Emerging adults (EAs) face elevated risks of mental health (MH) challenges [1], yet service systems often struggle to provide care that is both timely and suited to their developmental needs [2-4]. Emerging adulthood, defined as the transitional phase between adolescence and adulthood, typically spans 18 to 29 years [5], prominently characterized by 5 normative features: identity exploration, instability, self-focus, feeling-in-between, and possibilities/optimism [6,7]. This life stage coincides with the highest onset rates of mental illness (eg, mood and anxiety disorders and substance use disorders), with approximately 75% of lifetime disorders emerging before age 24 years [1]. The combination of ongoing neurobiological maturation, shifting social roles, independence, and increased academic and economic pressures contributes to this heightened vulnerability to MH disorders [7-10].

Despite clear evidence of need, MH systems remain poorly structured to serve this population, resulting in a substantial treatment gap [8,11]. The division between child/adolescent (hereafter, “youth”) and adult service systems often leaves EAs without proper care, as many age out of youth programs yet are not well supported by adult services that are not designed with their developmental needs in mind [8,11]. A recent systematic review [8] indicates that transition pathways in Canada are largely uncoordinated and that governmental supports are insufficient, contributing to inconsistent access to services at a time when many EAs require continuous care. The review also identifies a lack of national or provincial strategies that recognize emerging adulthood as a distinct period, creating uneven service delivery across regions and weak integration among care providers. These structural gaps limit the adoption of evidence-informed approaches (eg, community-based service delivery and electronic-MH initiatives) and leave many EAs without timely or developmentally appropriate care [8]. MH presentations in this age group tend to shift over short periods and often do not fit diagnostic categories created for younger or older populations [12], which complicates assessment and treatment planning, particularly when delays occur between initial contact and the start of care [13-15].

At the same time, EAs may seek a more active role in their MH care, and opportunities to take part in treatment decisions contribute to their transition toward greater autonomy in adulthood [14]. However, many services continue to prioritize clinician-led decision-making, which limits opportunities for individualized engagement [16,17] and often affects EAs more than other ages [18]. Assessment practices reinforce this pattern, such that systems that often rely on single-score distress measures, combined with clinical judgment, may not fully capture the complexity of EA needs or preferences [19]. These structural factors intersect with broader barriers related to stigma, financial concerns, poor MH literacy, and limited service availability, including long wait times [14,15]. Consequently, many EAs disengage from care altogether [14], with service use declining by as much as 50% to 70% during this critical transition period [20].

Stratified care has emerged as a promising model for addressing systemic gaps through a more personalized and adaptive approach to MH service delivery [21]. Traditional MH service models are often shaped by program structures and organizational contexts, such that evidence-based interventions are delivered in relatively fixed ways that reflect service design and availability rather than being readily adapted to clients’ changing needs [22]. Stratified care, in combination with structured use of standardized assessment data, contributes to this shift by identifying an individual’s position along the care pathway and guiding changes in intervention intensity [23,24]. Integrating a transdiagnostic framework further strengthens this approach by focusing on shared symptom processes across conditions rather than discrete diagnoses [12,25-28]. Transdiagnostic interventions draw on strategies, such as targeting emotion regulation skills or reducing avoidance patterns, allowing them to be applied across co-occurring difficulties [26,29]. This process-focused approach helps stratified care models respond to overlapping needs as clients move through care. This combined approach is particularly relevant for EAs, as it accommodates developmental changes and social contexts that shape their help-seeking and engagement, thereby addressing gaps that often emerge as young people transition between youth and adult service systems [24]. Hereafter, stratified care will refer to this combined approach.

