Using Group Model Building to Map the Mobile Crisis Workforce Pipeline in Illinois and Broaden Stakeholder Perspectives

Using Group Model Building to Map the Mobile Crisis Workforce Pipeline in Illinois and Broaden Stakeholder Perspectives | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Using Group Model Building to Map the Mobile Crisis Workforce Pipeline in Illinois and Broaden Stakeholder Perspectives Jeremy Fine, Maria Guta, Helen Newton, Nathaniel Sowa, Amy Watson, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9568624/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: The purpose of this study was to use Group Model Building (GMB), a participatory systems thinking method, to build a system structure map of the mobile crisis workforce pipeline in Illinois (IL). Additionally, this study sought to determine if GMB effectively incorporates systems thinking into the mental models of participants. Methods: 14 stakeholders from across the mobile crisis workforce pipeline in IL gathered for a 4.5 hour GMB session, during which various systems thinking activities were performed to elicit the mental models of the workforce from participants. System structure diagrams were face-validated by at least two participants after the session. Moreover, responses to initial and final problem framing surveys were qualitatively dual coded at the level of the primary problem, potential solutions, and the level of the socioecological model associated with the solutions. These codes were compared within participants to determine if participants’ mental models shifted following GMB. Results: The GMB session produced two system structure diagrams, one for each member of the mobile crisis response dyad, that were validated by participants. Furthermore, most participants exhibited change in at least one dimension measured in the problem framing activity. Conclusions: GMB was effectively used to map the mobile crisis workforce pipeline in IL, including multiple feedback loops and multi-layered composite variables. Additionally, the initial and final problem framing activity illustrated the expansion of participant mental models. Health Policy Psychiatry mental health mental health workforce crisis mobile crisis mobile crisis workforce group model building systems thinking participatory research state mental health policy mental health policy Figures Figure 1 Figure 2 Figure 3 Plain language summary Group Model Building (GMB) is a method that gathers stakeholders from a particular system to solve a particular problem of interest by creating a map of their system. In this case, GMB was used to create a map of the mobile crisis workforce pipeline in IL. Additionally, a qualitative survey was used to demonstrate that GMB can help participants view problems from a systems perspective. Introduction The incidence of mental health crises in the United States (US) has increased substantially in recent years. 1 , 2 Unfortunately, in many places there is an insufficient workforce to meet this need; 40 of 43 polled states reported a crisis workforce shortage in 2023, 3 consistent with evidence that the mental health workforce generally faces a high rate of turnover associated with burnout. 4 Mobile Crisis Teams (MCTs) provide community-based crisis intervention and referral to clinically appropriate resources, and have been recommended as a less restrictive alternative to law enforcement. 5 , 6 The Substance Abuse and Mental Health Services Administration (SAMHSA) 2020 guidelines recommend that the team consists of an individual trained to use their lived experiences with mental health conditions to support others in recovery (i.e. a peer support specialist) and a clinical professional. 7 Despite new policies to expand the mobile crisis workforce, optimal strategies remain unclear given the challenge of sustaining 24/7 coverage with entry-level peer and clinical staff funded through braided streams. 8 Systems thinking is a conceptual framework that helps reveal how the structures underlying a system (e.g. the mobile crisis workforce pipeline) produce a particular outcome of interest (e.g. capacity of the workforce); it can help decisionmakers learn how changes in the system affect workforce outcomes. 9 Group Model Building (GMB) is a systems thinking method that has been used to solve healthcare workforce issues by engaging key stakeholders to create a qualitative illustration of the system structure (i.e. a stock-and-flow model), a quantified simulation model, and/or collaboratively-developed strategies capable of improving objectives. 10 – 14 By mapping how actions within one part of a system affect others, GMB helps participants recognize how siloed practices contribute to system-level problems, thus changing their internal conceptual representation of the system (i.e. their mental models). 15 , 16 While GMB has never been used to model the mobile crisis workforce, the complex funding streams and unclear workforce pathways mean it may be a valuable tool for solving mobile crisis workforce issues. 8 , 17 , 18 Additionally, GMB is generally thought to expand participants’ mental models, 19 little research explicitly and empirically tests this. 20 This is a key gap in the literature, as GMB is not just a modeling tool: it is an intervention for building shared understanding among stakeholders from different siloes. 20 , 21 This paper therefore has two aims: 1) apply GMB to model the mobile crisis workforce pipeline, and 2) to empirically measure the effectiveness of GMB in incorporating systems thinking into the mental models of participants. Methods Ethical Approval This study was deemed exempt by the Institutional Review Board of the lead author. Study Setting For this study, stakeholders from Illinois (IL) were recruited for a GMB session designed to model the state’s mobile crisis workforce pipeline. IL was chosen because the state has enacted policies to rapidly expand their MCT infrastructure and workforce, and the to leadership at the Illinois Department of Human Services Division of Behavioral Health and Recovery (IDHS-DBHR) was willing to engage with the lead author. Anecdotal evidence from stakeholders in IDHS-DBHR and testimony to the IL General Assembly from representatives of behavioral health crisis organizations confirmed that IL faces shortages like those reported around the US. 22 IL is expanding its mobile crisis infrastructure in accordance with the best practice guidelines issued by SAMHSA 2020. 23 This guidance recommends that MCTs be composed of peer support specialists, referred to as Engagement Specialists (ESs) in IL, and clinical professionals, referred to as Crisis Counselors (CCs) in IL. In part to generate a trained-ES workforce, in 2021 IDHS-DBHR enacted the Certified Recovery Support Specialist Program (CRSS-SP), which financially supports adults living in recovery from a behavioral health challenge in obtaining peer specialist training at educational institutions throughout the state. After 100 hours of classroom training and 300 internship hours, students graduate, and are eligible to sit for a certification exam. Prior to 2021, the only route to certification was the “independent pathway,” which involves piecing together 100 hours of course work from various sources and completing 2000 hours of work experience before taking the exam. 24,25 To ensure there is an adequate network of MCTs across the state, in 2021 IDHS-DBHR initiated a grant program called Program 590, which provides grant dollars to organizations that provide mobile crisis services. 26 These policies exist in a complex and fragmented training, administrative, care-delivery, and funding ecosystems; such landscapes are well-suited to benefit from GMB. 27 Participants and Recruitment Three initial participants (i.e. sample seeds) were used to initiate snowball sampling for the GMB session: two deputy directors from the IL IDHS-DBHR and the fifth author of this study. These seeds were chosen due to their non-overlapping networks to prevent over-representation of a particular network or group. 28 A key recruitment goal was to include equal numbers of individuals knowledgeable about the ES and CC workforces in the GMB session. This goal was achieved through the participation of 14 individuals, approximately evenly divided between ES and CC workforce expertise. This ensured thorough mapping of both pipelines while avoiding an excessively large group. 29 Group Model Building Session The 4.5-hour GMB session occurred in early April 2025. Session activities included an initial and final problem framing activity, instruction on stock and flow diagrams, creation of simple individual stock and flow diagrams, and two small group collaborative creation of complex stock and flow diagrams for the ES and CC workforce. Notably, responses to the initial problem framing activity were summarized by artificial intelligence (AI) during introductions and then presented to participants to prime them with outside perspectives. These activities are outlined in detail in Supplementary File 1 . Model Refinement and Validation After the meeting, the lead author refined the complex models created during the session, including by adding variables created via qualitative data collection from crisis program directors prior to the GMB (described here 30 ). Face validation was then sought for both diagrams from participants who were present in the ES and CC breakout rooms. Validation consisted of two virtual meetings per model during which participants were walked through the model, first discussing the underlying structure of the model and making corrections, and then doing the same for the variables and policies that impact the flow through the model. In this process, a few composite variables were created that directly interact with the model; this allowed variables with multiple drivers (e.g. variables influencing departure) to retain qualitative complexity, while preventing overspecification of the main model. each with participants from the corresponding GMB small group. GMB Effectiveness Analysis The initial and final problem framing activities were adapted from the method outlined by Fokkinga et al in 2009. 31 In these surveys, participants were asked to share their perception of the main problem related to the mobile crisis workforce pipeline, its cause, who the problem impacts, and three potential solutions. The initial and final problem framing activities were the same, except the initial activity also collected participant characteristics. The initial survey is presented in Supplementary File 2 . The first and second author independently applied inductive codes to (1) problem topic(s) and (2) affected group in pre- and post-responses, with inter-rater reliability calculated and disagreements resolved by discussion (κ=0.80 for topics; κ=0.85 for affected groups; calculations in Supplementary File 3 ). In cases in which more than one problem was identified, the topics of each problem were coded. A codebook is present in Supplementary File 3 which contains the unique codes used for the analysis of the topics and the affected groups. The identified groups were also given tags to indicate their level of specificity, and the percentage of identified groups at each level was calculated. Lastly, each of the three solutions for the problem(s) identified were coded according to the socioecological model of public health (SMPH). 32 This model was chosen because it naturally captures the range of possible solutions on a spectrum from individual to system level, thereby demonstrating how participants have changed their level of system thinking following GMB. 32 Each coder independently selected the single best level of the five potential levels of the SMPH for each of the three solutions given by each participant. Cohen’s kappa was calculated based on initial codes (κ =.71), before the authors met to resolve disagreements. Results Participant characteristics are described in Table 1 . 9 of 14 participants completed both the pre- and post-surveys, although 2 of these 9 participants missed the second hour of the 4.5-hour meeting due to an unforeseen conflict. 