Integrating Motivational Interviewing into Community Coalition Technical Assistance: The Coalition Check-Up

Abstract

Community coalitions often form as vehicles to support inclusive community change. Yet, community coalition work is complex, and intensive technical assistance (TA) is potentially cost-prohibitive to sustain. A comprehensive review suggests a data-informed approach with “just-enough” contact between coalition partners and technical assistance providers that integrates Motivational Interviewing into interactions may be effective. As a result, we developed and tested the Coalition Check-Up (CoCU), a cyclical 4-step TA model to support all kinds of community coalitions. The current study examines implementation fidelity of the CoCU TA model, including its dosage, adherence to utilizing the data-informed tools, and quality by investigating the degree to which Motivational Interviewing skills were integrated into TA provider – coalition leader interactions. Thirty-two coalitions participated in this study. All coalitions received CoCU TA. Data from meeting recordings was coded with the MITI and data reported by TA providers that described TA provider interactions with coalition leaders and coalitions were used in this study. We found that coalitions received a high dosage of the CoCU TA model. The data tools were used with a high level of adherence, and MI behaviors were integrated at a modest to strong level. This novel study suggests applicability of MI in additional non-therapeutic contexts.

Introduction

Community coalitions are groups of individuals representing many organizations and agencies who unite around a specific cause or goal. Coalitions leverage shared resources, expertise and power to exert greater influence in addressing complex community challenges. Prevention focused coalitions often include representatives from mental and physical health agencies, education, social services, law enforcement, the faith community, parents, youth, and other youth-serving organizations (Center for Communities That Care, 2019; 2002–2025). Representation within the community is vital to understand community needs and create buy-in for change (Penn State Extension, 2023). These collaborative groups serve many functions in the community, including identifying priorities, action planning and implementing activities or programs to promote positive emotional, behavioral, and physical health for youth (Butterfoss & Kegler, 2002; Chilenski et al., 2023; Foster-Fishman et al., 2001). Community coalitions are prevalent, with approximately 100 functioning coalitions in each state (CADCA, 2016), and researchers have noted their essential role in the public health and prevention delivery system to improve health and wellness outcomes for youth and families (Wandersman et al., 2012).

Community coalition work has been complex, and the most well-documented evidence-based coalition models such as Communities That Care and PROSPER, have included an external implementation support expert at 25% FTE to support coalitions (Chilenski et al., 2020). This implementation support provider (i.e., TA provider) is often connected to an intermediary or university center and teaches or coaches practitioners how to build, implement, and sustain specific coalition models (Hawkins et al., 2008; Spoth et al., 2004). Depending on the model, the relationship between the TA provider and the coalition varies in contact frequency and function, however it often includes both scheduled and on-request phone or virtual calls, and in-person visits to coalition meetings to provide training and support. The TA provider functions as a subject-matter expert, a consultative resource for guidance, and a collaborative thought-partner in the development and implementation of initiatives for both coalition leadership and coalition members. Despite the work that has shown TA and coaching crucial for success (Fixsen et al., 2005; Wandersman & Scheier, 2024), this resource level has made TA and coaching expensive and potentially cost-prohibitive to sustain.

Each community is unique, and many types of community coalitions exist. With the importance of creating positive relationships between TA providers and lead implementers to support knowledge and skill growth (Chilenski et al., 2016; Metz et al., 2022) and the importance of promoting efficient interactions, we must ask ourselves, “Can we develop a lower-intensive TA model to effectively support all kinds of community coalitions?” Consequently, the aims of this study were to present the literature that was used to build the Coalition Check-Up (CoCU) TA model, a model that utilizes Motivational Interviewing (Miller & Rollnick, 2023) and audit- and-feedback (Sarkies et al., 2023) as core implementation strategies to support interactions between community coalitions and TA providers, and to examine the implementation fidelity of the CoCU in its recent randomized trial (Brown et al., 2021).

Why use motivational interviewing with coalitions?

MI is a person-centered, skills-based, and goal-oriented technique used to help individuals resolve ambivalence and enhance motivation for change (Miller & Rollnick, 2023). Initially developed as a therapeutic approach for individuals with alcohol use disorder (Miller, 1983), MI has since been adapted for a range of contexts, including organizational change and systems-level implementation (Arbuckle et al., 2020; Grimolizzi-Jensen, 2018), as well as implementation support settings such as the Family Check-Up (Dishion et al., 2003), Classroom Check-Up (Reinke et al., 2011), and the PATHS to PAX program and intervention (Reinke et al., 2012) to create a working alliance, assess practices, share feedback, provide consultation, and support implementation fidelity (Lee et al., 2014).

Coalitions frequently encounter challenges such as competing priorities, high staff turnover, strained education and social service systems, and local political dynamics that can slow or stall progress (Bryant, 2024; Kadushin et al., 2005; Kegler et al., 2010; Lubienski & Perry, 2019; Turri et al., 2016). TA providers can provide implementation support through these challenges but without sufficient buy-in, efforts may be perceived as externally imposed, leading to defensiveness, disengagement, or procedural compliance (Arbuckle et al., 2020). The emphasis on collaboration, autonomy, and evoking motivation in MI aligns closely with the needs and goals of community coalitions receiving implementation support (Katz & Wandersman, 2016; Keener, 2007).