Digital measurement-based care (dMBC) is a relatively new, evidence-based approach [23,30] that can facilitate the development of streamlined, stratified, and transdiagnostic models in MH care [24,28]. This approach uses digital MH (dMH) platforms, such as the Australian web-based platform “InnoWell” [23], to systematically collect and apply patient-reported outcome measures (PROMs) that quantify self-reported symptoms, functional status, and well-being over time to guide treatment decisions [31-33]. PROMs are structured tools that capture clinically relevant information directly from clients and translate it into data to inform care in real time [34]. dMH platforms select PROMs that reflect key areas of MH and are grouped into domains such as everyday functioning, anxiety, psychological distress, and suicidal thoughts and behaviors. The core of dMBC involves the digital administration and automatic scoring of PROMs, which quantify symptom patterns that help identify and continuously monitor underlying transdiagnostic processes [23,31,32]. Clients and clinicians can review and track this data through interactive dashboards that show change over time [23,31,32]. Recent work shows that these platforms enhance youth and EA engagement when clinicians actively integrate the collected data into session discussions and treatment decision-making, allowing young people to better understand their symptom patterns and remain actively involved in their care [33,35].

Despite these advances, substantial implementation challenges continue to limit the reach and sustainability of dMBC within youth and EA MH services. System-level barriers commonly include variability in technology infrastructure, limited staffing resources, and the absence of clear organizational processes for integrating digital tools into routine workflows, which limit consistent use of dMBC across settings [36-39]. Digital platforms also introduce technical and procedural constraints when they do not integrate smoothly with existing electronic health records, creating additional or duplicative work for clinicians and reducing the feasibility of sustained adoption [36]. Clinician-level challenges include concerns about the time required to incorporate PROM data into sessions, uncertainty about interpreting digitally collected information, and apprehension that structured measures may constrain clinical dialogue or obscure the complexity of EA presentations [2,37,39]. For young people, barriers arise when measures feel repetitive or disconnected from their care experience, when the purpose of routine measurement is unclear, or when concerns about privacy and sensitive content lead to disengagement [2,40]. Items related to suicide risk introduce further complexity [28]. EAs may feel distressed when responding without real-time support, and clinicians often express concerns about liability and the operational pressures of responding to risk notifications [28,38,41,42]. These challenges illustrate that emerging solutions do not always translate automatically into effective implementation and that the success of dMBC depends on systems that can integrate dMH tools into everyday practices in ways that account for workflow realities, clinical judgment, and the lived experiences of young people accessing MH services. Future publications from our research will expand on these implementation barriers.

dMBC implementation can be strengthened through a rapid learning health system (RLHS) framework [24], which leverages routinely collected health data to evaluate outcomes and guide ongoing improvements in service delivery [43,44]. This framework creates a continuous feedback cycle in which information from everyday clinical practice is analyzed and applied to enhance the quality and precision of care. Drawing on data from diverse real-world populations allows the RLHS to support adaptive learning and closer collaboration among clinicians, clients, and researchers [44-46]. A current study led by Dimitropoulos et al [24] is actively assessing the feasibility and acceptability of implementing an RLHS to support dMBC practices in stratifying and supporting EAs in their care pathways. This research is ongoing, and results have not yet been published. Nevertheless, embedding dMBC within an RLHS framework may not only be a practical integration of 2 evidence-based models but also a necessary step toward creating a more responsive and sustainable system of care.

Integrating co-design (CD) within an RLHS could further optimize dMBC implementation by positioning EAs and clinical service providers as active co-collaborators in identifying system barriers and developing service-level solutions. CD uses structured participatory techniques to elicit experiential knowledge and is regarded as an ethical and pragmatic approach because it positions those directly involved in a service context as active contributors whose insights inform the development or improvement of interventions that are responsive to real-world conditions [47,48]. Although dMH platforms, such as InnoWell, were initially informed by young people during development, there is limited research involving them together with clinicians in improving the actual delivery systems that support ongoing use of dMBC once the technology is introduced into clinical practice [35,49]. Consequently, decisions about how dMBC is introduced, maintained, or adapted often proceed without EA perspectives and can result in processes that may not fully reflect their lived experiences or the developmental factors that influence engagement [35]. Embedding CD in an RLHS addresses this gap by creating opportunities for EAs and MH service providers to participate in the continuous refinement of dMBC practices, promoting system-level changes informed by the realities of those who rely on these services and those who deliver them.