3 of 14 participants completed only the pre-survey, with one leaving the meeting after the third hour. Finally, 2 of 14 individuals completed neither survey, with one individual arriving during Introductions and staying for the remainder of the session, while the other individual attended only for the third and fourth hour of the meeting and left before the final half hour. Using GMB to Model the Mobile Crisis Workforce Pipeline Model Validation For the CC model, one participant in each meeting confirmed the underlying structure, noted no additional meaningful inflows (e.g., master’s/licensed clinicians migrating from other sectors), and affirmed outflows as depicted; minor revisions to salary components were made and applied to the ES model given shared determinants. For the ES model, one meeting (two participants) and a second (one participant) led to removal of a rarely used pathway (out-of-state entrants seeking IL certification) and two GMB-added variables judged not reflective of current practice. Overall, both models were deemed structurally sound with boundaries adequate to capture major inflows and outflows. Diagrams, Feedback Loops and Variables Two maps were created: one for the ES workforce ( Figure 1 ) and one for the CC workforce ( Figure 2 ). Both maps suggested a vicious cycle in which the workforce becomes smaller and less skilled over time unless burnout is reduced. This is visualized in Figure 3 , a causal-loop diagram based on the stock and flow models created during the GMB session. In the “Departure-Workload Reinforcing Loop” (R1), as staff departures increase, the number of trained staff decreases, increasing the workload among the remaining trained staff, subsequently increasing burnout and departures. Another loop called the “Departure-Training-Workload Reinforcing Loop” (R2) depicts that as trained staff decrease, after a delay, new hires increase, who each require time for training and supervision by the remaining trained staff members. This again increases the workload for those staff, furthering burnout and departures. Figure 1: Engagement Specialist Workforce Model CRSS = Certified Recovery Support Specialist; IDHS-DBHR = Illinois Department of Human Services Division of Behavioral Health and Recovery; ES = Engagement Specialist; HRSA = Health Resources and Services Administration; O = Opposite; PSW = Peer Support Worker; S = Same Figure 2: Crisis Counselor Workforce Model CADC = Certified Alcohol and Drug Counselor; LPHA = Licensed Practitioner of the Healing Arts; MHP = Mental Health Professional; O = Opposite direction relationship (increase in one variable decreases the other); QMHP = Qualified Mental Health Professional; S = Same Figure 3: Causal Loop Diagram of Mobile Crisis Workforce Burnout Dynamics O = Opposite; S = Same In addition, participants identified a host of drivers of burnout. These drivers are illustrated in Supplementary File 4 , along with the drivers of other complex composite variables created for salary, position awareness, position attractiveness, and applicant pool size. Determining GMB Effectiveness in Increasing Systems Thinking Results for the pre- and post-survey are shown in Table 2 . Dimensions of analyses included number of problems, coded themes, and affected groups added and dropped in the post-survey. Jaccard overlap indices were calculated for each participant to determine the relative overlap for each dimension between the pre- and post-surveys. The majority (7 of 9 participants) exhibited a change in one or more of these dimensions. Change in percentage of affected groups at each level of specificity was also calculated and is presented in Supplementary File 3 . SMPH-levels for solutions were stable between the pre- and post-survey. Across 54 coded solutions (pre n=27; post n=27), most targeted the Public Policy level (pre- 14/27; post 14/27) and the Institutional level (pre 10/27; post 11/27), with fewer at the Community level (pre 3/27; post 2/27) and none at Interpersonal or Intrapersonal. Primary-problem responses shortened from 22.1 ± 26.4 words (range 9–91) pre to 10.6 ± 9.1 (range 1–32) post; solution responses declined from 14.6 ± 7.25 (range 4–33) to 12.1 ± 7.3 (range 1–24). Discussion Model Creation GMB was able to effectively create two models that expert members from the GMB judged to have face validity. Not only did GMB produce two system structure diagrams of systems that have never been mapped previously, but it also surfaced a plethora of variables that impact inflow and outflow to the workforce. These can be parameterized, and the qualitative models may serve as the foundation for future simulation modeling efforts. This study suggests that GMB is a method by which other states may map their mobile crisis workforce pipelines as well. Many of the factors impacting the mobile crisis workforce uncovered in this study have been documented in the workforce literature on peer support specialists, 33–35 general mental health workers, 36–38 and emergency medical technicians, 39–41 and are discussed in depth in the companion paper to this one. 30 While the models share many drivers of system throughput, there are key differences between the two complex stock and flow models. The initial stock in the CC model reflects that CCs may have one of 9 distinct educational backgrounds per the IL Medicaid definition of a Mental Health Professional (MHP). 42 In this model, one stock of individuals from a plethora of sources from outside the boundaries of the model are eligible for the role, and a certain number join the workforce. This reflects the heterogeneity within the entry-level CC workforce, for which there is little data and no dedicated training pathway. The CC model has a four-stock career pathway, enabling CCs to advance within the workforce, should there be positions that pay a higher wage for obtaining additional education and credentials. In contrast, the ES model contains two distinct paths: the training program and independent pathways. In this model, ESs have only a two-stock pathway to advance: uncertified and certified. These differences have implications for policy design. Multiple stakeholders suggested the creation of a dedicated training pathway for MHPs, which they argued could help to standardize the capabilities of this workforce, potentially decreasing the amount of time required for shadowing and on-the-job training. On the other hand, with few opportunities for growth within the mobile crisis workforce, incentivizing ESs to stay by other means and decreasing burnout appears essential for maintaining workforce capacity. The next step for this line of work is to parameterize the models for system dynamics simulation modeling using administrative data from the CRSS-SP and Program 590. These simulations will test policies designed to strengthen the mobile crisis workforce. GMB Effectiveness The GMB effectiveness survey appears to be a feasible method by which to understand whether and how participants’ mental models shift over the course of the session. In this case, GMB seems capable of prompting multiple participants to reframe their mental model of the mobile crisis workforce pipeline. Jaccard indices of unique problems, problem themes, and affected groups identified by each participant demonstrate that new constructs consistently entered the mental models of participants by the end of the session. Though based only on a single-session sample, this empirically supports the effectiveness of GMB as an intervention for altering the mental models of key stakeholders in solving a complex workforce problem. Overall this study contributes to the growing literature that seeks to empirically evaluate the effectiveness of systems science methods in changing participant mental models. 43 There was little change in the SMPH levels of the solutions identified by participants, with solutions both before and after the session concentrated at the policy and institutional levels. This likely reflects the sample of individuals who were recruited to participate in the GMB. Their interest in GMB may indicate a prior tendency towards systems thinking. Many participants' worked in a policy space, and others were directors of crisis programs, consistent with policy and institutional solutions. Future work may seek to use a potentially more sensitive scale test if the solutions shifted toward a systems-perspective, such as the 12 Levels of Leverage framework by Meadows. 44 Response length analysis suggests shorter responses in the post-survey may be attributable to participant fatigue at the end of the 4.5 hour session. This is reinforced by the fact that three participants left without completing the survey. This underscores a challenge of studying the impact of GMBs intra-experimentally. While seeking responses to the post-survey 24 hours after the GMB to minimize fatigue may have boosted participation, this was not done to avoid confounding due to the time gap. One additional contribution of this study is that it highlights the potential for AI to aid in GMB facilitation. In this case, ChatGPT 4o rapidly summarized participant responses, which otherwise would not have been feasible given the small size of our facilitation team. This suggests that such tools may enhance current GMB scripts, especially when summarization of responses illustrates perspectives from other participants. This is consistent with emerging evidence that AI tools may help facilitate effective participatory research design. 45 Limitations This study has several limitations. While the structure of the model was validated, many proportion-based parameters (e.g. the CRSS-SP graduation rate) and delay values (e.g. duration time graduates on the training program pathway wait to take the exam) were not estimated and will need to be incorporated from data and expert estimates prior to simulation modeling. Many participants also reported lacking detailed knowledge of organizational salary determinants. Although salaries can be treated as an independent parameter during simulation, additional input from business managers would strengthen understanding of how organizational factors shape compensation. Moreover, the Health Resources and Services Administration entry pathway into the workforce was in nascent stages at the time of this work, and its development may alter the structure of the ES workforce in the future. Finally, the small number of participants completing both the initial and final problem framing surveys limits confidence in the magnitude of changes (e.g. in number of problems, Jaccard indices) in participant mental models, though it qualitatively demonstrates the feasibility of the adapted Fokkinga et al. evaluation framework. Conclusion Growing the mobile crisis workforce requires coordinated action by government, mental health systems, and training programs. Using Group Model Building (GMB), this study elicited the structure of the workforce pipeline and the interdependent drivers of capacity, and documented pre–post shifts in participants’ mental models using an instrument adapted from Fokkinga et al. These findings suggest that GMBs can facilitate cross-sector alignment and inform strategies for states seeking to expand and sustain their mobile crisis workforces. Declarations The study was reviewed by the Institutional Review Board at the University of North Carolina at Chapel Hill and determined to be exempt from human subjects review requirements. Formal consent requirements to participate were therefore waived. References Bommersbach TJ, Olfson M, Rhee TG (2024) National Trends in Emergency Department Visits for Suicide Attempts and Intentional Self-Harm. Am J Psychiatry 181(8):741–752. 10.1176/appi.ajp.20230397 CDC. Suicide Data and Statistics. Suicide Prevention. Accessed October 6 (2025) https://www.cdc.gov/suicide/facts/data.html National Association of State Mental Health Program Directors Research Institute. State Behavioral Health Workforce Shortages and Initiatives (2024) Accessed April 15, 2025. https://www.nri-inc.org/media/tghpz5uu/smha-workforce-shortages-2023.pdf Morse G, Salyers MP, Rollins AL, Monroe-DeVita M, Pfahler C (2012) Burnout in Mental Health Services: A Review of the Problem and Its Remediation. Adm Policy Ment Health Ment Health Serv Res 39(5):341–352. 10.1007/s10488-011-0352-1 Ramasamy RS, Thompson A, Simmons S (2022) Responding to Acute Mental Health Crises in Black Youth: Is It Safe to Call 911? Community Ment Health J Published online May 27. 10.1007/s10597-022-00980-4 Committee on Psychiatry The Community for the Group for the Advancement of Psychiatry. ROADMAP TO THE IDEAL CRISIS SYSTEM. Published online 2021 Substance Abuse and Mental Health Services Administration National Guidelines for Behavioral Health Crisis Care – A Best Practice Toolkit Knowledge Informing Transformation. Published online 2020. https://www.samhsa.gov/sites/default/files/national-guidelines-for-behavioral-health-crisis-care-02242020.pdf Edmonds A, Saint-Phard E, Harrison E, Natzke B, Vine M, Brown J (2025) Financing Crisis Services Through Public and Commercial Insurance: Current Landscape and Future Opportunities . https://aspe.hhs.gov/sites/default/files/documents/39f90405c77dd3b192c72a182ed5202e/financing-crisis-services-current-future-opportunities.pdf McNab D, McKay J, Shorrock S, Luty S, Bowie P (2020) Development and application of ‘systems thinking’ principles for quality improvement. BMJ Open Qual 9(1):e000714. 