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Abstract

Background

The collection, storage, and use of data are essential elements for advancing mental health services, clinical care, and policy. Data governance is the framework of rules and processes that guide decisions impacting how data are stored, accessed, and controlled, and is foundational for the ethical management of data overall. As digital data practices grow, governance models must reflect the values of different communities. This scoping review aims to (1) understand the values and principles that are important to youth in the governance of their mental health data, (2) identify existing implementations of co-created frameworks of values and principles for data governance, and (3) explore opportunities for integration with existing data governance frameworks.

Methods

The recommended scoping review methodology by Arksey and O’Malley, alongside updated methodology by Peters et al., was followed. We searched four databases (Scopus, MEDLINE (Ovid), Embase (Ovid), and APA PsycINFO (Ovid)) on June 7, 2024 for records from 2013 to present.

Results

Of 23 included studies, only four explicitly explored youths’ preferences for mental health data use and co-creation of governance frameworks. None focused specifically on youths’ data-related values, and few addressed issues of data governance. Important themes emerged around privacy, trust, transparency, and control.

Conclusion

Findings suggest that urgent attention is required to improve data governance for youth receiving mental health services. In particular, the collaborative development of values and principles for governance frameworks of youth mental health data should be central when developing youth-centered services that collect and use these data.

Keywords

Data governance data ethics values youth mental health integrated youth services health systems

Introduction

The collection, storage, and use of data presents an important opportunity to help address the mental health difficulties experienced by youth and the communities they belong to. The appropriate use of accurate, high-quality data may strengthen researchers’ understanding about the mental health challenges faced by youth, and help support youth and their service providers and caregivers make meaningfully informed decisions to navigate those challenges. Moreover, if done effectively, processes of data collection and use can facilitate the development and evaluation of improved health systems to support youth. For example, in measurement-based care, data from patient-reported outcome measures not only informs the interaction between service providers and youth, but also serve as important sources of data that can be collected and interpreted to evaluate the delivery of a service overall.

Data governance “establishes the broad policies for access, management, and permissible uses of data; identifies the methods and procedures necessary for the stewardship [of data]; and establishes the qualifications of those who would use the data and the conditions under which data access can be granted.”¹^{(pp1444–1445)} Evidence suggests that including “interest holders”² in the creation, development, and implementation of their own governance frameworks is essential towards ensuring that equity-focused safeguards that determine how data are collected, stored, and used are realized.³ Despite this, very little is known about the values and principles that are important to youth regarding the governance of their own data, particularly their health data.⁴ For our purposes, values are qualities that are deemed worthwhile or desirable for individuals or groups,⁵ while principles are more often related to guiding actions about the right thing to do.^6,7

Here, we follow Leonelli's⁸ view of data “as any product of research activities, ranging from artifacts such as photographs to symbols such as letters or numbers, which is collected, stored and disseminated in order to be used as evidence for knowledge claims” (p. 817). Data is a valuable resource that needs to be ethically managed, or it risks being exploited. Our analysis recognizes data as a relational good and reinforces the belief that data governance should be grounded in equity considerations that reflect its value to communities and society.⁹

Literature review

Globally, the misuse and mismanagement of data has contributed to eroding public trust in open and honest data sharing.^3,10 Meaningful participatory data governance practices can empower interest holders to make informed decisions about how their data are stored and managed. Participatory data governance practices, in turn, enhance the use of these data and mitigate risks associated with its mismanagement.¹¹ Participatory governance practices are important due to historical and ongoing unethical data extraction and maintenance practices that have contributed directly to the oppression of different communities. For example, Indigenous communities in Canada, including youth, have faced exploitative data extraction practices and had their data misused with tragic, long-lasting consequences.¹² In response to this, First Nations, Inuit, and Métis communities across Canada and outside of North America have articulated governance principles and mechanisms to safeguard and control their own data.^13–16