This study protocol outlines the current phase of the ongoing RLHS implementation study by Dimitropoulos et al [24]. The phase was initiated in January 2026 and is expected to conclude in November 2026. A CD approach is currently applied to engage EAs, clinicians, and clinical service leaders in co-developing practical implementation resources to support the integration of dMBC into routine care. These resources are intended to improve the feasibility, acceptability, and usability of dMBC for both EAs receiving care and the clinical staff responsible for delivering it. To achieve these aims, we distinguish between primary and secondary objectives that address different aspects of the CD process (Textbox 1). The primary objectives focus on the intended outcomes of the CD work, whereas the secondary objectives examine the quality of the engagement process that supports those outcomes. This distinction enables this phase to assess not only what is produced through the CD but also how the participatory process affects collaboration, inclusivity, and the overall integrity of the findings. Our objectives reflect Canada’s Strategy for Patient-Oriented Research, which promotes active patient and stakeholder engagement to generate outcomes that are relevant, feasible, and applicable to improving care [50].

Our study is one of several research projects conducted through the Framework for Research in Emerging Adults (FREA), a clinical research initiative led by the University of Calgary in partnership with Alberta Health Services that aims to transform the care and long-term health of EAs. Our study uses a concurrent mixed methods implementation design to evaluate dMBC integration into routine care while supporting continuous learning and iterative refinement of implementation practices. This study is ongoing and is anticipated to be completed in mid-2029.

To inform this CD phase, data collected between 2023 and 2025, including quantitative implementation data (eg, dMBC platform use, PROM completion rates, and longitudinal dMBC data collected between baseline and up to 12 months) and qualitative interviews and focus groups with EAs, clinicians, and clinical service leaders, were analyzed. Collectively, these findings identified consistent opportunities to strengthen the introduction, integration into clinical workflows, and use of dMBC during treatment to support care and clinical decision-making. Similar implementation needs were also identified through the study’s principal investigator’s (PI) parallel qualitative implementation research [2,36,37,41,42,51-53], which examined dMBC across various youth and EA MH care settings under different care models within Alberta between 2020 and 2025, providing the foundation for the current CD phase.

This FREA study is conducted at 2 outpatient MH clinics in Calgary, part of Alberta’s provincially coordinated health care system, including 1 specialized and 1 community-based clinic. Both clinics operate at a level 3 (high-intensity community-based services) according to the Level of Care Utilization System (LOCUS) developed by the American Association of Community Psychiatrists [54]. This means that these clinics provide services for individuals with moderate to high clinical needs who require intensive treatment but still can be appropriately managed in a community setting [54]. Both clinics offer comprehensive assessment, individual and group psychotherapy, psychiatric consultation, and coordinated referral pathways to facilitate continuity of care.

Prior to March 2026, dMBC under a stratified care model was implemented at both clinics using the InnoWell platform. The platform contained 23 biopsychosocial domains (eg, overall MH, depressed mood, and suicidal thoughts and behaviors), each linked to 1 or more corresponding PROMs used to assess that domain. Additional details on the domains [24] and the platform [23] are described elsewhere. Clinicians reviewed PROMs collected at 4 clinical time points: baseline, 6 and 12 months, discharge, or intervals selected by clinicians. EAs were also encouraged to use the platform at their own discretion. Following the conclusion of InnoWell use, both clinics have paused active dMBC implementation while the research team and clinic partners explore other dMBC platforms and use CD findings to adjust the implementation approach.

Care delivery at both clinics follows the same stratified care model; however, implementation may vary across sites. Although both clinics use the same overall pathway, differences may exist in how intake assessments are conducted, how information is incorporated into stratification decisions, and how clinical service leadership supports and oversees clinicians’ use of dMBC. At both clinics, EAs first participate in a fundamentals of change (FOC) psychoeducational group before undergoing treatment stratification. Information collected from the FOC group, intake assessments (including clinicians’ own assessment practices and, when available, dMBC PROM baseline scores), and clinician evaluations inform stratification decisions. Based on this, EAs are allocated to either a low-intensity (approximately 6-8 sessions) or high-intensity (approximately 12-14 sessions) psychotherapy stream, with access to additional services, such as psychiatry or group therapy, offered as needed. Once stratified, primary treatment clinicians use dMBC PROM scores collected at clinical time points, alongside clinical judgment, to monitor progress and adjust the intensity or direction of care as needed.

