Health Technology Review

Environmental Scan of Mental Health App Libraries

The Challenge

• Mental health apps offer new ways to access mental health information, self-management tools, and services. However, the number of available apps and differences in quality, privacy, security, evidence, and usability can make it difficult for end users and health care professionals to identify appropriate digital mental health resources.

• Mental health app libraries and gateway models have emerged as approaches to help end users, clinicians and other mental health care providers identify, assess, and navigate digital mental health resources. However, these models vary in their purpose, functions, governance, and operating approaches, raising questions about which approaches may be appropriate in the Canadian context.

The Evidence

• Canada’s Drug Agency conducted this Environmental Scan in response to an external request by the Mental Health Commission of Canada (the Commission) to understand the opportunities and challenges of mental health app libraries and gateway models that exist in Canada and internationally. The scan examined published and grey literature on mental health app libraries and gateway models in Canada and internationally. It considered model design, governance structure, implementation, use, funding, maintenance, sustainability, and emerging trends.

• CDA-AMC also surveyed health organizations, clinicians and other mental health professionals, and people with lived experience to provide additional context on the implementation, use, and considerations relevant to these models. The Commission supported survey engagement through their existing networks.

What CDA-AMC Found

• Mental health app libraries and gateway models differ in their scope, governance structure, assessment approaches, and integration with health systems.

• App libraries primarily assess, curate, and present information about digital mental health apps. Gateway models have a broader function and may combine app discovery with features such as self-assessment, guided navigation, referral pathways, service directories, crisis resources, and links to health and community services. A gateway may or may not also include an app library component.

• Common considerations for the design, implementation, and ongoing operation of mental health app libraries and gateway models include governance, transparent app assessment, privacy, accessibility, provider engagement, integration with care, maintenance, and sustainable operational capacity.

• Survey respondents reinforced the importance of privacy and data protection, usability and accessibility, trust and organizational credibility, and evidence of effectiveness when considering the use and uptake, adoption, recommendation, and implementation of these models. They also highlighted implementation considerations, including cost, funding, infrastructure, and service integration.

Why It Matters

• Implementing a mental health app library or gateway model involves more than developing a digital platform. The evidence identified in this scan indicates that implementation involves clear governance, sustained operational support, integration with existing services, and ongoing evaluation.

• The literature identified in this Environmental Scan provided limited comparative or long-term information on effectiveness, costs, workforce requirements, sustainability, and health system impacts. Further evaluation could examine these areas.

• These findings provide important considerations to inform evidence-based planning and policy considerations related to mental health app library and gateway models in Canada.

Context

Mental Health and Digital Mental Health Technologies

Mental health conditions can affect quality of life, functioning, education, employment, and community participation.^1,2 Many people face barriers to timely support, including limited service availability, long wait times, geographic barriers, and inconsistent care pathways.^3-5 Digital mental health technologies may complement existing services, improve access to information and support, and help people navigate available resources.

Digital mental health technologies include synchronous services delivered in real time and asynchronous resources that end users can access at different times (i.e., does not require real-time interaction).^3,5-7 Examples include self-guided therapy programs, mood tracking tools, cognitive behavioural therapy modules, peer support platforms, service navigation resources, and other digital supports.

Mental health apps have expanded rapidly in number and function. This growth has raised concerns about the quality, privacy, security, clinical evidence, usability, transparency, and cost of available apps. App store rankings and commercial visibility do not necessarily reflect app quality or suitability.^3,8-14

Mental Health App Libraries and Gateway Models

Mental health app libraries and related gateway models were developed to support the identification and navigation of digital mental health resources. Mental health app libraries are searchable platforms that primarily curate and present information about mental health apps. Some also assess apps using defined criteria, such as privacy, security, evidence, and usability.^8,10,15,16 Gateway models have a broader function and may combine app discovery with additional features, such as self-assessment, guided navigation, referral pathways, service directories, crisis resources, or links to health and community services.^3,5-7,14 A gateway may or may not include an app library component. Throughout this report, models refers to mental health app libraries and gateway models collectively, unless otherwise specified.^6,14

App libraries and gateway models vary in their purpose, functions, governance, and operating approaches. This variation can make it challenging to determine which approaches may be appropriate for different contexts. Describing existing models and their implementation can help identify considerations relevant to planning app library or gateway models in Canada.

Canada’s Drug Agency (CDA-AMC) conducted this Environmental Scan to inform evidence-based planning and policy decisions related to mental health app library or gateway models in Canada. The Environmental Scan:

• identifies and describes the current landscape of national and international mental health app libraries and gateway models

• summarizes governance, assessment, implementation, use, funding, maintenance, and sustainability approaches and experiences

• incorporates contextual perspectives from 3 knowledge user groups regarding implementation and evidence gaps

• describes emerging trends, including artificial intelligence (AI)-enabled functions, and their potential implications for the design and sustainability of mental health app libraries and gateway models

• identifies considerations from existing models that may be relevant to the Canadian context.

Objective

The purpose of this report is to identify national and international experience, implementation considerations, and evidence gaps relevant to mental health app libraries and gateway models in Canada to inform evidence-based planning and policy considerations.

This Environmental Scan examines mental health app libraries and gateway models rather than individual mental health apps. It does not include an assessment of the clinical or cost-effectiveness of mental health apps. Thus, conclusions or recommendations about the value of individual mental health apps or their place in therapy are outside of the scope of this report.

Research Questions

1. What national and international models of mental health app libraries or gateways currently exist, and how are they structured and governed?

2. What is known about their public uptake, provider recommendation pathways, implementation, sustainability, and lessons learned?

3. What signals exist regarding financial investment requirements, funding models, and sustainability considerations?

4. How are emerging trends, including the growing use of AI-enabled mental health tools, affecting the relevance, design, and sustainability of app library or gateway models?

5. What strategic considerations from existing models may be most relevant to the Canadian context?

Approach

CDA-AMC conducted a multimethod environmental scan using literature from academic and grey literature searches and 3 targeted surveys for health organizations, mental health care professionals, and people with lived experience. The environmental scan was designed to provide evidence-informed decision support by describing and contextualizing existing approaches rather than conducting a comprehensive systematic review or establishing comparative effectiveness or best practices. An information specialist conducted a customized literature search, balancing comprehensiveness with relevance, of multiple sources and a focused internet search on April 14, 2026. CDA-AMC also considered contextual evidence that did not describe an existing app library or gateway model when it directly informed the current scope. This included evidence on functions or implementation considerations, such as app assessment, governance and oversight, navigation, or integration with health services.

CDA-AMC used separate surveys for each knowledge user group because each group has different roles, experiences, and information needs. The survey questions were designed to provide contextual perspectives on awareness, trust, accessibility, implementation, operational requirements, sustainability, and future relevance.

The project benefited from ongoing collaboration between the Mental Health Commission of Canada (the Commission) and CDA-AMC. The Commission supported knowledge user engagement, including survey development and dissemination, and facilitated connections with relevant organizations and knowledge users. The collaboration also helped ensure that the work remained aligned with the project’s intended scope and information needs.

Appendix 1 provides detailed literature search, screening, and evidence synthesis methods. Appendix 2 provides a list of additional models and resources identified in the environmental scan, with supplementary information on app assessment frameworks (Table 5). Appendix 3 provides the survey instruments administered to health organizations, clinicians and other mental health care providers, and people with lived experience. Appendix 4 summarizes selected closed-ended findings by respondent group (Table 6).

Literature Findings

Overview of Existing Models and Key Characteristics

CDA-AMC identified a diverse range of mental health app libraries and gateway models that vary in purpose, functionality, governance, intended users, and integration with health systems.^6,7,10,14,17 Because terminology is inconsistent across the literature, models are best distinguished by their functions rather than their names.^{6,7,10,14,17,18}

Across the identified literature, app libraries and gateway models showed both overlapping and distinct functions and operating characteristics. Table 1 summarizes key characteristics of the 2 approaches described in the literature. The examples presented in Table 2 illustrate variation in model characteristics and operating contexts rather than provide a comprehensive list of all models identified through the literature searches. Additional identified models included similar implementations, such as regional or organization-specific examples, that would add limited distinct information to the table. Appendix 2 provides a broader list of models and resources identified in the environmental scan, with supplementary information on app assessment approaches (Table 5).

Table 1: Comparison of Key Characteristics of App Libraries and Gateway Models

How Existing Models Operate

The identified mental health app libraries and gateway models varied considerably in their governance, approaches to app assessment and selection, funding, staffing, information management, privacy protection, maintenance, and ongoing oversight. However, relatively few studies evaluated how these factors influence implementation, operational performance, or long-term sustainability, limiting direct comparisons among organizational approaches. The following sections describe who operated the models, how organizations assessed and selected apps, and the processes and resources used to support ongoing maintenance and service delivery. Overall, the identified literature provided limited comparative information on the implementation, operation, and sustainability of different organizational approaches.

Governance and Operational Features

Entities operating existing models include government agencies, publicly funded health systems, nonprofit organizations, academic institutions, health care organizations, commercial organizations, and multisector partnerships.^{6,15-17,21-25}

Who Is Involved?

Across the identified literature, governance commonly involved multidisciplinary oversight. Depending on the model, clinical experts, digital health specialists, researchers, advisory groups, clinicians, community organizations, and people with lived experience contributed to model development, app assessment, implementation, and review.^{5,6,16,22,24,26-28} Other studies described partnerships among governments, health care organizations, academic institutions, nonprofit organizations, and specialist assessment organizations to support governance and decision-making.^29-32

What Is Involved?

Governance activities extended beyond app assessment to include oversight of implementation, maintenance processes, and ongoing quality assurance. Ongoing oversight included maintaining accurate platform information, monitoring changes to apps and supporting evidence, reviewing privacy and security information, updating directories and web links, and revising resources when required.^{3,14,22,24,33-35} CDA-AMC identified little published literature directly comparing governance approaches, accountability arrangements, resource requirements, or long-term performance.^{3,10,14,15,17,21-24}

Mental Health App Assessment and Selection

Mental health app assessment approaches varied considerably, but most contemporary frameworks considered multiple domains rather than clinical effectiveness alone. Common assessment domains included clinical evidence, safety, privacy and security, usability, accessibility, transparency, technical performance, interoperability, user experience, and organizational governance.^{8,10,14,22,24,36-39}

Models differed in the depth and formality of assessment completed before an app was listed or recommended.^{24,27,29,37,40,41} Some platforms functioned mainly as app directories, whereas others applied structured eligibility criteria, standardized frameworks (refer to Table 5 for examples of assessment domains identified across app assessment frameworks), multidisciplinary review, or independent appraisal.⁶ For example, the National Health Service (NHS) Apps Library required evidence of effectiveness, clinical safety, regulatory approval (where applicable), privacy and security standards, accessibility requirements, and technical stability before apps could be included.¹⁰ The Alberta Health Services Addiction and Mental Health Mobile Application Directory also applied inclusion criteria based on supporting research evidence, expert review, or, in some cases, apps from a known reliable source.¹⁰ Many organizations combined internal review with external assessment services.^{15,24,29,35,42} In this context, the Organisation for the Review of Care and Health Apps (ORCHA) was identified as a provider of app assessment services and as a provider of digital health app libraries.¹⁰

Existing models described assessment as an ongoing activity.^8,10,12 Because apps and the information about them can change over time, ongoing review and monitoring are needed to ensure recommendations remain accurate and appropriate.^22,24,42,43 The identified literature did not compare assessment frameworks or evaluate their relative performance; therefore, it did not identify a preferred assessment framework. The literature also highlighted that app assessment is distinct from regulation, accreditation, certification, and reimbursement.^{8,10,37,38,42}

Funding, Maintenance, and Resources

The literature indicated that implementing and maintaining mental health app libraries and gateway models require sustained organizational investment beyond initial model development.^{6,14,17,23,24,29}

Funding

Funding arrangements varied across the included models, covering government, public health systems, nonprofit, academic, nonprofit, commercial, and mixed funding arrangements.^{6,15,17,21,23,24,29,35,42} The published literature did not describe a funding model that was consistently associated with long-term sustainability. Instead, operational reports emphasized sustained organizational commitment, defined governance responsibilities, and dedicated operational capacity as important components of sustainability. However, the identified literature did not establish whether particular funding approaches were more sustainable than others.

