The wait time for mental health treatment among adolescents is a critical period of unmet need. In Australia, adolescents report waiting more than 100 days to access their first session of treatment after referral by their general practitioner (GP) [1]. Similar wait times have been reported in other regions, including the United Kingdom, the United States, and Canada [2-4]. Modeling indicates that, if current referral patterns persist, wait times for mental health treatment are likely to increase due to limited capacity in mental health care systems to meet demand [5-8]. These prolonged and potentially increasing wait times may exacerbate mental ill-health among adolescents, highlighting the importance of understanding and addressing the impacts of waiting on young people.

Adolescents have reported significant unmet psychological needs during the wait time for mental health treatment, including severe psychological distress, increased maladaptive coping strategies, and feelings of abandonment [1,9]. Long wait times are also associated with treatment dropout, leading to poorer mental health across the life span [9-12]. Despite this heightened risk, wait time offerings for adolescents across the mental health sector are sparse and lack clear evidence of effectiveness for improving mental health and well-being [13-16]. Beyond reducing wait times, mental health services must also be redesigned to ensure that health care providers recognize and respond to the unique needs of adolescents during this period.

Formative research indicates that the wait time for mental health treatment represents a critical gap in service delivery and is often overlooked in service model design despite the significant impact on individuals’ help seeking and overall service experience [17-19]. However, limited research has conceptualized the waiting period as a distinct phase in service flows that warrants specific consideration of consumers’ needs, wants, and interactions. Few studies have explored how to address adolescents’ psychological needs during this period in a timely and responsive manner without adding to overall service demand [14,20,21].

We argue that design thinking (DT) offers a contemporary lens for reimagining the wait time as a unique and critical phase of mental health service delivery. While there is not a uniform definition, DT is generally understood as an iterative, human-centered problem-solving and innovation process that uses methods such as creative thinking, visualization, and experimentation to generate solutions and foster innovation [22,23]. In service design, DT provides a structured, iterative approach that prioritizes the context and needs of consumers and end users, leveraging collaborative multidisciplinary teams with rapid action-oriented ideation to develop solutions [24]. In contrast to empirical scientific practices, DT is a fundamentally subjective practice that facilitates deeper insights into users’ experiences, which encompasses cognitive, affective, and behavioral needs, motivations, and reactions to service events [25,26]. DT offers a process of learning from and together with end users and those with lived experience rather than treating them as research participants. In this way, DT may be particularly valuable in developing services for underserved populations that are underrepresented in traditional scientific research, such as adolescents, and in enhancing complex service pathways associated with high levels of risk, such as mental health care.

It is unclear how widely DT has been applied to mental health service design. A systematic review on DT in health care found only 24 studies using this approach, and only 2 of these were for mental health care [25]. The interventions underpinned by DT were found to have better health outcomes, higher usability, and greater satisfaction than those designed through traditional research methods. Co-design is one method of DT that has increasingly been used to enhance the engagement of adolescents with digital mental health interventions [26,27], with over 20 studies to date applying this approach [28-30]. However, many of these studies have lacked important details on the methods used and rarely involved end users across all stages of intervention design, development, and evaluation [27,28,31]. As such, there are few published applications of DT in the field of adolescent mental health service provision, and none have addressed the wait time.

This early report outlines the application of DT to the development of a new service model (coined While We Wait) that aims to address the psychological needs of adolescents (aged 14 to 17 years) during the wait time for mental health treatment in Australia when referred by their treating GP. Specifically, we focused on the application of service blueprinting, which is a flexible process modeling approach within DT that can be used to depict a service, facilitating the refinement of a single step as well as the creation of a comprehensive visual overview of an entire service process. Service blueprints allow all stakeholders to visualize an entire service and its underlying support processes, providing common groups from which critical points of consumer experience can be identified.