The CD phase is led by a multidisciplinary research team with expertise in youth and EA MH, implementation science, and community-based research. The core team includes the study PI, 2 research coordinators, 1 postdoctoral researcher, and 3 research assistants. Three implementation leads from both this FREA study and the parallel dMBC implementation study have contributed to early-phase activities, including participant recruitment, early session material development, and co-facilitating several CD sessions. All team members have several years of experience in implementation research through sustained involvement in the study PI’s research program. With the exception of the postdoctoral researcher, the core team members were also involved in the parallel dMBC implementation study, providing familiarity with the implementation context, participating service settings, and experiences of clinicians and EAs throughout implementation. The team’s diverse educational and professional backgrounds contribute complementary perspectives throughout the CD process. Recognizing that these experiences, prior involvement in the parallel study, and interactions with participants may shape facilitation and interpretation, we engage in regular reflexive postsession debrief meetings and weekly team meetings. These discussions are used to consider how our perspectives shape facilitation and interpretation as the study phase evolves, thereby keeping the CD process grounded in participant contributions rather than researcher assumptions.

The CD phase adopts a concurrent multimethod design that integrates qualitative CD activities with quantitative process evaluation data collected throughout the study. The CD process consists of a series of semistructured interactive sessions organized around the study’s 5 primary objectives and guided by the American Psychological Association’s measurement-based care (MBC) Professional Practice Guidelines [55], which outline the core competencies for administering measures, reviewing data collaboratively, and integrating MBC into ongoing treatment decisions. The sessions also address the guideline’s future directions by focusing on how MBC can be improved in practice, particularly using decision-support tools and attention to its application to EA MH care. Through this process, 4 key implementation resources will be developed to operationalize these priorities and provide concrete materials for piloting in the study’s next phase (Figure 1).

We draw on 2 methodological frameworks that combine user-centered design (UCD) [56] and participatory design (PD) [57,58]. Integrating these frameworks establishes a structured yet adaptive foundation for our study, consistent with participatory approaches in implementation science. This integration facilitates a process that maintains methodological rigor while remaining relationally and contextually grounded. It supports the systematic development of the implementation resources as evidence-informed tools that reflect the practical and experiential realities of EAs and clinical staff involved in dMBC implementation.

The foundation of UCD is grounded in established frameworks that emphasize a systematic understanding of end users’ needs, goals, and contexts through intentional, structured engagement [56]. End users are conceptualized as individuals who interact with or are directly affected by a system or process [56], consistent with how PROM users are commonly described [59,60]. This definition will serve as the basis for identifying end users in this study and establishes the foundation for their involvement in the CD process. According to Gulliksen et al [56], the effectiveness of UCD depends on users’ meaningful participation throughout all stages of design, ensuring that their experiential knowledge informs both conceptual development and practical implementation. The design process is inherently iterative, characterized by cycles of feedback, testing, and refinement that enable responsiveness to contextual and emergent challenges. Sustained engagement also requires adequate resources and a deliberate effort to integrate user experiences with organizational and operational considerations. Within this framework, end users are positioned as active collaborators whose insights shape how systems are conceptualized, developed, and evaluated.

The UCD principles are applied through our CD sessions, in which participants collaborate with the research team to generate and refine practical outputs to support the implementation of dMBC in real-world MH settings. This approach preserves UCD’s emphasis on iterative development and responsiveness to user needs.

