Globally, depression and anxiety are two of the most prevalent mental health disorders. In 2019, an estimated 280 million people were living with a depressive disorder, while >300 million people were living with an anxiety disorder [1]. Depression and anxiety commonly co-occur, with comorbidity rates as high as 50% [2]. These disorders are associated with a decreased quality of life due to poor physical health, disability, and reduced life expectancy [3], as well as lower workforce productivity and high economic costs [4]. Fortunately, there are many effective treatments for depression and anxiety that either target specific disorders or use a transdiagnostic approach [5]. However, several barriers affect access to treatment. These include high out-of-pocket costs and inconsistencies in the quality and type of care received [1]. Concerns about seeking help in person due to negative beliefs and stigma surrounding mental illness also play a role [6]. In addition, long waiting times persist due to a shortage of trained mental health professionals and inadequate funding of mental health services [1,6].

Digital mental health interventions (DMHIs), such as smartphone apps or online programs, address many of the barriers to face-to-face mental health care. DMHIs allow people to access psychotherapy skills and content in their own time and empower them to self-manage their symptoms [7-11]. Due to these advantages and the need to minimize face-to-face contact during the COVID-19 pandemic, many DMHIs have been developed and implemented quickly in recent years [12]. DMHIs can be used in a self-guided format (ie, without human support) [8,9], guided format (ie, with remote support from a health professional or coach), or together with face-to-face therapy sessions in person or with telehealth in a “blended” format (blended care) [12-14]. Evidence supports the efficacy of DMHIs, particularly those based on cognitive behavioral therapy (CBT), in reducing symptoms of depression and anxiety [15,16]. A 2021 meta-analysis [15] found that compared to control conditions, both guided and self-guided DMHIs significantly reduced depressive symptoms across 83 studies, with a medium pooled effect size (Hedges g=0.52; 95% CI 0.43-0.60). For anxiety, a recent meta-analysis [16] reported that compared to inactive controls, guided and self-guided DMHIs significantly reduced anxiety symptoms across 47 studies, with a large pooled effect size (Hedges g=0.80; 95% CI 0.68-0.93). While most studies have evaluated internet-delivered DMHIs (ie, delivered on websites), smartphone apps targeting depressive and anxiety symptoms have also shown positive results, with small to medium pooled effect sizes for anxiety (Hedges g=0.26; 95% CI 0.21-0.31) and depression (Hedges g=0.50; 95% CI 0.40-0.61) [17,18].

Despite this evidence showing that smartphone apps and internet-based interventions are effective in improving symptoms of depression and anxiety, DMHIs are not typically integrated into routine mental health care [19]. There are several reasons for this, including a lack of practitioner confidence and training in integrating these tools into practice, difficulties in personalizing these interventions, and a lack of integration with practice management software and electronic health records [20]. There is promising preliminary research into the combination of DMHIs with face-to-face therapy in blended care for depression and anxiety [14,21,22]. However, research on the efficacy and effectiveness of blended care is limited compared to the evidence base for self-guided and guided DMHIs [8,9,23] and is confined mainly to Europe and North America [14,24]. In practice, many existing DMHIs have high attrition rates and low user engagement, especially when accessed in stand-alone self-guided formats [25,26] and in “real-world” naturalistic settings outside of controlled research studies [27]. For example, a review by Linardon and Fuller-Tyszkiewicz [26] found that the dropout rate of users participating in studies that included smartphone apps for depressive or anxious symptoms was 36% and 21%, respectively. Dropout rates are even higher in naturalistic community settings. For instance, studies have shown that completion rates of DMHIs in naturalistic settings are at best half of what is found in clinical trials of the same intervention [28-30]. Several factors contribute to low DMHI engagement, including technical issues, motivation issues, and a lack of user-driven design [11,25,31,32]. Reviews of the existing literature also show that various features, functionality, and design considerations can promote user engagement with DMHIs. These include the perceived usefulness; positive impact and relevance of DMHIs; content that promotes good mental, physical, and cognitive health [33,34] and social connection [25,31]; design aspects (eg, ease of use and interface); personalized content and choice [35-37]; data security and privacy; and therapist guidance [25].