The foundation of the coalition check-up: proactive, regular contact

In forming the foundation of the CoCU Model, previous research suggests that regular contact with TA providers is important (Chilenski et al., 2020); however, the ideal level needed to support positive coalition progress remains unclear (Scott et al., 2022). While some studies showed positive associations between TA dosage and coalition capacity, others have found no significant or sustained effects (Chilenski et al., 2020, M.E. Feinberg, Ridenour et al., 2008; Scott et al., 2022). Additionally, improvements sometimes diminished after TA support ended even with higher TA dosage (Scott et al., 2022). Overly intensive TA may undermine long-term sustainability, while insufficient contact may fail to build the momentum for long-term change (Scott et al., 2022).

Given this mixture of findings, our prior experience with the PROSPER model that encouraged two TA provider interactions with coalition leaders each month and attendance at every coalition meeting (Chilenski et al., 2020), our focus on sustained coalitions, and that we were not coaching coalitions to maintain fidelity to a particular model, we expected that a regular TA contact schedule that included more than e-mail and phone contact, but was less than what was done in PROSPER, was necessary. Consequently, we designed the CoCU model to have 16 TA provider contacts over the course of a year – one phone or web-based contact each month between TA providers and coalition leaders, and four in person or web-based contacts between TA providers and coalitions. We conceived this level of contact to be “just-enough” contact with coalitions and coalition leaders.

The two primary implementation strategies inside coalition check-up interactions: audit-and-feedback with motivational interviewing

With 16 annual contacts, we designed interactions to be efficient and focused on positive collaborative working relationships (S. M. Chilenski et al., 2025). Coalitions and TA providers needed to quickly identify potential improvement areas, determine intervention strategies to realize improvement, motivate movement on these intervention plans, and build capacity to successfully implement these plans. Efficient data-informed decision-making processes and continual motivation are central to the success of this approach.

Audit and feedback as an implementation strategy

Using data to make improved and informed health-related decisions has increased over time (Wu et al., 2020), yet little is known about how to best integrate this practice in a community collaborative context (Harrison & Pardo, 2021). Community collaboratives have experienced some success using data to track progress and provide direction for selecting, planning, implementing, and evaluating evidence-based programs (Chilenski et al., 2020; Fagan et al., 2009; Parker et al., 2025; Quinby et al., 2008); the CoCU extended this data-for-decision-making practice to supporting TA with community coalitions.

Using data for decision-making can be framed in the context of audit and feedback, a practice that includes continuous data collection, data review, discussion, and decision-making (Brown et al., 2021). Audit and feedback has been a promising but understudied strategy with inconclusive evidence when used in collective decision-making (Sarkies et al., 2023; Stone et al., 2020); evidence has suggested that data is not always reviewed carefully and may not be used when making decisions. Consequently, to ensure use of audit and feedback, we explicitly and concretely infused data into every TA provider interaction with coalitions and coalition leaders.

Motivational interviewing as an implementation strategy

Positive, collaborative relationships are widely recognized as being foundational to effective TA in community-based implementation efforts (Aldridge et al., 2023; Chilenski et al., 2016; Metz et al., 2022). Rather than relying solely on step-by-step guidance, effective TA integrates strategies that emphasize empathy, active and reflective listening, and responsiveness to local context to promote coalition engagement, learning, and sustainability (Le et al., 2016). Observational research on prevention coalitions has shown strong collaborative working relationships between TA providers and coalition leaders are associated with improved internal functioning, greater trust, and more successful implementation over time (Chilenski et al., 2016). Collaborative relationships can also help coalitions formulate and drive their own decision-making strategies (Strompolis et al., 2020). Coalitions that are empowered to identify local needs, set priorities, and implement contextually relevant strategies are more likely to foster community buy-in, sustain engagement, and produce lasting outcomes (S. M. x. Chilenski et al., 2025; Hawkins et al., 2002; Watson & Foster-Fishman, 2013).

Creating positive collaborative working relationships that stimulate and reinforce forward movement (i.e., “change”) can be framed in the context of MI and utilizing MI as a core implementation strategy may promote positive collaborative working relationships in a systematic way, rather than leave it to chance. MI skills include both relational and technical components (Miller & Rollnick, 2023), both relevant in a coalition context. The relational component has been referred to as “MI Spirit” and includes developing a context that promotes empathy, understanding, and partnership, including recognizing the coalition and the coalition leader as experts. The technical component, referred to as “MI Skills” includes developing a context that enhances the coalition’s motivation to move their action plans and planned improvements forward, (i.e., “change talk”) rather than sustaining the status quo and maintaining current levels of coalition activity, process, and work (i.e., “sustain talk”) (Miller & Rollnick, 2023).

Rather than being directive and instructive, MI’s conversation skills include asking open-ended questions, summarizing, and reflective listening. When combined with statements that (a) emphasize the skills and abilities of the coalition and coalition leader (i.e., affirmation), (b) share power, instead of placing the TA provider as the one in charge (i.e., seek collaboration), and (c) emphasize the coalition’s and coalition leader’s expertise and ability to implement their plans (i.e., emphasize autonomy), the TA interaction would promote the exploration of ambivalence which increases motivation and commitment to being successful in their work (i.e., “change) (Miller & Rose, 2009). It is also important that TA providers do not try to persuade or convince a coalition and coalition leader to undertake certain activities or confront them. Consequently, we explicitly and concretely infused Motivational Interviewing into every TA provider interaction so that CoCU TA model uses MI as a key component in all processes and decision-making. When integrated into TA, MI helps providers navigate the complex dynamics of community collaboration by identifying barriers, amplifying successes, encouraging change talk, and reinforcing confidence in their ability to implement solutions (Reinke et al., 2011). This approach reflects best practices in community capacity coaching by promoting local ownership and providing TA support as coalitions construct their own solutions and build internal capacity (Strompolis et al., 2020).