We adopt the core principles of PD to guide our approach, focusing on its foundational commitment to equitable collaboration and shared decision-making among stakeholders [57,58]. While we are not implementing the full traditional PD methodology, which typically involves multiple cycles of piloting an intervention and reconvening groups for iterative refinement, we integrate its essential structured approaches. These include specific protocols for dialogue, consensus building, and iterative feedback that ensure all participants have clearly defined opportunities to contribute. These methods actively mitigate hierarchies that could silence less powerful voices. This framework positions EA clients, clinicians, and clinical service leaders as active collaborators rather than consultees, with each group contributing expertise rooted in their respective roles: clients with lived experience, clinicians in care delivery, and decision-makers in organizational implementation. PD principles specifically address inherent power differentials through structured opportunities for reciprocal dialogue and shared decision-making [58]. We use adapted techniques inspired by cooperative prototyping and facilitated dialogue sessions that enable participants to challenge assumptions and contribute equally to solution development [57].

This approach ensures that our co-designed implementation resources reflect multiple perspectives and remain grounded in both experiential and operational realities. The PD framework provides a structured process for validating ideas across participant groups, which helps balance client-centered priorities with the practical requirements of clinical feasibility and organizational sustainability [58]. When applied throughout the CD process, PD promotes the development of interventions that are meaningful to clients while remaining feasible to implement within existing health care systems [57].

Eligible EA participants must be aged between 17 and 26 years and either actively receiving or have been discharged within the previous 12 months (starting from when active EA recruitment begins) from one of the participating clinics. All eligible EAs will have previously used the InnoWell platform as part of their care at the clinic. Clinicians and clinical service leaders will participate together as a single clinical staff group at each site, as both roles contribute complementary clinical and operational perspectives on the implementation and use of dMBC. Conducting site-specific clinical staff groups ensures that discussions reflect each clinic’s local workflows, implementation practices, and organizational context. Clinical staff will be eligible if they are currently providing EA MH services at a participating clinic. Although prior involvement with the implementation of InnoWell before its conclusion is desirable, it is not required. New clinical staff who will be involved in ongoing dMBC implementation are also eligible to participate.

The planned group composition and size were informed by focus group methodology [61], which recommends organizing participants according to shared characteristics, levels of expertise, or relative power related to the topic under investigation. Groups of approximately 5 to 10 participants are generally recommended to facilitate meaningful discussion while ensuring a diversity of perspectives. Accordingly, 2 types of CD participant groups are being implemented. EAs and clinical staff participate in separate groups to minimize potential power dynamics, particularly because some clinicians may be current or former providers of participating EAs.

The original protocol proposed 1 cross-site EA cohort of approximately 5 to 10 participants and 2 site-specific clinical groups of approximately 5 to 10 participants (10-20 clinical staff participants overall). Following commencement of the first EA cohort, the protocol was amended to recruit a second EA cohort to account for participant withdrawals and anticipated attrition across the multiple scheduled CD sessions over the summer months, increasing the planned EA sample from 1 cohort (5-10 participants) to 2 cohorts (10-20 participants). This sample size was further informed by the concept of information power [62], which suggests that qualitative studies with focused aims and participants possessing highly relevant experience may require fewer participants to generate information-rich data. Because participants were recruited based on their direct experience with dMBC at the participating clinics and contributed across multiple CD sessions, the planned sample size was considered appropriate to address the study phase’s objectives.

A purposive sampling strategy [63] was used to recruit participants who met the eligibility criteria. EAs were recruited from a pool of approximately 150 individuals who had previously consented to be contacted for future research participation. Invitations were distributed by telephone, email, and/or SMS text message. Clinical staff were introduced to the CD phase during scheduled team meetings at their respective sites in December 2025, followed by research team follow-up in January 2026 to provide additional study information and confirm participation. Recruitment of the first EA cohort occurred between February and March 2026, with 9 participants enrolled. Before the first CD session, 2 participants withdrew. Recruitment of the second cohort occurred between March and May 2026, resulting in 11 additional participants. To date, 1 participant has withdrawn from each cohort. Clinical staff recruitment resulted in 12 participants at one site and 8 at the second site. Initial recruitment exceeded the recommended focus group size to account for anticipated attrition throughout the longitudinal CD process. As the CD process remains ongoing, attendance varies across sessions due to participant availability, while session sizes remain consistent with recommended focus group sizes.