10.1136/bmjoq-2019-000714 Barber P, López-Valcárcel BG (2010) Forecasting the need for medical specialists in Spain: application of a system dynamics model. Hum Resour Health 8(1):24. 10.1186/1478-4491-8-24 Taba ST, Atkinson SR, Lewis S, Chung KSK, Hossain L (2015) A systems life cycle approach to managing the radiology profession: an Australian perspective. Aust Health Rev Publ Aust Hosp Assoc 39(2):228–239. 10.1071/AH14113 Brailsford S, De Silva D (2015) How many dentists does Sri Lanka need? Modelling to inform policy decisions. J Oper Res Soc 66(9):1566–1577. 10.1057/jors.2014.136 Cave S, Willis G (2020) System Dynamics and Workforce Planning. In: Dangerfield B (ed) System Dynamics. Springer US, pp 431–457. doi: 10.1007/978-1-4939-8790-0_659 Hassmiller Lich K, Urban JB, Frerichs L, Dave G (2017) Extending systems thinking in planning and evaluation using group concept mapping and system dynamics to tackle complex problems. Eval Program Plann 60:254–264. 10.1016/j.evalprogplan.2016.10.008 Scott RJ, Cavana RY, Cameron D (2016) Mechanisms for Understanding Mental Model Change in Group Model Building. Syst Res Behav Sci 33(1):100–118. 10.1002/sres.2303 Doyle JK, Ford DN (1998) Mental models concepts for system dynamics research. Syst Dyn Rev 14(1):3–29. 10.1002/(SICI)1099-1727 ::AID-SDR140>3.0.CO;2-K Huber B, Belenky N, Watson C, Gibbons B (2023) Reimbursement Mechanisms and Challenges in Team-Based Behavioral Health Care. Published online Oct 17, https://www.ncbi.nlm.nih.gov/books/NBK606628/ Gupta P, Jacobs L, Luk K, Jones T (2026) Acting as the Face of a Broken System: Challenges Experienced by Mobile Crisis Workers. Community Ment Health J Published online April 6. 10.1007/s10597-026-01609-6 Rouwette EAJA, Vennix JAM, Mullekom TV (2002) Group model building effectiveness: a review of assessment studies. Syst Dyn Rev 18(1):5–45. 10.1002/sdr.229 Estrada-Magbanua WM, Huang TTK, Lounsbury DW et al (2023) Application of group model building in implementation research: A systematic review of the public health and healthcare literature. Das JK, ed. PLOS ONE . ;18(8):e0284765. 10.1371/journal.pone.0284765 Siokou C, Morgan R, Shiell A (2014) Group model building: a participatory approach to understanding and acting on systems. Public Health Res Pract 25(1):e2511404. 10.17061/phrp2511404 Behavioral Health Workforce Shortage (2024) Written Testimony. Published online January 25, https://www.ilga.gov/documents/house/committees/103Documents/HMEH/Book%20-%20Behavioral%20Health%20Workforce%20Shortage%201-25-24.pdf Illinois Department of Human Services. Illinois 988 FAQs - August 2022 Edition. 988 Suicide & Crisis Lifeline Planning Page (2022) August https://www.dhs.state.il.us/page.aspx?item=145429 Illinois Certification Board. The Illinois Model For Mental Health Certified Recovery Support Specialist (CRSS) Published online July 2024. https://iaodapca.org/Portals/0/PDF/CRSS%20Model%20April%202023.pdf?ver=u7GTIHA-WLcYKR 1lAk0hBw%3D%3D×tamp=1682975157630 Illinois Certification Board, International Certification and Reciprocity Consortium. The Illinois Model For International Certification of Peer Recovery Specialist (CPRS) Published online July 2024. https://iaodapca.org/Portals/0/PDF/CPRS%20Model%20April%202023.pdf?ver=IM7 rZeJP_40oGJQm6ZWv2A%3D%3D×tamp=1682975616608 2539 Notice of Funding Opportunity (590). Illinois Department of Human Services. April 13 (2021) https://www.dhs.state.il.us/page.aspx?item=131575 Simon J, Guynn I, Dowsett C, Lich KH (2026) Systems exploration workshops: Using a virtual group model building approach to advance public health systems change. Eval Program Plann 114:102698. 10.1016/j.evalprogplan.2025.102698 Magnani R, Sabin K, Saidel T, Heckathorn D (2005) Review of sampling hard-to-reach and hidden populations for HIV surveillance. AIDS 19(Supplement 2):S67–S72. 10.1097/01.aids.0000172879.20628.e1 Vennix JA (2001) Chapter 4: Designing Group Model-Building Projects. Group Model Building: Facilitating Team Learning Using System Dynamics. Reprinted. Wiley;, pp 101–120 Fine J, Guta M, Newton H, Sowa N, Watson A, Lich KH (2026) A Qualitative Systems Analysis of the Illinois Mobile Crisis Workforce: Crisis Program Director Perspectives and Policy Recommendations. Rev Preprint posted online April 16. 10.21203/rs.3.rs-9417637/v1 Fokkinga B, Bleijenbergh I, Vennix J (2009) Group model building evaluation in single cases: A method to assess changes in mental models. In: Proceedings of the 27th International Conference of the System Dynamics Society McLeroy KR, Bibeau D, Steckler A, Glanz K (1988) An Ecological Perspective on Health Promotion Programs. Health Educ Q 15(4):351–377. 10.1177/109019818801500401 Bell JS, Watson DP, Griffin T et al (2025) Workforce outcomes among substance use peer supports: a scoping review of individual and organizational influences. Front Public Health 12. 10.3389/fpubh.2024.1515264 Krueger DK, Zerden LDS, Jensen TM, Lombardi BM (2026) Burnout and Job Satisfaction among U.S. Peer Recovery Support Specialists: Personal Resilience and Satisfaction with Supervisor and Organizational Support as Mediating Mechanisms. Community Ment Health J 62(2):208–218. 10.1007/s10597-025-01515-3 Collier KM, Halvorsen CJ, Fortuna KL (2024) Assessing Mental Healthcare Worker Experiences of Workplace Fairness and Organizational Value: A National Survey of Peer-Support Specialists. Workplace Health Saf 72(1):14–20. 10.1177/21650799231200028 Brabson LA, Harris JL, Lindhiem O, Herschell AD (2020) Workforce Turnover in Community Behavioral Health Agencies in the USA: A Systematic Review with Recommendations. Clin Child Fam Psychol Rev 23(3):297–315. 10.1007/s10567-020-00313-5 Hallett E, Simeon E, Amba V, Howington D, McConnell KJ, Zhu JM (2024) Factors Influencing Turnover and Attrition in the Public Behavioral Health System Workforce: Qualitative Study. Psychiatr Serv 75(1):55–63. 10.1176/appi.ps.20220516 Fukui S, Rollins AL, Salyers MP (2020) Characteristics and Job Stressors Associated With Turnover and Turnover Intention Among Community Mental Health Providers. Psychiatr Serv 71(3):289–292. 10.1176/appi.ps.201900246 Patterson PD, Probst JC, Leith KH, Corwin SJ, Powell MP (2005) Recruitment and retention of emergency medical technicians: a qualitative study. J Allied Health 34(3):153–162 Patterson PD, Moore CG, Sanddal ND, Wingrove G, LaCroix B (2009) Characterizing job satisfaction and intent to leave among nationally registered emergency medical technicians: an analysis of the 2005 LEADS survey. J Allied Health 38(3):e84–91 Kamholz JC, Gage CB, Van Den Bergh SL, Logan LT, Powell JR, Panchal AR (2025) Association Between Organizational Culture and Emergency Medical Service Clinician Turnover. Int J Environ Res Public Health 22(5):756. 10.3390/ijerph22050756 Illinois Administrative Code - Title 59 - Mental Health . 132.25:Subpart A: General Provisions. http://www.dhs.state.il.us/OneNetLibrary/27896/documents/By_Division/MentalHealth/Rule132/JCAR%20final%20and%20emergency%2007.07.pdf Frerichs L, Young TL, Dave G, Stith D, Corbie-Smith G, Hassmiller Lich K (2018) Mind maps and network analysis to evaluate conceptualization of complex issues: A case example evaluating systems science workshops for childhood obesity prevention. Eval Program Plann 68:135–147. 10.1016/j.evalprogplan.2018.03.003 Bolton KA, Whelan J, Fraser P, Bell C, Allender S, Brown AD (2022) The Public Health 12 framework: interpreting the ‘Meadows 12 places to act in a system’ for use in public health. Arch Public Health 80(1):72. 10.1186/s13690-022-00835-0 Van Den Broek S, Sankaran S, De Wit J, De Rooij A Exploring the Supportive Role of Artificial Intelligence in Participatory Design: A Systematic Review. In: Participatory Design Conference 2024 . ACM; 2024:37–44. 10.1145/3661455.3669868 Tables Table 1: Group Model Building Participant Characteristics Variable Item Problem Framing Activity Completion Status Total ( n = 14) Both pre- and post-activity (n = 9) Pre-activity only (n = 3) Neither (n = 2) Present >90% of session Yes 7 (77.8%) 2 (66.7%) 1 (50.0%) 10 (71.4%) No 2 (22.2%) 1 (33.3%) 1 (50.0%) 4 (28.6%) Gender Female 9 (100.0%) 2 (66.7%) 1 (50.0%) 12 (85.7%) Male 0 (0.0%) 1 (33.3%) 1 (50.0%) 2 (14.3%) Race Asian 1 (11.1%) 0 (0.0%) — 1 (8.3%) Black 1 (11.1%) 1 (33.3%) — 2 (16.7%) White 7 (77.8%) 2 (66.7%) — 9 (75.0%) Missing (n) 0 0 2 2 Age (years) Mean ± SD 40.9 ± 6.8 42.0 ± NA NA 41.0 ± 6.5 Missing (n) 0 2 2 4 Hispanic No 9 (100.0%) 2 (100.0%) — 11 (100.0%) Missing (n) 0 1 2 3 Role relative to mobile crisis workforce Certified Peer Support Specialists 0 (0.0%) 0 (0.0%) 1 (50.0%) 1 (7.1%) Provides Crisis Care 3 (33.3%) 1 (33.3%) 0 (0.0%) 4 (28.6%) Policymaker 4 (44.4%) 2 (66.7%) 1 (50.0%) 7 (50.0%) Trains Peer Support Specialists 2 (22.2%) 0 (0.0%) 0 (0.0%) 2 (14.3%) Employer type Academic–Government Partnership 2 (22.2%) 0 (0.0%) 1 (50.0%) 3 (21.4%) Educational Institution Training Peer Support Specialists 2 (22.2%) 0 (0.0%) 0 (0.0%) 2 (14.3%) Government 2 (22.2%) 2 (66.7%) 0 (0.0%) 4 (28.6%) Non-profit 0 (0.0%) 0 (0.0%) 1 (50.0%) 1 (7.1%) Organizations Providing Crisis Services 3 (33.3%) 1 (33.3%) 0 (0.0%) 4 (28.6%) Ever provided behavioral health services Yes 9 (100.0%) 3 (100.0%) 1 (100.0%) 13 (100.0%) Missing (n) 0 0 1 1 CRSS/CPRS certified Yes 2 (22.2%) 1 (33.3%) — 3 (25.0%) No 7 (77.8%) 2 (66.7%) — 9 (75.0%) Missing (n) 0 0 2 2 Provided or directed mobile crisis services Yes 5 (55.6%) 2 (66.7%) — 7 (58.3%) No 4 (44.4%) 1 (33.3%) — 5 (41.7%) Missing (n) 0 0 2 2 Notes: Percentages are computed by column, excluding missing (shown as “Missing (n)”). Missing values are included only when at least 1 value is nonzero. A dash (—) indicates the percentage is undefined because all responses in that column were missing for that characteristic. Age is reported as mean ± SD; NA reflects insufficient data. Abbreviations: CRSS = Certified Recovery Support Specialist; CPRS = Certified Peer Recovery Specialist. Table 2. Summary of Pre–Post Changes in Participant Responses Following the GMB Session Participant Response Measure Dimensions Primary Problems Problem Themes Affected Groups Per-participant count (Pre-survey) — Average (Range) 1.3 (1–2) 1.3 (1–2) 2.4 (1–3) Per-participant count (Post-survey) — Average (Range) 1.2 (1–3) 1.3 (1–3) 2.8 (2–5) Number of participants with any new dimension in the post-survey, n/n total (%) 5/9 (55.6%) 5/9 (55.6%) 6/9 (66.7%) Number of added dimensions in the post-survey — Average (Range) .7 (0–2) .8 (0–2) 1.2 (0–4) Number of dropped dimensions in the post-survey — Average (Range) .8 (0–2) .8 (0–2) .9 (0–2) Number of participants with any added or dropped dimension in the post-survey, n/N (%) 6/9 (66.7%) 7/9 (77.8%) 6/9 (66.7%) Overlap of dimensions (Jaccard index) — Median (Range) 0.3 (0–1.00) 0.3 (0–1.00) 0.3 (0.14–1.00) Note: Jaccard index = intersection of unique terms ÷ total unique terms, ranging from 0 (no overlap) to 1 (complete overlap). Additional Declarations The authors declare potential competing interests as follows: Author AW reports an ongoing contract with the Illinois Department of Human Services Division of Behavioral Health and Recovery to collect data related to its 9-8-8 and mobile crisis (Program 590) grant programs; this relationship did not provide funding for the present study. Authors KHL and HN report work related to mental health crisis systems in North Carolina, funded by the North Carolina Department of Health and Human Services, Division of Mental Health, Developmental Disabilities, and Substance Use Services; these relationships did not provide funding for the present study. Supplementary Files SupplementaryFile1GroupModelBuildingAgenda.docx Supplementary File 1 SupplementaryFile2GroupModelBuildingProblemFramingActivity.pdf Supplementary File 2 SupplementaryFile3CodebookandKappas.xlsx Supplementary File 3 SupplementaryFile4AdditionalVariables.docx Supplementary File 4 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9568624","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":631944802,"identity":"fa7f86d1-2a3e-49aa-b334-26e19dce189c","order_by":0,"name":"Jeremy Fine","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYBACxobEBwcYGGyAzASo0AGCWpINgGrSSNDCwJBsACQOk6CFuT2Z8XBBxflofvYENumCGgY5vhsJ+LUw9jxmODzjzO3cmT0P2KRnHGMwliSoZUb+gcO8bbdzN9wA2sLbwJC4gbCWZIbDvP/O5e6HaqknUkvDgdwNEhAtCQZE+YXnWHLujDMPm615jkkYzjzzAL8Ww/Zk5s88NXa5/e3JB2/z1NjI8x0nYIthA8JCEFMCv3IQkCesZBSMglEwCkY8AAD2VUe/Z7Bm/AAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-1055-3026","institution":"University