Frameworks such as the OCAP^® principles (Ownership, Control, Access, and Possession) and the CARE principles (Collective Benefit, Authority to Control, Responsibility, and Ethics) for Indigenous Data Governance, provide concrete approaches that emphasize Indigenous control over data collection and use.^17,18 Specific initiatives, such as the First Nations Regional Health Survey,¹⁹ also demonstrate participatory governance in practice and include youth-specific data and involvement. These frameworks may be especially relevant for Indigenous youth, whose perspectives, rights, and futures are increasingly being centered in community-driven research and governance efforts. However, little is known about how they are used in health services data research, including how they are implemented. There is already a body of literature on participatory governance practices,^3,11 the data governance of Indigenous communities in healthcare,^13,15,20 and the participation of Indigenous youth in the co-design of digital mental health interventions.²¹ A recent scoping review identified issues of data governance, where privacy, confidentiality, and the security of user data were recognized as the most significant challenges facing digital mental health services for youth.²² Recently articulated health data governance principles prioritize equity, engagement, and participatory action as important values and approaches.^3,9 For example, the Ada Lovelace Institute discusses “participatory data stewardship” as practices that “empower people to help inform, shape and—in some instances—govern their own data.”³^(pp3–4) Little work, however, has been done to identify the preferences, values, and priorities of youth regarding the governance of their mental health data.⁴ Our review addresses this gap by examining the available literature on the creation and implementation of participatory data governance frameworks with youth in relation to their mental health data.

Current study

The motivation for the scoping review is tied to our work building the Canadian Youth Mental Health Insight Platform,²³ henceforth referred to as “Youth Insight Platform.” The Youth Insight Platform is a pan-Canadian initiative to build a state-of-the-art youth mental health data platform that can be used for research, service delivery and access, and policy. A key objective of this initiative is the co-creation of an equity focused data governance framework with youth, ensuring ethical and values-aligned management of youth mental health data. Co-creation is often described as shared planning and decision-making responsibilities between citizens and power-holders, involving true power redistribution and expertise.²⁴

Across Canada, the aim is for the framework to support knowledge development and the integration of different types of data, including qualitative and arts-based data; open data; machine learning; improved communication between school-based research; population-based cohort studies; integrated youth services; and hospital-based cohort research. This larger, collaborative project is focused on benefits to youth, their families/caregivers, communities, and the health system more broadly. In alignment with our equity commitments, we adopt Braveman and Gruskin's definition of health equity as “the absence of systematic disparities in health (or in the major social determinants of health) between social groups who have different levels of underlying social advantage/disadvantage.”²⁵^(p254) To uphold this vision, the data governance framework must reflect not only established theories and ethical standards but also the lived experiences, priorities, and values of youth and other key interest groups, including clinicians, caregivers, researchers, and policy leaders. However, despite growing interest in participatory and equity-driven approaches to data governance, there is limited synthesis of existing frameworks that prioritize youth perspectives and equity principles. In addition, while there is growing interest in participatory and equity-driven approaches to data governance, there remains a significant gap in the literature regarding how these values and principles are translated into practice. Specifically, little is known about how co-created frameworks are operationalized, implemented, or evaluated in real-world settings. This lack of evidence limits our ability to build frameworks that are both meaningful to youth and feasible within institutional and policy contexts.

To inform the development of our co-created framework, we conducted a scoping review to explore:

What is known in the existing literature about the values and principles that inform equity-focused, co-created data governance frameworks for youth mental health data, and how are they implemented?

We aimed to identify values and principles relevant to data governance that were important to youth in the studies we examined. We also explored two secondary aims. First, we examined whether the values and principles that youth identified in the included studies had also been implemented as part of how the data were managed or within a stated governance framework. Second, as noted above, substantial work on Indigenous data governance frameworks already exists; accordingly, we aimed to learn whether these studies had identified areas of overlap, used the frameworks as a resource, or attempted to collaborate with Indigenous partners in the development of new frameworks and their implementation.

Methods

Study design

Scoping reviews are appropriate for mapping literature relative to a more general question in a field, and can provide an overview of the depth and breadth of a field while also identifying gaps in the existing literature.^26,27,28 We used the scoping review methodology as outlined by Arksey and O’Malley,²⁶ alongside updated methodology by Peters et al.²⁷ and modifications proposed by Levac et al.²⁸ We used the reporting guidelines set out by JBI on Scoping Reviews²⁹) and PRISMA,³⁰ and followed the recommended six-step process from Arksey and O’Malley's²⁶ paper, including the sixth optional stage:

Identifying the research question;

Identifying relevant studies;

Study selection;

Charting the data;

Collating, summarizing, and reporting the results;

Consultation

The following sections take up each of these elements in turn as they pertain to the study. The work of the review was an iterative and collaborative process carried out within the context of the data governance working group for the Youth Insight Platform. As such, authors and reviewers regularly reported and benefited from ongoing feedback from the broader team. The main activities of identifying relevant studies, study selection, charting the data, and reporting the results were carried out jointly between the first author and a youth member of the team (TB). This youth engagement was an intentional element of the study design that ensured a youth team member was a core contributor to the main elements of the study. We did not publish a protocol for nor register this review.