Qualitative findings will be used to develop the implementation resources throughout the CD process. Resource content will be informed by shared understandings, recommendations, and priorities identified across participants, alongside divergent perspectives that provide meaningful insights for implementation. Throughout the CD process, the research team will collectively review and discuss emerging findings to determine which insights are appropriate and feasible to include in the implementation resources. Where perspectives differ between EAs and clinical staff, these distinctions will be retained and, where appropriate, clearly identified within the resources to ensure participant-group-specific recommendations are accurately represented.

As the implementation resources evolve, emerging content and unresolved questions will be brought back to the participants during subsequent CD sessions to gather feedback and guide further refinement. Additional implementation resources may also be developed if identified through the CD process.

The final CD objective may be completed over more than 1 session. During the initial session, draft versions of the resources may be presented to obtain participants’ initial feedback. We may then incorporate this feedback into revised drafts, which may then be emailed to participants as watermarked copies for internal review only. Participants may subsequently be invited to another review session to provide additional feedback on the revised resources. Implementation resources are expected to be finalized by November 2026.

We hold weekly team meetings throughout the CD process to review phase progress, discuss implementation considerations from session findings, and monitor methodological consistency. Adaptations to session materials, facilitation approaches, and development of the implementation resources are discussed and documented during these meetings. Standardized facilitation materials and documented team decisions will support consistency and provide a transparent audit trail of iterative refinements.

Key findings generated through the CD process will be shared through future peer-reviewed publications, academic conferences, and targeted knowledge translation presentations to clinical partners. The finalized co-designed implementation resources will not be publicly disseminated following this CD phase. Instead, they will be piloted and evaluated within the participating clinics during the next phase of the implementation study before any broader dissemination is considered.

Ethical approval for the implementation study was obtained from the University of Calgary’s Conjoint Health Research Ethics Board (REB21-0616). The same ethics board also approved the CD phase (REB25-1537).

All eligible participants provided informed consent prior to joining the CD phase. Consent was either obtained electronically through REDCap prior to the first session or electronically or physically at the start of the first session. Only those who provided consent can participate in the CD phase. EAs aged 17 years were required to demonstrate full decision-making capacity prior to confirming eligibility. This was assessed by a member of the research team using a 4-item decision-making capacity questionnaire developed for the implementation study (Multimedia Appendix 2). To demonstrate adequate capacity to provide informed consent, minors must correctly answer all 4 questions.

Only EA participants will receive compensation for their time and contributions. Compensation is set at US $18.05 per hour of participation and will be distributed after each session, allowing EA participants to withdraw at any time without penalty and still receive compensation for sessions already attended. Clinical staff will not be compensated, as their participation is considered part of their professional responsibilities and organizational quality improvement efforts within their respective clinics. Participants can leave the CD phase at any time.

If requested, their quantitative data will be removed within 7 days of their withdrawal. However, this does not apply to data collected during group-based research activities (eg, CD sessions or focus group interviews). Given the interactive nature of these activities, individual contributions become integrated with those of other participants and may inform collaboratively generated materials, making it infeasible to isolate and remove an individual participant’s data after collection. This limitation has been communicated to all participants during the informed consent process and documented in the consent form.

All research data will be stored on secure University of Calgary servers using approved platforms, with transcripts deidentified so that participants are referenced only by study ID and role. Data access will be restricted to authorized research team members. Given the group-based nature of the CD sessions, absolute confidentiality cannot be guaranteed. To promote privacy and respectful participation, a confidentiality pledge will be reviewed at the outset, and participants will be reminded to use first names only and to share information they are comfortable disclosing. They will also be informed of the limits to confidentiality, including mandatory reporting requirements for potential risks of harm to self or others.

