo;identified mentor\u0026rdquo; when reviewing consultation notes. It was agreed that \u0026ldquo;connect with co-investigator\u0026rdquo; would be reserved for projects not associated with K or other career development awards, whereas \u0026ldquo;identified mentor\u0026rdquo; would be used exclusively for consultations involving mentorship support tied to early-career development mechanisms (e.g., K awards). In another instance, the broad code \u0026ldquo;guidance on sustainability\u0026rdquo; was reviewed and refined to \u0026ldquo;guidance on sustainability methods\u0026rdquo;, better reflecting the type of technical support offered (i.e., applying DIS theories, models, and frameworks to sustainability planning and evaluation, methods to address sustainability barriers, identifying adaptations for sustainability etc.).\u003c/p\u003e \u003cp\u003e \u003cb\u003eStep two - Familiarize ChatGPT to Data\u003c/b\u003e, using ChatGPT as a tool to facilitate the content analysis, the coding team familiarized ChatGPT to the database, conducting iterative checks to ensure accurate data. ChatGPT was provided with key background information related to the consultation notes (e.g., \u0026ldquo;\u003cem\u003ethese notes are from DIS consultations\u0026hellip;\u0026rdquo;\u003c/em\u003e); total number of notes in the database; and a copy of the codebook to use as a reference. It was prompted to summarize the dataset and the coding team used their existing knowledge of the data to question any inconsistencies until an accurate summary was produced. For example, ChatGPT initially miscalculated the number of consultation notes due to formatting errors in the coded entries. Specifically, it misinterpreted commas as delimiters for separate notes rather than as separators between multiple codes within a single entry. To correct this, the team issued a refinement prompt clarifying the structure of the database: \u003cem\u003e\u0026ldquo;Note: Each row in the dataset represents one individual consultation note. Within each row, codes are separated by commas but do not indicate separate consultation entries. Do not count comma-separated codes as separate notes. Instead, use the row count to determine the total number of consultation notes in the dataset.\u0026rdquo;.\u003c/em\u003e This clarification enabled ChatGPT to correctly compute the total number of consultations and to produce accurate frequency counts of individual codes. The refinement prompt strategy was used throughout the analysis to ensure consistency between the model\u0026rsquo;s interpretation and the database structure. This iterative process helped mitigate the risks of hallucinations and response degradation, as noted in other AI-supported qualitative analysis research (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eStep three \u0026ndash; AI Assisted Thematic Synthesis\u003c/b\u003e, the coding team developed a structured prompt framework to guide the model\u0026rsquo;s thematic synthesis (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), which included prompting ChatGPT to: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) analyze the database using the codebook to organize content into overarching categories and (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) summarize the frequency of each code within those categories. To begin, ChatGPT was given explicit instructions to analyze the full list of consultation codes (categorized by consultation function, form, and resources shared) and group them into higher-level content buckets. For example, the coding team provided the following instruction: \u0026ldquo;\u003cem\u003eUsing the codebook, group the consultation forms into broader thematic categories. For each category, include the name, a short label, and a list of the individual codes it contains. Then provide the frequency of each code based on the number of times it appears in the dataset. Ensure the categories are mutually exclusive.\u0026rdquo;\u003c/em\u003e\u003c/p\u003e \u003cp\u003eUsing ChatGPT\u0026rsquo;s interactive design, the coding team asked follow-up questions to gather additional detailed and validate responses. If the coding team was unsure about ChatGPT\u0026rsquo;s categorization, they would escalate it to the larger study team for review and feedback. For example, the overarching category of \u0026ldquo;implementation science application\u0026rdquo; was initially called \u0026ldquo;implementation strategies \u0026amp; feedback\u0026rdquo;. However, this overarching theme did not capture all of the other items in the category. The larger study team advised the coding team to have ChatGPT update the name of the overarching category to better capture the application of implementation science principles, not just implementation strategies. The coding team proceeded to instruct ChatGPT to avoid overlapping categories and to suggest revised category names if existing labels were too narrow or broad: \u003cem\u003e\u0026ldquo;Review the content within the \u0026lsquo;implementation strategies \u0026amp; feedback\u0026rsquo; category. Some codes in this group pertain to broader applications of DIS (e.g., implementation outcomes, team science/team effectiveness, dissemination strategies). Propose a more inclusive label for this category that better reflects these elements.\u0026rdquo;.\u003c/em\u003e Then, ChatGPT was prompted to quantify the data by summarizing how many times each code appeared in the dataset: \u0026ldquo;\u003cem\u003eFor each category, list the number of times each individual code appears, and then sum the total number of codes within that category. Output the results in a table format\u003c/em\u003e\u0026rdquo;.\u003c/p\u003e \u003cp\u003eThe iterative approach allowed the team to not only leverage the model\u0026rsquo;s capacity for thematic synthesis but also maintain oversight and analytic accuracy throughout the content analysis process (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Competency Mapping\u003c/h2\u003e \u003cp\u003eConsultation forms, representing actionable guidance, were mapped to DIS competencies (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) by linking each form to its most relevant domain (e.g., Theory, Design and Analysis, Practice-Based Considerations). For each form, the study team identified the most closely related competency based on its primary focus. Forms addressing theoretical or conceptual issues were mapped to competencies in Section A (Definition, Background, and Rationale) or Section B (Theory and Approaches). Forms related to methodology and study design were mapped to Section C (Design and Analysis), while those emphasizing community engagement or practical applications were assigned to Section D (Practice-Based Considerations). Forms that did not align with a specific competency were categorized under broader DIS competencies and noted accordingly. Multiple rounds of validation occurred with the study team to ensure the accuracy of the competency mapping.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Gap Analysis\u003c/h2\u003e \u003cp\u003eThe gap analysis was conducted by comparing the DIS competencies from Hubeschmann et al. (2022) with the DIS competencies mapped to the identified consultation forms. Competencies were categorized across the four competency domains. The number and percentage of competencies covered in each domain were used to assess gaps in coverage across consultation forms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Consultation Outcomes\u003c/h2\u003e \u003cp\u003eThe DISC and IN STEP programs collect post-consultation outcome data from the consultees through brief surveys (DISC via JotForm and IN STEP via Qualtrics) sent approximately six months after the initial consultation. Since the IS Hub exclusively supports ongoing funded EHE projects, comparable follow-up mechanisms were not in place and therefore excluded from this analysis.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eAt the time of analysis, the three programs conducted a total of 302 consultations: The DISC completed 238 consultations (2019\u0026ndash;2024), the IS Hub completed 33 consultations (2021\u0026ndash;2024), and IN STEP completed 31 consultations (2022\u0026ndash;2024). Average monthly consultation rates were calculated based on annual volumes for each program, not total divided by years in operation: DISC averaged 4.1/month, IS Hub 3.6/month, and IN STEP 2/month. Not all consultations had associated notes. Of the 302 consultation meetings, 121 consultation notes were identified, and 108 included in the analysis after excluding entries with insufficient detail (e.g., one-sentence notes lacking content). These comprised of 46 from DISC, 38 from IS Hub, and 24 from IN STEP.