Identifying the research question

As mentioned, the authors belong to a broader working group on data governance for the Youth Insight Platform. This is a diverse interdisciplinary group that includes service providers, youth engagement specialists, Indigenous research specialists, artificial intelligence (AI) and data systems specialists, and researchers from a variety of disciplines. These include bioethics, occupational therapy, psychiatry, psychology, sociology, and philosophy. The research question was determined and refined with input from the working group as a whole.

Identifying the relevant studies

Our search strategy was developed with the close guidance of a Librarian at McGill University (GG). First, one reviewer (SRD) carried out a preliminary search of two databases (SCOPUS and PubMed) and Google Scholar to identify initial search terms. They submitted this preliminary search to the McGill University Librarian for consultation, who then helped refine a search strategy and identify additional search terms. The search strategy was developed around core concepts of “Data”; “Mental Health”; “Governance”; “Collaboration”; and “Youth.” The reviewer piloted the search strategy and, in consultation with this research's co-authors, finalized its keywords. The search query was limited to items beginning in 2013 and executed in SCOPUS, PsycINFO, Medline, and Embase. Search results were structured and managed through Covidence. The search strategy is included in the Supplemental material 1. The searches were executed on June 7, 2024 and the review process was undertaken from June to August 2024.

Reviewers also manually searched the included studies for relevant sources in their bibliographies and conducted internet searches to identify organizations that may have issued relevant materials. A search of Google Scholar limited to the first 200 entries was conducted to identify additional sources.

The first round of title and abstract screening was carried out by two reviewers (SRD, TB), meeting weekly with a third reviewer (SB) to resolve conflicts. The first round of screening yielded 64 full-text articles to be assessed for eligibility. Full-text review followed a similar process, with two primary reviewers and a third reviewer to resolve conflicts, which yielded a final set of 23 articles to be included in the final review. The process is illustrated in Figure 1. The two primary reviewers conducted a manual search of the 23 selected source's bibliographies, as well as structured Google searches, to identify possible grey literature. No new sources were identified through this process.

Figure 1.

PRISMA diagram of included studies.

Study selection

We focused on mental health services that collect and store young people's data. Our inclusion criteria regarding the target intervention was developed iteratively. While our original area of concern was mental health services delivered at integrated youth services³¹ and digital mental health services, we broadened our inclusion criteria over the review process to include studies that have a collaborative component or had directly elicited youth preferences. Specifically, we revisited all previously screened titles and abstracts to ensure that potentially relevant studies that may have been excluded under the original, narrower criteria were reassessed under the updated criteria. This step was essential to maintain the comprehensiveness and integrity of our review. Therefore, to be included, studies had to possess some element of collaboration with youth, involve the collection and storage of youth mental health data, and address the preferences of youth regarding data governance. Preferences about data sharing emerged either as part or target of a study, or when youth were asked questions that related to how their data are shared or handled in mental health services.

We were interested in learning about the values, principles, and preferences that youth have endorsed or that have been identified by researchers in collaboration with youth. For exploratory purposes, we examined whether these values, principles, and/or guidelines were implemented, and if existing Indigenous frameworks had been considered by the included studies.

Given the relatively new area of data governance research, our inclusion criteria were meant to be broadly inclusive to capture as many sources as possible that were related to our question. Therefore, we included a variety of research projects, including observational studies, qualitative studies, mixed-methods studies, literature reviews, and case studies. We also included a search of relevant grey literature on the topic. There was no search of preprint servers. We only excluded studies if they were Masters or PhD thesis dissertations. Finally, we included literature published in English or French, regardless of the country of origin.

While the target demographic for the field of youth mental health is usually 12 to 25,³² our goal was to be maximally inclusive in order to identify as many relevant studies as possible. Towards this aim, we broadened the age range to include studies with participants between the ages 10 to 30.

Part of our objective was to identify participatory data governance frameworks by Indigenous youth, including how identified population-wide approaches align with existing frameworks for Indigenous data governance. For this specific analysis, we follow Povey et al.'s inclusion criteria for a recent scoping review on participatory design for mental health interventions for Indigenous youth. They focus on Indigenous youth, “from Australia (Aboriginal and Torres Strait Islander), New Zealand (Maori), Canada (Inuit, Métis, First Nations people), and the US. (First Nations People),” which we adopted.