These findings provide guidance for improving participant engagement and reducing attrition for DMHIs overall, which is especially relevant given the increased availability of DMHIs following the COVID-19 pandemic. However, an often-overlooked issue is how DMHIs should be integrated into routine clinical care for depression, anxiety, and other mental disorders [9]. Many existing self-guided and guided DMHIs include linear, one-size-fits-all programs for a specific disorder (eg, major depressive disorder) or multiple disorders (eg, transdiagnostic programs for mixed anxiety or anxiety and depression). In this model, programs follow a mostly set structure, delivering a series of modules that are completed in the same order for each person. While this approach has benefits [38], the downside is that the DMHI cannot be individually tailored to suit a person’s goals, needs, symptoms, and problems. This lack of personalization negatively affects user engagement [11,25] and is a barrier for mental health professionals using these programs in practice [39]. Another important clinical consideration is that people experiencing severe depression and anxiety symptoms, and frequent suicidal ideation, use DMHIs once they are released into the community, although the programs are often not designed for these clients (eg, myCompass and THIS WAY UP) [40-42]. The needs, preferences, and expectations of people with varying symptom severity and suicidal risk levels need to be considered at the outset when developing interventions for depression and anxiety. Another factor affecting the inclusion of DMHIs in routine clinical care is that many of these interventions have been designed as “self-help” or “stand-alone” products [8,43,44]. This has contributed to the low uptake of DMHIs in practice and limits their potential use, reach, and benefits for people with depression and anxiety at various stages of care (eg, before, during, and after seeking in-person therapy).

Incorporating the needs of the intended target audience directly into DMHI design and development can potentially help address poor user engagement, high attrition, and the lack of integration of DMHIs into clinical practice. Participatory design approaches, such as co-design and co-creation, actively incorporate multiple stakeholders’ perspectives into defining a problem and collaborating with them on potential solutions [45,46]. In digital mental health, participatory design involves partnering with the intended target audience during DMHI design, development, refinement, and evaluation to ensure the product or service reflects their needs. Unfortunately, in DMHI research that uses participatory approaches, these details are often inconsistent, use varied terminology, or are not reported clearly [45,46]. Moreover, the few existing DMHI studies that use co-design principles have been limited to young adult samples (aged 18-34 years) or mental health professionals, with very few in adults aged ≥35 years [45]. Using participatory design and co-design principles to create DMHIs that fit into routine care may help adults with anxiety and depression, along with their mental health professionals, adopt blended care more easily [21]. However, to date, only 1 European study [47] reports the participatory design process during the development of a blended care intervention with people with lived experience of mental illness and psychotherapists. In that study, people with lived experience preferred a DMHI that was gentle and compassionate rather than performance based and they valued having the autonomy to choose modules themselves or have them selected by their therapist. It was also important that the DMHI included crisis support, transparent data security, and confidentiality information. Finally, people with lived experience preferred inclusive, varied, concise content delivered in various formats (eg, text, images, and videos) to ensure the DMHI was accessible to many people.

Blending digital and face-to-face therapy is a promising approach for integrating DMHIs into routine mental health care [14,21,22,24]. However, to date, only 1 study has used participatory design to incorporate the needs of people with lived experience of mental illness into the design of a blended care intervention [47]. Blended care interventions can address the limitations of DMHIs, especially stand-alone options; hence, there is a need to further investigate the utility of the blended care approach. For depression and anxiety, the option of mental health professional involvement would add an extra layer of clinical safety and permit better tailoring of DMHI use for people experiencing depression and anxiety. This study is part of a larger Australian research project that aims to design, develop, and evaluate a new transdiagnostic DMHI for adults with depression and/or anxiety (ie, myNewWay) [48]. The intervention is intended to address limitations of existing DMHIs and be suitable for use as part of blended care. Australian research on blended care is limited; however, preliminary results align with studies in other countries [14,21,22,24] and indicate that blending digital and face-to-face therapy may improve symptoms of depression [49-51] and anxiety [51]. To the best of our knowledge, there are also currently no transdiagnostic blended care models in Australia designed with target audience input and tailored to the specific needs and preferences of adults with depression and anxiety.

This study is 1 of 2 related participatory design studies in which we partnered with people with lived and living experiences of depression and anxiety and mental health professionals in the design of the new blended care DMHI. This paper reports on the findings of people with lived and living experience. Findings from mental health professionals are reported separately in part 2 of this manuscript series [52]. The DMHI will be transdiagnostic rather than diagnosis specific, as transdiagnostic approaches are acceptable, feasible, efficient, and effective for treating multiple symptoms and diagnoses within 1 treatment program [5,40]. We will use findings of this study to co-design and then develop a program that will be engaging, safe, and effective for people with varying severity levels, including those experiencing suicidal ideation. The program could be personalized to individual goals and needs and integrated into face-to-face or telehealth mental health care. We also wanted to ensure that the DMHI met the needs of adults with lived and living experience by including relevant therapeutic content and sustaining their interest with appealing design features and functionality, especially given that user engagement is associated with better treatment outcomes [15,53] and more cost-effective treatment [54,55].