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Program Metrics\u003c/h2\u003e \u003cp\u003e \u003cem\u003eConsultee demographics\u003c/em\u003e \u003c/p\u003e \u003cp\u003eConsultations were requested by a diverse group of consultees with overlapping roles: Assistant Professors (n\u0026thinsp;=\u0026thinsp;86, 26%), Professors (n\u0026thinsp;=\u0026thinsp;62, 18%), Associate Professors (n\u0026thinsp;=\u0026thinsp;55, 16%), Postdoctoral Trainees (n\u0026thinsp;=\u0026thinsp;35, 10%), Graduate Students (n\u0026thinsp;=\u0026thinsp;26, 8%), and Clinicians/Healthcare Providers (n\u0026thinsp;=\u0026thinsp;22, 7%). Disciplines included Medicine (n\u0026thinsp;=\u0026thinsp;137, 43%), Public Health (n\u0026thinsp;=\u0026thinsp;68, 21%), Psychiatry (n\u0026thinsp;=\u0026thinsp;48, 15%), and Psychology (n\u0026thinsp;=\u0026thinsp;27, 9%). DISC and IN STEP also collected data on consultee affiliations: most were from academic institutions (n\u0026thinsp;=\u0026thinsp;261, 87%), followed by healthcare systems (n\u0026thinsp;=\u0026thinsp;18, 6%), and community agencies (n\u0026thinsp;=\u0026thinsp;12, 4%). (See Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eProgram Metrics by Program\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRoles/Titles \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eOverall (N\u0026thinsp;=\u0026thinsp;336)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eDISC (n\u0026thinsp;=\u0026thinsp;235)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eIS Hub (n\u0026thinsp;=\u0026thinsp;42)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eIN STEP (n\u0026thinsp;=\u0026thinsp;59)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProfessor \u003csup\u003eD, IS, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssociate Professor \u003csup\u003eD, IS, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e38%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssistant Professor \u003csup\u003eD, IS, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdjunct Professor \u003csup\u003eIS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePostdoctoral Trainee \u003csup\u003eD, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e22%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGraduate Student \u003csup\u003eD, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinician/Healthcare Provider \u003csup\u003eD, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProject/Research Scientist \u003csup\u003eD, IS, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-faculty Researcher \u003csup\u003eD\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResearch Staff \u003csup\u003eD, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDirector \u003csup\u003eIS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther (Associate Dean etc.) \u003csup\u003eD, IS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDegrees\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOverall (N\u0026thinsp;=\u0026thinsp;117)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eDISC\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cb\u003eIS Hub (n\u0026thinsp;=\u0026thinsp;40)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003eIN STEP (n\u0026thinsp;=\u0026thinsp;77)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhD/DrPH \u003csup\u003eIS, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e70%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScD \u003csup\u003eIS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrPH \u003csup\u003eIS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMD/DO \u003csup\u003eIS, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e52%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMPH/MSPH \u003csup\u003eIS, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMA/MS \u003csup\u003eIN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBA/BS/BSN \u003csup\u003eIN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDepartments\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOverall (N\u0026thinsp;=\u0026thinsp;317)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eDISC (n\u0026thinsp;=\u0026thinsp;275)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cb\u003eIS Hub (n\u0026thinsp;=\u0026thinsp;42)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003eIN STEP\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedicine (Includes all sub-specialties) \u003csup\u003eD, IS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic Health \u003csup\u003eD, IS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychiatry \u003csup\u003eD, IS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychology \u003csup\u003eD, IS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlobal Health \u003csup\u003eIS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNursing \u003csup\u003eD\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial Work \u003csup\u003eD, IS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther (Health Systems, Anthropology, Medical Social Sciences etc.) \u003csup\u003eD, IS\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExperience Levels\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOverall (N\u0026thinsp;=\u0026thinsp;333)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eDISC\u003c/b\u003e\u003csup\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e(n\u0026thinsp;=\u0026thinsp;193)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cb\u003eIS Hub\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003eIN STEP (n\u0026thinsp;=\u0026thinsp;48)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNovice \u003csup\u003eD, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e52%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdvanced Beginner \u003csup\u003eD, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e47%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e27%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate \u003csup\u003eD, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e17%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdvanced \u003csup\u003eD, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e1\u003c/sup\u003e \u003cem\u003eAggregate of two separate measures of DIS experience\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAffiliations\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eOverall (N\u0026thinsp;=\u0026thinsp;301)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cb\u003eDISC (n\u0026thinsp;=\u0026thinsp;207)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u003cb\u003eIS Hub\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e\u003cb\u003eIN STEP (n\u0026thinsp;=\u0026thinsp;74)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcademic Institutions \u003csup\u003eD, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e77%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthcare Systems \u003csup\u003eD, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity Agency (e.g., Federally qualified health center) \u003csup\u003eD, IN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCounty Department (e.g., health, education etc.) \u003csup\u003eIN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther (Private organization etc.) \u003csup\u003eIN\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e11%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e\u003cem\u003eNote\u003c/em\u003e: \u003csup\u003ea\u003c/sup\u003e Available metrics by program: D\u0026thinsp;=\u0026thinsp;DISC, IS\u0026thinsp;=\u0026thinsp;IS Hub, and IN\u0026thinsp;=\u0026thinsp;IN STEP\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAdditionally, through the DISC and IN STEP consultation requests, consultees are able to self-disclose their experience levels with DIS (DISC-only) and team effectiveness research (TER) (IN STEP-only). DISC consultees reported varying DIS experience: 63% (n\u0026thinsp;=\u0026thinsp;122) identified as novices (e.g., no prior engagement with DIS activities or frameworks), 47% (n\u0026thinsp;=\u0026thinsp;91) as advanced beginners (e.g., having participated in some DIS training, contributed to a DIS project, or used DIS frameworks once or twice), 24% (n\u0026thinsp;=\u0026thinsp;46) as intermediate (e.g. having engaged in DIS activities and applied frameworks multiple times, they had not led a DIS-focused project or proposal), and 13% (n\u0026thinsp;=\u0026thinsp;26) as advanced (e.g., having led grants or projects with DIS as a central research focus or incorporated DIS frameworks as a core part of study design).\u003c/p\u003e \u003cp\u003eSimilarly, among IN STEP consultees, 52% (n\u0026thinsp;=\u0026thinsp;25) identified as novices (e.g., no prior engagement with TER activities or frameworks), 27% (n\u0026thinsp;=\u0026thinsp;13) as advanced beginners (e.g., having participated in TER training or contributed to a TER project), 17% (n\u0026thinsp;=\u0026thinsp;8) as intermediate (e.g., having engaged in TER activities, but not led a TER-focused project or proposal), and 4% (n\u0026thinsp;=\u0026thinsp;2) as advanced (e.g., having led grants or projects with TER as a central research focus).\u003c/p\u003e \u003cp\u003e \u003cem\u003eType of support requested\u003c/em\u003e \u003c/p\u003e \u003cp\u003eAcross 302 consultation requests, 329 distinct support types were reported (requests could include multiple types). Most commonly was support related to grant proposals (n\u0026thinsp;=\u0026thinsp;177, 54%) and ongoing D\u0026amp;I projects (n\u0026thinsp;=\u0026thinsp;82, 25%). Additional requests included D\u0026amp;I mentoring and career development (n\u0026thinsp;=\u0026thinsp;44, 13%), support on publications (n\u0026thinsp;=\u0026thinsp;17, 5%), general program inquires (n\u0026thinsp;=\u0026thinsp;4, 1%), other support (e.g., dissertation support) (n\u0026thinsp;=\u0026thinsp;3, 1%), and Ongoing TER research project (n\u0026thinsp;=\u0026thinsp;2, 1%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Content Analysis: Consultation Functions \u0026amp; Forms\u003c/h2\u003e \u003cp\u003e \u003cem\u003eConsultation Functions\u003c/em\u003e \u003c/p\u003e \u003cp\u003eA total of 370 topic observations were identified across 108 consultation notes (multiple topics per note). The most common functions included implementation science applications (e.g., implementation strategies; applying DIS theories, models, and frameworks; adaptations etc.) (n\u0026thinsp;=\u0026thinsp;201, 55%) and grant development (e.g., study design; metrics \u0026amp; measures; identifying a co-investigator etc.) (n\u0026thinsp;=\u0026thinsp;113, 31%), while topics on analytical methods and evaluation (e.g., data analysis; qualitative/quantitative methods support etc.) (n\u0026thinsp;=\u0026thinsp;31, 8%) and professional development and training (e.g., publications, discussion of program services, general DIS education etc.) (n\u0026thinsp;=\u0026thinsp;25, 7%) were also present. (See Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eContent Analysis Results\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopic Discussed\u0026nbsp;(Consultation Functions)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (N\u0026thinsp;=\u0026thinsp;370)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eImplementation Science