The current study

The current study examined the implementation of a low-burden, efficient TA system to support community coalitions across three years. Building on previous research, we developed a cyclical, four-step process consisting of 16 TA provider contacts that typically unfold across one year before repeating (Figure 1). Step 1 started with data collection, collecting information about coalition functioning, resources, and community change activities. Step 2 moves the coalition into reviewing the summarized data in a Feedback Summary and identifying priorities for change. In Step 3, coalitions refer to research evidence to write an action plan to successfully address the identified priority. In Step 4, coalitions implement the action plan. Throughout this process, a designated TA provider interacts with coalition leaders and coalitions to bring the data- and evidence-informed tools into the process and use MI Spirit and skills guide conversations with coalition leaders in the moment.

Figure 1.

The four-step, cyclical coalition Check-Up data feedback and technical support process.

We used three research questions to examine the implementation of the CoCU. We first investigated dosage; how many meetings occurred with TA providers? Second, we investigated adherence, how often did TA providers utilize the data-informed tools? Third, we examined quality, how well did TA providers integrate the technical and relational components of MI during their interactions with coalition leaders?

Method

We used a single group posttest design and drew from the 34 of 68 coalitions that were randomly assigned to receive the CoCU TA model intervention (Brown et al., 2021). Coalitions needed to have been in existence for at least one year; have held at least four coalition meetings annually with multiple sectors in attendance; have designated a coalition leader (paid or unpaid); have included promoting positive youth development or preventing adolescent substance use as part of their mission; have been willing to participate in CoCU activities including being randomly assigned to receive or not receive CoCU TA. Of the 34 coalitions that were randomly assigned to the intervention condition, one coalition disbanded within two months of the study start and dropped from the study; one additional coalition dropped three months later, leading to 32 coalitions in the current study. All study procedures were approved by The Pennsylvania State University Institutional Review Board, determined as the single IRB for this project.

Coalitions were recruited by the study PI and the Evidence-based Prevention and Support team in Penn State University’s Prevention Research Center through e-mail communications, coalition meetings, phone calls, one-on-one and small-group web meetings, and in-person visits. We recruited a diverse coalition sample; see Table (supplementary material). Coalitions’ service areas ranged from small, rural school districts to neighborhoods in densely populated cities, to counties and clusters of counties with populations ranging from 1,171 to 558,979. When recruited, coalitions were operating for between one and 37 years. Coalitions varied in model type. A majority had received funding to support activities and received TA.

Intervention procedures: Coalition Check-Up model overview

The CoCU follows a cyclical, four-step process (Figure 1). Throughout, a designated TA provider interacts with coalitions and their leaders to facilitate capacity building, problem-solving, and decision-making using data-informed methodologies (Brown et al., 2021).

Step 1: data collection

The initial phase of the CoCU process involves data collection on coalition activities, programs, strategies, capacity, and organizational structure. Participation is voluntary. Data are synthesized into a site-specific CoCU Feedback Summary (Chilenski & Brown, 2021), including visualizations with descriptions of each item and coalition means for reference. A color-coding system and dashboard allow for easy identification of strengths and challenges.

Step 2: data review

In this phase, the TA provider guides coalition leaders through the Feedback Summary following their preferences to identify priority areas for improvement. By the end of the meeting, the coalition leader identifies a small subset of issues to share with the coalition, including areas of strength and potential areas of growth. The coalition leader and TA provider present key issues to the full coalition in a semi-structured conversation following coalition leader strategy recommendations. The coalition works with the TA provider to select one improvement priority.

The TA provider acts as a facilitator, encouraging coalition-driven decisions. The TA provider emphasizes that the coalitions are the experts in their community and have the knowledge and expertise to interpret and make decisions with their Feedback Summary. The TA provider uses MI techniques such as seeking collaboration, emphasizing autonomy, and cultivating change talk during this process. Coalition members are encouraged to use an explicit consensus-building strategy, Gradients of Agreement, to make decisions (Kaner, 2018). If consensus was not reached, further discussion occurs to encourage change talk and agreement.

Step 3: data-based decision-making and action planning

Once a coalition selects a priority, Step 3 focuses on developing an evidence-informed action plan. The TA provider meets with the coalition leader to introduce data-informed materials such as the CoCU Guidebook (Brown & Chilenski, 2022) and Action Planning Worksheets (S. M. Chilenski, Fausey et al., 2024) and to discuss strategies to engage the coalition. Action planning begins with identifying underlying challenges, brainstorming potential solutions based on best practices outlined in the Guidebook. Coalition members use the Gradients of Agreement (Kaner, 2018) method again, as needed. Then, coalitions develop a step-by-step implementation plan, assigning responsibilities and defining success metrics.

Step 4: action plan implementation

Step 4 occurs over the remainder of the year, or until the coalition completes the action plan. Coalitions implement their chosen strategy with ongoing support from the TA provider, which includes monthly check-ins with coalition leaders and two coalition meetings. The Action Planning Progress Tool (Fausey et al., 2024) documents progress through notes and a numerical, color-coded rating which allows the TA provider to tailor support based on progress, employing MI to sustain momentum. While the CoCU process can span one year, Step 4 does not need to be completed before reinitiating Step 1. This cyclical structure ensures continuous improvement and adaptation based on coalition needs.