Conducting participatory design within an Australian context is important to ensure that the new blended care model aligns with the needs and expectations of adults living with anxiety and depression. In Australia, adults with depression and anxiety are treated in the private mental health system and can access up to 10 psychotherapy sessions per calendar year with partial government rebates [56]. Blending DMHIs with this existing treatment pathway could increase the quality of care, and, thereby, enhance recovery by providing access to evidence-based resources for depression and anxiety before, during, and after psychotherapy. Given that most blended care research has been conducted in Europe and North America [14,24], conducting research outside these cultural contexts also helps to show which elements of blended care may be universal and which elements are not. The first aim of this study was to examine the needs and expectations of participants regarding the content, features, functionality, and look and feel of the DMHI. This also includes how people with depression and anxiety want to access the DMHI, their preferences for content delivery, and the overall blended model of care. With respect to the blended care model, we asked about the types of therapeutic guidance and human-based support they would like to receive while using a DMHI that blends with psychotherapy, as well as their preferences for sharing data from the DMHI with health professionals. Understanding participants’ preferences for including guided components within a DMHI will ensure that it meets their needs and leverages the potential benefits of guided DMHIs for depression and anxiety [15]. Our second aim was to identify factors that would affect engagement with the new blended DMHI, which could be addressed in the design of the interface, functionality, or content of the intervention to maximize sustained engagement with the DMHI.

A mixed methods convergent parallel design [57] was used for this study, which included a convenience sample of people with lived and living experience. This approach ensured that both a broad range of perspectives (ie, web-based survey) and in-depth insights (ie, qualitative interviews) were represented to achieve the study aims and conclusions [57]. Stage 1 was the web-based survey, which assessed participants’ experiences and attitudes toward DMHIs and the barriers and facilitators to their use. The survey was developed in accordance with the Checklist for Reporting Results of Internet E-Surveys [58]. For stage 2, a subset of survey respondents completed one-on-one online qualitative interviews on their preferences for the DMHI. For people with lived and living experience, stage 3 included co-design sessions and prototype testing of designs based on findings from stages 1 and 2; however, these results are not reported in this paper. The survey and interview questions were developed by the research team, which included health professionals, people with lived experience, user experience and user interface experts, and those with knowledge of implementation research (Multimedia Appendix 1). The data collection methods used in stages 1 and 2 are consistent with prior participatory design research in digital health [45]. In addition, 5 people with lived experience of depression and anxiety served as lived experience advisors during stages 1 to 3. The lived experience advisors took part in each stage of the broader project, including both the survey and qualitative interviews conducted in this study.

All research procedures received ethics approval from the University of New South Wales Human Research Ethics Committee (HC200541), and all participants provided informed consent before participating. If participants wished to withdraw their consent, they could contact the research team. Participant data from the online survey and interview was deidentified and replaced with a number and saved in password protected file accessible only by the research team. Participants were given the option to enter a draw to win an Aus $100 (US $65) online gift card for taking part in the online survey. For the interview, participants were reimbursed with an Aus $30 (US $20) online gift card.

The web-based 20-minute open survey was distributed between October and December 2020. The survey was advertised via the Black Dog Institute website and social media (eg, Facebook and Instagram) and the Black Dog Institute Lived Experience Resource Network. Interested participants were directed to the Black Dog Institute website, which outlined the eligibility criteria for the study and included a link to the web-based survey hosted on Qualtrics (version 2020; SAP Inc) software. At the start of the survey, respondents read the participant information sheet and consent form outlining the purpose of the research study, eligibility criteria, where their data were stored and who had access to it, the length of time to complete the study, and their reimbursement incentive. Eligibility criteria were that participants were aged >18 years, could speak English, currently lived in Australia, and had current or previous experience with anxiety or depression. The web-based survey included questions (Multimedia Appendix 1) on participant demographics, their mental health treatment history, current technology use, their experiences with DMHIs, and preferences for a new DMHI targeted at reducing symptoms of depression and anxiety. Participants were asked what features in the DMHI they would find helpful, how they would like any content displayed, and their preferred medium for accessing the DMHI (eg, smartphone and laptop). Participants’ current levels of depression, anxiety, and stress were also assessed using the validated 21-item Depression Anxiety Stress Scale (DASS-21) [59]. The DASS-21 is reported to have sound psychometric properties [60]. Respondents rate each item on a 4-point Likert scale (never=0 to almost always=3), with higher scores indicating more severe levels of depression, anxiety, or stress.