of North Carolina at Chapel Hill School of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Jeremy","middleName":"","lastName":"Fine","suffix":""},{"id":631944803,"identity":"ba8008a4-6eee-4299-b26f-83e49fd5e1b3","order_by":1,"name":"Maria Guta","email":"","orcid":"https://orcid.org/0009-0002-2025-2400","institution":"University of North Carolina at Chapel Hill","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Guta","suffix":""},{"id":631944804,"identity":"8a21a5b6-f4db-445f-b0b1-b4f0ed7734bb","order_by":2,"name":"Helen Newton","email":"","orcid":"https://orcid.org/0000-0002-0989-953X","institution":"University of North Carolina at Chapel Hill School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Helen","middleName":"","lastName":"Newton","suffix":""},{"id":631944805,"identity":"7b61a9a4-b5a0-4bec-b9e1-7adeb5317c3a","order_by":3,"name":"Nathaniel Sowa","email":"","orcid":"https://orcid.org/0000-0002-3021-4005","institution":"University of North Carolina at Chapel Hill School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Nathaniel","middleName":"","lastName":"Sowa","suffix":""},{"id":631944806,"identity":"3df484d4-7750-45c3-a461-27a8bdf46cb1","order_by":4,"name":"Amy Watson","email":"","orcid":"https://orcid.org/0000-0002-5310-6293","institution":"Wayne State University","correspondingAuthor":false,"prefix":"","firstName":"Amy","middleName":"","lastName":"Watson","suffix":""},{"id":631944807,"identity":"72bbda79-1347-43c1-872e-2440e9737dc3","order_by":5,"name":"Kristen Hassmiller Lich","email":"","orcid":"https://orcid.org/0000-0002-3311-4202","institution":"University of North Carolina at Chapel Hill","correspondingAuthor":false,"prefix":"","firstName":"Kristen","middleName":"Hassmiller","lastName":"Lich","suffix":""}],"badges":[],"createdAt":"2026-04-29 17:17:06","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":true,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9568624/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9568624/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109068447,"identity":"9c42b324-8133-4616-92cc-21cdf7d6eec4","added_by":"auto","created_at":"2026-05-12 10:11:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":926061,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cu\u003e\u003cstrong\u003eFigure 1: Engagement Specialist Workforce Model\u003c/strong\u003e\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eCRSS = Certified Recovery Support Specialist; IDHS-DBHR = Illinois Department of Human Services Division of Behavioral Health and Recovery; ES = Engagement Specialist; HRSA = Health Resources and Services Administration; O = Opposite; PSW = Peer Support Worker; S = Same\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-9568624/v1/6ac5c3597c2fd3554a030343.png"},{"id":109070247,"identity":"999aeb17-6c08-4d9c-9c3c-caa9e797ee34","added_by":"auto","created_at":"2026-05-12 10:30:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":180064,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cu\u003e\u003cstrong\u003e\u0026nbsp;Figure 2: Crisis Counselor Workforce Model\u003c/strong\u003e\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eCADC = Certified Alcohol and Drug Counselor; LPHA = Licensed Practitioner of the Healing Arts; MHP = Mental Health Professional; O = Opposite direction relationship (increase in one variable decreases the other); QMHP = Qualified Mental Health Professional; S = Same \u0026nbsp;\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-9568624/v1/bb99042b6a7a12feff6c1556.png"},{"id":109069283,"identity":"f1cf1f5b-f90a-4088-8778-d0c6e63edcc0","added_by":"auto","created_at":"2026-05-12 10:22:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":162719,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cu\u003e\u003cstrong\u003eFigure 3: Causal Loop Diagram of Mobile Crisis Workforce Burnout Dynamics\u003c/strong\u003e\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eO = Opposite; S = Same\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-9568624/v1/4776a94f8cdc30e24fb553ce.png"},{"id":109073179,"identity":"4dda0e99-00d9-424f-8f4d-cc966346c405","added_by":"auto","created_at":"2026-05-12 10:44:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1499031,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9568624/v1/af8f9bfb-ab37-4767-be5a-65ad695ccf3e.pdf"},{"id":109069277,"identity":"cc9e2ee8-031b-48bd-8ca2-9e9a153cc76f","added_by":"auto","created_at":"2026-05-12 10:22:13","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":177331,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary File 1\u003c/p\u003e","description":"","filename":"SupplementaryFile1GroupModelBuildingAgenda.docx","url":"https://assets-eu.researchsquare.com/files/rs-9568624/v1/b414690573b45a2d9abbea7d.docx"},{"id":109068491,"identity":"3b70a7ba-c46a-4deb-b995-d50eea6ca38f","added_by":"auto","created_at":"2026-05-12 10:12:41","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":214837,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary File 2\u003c/p\u003e","description":"","filename":"SupplementaryFile2GroupModelBuildingProblemFramingActivity.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9568624/v1/d5893813445e2824afc798ba.pdf"},{"id":109069285,"identity":"04011f2d-0267-44b7-98ea-8c4ebceaf23c","added_by":"auto","created_at":"2026-05-12 10:22:20","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":18760,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary File 3\u003c/p\u003e","description":"","filename":"SupplementaryFile3CodebookandKappas.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-9568624/v1/2f5d149b0a6b2969ad9a5e21.xlsx"},{"id":109069280,"identity":"c104cfef-76d1-491e-9608-86821ea8e5e5","added_by":"auto","created_at":"2026-05-12 10:22:15","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":33101,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary File 4\u003c/p\u003e","description":"","filename":"SupplementaryFile4AdditionalVariables.docx","url":"https://assets-eu.researchsquare.com/files/rs-9568624/v1/d8c03ba3c1f01e0eebade5d1.docx"}],"financialInterests":"The authors declare potential competing interests as follows: Author AW reports an ongoing contract with the Illinois Department of Human Services Division of Behavioral Health and Recovery to collect data related to its 9-8-8 and mobile crisis (Program 590) grant programs; this relationship did not provide funding for the present study. Authors KHL and HN report work related to mental health crisis systems in North Carolina, funded by the North Carolina Department of Health and Human Services, Division of Mental Health, Developmental Disabilities, and Substance Use Services; these relationships did not provide funding for the present study.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eUsing Group Model Building to Map the Mobile Crisis Workforce Pipeline in Illinois and Broaden Stakeholder Perspectives\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Plain language summary","content":"\u003cp\u003eGroup Model Building (GMB) is a method that gathers stakeholders from a particular system to solve a particular problem of interest by creating a map of their system. In this case, GMB was used to create a map of the mobile crisis workforce pipeline in IL. Additionally, a qualitative survey was used to demonstrate that GMB can help participants view problems from a systems perspective.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eThe incidence of mental health crises in the United States (US) has increased substantially in recent years.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Unfortunately, in many places there is an insufficient workforce to meet this need; 40 of 43 polled states reported a crisis workforce shortage in 2023,\u003csup\u003e3\u003c/sup\u003e consistent with evidence that the mental health workforce generally faces a high rate of turnover associated with burnout.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Mobile Crisis Teams (MCTs) provide community-based crisis intervention and referral to clinically appropriate resources, and have been recommended as a less restrictive alternative to law enforcement.\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e The Substance Abuse and Mental Health Services Administration (SAMHSA) 2020 guidelines recommend that the team consists of an individual trained to use their lived experiences with mental health conditions to support others in recovery (i.e. a peer support specialist) and a clinical professional.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e Despite new policies to expand the mobile crisis workforce, optimal strategies remain unclear given the challenge of sustaining 24/7 coverage with entry-level peer and clinical staff funded through braided streams.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eSystems thinking is a conceptual framework that helps reveal how the structures underlying a system (e.g. the mobile crisis workforce pipeline) produce a particular outcome of interest (e.g. capacity of the workforce); it can help decisionmakers learn how changes in the system affect workforce outcomes.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Group Model Building (GMB) is a systems thinking method that has been used to solve healthcare workforce issues by engaging key stakeholders to create a qualitative illustration of the system structure (i.e. a stock-and-flow model), a quantified simulation model, and/or collaboratively-developed strategies capable of improving objectives.\u003csup\u003e\u003cspan additionalcitationids=\"CR11 CR12 CR13\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e By mapping how actions within one part of a system affect others, GMB helps participants recognize how siloed practices contribute to system-level problems, thus changing their internal conceptual representation of the system (i.e. their mental models).\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e While GMB has never been used to model the mobile crisis workforce, the complex funding streams and unclear workforce pathways mean it may be a valuable tool for solving mobile crisis workforce issues.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e Additionally, GMB is generally thought to expand participants\u0026rsquo; mental models,\u003csup\u003e19\u003c/sup\u003e little research explicitly and empirically tests this.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e This is a key gap in the literature, as GMB is not just a modeling tool: it is an intervention for building shared understanding among stakeholders from different siloes.\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThis paper therefore has two aims: 1) apply GMB to model the mobile crisis workforce pipeline, and 2) to empirically measure the effectiveness of GMB in incorporating systems thinking into the mental models of participants.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eEthical Approval\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was deemed exempt\u0026nbsp;by the Institutional Review Board of the lead author.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStudy Setting\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFor this study, stakeholders from Illinois (IL) were recruited for a GMB session designed to model the state’s mobile crisis workforce pipeline. IL was chosen because the state has enacted policies to rapidly expand their MCT infrastructure and workforce, and the to leadership at the Illinois Department of Human Services Division of Behavioral Health and Recovery (IDHS-DBHR) was willing to engage with the lead author. Anecdotal evidence from stakeholders in IDHS-DBHR and testimony to the IL General Assembly from representatives of behavioral health crisis organizations confirmed that IL faces shortages like those reported around the US.\u003csup\u003e22\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIL is expanding its mobile crisis infrastructure in accordance with the best practice guidelines issued by SAMHSA 2020.\u003csup\u003e23\u003c/sup\u003e This guidance recommends that MCTs be composed of peer support specialists, referred to as Engagement Specialists (ESs) in IL, and clinical professionals, referred to as Crisis Counselors (CCs) in IL. In part to generate a trained-ES workforce, in 2021 IDHS-DBHR enacted the Certified Recovery Support Specialist Program (CRSS-SP), which financially supports adults living in recovery from a behavioral health challenge in obtaining peer specialist training at educational institutions throughout the state. After 100 hours of classroom training and 300 internship hours, students graduate, and are eligible to sit for a certification exam. Prior to 2021, the only route to certification was the “independent pathway,” which involves piecing together 100 hours of course work from various sources and completing 2000 hours of work experience before taking the exam.