Application\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImplementation Strategies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModels \u0026amp; Frameworks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity and/or Stakeholder Engagement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImplementation Outcomes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImplementation Determinants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImplementation Outcomes Crosswalk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSustainability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdaptations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTeam Science/Team Effectiveness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgram Design\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDissemination Strategies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTeam mechanisms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntervention Selection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGrant Development\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy Design\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMetrics \u0026amp; Measures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeeking co-investigator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFunding opportunities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFuture grant proposal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnalytical Methods and Evaluation Support\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eData Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQualitative methods support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgram Evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuantitative methods support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProfessional Development and Training\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublication/Presentation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral D\u0026amp;I education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeeking mentor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCareer Development\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTypes of DIS Guidance Provided (Consultation Forms)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eFrequency (N\u0026thinsp;=\u0026thinsp;262)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePercentage (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDissemination \u0026amp; Implementation Concepts and Methods\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGuidance on selecting, applying, evaluating, and adapting implementation and/or dissemination strategies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGuidance on identifying and addressing implementation determinants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse of DIS tools (e.g., implementation logic model; implementation outcomes crosswalk)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGuidance on team science methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGuidance on sustainability methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProvided general D\u0026amp;I education (e.g., discussion of D\u0026amp;I topics and concepts, directing towards educational resources)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIdentify dissemination avenues (e.g., conference presentations)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProvide guidance on intervention selection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGuidance on selecting and applying D\u0026amp;I theories, models, frameworks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdapting D\u0026amp;I theories, models, and frameworks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStudy \u0026amp; Project Guidance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGuidance on study design\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeedback on grant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConnect with DIS co-investigator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotential funding opportunities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProvide feedback on program\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeedback on manuscript\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeedback on presentation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCommunity/Stakeholder Engagement Strategies\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConceptualizing and/or operationalizing stakeholder engagement methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGuidance on community-engagement methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisseminating findings to community and/or stakeholders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvaluating community/stakeholder engagement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMentorship/Career Development\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEstablishing co-investigator/mentorship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGeneral Career Development (e.g., submitting a K award etc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIdentify DIS mentor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTypes of Resources Shared\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eFrequency (N\u0026thinsp;=\u0026thinsp;113)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePercentage (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRelevant readings (e.g. journal articles, policy brief, grant RFA etc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeb resource (e.g. D\u0026amp;I models, webtools)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConnect with content expert\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation and training opportunities (e.g. workshop information, fellowship opportunities etc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOffer program support (e.g. Letter of Support, data analysis and interpretation)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eConsultation Forms\u003c/em\u003e \u003c/p\u003e \u003cp\u003eWe documented 262 instances of DIS guidance, categorized as consultation forms (not mutually exclusive). The most frequent consultation form was guidance on DIS concepts and methods (n\u0026thinsp;=\u0026thinsp;124, 47%) (e.g., selecting, applying, evaluating, and adapting implementation strategies, identifying and addressing implementation determinants etc.), followed by study and project guidance (n\u0026thinsp;=\u0026thinsp;96, 37%) (e.g., feedback on study design, grant proposals, and making connections with DIS co-investigators). Additional forms included community/stakeholder engagement strategies (n\u0026thinsp;=\u0026thinsp;28, 11%) (e.g., conceptualizing and operationalizing community/stakeholder methods) and mentorship/career development (n\u0026thinsp;=\u0026thinsp;14, 5%) (e.g., agreeing to be listed as a mentor on career development award). (See Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cem\u003eTypes of Resources Shared\u003c/em\u003e \u003c/p\u003e \u003cp\u003eAmong 109 documented resources, 45% (n\u0026thinsp;=\u0026thinsp;51) were relevant readings (e.g., journal articles, grant examples), 22% (n\u0026thinsp;=\u0026thinsp;25) were DIS-related webtools (e.g., the D\u0026amp;I Models in Health Webtool), 17% (n\u0026thinsp;=\u0026thinsp;19) were connections to content experts, and 12% (n\u0026thinsp;=\u0026thinsp;14) were educational resources. Letters of support were shared in two consultations (2%). (See Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Competency Mapping \u0026amp; Gap Analysis\u003c/h2\u003e \u003cp\u003e \u003cem\u003eCompetency Mapping\u003c/em\u003e \u003c/p\u003e \u003cp\u003eOf the total 54 DIS competencies (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), 25 were mapped to the consultation forms. Eleven forms aligned with multiple competencies, which were recorded in secondary columns (see Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Sub-forms were also captured (e.g., \u0026ldquo;Use of DIS tools\u0026rdquo; was broken down into guidance on logic models and outcomes crosswalks). Notably, of the two uncategorized competencies reported by Huebschmann and colleagues (2022), we were able to map one, \u0026ldquo;Apply theory and strategies from team science to promote team effectiveness in D\u0026amp;I research\u0026rdquo;, onto the consultation form \u0026ldquo;Guidance on team science methods\u0026rdquo;.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eDIS Competencies Mapped\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eConsultation Form\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompetency Section\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eCompetency\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCompetency Level\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCompetency Section\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCompetency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCompetency Level\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1. Guidance on selecting, applying, evaluating, and adapting implementation and/or dissemination strategies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection D: Practice-Based Considerations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIdentify and develop sustainable partnerships for D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSection D: Practice-Based Considerations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUse evidence to evaluate and adapt D\u0026amp;I strategies for specific populations, settings, contexts, resources, and/or capacities.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAdvanced\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1a. Guidance on evaluation methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection C: Design and Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIdentify and measure outcomes that matter to stakeholders, adopters, and implementers.