The interviews were conducted with Zoom videoconferencing software (Zoom Communications, Inc) and lasted 60 minutes on average (SD 10.52 min; range 35-74 min). The semistructured interviews included open-ended questions (Multimedia Appendix 1) that assessed attitudes toward and experiences with DMHIs, preferences for features and functionality, and suggestions for improving engagement with DMHIs. A clinical psychologist (KO) and the user experience designer (KV) facilitated interviews. All interviews were audio-recorded and later transcribed by the project officer (KK).

Quantitative data from the web-based survey were analyzed using SPSS (version 26.0; IBM Corp). Descriptive statistics were calculated for closed-ended survey questions. Sample counts and percentages were provided for each survey question. Reflexive thematic analysis was adopted for qualitative data because this methodology was appropriate for answering the research questions [61]. Following each interview, transcripts were checked and cleaned against the original audio by KK. KK (project officer), KO (clinical psychologist), and RKM (project officer) read the transcripts several times, and after familiarization, they used a general inductive approach to generate the initial set of codes. The 3 authors have experience with digital mental health and thematic analysis. Codes were categorized in Microsoft Excel (version 2024) to create the initial coding framework, which was revised iteratively by KK, RKM, and JATM (research assistant with experience in digital mental health and thematic analysis) for consensus on final themes and subthemes. Any disagreements on codes were resolved through discussion with the research team (including KO, JMN, and AEW, who are psychologists) until a consensus was reached.

The objective of this study was to use participatory design to incorporate the perspectives of people with lived and living experiences of depression and anxiety into a new DMHI that could be integrated into clinical practice as part of a blended care model. To the best of our knowledge, this research is the first Australian study to partner with adults with living and lived experiences of depression and anxiety and use participatory design to conceive a blended care DMHI. Our mixed methods approach also provided valuable insight into our participants’ needs, preferences, and expectations of DMHIs and clarified how the new DMHI could be integrated with psychotherapy in a blended care model. Survey data highlighted how respondents wanted to access the DMHI and their preferences for features, content delivery, and sharing of information via the DMHI. Interview findings converged with survey data but also provided in-depth detail on preferred content and features and how to sustain engagement with the new DMHI. To date, the study findings have informed the designs for a new Australian blended care digital system called myNewWay [48], which includes a mental health smartphone app that can be used alone or as part of blended care.

Survey findings indicated that participants preferred accessing a DMHI via a smartphone app, rather than on a computer or tablet. This preference and other findings may reflect the opinions of people who are familiar with digital technology, as the level of digital literacy was relatively high in the study sample. Two important factors for addressing the needs, preferences, and expectations of people with lived and living experiences of depression and anxiety were ensuring that the DMHI was well designed and easy to use. Qualitative interviews also highlighted that including a variety of therapeutic content was important to people with lived and living experiences of depression and anxiety. These findings are consistent with DMHI research conducted before, during, and after the COVID-19 pandemic [11,31,47,62], indicating these 3 factors should be considered in the design of DMHIs for depression and anxiety. Though no clear trends in the graphic design of the DMHI were identified in surveys and interviews, participants wanted the overall esthetic, tone, and feel of the DMHI to be positive, encouraging, and uplifting. This is an important consideration given that past research has found that the esthetic qualities of DMHI design are linked to better usability and user-friendliness [11,62].

Participants were keen for a DMHI to be user-friendly, simple to navigate, and lacking in technical issues, given that (a lack of) ease of use was often associated with past negative DMHI experiences and disengagement. However, most participants were currently using or had used DMHIs, which aligns with the relatively high levels of digital literacy in the study sample. Future research should give special consideration to defining whether these qualities can be addressed in a similar way for people with higher or lower levels of digital literacy. In addition, a novel finding from qualitative interviews that builds upon previous work is that DMHI users preferred to receive short, positive motivational messages within the DMHI or via push notifications (if app based). This finding is aligned with research conducted before the COVID-19 pandemic [63], which found short motivational messages to be the most commonly used component of the myCompass self-help program. While this preference for short, positive motivational messages may be specific to conditions before the COVID-19 pandemic and DMHI users with high digital literacy, existing literature does suggest that the language used in DMHIs should be hopeful and confident [64]. Moreover, people with depression and anxiety may be experiencing concentration and working memory problems alongside any mental health symptoms or co-occurring issues, further supporting the notion that the length of messages should not be overly long.