Maintenance

The examined literature consistently identified maintenance as a core operational requirement. Maintenance activities extended beyond app assessment to include monitoring platform functionality, directory content, broken web links, emerging evidence, privacy and security information, app availability, regulatory status (where applicable), and accessibility.^{8,12,14,24,29,35,42}

Resourcing

Ongoing operations required technical infrastructure and multidisciplinary expertise in clinical care, digital health, information management, communications, implementation, and end user engagement.⁶ Operational capacity also included resources to support app assessment, quality assurance, and ongoing model and platform management.^10,44 Models relied on external expertise for some of these activities, including app assessment, quality assurance, and operational continuity.^24,29-32 The identified literature described these resourcing requirements and operational experiences, but did not establish best supported long-term implementation across different health systems.^6,10,14,17

Table 2: Selected Existing Mental Health App Libraries and Gateway Models

CAR-NIMHANS = Centre for Advanced Research at the National Institute of Mental Health and Neuro Sciences; HSCNI = Health and Social Care Northern Ireland; IAR-DST = Initial Assessment and Referral Decision Support Tool; NHS = National Health Service; NL = Newfoundland and Labrador; NZ = New Zealand; UHN = University Health Network; ORCHA = Organisation for the Review of Care and Health Apps.

^aModel types reflect the operational definitions used in this Environmental Scan and may not correspond to the terminology used by the original source or model. Classification was based on the functions described in the identified evidence source.

^bKids Help Phone is a gateway that lists mental help apps as part of their “Resources Around Me.” It was not classified as having a curated app library because the identified information did not describe a distinct process for selecting, reviewing, or assessing apps as an app collection.

^cThe platform is not integrated into the Quebec health system, but it is operated by a provincial nonprofit, Association québécoise de prevention du suicide (AQPS), with 3 suicide prevention centres.

^dThe Government of Canada transitioned away from Wellness Together Canada in April 2024 following the emergency phase of the COVID-19 pandemic.⁴⁹

^eThe NHS Apps Library was decommissioned in 2021 as part of the NHS digital ecosystem. The NHS subsequently incorporated app-related functions into redesigned digital platform with expanded functionality beyond the original stand-alone NHS Apps Library.⁵⁴

^fMedicare Mental Health is the current name of the Australian national Head to Health website. The website was rebranded in 2025; the Australian Government reported that the name change did not affect the services or how the website operates.⁵⁵

What CDA-AMC Learned From Existing Models

The following sections summarize the identified literature on use and uptake, provider engagement, trust, and credibility, as well as equity, accessibility, and cultural considerations. Across these domains, the literature did not establish which combination of funding, staffing, maintenance, and partnership arrangements best supports the long-term operation of mental health app libraries and gateway models.

Use and Uptake

The literature examined in this report primarily described measures of use and uptake rather than longer-term outcomes. Reported measures included website visits, searches, registrations, referrals, downloads, and feature use rather than sustained engagement, successful connections to recommended health and community services, clinical outcomes, or health system effects.^6,7,17,21,36 Use across app libraries and gateway models appeared to depend on factors such as awareness, provider engagement, organizational credibility, implementation support, and ongoing promotion.^{5-7,17,21,23,24,36,42,56} Gateway-specific evidence based on the identified literature, identified intuitive navigation design, self-assessment, referral pathways, and integration with existing services as relevant considerations.^{5-7,17,21,23,24,36,42,56}

End user characteristics and context, including digital and health literacy, language, accessibility (including device and internet access), and privacy preferences also influenced engagement.^3,5,13,24,57 Accessible and user-friendly information, current service information, and alignment with user needs were described as supportive of navigation and engagement. Limited accessibility, outdated information, and difficulties navigating available resources were identified as barriers. However, the literature did not establish which models or implementation strategies were associated with sustained use, successful navigation, or improved outcomes.

Provider Engagement

Provider engagement emerged as a central implementation consideration across mental health app libraries, gateway models, and related digital navigation initiatives. Across the published literature, mental health professionals contributed to app selection and recommendation, shared decision-making with patients, implementation, monitoring, and integration of digital resources into care.^{4,5,17,20,23,24,26,42,44,53,56,58,59}

To support provider participation, several models included provider education, clinical guidance, implementation toolkits, decision support resources, workflow tools, technical support, and digital navigator roles.^{4,20,23,28,42,51,56,58} Digital navigators are individuals who help providers and users identify, access, and integrate appropriate digital mental health resources into routine care.^20,44

The literature also identified several factors associated with provider confidence and engagement. Provider confidence was associated with transparent app assessment, supporting clinical evidence, privacy and security, organizational endorsement, integration into routine workflow and service delivery, and clarity about professional responsibilities.^{10,15,24,29,33,34}

Reported barriers to provider engagement included time, competing clinical priorities, uncertainty about app quality, privacy, limited digital competencies, insufficient organizational support, and unclear accountability.^4,10,20,44 The literature did not establish whether provider engagement improves sustained use, service delivery, or health outcomes.^{4,5,14,17,20,44}

Trust and Credibility

Trust and credibility influenced whether end users used or health care professionals recommended digital mental health resources, including apps, app libraries, and gateway models. The literature consistently linked trust and credibility to evidence quality, transparent assessment, privacy and security, organizational accountability, usability, accessibility, and up-to-date information.^{3,8-13,17,33,36,53,60} Models used multidisciplinary review, explicit eligibility criteria, standardized evaluation domains, disclosure of methods, conflict-of-interest processes, routine reassessment, version control, and public reporting to support credibility.^{8,10,22,24,33,61}

The literature also identified organizational accountability as a key contributor to building trust. Public, professional, academic, and nonprofit organizations were more often described as trusted hosts when they clearly accepted responsibility for assessment, maintenance, and ongoing oversight. Unclear governance, undocumented assessment methods, outdated information, broken web links, and inconsistent privacy information could reduce confidence.^{3,8-12,14,15,24,33,37,38,42} The identified studies did not establish whether specific approaches to building trust improved and sustained engagement or implementation.^8,14,15,33

Equity, Accessibility, and Cultural Considerations

Equity and accessibility considerations in the design and implementation of mental health app libraries and gateway models extended beyond platform availability. To accommodate diverse populations, preferences, and different service contexts, models described plain-language content, multiple entry points to care, accessibility standards, multilingual resources, support for accessibility technologies, end user–experience testing, culturally adapted content, population-specific resources, user-centred design, codesign with intended end users, and integration with health services.^{3,5,6,13,14,17,22,23,26,34,36,53,62}

The literature described several approaches intended to support accessibility and be culturally responsive. Reported accessibility approaches included intuitive navigation, multilingual resources, support for accessibility technologies, and ongoing end user–experience testing to support users with varying levels of digital and health literacy. Several models also described culturally responsive approaches, including Indigenous-specific resources, culturally adapted content, resources for specific populations such as youth, caregivers, and 2SLGBTQ+ communities, partnerships with community organizations, and codesign with intended end users to improve access and usability for people with different languages, abilities, cultural backgrounds, and service needs.^{5,6,14,22,24,26,34,36,62}

Persistent barriers to equitable access and use included limited internet connectivity and access to digital devices, cost associated with apps or digital access, language barriers, limited accessibility supports, and varying levels of digital and health literacy. These barriers were more frequently reported among rural and remote communities and other underserved populations.^{3,6,7,13,14,17,24,34,53,62} The literature did not establish whether specific equity and accessibility approaches reduced inequities or improve patient outcomes.^{3,6,13,14,17,26,53}

Emerging Trends

Models are increasingly combining app assessment and app information with broader navigation functions (i.e., gateway models), including screening, triage, referral, self-management resources, virtual care, crisis services, and links to community and clinical services.^{6,17,24,29,34,51,53,62} Digital navigation is also being integrated more closely with routine care through provider engagement, interoperability, referral pathways, measurement-based care, and integration into existing health services.^{4,5,17,20,24,26,34,56,62}

Alongside this broader integration, recent models have placed greater emphasis on continuous quality assurance, life cycle oversight, routine assessment, analytics, end user feedback, personalization, accessibility, and culturally adaptive resources.^{4,6,8,10,14,15,24,26,29,34,35} These developments are described mainly in implementation reports and conceptual work rather than comparative evaluations.

AI-enabled functions represent another emerging development. Recent sources described conversational AI, adaptive screening questions that tailor subsequent questions based on user responses, automated identification of potential end user concerns, and personalized navigation to appropriate resources. While these functions may support earlier identification of user needs or guide users to appropriate resources, the identified literature remains largely conceptual or descriptive.^{6,14,23,26,42}

Other emerging models and technologies include:

• A proposed model for youth in Canada included adaptive microscreeners, natural language processing of referral information, and automated identification of potential concerns.²⁶ These functions remained conceptual and were not evaluated.²⁶ The model emphasized consent, privacy, transparency, equitable access, and youth control over data sharing.²⁶

• The Mindline gateway (Singapore) included access to the Wysa conversational AI chatbot as a component of the broader platform. Reported use indicated adoption of the feature but the reporting study did not evaluate effectiveness, safety, or comparative performance.⁶

• Human-supported digital navigation was another approach described in the literature, with trained navigators helping users or providers select, access, and use digital mental health resources.⁴⁴

As models incorporate broader navigation and AI-enabled functions, governance and oversight remain important considerations. Privacy, transparency, algorithmic bias, safety, equitable access, human oversight, and ongoing monitoring were identified as relevant considerations.^4,26 However, the literature did not establish effects on navigation, connection to recommended health and community services, sustained engagement, clinical outcomes, or sustainability of mental health app libraries and gateway models.

Survey Findings

There were 48 respondents who participated, including the following:

• There were 14 health organization representatives including 10 from Canada; 1 each from Australia, the UK, and the US; and 1 reporting from a global jurisdiction. Five respondents were in health system or organizational leadership positions and 2 each were in policy or governance, program or service delivery, or clinical roles; the roles of 2 respondents were unclear.