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSection C: Design and Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIdentify common D\u0026amp;I measures and analytic strategies relevant to your research question(s).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1b. Guidance on documenting and evaluating adaptations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection D: Practice-Based Considerations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescribe how adaptations will be documented throughout the D\u0026amp;I research project.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSection D: Practice-Based Considerations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eExplain how to maintain fidelity of original interventions during the adaptation process.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2. Guidance on identifying and addressing implementation determinants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection A: Definition, Background, and Rationale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFormulate methods to address barriers and facilitators of D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3. Use of DIS tools (e.g., implementation logic model; implementation outcomes crosswalk)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eNot explicitly mapped, but aligns with broader guidance competencies (e.g., Section B: Theory and Approaches; Section C: Design and Analysis). Expanded to include sub-forms that were able to be mapped onto individual competencies.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3a. Guidance on completing/refining implementation outcomes crosswalk\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection B: Theory and Approaches\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCharacterize process models that support iterative cycles of implementation and adaptation based on learning.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSection C: Design and Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDevelop and assess processes and outcomes that support iterative cycles of implementation and bidirectional flow of information (e.g., learning health systems).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAdvanced\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3b. Guidance on developing implementation logic model for projects\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection B: Theory and Approaches\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescribe a process for designing for dissemination (planning for adoption, implementation, and sustainability during the intervention development stage).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4. Guidance on team science methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection B: Theory and Approaches\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eApply theory and strategies from team science to promote team effectiveness in D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5. Guidance on sustainability methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection C: Design and Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEffectively integrate the concepts of sustainability/sustainment and the rationale behind them in D\u0026amp;I study design.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSection C: Design and Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEvaluate and refine innovative scale-up and spread methods (e.g., technical assistance, interactive systems, novel incentives, and 'pull' strategies).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAdvanced\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6. Provided general D\u0026amp;I education (e.g., discussion of D\u0026amp;I topics and concepts, directing towards educational resources)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection A: Definition, Background, and Rationale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDefine and communicate dissemination and implementation (D\u0026amp;I) research terminology.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7. Identify dissemination avenues (e.g., conference presentations)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eNot explicitly mapped to competencies but aligns with broader guidance competencies (e.g., Section D: Practice-Based Considerations).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8. Provide guidance on intervention selection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection A: Definition, Background, and Rationale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDetermine which evidence-based interventions are worth disseminating and implementing.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9. Guidance on selecting and applying D\u0026amp;I theories, models, frameworks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection B: Theory and Approaches\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIdentify appropriate conceptual models, frameworks, or program logic for D\u0026amp;I change.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSection B: Theory and Approaches\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDescribe a process for designing for dissemination (planning for adoption, implementation, and sustainability during the intervention development stage).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10. Adapting D\u0026amp;I theories, models, and frameworks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection D: Practice-Based Considerations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescribe how adaptations will be documented throughout the D\u0026amp;I research project.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11. Guidance on study design\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection C: Design and Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIdentify and articulate the trade-offs between a variety of different study designs for D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSection C: Design and Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOperationalize hybrid effectiveness-implementation designs when appropriate to accelerate the implementation of evidence-based interventions in real-world settings.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAdvanced\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11a. Guidance on selecting, measuring, and determining implementation outcomes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection C: Design and Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIdentify common D\u0026amp;I measures and analytic strategies relevant to your research question(s).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSection C: Design and Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIdentify and measure outcomes that matter to stakeholders, adopters, and implementers.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11b. Review and provide feedback on measures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection C: Design and Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescribe gaps in D\u0026amp;I measurement and critically evaluate how to fill them.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAdvanced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11c. Guidance on data collection, analysis, and interpretation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection C: Design and Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescribe the application and integration of mixed-method (quantitative and qualitative) approaches in D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSection C: Design and Analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eApply common D\u0026amp;I measures and analytic strategies relevant for your research question(s) within your model/framework.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12. Feedback on grant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eNot explicitly mapped to competencies but aligns with broader guidance competencies (e.g., Section C: Design and Analysis \u0026amp; Section D: Practice-Based Considerations).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13. Connect with DIS co-investigator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection D: Practice-Based Considerations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIdentify and develop sustainable partnerships for D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14. Potential funding opportunities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eIndirectly aligns with sustainability and equity strategies in partnerships (e.g., Section D: Practice-Based Considerations).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15. Provide feedback on program\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eNot explicitly mapped to competencies but aligns with broader guidance competencies (e.g., Section C: Design and Analysis; Section D: Practice-Based Considerations).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16. Feedback on manuscript\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eNot explicitly mapped to competencies but aligns with broader guidance competencies (e.g., Section C: Design and Analysis; Section D: Practice-Based Considerations).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17. Feedback on presentation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eNot explicitly mapped to competencies but aligns with broader guidance competencies (e.g., Section C: Design and Analysis; Section D: Practice-Based Considerations).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18. Conceptualizing and/or operationalizing stakeholder engagement methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection D: Practice-Based Considerations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntegrate strategies within D\u0026amp;I research to facilitate meaningful stakeholder engagement (e.g., shared power, shared decision-making, co-learning).