Led by service design experts from Deloitte Digital Australia in partnership with young people with lived experience, GPs with professional experience, and digital mental health researchers, this project aimed to develop a service blueprint for supporting adolescents during the wait time for mental health treatment. The blueprint sought to identify the key psychological needs of adolescents during this time; recognize the important role that GPs may play in supporting adolescents while they wait for specialist care; and address these needs through evidence-based approaches delivered via digital technology to enhance accessibility, scalability, and cost-effectiveness. The model was also designed to allow service commissioners the flexibility to adapt or prioritize service components to suit local contexts without compromising the integrity of the core service model.

The initial “essential elements” of the model were identified through a needs assessment phase informed by conversations with youth with lived experience [1], GPs [32], and academic research [21,33] and were subsequently integrated into the blueprint. The model was underpinned by several key assumptions: first, that GPs have the potential to act as trusted advisors for adolescents experiencing mental health difficulties and, second, that young people would be willing to re-engage with their GPs during the wait time for specialist care. These assumptions shaped the design of the proposed service model. However, several design issues needed to be resolved before the model could be operationalized.

This early report aims to describe how we applied DT methods to resolve design issues and refine the service model, with the goal of transforming the waiting period into an opportunity for early intervention and sustained support, ultimately improving mental health outcomes and service accessibility for adolescents.

This project used an industry-led, rapid 6-week health service design sprint, which took place between November 2024 and December 2024. Our reporting of this work aligns with the proposed guideline by Bazzano et al [34] for the reporting of health research involving design.

The University of New South Wales Human Research Ethics Committee provided ethics approval for the needs assessment among adolescents (HC190382) and GPs (HC220107) conducted prior to this project and published elsewhere [1,32]. The youths with lived experience and GPs involved in the sprint were employed as lived experience and service delivery experts, respectively, and were paid for their time in accordance with the Australian National Mental Health Commission lived experience paid participation policy [35]. Under Australia’s National Health and Medical Research Council National Statement on Ethical Conduct in Human Research 2023 [36], some research is eligible for exemption from ethics review when it carries lower risk to participants or the community, does not collect personal identifiers, and is conducted for quality assurance or program use. We obtained an ethical exemption from Flinders University Human Research Ethics Committee (7902) for this sprint activity as no team members were treated as human research subjects and no personal data collection, testing, or collection of personal materials occurred. All team members were aged ≥18 years.

The final service design blueprint is provided in Multimedia Appendix 1. On the basis of the needs assessment in the sprint, adolescents were identified as the primary service end users, and GPs were identified as key service actors. Family caregivers, referred service providers, other formal supports (eg, school counselors), and service commissioners were also identified as potential service actors but deemed beyond the scope of the current sprint.

For adolescents, 5 key service experience principles were identified to guide the design of support during the wait time: “I’m never alone,” “It’s for me,” “I’m in control,” “It’s easy to use,” and “It lifts me up.” These principles were extracted from the service blueprint (Multimedia Appendix 1) and are explained in Figure 1.

During the initial sprint with youths with lived experience, 2 service experience concepts required further clarification through additional workshopping: personalization and peer support. In relation to personalization, the sprint revealed differing interpretations of the term among stakeholders. To clarify how this concept should be applied within the proposed service model, an additional 1-hour concept-mapping workshop was conducted. During this workshop, youths with lived experience distinguished between different forms of personalization and indicated a preference for support that was tailored specifically to the stage of help seeking (ie, the wait time) rather than to a specific mental health condition or symptom profile (eg, depression or anxiety). It was emphasized that support during the wait time should focus on helping young people manage distress while waiting for care rather than providing condition-specific advice. This preference was reflected in the service experience principle “It’s for me,” which captures the importance of resources and strategies that are tailored to the wait time experience rather than their mental health condition or other situational factors.

The conceptualization of peer support also required further refinement. To explore how peer support could be integrated within the wait time, an additional prioritization workshop was conducted using a prioritization matrix. Existing and potential forms of peer support were mapped, and several features that were considered important during the waiting period were identified. These included access to positive and uplifting stories from peers, support that reflected lived experience perspectives, opportunities to maintain a sense of ongoing connection with others, and opportunities to share their own lived experiences. Youths with lived experience reflected that the existing peer support approaches available to them did not fully align with these priorities for the wait time context.