• There were 17 clinicians and other mental health providers from Canada. These included 7 counsellors or psychotherapists, 3 psychologists, 2 registered nurses; 1 each of nurse practitioner, psychiatrist, social worker, health promotion coordinator; and a respondent from a nonprofit organization supporting parents and caregivers.

• There were 17 people with lived experience from Canada, including 10 family members or caregivers and 8 peer support workers or mental health advocates. Many respondents identified with more than 1 role.

Findings are descriptive, and not statistically representative. Table 3 summarizes respondent numbers, familiarity with app library or gateway models, direct or previous experience with these models, and whether respondents anticipated a future role for these models, by respondent group. Appendix 4 provides selected closed-ended findings on factors affecting credibility, recommendation, or use as well as challenges related to adoption, recommendation, or use across the 3 respondent groups (refer to Table 6).

Awareness and Involvement

Awareness and direct experience with app libraries and gateway models differed across respondent groups. Most clinicians and people with lived experience were unfamiliar with app libraries or gateway models. Among clinicians, 9 of 17 respondents reported being familiar with these models, and 5 of 17 reported current or previous use or recommendation. Among people with lived experience, 5 of 17 respondents reported familiarity with the models, and 4 of 17 reported current or previous use.

Respondents from health organizations represented organizations with varying levels of involvement. Most respondents from health organizations (9 of 14) considered both app libraries and gateway models when responding to survey questions. Six of 14 operated or managed existing models (model custodians); 2 of 14 used, recommended, or integrated existing models; and 6 of 14 were not currently involved in these activities.

Across respondent groups, responses described potential value in helping people identify and navigate appropriate, trustworthy mental health resources. Health organizations also identified potential roles in service delivery and health system use.

Factors Influencing Credibility, Recommendation, or Use

Among the respondents from health organizations, the most frequently selected factors contributing to trust and credibility were privacy and data protection (14 of 14) and usability and accessibility (13 of 14). Clinical effectiveness and clinical safety were each selected by 11 of 14 respondents, and security and technical stability by 9 of 14 respondents.

Among clinicians, the most frequently selected factors influencing recommendation were trust and credibility in the organization providing the model, evidence of effectiveness, and ease of use (15 of 17 for each). Privacy and data protection were selected by 12 of 17 respondents.

Among the 5 respondents who were people with lived experience and who answered this question about factors influencing use based on their reported familiarity with these models, all 5 selected accessibility. Four selected trust in the organization providing the model and ease of use, and 3 selected each of privacy and data protection, clinical effectiveness, and clinical safety.

Challenges Related to Adoption, Recommendation, or Use

Among the 13 respondents from health organizations who answered the question about challenges adopting or supporting models, the most frequently selected was lack of funding and resources (7 of 13). Technology/infrastructure limitations, challenges with integration into services, and organizational readiness were each selected by 6 of 13 respondents.

Among clinicians, the most frequently selected challenges to use or recommend models were cost considerations (14 of 17). Unclear accountability and limited patient interest were each selected by 9 of 17 respondents, followed by cultural relevance (8 of 17), and privacy and data protection (7 of 17).

Among the 5 respondents who were people with lived experience and who answered this question about challenges in using models, all 5 selected cost of apps. Four selected difficulty knowing which mental health apps to trust, 4 selected privacy and data protection concerns, and 3 selected limited accessibility.

Future

Across all 3 respondent groups, more than half anticipated a role for app libraries and gateway models over the next 3 to 5 years. Respondents from health organizations were more likely to anticipate a future role (12 of 14) than clinicians (9 of 17) or people with lived experience (9 of 17), among whom responses reflected greater uncertainty. Among the 6 health organizations not currently involved with these models, 4 anticipated a future role.

Open-ended responses also identified AI as an emerging consideration, with respondents describing its increasing use and potential role in supporting navigation or engagement, alongside concerns about privacy, accuracy, ethics, and appropriate safeguards.

Table 3: Key Descriptive Survey Findings

^aModels = mental health app library or gateway.

^bHealth organizations represented a range of roles, including model custodians, organizations integrating or recommending existing models, organizations involved in governance oversight, and organizations not currently involved with app libraries or gateway models.

^cFamiliarity with the model was not assessed for health organizations respondents because their survey instead asked about their organization’s involvement with the app library or gateway model.

^dSurvey respondents that did not select yes to an anticipated role of models over the next 3 to 5 years answered unsure (2 of 14 respondents from health care organizations, 8 of 17 respondents from clinician and other providers group, and 8 of 17 respondents from the people with lived experience group).

Discussion

The identified evidence describes mental health app libraries and gateway models as a varied and evolving landscape rather than a single intervention. App libraries generally focus on assessing, curating, and presenting information about digital mental health apps. Gateway models provide broader navigation functions that may include screening, triage, referral pathways, crisis support, self-management resources, virtual care, and connections to health and community services. Many contemporary gateway models also incorporate app library functions, bringing complementary assessment and navigation functions together within the same model.^{6,7,10,14,17,53} Across these models, the identified evidence focuses on model characteristics, implementation experience, operational requirements, and knowledge user perspectives. Less information is available on comparative effectiveness or long-term performance. Accordingly, this discussion focuses on recurring implementation considerations, their relevance to Canada, and the uncertainties that would need to be addressed in any future exploration.^{4,14,17,21,36}

What Appears Consistent Across Evidence Sources

Providing access to a mental health app library alone did not consistently translate into sustained use or integration with care. Throughout the published evidence, implementation depended on interacting factors such as awareness, intuitive navigation, organizational credibility, provider engagement, workflow integration, practical implementation support, and connections with existing services.^{5,7,20,36,53,56,59} Findings from the CDA-AMC knowledge user surveys identified similar considerations related to adoption and implementation, recommendation, and use. Among survey participants, responses identified considerations relevant to implementation by health organizations, recommendation by clinicians and other care providers, and use by end users.

Although many considerations were shared across respondent groups, the relevance to use, adoption, recommendation, and implementation varied by respondent group. Health organizations emphasized privacy and data protection, usability and accessibility, and clinical effectiveness and safety, while funding, infrastructure, service integration, and organizational readiness were prominent implementation challenges. Clinicians highlighted organizational credibility, evidence of effectiveness, and ease of use when considering recommendation, while cost was the most frequently selected challenge. People with lived experience pointed to accessibility, trust in the organization providing the model, and ease of use, while cost of apps was also the most frequently selected challenge.

Human-supported digital navigation was 1 approach described in the literature in which a trained person helps users identify, access, and use appropriate digital mental health resources.⁴⁴ Digital navigation may complement an app library or gateway model by supporting app selection, onboarding, digital literacy, troubleshooting, user engagement, and preparation of app-generated information for clinical review.^4,44,56,59 Although the literature increasingly describes these approaches, the identified evidence did not establish whether digital navigator support improves sustained use, provider workload, service integration, or health outcomes.

Trust and credibility also emerged as cross-cutting considerations for the use and recommendation of digital mental health resources. Transparent governance, evidence-informed recommendations, privacy and security protections, organizational accountability, usability, accessibility, and current information were repeatedly identified as factors influencing confidence in app libraries and gateway models.^{3,8,10-12,14,15,33,61} Findings from the knowledge user surveys were consistent with these themes, although the relative emphasis differed across respondent groups.

Equity, accessibility, and cultural responsiveness were not discrete add-on features but intersecting considerations influencing whether people could identify, access, understand, and use available resources. Examples of relevant considerations included digital and health literacy, language accessibility, affordability, internet and device access, privacy preferences, cultural relevance, and flexible pathways to professional or self-directed support.^3,5,13,14,26 However, the identified literature provided limited evidence on whether specific equity-focused approaches reduced inequities or improved patient outcomes.^5,14,26 Collectively, these recurring themes provide a foundation for interpreting the operational experience reported across existing models.

Lessons From Existing Models

Existing models indicate that maintaining current and accurate information is an ongoing operational requirement rather than a one-time activity. Apps and supporting information can change over time, requiring ongoing reassessment, monitoring, updating, and quality assurance.^{8,10,12,14,33} This requirement applies equally to gateway models because service directories, referral information, web links, and wait-time information can also become incomplete or outdated.

Experiences with discontinued or substantially modified models also provide information about model continuity. The Government of Canada transitioned away from the Wellness Together Canada initiative in 2024 following the emergency phase of the COVID-19 pandemic, directing users to other mental health resources and provincial and territorial systems of care.⁴⁹ The NHS Apps Library provides another example of discontinuation in which NHS England Digital reported that the service was decommissioned in 2021.⁶³ The NHS reported integrating app-related content into its broader digital services rather than maintaining the original stand-alone library.⁵⁴ These examples show the importance of considering how models may change over time in response to evolving service needs and broader health system and digital service environments.

Model design and assessment approaches varied across organizational and jurisdictional contexts, including their relationships with regulation, accreditation, reimbursement, clinical services, and community resources.¹⁰ Examples from Australia and the US also described differences in selection and navigation priorities related to language, privacy, accessibility, cultural safety, affordability, and community needs.^5,16 The identified evidence did not establish whether adapting approaches to different contexts improves outcomes or whether any particular governance or assessment approach performs better than another.

Experience with gateway models also showed that platform availability and reported traffic do not, by themselves, demonstrate effective navigation or sustained engagement. Users may reach specific content through external searches rather than follow an intended navigation pathway. Promotional activities may generate short-term increases in traffic; visits, searches, registrations, downloads, and feature use represent different stages of engagement.^6,7,17,21 These metrics require interpretation alongside information on completed connections to health and community services, continued use, user experience, equity, and outcomes.

Provider exposure and positive perceptions likewise did not necessarily translate into routine implementation. A facilitated demonstration of Head to Health (now Medicare Mental Health),⁵⁵ an Australian gateway model, was followed by high level of reported willingness among practitioners to recommend the gateway, but subsequent recommendation and routine use were not evaluated.^23,53 Similarly, TherAppX, a Canadian app library, was viewed positively by professionals, but observed use remained low and the reviewed content did not become part of routine practice during the pilot.^36,53 Collectively, these examples suggest that awareness, organizational endorsement, provider training, and workflow integration may influence implementation, although the identified evidence did not establish their effects on sustained adoption. These international and model-specific experiences also provide context for considering the potential relevance of app libraries and gateway models within health systems in Canada.

Relevance to Health Care Context in Canada

Evidence from Canada included national and provincial models, an app library pilot, a Canadian app assessment framework, relevant regulatory context, and a proposed federated youth navigation model.^{7,10,17,26,36,61} The app library and gateway models and the app library pilot provided evidence on models directly relevant to this report. The assessment framework, regulatory context, and proposed navigation model provided complementary evidence relevant to app assessment, oversight, navigation, and potential model development. These sources were included for the functions and implementation considerations they informed rather than because each represented an actual app library or gateway model. None of these sources provided a direct comparison between app libraries and gateway models.

Findings from the CDA-AMC knowledge user surveys provided additional context from health organizations, clinicians and other mental health providers, and people with lived experience in Canada and internationally. Respondents from health organizations were more likely to anticipate a future role for app libraries and gateway models than clinicians or people with lived experience. Survey responses identified considerations related to trust and credibility, clinical evidence, privacy, accessibility, implementation, and use that were consistent with the themes identified in the literature. However, the survey findings were not intended to be generalized to the broader populations represented by the respondent groups or establish a preferred model.