\u003csup\u003e24,25\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eTo ensure there is an adequate network of MCTs across the state, in 2021 IDHS-DBHR initiated a grant program called Program 590, which provides grant dollars to organizations that provide mobile crisis services.\u003csup\u003e26\u003c/sup\u003e These policies exist in a complex and fragmented training, administrative, care-delivery, and funding ecosystems; such landscapes are well-suited to benefit from GMB.\u003csup\u003e27\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eParticipants and Recruitment\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThree initial participants (i.e. sample seeds) were used to initiate snowball sampling for the GMB session: two deputy directors from the IL IDHS-DBHR and the fifth author of this study. These seeds were chosen due to their non-overlapping networks to prevent over-representation of a particular network or group.\u003csup\u003e28\u003c/sup\u003e A key recruitment goal was to include equal numbers of individuals knowledgeable about the ES and CC workforces in the GMB session. This goal was achieved through the participation of 14 individuals, approximately evenly divided between ES and CC workforce expertise. This ensured thorough mapping of both pipelines while avoiding an excessively large group.\u003csup\u003e29\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGroup Model Building Session\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe 4.5-hour GMB session occurred in early April 2025. Session activities included an initial and final problem framing activity, instruction on stock and flow diagrams, creation of simple individual stock and flow diagrams, and two small group collaborative creation of complex stock and flow diagrams for the ES and CC workforce. Notably, responses to the initial problem framing activity were summarized by artificial intelligence (AI) during introductions and then presented to participants to prime them with outside perspectives. These activities are outlined in detail in \u003cstrong\u003eSupplementary File 1\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eModel Refinement and Validation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAfter the meeting, the lead author refined the complex models created during the session, including by adding variables created via qualitative data collection from crisis program directors prior to the GMB (described here\u003csup\u003e30\u003c/sup\u003e). Face validation was then sought for both diagrams from participants who were present in the ES and CC breakout rooms. Validation consisted of two virtual meetings per model during which participants were walked through the model, first discussing the underlying structure of the model and making corrections, and then doing the same for the variables and policies that impact the flow through the model. In this process, a few composite variables were created that directly interact with the model; this allowed variables with multiple drivers (e.g. variables influencing departure) to retain qualitative complexity, while preventing overspecification of the main model. each with participants from the corresponding GMB small group.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGMB Effectiveness Analysis\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe initial and final problem framing activities were adapted from the method outlined by Fokkinga et al in 2009.\u003csup\u003e31\u003c/sup\u003e In these surveys, participants were asked to share their perception of the main problem related to the mobile crisis workforce pipeline, its cause, who the problem impacts, and three potential solutions. The initial and final problem framing activities were the same, except the initial activity also collected participant characteristics. The initial survey is presented in \u003cstrong\u003eSupplementary File 2\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe first and second author independently applied inductive codes to (1) problem topic(s) and (2) affected group in pre- and post-responses, with inter-rater reliability calculated and disagreements resolved by discussion (κ=0.80 for topics; κ=0.85 for affected groups; calculations in \u003cstrong\u003eSupplementary File 3\u003c/strong\u003e). In cases in which more than one problem was identified, the topics of each problem were coded. A codebook is present in \u003cstrong\u003eSupplementary File 3\u003c/strong\u003e which contains the unique codes used for the analysis of the topics and the affected groups. The identified groups were also given tags to indicate their level of specificity, and the percentage of identified groups at each level was calculated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Lastly, each of the three solutions for the problem(s) identified were coded according to the socioecological model of public health (SMPH).\u003csup\u003e32\u003c/sup\u003e This model was chosen because it naturally captures the range of possible solutions on a spectrum from individual to system level, thereby demonstrating how participants have changed their level of system thinking following GMB.\u003csup\u003e32\u003c/sup\u003e Each coder independently selected the single best level of the five potential levels of the SMPH for each of the three solutions given by each participant. Cohen’s kappa was calculated based on initial codes (κ =.71), before the authors met to resolve disagreements.\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eParticipant characteristics are described in \u003cstrong\u003eTable 1\u003c/strong\u003e. 9 of 14 participants completed both the pre- and post-surveys, although 2 of these 9 participants missed the second hour of the 4.5-hour meeting due to an unforeseen conflict. 3 of 14 participants completed only the pre-survey, with one leaving the meeting after the third hour. Finally, 2 of 14 individuals completed neither survey, with one individual arriving during Introductions and staying for the remainder of the session, while the other individual attended only for the third and fourth hour of the meeting and left before the final half hour.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eUsing GMB to Model the Mobile Crisis Workforce Pipeline\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eModel Validation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFor the CC model, one participant in each meeting confirmed the underlying structure, noted no additional meaningful inflows (e.g., master\u0026rsquo;s/licensed clinicians migrating from other sectors), and affirmed outflows as depicted; minor revisions to salary components were made and applied to the ES model given shared determinants. For the ES model, one meeting (two participants) and a second (one participant) led to removal of a rarely used pathway (out-of-state entrants seeking IL certification) and two GMB-added variables judged not reflective of current practice. Overall, both models were deemed structurally sound with boundaries adequate to capture major inflows and outflows.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDiagrams, Feedback Loops and Variables\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eTwo maps were created: one for the ES workforce (\u003cstrong\u003eFigure 1\u003c/strong\u003e) and one for the CC workforce (\u003cstrong\u003eFigure 2\u003c/strong\u003e). Both maps suggested a vicious cycle in which the workforce becomes smaller and less skilled over time unless burnout is reduced. This is visualized in \u003cstrong\u003eFigure 3\u003c/strong\u003e, a causal-loop diagram based on the stock and flow models created during the GMB session. In the \u0026ldquo;Departure-Workload Reinforcing Loop\u0026rdquo; (R1), as staff departures increase, the number of trained staff decreases, increasing the workload among the remaining trained staff, subsequently increasing burnout and departures. Another loop called the \u0026ldquo;Departure-Training-Workload Reinforcing Loop\u0026rdquo; (R2) depicts that as trained staff decrease, after a delay, new hires increase, who each require time for training and supervision by the remaining trained staff members. This again increases the workload for those staff, furthering burnout and departures.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1: Engagement Specialist Workforce Model\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCRSS = Certified Recovery Support Specialist; IDHS-DBHR = Illinois Department of Human Services Division of Behavioral Health and Recovery; ES = Engagement Specialist; HRSA = Health Resources and Services Administration; O = Opposite; PSW = Peer Support Worker; S = Same\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 2: Crisis Counselor Workforce Model\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCADC = Certified Alcohol and Drug Counselor; LPHA = Licensed Practitioner of the Healing Arts; MHP = Mental Health Professional; O = Opposite direction relationship (increase in one variable decreases the other); QMHP = Qualified Mental Health Professional; S = Same\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 3: Causal Loop Diagram of Mobile Crisis Workforce Burnout Dynamics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eO = Opposite; S = Same\u003c/p\u003e\n\u003cp\u003eIn addition, participants identified a host of drivers of burnout. These drivers are illustrated in \u003cstrong\u003eSupplementary File 4\u003c/strong\u003e, along with the drivers of other complex composite variables created for salary, position awareness, position attractiveness, and applicant pool size.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDetermining GMB Effectiveness in Increasing Systems Thinking\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eResults for the pre- and post-survey are shown in \u003cstrong\u003eTable 2\u003c/strong\u003e. Dimensions of analyses included number of problems, coded themes, and affected groups added and dropped in the post-survey. Jaccard overlap indices were calculated for each participant to determine the relative overlap for each dimension between the pre- and post-surveys. The majority (7 of 9 participants) exhibited a change in one or more of these dimensions. Change in percentage of affected groups at each level of specificity was also calculated and is presented in \u003cstrong\u003eSupplementary File 3\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSMPH-levels for solutions were stable between the pre- and post-survey. Across 54 coded solutions (pre n=27; post n=27), most targeted the Public Policy level (pre- 14/27; post 14/27) and the Institutional level (pre 10/27; post 11/27), with fewer at the Community level (pre 3/27; post 2/27) and none at Interpersonal or Intrapersonal. Primary-problem responses shortened from 22.1 \u0026plusmn; 26.4 words (range 9\u0026ndash;91) pre to 10.6 \u0026plusmn; 9.1 (range 1\u0026ndash;32) post; solution responses declined from 14.6 \u0026plusmn; 7.25 (range 4\u0026ndash;33) to 12.1 \u0026plusmn; 7.3 (range 1\u0026ndash;24).\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cem\u003eModel Creation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eGMB was able to effectively create two models that expert members from the GMB judged to have face validity. Not only did GMB produce two system structure diagrams of systems that have never been mapped previously, but it also surfaced a plethora of variables that impact inflow and outflow to the workforce. These can be parameterized, and the qualitative models may serve as the foundation for future simulation modeling efforts. This study suggests that GMB is a method by which other states may map their mobile crisis workforce pipelines as well.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Many of the factors impacting the mobile crisis workforce uncovered in this study have been documented in the workforce literature on peer support specialists,\u003csup\u003e33–35\u003c/sup\u003e general mental health workers,\u003csup\u003e36–38\u003c/sup\u003e and emergency medical technicians,\u003csup\u003e39–41\u003c/sup\u003e and are discussed in depth in the companion paper to this one.