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSection D: Practice-Based Considerations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eDescribe the appropriate process for eliciting input from community-based practitioners for adapting an intervention.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19. Guidance on community-engagement methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection D: Practice-Based Considerations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntegrate strategies within D\u0026amp;I research to facilitate meaningful stakeholder engagement (e.g., shared power, shared\u003c/p\u003e \u003cp\u003edecision-making, co-learning).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSection D: Practice-Based Considerations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSummarize the importance of ethically and culturally competent clinical and community-based research in D\u0026amp;I science.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20. Disseminating findings to community and/or stakeholders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eNot explicitly mapped to competencies but aligns with broader guidance competencies (e.g., Section C: Design and Analysis; Section D: Practice-Based Considerations).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21. Evaluating community/stakeholder engagement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection D: Practice-Based Considerations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntegrate strategies within D\u0026amp;I research to facilitate meaningful stakeholder engagement (e.g., shared power, shared\u003c/p\u003e \u003cp\u003edecision-making, co-learning).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22. Establishing co-investigator/mentorship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection A: Definition, Background, and Rationale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescribe the range of expertise needed\u003c/p\u003e \u003cp\u003eto conduct D\u0026amp;I research (e.g., mixed-methods experience, economic, organizational, policy, clinical).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23. General Career Development (e.g., submitting a K award etc.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c7\" namest=\"c2\"\u003e \u003cp\u003eNot explicitly mapped to competencies but aligns with broader guidance competencies (e.g., Section C: Design and Analysis; Section D: Practice-Based Considerations).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24. Identify DIS mentor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSection D: Practice-Based Considerations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIdentify and develop sustainable partnerships for D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eGap Analysis\u003c/em\u003e \u003c/p\u003e \u003cp\u003eAmong the 24 mapped competencies with defined expertise levels, most were Intermediate (n\u0026thinsp;=\u0026thinsp;14, 58%), followed by Beginner (n\u0026thinsp;=\u0026thinsp;5, 21%) and Advanced (n\u0026thinsp;=\u0026thinsp;5, 21%). Most frequently observed competencies came from Section C: Design and Analysis (n\u0026thinsp;=\u0026thinsp;10, 63%) and Section D: Practice-Based Considerations (n\u0026thinsp;=\u0026thinsp;7, 44%).\u003c/p\u003e \u003cp\u003eFor example, \u0026ldquo;Guidance on study design\u0026rdquo; mapped to \u0026ldquo;Identify and articulate the trade-offs between a variety of different study designs for D\u0026amp;I research\u0026rdquo; (Section C, Intermediate). \u0026ldquo;Guidance on stakeholder engagement\u0026rdquo; mapped to \u0026ldquo;Identify and develop sustainable partnerships for D\u0026amp;I research\u0026rdquo; (Section D, Intermediate). Fewer competencies were observed in Section A: Definition, Background, and Rationale (n\u0026thinsp;=\u0026thinsp;4, 36%) and Section B: Theory and Approaches (n\u0026thinsp;=\u0026thinsp;3, 33%). (see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDIS Competency Gap Analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCompetency Sections (N\u0026thinsp;=\u0026thinsp;54)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eCompetencies Observed (N\u0026thinsp;=\u0026thinsp;25, 46%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eCompetencies not observed (N\u0026thinsp;=\u0026thinsp;29, 52%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpecific Competencies Observed (n\u0026thinsp;=\u0026thinsp;4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLevel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSpecific Competencies Not Observed (n\u0026thinsp;=\u0026thinsp;7)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLevel\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e\u003cb\u003eSection A: Definition, Background, and Rationale (N\u0026thinsp;=\u0026thinsp;11)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFormulate methods to address barriers and facilitators of D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExamine the importance of rapid research to advance D\u0026amp;I science concepts and directions.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDetermine which evidence-based interventions are worth disseminating and implementing.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDefine what is and what is not D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefine and communicate dissemination and implementation (D\u0026amp;I) research terminology.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDifferentiate between D\u0026amp;I research and other related areas, such as efficacy research and effectiveness research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eDescribe the range of expertise needed\u003c/p\u003e \u003cp\u003eto conduct D\u0026amp;I research (e.g., mixed-methods experience, economic, organizational, policy, clinical)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIdentify the potential impact of disseminating, implementing, and sustaining effective interventions, including assessments of equity and representativeness.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAssess, describe, and quantify (where possible) the context for effective D\u0026amp;I (setting characteristics, culture, capacity, and readiness).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIdentify existing gaps in D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIdentify the potential impact of scaling down (aka de-implementing) an ineffective but often used intervention.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSpecific Competencies Observed (n\u0026thinsp;=\u0026thinsp;3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eLevel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eSpecific Competencies Not Observed (n\u0026thinsp;=\u0026thinsp;6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eLevel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eSection B: Theory and Approaches (N\u0026thinsp;=\u0026thinsp;9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIdentify appropriate conceptual models, frameworks, or program logic for D\u0026amp;I change.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDescribe a range of D\u0026amp;I strategies, models, and frameworks.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDesign strategies to address the multi-level influences of health inequities as it relates to the implementation of an evidence-based intervention.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDescribe a process for designing for dissemination (planning for adoption, implementation, and sustainability during the intervention development stage).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDescribe the relationships between various organizational dimensions (e.g., climate, culture) and D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eExplain how knowledge from disciplines outside of health (e.g., business, marketing, and engineering) can help inform further transdisciplinary efforts in D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacterize process models that support iterative cycles of implementation and adaptation based on learning.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIdentify and articulate the interplay between policy and organizational processes in D\u0026amp;I.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIdentify core elements (effective ingredients) of effective interventions, and recognize risks of making modifications to these.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSpecific Competencies Observed (n\u0026thinsp;=\u0026thinsp;10)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eLevel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eSpecific Competencies Not Observed (n\u0026thinsp;=\u0026thinsp;6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eLevel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003e\u003cb\u003eSection C: Design and Analysis (N\u0026thinsp;=\u0026thinsp;16)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdentify and articulate the trade-offs between a variety of different study designs for D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDescribe the core components of external validity and their relevance to D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescribe the application and integration of mixed-method (quantitative and qualitative) approaches in D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdentify common D\u0026amp;I measures and analytic strategies relevant to your research question(s).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIdentify possible methods to address external validity in study design reporting and implementation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApply common D\u0026amp;I measures and analytic strategies relevant for your research question(s) within your model/framework.