For Canada, the relevance of an app library or gateway model would depend on the purpose and functions required, and the populations to be served. Other considerations include alignment with the existing services and care pathways, jurisdictional responsibilities, and resources available to support the model.

Implementation Considerations Relevant to Health Care Context in Canada

Findings from the identified literature highlighted several interdependent considerations for any future exploration. Consideration of mental health app libraries and gateway models should be guided primarily by the problem to be addressed and the functions required, rather than by the model label itself.^6,7,14,17 App libraries can support structured assessment and organized access to information about digital mental health apps.^{8,10,15,16,19} Gateway models may incorporate these app library functions while also supporting screening, triage, referral, crisis support, self-management resources, and connections to health and community services.^3,5-7 Their broader functional scope may also require greater governance, service coordination, infrastructure, workforce support, and ongoing maintenance.

The first is model scope. Is the intended function limited to providing assessed app information or does it extend to screening, triage, personalized navigation, referral, crisis support, virtual services, and connections to community or clinical care. Because app libraries and gateway models may combine these functions in different ways, clearly defining a model’s intended purpose, scope, and boundaries is likely to be more informative.^6,7,14,17 Relying on the model label alone may provide less useful information.

The second is governance and accountability. Existing models commonly incorporated features such as multidisciplinary oversight, organizational partnerships, clinical and technical expertise, end user involvement, privacy protection, and transparent assessment processes. However, few of the identified sources compared governance arrangements, decision-making authority, accountability, assessment ownership, conflict-of-interest management, and responsibility for maintaining current information.^14,15,42,61

The third is sustained operational capacity, recognizing that platform development represents only an initial requirement. Ongoing operation may require activities such as app and content reassessment, technical maintenance, accessibility review, communications, analytics, end user engagement, provider support, and coordination with services and referral pathways.⁶ The identified literature did not establish whether any particular funding, staffing, or partnership model was associated with long-term sustainability.^6,8,14,15,17

The fourth is implementation within care and community settings. The identified literature that focused on clinicians and other health care professionals identified considerations such as training, practical evaluation resources, technical support, organizational endorsement, time, professional accountability, and workflow integration as important considerations.²⁰ Evidence focused on end users emphasized factors such as understandable information, trust, privacy, accessibility, autonomy, and options for human support.⁶ Other implementation factors included centralized access, intuitive navigation, transparent assessment, provider engagement, implementation support, integration with care pathways, communication, interoperability, and continuous quality improvement.^{4,5,20,22-24,26,34,37,38} Reported barriers included limited funding and workforce capacity, competing priorities, workflow challenges, uncertainty about app quality, privacy, and limited awareness. Other barriers included complex navigation, digital literacy, cost, language and accessibility needs, and unequal access to digital devices or reliable internet.^{8,10,13,24,29,34,44} These considerations are interdependent because a technically functional platform may still achieve limited use or uptake if it is poorly aligned with end user needs or existing service pathways.^3,13,20,44

Finally, AI-enabled functions integrated into app library or gateway models warrant separate governance attention. The identified literature described conversational assistance, adaptive screening, and automated identification of potential concerns, with much of the evidence being conceptual or descriptive.^6,14,26 Relevant considerations included privacy, transparency, algorithmic bias, equitable access, safety, human oversight, and ongoing monitoring. Although these considerations were frequently reported, the identified literature did not establish the comparative value or effects of these functions on implementation, navigation, service connection, clinical outcomes, or long-term sustainability.

Remaining Uncertainties and Areas for Future Exploration

The identified literature leaves uncertainties about comparative effectiveness, sustained use, service connection, health outcomes, costs, scalability, and long-term sustainability. Much of the identified literature describes existing models, early implementation, utilization, or knowledge user perspectives rather than comparative or longitudinal evaluation.^{5,17,36,44,59,64} Consequently, the identified literature did not establish a preferred model or which combinations of functions, governance, assessment, implementation support, and maintenance are most effective.

Future exploration could examine how different models influence the full pathway from resource discovery to service connection, including whether users identify appropriate resources, complete referrals, continue using selected tools, and experience improved access or outcomes. Evaluation would also benefit from distinguishing reach and awareness from adoption, sustained engagement, and clinical or health system outcomes.^7,17,21,53

Further evaluation could address uncertainties in governance and operational requirements, including assessment ownership, reassessment frequency, staffing, training, technical escalation, data-review protocols, funding, partnership arrangements, interoperability, and coordination across jurisdictions and services.^14,20,44,61 Questions also remain regarding how international frameworks and models could be adapted to languages, cultures, regulatory environments, health system structures, and population needs in Canada. Further work could examine equity and differential access, including the experiences of people facing barriers related to digital connectivity, device access, cost, language, disability, health literacy, privacy, geography, and cultural relevance. The identified literature included limited representation of several populations and provides little comparative evidence regarding which design or implementation approaches improve equitable access.^3,5,13,14

The identified evidence did not provide sufficiently consistent cost information to estimate the financial investment required to establish or operate an app library or gateway model. Instead, the literature identified resource requirements related to areas such as staffing, technology, app assessment, maintenance, governance, and service integration.

Overall, the identified literature focused more on model characteristics, implementation experience, and operational considerations than on comparative effectiveness or long-term performance. These uncertainties prevent firm conclusions about which approaches are most effective or sustainable, and identify priorities for future evaluation.

Limitations

This Environmental Scan has methodological and evidence-based limitations that should be considered when interpreting the findings. These findings reflect the evidence identified through this Environmental Scan and should not be interpreted as an exhaustive assessment of all available literature. The identified literature varied in study design, setting, population, terminology, model type, and measures of use and uptake, which limits direct comparisons across app libraries, gateway models, assessment frameworks, and human support functions. Much of the literature described model characteristics, conceptual approaches, operational processes, or early implementation rather than long-term evaluation. The identified literature focused more on governance, assessment domains, platform features, and implementation considerations than for comparative effectiveness, sustained engagement, costs, scalability, service outcomes, or health system effects.^4,14,17 Information related to funding, workforce requirements, maintenance, and sustainability was often incomplete or insufficiently detailed to support meaningful comparisons. Measures of use and uptake included website visits, searches, registrations, downloads, referrals, feature activity, and stated intentions. These measures represent different stages of engagement, and did not establish sustained use, connection to health and community services, clinical benefit, or population-level impact.^6,7,17,21,53

Within the identified literature, knowledge user perspectives were represented unevenly across studies. Some studies included small, geographically concentrated or setting-specific samples, and several populations and accessibility needs were underrepresented.^3,5,13,36 These limitations reduce confidence in transferring findings across populations and jurisdictions.

The survey component was voluntary and included 48 respondents who consented and represented health organizations, clinicians, and people with lived experience. The number, distribution, and recruitment of respondents do not support population estimates or representative conclusions regarding organizations, providers, or person with lived experience in Canada. Geographic representation was also uneven and could not be fully characterized because some respondents participated anonymously. The people with lived experience sample also included a higher proportion of older participants with substantial representation from family members or caregivers and peer support workers or mental health advocates. Some respondents identified more than 1 role. These characteristics may have limited the range and balance of perspectives from people with lived experience. Respondents also differed in their familiarity with and direct experience of app libraries and gateway models, which may have influenced their perspectives. Some organizations were targeted because of their expected relevance to the scan but did not respond, so their perspectives were not represented. Accordingly, the survey findings should be interpreted as contextual knowledge user perspectives rather than representative views.

The transferability of the evidence to the health care context in Canada also remains uncertain. Although evidence from Canada included several relevant models and frameworks, the identified literature provided limited information on long-term performance and direct comparisons. International literature sources provided valuable operational context; however, differences in regulation, funding, health system organization, populations, and digital infrastructure limit assumptions regarding direct applicability. Therefore, the findings are best interpreted as evidence-informed implementation considerations and areas of uncertainty rather than evidence supporting a specific model.

Conclusions

Summary of Evidence

Across the entire body of evidence included in this report, considerations relevant to mental health app libraries and gateway models extended beyond the availability of digital resources. Governance, transparent assessment, privacy and security, accessibility, provider engagement, integration with care pathways, current information, and sustained operational capacity consistently emerged as important considerations. App libraries can support structured assessment and organized access to trusted information about digital mental health apps. Gateway models can address broader navigation needs through functions such as screening, triage, referral, crisis support, self-management resources, and connections to care. The evidence identified in this report did not establish that 1 approach is consistently preferable or more effective than the other. Rather, the most appropriate scope is likely to depend on the intended purpose, user needs, existing services in Canada, jurisdictional responsibilities, and the organizational capacity required to operate and maintain the model.

Implications for Decision-Making

For decision-makers, the principal implication is that consideration of a model extends beyond selecting a digital platform to defining the broader operating model. Relevant considerations include governance and accountability, assessment and reassessment processes, privacy, safety, accessibility, and provider and user support. Other considerations include integration with health and community services, data management and interoperability, equitable access, sustainable resources, and evaluation of reach, use, connections to health and community services, and outcomes. These represent areas for future exploration rather than recommendations for a specific model or implementation approach.

Important uncertainties remain regarding comparative effectiveness, long-term sustainability, costs, workforce requirements, implementation strategies, and health system impacts. Taken together, the published literature, and knowledge user survey findings support further exploration of the functions that may be valuable within the health care context in Canada. Gateway functions may warrant particular consideration if the intended purpose extends beyond app assessment and presentation to include navigation, referral, service coordination, or connection with care. However, the evidence identified in this report did not establish whether a gateway model is preferable to a stand-alone app library, or the level of financial investment required to establish or sustain either model type. Context-specific costing of staffing, technology, assessment, maintenance, governance, and service integration requirements would be needed to inform further planning.