\u003csup\u003e30\u003c/sup\u003e While the models share many drivers of system throughput, there are key differences between the two complex stock and flow models. The initial stock in the CC model reflects that CCs may have one of 9 distinct educational backgrounds per the IL Medicaid definition of a Mental Health Professional (MHP).\u003csup\u003e42\u003c/sup\u003e In this model, one stock of individuals from a plethora of sources from outside the boundaries of the model are eligible for the role, and a certain number join the workforce. This reflects the heterogeneity within the entry-level CC workforce, for which there is little data and no dedicated training pathway. The CC model has a four-stock career pathway, enabling CCs to advance within the workforce, should there be positions that pay a higher wage for obtaining additional education and credentials. \u0026nbsp;In contrast, the ES model contains two distinct paths: the training program and independent pathways. In this model, ESs have only a two-stock pathway to advance: uncertified and certified.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese differences have implications for policy design. Multiple stakeholders suggested the creation of a dedicated training pathway for MHPs, which they argued could help to standardize the capabilities of this workforce, potentially decreasing the amount of time required for shadowing and on-the-job training. On the other hand, with few opportunities for growth within the mobile crisis workforce, incentivizing ESs to stay by other means and decreasing burnout appears essential for maintaining workforce capacity.\u003c/p\u003e\n\u003cp\u003eThe next step for this line of work is to parameterize the models for system dynamics simulation modeling using administrative data from the CRSS-SP and Program 590. These simulations will test policies designed to strengthen the mobile crisis workforce.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eGMB Effectiveness\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe GMB effectiveness survey appears to be a feasible method by which to understand whether and how participants’ mental models shift over the course of the session. In this case, GMB seems capable of prompting multiple participants to reframe their mental model of the mobile crisis workforce pipeline. Jaccard indices of unique problems, problem themes, and affected groups identified by each participant demonstrate that new constructs consistently entered the mental models of participants by the end of the session. Though based only on a single-session sample, this empirically supports the effectiveness of GMB as an intervention for altering the mental models of key stakeholders in solving a complex workforce problem. Overall this study contributes to the growing literature that seeks to empirically evaluate the effectiveness of systems science methods in changing participant mental models.\u003csup\u003e43\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThere was little change in the SMPH levels of the solutions identified by participants, with solutions both before and after the session concentrated at the policy and institutional levels. This likely reflects the sample of individuals who were recruited to participate in the GMB. Their interest in GMB may indicate a prior tendency towards systems thinking. Many participants' worked in a policy space, and others were directors of crisis programs, consistent with policy and institutional solutions. Future work may seek to use a potentially more sensitive scale test if the solutions shifted toward a systems-perspective, such as the 12 Levels of Leverage framework by Meadows.\u003csup\u003e44\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eResponse length analysis suggests shorter responses in the post-survey may be attributable to participant fatigue at the end of the 4.5 hour session. This is reinforced by the fact that three participants left without completing the survey. This underscores a challenge of studying the impact of GMBs intra-experimentally. While seeking responses to the post-survey 24 hours after the GMB to minimize fatigue may have boosted participation, this was not done to avoid confounding due to the time gap.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOne additional contribution of this study is that it highlights the potential for AI to aid in GMB facilitation. In this case, ChatGPT 4o rapidly summarized participant responses, which otherwise would not have been feasible given the small size of our facilitation team. This suggests that such tools may enhance current GMB scripts, especially when summarization of responses illustrates perspectives from other participants. This is consistent with emerging evidence that AI tools may help facilitate effective participatory research design.\u003csup\u003e45\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLimitations\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. While the structure of the model was validated, many proportion-based parameters (e.g. the CRSS-SP graduation rate) and delay values (e.g. duration time graduates on the training program pathway wait to take the exam) were not estimated and will need to be incorporated from data and expert estimates prior to simulation modeling. Many participants also reported lacking detailed knowledge of organizational salary determinants. Although salaries can be treated as an independent parameter during simulation, additional input from business managers would strengthen understanding of how organizational factors shape compensation. Moreover, the Health Resources and Services Administration entry pathway into the workforce was in nascent stages at the time of this work, and its development may alter the structure of the ES workforce in the future.\u0026nbsp;Finally, the small number of participants completing both the initial and final problem framing surveys limits confidence in the magnitude of changes (e.g. in number of problems, Jaccard indices) in participant mental models, though it qualitatively demonstrates the feasibility of the adapted Fokkinga et al. evaluation framework.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eGrowing the mobile crisis workforce requires coordinated action by government, mental health systems, and training programs. Using Group Model Building (GMB), this study elicited the structure of the workforce pipeline and the interdependent drivers of capacity, and documented pre\u0026ndash;post shifts in participants\u0026rsquo; mental models using an instrument adapted from Fokkinga et al. These findings suggest that GMBs can facilitate cross-sector alignment and inform strategies for states seeking to expand and sustain their mobile crisis workforces.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe study was reviewed by the Institutional Review Board at the University of North Carolina at Chapel Hill and determined to be exempt from human subjects review requirements. Formal consent requirements to participate were therefore waived.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBommersbach TJ, Olfson M, Rhee TG (2024) National Trends in Emergency Department Visits for Suicide Attempts and Intentional Self-Harm. Am J Psychiatry 181(8):741\u0026ndash;752. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1176/appi.ajp.20230397\u003c/span\u003e\u003cspan address=\"10.1176/appi.ajp.20230397\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCDC. Suicide Data and Statistics. Suicide Prevention. Accessed October 6 (2025) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cdc.gov/suicide/facts/data.html\u003c/span\u003e\u003cspan address=\"https://www.cdc.gov/suicide/facts/data.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNational Association of State Mental Health Program Directors Research Institute. State Behavioral Health Workforce Shortages and Initiatives (2024) Accessed April 15, 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.nri-inc.org/media/tghpz5uu/smha-workforce-shortages-2023.pdf\u003c/span\u003e\u003cspan address=\"https://www.nri-inc.org/media/tghpz5uu/smha-workforce-shortages-2023.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMorse G, Salyers MP, Rollins AL, Monroe-DeVita M, Pfahler C (2012) Burnout in Mental Health Services: A Review of the Problem and Its Remediation. Adm Policy Ment Health Ment Health Serv Res 39(5):341\u0026ndash;352. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10488-011-0352-1\u003c/span\u003e\u003cspan address=\"10.1007/s10488-011-0352-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRamasamy RS, Thompson A, Simmons S (2022) Responding to Acute Mental Health Crises in Black Youth: Is It Safe to Call 911? Community Ment Health J Published online May 27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10597-022-00980-4\u003c/span\u003e\u003cspan address=\"10.1007/s10597-022-00980-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCommittee on Psychiatry The Community for the Group for the Advancement of Psychiatry. ROADMAP TO THE IDEAL CRISIS SYSTEM. Published online 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSubstance Abuse and Mental Health Services Administration National Guidelines for Behavioral Health Crisis Care \u0026ndash; A Best Practice Toolkit Knowledge Informing Transformation. Published online 2020. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.samhsa.gov/sites/default/files/national-guidelines-for-behavioral-health-crisis-care-02242020.pdf\u003c/span\u003e\u003cspan address=\"https://www.samhsa.gov/sites/default/files/national-guidelines-for-behavioral-health-crisis-care-02242020.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEdmonds A, Saint-Phard E, Harrison E, Natzke B, Vine M, Brown J (2025) \u003cem\u003eFinancing Crisis Services Through Public and Commercial Insurance: Current Landscape and Future Opportunities\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://aspe.hhs.gov/sites/default/files/documents/39f90405c77dd3b192c72a182ed5202e/financing-crisis-services-current-future-opportunities.pdf\u003c/span\u003e\u003cspan address=\"https://aspe.hhs.gov/sites/default/files/documents/39f90405c77dd3b192c72a182ed5202e/financing-crisis-services-current-future-opportunities.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcNab D, McKay J, Shorrock S, Luty S, Bowie P (2020) Development and application of \u0026lsquo;systems thinking\u0026rsquo; principles for quality improvement. BMJ Open Qual 9(1):e000714. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmjoq-2019-000714\u003c/span\u003e\u003cspan address=\"10.1136/bmjoq-2019-000714\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarber P, L\u0026oacute;pez-Valc\u0026aacute;rcel BG (2010) Forecasting the need for medical specialists in Spain: application of a system dynamics model. Hum Resour Health 8(1):24. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/1478-4491-8-24\u003c/span\u003e\u003cspan address=\"10.1186/1478-4491-8-24\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaba ST, Atkinson SR, Lewis S, Chung KSK, Hossain L (2015) A systems life cycle approach to managing the radiology profession: an Australian perspective. Aust Health Rev Publ Aust Hosp Assoc 39(2):228\u0026ndash;239. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1071/AH14113\u003c/span\u003e\u003cspan address=\"10.1071/AH14113\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrailsford S, De Silva D (2015) How many dentists does Sri Lanka need? Modelling to inform policy decisions. J Oper Res Soc 66(9):1566\u0026ndash;1577. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1057/jors.2014.136\u003c/span\u003e\u003cspan address=\"10.1057/jors.2014.136\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCave S, Willis G (2020) System Dynamics and Workforce Planning. In: Dangerfield B (ed) System Dynamics. Springer US, pp 431\u0026ndash;457. doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/978-1-4939-8790-0_659\u003c/span\u003e\u003cspan address=\"10.1007/978-1-4939-8790-0_659\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHassmiller Lich K, Urban JB, Frerichs L, Dave G (2017) Extending systems thinking in planning and evaluation using group concept mapping and system dynamics to tackle complex problems. Eval Program Plann 60:254\u0026ndash;264. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.evalprogplan.2016.10.008\u003c/span\u003e\u003cspan address=\"10.1016/j.evalprogplan.2016.10.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eScott RJ, Cavana RY, Cameron D (2016) Mechanisms for Understanding Mental Model Change in Group Model Building. Syst Res Behav Sci 33(1):100\u0026ndash;118. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/sres.2303\u003c/span\u003e\u003cspan address=\"10.1002/sres.2303\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDoyle JK, Ford DN (1998) Mental models concepts for system dynamics research. Syst Dyn Rev 14(1):3\u0026ndash;29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/(SICI)1099-1727\u003c/span\u003e\u003cspan address=\"10.1002/(SICI)1099-1727\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e::AID-SDR140\u0026gt;3.0.CO;2-K\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuber B, Belenky N, Watson C, Gibbons B (2023) Reimbursement Mechanisms and Challenges in Team-Based Behavioral Health Care. Published online Oct 17, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/books/NBK606628/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/books/NBK606628/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGupta P, Jacobs L, Luk K, Jones T (2026) Acting as the Face of a Broken System: Challenges Experienced by Mobile Crisis Workers. Community Ment Health J Published online April 6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10597-026-01609-6\u003c/span\u003e\u003cspan address=\"10.1007/s10597-026-01609-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRouwette EAJA, Vennix JAM, Mullekom TV (2002) Group model building effectiveness: a review of assessment studies. Syst Dyn Rev 18(1):5\u0026ndash;45. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/sdr.229\u003c/span\u003e\u003cspan address=\"10.1002/sdr.229\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEstrada-Magbanua WM, Huang TTK, Lounsbury DW et al (2023) Application of group model building in implementation research: A systematic review of the public health and healthcare literature. Das JK, ed. \u003cem\u003ePLOS ONE\u003c/em\u003e. ;18(8):e0284765. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0284765\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0284765\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSiokou C, Morgan R, Shiell A (2014) Group model building: a participatory approach to understanding and acting on systems. Public Health Res Pract 25(1):e2511404. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.17061/phrp2511404\u003c/span\u003e\u003cspan address=\"10.17061/phrp2511404\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBehavioral Health Workforce Shortage (2024) Written Testimony. Published online January 25, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ilga.gov/documents/house/committees/103Documents/HMEH/Book%20-%20Behavioral%20Health%20Workforce%20Shortage%201-25-24.pdf\u003c/span\u003e\u003cspan address=\"https://www.ilga.gov/documents/house/committees/103Documents/HMEH/Book%20-%20Behavioral%20Health%20Workforce%20Shortage%201-25-24.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIllinois Department of Human Services. Illinois 988 FAQs - August 2022 Edition. 988 Suicide \u0026amp; Crisis Lifeline Planning Page (2022) August \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.dhs.state.il.us/page.aspx?item=145429\u003c/span\u003e\u003cspan address=\"https://www.dhs.state.il.us/page.aspx?item=145429\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIllinois Certification Board. The Illinois Model For Mental Health Certified Recovery Support Specialist (CRSS) Published online July 2024. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://iaodapca.org/Portals/0/PDF/CRSS%20Model%20April%202023.pdf?ver=u7GTIHA-WLcYKR\u003c/span\u003e\u003cspan address=\"https://iaodapca.org/Portals/0/PDF/CRSS%20Model%20April%202023.pdf?ver=u7GTIHA-WLcYKR\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e1lAk0hBw%3D%3D\u0026amp;timestamp=1682975157630\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIllinois Certification Board, International Certification and Reciprocity Consortium. The Illinois Model For International Certification of Peer Recovery Specialist (CPRS) Published online July 2024. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://iaodapca.org/Portals/0/PDF/CPRS%20Model%20April%202023.pdf?ver=IM7\u003c/span\u003e\u003cspan address=\"https://iaodapca.org/Portals/0/PDF/CPRS%20Model%20April%202023.pdf?ver=IM7\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003erZeJP_40oGJQm6ZWv2A%3D%3D\u0026amp;timestamp=1682975616608\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e2539 Notice of Funding Opportunity (590). Illinois Department of Human Services. April 13 (2021) \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.dhs.state.il.us/page.aspx?item=131575\u003c/span\u003e\u003cspan address=\"https://www.dhs.state.il.us/page.aspx?item=131575\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSimon J, Guynn I, Dowsett C, Lich KH (2026) Systems exploration workshops: Using a virtual group model building approach to advance public health systems change. Eval Program Plann 114:102698. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.evalprogplan.2025.102698\u003c/span\u003e\u003cspan address=\"10.1016/j.evalprogplan.2025.102698\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMagnani R, Sabin K, Saidel T, Heckathorn D (2005) Review of sampling hard-to-reach and hidden populations for HIV surveillance. AIDS 19(Supplement 2):S67\u0026ndash;S72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/01.aids.0000172879.20628.e1\u003c/span\u003e\u003cspan address=\"10.1097/01.aids.0000172879.20628.e1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVennix JA (2001) Chapter 4: Designing Group Model-Building Projects. Group Model Building: Facilitating Team Learning Using System Dynamics. Reprinted. Wiley;, pp 101\u0026ndash;120\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFine J, Guta M, Newton H, Sowa N, Watson A, Lich KH (2026) A Qualitative Systems Analysis of the Illinois Mobile Crisis Workforce: Crisis Program Director Perspectives and Policy Recommendations. Rev Preprint posted online April 16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.21203/rs.3.rs-9417637/v1\u003c/span\u003e\u003cspan address=\"10.21203/rs.3.rs-9417637/v1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFokkinga B, Bleijenbergh I, Vennix J (2009) Group model building evaluation in single cases: A method to assess changes in mental models. In: \u003cem\u003eProceedings of the 27th International Conference of the System Dynamics Society\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcLeroy KR, Bibeau D, Steckler A, Glanz K (1988) An Ecological Perspective on Health Promotion Programs. Health Educ Q 15(4):351\u0026ndash;377. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/109019818801500401\u003c/span\u003e\u003cspan address=\"10.1177/109019818801500401\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBell JS, Watson DP, Griffin T et al (2025) Workforce outcomes among substance use peer supports: a scoping review of individual and organizational influences. Front Public Health 12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fpubh.2024.1515264\u003c/span\u003e\u003cspan address=\"10.3389/fpubh.2024.1515264\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrueger DK, Zerden LDS, Jensen TM, Lombardi BM (2026) Burnout and Job Satisfaction among U.S. Peer Recovery Support Specialists: Personal Resilience and Satisfaction with Supervisor and Organizational Support as Mediating Mechanisms. Community Ment Health J 62(2):208\u0026ndash;218. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10597-025-01515-3\u003c/span\u003e\u003cspan address=\"10.1007/s10597-025-01515-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCollier KM, Halvorsen CJ, Fortuna KL (2024) Assessing Mental Healthcare Worker Experiences of Workplace Fairness and Organizational Value: A National Survey of Peer-Support Specialists. Workplace Health Saf 72(1):14\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/21650799231200028\u003c/span\u003e\u003cspan address=\"10.1177/21650799231200028\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrabson LA, Harris JL, Lindhiem O, Herschell AD (2020) Workforce Turnover in Community Behavioral Health Agencies in the USA: A Systematic Review with Recommendations. Clin Child Fam Psychol Rev 23(3):297\u0026ndash;315. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10567-020-00313-5\u003c/span\u003e\u003cspan address=\"10.1007/s10567-020-00313-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHallett E, Simeon E, Amba V, Howington D, McConnell KJ, Zhu JM (2024) Factors Influencing Turnover and Attrition in the Public Behavioral Health System Workforce: Qualitative Study. Psychiatr Serv 75(1):55\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1176/appi.ps.20220516\u003c/span\u003e\u003cspan address=\"10.1176/appi.ps.20220516\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFukui S, Rollins AL, Salyers MP (2020) Characteristics and Job Stressors Associated With Turnover and Turnover Intention Among Community Mental Health Providers. Psychiatr Serv 71(3):289\u0026ndash;292. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1176/appi.ps.201900246\u003c/span\u003e\u003cspan address=\"10.1176/appi.ps.201900246\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatterson PD, Probst JC, Leith KH, Corwin SJ, Powell MP (2005) Recruitment and retention of emergency medical technicians: a qualitative study. J Allied Health 34(3):153\u0026ndash;162\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePatterson PD, Moore CG, Sanddal ND, Wingrove G, LaCroix B (2009) Characterizing job satisfaction and intent to leave among nationally registered emergency medical technicians: an analysis of the 2005 LEADS survey. J Allied Health 38(3):e84\u0026ndash;91\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKamholz JC, Gage CB, Van Den Bergh SL, Logan LT, Powell JR, Panchal AR (2025) Association Between Organizational Culture and Emergency Medical Service Clinician Turnover. Int J Environ Res Public Health 22(5):756. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijerph22050756\u003c/span\u003e\u003cspan address=\"10.3390/ijerph22050756\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u003cem\u003eIllinois Administrative Code - Title 59 - Mental Health\u003c/em\u003e. 132.25:Subpart A: General Provisions. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.dhs.state.il.us/OneNetLibrary/27896/documents/By_Division/MentalHealth/Rule132/JCAR%20final%20and%20emergency%2007.07.pdf\u003c/span\u003e\u003cspan address=\"http://www.dhs.state.il.us/OneNetLibrary/27896/documents/By_Division/MentalHealth/Rule132/JCAR%20final%20and%20emergency%2007.07.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFrerichs L, Young TL, Dave G, Stith D, Corbie-Smith G, Hassmiller Lich K (2018) Mind maps and network analysis to evaluate conceptualization of complex issues: A case example evaluating systems science workshops for childhood obesity prevention. Eval Program Plann 68:135\u0026ndash;147. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.evalprogplan.2018.03.003\u003c/span\u003e\u003cspan address=\"10.1016/j.evalprogplan.2018.03.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBolton KA, Whelan J, Fraser P, Bell C, Allender S, Brown AD (2022) The Public Health 12 framework: interpreting the \u0026lsquo;Meadows 12 places to act in a system\u0026rsquo; for use in public health. Arch Public Health 80(1):72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13690-022-00835-0\u003c/span\u003e\u003cspan address=\"10.1186/s13690-022-00835-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Den Broek S, Sankaran S, De Wit J, De Rooij A Exploring the Supportive Role of Artificial Intelligence in Participatory Design: A Systematic Review. In: \u003cem\u003eParticipatory Design Conference 2024\u003c/em\u003e. ACM; 2024:37\u0026ndash;44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1145/3661455.3669868\u003c/span\u003e\u003cspan address=\"10.1145/3661455.3669868\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1: Group Model Building Participant Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"624\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 106px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 308px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProblem Framing Activity Completion Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(\u003cem\u003en\u0026nbsp;\u003c/em\u003e= 14)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBoth pre- and post-activity (n = 9)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ePre-activity only (n = 3)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eNeither (n = 2)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 111px;\"\u003e\n \u003cp\u003ePresent \u0026gt;90% of session\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e7 (77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e2 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e10 (71.