Protocol development and training of TA providers

We integrated MI techniques into CoCU training and instruction materials (Chilenski, Fausey et al., 2024). Instruction materials included scripts and annotated agendas tailored to each prescribed touchpoint. We developed a crosswalk with CoCU content and specific MI techniques to ensure alignment. Techniques such as emphasizing autonomy, increasing partnership, seeking collaboration, asking open-ended questions, giving affirmations, providing simple and complex reflections, cultivating change talk, showing empathy, setting goals, and giving information are mapped for each interaction. We included language prompts to assist TA providers in successfully utilizing MI techniques throughout their interactions.

Before starting the CoCU intervention, TA providers received two, two-hour trainings from an MI trainer. Training covered MI fundamentals and included opportunities to role-play. Following the MI training, TA providers practiced these techniques in mock meetings, using volunteers familiar with coalition work. These sessions were recorded and reviewed by the project PI and MI trainer, who provided informal feedback. To support ongoing skill development, we held monthly MI booster sessions. Audio recordings of coalition leader and coalition meetings were used to facilitate peer learning and enhance MI proficiency. Role-playing continued using actual scenarios to help TA strengthen skills. Additionally, data from the fidelity coding protocol, Motivational Interviewing Treatment Integrity (MITI) (Moyers et al., 2015), guided individualized coaching for TA providers, ensuring adherence to MI best practices and continuous skill development. TA providers received access to their MITI coding reports as well, which highlighted strengths and areas for improvement.

Study participants

CoCU TA providers (N = 4) received training in the CoCU procedures. All TA providers had experience with coalitions prior to learning about and implementing the CoCU model. Three TA providers were new; one had several years of experience. One TA provider had some training in MI prior to this study. Two TA providers were female; all were mid-career.

Data collection procedures

Meeting observations

We used an implied consent procedure to record coalition leader and coalition meetings with TA providers. Zoom was used for recording in person and web-based meetings. We only recorded audio and every attendee needed to be at least 18 years old. Coalition leaders, coalition members, and TA providers were informed about the wish to audio record their interactions at the beginning of the study. Consent to record audio came at the start of each meeting. In-person recording of coalition meetings only occurred if everyone consented to the recording. Individuals participating in web-based coalition meetings were given the opportunity to leave the zoom line if they do not want their audio recorded. Almost all meetings were recorded. Audio recordings were identified by a code unique to coalition and TA provider. No personally identifying information was connected to any of the audio recordings. A total of 602 meetings were recorded.

After excluding TA provider meetings with coalitions (n = 160), we randomly selected 60 out of the 442 remaining recorded meeting with coalition leaders for coding by two coders that were active members of the Motivational Interviewing Network of Trainers (MINT) and trained by coauthors of the 4.2.1 manual, who have been coding together, including regularly checking their progress with each other, for 10 years. They also often conduct MITI coding for Trainings of New Trainers and other certification processes (Juarez, 2025). Coders followed the MITI 4.2.1 protocol (Moyers et al., 2015) including coding global ratings and behavioral counts. The four global ratings included: Cultivating Change Talk (MI Skills), Softening Sustain Talk (MI Skills), Partnership (MI Spirit), and Empathy (MI Spirit). The behavioral counts included: giving information, persuade, persuade with permission, question, simple reflection, complex reflection, affirm, seeking collaboration, emphasizing autonomy, and confront. Coded items can be collapsed into summary measures to give a holistic understanding of how well MI was implemented. To assess feasibility and validity of the MITI codes in this context, we first coded 20 entire meetings. Then, PIs, raters, and TA providers reviewed and discussed the ratings and agreed that the ratings were representative of TA behaviors, captured the use of MI in this context, and were useful. Following this decision, all future recordings were coded following the MITI 4.2.1 coding recommendation of randomly selecting a 20-minute segment to code.

TA documentation

The TA providers completed one 5-minute REDCap (Harris et al., 2009) survey after each phone, in-person, or web meeting. It tracked implementation of CoCU core components. Surveys were identified by a code unique to coalition and TA provider. No personally identifying information was connected to the survey. TA providers submitted the coalition action plans for research inclusion after they were completed. These procedures were 100% completed due to project manager monitoring.

Measures

This current study used multiple measures to assess dosage, adherence, and quality of the CoCU. Information is listed below.

Dosage

A count of TA provider contacts was created to assess the dosage of the CoCU TA model. The occurrence of each planned Step 1, Step 2, Step 3, and Step 4 meeting, and the occurrence of other unplanned CoCU-related meetings (0 = not occurred; 1 = occurred) that occurred over a one-year period was summed, creating three scales: the annual number of TA provider meetings with coalition leaders; the annual number of TA provider meetings with coalitions; and the annual number of other CoCU meetings.

Adherence

We used four behavior or task indicators from TA documentation as measures of adherence to data-informed TA interactions. First, reviewing the Feedback Summary was tracked by the TA provider in the TA Record (0 = Not Reviewed by the TA with the coalition leader; 1 = Reviewed by TA with the coalition leader). Second, we tracked whether the coalitions decided to prioritize something for action planning (1 = Yes, selected a priority; 0 = No, did not select a priority). Third, we tracked whether the coalitions created an Action Plan (1 = Yes, created an action plan; 0 = No, did not create an action plan). Fourth, the use of the Coalition Guidebook when creating the Action Plan was measured by coding how well the steps itemized in the action plan connected to the strategies and actions outlined in the Guidebook; 1 = Not Connected; 2 = Slightly Connected; 3 = Moderately Connected; and 4 = Fully Connected.