References

1.World Health Organization. Mental Health Fact Sheets: Strengthening Our Response. 2025. Updated October 8, 2025. Accessed August 6, 2026. https://www.who.int/news-room/fact-sheets/detail/mental-health-strengthening-our-response

2.World Health Organization. Mental Health, Brain Health and Substance Use: Comorbidities with physical health. 2025. Updated October 8, 2025. Accessed August 6, 2026. https://www.who.int/teams/mental-health-and-substance-use/treatment-care/comorbidities-with-physical-health

3.Stafford E, Brister T, Duckworth K, Rauseo-Ricupero N, Lagan S. Needs and experiences of users of digital navigation tools for mental health treatment and supportive services: survey study. JMIR Ment Health. 2021;8(6):e27022. doi:10.2196/27022 PubMed

4.Choudhary S, Mehta UM, Naslund J, Torous J. Translating digital health into the real world: the evolving role of digital navigators to enhance mental health access and outcomes. J Technol Behav Sci. 2025. doi:10.1007/s41347-025-00569-0

5.Bartel K, Siriwardene AM, Worley P, et al. Improving mental health referral systems in rural Australia: co-Design study with health professionals and consumers. JMIR Hum Factors. 2025;12:e73460. doi:10.2196/73460 PubMed

6.Weng JH, Hu Y, Heaukulani C, et al. Mental wellness self-care in Singapore with mindline.sg: a Tutorial on the development of a digital mental health platform for behavior change. J Med Internet Res. 2024;26:e44443. doi:10.2196/44443 PubMed

7.Cote LP, Lane J. Evaluation of the effectiveness of Suicide.ca, Quebec's digital suicide prevention strategy platform: cross-sectional descriptive Study. JMIR Form Res. 2024;8:e46195. doi:10.2196/46195 PubMed

8.Dwyer B, Mikkelson J, Burns J, Diaz-Pacheco V, Torous J. Mental health apps and crisis support: exploring the impact of 988. Psychiatr Serv. 2025;76(10):867-871. doi:10.1176/appi.ps.20240485 PubMed

9.Ghosal S, Zhang M, Bogosian A, et al. Virtual reality-based mindfulness applications: a commercial health app review. BMJ Health & Care Informatics. 2026;33(1):18. doi:10.1136/bmjhci-2025-101510 PubMed

10.Khadjesari Z, Brown T, Naughton F. Regulation and accreditation of addictive behaviour applications-navigating the landscape. Addiction. 2021;116(12):3276-3283. doi:10.1111/add.15484 PubMed

11.Larsen ME, Huckvale K, Nicholas J, et al. Using science to sell apps: evaluation of mental health app store quality claims. Npj Digital Medicine. 2019;2:18. doi:10.1038/s41746-019-0093-1 PubMed

12.Melcher J, Torous J. Smartphone apps for college mental health: a concern for privacy and quality of current offerings. Psychiatr Serv. 2020;71(11):1114-1119. doi:10.1176/appi.ps.202000098 PubMed

13.Pretorius C, Chambers D, Coyle D. Young people's online help-seeking and mental health difficulties: systematic narrative review. J Med Internet Res. 2019;21(11):e13873. doi:10.2196/13873 PubMed

14.Woods CE, Furst MA, Dissanayake M, et al. Mental health care navigation tools in Australia: infoveillance study. JMIR Public Health Surveill. 2024;10:e60079. doi:10.2196/60079 PubMed

15.Garland AF, Jenveja AK, Patterson JE. Psyberguide: a useful resource for mental health apps in primary care and beyond. Fam Syst Health. 2021;39(1):155-157. doi:10.1037/fsh0000587 PubMed

16.Montgomery RM, Brandysky L, Neary M, et al. Curating the digital mental health landscape with a guide to behavioral health apps: a county-driven resource. Psychiatr Serv. 2021;72(10):1229-1232. doi:10.1176/appi.ps.202000803 PubMed

17.Basnet S, Chaiton M. Effectiveness of the Wellness Together Canada Portal as a digital mental health intervention in Canada: protocol for a randomized controlled trial. JMIR Res Protoc. 2024;13:e48703. doi:10.2196/48703 PubMed

18.Psihogios AM, Stiles-Shields C, Neary M. The needle in the haystack: identifying credible mobile health apps for pediatric populations during a pandemic and beyond. J Pediatr Psychol. 2020;45(10):1106-1113. doi:10.1093/jpepsy/jsaa094 PubMed

19.Leigh S, Ouyang J, Mimnagh C. Effective? Engaging? Secure? Applying the ORCHA-24 framework to evaluate apps for chronic insomnia disorder. Evidence-Based Mental Health. 2017;20(4):e20. doi:10.1136/eb-2017-102751 PubMed

20.Emerson MR, Dinkel D, Watanabe-Galloway S, Torous J, Johnson DJ. Adaptation of digital navigation training for integrated behavioral health providers: interview and survey study. Transl Behav Med. 2023;13(8):612-623. doi:10.1093/tbm/ibad016 PubMed

21.Leigh S, Daly R, Stevens S, et al. Web-based internet searches for digital health products in the United Kingdom before and during the COVID-19 pandemic: a time-series analysis using app libraries from the Organisation for the Review of Care and Health Applications (ORCHA). BMJ Open. 2021;11(10):e053891. doi:10.1136/bmjopen-2021-053891 PubMed

22.Mental Health Commission of Canada. Assessment framework for mental health apps. 2023. Accessed May 5, 2026. https://mentalhealthcommission.ca/app-assessment/

23.Bassilios B, Ftanou M, Machlin A, et al. Independent evaluation of the head to health digital mental health gateway final report. The University of Melbourne. Accessed May 5, 2026. https://www.health.gov.au/sites/default/files/documents/2022/10/independent-evaluation-of-the-head-to-health-digital-mental-health-gateway-final-report.pdf

24.Healthify. Mental health and wellbeing apps. 2026. Accessed May 5, 2026. https://healthify.nz/apps/m/mental-health-and-wellbeing-apps

25.National Health Service England. The NHS App. Accessed May 5, 2026. https://digital.nhs.uk/services/nhs-apps-library

26.Danielyan H, Hussain A, Patel K, Das Pooja S. From silos to synergy: co-Designing a youth-centered, cost-effective digital health model for adolescent mental health in Canada. Stud Health Technol Inform. 2026;334:47-51. doi:10.3233/shti260013 PubMed

27.Quebec. Take care of your mental health with selected mobile apps. Updated February 25, 2026. Accessed May 5, 2026. https://appsantementale.ca/en

28.American Psychiatric Association. App advisor. Accessed May 5, 2026. https://www.psychiatry.org/psychiatrists/practice/mental-health-apps/the-app-evaluation-model

29.Mental Health Commission of Canada. MHCC assessed mental health apps collection. 2023. Accessed May 5, 2026. https://mentalhealthcommission.ca/mhcc-assessed-mental-health-apps/

30.American College of Physicians. Library of digital health apps for patients. Accessed May 5, 2026. https://www.acponline.org/practice-career/business-resources/telehealth-guidance-and-resources/library-of-digital-health-apps-for-patients?

31.Birmingham Community Healthcare. Embracing wellness. Accessed May 5, 2026. https://bhamcommunity.orchahealth.com/en-GB/embracing-wellness

32.Northern Ireland Social Care Council. HSCNI apps library for mental health and well-being. Accessed May 5, 2026. https://learningzone.niscc.info/learning-resources/hscni-apps-library-for-mental-health-and-well-being/

33.Torous JB, Chan SR, Gipson SYT, et al. A hierarchical framework for evaluation and informed decision making regarding smartphone apps for clinical care. Psychiatr Serv. 2018;69(5):498-500. doi:10.1176/appi.ps.201700423 PubMed

34.ORCHA. Appfinder. Accessed May 5, 2026. https://appfinder.orcha.co.uk

35.One Mind. One mind psyberguide. Accessed May 5, 2026. https://onemindpsyberguide.org/

36.Lane J, Manceau LM, de Chantal PL, et al. Implementing a mental health app library in primary care: A feasibility study. Eval Program Plann. 2024;103:102413. doi:10.1016/j.evalprogplan.2024.102413 PubMed

37.American Psychiatric Association. The app evaluation model. Accessed May 5, 2026. https://www.psychiatry.org/psychiatrists/practice/mental-health-apps/the-app-evaluation-model

38.BIDMC Division of Digital Psychiatry. MIND. Accessed May 5, 2026. https://mindapps.org/Apps

39.ORCHA. ORCHA Baseline Review (OBR). Accessed May 5, 2026. https://www.orchahealth.com/resources/assessment-frameworks/orcha-baseline-review

40.Appguide. Reduce the chaos between Google and the consultation. Guide your patients. Accessed May 5, 2026. https://appguide.ca/en

41.Government of India. Library and information centre. Accessed May 5, 2026. https://www.nimhans.ac.in/library

42.ORCHA. Digital health app library. Accessed May 5, 2026. https://www.orchahealth.com/solutions/health-app-library

43.TherAppX. Appguide. Accessed May 5, 2026. https://appguide.ca/

44.Wisiewski H, Torous J. Digital navigators to implement smartphone and digital tools in care. Acta Psychiatr Scand. 2020;141(4):350-355. doi:10.1111/acps.13149 PubMed

45.Centre d'expertise en technologie de l'information en santé mentale dépendance et itinérance. Take care of your mental health with selectd mobile apps. Accessed May 5, 2026. https://appsantementale.ca/en

46.Government of Newfoundland and Labrador. Newfoundland and Labrador mental health and addictions app library. Accessed May 5, 2026. https://nl-healthapps.orchahealth.com/en-GB

47.University Health Network. Health and wellness apps. Accessed May 5, 2026. https://www.uhn.ca/PatientsFamilies/Health_Information/Patient_Family_Education/Libraries/Pages/health_wellness_apps.aspx

48.Kids Help Phone. Resources around me. 1989. Accessed May 5, 2026. https://kidshelpphone.ca/resources-around-me

49.Health Canada. Health Canada announces transition of mental health resources from Wellness Together Canada. 2024. Accessed August 11, 2026. https://www.canada.ca/en/health-canada/news/2024/02/health-canada-announces-transition-of-mental-health-resources-from-wellness-together-canada.html

50.Mind. Mind app library. Accessed May 5, 2026. https://mind.orchahealth.com/en-GB

51.Mind. Mental health apps. Accessed May 5, 2026. https://www.mind.org.uk/information-support/tips-for-everyday-living/looking-after-your-mental-health-online/mental-health-apps/

52.Department of Health. Your health app finder. Accessed May 5, 2026. https://apps4healthcareni.hscni.net/en-GB

53.Sturk H, Crowther R, Kavanagh DJ. Head to health: practitioner perceptions of the new digital mental health gateway. Aust J Rural Health. 2019;27(5):448-453. doi:10.1111/ajr.12574 PubMed

54.National Health Service England. New look NHS App: What has changed. 2025. Accessed May 5, 2026. https://digital.nhs.uk/services/nhs-app/resources/new-look-nhs-app-what-is-changing

55.Medicare Mental Health Phone Service. Medicare mental health phone service national service model. 2025. Accessed May 5, 2026. https://www.health.gov.au/sites/default/files/2025-05/national-service-model-medicare-mental-health-phone-service.pdf

56.Gorban C, Chong MK, Poulsen A, et al. Young people's experiences using a digital mental health tool to support their care in a real-world service: lived experience-led qualitative study. JMIR Ment Health. 2025;12:e70154. doi:10.2196/70154 PubMed

57.Australian Government. Service model for head and health adult mental health centres and satellites. 2021. Accessed May 5, 2026. https://consultations.health.gov.au/mental-health-services/adult-mental-health-centres/results/revisedheadtohealthcentresandsatellitesservicemodeljune2021.pdf

58.E-mental Health in Practice-eMPHprac. Australian digital mental health: a directory for health practitioners. Accessed May 5, 2026. https://www.emhprac.org.au/wp-content/uploads/2026/02/Australian-Digital-Mental-Health-A-Directory-for-Health-Practitioners.pdf

59.Chen K, Lane E, Burns J, Macrynikola N, Chang S, Torous J. The digital navigator: standardizing human technology support in app-integrated clinical care. Telemed J E Health. 2024;30(7):e1963-e1970. doi:10.1089/tmj.2024.0023 PubMed

60.Garland SN. A step in the right direction: making cognitive-behavioral therapy for insomnia more accessible to people diagnosed with cancer. JSDR. 2021;44(11):1-3. doi:10.1093/sleep/zsab202 PubMed

61.Zelmer J, van Hoof K, Notarianni M, van Mierlo T, Schellenberg M, Tannenbaum C. An assessment framework for e-mental health apps in Canada: results of a modified delphi process. JMIR Mhealth Uhealth. 2018;6(7):e10016. doi:10.2196/10016 PubMed

62.Bassilios B, Ftanou M, Tan A, et al. Environmental scan of digital mental health services. The University of Melbourne; 2022. Accessed May 5, 2026. https://www.health.gov.au/sites/default/files/documents/2022/10/environmental-scan-of-digital-mental-health-services.pdf

63.National Health Service England. The NHS Apps Library has closed. 2021. Accessed May 5, 2026. https://www.nhs.uk/apps-library/filter/?categories=Mental%20health

64.Alon N, Perret S, Cohen A, et al. Digital navigator training to increase access to mental health care in community-based organizations. Psychiatr Serv. 2024;75(6):608-611. doi:10.1176/appi.ps.20230391 PubMed

Appendix 1: Detailed Methods

Please note this appendix has not been copy-edited.