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eList the potential roles of mediators and moderators in a D\u0026amp;I study.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdentify and measure outcomes that matter to stakeholders, adopters, and implementers.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOperationalize hybrid effectiveness-implementation designs when appropriate to accelerate the implementation of evidence-based interventions in real-world settings.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdvanced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEffectively explain and incorporate concepts of de-adoption and de-implementation into D\u0026amp;I study design.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdvanced\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescribe gaps in D\u0026amp;I measurement and critically evaluate how to fill them.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdvanced\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEvaluate and refine innovative scale-up and spread methods (e.g., technical assistance, interactive systems, novel incentives, and 'pull' strategies).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdvanced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEffectively integrate the concepts of sustainability/sustainment and the rationale behind them in D\u0026amp;I study design.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescribe how to frame and analyze the context of D\u0026amp;I as a complex system with interacting parts.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDevelop and assess processes and outcomes that support iterative cycles of implementation and bidirectional flow of information (e.g., learning health systems).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdvanced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIncorporate methods of economic evaluation (e.g., implementation costs, cost-effectiveness) in D\u0026amp;I study design.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAdvanced\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSpecific Competencies Observed (n\u0026thinsp;=\u0026thinsp;7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eLevel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eSpecific Competencies Not Observed (n\u0026thinsp;=\u0026thinsp;9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eLevel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003e\u003cb\u003eSection D: Practice-Based Considerations (N\u0026thinsp;=\u0026thinsp;16)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdentify and develop sustainable partnerships for D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDescribe the importance of incorporating the perspectives of different stakeholder groups (e.g., patient/family, employers, payers, healthcare settings, public organizations, community, and policy makers).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescribe how adaptations will be documented throughout the D\u0026amp;I research project.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDescribe the concept and measurement of fidelity.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSummarize the importance of ethically and culturally competent clinical and community-based research in D\u0026amp;I science.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eArticulate the strengths and weaknesses of participatory research in D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntegrate strategies within D\u0026amp;I research to facilitate meaningful stakeholder engagement (e.g., shared power, shared\u003c/p\u003e \u003cp\u003edecision-making, co-learning).\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBeginner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDetermine when engagement in participatory research is appropriate with D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eUse evidence to evaluate and adapt D\u0026amp;I strategies for specific populations, settings, contexts, resources, and/or capacities.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAdvanced\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIdentify and apply techniques for stakeholder analysis and engagement when implementing evidence-based practices.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIdentify a process for adapting an intervention and implementation strategy prior to and during implementation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExplain how to maintain fidelity of original interventions during the adaptation process.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIdentify sites to participate in D\u0026amp;I studies, and negotiate or provide incentives to secure their involvement.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDescribe the appropriate process for eliciting input from community-based practitioners for adapting an intervention.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDescribe how to measure successful partnerships for D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDevelop strategies to promote equity in resource distribution across all external research partners, including community partners or other external organizations and the researcher\u0026rsquo;s institution.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIntermediate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSpecific Competencies Observed (n\u0026thinsp;=\u0026thinsp;1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eLevel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eSpecific Competencies Not Observed (n\u0026thinsp;=\u0026thinsp;1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eLevel\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNot Categorized (N\u0026thinsp;=\u0026thinsp;2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApply theory and strategies from team science to promote team effectiveness in D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eApply systems science and systems modeling approaches in D\u0026amp;I research.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Consultation Follow Up Data\u003c/h2\u003e \u003cp\u003e \u003cem\u003eConsultation Satisfaction\u003c/em\u003e \u003c/p\u003e \u003cp\u003eOf the 223 DISC consultation follow up surveys collected, 77 had completed satisfaction questions. Consultees rated their consultation experience using a 5-point Likert scale (1\u0026thinsp;=\u0026thinsp;Strongly Disagree to 5\u0026thinsp;=\u0026thinsp;Strongly Agree). Responses were highly positive: 100% agree consultants actively listened (n\u0026thinsp;=\u0026thinsp;77), 93.4% (n\u0026thinsp;=\u0026thinsp;71) strongly agreed the consultation was useful, and 90.9% (n\u0026thinsp;=\u0026thinsp;70) strongly agreed the meeting was timely and that they would recommend the service. Somewhat lower agreement (84.4%, n\u0026thinsp;=\u0026thinsp;65) was seen for post-meeting collaboration follow-through (See Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). One consultee shared: \u003cem\u003e\u0026ldquo;DISC consultation helped me establish my first connection with a DISC expert, from which a mentor-mentee relationship was developed (and still is). Through this relationship I was able to tailor my K01 proposal with strong Implementation Science focus. The proposal was completed and submitted\u0026rdquo;.\u003c/em\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eDISC Consultation Satisfaction Ratings\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStrongly Disagree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSomewhat Disagree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNeither Agree/Disagree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSomewhat Agree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStrongly Agree\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe consultation meeting was scheduled in a timely manner.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e70 (90.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMy immediate needs were addressed during this first consultation.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (11.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e66 (86.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe consultation meeting was useful.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e71 (93.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe consultant addressed my questions clearly and completely.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e70 (92.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI understand my steps or action items.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (11.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e53 (86.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThere is a clear continuation plan to keep my work moving forward.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (15.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e62 (80.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResources or tools mentioned during the consultation were shared afterwards.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (9.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e68 (89.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe consultation improved my understanding of D\u0026amp;I frameworks and models.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (12.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e44 (88.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe consultant actively listened to my questions and description.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e75 (100.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConnections and/or collaborations offered during the meeting were shared afterwards.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (7.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e65 (84.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI would recommend the DISC consultation service to my colleagues.