Charting the data

We followed PRISMA scoping review reporting guidelines,³⁰ omitting a critical appraisal of the evidence as it was not pertinent to the review. We recorded the relevant information in a data extraction sheet that included important information on each of the identified sources: the authors; year of publication; location of the study; type of study (e.g. qualitative, mixed methods, etc.); number and age range of participants; and identified data governance issues. A chart with data on the included studies is included in Table 2 of the Supplemental materials.

Collating, summarizing, and reporting the results

Through an iterative process of reviewing the sources, we identified key themes that touched on values and principles relevant to the management and storage of youth's mental health data. These themes and related sources are presented in Table 3 of the Supplemental materials, including the number of mentions for each theme. We also coded each study as “low,” “medium,” or “high” depending on the degree of collaboration with youth. We expand on the meaning of these broad categories in the Results section, and include a table to summarize this aspect of the results (Table 1).

Table 1.

Degrees of collaboration in our data were ranked from low to high following an adapted ladder of participation in mental health from Slay and Stephens.⁴¹

Chart category	Degree of empowerment	Research activity
Low	Doing to	InformingEducatingCoercing
Medium	Doing for	EngagingConsulting
High	Doing with	Co-producingCo-designingCo-creating

Consultation

Finally, consultation was done with the working group on an ongoing basis, resulting in an iterative review and analysis process and input on the draft manuscript. This meant that the research question, search strategy, results, and draft manuscript were discussed at regular timepoints with the working group at large. At the final stage, working group members were able to provide comments and contribute to the draft of the paper. As mentioned, the working group included members of diverse interest holder groups relevant to the study.

Results

Our search retrieved a total of 6267 sources. This includes 200 sources that were preliminarily pulled from Scopus during the pilot of the search strategy. Covidence filtered 1778 duplicates, leaving a total of 4519 for title and abstract screening. Sixty-four full-text articles were assessed for eligibility, of which a final 23 sources were identified to meet the eligibility for data extraction in the final review. Figure 1 shows the reasons for study exclusion. Table 1 includes the data that was extracted from the included studies. Table 2 in the Supplemental materials offers further details on the governance themes that emerged from the studies as described in this section.

The identified studies were from Australia (n = 6), Canada (n = 2), Colombia (n = 1), Germany (n = 1), Ireland (n = 1), New Zealand (n = 1), the UK (n = 9), and the USA (n = 1). The MindKind study⁴ was an international collaboration between teams in India, South Africa, and the UK. Publication dates ranged from 2015 to 2024, and these studies’ participants were aged 12 to 30. Overall, our findings reveal a gap in the literature regarding the co-creation of data governance frameworks with youth. Most studies did not describe collaborative efforts towards shaping and implementing data governance frameworks in their research process. While many of the originally identified studies had technology or data components as part of a collaborative approach (e.g. e-health or mental health service delivery), most consistently stopped short of exploring what would happen to a dataset once it was collected.

To our knowledge, the MindKind initiative^4,33 is the only project that both approached data use and storage as issues of data governance and aimed to co-create a data governance framework that reflects the values of youth. One other study co-developed a privacy framework with youth, which is closely related.³⁴ However, only the MindKind study conceptualized the issue as both related to questions of data governance and linked them to youth-identified values and principles. While the terms “values” and “principles” came up in some of the studies (n = 8), they were the primary focus of investigation only in the MindKind initiative.^4,33

When studies did elicit preferences of youth data governance, they did not address or link them to values or principles. Towards addressing one of our secondary aims, we identified only three studies^35–37 that indicated whether they had partly implemented some of the findings of their study. In answer to our other secondary aim, one Australian study included Aboriginal and Torres Strait Islander participants, but did not clarify how their participants’ input was used to inform the project's results.³⁵ A second study from Canada was the only study to explore data partnerships, including for mental health data, with an Métis community in a needs assessment study,³⁸ but it was not clear which input came from youth specifically. The researchers in the study emphasize the importance of data sovereignty for Indigenous communities and OCAP^® principles, but do not discuss or distinguish them from other governance principles already developed by Métis and Inuit communities.^14,16 This represents a further gap in our findings. OCAP^® principles are reflective of First Nations data governance principles, however, they may not be reflective of Inuit or Métis-specific data governance, which was not discussed by any of the included studies.