Quality

Given our application of MI into a non-therapeutic context, we selected the most relevant scales from MITI 4.2.1 (Moyers et al., 2015) to be used in this study to measure the integration of MI into TA provider interactions with coalitions and coalition leaders. The summary scale, MI Adherent Behaviors, a sum of affirming, seeking collaboration, and emphasizing autonomy behavior counts, was used; higher counts indicated higher MI adherence (Moyers et al., 2016). Second, we used behavior counts of confront and persuade; higher counts indicated more undesirable TA interactions (Moyers et al., 2016). Third, we used summary scores of global measures. The Technical Globals scale measured MI skills and was created by averaging the Cultivating Change Talk and Softening Sustain Talk global scores. Cultivating Change Talk (1 = low to 5 = high) measured the extent to which the TA provider actively encouraged the coalition leader’s own language in favor of the target goal, confidence about change, and ability to execute next steps. To receive a score of 5, conversations needed to be focused on making changes or next steps. Softening Sustain Talk (1 = low to 5 = high) measured the extent to which the TA provider did not focus on change talk, maintained reasons against changing or the status quo, or reasons for not taking next steps (Moyers et al., 2016). The Relational Global scale measures MI spirit and was created by averaging two global ratings: Partnership and Empathy. Partnership (1 = low to 5 = high) measured the extent to which the TA provider conveyed an understanding that expertise about change, or in this case, next steps regarding coalition activities, reside mostly within the coalition leader. Empathy (1 = low to 5 = high) measured the extent to which the TA provider tried to understand the coalition leader’s perspective and experience (Moyers et al., 2016). Higher scores on Partnership and Empathy indicated greater MI quality.

Results

Dosage of the CoCU TA model

See results in Table 1. The observed frequency of planned CoCU meetings with coalition leaders ranged from 5.5 to 8.1 per year. Regarding coalition meetings, the annual average ranged from 3.0 to 3.5. In addition, non-planned interactions occurred, on average, 0.81 times per year.

Table 1.

Dosage of CoCU: the number of meetings each TA provider had with their respective coalition leaders and full coalitions each implementation year, with 95% confidence intervals.

	n	Mean	Std Err	LCL, UCL	Min	Max
Planned Coalition Leader Meetings
Intervention Year 1	32	5.5	0.30	4.88, 6.11	1.0	8.0
Intervention year 2	30	8.1	0.65	6.76 9.43	0.0	15.0
Intervention Year 3	29	6.4	0.54	5.27, 7.49	0.0	11.0
Planned Full Coalition Meetings
Intervention Year 1	32	3.53	0.22	3.09, 3.97	2.0	6.0
Intervention year 2	30	3.43	0.28	2.85, 4.01	0.0	6.0
Intervention Year 3	29	3.03	0.28	2.46, 3.60	0.0	6.0
Other CoCU Meetings
Intervention Year 1	32	3.53	0.22	3.09, 3.97	2.0	6.0
Intervention year 2	30	3.43	0.28	2.85, 4.01	0.0	6.0
Intervention Year 3	29	3.03	0.28	2.46, 3.60	0.0	6.0

Adherence to data tools

See results in Table 2. On average, 97% of active coalitions reviewed the Feedback Summary each year. Additionally, all intervention coalitions used the Guidebook during their action planning; approximately 63% of coalition action plans were “fully connected” and 29% were “moderately connected” to the Guidebook’s recommended strategies.

Table 2.

Number of coalitions in each implementation year that successfully reviewed the feedback Summary and created an action plan.

				Number of Action Plans Connected to the Guidebook*
	Active Coalitions	Reviewed Feedback Summary	Created Action Plan	Slightly Connected	Moderately Connected	Fully Connected
Intervention Year 1	32	32	32	3	10	19
Intervention Year 2	32	29	26	1	10	17
Intervention Year 3	29	29	25	3	5	18

^*Two coalitions created two action plans in Year 2; in Year 3, one coalition created two action plans; information on all Action Plans is presented here.

Quality of the CoCU

See results in Tables 3–5. Across all coded meetings, the mean score for the Technical Globals measure, assessing MI Skill, was 3.18 (Table 5). The majority of meetings received a 2.0 on Cultivating Change Talk (60%); whereas almost all (97%) meetings scored a 4.0 on Softening Sustain Talk (Table 4). The mean score for the Relational Globals measure, assessing MI Spirit, was 3.08 (Table 5). See Table 4, almost all (92%) coded meetings scored a 3.0 or a 4.0 on Partnership; Empathy scores hovered around 2.0 (40%) and 3.0 (47%). The mean on the MI Adherent measure equaled 3.96 (Table 5). The number of confront and persuade behaviors, were almost non-existent (Table 5).

Table 3.

Frequencies and percentages of MITI Global ratings that reached “fair” and “good” levels.

	Reach “Fair”		Reach “Good”
	n	%	n	%
Technical Global (MI Skill)	59	98%	0	0%
Relational Global (MI Spirit)	17	28%	3	5%

Table 5.