In this study, the appeal of the DMHI was also connected to whether the product helped to improve their mental health symptoms and well-being. These results support the findings of the systematic review by Borghouts et al [25], who found that the perceived effectiveness of a DMHI will affect whether a user engages with it. Participants also suggested that the DMHI could help them monitor their mental health symptoms via a self-tracking feature (ie, mood and sleep), which is consistent with previous research [31,62]. One point of differentiation between this study and past research is that interview findings showed which aspects of self-tracking were most preferred, including the visualization of changes over time, reflective journaling, and the ability to share progress with a mental health professional. In qualitative interviews, participants also expressed a strong preference for diverse DMHI content that referred to wellness practices in addition to a wide range of therapeutic techniques, such as healthy eating, physical exercise, and gratitude practices. This desire for diverse and comprehensive content may have stemmed from many participants’ previous experiences with DMHIs that focus on a single therapeutic modality, such as CBT or mindfulness. Participants also wanted the DMHI to include features that help facilitate social connections, which again was most evident in the qualitative interview findings. This is unsurprising, given the importance of social connectedness in positive mental health outcomes [33], especially for depression [34]. Features that support social connectedness were also desired as an inclusion in past DMHIs [11,25], and the need for isolation during the COVID-19 pandemic may have exacerbated this need. Suggestions included incorporating an online community where DMHI users could connect with peers with similar experiences or being able to read or listen to personal stories of people who had overcome mental health challenges.

In line with our secondary aim, participants identified 4 strategies in surveys and interviews that could enhance user engagement with a DMHI: personalization, reminders, goal setting, and including short and achievable activities within the DMHI. Consistent with previous research [11,31,62], participants wanted to personalize a DMHI to suit their needs and set goals. Unlike other studies that saw personalization as customizing the interface (ie, colors, theme, and music) and reminders, qualitative interviews showed that participants viewed personalization as the ability to pick and choose the content and activities or have the DMHI suggest them based on their responses. These findings are especially important, given that a lack of DMHI personalization is a common barrier to user engagement [25] and a common source of user dissatisfaction [11]. Participants preferred a modular, flexible design that could be individually tailored over a less flexible linear program where all users received the same content. Consistent with previous research [35,36,62], participants suggested using custom reminders to engage and maintain user interest in the DMHI in both surveys and qualitative interviews. For example, by allowing users to customize when reminders are delivered or by prompting the user to check in with the DMHI throughout the day. Furthermore, the finding from qualitative interviews that short and achievable activities would facilitate engagement with a DMHI was unique, yet important to consider, as users of DMHIs may be experiencing anxiety and depression and associated symptoms, such as rumination, fatigue, and low energy, which may hinder their ability to engage with longer activities. On the basis of their systematic review, Borghouts et al [25] proposed that shorter module durations were associated with better user engagement in self-guided DMHIs. However, this finding was only based on 2 studies, suggesting that more research is needed to verify this finding.

The study findings provide insight into participants’ preferences regarding whether and how they would use a DMHI with health professionals in a blended model of care. However, it is important to note that these findings represent the views of people who tended to have high digital literacy and were either currently using or had used DMHIs. Participants were open to sharing their information with health professionals via the DMHI, and there was no clear preference for a DMHI to be self-guided or guided in surveys and qualitative interviews. These findings are in line with the potential need for a program to be used flexibly, either in a self-guided or guided format, throughout their mental health recovery and navigation through mental health treatment. Survey data indicated that participants were also comfortable with and positive about sharing data from a DMHI with a trusted health professional, such as a psychologist, general practitioner, or psychiatrist. These findings extend prior research by highlighting that participants wanted autonomy and control over what information they could share, which is especially relevant given the rapid acceleration of remote care via DMHIs and other digital technology during the COVID-19 pandemic [12]. Several participants expressed concerns about how the data collected by the DMHI would be used, stored, and accessed. These results align with a blended care qualitative study [65], which found that clients were not concerned about sharing personal data via an app if their data were kept secure, anonymous, and private. Previous research on user perceptions of stand-alone DMHIs [25] and blended DMHIs [47] also confirmed that data security, confidentiality, and transparency affect user uptake of DMHIs both before and during the COVID-19 pandemic.