Overall, identified preferences and concepts relating to the values and principles that may be important to youth emerged in studies as part of a broader discussion around the use of technology in mental healthcare delivery. They also emerged as part of discussions about the role of social media; either as a dimension of youth's mental health or because social media data and youth's attitudes about social media might be the subject of research. Some insights emerged only peripherally to the discussion, for example, as barriers to use of technology (e.g. a perceived lack of privacy). Themes related to values and principles that emerged from youth preferences identified across the included studies included co-creation, privacy, lack of concern, trust, transparency, and control. These themes are discussed in more detail below.

Co-creation

Degrees of collaboration between youth and adult researchers can range from superficial and tokenistic to in-depth, participatory, and empowering.³⁹ We sought to map the degree of collaboration adopted by the identified studies. In our study, we understood “co-creation” as a broader construct that also encompasses related but distinct terms, such as “co-production” and “co-design.”⁴⁰ We ranked the included studies along a gradient of “low,” “medium,” and “high” to indicate the degree of collaboration with youth. This is illustrated in Table 1. Here, we also group degrees of collaboration along three categories of engagement ranging in their degree of collaboration from most coercive to most empowering.⁴¹

A significant number of studies had a high level of collaboration (n = 10), a substantial number had a low level of collaboration (n = 8), while two fell somewhere in between. Importantly, while there were a number of studies with a high degree of collaboration, only a few were co-creation studies about youth's preferences or views regarding data governance in particular. Most of the studies were collaborations that had data components, where preferences around issues like privacy passively emerged during the research process.

Privacy

Privacy emerged as a key and overarching concern, particularly towards data sharing, barriers to data sharing, and the ways in which youth's data are used after sharing. Youth stressed the importance of being able to opt for anonymity^4,33,36^42–45 and worried about the vulnerability of their data, for instance, whether it could be corrupted or breached.³³ The type of data being collected and shared also made a difference to some youth, as there was a higher reluctance to share social media data over mental health data.⁴⁶ This was related to a concern about clinicians judging youth for how they use the internet.⁴⁶ Other concerns about privacy included specific fears of being tracked⁴⁷ or involuntarily put in a hospital due to privacy being breached,⁴⁷ a more general fear that data may be misused,⁴⁷ and a fear of potential negative impacts on therapeutic relationships due to privacy being breached.⁴⁷

Lack of concern

Some studies identified an overall lack of interest in how data is being used.⁴⁸ Youth acknowledged that personal data is often collected without consent in day-to-day life and were resigned to this as a part of data sharing.⁴⁹ Some youth did not demonstrate specific concern for how their data would be used or handled, so long as users were compliant with international cybersecurity standards.⁵⁰ For example, one study's young participants indicated no privacy concerns regarding AI use in apps.⁴⁹ Sometimes, convenience and ease of use was traded off against safety or privacy concerns; indeed, youth in one study supported the use of geolocation to save time collecting demographic information.⁵⁰

Trust

In some studies, youth emphasized that their willingness to share data depended on the intentions and individuals or groups hoping to use their data. For example, youth indicated they were comfortable sharing data with clinicians^35,46 and researchers, but expressed concern when data would be used for-profit or potentially sold to third parties.^33,37 In one study, youth expressed more trust for non-commercial providers⁴⁹ and a preference that data be used to benefit others, not for-profit.⁴ Again, depending on the type of data, youth also expressed reluctance to share it with supportive others,³⁵ particularly if the data would be used during a mental health consultation.⁴⁶ Relatedly, the acceptability of data collection seemed to depend on the topic being investigated.⁵¹ In one study, trust increased if data sharing was encouraged by a trusted source, such as a school staff member or healthcare provider.³⁶ Another study identified skepticism about the ability of AI to help or diagnose mental health issues.⁴⁹

Transparency

There was a strong emphasis on transparency in data use guidelines and policies. Youth wanted the information necessary to understand how their data would be used and indicated that privacy policies should have less jargon and be presented upfront.^34–37^,42,43,45 Some youth suggested that they should not be required (in the case of mental health apps, for instance) to create an account using email in order to access resources or view privacy policies.^34,42 Transparency preferences included youth's desire for data findings to be free to access and easy to understand.^4,33 Two studies discussed youth's considerations about which data is worth collecting, depending on whether it is relevant, beneficial, or private.^51,52