A growing body of implementation research highlights that system-level decisions in EA MH often overlook the relational, experiential, and developmental factors that shape engagement during this life stage, contributing to the inconsistent uptake of dMBC despite evidence that routine PROM feedback strengthens clinical decision-making and outcomes [75,76]. This protocol responds to that gap by examining CD as a methodological approach that can strengthen the responsiveness of dMBC within an RLHS structure. CD is used to refine existing implementation processes in ways that center EA perspectives and address barriers that are commonly missed when decisions are made at organizational or clinical levels without sustained EA involvement. Embedding CD within an RLHS positions EAs as active contributors to iterative refinements, supporting the development of implementation strategies that evolve through continuous learning and reflect the complexities of EA service use. We anticipate that insights generated through this CD process will inform practical adaptations to dMBC implementation and demonstrate the value of CD in producing implementation resources grounded in participant contributions and suited to real-world care contexts. What is learned through this process will also guide refinements to our CD methodology in future work, particularly efforts to deepen EA engagement in research activities and amplify their influence in service improvement initiatives.

A key potential strength of this CD phase is our design, which supports iterative learning and responsiveness throughout the CD process, allowing implementation strategies and resources to evolve in ways that reflect the realities of EA MH care. The multimodal methodological framework guiding the CD sessions provides a structure that attends to the experiential and emotional dimensions throughout the implementation design, creating conditions for participants to contribute insights grounded in their lived experiences. The use of RQA and postsession feedback may further strengthen this approach, as these methods provide systematic ways to synthesize emerging insights and incorporate them into subsequent sessions, thereby fostering continuity and refinement throughout the CD process.

This work will also advance equity in MH implementation research by attending to populations whose developmental transitions and intersecting identities shape distinct experiences of access and engagement. Although RLHS models emphasize learning cycles that incorporate evidence, practice, and interest-holder perspectives, key perspectives remain underrepresented in service design [77]. Positioning equity as a guiding principle enables decision-making and adaptation that reflect the complexities of EA experiences and the varied clinical perspectives and expertise of participating staff. This approach treats equity as integral to our implementation study’s ongoing learning process rather than as an outcome assessed at the end of the study.

A potential limitation of this CD phase is the narrow range of variability in service contexts, which may limit the transferability of the findings. The organizational structures, priorities, and client needs represented in the participating clinics may not reflect those of other MH settings, particularly services operating in rural or remote regions or under different clinical or administrative models. Although this work is situated within an RLHS intended to support the translation of CD insights into implementation and technology-related refinements, some findings may remain shaped by local conditions rather than generalizable patterns across the broader system.

Another limitation is the use of separate participant groups for EAs and clinical staff. Although this approach was intentionally adopted to promote open discussion and minimize potential power imbalances, it may preclude direct dialogue between the groups and may limit opportunities to collectively explore and reconcile differing perspectives. To mitigate this limitation, we will present emerging findings from previous sessions and participant groups throughout the CD process to encourage consideration of alternative perspectives and inform the development of implementation resources that reflect the priorities of all participant groups.

Additionally, the use of the GSRS measure serves as another limitation. The measure was originally developed and psychometrically validated to measure therapeutic alliance in group therapy settings, specifically the client-leader-group relationship within clinical care, rather than participatory research or CD. However, given that our implementation study is situated within a clinical care setting and participants were already familiar with the measure through routine group therapy programs, the GSRS was considered an appropriate and pragmatic tool for capturing brief session feedback to support iterative refinement of the CD process. As the measure has not been validated for use in participatory research or CD settings, the findings should be interpreted as process feedback rather than a formal evaluation of participant engagement or the quality of the CD process.

The next phase of this work will involve piloting the co-designed implementation resources. While the CD participants will not be reconvened during the pilot, the perspectives of EAs and clinical staff will continue to iteratively inform the process through future evaluative surveys, interviews, and focus groups. This will allow us to evaluate how the outputs function in practice and how they can be further refined.

Moreover, our future research will expand on the secondary objectives of this phase, which examine participants’ expectations, experiences, and the impact of involvement in the CD process. Insights from these findings will inform future CD initiatives on how to better support equitable participation and foster conditions that promote increased engagement and shared decision-making. This direction will guide the development of a new CD study involving EAs accessing MH services in postsecondary settings, where institutional and developmental contexts may influence participation differently. This will involve investigating how these factors can support a more evidence-informed perspective on adapting CD methods to promote meaningful collaboration and create conditions for participant perspectives to continue shaping the evolution of dMBC and other system-level innovations.