Other factors that impacted whether someone was willing to use a DMHI were the product’s credibility, cost, the inclusion of crisis support, and immediate distress management. In qualitative interviews, participants emphasized that a DMHI should be backed by scientific research and developed by a reputable organization, consistent with previous research that showed that inadequate information about credibility can affect user trust in a DMHI [11]. The inclusion of a crisis support section was highlighted as important in this study, as well as in the European user-centered study by Behr et al [47]. The inclusion of this feature can act as an additional safety feature when the program is released into the community, especially if it is used by individuals with higher symptom severity and frequent suicidal ideation in a self-guided format. The addition of distress management tools that can help an individual feel calmer in the moment may also be helpful for people with varying severity levels and assist with developing emotion regulation and distress tolerance. Finally, in both surveys and qualitative interviews, we found that participants were reluctant to pay for a DMHI and strongly believed it should be free or offered at a very low cost (ie, Aus $1-$10 [US $0.65-$6.5]). This corresponds with existing research indicating that many studies have found that participants prefer free DMHIs [11], highlighting the need for future DMHIs to be accessed free of charge or at a low cost. Future research should explore the drivers of this low willingness to pay for DMHIs and understand whether it is due to the low perceived value of these interventions, general expectations that mental health care should be free, or other factors. Future research also needs to explore the optimal funding and business models to support the ongoing maintenance required to successfully integrate DMHIs into routine clinical care, especially given the higher availability of DMHIs overall following the COVID-19 pandemic.

Two main limitations may affect the generalizability of the findings of this study. The first limitation was the nature of the sample recruited for the study. Although the sample included people with a wide range of symptom severity, it predominantly consisted of female, English-speaking, and city-dwelling individuals, with most having previously received mental health treatment. Most participants had good self-rated digital literacy (229/306, 74.8%) and spent >1 hour per day online (287/306, 93.8%), and >40% (131/306) had also used DMHIs in the past. Their opinions may not be representative of the general community, who may be eventual users of DMHIs, especially those who do not usually use digital products or those who have never accessed mental health support. The second limitation was that recruitment for this study took place during the COVID-19 pandemic. Due to the need for many people to isolate before COVID-19 vaccines were widely available, the digital provision of mental health services was expedited during this time [12] (eg, telehealth). Whether the findings generalize to the mental health care system after the COVID-19 pandemic is unknown, and further research will be needed to verify this for this study and other DMHI research conducted before the COVID-19 pandemic.

This study provides clear insights into the needs, preferences, and expectations of adults with lived and living experiences of anxiety and depression for a transdiagnostic DMHI. Although our results are most relevant for people with high levels of digital literacy and experience with DMHIs, our findings highlight the importance of using mixed methods approaches to incorporate lived experience feedback into DMHI design and development. For people comfortable with digital technology, therapeutic interventions that improve mental health symptoms and are perceived as helpful, engaging, and effective are most desirable. Specific features that could enhance user engagement for a DMHI targeted at depression and anxiety include reminders, a self-tracking feature for symptoms, and content that facilitates social connection and peer support (eg, online forum and personal stories). The DMHI for depression and anxiety should also include access to support and resources that users can access when feeling unwell or in crisis. The potential for detection of severe symptomology, such as suicidality in depression, also supports the utility of a DMHI that a person can use as part of a blended care model with a mental health professional.

To date, findings from the participatory design study have been applied in subsequent parts of the larger Australian research project [48]. Designs for the new DMHI were subjected to a co-design and prototype testing process, which was then used to develop a smartphone app that is part of the myNewWay blended care digital system. The smartphone app provides therapeutic content and symptom management strategies primarily based on CBT, including psychoeducation, cognitive restructuring, emotion awareness and acceptance, goal setting, problem-solving, behavioral activation, exposure, relaxation, and mindfulness. Results from the participatory design study with mental health professionals were used similarly and informed the development of a health professional portal [52]. Phase 2 of the larger Australian research project involved an implementation clinical trial to evaluate the myNewWay app and Health Professional portal when used alongside psychological therapy for depression and anxiety. Currently, the myNewWay blended care system is being updated based on feedback from clients and psychologists involved in the clinical trial. The blended care system will also undergo further evaluation in a randomized controlled trial to compare the effectiveness of blended care with myNewWay to the self-guided use of the smartphone app for improving symptoms of depression and anxiety.