Control

In several studies, youth emphasized that there should be clearer control over information sharing, and that websites or apps should include multiple options for data privacy, with an emphasis on ownership.⁴^33–35^,44,45,49,51 Two studies identified a preference for users to be reminded of privacy policies and have the ability to change their privacy settings at any time.^34,43 One study discussed whether commercial companies should be required to pay to access data,⁴ while another study emphasized that youth should be part of discussions where data access and governance decisions are made.³³ Accountability emerged as an important consideration in another study, particularly when conflicting views about the efficacy of contracts to hold users liable arose.⁴

Discussion

In this scoping review, we explored data governance frameworks that are both for youth mental health data and co-created with youth. We aimed to identify important governance-related values and principles. We also worked to identify studies examining the intersection between the values and principles important to Indigenous data governance. Finally, we hoped to find co-created implementation strategies for such governance frameworks by examining how data governance values and principles have been operationalized into actionable components within youth mental healthcare frameworks.

Our results reveal a significant gap in the literature in all these dimensions. Further research is needed to conceptualize the ethical dimensions of data collection and use, and to better understand youth's data preferences. This includes collaboratively exploring relevant ethical concepts in order to have meaningful discussions about what is at stake with mental health data sharing and use in healthcare contexts. As noted in the Introduction, interest holders (e.g. government, funders) view data as a new frontier of resource extraction, and there is a long history of data misuse in settler societies and beyond. While concepts such as privacy, transparency, and control emerged as important towards ethical, youth engaged data governance, it is critical to understand why certain data-related concepts are important to youth and how they should be operationalized. For this reason, conceptualizing youth's data governance preferences as values and linking them to specific principles may be helpful. We discuss this further in the Recommendations section.

Outside of research related to the MindKind initiative,^4,33 no study discussed issues central to data governance as issues of data governance specifically. Just like broaching ethical issues without ethical concepts leaves out important ways in which to discuss these issues, referencing governance issues without the conceptual background of data governance frameworks and issues also leaves out important ways in which these issues can be discussed. The MindKind study is unique in its efforts to develop materials that concretely explain data governance alongside its strategy to elicit youth preferences on data governance choices.⁴

As mentioned above, many youth's data governance preferences emerged around privacy; for instance, concerns with data sharing with others, including their providers.^4,33,36^42–47 While privacy is no doubt a central concern in data governance, it is by no means the only issue, as some of the other identified themes suggest (e.g. trust, transparency). Approaching work around data governance with a broader conceptual suite would allow for richer exchanges between researchers and youth. For example, equity and inclusion may be an important value in the case of data governance overall,^3,9 but was not explicitly discussed in any of the reviewed studies.

Moreover, while many young participants expressed worry or fear about different aspects of how their data would be used or stored,⁴⁷ some also expressed an overall lack of concern or resignation at the idea that their data was being shared or stored without their input.^48–50 This stands in stark contrast to the view of data extraction by different actors that we have alluded to.⁹ Providing participants with broader knowledge about data governance and explaining what is at stake ahead of discussions may significantly improve our understanding of what youth value regarding their data. For example, the MindKind study provided extensive background materials for participants in order to inform the discussions to be held afterwards.⁴

It is notable that only one study³⁸ discussed its potential overlap with existing Indigenous governance frameworks^13–16 as part of a collaboration on youth mental health to embed digital platforms in partnership with Indigenous communities. As governance frameworks for youth's data emerge, research must strive to understand how their findings might interact with already existing frameworks. This includes the ways in which the misuse of data has harmed Indigenous communities in the past.

Finally, it is worth stressing that we rejected many studies that were collaborations with youth and included a data component but stopped short of considering what would happen to the data once gathered. This suggests that many studies do not consider data governance as part of their study design, nor ask youth about their preferences regarding their data following its collection. We suggest that the ethics of data governance and the preferences of youth regarding their data are at least as important as collaborating on other elements of technology-based interventions for youth in mental health. Moreover, few studies had a high level of collaboration about data governance preferences themselves. In other words, most youth preferences around data governance emerged as part of collaborative projects, but the collaboration was not about the governance framework itself. With concerns about privacy and transparency emerging across youth's discussions about technology, there is a clear and urgent need for further research on youth's data governance preferences to be done.

Limitations

Many of our findings emerged peripherally as part of broader collaborative projects not necessarily focused on data governance or data-related concerns. Furthermore, it was not clear in the two studies^35,38 that involved Indigenous participants whether the findings emerged directly from their youth participants. While several of the papers we reviewed included collaboration as part of their methodology, the depth of collaboration varied widely.