Descriptive statistics of MITI scores: global assessments of MI Skills and MI Spirit and counts of desirable and undesirable behaviors.

	n	Mean	Std. Err.	LCL, UCL	Min	Max
Global Assessments
Technical Global (MI Skill)	60	3.18	0.03	3.12, 3.25	2.50	3.50
Relational Global (MI Spirit)	60	3.08	0.06	2.96, 3.20	2.00	4.50
Behavioral Counts
Total MI Adherent	60	3.96	0.35	3.26, 4.65	0.00	14.32
Confront	60	0.00	0.00	0.00, 0.00	0.00	0.00
Persuade	60	0.38	0.12	0.15, 0.62	0.00	4.95

Table 4.

Distribution, including frequency and percentages, of technical (MI Skill) and Relational (MI Spirit) Global ratings.

	1	2	3	4	5
	n (%)	n (%)	n (%)	n (%)	n (%)	Mean (SD)
Technical Global (MI Skill)
Cultivating Change Talk	0	36 (60%)	24 (40%)	0	0	2.4 (.49)
Softening Sustain Talk	0	0	2 (3%)	58 (97%)	0	4.0 (.18)
Relational Global (MI Spirit)
Partnership	0	2 (3%)	30 (50%)	25 (42%)	3 (5%)	3.5 (.65)
Empathy	1 (2%)	24 (40%)	28 (47%)	7 (12%)	0	2.7 (.70)

Discussion

We used a process evaluation with multiple measures to track the implementation and fidelity to the planned CoCU TA model. Three main takeaway points surfaced. First, contact between TA providers and their respective coalition leaders and coalitions occurred less than planned, with 75% or more of planned meetings completed. Second, CoCU data-informed tools were used regularly. Third, TA interaction quality, as measured by the MITI and assessing the use of MI-related skills, was at least somewhat consistent with the use of MI. This study presents a novel application of the use of MI, adding to the literature that demonstrates MI’s applicability in a wide range of contexts.

Dosage of the CoCU: frequency of contact occurred regularly but less than planned

Contact between TA providers and their coalition partners occurred regularly but less than planned and less than prior research suggested was necessary (Chilenski et al., 2020), with coalition leader contacts occurring about half as often as planned and contact with coalitions occurring about 75% of the time. Discussion with TA providers reveal that monthly meetings was impacted by last-minute cancelations due to scheduling conflicts, sickness, vacation, and holiday schedules. Also, coalitions frequently meet less during the summer. Both states also had one large annual prevention conference, which consistently required schedule adjustments. Each of these factors could lead to fewer TA contacts and needing less TA. It is also possible that some TA providers could adhere better to the regular monthly meeting schedule than others. This finding may have been partially driven by a few struggling coalitions that ended up disbanding. Though TAs tried to provide regular support during these times, sometimes coalition members would not respond to meeting requests. At times, they left their positions without a replacement, as is common in the human and social service fields (Glisson et al., 2008; Kegler et al., 1998). Although not all meetings occurred as planned, few additional, unplanned contacts occurred. The goals of these meetings varied.

Other project research currently in progress suggests that coalitions were largely effective in implementing their action plans (Gaddy et al., 2025). Though it seems monthly contact is reasonable, it may be that a targeted, light touch strategy such as the CoCU, drawing on data and integrating MI, can be effective, even if some meetings are canceled.

Adherence of the CoCU: employing audit and feedback with data-focused tools

Our second main takeaway is that the data components of the CoCU model were integrated at a high rate into TA encounters. The Feedback Summary was reviewed with coalition leaders and coalitions 97% of the time across the three-year period, and 92% of the Action Plans were at least moderately connected to the evidence-informed Coalition Guidebook (Brown & Chilenski, 2022). This high rate of integration suggests that audit and feedback processes used in individual health settings (Curry et al., 2008; Sarkies et al., 2023; Stone et al., 2020) may generalize; using data to inform TA interactions and to determine next steps with specific data-tracking tools may in fact be feasible and acceptable to TA providers and coalitions alike. This project included a variety of coalitions and contexts; it is possible that integrating data-informed tools have broad applicability and potential for data-driven TA strategies, especially in community coalitions concerned about adolescent and youth wellness contexts (Fagan et al., 2009; Parker et al., 2025). Interestingly, year 3, with fewer coalitions, also had stronger connections to the guidebook in their action plans. This could be because struggling coalitions disbanded, or a practice effect. Otherwise, one important consideration is that considerable effort was invested in presenting data in an easily understandable format, using a visual dashboard. Our experience suggests it is important to thoughtfully design the presentation of data and plan how it will be used to support decision-making. Pairing data with TA interactions may also have facilitated a lower number of TA provider contacts. Collectively, these findings underscore the central role of data utilization in the coalition support model and in embedding data across coalition decision-making processes.