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e70 (90.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe consultation improved my ability to apply D\u0026amp;I frameworks and models.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eNote.\u003c/em\u003e Participants rated each item on a 5-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). D\u0026amp;I\u0026thinsp;=\u0026thinsp;Dissemination and Implementation. Data presented as a frequency.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor IN STEP, there were a total of 13 follow up surveys collected. All respondents selected the highest possible score across satisfaction with the consultation service (\u0026ldquo;Extremely satisfied\u0026rdquo;), perceived value of the consultation (\u0026ldquo;Very valuable\u0026rdquo;), and likelihood to recommend the service (\u0026ldquo;Extremely likely\u0026rdquo;). Due to uniformity in responses, these data are summarized narratively.\u003c/p\u003e \u003cp\u003e \u003cem\u003eProject Outcomes\u003c/em\u003e \u003c/p\u003e \u003cp\u003eDISC and IN STEP also collected data on project status. Six non-mutually exclusive categories were shared across the two programs: Grant Proposal Submitted (34.1%, n\u0026thinsp;=\u0026thinsp;15), Grant Submission-In Progress (25.0%, n\u0026thinsp;=\u0026thinsp;11), Other (15.9%, n\u0026thinsp;=\u0026thinsp;7), Grant Funded (13.6%, n\u0026thinsp;=\u0026thinsp;6), Paper Submission-In Progress (6.8%, n\u0026thinsp;=\u0026thinsp;3), and Paper Submitted (4.5%, n\u0026thinsp;=\u0026thinsp;2). (See Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study expands our understanding of DIS consultations by examining core functions and forms of consultations across three DIS capacity-building programs. While several formal DIS training programs have evaluated educational activities (e.g., coursework, seminars, mentoring), less is known about the consultation services embedded within these programs (\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Given that consultations represent approximately 67% of DIS capacity-building activities (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), this study fills a critical gap by detailing consultation content, guidance forms, and alignment with DIS competencies (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). These findings contribute to a more nuanced understanding of consultations as a central DIS capacity-building mechanism.\u003c/p\u003e \u003cp\u003eProgram metrics showed that most consultees were faculty at academic institutions (ranging from early-career to senior investigators) or clinicians/healthcare professionals working in healthcare systems, often identifying as novices. Consultation largely supported ongoing DIS projects and grant proposals. Notably, the IS Hub\u0026rsquo;s focus on Ending the HIV Epidemic projects likely contributed to its higher proportion of project-based consultations.\u003c/p\u003e \u003cp\u003eFollow up data from DISC and IN STEP consultations indicated high levels of satisfaction, with strong ratings across satisfaction dimensions. Project outcomes suggested early signs of consultation impact: 34.1% of DISC and IN STEP consultees reported grant proposal submissions, and 13.6% reported funded grants following consultation. These findings reinforce consultations\u0026rsquo; potential value not only for education but also for advancing tangible research outputs (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eContent analysis systematically identified consultation functions (topics discussed), forms (guidance provided), and resources shared (\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Implementation science applications and grant development emerged as the most common functions; DIS methods guidance and study/project support were the most frequent forms. Shared resources included relevant readings, DIS web tools, expert connections, and educational opportunities. Although letters of support were infrequently shared during sessions, they remain a resource offered by these programs outside of the consultation service and not explicitly captured through consultation notes.\u003c/p\u003e \u003cp\u003eMapping consultation forms to DIS competencies allowed objective evaluation of how these consultations align with DIS training standards (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). The gap analysis showed concentration in competencies related to Design and Analysis and Practice-Based Considerations, with fewer consultations addressing foundational theory and background. Additionally, consultations were predominantly aligned with intermediate-level competencies, with fewer consultations mapping onto beginner- and advanced-level competencies.\u003c/p\u003e \u003cp\u003eApplying the Core Functions and Forms framework to consultations helped to clarify their role among DIS capacity building efforts (\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e) and offers a framework for evaluation (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Identifying gaps in consultation coverage presents an opportunity to enhance training and foundational DIS skill development.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Limitations\u003c/h2\u003e \u003cp\u003eDespite generating valuable insights, this study has limitations. First, while the three programs share administrative resources and commonalities, their distinct structures and processes complicated data synthesis. Developing systematic methods to track project outcomes across programs could improve data comparability and capture long-term impacts.\u003c/p\u003e \u003cp\u003eSecond, consultation notes varied in detail, limiting the ability to fully capture consultation nuances. Future efforts could involve recording consultations and using AI tools to generate transcripts and meeting summaries to enhance the quality and comprehensiveness of consultation records. This approach could reduce the burden of manual note-taking, ensure consistency, and provide valuable resources for training future consultants. However, AI-generated transcripts and notes must be validated by program coordinators to mitigate inaccuracies. This is because AI transcription tools may struggle with specialized terminology, multiple speakers, or poor audio quality, potentially resulting in incomplete or misleading data (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThird, although ChatGPT supported the content analysis (organizing codes, summarizing frequencies, proposing categories), all outputs were reviewed and refined by the study team. Clarification were often needed to avoid misclassification due to database formatting or code ambiguities. While this validation minimized AI biases, reliance on AI tools still poses risks of oversimplification or contextual misinterpretation (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Future research should continue to explore best practices for integrating generative AI tools into qualitative and mixed methods research, including structured prompts, validation strategies, and mitigation of AI limitations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Implications for Future Research and Practice\u003c/h2\u003e \u003cp\u003eFindings suggest several practical strategies for optimizing DIS consultation services. First, improving consultation tracking and standardization could enhance program evaluation and demonstrate impact. Pre/post surveys, qualitative interviews, and periodic follow ups would provide richer insights into consultation contributions to skill-building and project outcomes. Second, the gap analysis identified lower coverage of competencies related to Definition, Background, and Rationale and Theory and Approaches. Since these domains serve as the foundation for DIS, consultation services could intentionally integrate theoretical and background content into sessions (e.g., onboarding modules for newcomers) or complementary training activities appropriate across career stages and experience levels (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Third, formalizing resource-sharing practices, such as curated repositories of recommended readings and webtools, could streamline consultations (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Expanding mentorship networks and expert connections would also strengthen capacity-building efforts (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Finally, these results can inform the development of standardized DIS consultation frameworks that can be adapted and scaled across different institutions (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Shared consultation protocols, structured resource sharing, and standardized evaluation indicators would strengthen individual programs and foster a broader DIS infrastructure.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study provides foundational insights into DIS consultations, clarifying their functions and forms within capacity-building efforts. By improving consultation tracking, standardizing processes, and tailoring services across skill levels, programs can further enhance DIS training and workforce development. Future research should explore longitudinal consultation outcomes, examine the relationship between guidance types and project success, and refine scalable consultation models to maximize DIS capacity-building impact.