Described in Figure 2, the proposed service design encompassed a five-stage journey: (1) recognition of the need for support by the adolescent, (2) initial consultation and onboarding with the GP, (3) support and monitoring, (4) preparation for specialist treatment, and (5) transition to specialist care and follow-up.

The sprint also identified 5 key “moments that mattered” in the service flow. Described in Figure 3, these were (1) ensuring that the voice of the GP is empathetic, supportive, and continuously present; (2) enhancing choice and optionality where possible; (3) building trust, setting expectations, and being transparent with adolescents about service features; (4) avoiding repetition and enhancing seamless transition at the beginning and end of the service; and (5) focusing on building momentum in help seeking across each phase of the service journey.

As shown in the blueprint (Multimedia Appendix 1), the core experience outcomes and example measures of success were mapped across the service journey. At the adolescent level, the suggested service outcomes for the pilot trial included their levels of uptake and acceptability, self-advocacy, mental health and well-being, perceptions of the quality of care, and help seeking intentions and behavior. For the GPs, the suggested service outcomes included GP uptake, feasibility, acceptability, and confidence in caring for adolescents during the wait time. Other information on these suggested outcomes is shown in Multimedia Appendix 1.

While DT offers several advantages, our sprint also highlighted the unique challenges that this approach can pose in mental health care service design, particularly in reconciling differing priorities among stakeholders [24]. Specifically, tensions emerged between adolescents’ perspectives and the priorities of GPs. Some GPs strongly advocated for prioritizing immediate access to face-to-face care (ie, the primary focus should be on reducing wait times overall). In contrast, our youth with lived experience experts expressed greater acceptance of waiting times but emphasized the need for self-management support. This aligns with previous research where consumer satisfaction with care was found to be influenced by subjective perceptions of the wait time rather than actual duration alone [18]. Furthermore, multiple studies have demonstrated persistent discrepancies in service outcome priorities among different stakeholders, including young people and clinicians [47-49]. Thus, a central challenge in applying DT to mental health care lies in balancing the development of services and interventions that are not only effective but also acceptable and feasible for both providers and service users. The iterative nature of the sprint provided the flexibility needed for us to explore stakeholder differences; however, some additional workshops were required, inadvertently increasing resource demands.

The service blueprint was not intended to serve as a comprehensive back-end design document. As such, additional resources will be required to refine the technical specifications and translate the blueprint into a fully operational service. A key consideration in this process will be the level of user effort required to access and engage with the service offerings. The proposed model was centered on SMS text message and web link resources, leveraging the minimal effort needed for user engagement with these modalities. This is an important factor given that many adolescents accessing the service may be experiencing motivational deficits. The sprint enabled the team to propose alternative technical solutions such as smartphone apps or web-based platforms while remaining cognizant of the implementation challenges associated with these modalities [50]. Given the importance of knowledge sharing, disseminating the final technical specifications will be crucial to enabling service providers and researchers to adapt and build upon this model. Additionally, further refinement of the outcome monitoring framework is needed, particularly in selecting appropriate measures that can effectively capture the expected impacts valued by adolescents, GPs, and service designers [51]. Finally, piloting the model within real-world service delivery environments is essential to assess whether the core service principles can be maintained in practice [52].

This work demonstrates that a rapid, industry-led DT approach may help identify priorities for developing services that address adolescents’ needs during the wait time for mental health treatment. More broadly, the findings suggest that the waiting period for adolescent mental health care should be conceptualized not merely as a delay before treatment but also as a distinct and potentially therapeutic phase of the care pathway. Therefore, DT approaches may offer a promising framework for identifying how services can better support adolescents during this time, particularly when integrating digital interventions and lived experience perspectives. Additionally, the project highlights the value of innovative partnerships between researchers, adolescents with lived experience, industry specialists, and service providers in the co-design of mental health services. Future research should focus on translating these service design principles into scalable interventions and evaluating whether structured wait time supports can reduce distress during the waiting period, improve engagement with care, and enhance subsequent treatment outcomes.