Recommendations

The harnessing of data presents enormous opportunities to enhance service delivery, inform research and policymaking, and increase youth's participation regarding their mental health information towards improving their outcomes. However, data must be governed and stewarded according to the principles and values of the people to whom this data belongs. This is essential to mitigate the possible harms associated with data misuse, and to foster the trust and empowerment of those sharing their data. We urge researchers working in technology-driven youth mental health interventions, frameworks, and solutions to consider the importance of data governance as an essential feature of their work. We recommend distinguishing between values and principles and setting up robust co-creation processes to both identify and define what is meant by different values and principles, and to operationalize them into actionable methodologies for how data is managed and stored.

By values, we mean broadly what matters to an individual or a group—what they care about and view as good or desirable.⁵ On the other hand, operationalizing these into concrete principles can help identify how we should act in relation to a value or set of values. In other words, principles are often thought of in ethics as “action guiding”^6,7 and concern the right thing to do in relation to what we identify as good (i.e. our value/s).

We stress this distinction to lay out a research agenda for the collaborative development of data governance frameworks with youth. Eliciting youth's data-related preferences is one way of learning about the values they may have regarding the governance of their data.^4,33 However, youth's values should be collaboratively explored over time to discern what each value means to different groups, and how they may apply in different contexts. As we note in our discussion of “co-creation” above, degrees of collaboration can range by the level of empowerment of participants. This is illustrated earlier in Table 1. The notions of “doing to,” “doing for,” and “doing with” are a useful heuristic for critically assessing the suitability of a methodology. We urge researchers to choose methods which are genuinely collaborative, and which are empowering of participants. The MindKind study⁴ is an excellent example of such methods.

Finally, to strengthen future clinical and research initiatives, it is essential to co-develop and clearly operationalize data governance values and principles with youth interest groups. Without this foundational step, teams lack a coherent basis for interpreting value-based disagreements, resolving conflicts, or making transparent decisions about data use throughout the research lifecycle. Although our study identifies what youth say matters to them regarding their data, these insights cannot be meaningfully incorporated into practice unless they are translated into explicit, actionable principles. Likewise, eliciting youth preferences about data sharing in the absence of an articulated value framework risks producing guidance that is difficult to interpret or prioritize—particularly when preferences conflict or evolve over time. We therefore recommend that clinical and research teams engage youth early and collaboratively to define the core values that should guide data governance, and to translate these values into concrete criteria for decision-making. This approach will provide a defensible and transparent structure for navigating trade-offs, ensuring that youth perspectives meaningfully shape data practices.

Conclusion

Our review aimed to map the literature on what matters to youth regarding their mental health data and how it is governed. What emerged was a gap in the literature about this topic, with only a few studies directly addressing the question. Data governance is a central concern as the use of technology, e-health, AI, and nationwide data platforms like the Youth Insight Platform are implemented. Data governance is a solution to a problem about the ethics of data, and the ethics of data require an elucidation of the values and principles that are relevant in each context. Collaboratively investigating values and principles for data governance with youth is therefore an essential aspect of any mental health intervention that collects and houses youth's health data. Our review reveals the broad practice of engaging in technology-driven solutions for mental health without due attention to the ethics of data collection, storage, and management. Finally, this work underscores an important opportunity for researchers to contribute to the ethical use of data and the development of health systems more broadly.

Supplemental Material

sj-docx-1-dhj-10.1177_20552076251404219 - Supplemental material for Co-created data governance frameworks for youth mental healthcare: Values, principles, and implementation—A scoping review

Supplemental material, sj-docx-1-dhj-10.1177_20552076251404219 for Co-created data governance frameworks for youth mental healthcare: Values, principles, and implementation—A scoping review by Sebastian Rodriguez Duque, Eran Tal, Taite Beggs, Genevieve Gore, Mary Hanna, Natalie Beedle, Georgina Dimitropoulos, Daniel Felsky, Srividya N Iyer, Nicole Kozloff, David Rotenberg, Amber-Lee Varadi, , Sean Hill, Jo Henderson and Skye Barbic in DIGITAL HEALTH

Supplemental Material

sj-docx-2-dhj-10.1177_20552076251404219 - Supplemental material for Co-created data governance frameworks for youth mental healthcare: Values, principles, and implementation—A scoping review