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eDissemination and implementation science (DIS); Implementation Research Institute (IRI); Mentored Training for Dissemination and Implementation Research in Cancer (MT-DIRC); Knowledge Translation Summer Institute (KTSI); Training in Dissemination and Implementation Research in Health (TIDIRH); Dissemination and Implementation Science Center (DISC);\u003cem\u003e\u0026nbsp;\u003c/em\u003eSan Diego Center for AIDS Research Implementation Science Hub (SD CFAR IS Hub); Implementation Science and Team Effectiveness in Practice (IN STEP); National Institutes of Health (NIH); National Institute of Mental Health (NIMH); National Institute of Allergy and Infectious Diseases (NIAID); Artificial Intelligence (AI); Large Language Models (LLMs); Ending HIV Epidemic (EHE);\u003cem\u003e\u0026nbsp;\u003c/em\u003e \u003cem\u003e\u0026nbsp;\u003c/em\u003e\u0026nbsp; \u0026nbsp;Team effectiveness research (TER); Dissemination and implementation (D\u0026amp;I)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request [KS]. The datasets presented in this article are not readily available because the project is still ongoing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding for this work was supported by: The University of California San Diego Altman Clinical and Translational Research Institute Dissemination and Implementation Science Center (DISC) (UL1 TR001442); University of California San Diego ImplementatioN Science and Team Effectiveness in Practice (IN STEP) Children’s Mental Health Research Center (P50MH126231); and the San Diego Center for AIDS Research Implementation Science Hub (P30-AI036214 CFAR Supplement).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKS \u0026amp; BR contributed by designing the study. KS contributed by leading the data analysis and interpretation. KS, IB, KC, CV, CG, LC, ZD, \u0026amp; AB contributed by collecting and synthesizing consultation data. KS \u0026amp; IB contributed to coding consultation notes. KS, IB, NS, GA, LBF, \u0026amp; BR contributed to development, refinement, and finalization of the qualitative codebook. KS, IB, ZD, NS, GA, LBF, MS, CV, LC, AB, CG, KC, \u0026amp; BR contributed to editing multiple drafts of the paper. All authors revised the paper multiple times and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to acknowledge the DISC, IS Hub, and IN STEP consultation teams for their contributions to the consultation services that made this work possible. Their expertise, commitment to dissemination and implementation science, and support of DIS capacity building efforts were instrumental to this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNorton WE, Lungeanu A, Chambers DA, Contractor N. Mapping the growing discipline of dissemination and implementation science in health. Scientometrics. 2017 Sep;112(3):1367\u0026ndash;90. \u003c/li\u003e\n\u003cli\u003eProctor EK, Chambers DA. Training in dissemination and implementation research: a field-wide perspective. Transl Behav Med. 2017 Sep 1;7(3):624\u0026ndash;35. \u003c/li\u003e\n\u003cli\u003eBaumann AA, Adams DR, Baldwin LM, Tabak RG, Malone S, Kepper MM, et al. A mapping review and critique of the literature on translation, dissemination, and implementation capacity building initiatives for different audiences. Implement Sci Commun. 2025 Apr 3;6(1):34. \u003c/li\u003e\n\u003cli\u003eBeidas R, Bennett I, Fleischer L, Day T, Meisel Z. 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J Med Internet Res. 2024 Jul 25;26:e59050. \u003c/li\u003e\n\u003cli\u003eAllen CG, Sterba K, Oppenheimer S, Hanson RF, Coen E, Gimbel R, et al. Development of the Dissemination and Implementation Science Collaborative (DISC): Opportunities to enhance implementation science capacity among researchers and practitioners in South Carolina. J Clin Transl Sci. 2024 Jan;8(1):e161. \u003c/li\u003e\n\u003cli\u003eTabak RG, Bauman AA, Holtrop JS. Roles dissemination and implementation scientists can play in supporting research teams. Implement Sci Commun. 2021 Jan 15;2(1):9. \u003c/li\u003e\n\u003cli\u003eLeppin AL, Baumann AA, Fernandez ME, Rudd BN, Stevens KR, Warner DO, et al. Teaching for implementation: A framework for building implementation research and practice capacity within the translational science workforce. J Clin Transl Sci. 2021;5(1):e147. \u003c/li\u003e\n\u003cli\u003eGresty P. The Limitations of AI Transcription in Research Work [Internet]. The Typing Works. 2025 [cited 2025 Apr 16]. Available from: https://thetypingworks.com/the-limitations-of-ai-transcription-in-research-work/\u003c/li\u003e\n\u003cli\u003eKuckartz U, R\u0026auml;diker S. Integrating Artificial Intelligence (AI) in Qualitative Content Analysis. In: Qualitative content analysis: Methods, practice and using software [Internet]. Beltz Juventa; 2024. Available from: https://qca-method.net/documents/kuckartz-raediker-2024-integrating-ai-in-qualitative-content-analysis.pdf\u003c/li\u003e\n\u003cli\u003eDarnell D, Dorsey CN, Melvin A, Chi J, Lyon AR, Lewis CC. A content analysis of dissemination and implementation science resource initiatives: what types of resources do they offer to advance the field? Implement Sci. 2017 Nov 21;12(1):137. \u003c/li\u003e\n\u003cli\u003eL\u0026rsquo;Hotta AJ, Jacob RR, Mazzucca-Ragan S, Glasgow RE, Straus SE, Norton WE, et al. Building capacity in dissemination and implementation research: the presence and impact of advice networks. Implement Sci IS. 2024 Nov 29;19(1):78. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"implementation-science-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iscm","sideBox":"Learn more about [Implementation Science Communications](https://implementationsciencecomms.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ISCM/default.aspx","title":"Implementation Science Communications","twitterHandle":"@ImplementSci","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Dissemination, Implementation, Capacity Building, Consultation","lastPublishedDoi":"10.21203/rs.3.rs-6559185/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6559185/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The number of Dissemination and Implementation Science (DIS) capacity building programs is increasing worldwide. These programs aim to enhance diverse DIS skills through a variety of activities. Our team’s systematic review of DIS programs determined that DIS consultations were offered across 67% of programs, yet their specific roles in capacity development were not well defined. This mixed methods study aimed to identify and categorize the functions and forms of consultation activities across three DIS capacity building programs at the University of California San Diego that varied in content focus and infrastructure and then to map findings onto DIS competencies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e Consultation notes from the three programs were extracted for content analysis to identify discussion topics, DIS guidance provided, and resources shared. Generative artificial intelligence (ChatGPT Plus) facilitated content analyses with multiple rounds of validation from program consultants to refine and finalize themes. Themes were categorized into consultation functions and forms. Forms were mapped onto DIS competencies and a gap analysis was conducted to identify areas for improvement. Program metrics were used to further contextualize findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A total of 108 consultation notes were analyzed across the three programs. The most common types of support requested related to grant proposals (54%) and ongoing D\u0026amp;I projects (25%). Consultation discussion topics most frequently involved applying implementation science principles (55%) grant development (31%), guidance centered on DIS methods (47%), and study/project design (37%). Consultation guidance was most often aligned with intermediate-level DIS competencies (58%), primarily in the design and analysis and practice-based considerations domains.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e These findings highlight the nature of DIS consultation services, particularly among those seeking support for grant proposals and ongoing implementation projects. Consultations primarily addressed intermediate-level competencies within the domains of design, analysis, and practice-based implementation strategies, indicating a clear opportunity to strengthen support for both foundational and advanced skill development. These results suggest the need for scalable consultation frameworks, improved tracking systems, and tiered training resources to optimize the reach and impact of DIS capacity-building efforts.\u003c/p\u003e","manuscriptTitle":"Beyond the Surface of Capacity Building: A Mixed-Methods Study of the Core Functions and Forms of Dissemination and Implementation Science Consultations","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-13 08:41:04","doi":"10.21203/rs.3.rs-6559185/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revision","date":"2025-06-06T03:23:32+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-05-15T14:30:36+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-08T12:34:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-01T05:10:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Implementation Science Communications","date":"2025-04-29T15:40:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"implementation-science-communications","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"iscm","sideBox":"Learn more about [Implementation Science Communications](https://implementationsciencecomms.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ISCM/default.aspx","title":"Implementation Science Communications","twitterHandle":"@ImplementSci","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"96cc076d-ef29-48ee-83bb-27fe58482a53","owner":[],"postedDate":"May 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-08-25T16:34:59+00:00","versionOfRecord":{"articleIdentity":"rs-6559185","link":"https://doi.org/10.1186/s43058-025-00775-0","journal":{"identity":"implementation-science-communications","isVorOnly":false,"title":"Implementation Science Communications"},"publishedOn":"2025-08-18 16:29:24","publishedOnDateReadable":"August 18th, 2025"},"versionCreatedAt":"2025-05-13 08:41:04","video":"","vorDoi":"10.1186/s43058-025-00775-0","vorDoiUrl":"https://doi.org/10.1186/s43058-025-00775-0","workflowStages":[]},"version":"v1","identity":"rs-6559185","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6559185","identity":"rs-6559185","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}