Quality of the CoCU: use of MI-related skills

Our third key takeaway is that TA providers integrated MI Spirit and Skills into their interactions at least at a moderate level. Though not empirically validated, many global codes reached a minimum of a “fair” rating; those ratings along with the level of MI Adherent behaviors and almost non-existent persuasion and confronting, provide additional context and suggest that TA provider interactions with coalition leaders included affirming, seeking collaboration, and emphasizing autonomy behaviors (Miller, 1983; Moyers et al., 2015). Ratings of technical skills seem to be rated higher than relational skills, the MI Spirit, part of MI (Moyers et al., 2015). On average, CoCU TA provider technical globals reached fair levels determined for clinical contexts. This suggested that CoCU TA providers cultivated change talk and softened sustain talk while supporting the development of an Action Plan and determining next steps. Our tools, including action plan worksheets and an action plan progress tool, likely reinforced these skills. That said, the range for technical globals was very narrow – between 2.5 and 3.5 – so there is potential room for growth. We expected these skills to be more challenging as change talk looks different in this coalition context compared to a clinical context. The coalition leader’s ability to create change is not just up to them, but in their ability to lead and engage the coalition and hold it accountable to planned next steps. These scores suggest that the TA providers were consistent in focusing on change talk with their coalition leaders.

TA providers scored slightly lower on MI spirit, which captures understanding of the situation and displays of empathy (Moyers et al., 2016); without empirical validation, it is unknown if the levels reached in this study and for this context are adequate. Also, at times coders rated TA providers quite high in this regard, at close to 5.0, the maximum on the scale. Situations during which TAs demonstrated empathy through complex reflections indicate the use of active listening skills, rather than just responding to the coalition leaders’ questions or comments. TA providers found opportunities to express empathy and affirm progress, validating the coalition leaders’ efforts and encouraging growth (Cole et al., 2023). MI non-adherent behaviors occurred rarely, which seems lower than some prior research in other contexts (Moyers et al., 2016). Specifically, confronting behaviors never occurred in the randomly selected coded sections and persuade behaviors occurred rarely. Further investigation of the persuade code revealed that the high persuade outlier was a brainstorming session between the coalition leader and TA provider. Given the centrality of brainstorming for collaborative work, it is important to consider how to employ it in an autonomy supportive manner.

Implications for practice

These findings have several implications for educational and psychological consultation practice. Though further data collection and analyses are needed to better understand the effectiveness of the training and ongoing professional development, our results may suggest that we should review training materials and integrate more attention to training MI Spirit (Moyers, 2014), such as creating partnership and demonstrating empathy and understanding. It may be useful to revise CoCU protocols, scripts, and tools to reinforce MI spirit behaviors – partnership and empathy. Over time, common key questions or phrases surfaced, such as: “Can you tell me more about that? I’d like to better understand your experience.” and “What has worked for you in the past when you have been in a similar situation?” It may be useful to develop a handout of questions and reflections focused solely on developing and displaying empathy and understanding (Moyers, 2014). It may also be beneficial to incorporate MITI results regularly into trainings to help identify skill strengths and gaps and target ongoing training around them. We may want to attend to the role of brainstorming in coalition work and how to integrate MI Spirit and Skills into brainstorming sessions, as needed.

TA providers report that the initial MI training successfully introduced MI basics and the ability to comfortably use MI techniques in CoCU interactions, and that the booster sessions were especially helpful in refining and practicing skills. However, at this time, given the modest data and experiential reports, we cannot make strong recommendations regarding training.

We included an MI trainer and researcher on our team, and though our MI trainer did not have content experience with coalitions, we found this assistance with developing protocols and scripts and leading the MI training and monthly professional development sessions essential.

The CoCU TA protocol required organizational skills. We found it helpful to have a “lead” TA provider who helped develop structures and processes for all TAs to use in tracking their progress and next steps with each coalition and attending to coalition needs. Additionally, organizational skills may also need to be considered an essential skill when hiring TA providers working in this community collaborative context. Community coalition work is complex with many fluctuating components operating in unique contexts. It is likely that implementation benefitted from working with new TA providers that were familiar with community prevention coalitions but not yet seasoned TA providers. Prior research suggests those newer in their fields tend to be open to guidance and willing to adopt new behaviors (Aarons, 2004).

Additionally, our results suggest that sometimes TA providers and coalitions may need to connect on a topic outside of the planned protocol. We recommend that TA systems plan to foster this type of contact.

Limitations and suggestions for future research

There are a few factors to consider regarding the generalizability of our findings and many directions for future research. Though MI was integrated in meetings with coalitions and coalition leaders, we only coded 13.6% of the coalition leader meetings with the MITI. We also did not use all MITI scales in this study. Though we took extra steps to ensure that all TA providers were coded and received feedback and we used the data we felt was most relevant, it is possible that these recordings were not entirely representative of all TA interactions. The current study focused on MI-based interactions between the TA and the coalition leaders; we are missing coded data to inform how MI is used in a group or coalition context, which is beyond this study’s scope. We certainly acknowledge the potential of MI-based interactions in also facilitating change within coalition meetings, but we also acknowledge the complication. In a group, members sometimes use group-oriented language and other times individual-focused language. Also, at times, one person or some may be further along the motivation to change spectrum, engaged in change talk whereas others may be engaged in sustain talk. It would be beneficial for future studies to examine MI-based interactions within coalition interactions.

Because we utilized coders that are members of the MINT whose full-time job is to code and train MI, we did not conduct a second round of coding to produce inter-rater reliability estimates; this is important in future studies. We did not include a baseline evaluation on MI skills prior to training the TA providers and our data is descriptive, without a comparison group. Consequently, we cannot be confident in the quality of our training and we are unable to compare the initial skill levels of our TA staff in this coalition context compared to others that deliver MI in other contexts; however, we do know that three of our four TA providers had no experience with MI prior to this work. Future work needs to include a baseline evaluation of MI skills and experience.