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e2 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e1 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e4 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 111px;\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e9 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e2 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e12 (85.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e1 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e2 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 111px;\"\u003e\n \u003cp\u003eRace\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eAsian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e1 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e1 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e1 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e1 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e2 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e7 (77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e2 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e9 (75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eMissing (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 111px;\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e40.9 \u0026plusmn; 6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e42.0 \u0026plusmn; NA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e41.0 \u0026plusmn; 6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eMissing (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 111px;\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e9 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e2 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e11 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eMissing (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 111px;\"\u003e\n \u003cp\u003eRole relative to mobile crisis workforce\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eCertified Peer Support Specialists\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e1 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eProvides Crisis Care\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e3 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e1 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e4 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003ePolicymaker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e4 (44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e2 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e7 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eTrains Peer Support Specialists\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e2 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e2 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"5\" style=\"width: 111px;\"\u003e\n \u003cp\u003eEmployer type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eAcademic\u0026ndash;Government Partnership\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e2 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e3 (21.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eEducational Institution Training Peer Support Specialists\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e2 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e2 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eGovernment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e2 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e2 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e4 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eNon-profit\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e1 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eOrganizations Providing Crisis Services\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e3 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e1 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e4 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 111px;\"\u003e\n \u003cp\u003eEver provided behavioral health services\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e9 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e3 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e13 (100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eMissing (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 111px;\"\u003e\n \u003cp\u003eCRSS/CPRS certified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e2 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e1 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e3 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e7 (77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e2 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e9 (75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eMissing (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 111px;\"\u003e\n \u003cp\u003eProvided or directed mobile crisis services\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e5 (55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e2 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e7 (58.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e4 (44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e1 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e5 (41.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 106px;\"\u003e\n \u003cp\u003eMissing (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 100px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNotes:\u003c/strong\u003e Percentages are computed by column, excluding missing (shown as \u0026ldquo;Missing (n)\u0026rdquo;). Missing values are included only when at least 1 value is nonzero. A dash (\u0026mdash;) indicates the percentage is undefined because all responses in that column were missing for that characteristic. Age is reported as mean \u0026plusmn; SD; NA reflects insufficient data.\u003c/p\u003e\n\u003cp\u003eAbbreviations: CRSS = Certified Recovery Support Specialist; CPRS = Certified Peer Recovery Specialist.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Summary of Pre\u0026ndash;Post Changes in Participant Responses Following the GMB Session\u003c/strong\u003e\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"679\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 415px;\"\u003e\n \u003cp\u003eParticipant Response Measure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" colspan=\"3\" valign=\"top\" style=\"width: 264px;\"\u003e\n \u003cp\u003eDimensions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003ePrimary Problems\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003eProblem Themes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eAffected Groups\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 415px;\"\u003e\n \u003cp\u003ePer-participant count (Pre-survey) \u0026mdash; Average (Range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.3 (1\u0026ndash;2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1.3 (1\u0026ndash;2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.4 (1\u0026ndash;3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 415px;\"\u003e\n \u003cp\u003ePer-participant count (Post-survey) \u0026mdash; Average (Range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.2 (1\u0026ndash;3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e1.3 (1\u0026ndash;3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.8 (2\u0026ndash;5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 415px;\"\u003e\n \u003cp\u003eNumber of participants with any new dimension in the post-survey, n/n\u003csub\u003etotal\u003c/sub\u003e (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e5/9 (55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e5/9 (55.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e6/9 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 415px;\"\u003e\n \u003cp\u003eNumber of added dimensions in the post-survey \u0026mdash; Average (Range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e.7 (0\u0026ndash;2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e.8 (0\u0026ndash;2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.2 (0\u0026ndash;4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 415px;\"\u003e\n \u003cp\u003eNumber of dropped dimensions in the post-survey \u0026mdash; Average (Range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e.8 (0\u0026ndash;2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e.8 (0\u0026ndash;2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e.9 (0\u0026ndash;2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 415px;\"\u003e\n \u003cp\u003eNumber of participants with any added or dropped dimension in the post-survey, n/N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e6/9 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e7/9 (77.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e6/9 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 415px;\"\u003e\n \u003cp\u003eOverlap of dimensions (Jaccard index) \u0026mdash; Median (Range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.3 (0\u0026ndash;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 84px;\"\u003e\n \u003cp\u003e0.3 (0\u0026ndash;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.3 (0.14\u0026ndash;1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003eNote:\u003c/strong\u003e Jaccard index = intersection of unique terms \u0026divide; total unique terms, ranging from 0 (no overlap) to 1 (complete overlap).\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"c8e06786-a6e9-41b5-b355-d382c2428093","identifier":"10.13039/100000025","name":"National Institute of Mental Health","awardNumber":"F30MH136702","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of North Carolina at Chapel Hill School of Medicine","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"mental health, mental health workforce, crisis, mobile crisis, mobile crisis workforce, group model building, systems thinking, participatory research, state mental health policy, mental health policy","lastPublishedDoi":"10.21203/rs.3.rs-9568624/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9568624/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eObjective: The purpose of this study was to use Group Model Building (GMB), a participatory systems thinking method, to build a system structure map of the mobile crisis workforce pipeline in Illinois (IL). Additionally, this study sought to determine if GMB effectively incorporates systems thinking into the mental models of participants.\u003c/p\u003e\n\u003cp\u003eMethods: 14 stakeholders from across the mobile crisis workforce pipeline in IL gathered for a 4.5 hour GMB session, during which various systems thinking activities were performed to elicit the mental models of the workforce from participants. System structure diagrams were face-validated by at least two participants after the session. Moreover, responses to initial and final problem framing surveys were qualitatively dual coded at the level of the primary problem, potential solutions, and the level of the socioecological model associated with the solutions. These codes were compared within participants to determine if participants’ mental models shifted following GMB.\u003c/p\u003e\n\u003cp\u003eResults: The GMB session produced two system structure diagrams, one for each member of the mobile crisis response dyad, that were validated by participants. Furthermore, most participants exhibited change in at least one dimension measured in the problem framing activity.\u003c/p\u003e\n\u003cp\u003eConclusions: GMB was effectively used to map the mobile crisis workforce pipeline in IL, including multiple feedback loops and multi-layered composite variables. Additionally, the initial and final problem framing activity illustrated the expansion of participant mental models.\u003c/p\u003e","manuscriptTitle":"Using Group Model Building to Map the Mobile Crisis Workforce Pipeline in Illinois and Broaden Stakeholder Perspectives","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-09 00:42:52","doi":"10.21203/rs.3.rs-9568624/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"623579b2-1bb4-475c-a364-4bf564530ed0","owner":[],"postedDate":"May 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":67264669,"name":"Health Policy"},{"id":67264670,"name":"Psychiatry"}],"tags":[],"updatedAt":"2026-05-09T00:42:52+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-09 00:42:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9568624","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9568624","identity":"rs-9568624","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}