Supplemental material, sj-docx-2-dhj-10.1177_20552076251404219 for Co-created data governance frameworks for youth mental healthcare: Values, principles, and implementation—A scoping review by Sebastian Rodriguez Duque, Eran Tal, Taite Beggs, Genevieve Gore, Mary Hanna, Natalie Beedle, Georgina Dimitropoulos, Daniel Felsky, Srividya N Iyer, Nicole Kozloff, David Rotenberg, Amber-Lee Varadi, , Sean Hill, Jo Henderson and Skye Barbic in DIGITAL HEALTH

Supplemental Material

sj-docx-3-dhj-10.1177_20552076251404219 - Supplemental material for Co-created data governance frameworks for youth mental healthcare: Values, principles, and implementation—A scoping review

Supplemental material, sj-docx-3-dhj-10.1177_20552076251404219 for Co-created data governance frameworks for youth mental healthcare: Values, principles, and implementation—A scoping review by Sebastian Rodriguez Duque, Eran Tal, Taite Beggs, Genevieve Gore, Mary Hanna, Natalie Beedle, Georgina Dimitropoulos, Daniel Felsky, Srividya N Iyer, Nicole Kozloff, David Rotenberg, Amber-Lee Varadi, , Sean Hill, Jo Henderson and Skye Barbic in DIGITAL HEALTH

Supplemental Material

sj-docx-4-dhj-10.1177_20552076251404219 - Supplemental material for Co-created data governance frameworks for youth mental healthcare: Values, principles, and implementation—A scoping review

Supplemental material, sj-docx-4-dhj-10.1177_20552076251404219 for Co-created data governance frameworks for youth mental healthcare: Values, principles, and implementation—A scoping review by Sebastian Rodriguez Duque, Eran Tal, Taite Beggs, Genevieve Gore, Mary Hanna, Natalie Beedle, Georgina Dimitropoulos, Daniel Felsky, Srividya N Iyer, Nicole Kozloff, David Rotenberg, Amber-Lee Varadi, , Sean Hill, Jo Henderson and Skye Barbic in DIGITAL HEALTH

Footnotes

List of abbreviation

Acknowledgments

Respecting data governance in health is essential to this work, particularly in recognizing the rights of Indigenous Peoples to control, access, and steward data about their communities. As such, we acknowledge that our work took place on the traditional and ancestral territories of Indigenous Peoples across Canada, who have stewarded these lands since time immemorial. We are committed to upholding principles of ethical data governance by respectfully engaging with Indigenous knowledge systems and supporting Indigenous data sovereignty throughout our work.

ORCID iDs

Georgina Dimitropoulos

Nicole Kozloff

Skye Barbic

Author contributions

SDR conceptualized the study, wrote the main manuscript, led the data collection and analysis. ET conceptualized the study and guided the methodology. TB collected the data and supported data analysis and manuscript writing. SH, JH, and SB conceptualized the study and oversaw all project activities including manuscript writing. All authors reviewed the manuscript.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Funding for this review was received from Brain Canada Foundation.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Availability of data and materials

The final dataset used for analysis will be made available upon reasonable request and in accordance with institutional and publisher guidelines.

Supplemental material

Supplemental material for this article is available online.

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Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

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Co-created data governance frameworks for youth mental healthcare: Values,principles,and implementation—A scoping review

Abstract

Background

Methods

Results

Conclusion

Keywords

Introduction

Literature review

Current study

Methods

Study design

Identifying the research question

Identifying the relevant studies

Study selection

Charting the data

Collating, summarizing, and reporting the results

Consultation

Results

Co-creation

Privacy

Lack of concern

Trust

Transparency

Control

Discussion

Limitations

Recommendations

Conclusion

Supplemental Material

sj-docx-1-dhj-10.1177_20552076251404219 - Supplemental material for Co-created data governance frameworks for youth mental healthcare: Values, principles, and implementation—A scoping review

Supplemental Material

sj-docx-2-dhj-10.1177_20552076251404219 - Supplemental material for Co-created data governance frameworks for youth mental healthcare: Values, principles, and implementation—A scoping review

Supplemental Material

sj-docx-3-dhj-10.1177_20552076251404219 - Supplemental material for Co-created data governance frameworks for youth mental healthcare: Values, principles, and implementation—A scoping review

Supplemental Material

sj-docx-4-dhj-10.1177_20552076251404219 - Supplemental material for Co-created data governance frameworks for youth mental healthcare: Values, principles, and implementation—A scoping review

Footnotes

List of abbreviation

Acknowledgments

ORCID iDs

Author contributions

Funding

Declaration of conflicting interests

Availability of data and materials

Supplemental material

References

Supplementary Material