The environmental scan was conducted in response to an external request by the Commission to understand the opportunities and challenges of mental health app libraries and gateway models that exist in Canada and internationally.

To provide a comprehensive overview of this area, Canada’s Drug Agency produced a multi-method environmental scan using complementary evidence sources, including peer-reviewed literature, grey literature, structured surveys of selected knowledge-user groups, and targeted outreach, in partnership with the Commission, to identify relevant models and support survey distribution. CDA-AMC also broadened the research questions to provide a more thorough scan of the available evidence. The approach and scope were expanded to inform evidence-based planning and policy considerations related to mental health app library and gateway models in Canada.

Literature Search

Search Strategy

An information specialist conducted a literature search on key resources including MEDLINE, PsycInfo, the Cochrane Database of Systematic Reviews, the International HTA Database, Overton, the websites of health technology assessment agencies in Canada and major international HTA agencies, as well as a focused internet search. The search approach was customized to retrieve a limited set of results, balancing comprehensiveness with relevance. The search strategy comprised both controlled vocabulary, such as the US National Library of Medicine's MeSH (Medical Subject Headings), and keywords. Search concepts were developed based on the elements of the research questions and selection criteria. The main search concepts were mental health, app libraries, gateways, digital assessments, digital triage, digital navigation models, digital coordination, and digital portals. The search was completed on April 14, 2026 and limited to English-language documents. Retrieval was not limited by publication date. The search strategy is available on request.

Grey literature identified through the literature search was supplemented by targeted searches and resources identified by the project team through August 2026. Sources included app library and gateway websites, reports, organizational and health system resources, guidance, assessment frameworks, and other relevant documentation.

Screening and Study Selection

A single reviewer screened titles and abstracts from the peer-reviewed literature search and assessed the full texts of potentially relevant publications using the selection criteria summarized in Table 4. Relevant evidence identified through grey literature searches, reference lists, and other sources during the environmental scan was also screened for relevance using the same criteria. Grey literature was reviewed to identify existing and discontinued models and to capture operational information on governance, app assessment, delivery, use and uptake, funding and resources, maintenance, sustainability, and emerging trends. Final inclusion of the peer-reviewed and grey literature was based on the predefined selection criteria and relevance to project objective and research questions.

Table 4: Criteria for Literature Screening

Analysis

CDA-AMC synthesized the literature narratively according to the project’s predefined objectives and research questions.

Surveys

Methodology

CDA-AMC conducted 3 surveys, each targeting the perspectives of a distinct knowledge user group; health organizations, mental health care providers, and people with lived experience. The health organization survey targeted organizations involved in operating, governing, funding, recommending, integrating, or using mental health app libraries or gateway models, including organizations that directly operated or managed these platforms. The provider survey targeted clinicians and other professionals involved in delivering mental health care or related services. The people with lived experience survey sought perspectives from end users with experience using mental health services, supports, or digital mental health tools, as well as caregivers, peer support workers, and mental health advocates.

Each of the surveys included closed- and open-ended questions examining awareness and use of app libraries and gateway models, trust and credibility, governance, implementation, accessibility, barriers and facilitators, sustainability, emerging trends, and future considerations. Branching logic directed respondents to questions based on their role, familiarity with app libraries or gateway models, and direct experience. Appendix 3 contains the 3 survey instruments administered to health organizations, clinicians and other mental health providers, and people with lived experience. Appendix 4 provides selected closed-ended survey findings by respondent group.

CDA-AMC used purposive sampling to identify respondents and conducted targeted outreach to relevant organizations, professional networks, and other contacts identified during the environmental scan. The Commission also supported survey engagement by identifying potential contacts and knowledge user networks and sharing the survey instruments. The surveys underwent internal testing and peer review before distribution. Surveys were administered electronically using Alchemer between June 16 and July 30, 2026. Participation was voluntary and informed consent was required before responses were included in the study. All respondents indicated their confidentiality preferences, and respondents could optionally indicate their willingness to participate in follow-up discussions.

Synthesis and Reporting

Survey responses were organized by knowledge-user group and other relevant respondent characteristics, including jurisdiction, familiarity with app libraries or gateway models, and direct experience.

Closed-ended survey responses were summarized descriptively using response counts. Denominators reflected the number of respondents who answered each question, including where branching logic affected question eligibility. Open-ended responses were reviewed and organized around topics relevant to the research questions, with additional topics incorporated where they emerged during analysis. These responses were used to provide context, illustrate participant perspectives, and identify common or differing views across respondent groups. Because of the relatively small number of responses, findings were not statistically compared across respondent groups or jurisdictions.

Appendix 2: Existing Models

Please note this appendix has not been copy-edited.

App assessment frameworks varied in the domains considered. Table 5 provides examples of these domains and the frameworks in which they were reported. The examples illustrate areas considered when assessing apps and are not intended to represent a comprehensive set of assessment criteria.

Table 5: Examples of Assessment Domains Identified Across App Assessment Frameworks

APA = American Psychiatric Association (US), DiGA = Digitale Gesundheitsanwendungen (Digital Health Applications, Germany), MIND = MINDapps.org app library, ORCHA = Organization for the review of care and health apps, PsyberGuide = US-based nonprofit project run by “One Mind”

Additional Models and Resources Identified in the Environmental Scan

The following grey literature sources were identified as relevant to the environmental scan and are grouped according to their primary relevance to app libraries, gateway models and navigation, or app assessment. Some sources span more than 1 category and are listed according to their primary relevance to this report. Selected models are also presented in Table 2 to illustrate variation in model characteristics and operating contexts. The list includes sources that provided information directly relevant to these areas. Duplicate records and sources that only directed readers to another source listed here are not presented separately.

App Libraries

Canada

• Alberta Health Services Mobile Apps Directory (Alberta, Canada)

• AppGuide Pro (Canada)

• Brain Injury Canada Free Mental Health and Daily Living Apps (Canada)

• Confederation College Mental Health and Well-Being Smartphone Apps (Ontario, Canada)

• Kelty Mental Health Resource Centre Resource Library: App or Online Tool (British Columbia, Canada)

• Looking for a Mental Health App or website? (eMentalHealth.ca) (Canada)

• MHCC Assessed Mental Health Apps Collection (Canada)

• Newfoundland and Labrador Health Apps Library (Newfoundland and Labrador, Canada)

• Ontario Shores Online Tools and Mobile Apps (Ontario, Canada)

• Saskatchewan Mobile Apps for Mental Health and Wellness (Saskatchewan, Canada)

• Student Mental Health Network App Library (Canada)

• Take Care of Your Mental Health With Selected Mobile Apps, AppSantéMentale.ca (Quebec, Canada)

• Temiskaming Health Unit Managing Your Mental Health (Ontario, Canada)

• University Health Network Health and Wellness Apps (Ontario, Canada)

International

• ACP Digital Health Apps Library powered by ORCHA (US)

• Birmingham Community Healthcare ORCHA Library (UK)

• CAR-NIMHANS Mental Health App Repository (India)

• Coventry and Warwickshire Partnership NHS Trust ORCHA Library (UK)

• Cwm Taf Morgannwg WISE/ORCHA Library (Wales)

• HSCNI Apps Library for Mental Health and Well-being (Northern Ireland)

• Kaiser Permanente Digital Mental Health Tools (US)

• MIND Apps (US)

• Mind App Library powered by ORCHA (UK)

• NHS Apps Library (UK)

• NZ Health App Library (New Zealand)

• One Mind - PsyberGuide (US)

• ORCHA Digital Health App Library (UK)

• Our Dorset ORCHA Library (UK)

• Staffordshire ORCHA Library (UK)

• Sussex ORCHA Library (UK)

• UCSF Useful Wellness and Mental Health Apps (US)

Gateway Models

Canada

• Kids Help Phone Resources Around Me (Canada)

• Suicide.ca (Quebec, Canada)

• Wellness Together Canada (Canada)

International

• Ask Izzy (Australia)

• Head to Health (now Medicare Mental Health) Digital Mental Health Gateway (Australia)

• HealthPathways (Australia)

• IAR-DST (Initial Assessment and Referral Decision Support Tool) (Australia)

• Medicare Mental Health (Australia)

• mindline (Singapore)

• NHS Leicestershire Digital Directory for Mental Health and Wellbeing Support Services for Children and Young People (UK)

App Assessment Frameworks and Approaches

Canada

• MHCC Assessment Framework for Mental Health Apps (Canada)

International

• American Psychiatric Association App Advisor (US)

• Dartmouth Center for Technology and Behavioral Health App Evaluation Model (US)

• ORCHA AppFinder (UK/international)

Appendix 3: Surveys

Please note this appendix has not been copy-edited.

Survey Questions

Survey 1 (Health Organization)

Inclusion criteria: organizations involved in developing, managing, supporting, or using these mental health app libraries or gateways

Introduction and Consent

Canada’s Drug Agency (CDA-AMC) is conducting an environmental scan in partnership with the Mental Health Commission of Canada (MHCC). This work will inform evidence-based planning and policy considerations related to a potential national mental health app library or gateway model in Canada. It will also help assess its potential role, relevance, and feasibility.

This questionnaire aims to gather high-level insights on existing models, including their structure, use, implementation, and evolution over time, as well as key lessons learned.

Estimated time: 15 to 20 minutes. Participation is voluntary. You may choose not to respond to any question and may discontinue your participation at any time before submission. Unless otherwise specified, all questions are optional and may be skipped. You may save your progress and return to complete the survey at any time before submitting your responses.

Your responses will be used for research and planning purposes. Findings may be included in our Health Technology Review report and journal (published publicly), and will be shared with MHCC. Responses will be synthesized and may be used in aggregate or as illustrative examples unless you indicate otherwise. No organization or individual will be identified without explicit consent. Please inform CDA-AMC of your confidentiality preference at the end of the survey (Q27).

I have read the information above and consent to participate

☐ Yes (continue)

☐ No (end survey)

For the purpose of this survey:

• Mental health app library: A curated collection of digital apps that have been assessed against defined criteria (e.g., privacy, safety, clinical evidence, and usability). These apps are presented through a searchable platform, typically with descriptive information and/or assessment details to support user choice.