This project began in the fall of 2020 during the Covid-19 pandemic, a time of turmoil. Coalitions began meeting virtually. We were able to flex our protocols to match coalition operations and need. However, some coalitions stopped functioning during our study. While this is a natural phenomenon (Mark E. Feinberg, Ridenour et al., 2008), it may have been influenced by the multiple demands of the COVID context. We successfully recruited a wide variety of coalition types and community contexts but found that our sample of coalitions served majority white populations. Although partially due to the demographics of Pennsylvania and Missouri, it may also have been influenced by the additional challenges coalitions in low-income communities face, especially during this time (Brown et al., 2011; Greenberg et al., 2007).

We included four TA providers in this study. One TA provider left their position during the project, leaving three TA providers to carry the intervention coalitions. The transition between TA providers was challenging and may have impacted coalition progress.

Future research ideas in this area are plentiful. Future research connecting the MITI scores (Moyers et al., 2015) with how these behavior are being interpreted by coalition leaders and coalitions is important; this may be possible with other project data we collected from coalition leaders and TA providers that assesses their collaborative working relationship (S. M. Chilenski et al., 2025). This analysis is challenging due to multiple design issues. As a result, this work would need to proceed carefully. Yet, this work would increase our understanding of how MI behaviors link to perceptions of the TA experience. This work may help us understand the social validity of the intervention and allow us to iteratively modify the intervention based on feedback, improving the understanding of our theory of change.

Given the importance of implementation quality on intervention outcomes (Domitrovich & Greenberg, 2000), future research should link CoCU fidelity to community collaborative outcomes. It could be important to link fidelity to coalition proximal and distal outcomes such as the use of feedback, quality of action plans, action plan implementation, building of general coalition capacity, and eventual meeting of community improvement goals.

Conclusion

In summary, these results suggest that CoCU TA model was implemented with relatively good dosage, adherence, and quality, suggesting that TA provider interactions with coalition leaders and coalitions are appropriate contexts for data integration using an audit and feedback approach and MI. Future research will present CoCU effectiveness to better understand how this model can support community coalitions in obtaining their goals, and additional work in this area is suggested to better isolate the effectiveness of the training and professional development protocol related.

Supplementary Material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/10474412.2025.2603277

Biographies

Sarah M. Chilenski is a Research Professor at the Edna Bennett Pierce Prevention Research Center. She received her PhD in Human Development and Family Studies with a focus on Prevention Research at Penn State. She focuses on how communities, schools, and universities can collaborate in the pursuit of quality youth prevention programming. Her current applied community research projects focus on community collaboration; technical assistance for community coalition models supporting public health; dissemination of evidence-based programs and sustainability; and community context-related youth outcomes. She aims to examine youth outcomes of community prevention activities while using data to help empower participating communities.

Yoon Sun Hur is an Assistant Research Professor at the Administrative Data Accelerator at Penn State. She received her Ph.D. in Applied Economics from the University of Minnesota with expertise in applied microeconomics and development economics. Dr. Hur’s research interest pertains to the impact of policy intervention on the human capital accumulation and labor market outcome. Her research involves identifying the mechanism of influence from policy intervention on the household behavior such as investment in human capital and participation in labor market combining a rigorous applied microeconomics methodology.

Eric Harrison is a PhD student in Human Development and Family Studies at Penn State. Eric studies individual differences in addiction and recovery and implementation efforts to meet those needs.

Melissa Fausey holds a Certificate in Project Management and is currently a student in a Master of Project Management Course of study at Penn State. She provides technical assistance to a variety of community prevention efforts, including state drug and alcohol, county-level Single County Authorities, community prevention coalitions, and local organizations. Prior to providing technical assistance at EPIS, she coordinated her local community prevention coalition.

Kimberly Mallett is a research professor at Penn State University in the Prevention Research Center. Dr. Mallett received her Ph.D. in clinical psychology in 2005 from the University of Washington. She is a Motivational Interviewing trainer and integrates this expertise in her work. She is interested in developing and evaluating interventions aimed at reducing high-risk drinking and related consequences among college students and in the prevention of skin cancer among high-risk populations. In this work, Kim is interested in enhancing communication between physicians and patients and looking at how it impacts behavior change among patients.

Jeff Hogan is a technical assistance provider at EPIS for community coalitions and a variety of other community programs and initiatives. In this role he provides coaching and technical assistance for coalitions across Pennsylvania, including networking opportunities, resources, and professional development. He regularly hosts Learning Community Meetings to provide opportunities for coalition leaders, mobilizers, and facilitators to learn together from best practices in coalition work and prevention across Pennsylvania. Jeff has a bachelor’s degree in computer science with a minor in Computer Information Systems from Clarion University of Pennsylvania. He also has a master’s degree in leadership & business Ethics from Duquesne University. Prior to coming to EPIS Jeff served as the Executive Director and Mobilizer for his local community prevention coalitions. During his time with Karns City Communities That Care the coalition was named the “PA Prevention Coalition of the Year” for 2017–2018 through the Commonwealth Prevention Alliance.

Louis Brown is trained as a community psychologist and studies community-based interventions that promote mental and behavioral health. He is particularly interested in social justice, empowerment, and community engagement. His work with the implementation and evaluation of community-based interventions focuses on low-income, diverse populations. He has active lines of research with community prevention coalitions, self-help and mutual support, school-based preventive interventions, and Hispanic health disparities.

Data availability statement

The data that support the findings of this study are available from the corresponding author, SMC, upon request.