• Gateway (navigation model): A platform designed to guide users toward appropriate digital mental health resources. This may include apps, services, directories, and app libraries, along with triage or navigation functions to help users identify options that best match their needs.

Respondent Classification

Q1: Which best describes your organization’s role in relation to mental health app libraries or gateway models?

(Select one)

☐ We operate/manage a model (custodian)

☐ We use/recommend/integrate a model

☐ We fund/govern/oversee such models

☐ None / not currently involved

If selected option is not “custodian” → skip Section 5 entirely.

Respondent Information

Q2: Organization name

(Text)

Q3: Country / jurisdiction

(Text)

Q4: Your role

(Select one)

☐ Health system/organizational leadership

☐ Platform operator/custodian

☐ Policy/governance

☐ Program/service delivery

☐ Clinical

☐ Technical/digital health/IT

☐ Other (specify):

(Text)

Model Use and Uptake

Q5: Does your organization currently use or operate a mental health app library or gateway model as part of its mental health service offerings?

(Select one)

☐ Yes – fund/govern/oversee

☐ Yes – operate/manage

☐ Yes – use/recommend/integrate

☐ Yes – multiple roles

☐ No

☐ Other (specify):

(Text)

Q6: When responding, are you primarily referring to:

☐ App library model

☐ Gateway/navigation model

☐ Both

Q7: What role do these models play in your organization/system? (Select all that apply)

☐ Resource discovery

☐ Clinical support

☐ Patient self-management

☐ Navigation/triage

☐ Service integration

☐ Other (specify):

(Text)

Q8: Which factors influence your organization’s decision to use or adopt these models? (Select all that apply)

☐ Awareness

☐ Trust/credibility

☐ Usability

☐ Integration into workflows

☐ Policy alignment

☐ Resources/infrastructure

☐ Partnerships

☐ Other (specify):

(Text)

Optional: Please elaborate

(Text)

Q9: What challenges has your organization experienced or anticipates experiencing in adopting or supporting these models? (Select all that apply)

☐ Lack of funding/resources

☐ Limited evidence or validation

☐ Integration challenges

☐ Low user uptake

☐ Policy/regulatory barriers

☐ Technical limitations

☐ Organizational readiness

☐ Other (specify):

(Text)

Optional: Please elaborate

(Text)

Q10: Which factors make such models credible or trustworthy from your organization’s perspective? (select up to 3 to 5 most important factors)

☐ Privacy and data protection

☐ Evidence of clinical effectiveness

☐ Clinical safety

☐ Usability and accessibility

☐ Security and technical stability

☐ Cultural safety and equity standards

☐ Identity data governance

☐ Other (specify):

(Text)

Optional: Please elaborate

(Text)

Q11: Which governance or accountability considerations are important when adopting or supporting these models? (select up to 3 most important considerations)

☐ Regulatory oversight

☐ Data governance/privacy

☐ Clinical responsibility

☐ Liability considerations

☐ Quality assurance processes

☐ Other (specify):

(Text)

Optional: Please elaborate

(Text)

Q12: Have you observed positive examples of these models (within your organization or elsewhere)?

☐ Yes

☐ No

If yes:

→ Please briefly describe

(Text)

Q13: Have you observed models being modified or discontinued?

☐ Yes

☐ No

If yes:

→ What factors contributed to this?

(Text)

Q14: How do users typically find or access these models? (Select all that apply)

☐ Search engines

☐ Provider referral

☐ App stores

☐ Health system channels

☐ Social media

☐ Other (specify):

(Text)

Custodian-Specific Questions

(Only shown if Q1 = “We operate/manage a model”)

The following set of questions in this section apply only to organizations that operate or manage an app library or gateway model and focus on operational experience.

Q15: Who is the primary intended audience? (Select all that apply)

☐ General public/people seeking mental health support for themselves or others

☐ Health care providers

☐ Both

☐ Other (specify):

(Text)

Q16: What is the current status of your model? (Select 1 option only)

☐ Active

☐ In development

☐ Being redesigned

☐ Paused

☐ Discontinued

☐ Other (specify):

(Text)

Q17: How is your model operationally supported? (Select all that apply)

☐ Dedicated internal staff

☐ External/vendor support

☐ Partnerships

☐ Internal technical infrastructure

☐ External technical infrastructure

☐ Other (specify):

(Text)

Optional: Please elaborate

(Text)

Q18: Has your model changed over time?

☐ Yes

☐ No

If yes:

→ Please briefly explain how and why (limit to 1 to 2 lines)

(Text)

Q19: What factors have influenced sustainability of your model (Select all that apply)

☐ Funding availability / stability

☐ Staffing / human resources

☐ Partnerships / collaborations

☐ User demand / uptake

☐ Policy or regulatory alignment

☐ Integration with health systems

☐ Technology / infrastructure

☐ Leadership / organizational support

☐ Evaluation evidence / demonstrated impact

☐ Other (specify):

(Text)

Optional: Please elaborate

(Text)

Q20: Were there any components of your model that did not work as intended?

☐ Yes

☐ No

If yes:

→ Please briefly describe

(Text)

Future Considerations

Q21: How are broader digital trends (e.g., AI, evolving user expectations) affecting the relevance of these models?

(Text)

Q22: Do you see a role for these models in your organization/system in the next 3 to 5 years?

☐ Yes

☐ No

☐ Unsure

☐ Not applicable

If yes → Please briefly explain

(Text)

Q23: What key considerations should a national organization keep in mind when assessing the potential role of such models?

(Text)

Q24: Are there any materials you would be willing to share (e.g., reports, evaluations, links)?

If yes → Please provide documents, links, citations, or a brief description.

(Text / Upload button)

Follow-up and Confidentiality

Q25: May we follow up with you if clarification is needed or if additional context would help interpret your responses?

☐ Yes

☐ No

If yes:

→ Provide name and email address here

(Text)

Q26: Would you be open to participating in a follow-up interview or discussion if this work progresses to a second phase?

☐ Yes

☐ No

If yes:

→ Provide name and email address here

(Text)

Q27: Confidentiality

☐ May be attributed to my organization (i.e., responses may be quoted or summarized with organizational identification/name)

☐ Do not attribute responses to my organization (i.e., responses may be used only in aggregate or without identifying the organization)

Thank you Page

This marks the end of the survey. If the participant selects the “No” option during the consent page. They will be directed here.

Survey 2 (Clinicians and Other Mental Health Providers)

Inclusion criteria: Clinicians, other health care professionals, professional associations, and specialized provider groups involved in mental health care

Introduction and Consent

Canada’s Drug Agency (CDA-AMC) is conducting an environmental scan in partnership with the Mental Health Commission of Canada (MHCC). This work will inform evidence-based planning and policy considerations related to a potential national mental health app library or gateway model in Canada. It will also help assess its potential role, relevance, and feasibility.

This questionnaire aims to gather high-level insights on existing models, including their structure, use, implementation, and evolution over time, as well as key lessons learned.

Estimated time: 15 to 20 minutes. Participation is voluntary. You may choose not to respond to any question and may discontinue your participation at any time before submission. Unless otherwise specified, all questions are optional and may be skipped. You may save your progress and return to complete the survey at any time before submitting your responses.

Your responses will be used for research and planning purposes. Findings may be included in our Health Technology Review report and journal (published publicly) and will be shared with MHCC. Responses will be synthesized and may be used in aggregate or as illustrative examples unless you indicate otherwise. No organization or individual will be identified without explicit consent. Please inform CDA-AMC of your confidentiality preference at the end of the survey (Q20).

I have read the information above and consent to participate *

☐ Yes (continue)

☐ No (end survey)

For the purpose of this survey:

• Mental health app library: A curated collection of digital apps that have been assessed against defined criteria (e.g., privacy, safety, clinical evidence, and usability). These apps are presented through a searchable platform, typically with descriptive information and/or assessment details to support user choice. Example: https://nl-healthapps.orchahealth.com/en-GB

• Gateway (navigation model): A platform designed to guide users toward appropriate digital mental health resources. This may include apps, services, directories, and app libraries, along with triage or navigation functions to help users identify options that best match their needs. Example: https://www.medicarementalhealth.gov.au

Respondent Classification

Q1: Which best describes your profession? *

☐ Family physician

☐ Psychiatrist

☐ Psychologist

☐ Social worker

☐ Nurse practitioner

☐ Registered nurse

☐ Occupational therapist

☐ Educator or school-based professional

☐ Counsellor/psychotherapist (please specify)

(Text)

☐ Other (specify)

(Text)

Q2: City, Province/State, and Country *

(Text)

Q3: What is your primary practice setting? *

(Select one)

☐ Primary care/family practice clinic

☐ Specialized mental health care

☐ Hospital

☐ Community-based practice/centre

☐ Academic (School/college/university)

☐ Virtual

☐ Other (specify):

(Text)

Model Awareness, Use and Experience

Depending on your responses, some questions may be skipped if they do not apply to your experience.

Q4: How do patients typically find or access these mental health apps or digital tools? *

(Select all that apply)

☐ Search engines

☐ Referral from health or other trusted professionals

☐ App stores

☐ Social media

☐ Friends or family

☐ Online communities

☐ websites of health organizations

☐ Not sure

☐ Other (specify):

(Text)

Q5: Are you familiar with mental health app libraries or gateway models? *

(Select one)

☐ Yes

☐ No

If respondent answers

Yes → Continue to Q6–Q13.

No → Skip Q6–Q13 and proceed to Q14 (Section 4: Future Considerations)

Q6: Have you ever used or recommended a mental health app library or gateway model in your practice or professional role? *

(Select one)

☐ Yes, currently use/recommend

☐ Yes, used in the past

☐ Aware of them but have not used/recommended

☐ No

If respondent answers:

☐ Aware of them but have not used/recommended

☐ No

→ Skip Q8, Q12 and Q13 (questions requiring direct experience), but continue to Q9, Q10, Q11, Q14, and onwards since respondents can still provide views on adoption factors, barriers, and trust.

Otherwise, proceed to the following questions normally.

Q7. When responding, are you primarily referring to*:

(Select one)

☐ App library model

☐ Gateway/navigation model

☐ Both

Q8: In what ways have these models been useful in your practice or professional role? *

(Select all that apply)

☐ Helped me find appropriate mental health apps or tools for patients

☐ Helped me identify appropriate mental health services and supports for patients

☐ Improved my confidence in mental health app recommendations

☐ Saved time

☐ Supported self-management

☐ Facilitated referral/navigation

☐ Supported monitoring/follow-up

☐ They have not been helpful

☐ Other (specify):

(Text)

Q9: Which factors influence whether you would recommend these models to patients? *

(Select all that apply)

☐ Trust/credibility in the organization providing the model

☐ Privacy and data protection

☐ Evidence of effectiveness

☐ Ease of use

☐ Accessibility

☐ Cultural relevance

☐ Recommendations from health or other trusted professionals

☐ Endorsement by reputable organizations (e.g., MHCC, Canada 211, professional associations)

☐ Clinical relevance

☐ Patient preferences

☐ Integration into workflow

☐ Time required

☐ Organizational support

☐ Other (specify):

(Text)

Optional: Please elaborate

(Text)

Q10: What challenges have you experienced or would you anticipate when using or recommending these models? *

(Select all that apply)

☐ Limited evidence

☐ Privacy concerns

☐ Unclear accountability

☐ Lack of time

☐ Workflow integration challenges

☐ Limited patient interest

☐ Limited organizational support

☐ Accessibility

☐ Cultural relevance, safety, or appropriateness

☐ Cost considerations

☐ Technical issues

☐ Policy or regulatory barriers

☐ Other (specify):

(Text)

Optional: Please elaborate

(Text)

Q11: Which factors most influence your confidence in the credibility, trustworthiness or appropriateness of these models from your perspective? *

(Select up to 5 options that are most important to you)

☐ Privacy and confidentiality

☐ Evidence of clinical effectiveness

☐ Evidence of clinical safety

☐ Usability and accessibility

☐ Security and technical stability

☐ Cultural safety and equity standards

☐ Endorsement by trusted organizations

☐ Other (specify):

(Text)

Optional: Please elaborate

(Text)

Q12: Have you observed positive examples of these models (in your practice or elsewhere)?

☐ Yes

☐ No

If yes:

→ Please briefly describe

(Text)

Q13: Have you observed models being modified or discontinued?

☐ Yes

☐ No

If yes:

→ What factors contributed to this?

(Text)

Future Considerations

Q14: How are broader digital trends (e.g., AI, evolving user expectations) affecting the relevance of these models?

(Text)

Q15: Do you see a role for these models in your practice or professional role, and in mental health care more broadly, over the next 3 to 5 years?

☐ Yes

☐ No

☐ Unsure

Please briefly explain your response, including any factors influencing your view (optional)

(Text)

Q16: What key considerations should a national organization keep in mind when assessing the potential role of such models?

(Text)

Q17: Are there any materials you would be willing to share (e.g., reports, evaluations, links)?

☐ Yes

☐ No

If yes → Please provide documents, links, citations, or a brief description.

(Text / Upload button)

Follow-up and Confidentiality

Q18: May we follow up with you if clarification is needed or if additional context would help interpret your responses? *

☐ Yes

☐ No

If yes:

→ Provide name and email address here

(Text)

Q19: Would you be open to participating in a follow-up interview or discussion if this work progresses to a second phase? *

☐ Yes

☐ No

If yes:

→ Provide name and email address here

(Text)

Q20: Confidentiality *

☐ May be attributed to me or my organization (i.e., responses may be quoted or summarized with your or your organizational identification/name)

☐ Do not attribute my responses to me or my organization (i.e., responses may be used only in aggregate or without identifying yourself or the organization)

Thank you Page

This marks the end of the survey. If the participant selects the “No” option during the consent page. They will be directed here.

Survey 3 (People With Lived Experience)

Inclusion criteria: People with lived and living experience with mental health concerns (this survey would also be inclusive of family members or caregivers supporting someone with mental health concerns; peer support workers; and mental health advocacy groups and organizations

Introduction and Consent

Canada’s Drug Agency (CDA-AMC) is conducting an environmental scan in partnership with the Mental Health Commission of Canada (MHCC). This work will inform evidence-based planning and policy considerations related to a potential national mental health app library or gateway model in Canada. It will also help assess its potential role, relevance, and feasibility.

This questionnaire aims to gather high-level insights on existing models, including their structure, use, implementation, and evolution over time, as well as key lessons learned.

Estimated time: 15 to 20 minutes. Participation is voluntary. You may choose not to respond to any question and may discontinue your participation at any time before submission. Unless otherwise specified, all questions are optional and may be skipped. You may save your progress and return to complete the survey at any time before submitting your responses.

Your responses will be used for research and planning purposes. Findings may be included in our Health Technology Review report and journal (published publicly) and will be shared with MHCC. Responses will be synthesized and may be used in aggregate or as illustrative examples unless you indicate otherwise. No organization or individual will be identified without explicit consent. Please inform CDA-AMC of your confidentiality preference at the end of the survey (Q20).

I have read the information above and consent to participate

☐ Yes (continue)

☐ No (end survey)

For the purpose of this survey:

• Mental health app library: A curated collection of digital apps that have been assessed against defined criteria (e.g., privacy, safety, clinical evidence, and usability). These apps are presented through a searchable platform, typically with descriptive information and/or assessment details to support user choice. Example: https://nl-healthapps.orchahealth.com/en-GB

• Gateway (navigation model): A platform designed to guide users toward appropriate digital mental health resources. This may include apps, services, directories, and app libraries, along with triage or navigation functions to help users identify options that best match their needs. Example: https://www.medicarementalhealth.gov.au

About You

Q1: Which best describes your connection to mental health services or supports? *

(Select all that apply)

☐ I currently use mental health services or supports

☐ I have previously used mental health services or supports

☐ I have used mental health apps or digital mental health tools

☐ I am a family member or caregiver supporting someone with mental health concerns

☐ I am a peer support worker or mental health advocate

☐ Prefer not to say

☐ Other (specify)

(Text)

Q2: In which city, province/state and country do you live? *

(Text)

Q3: What age range do you belong to? (Optional)

☐ Under 18 years

☐ 18 to 24 years

☐ 25 to 34 years

☐ 35 to 44 years

☐ 45 to 54 years

☐ 5 to 64 years

☐ 65 years or older

☐ Prefer not to say

Experience with Mental Health App Libraries and Gateways

Depending on your responses, some questions may be skipped if they do not apply to your experience.

Q4: Before today, were you familiar with mental health app libraries or gateway models? *

(Select one)

☐ Yes

☐ No

If respondent answers: No

→ skip Q5–Q12 and proceed to Q13.

Q5: Have you ever used a mental health app library or gateway model? *

(Select one)

☐ Yes, currently use

☐ Yes, used in the past

☐ Aware of them but have not used them

☐ No

☐ Not sure

If respondent answers: Aware but have not used / No / Not sure

→ skip Q7, Q11, and Q12.

Q6: When responding, are you primarily referring to: *

(Select one)

☐ App library model

☐ Gateway/navigation model

☐ Both

☐ Not sure

Q7: How have these models been helpful to you, if at all? *

(Select all that apply)

☐ Helped me find mental health apps or tools that fit my needs

☐ Made me feel more confident about trying a mental health app

☐ Helped me understand which mental health apps are trustworthy

☐ Saved me time

☐ Helped me connect with mental health services or supports

☐ Helped me manage my mental health

☐ They have not been helpful

☐ Other (specify):

(Text)

Q8: Which factors influence whether you would use these models? *

(Select all that apply)

☐ Trust in the organization providing the model

☐ Privacy and data protection

☐ Evidence that mental health apps are clinically effective

☐ Evidence that mental health apps are clinically safe

☐ Ease of use

☐ Accessibility

☐ Recommendations from health or other trusted professionals

☐ Recommendations from friends or family

☐ Cultural relevance

☐ Other (specify):

(Text)

Optional: Please elaborate

(Text)

Q9: What challenges have you experienced or would you anticipate when using these models? *

(Select all that apply)

☐ Not relevant to my needs

☐ Too much information

☐ Hard to know which mental health apps to trust

☐ Privacy concerns

☐ Difficult to use

☐ Limited accessibility

☐ Not culturally relevant, safe or inclusive

☐ Cost of apps

☐ Lack of internet or device access

☐ Other (specify):

(Text)

Optional: Please elaborate

(Text)

Q10: Which factors would most influence your confidence in using these models? *

(Select up to 5 options that are most important to you)

☐ Privacy and data protection

☐ Evidence that mental health apps are clinically effective

☐ Evidence of clinical safety

☐ Ease of use and access

☐ Technical stability

☐ Cultural safety and inclusiveness

☐ Clear information about how personal information is used

☐ Recommendation by trusted organizations or professionals

☐ Other (specify):

(Text)

Optional: Please elaborate

(Text)

Q11: Have you seen examples of mental health app libraries or gateways that worked well?

☐ Yes

☐ No

If yes:

→ Please briefly describe

(Text)

Q12: Have you seen these kinds of models change or disappear over time?

☐ Yes

☐ No

If yes:

→ What factors contributed to this?

(Text)

Q13: Where would you look for mental health apps, digital mental health tools or related support?

(Select all that apply) *

☐ Search engines

☐ Recommendations from health or other trusted professionals

☐ App stores

☐ Social media

☐ Friends or family

☐ Online communities

☐ Health organization websites

☐ Other (specify):

(Text)

Future Considerations

Q14: How are broader digital trends (e.g., AI, evolving user expectations) affecting the relevance of mental health app libraries or gateway models to you, if at all?

(Text)

Q15: Do you see a role for these models in helping people access mental health support over the next 3 to 5 years?

☐ Yes

☐ No

☐ Unsure

If yes → Please briefly explain your response (optional).

(Text)

Q16: What should a national organization keep in mind when considering whether to develop a mental health app library or gateway in Canada?

(Text)

Q17: Are there any materials or resources you would be willing to share (e.g., reports, articles, or websites)? (Optional)

☐ Yes

☐ No

If yes → Please provide documents, links, citations, or a brief description.

(Text / Upload button)

Follow-up and Confidentiality

Q18: May we follow up with you if clarification is needed or if additional context would help interpret your responses? *

☐ Yes

☐ No

If yes:

→ Provide name and email address here

(Text)

Q19: Would you be open to participating in a follow-up interview or discussion if this work progresses to a second phase?*

☐ Yes

☐ No

If yes:

→ Provide name and email address here

(Text)

Q20: Confidentiality*

☐ I agree that my responses may be used as anonymous examples (including quotes)

☐ I prefer that my responses be used only in summary (without quotes)

Thank you Page

This marks the end of the survey. If the participant selects the “No” option during the consent page. They will be directed here.

Appendix 4: Information on Survey Respondents

Please note this appendix has not been copy-edited.

Table 6 presents selected closed-ended findings from the 3 knowledge-user surveys conducted as part of this environmental scan. The surveys were intended to complement the literature findings by providing descriptive input, though not statistically representative, from health organizations, clinicians and other mental health providers, people with lived experience, caregivers, and advocates regarding existing mental health app libraries and gateway models. Because of the relatively small number of respondents and the use of purposive sampling, survey findings are descriptive and should not be interpreted as statistically representative or as formal comparisons between respondent groups. Where multiselect questions were used, respondents could select more than 1 response option; therefore, totals across response options may exceed the number of respondents.

Table 6: Selected Closed-Ended Findings by Respondent Group

The findings summarized reflect different survey questions by respondent group. For health organizations, they relate to factors contributing to credibility or trustworthiness and challenges adopting or supporting models. For clinicians and other providers, they relate to factors influencing recommendation and challenges using or recommending models. For people with lived experience, they relate to factors influencing use and challenges using models. Denominators reflect the number of respondents who answered each question.

Respondents were permitted to select more than 1 response option. The maximum number of responses allowed varied by question (3 to 5).

For people with lived experience, questions about factors influencing use and challenges were asked only of respondents who reported familiarity with app libraries or gateway models (n = 5).