Role of boundary objects in identifying cross-sectoral promotion strategies for youth mental well-being in Stockholm municipalities

Role of boundary objects in identifying cross-sectoral promotion strategies for youth mental well-being in Stockholm municipalities | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Role of boundary objects in identifying cross-sectoral promotion strategies for youth mental well-being in Stockholm municipalities Harsha Krishna, Eswaran Subrahmanian, Adam S Darwich, Sebastiaan Meijer This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7701657/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Promoting youth well-being requires collaboration between various departments within a municipality that track socioeconomic, educational, environmental, and health factors. This makes the identification of strategies for promoting well-being, as well as the observation of progress and effects, challenging. It requires different departments to collaborate and achieve a comprehensive interpretation of underlying data, which is typically bound to the various professions involved. In this article, we frame a given municipality in Stockholm as an institution comprising multiple departments with diverse expertise. Using this framing, we demonstrate that data-driven visualizations and a network-based database, fused from various datasets, serve as boundary objects, helping experts from different departments to identify promotion strategies for youth well-being, despite differences in their expertise, knowledge, and definitions of well-being. We used these visualizations in workshops with experts and analyzed their interactions. We applied this method in two separate municipalities of Stockholm, Lidingö and Nynäshamn. We examined the impact of visualizations on workshop discussions to verify the operation of visualizations produced from a fused dataset as boundary objects. We further utilize this framing to propose a set of “boundary infrastructure” for Stockholm by extending our approach to other municipalities. Humanities/Complex networks Social science/Complex networks Physical sciences/Mathematics and computing boundary objects data-driven collaborations promotion strategies youth mental well-being visualizations Figures Figure 1 Figure 2 Figure 3 Introduction Youth mental well-being depends on multiple factors, such as socioeconomic, cultural, demographic, and environmental factors. These factors determine the youth’s lived experiences; thus, monitoring them would track their ability to pursue a fulfilling life 1–3 . Stockholm, too, has municipalities that employ various departments with specific responsibilities, as well as experts to monitor and implement interventions aimed at improving the well-being of youth residing within them 4 . However, within a given municipality, different departments exhibit variations based on the resident population. These differences include youth population demographics, socioeconomic factors, and geographic location, such as their distances from activity hubs. Additionally, internal factors such as the home environment, pre-existing conditions, physical activity levels, and access to various support systems also play a role. This leads to differences in perspectives among multiple departments regarding the youth well-being promotion strategies that could be employed. These strategies necessitate collaboration among various departments and experts. It has been a challenge to communicate effectively across different expertise and experience within departments. For example, departments working with the youth include the education system through schools or the health system through health centers. At schools, educators would observe the youth in the school environment. They collect data and have experience interacting with them and their families. The health systems would also interact with youth for routine examinations and health monitoring; however, they would only do so when approached by the youth. The combined data and experience from both domains would provide a better perspective on an individual's overall health, but this would require a fusion of experiences and norms learned within each community of practice, including medicine and pedagogy. As knowledge from more departments is added, the fusion processes become complex. This has led to the development of knowledge gaps between them. To overcome these gaps and identify effective strategies for promoting youth well-being, we propose utilizing boundary objects to achieve this goal. Boundary objects are cognitive artifacts with properties of two or more participating domains. Participants collaborate by interacting through boundary objects, allowing them to communicate knowledge and experience. Thus, they enable people from different social worlds to interact by bridging the gap through the transformation of methods and representations between the participating social worlds 5 . Boundary objects can facilitate communication between different experts and departments, thereby bridging the knowledge gaps that arise from various domains of expertise to create a comprehensive view of well-being across the municipality. Figure 1 illustrates the basic mechanism of the boundary object concept. Consider an example of a construction project; blueprints function as boundary objects by bridging the knowledge between architects, contractors, and builders. Architects have expertise in design and planning, contractors in procurement, and builders in assembling materials and executing. Their common goal and collective sense-making are in the creation of a building. Boundary objects were employed in the seminal works of Leigh Star et al. 5–7 , where they studied various large institutions that brought together experts from diverse fields to achieve a common goal within their institutions. We applied the concept of boundary objects to create a set of data visualizations that incorporated data from aspects affecting youth mental well-being, using the well-being continuum model 8 . To develop these visualizations, we constructed a network database of various datasets maintained by the departments. We then employed this database to generate visualizations, which we used in workshops with experts and stakeholders from multiple departments to discuss the promotion of youth mental well-being. A detailed discussion of the data and technical setup is under review. As an institution, municipalities have a common goal across all their departments to promote youth well-being. All departments involved, with their diverse sets of expertise and communities of practice, should work together to achieve this common goal. Using this problem frame, we proposed that data-driven visualizations created from fused datasets can serve as boundary objects between different departments, facilitating the identification of strategies that promote youth well-being. These boundary object visualizations would enable experts to identify overlaps and divergences among the various areas of expertise involved in promoting youth well-being across different municipalities in Stockholm. In this paper, we analyze the operation of the visualization boundary objects within the municipalities of Lidingö and Nynäshamn. We argue that deploying this approach across multiple municipalities of Stockholm would create a data and conceptual “boundary infrastructure,” which can lead to the development of standards and norms for youth mental well-being across different municipalities of Stockholm. Besides the development of standards, the boundary information infrastructure would provide the ability to perform comprehensive and coherent analysis over time of the effectiveness of well-being interventions. Background Municipalities of Stockholm Stockholm is divided into 290 municipalities. Each municipality has various departments responsible for governing and implementing programs for its residents. Municipalities have departments for education, culture, social support, environment, sports, health, and other related areas. They may be further subdivided based on the size and complexity of each municipality. The complete mental health continuum 1 , 9 (see Fig. 2 ) identifies factors that influence youth mental well-being. Thus, departments responsible for education, environment, social support, culture, and sports must collaborate to gain insight into promoting the mental well-being of youth in that municipality. Each municipality records the status of youth mental well-being and undertakes various programs to promote it through multiple surveys. For a given municipality, improving the mental well-being of resident youths is one of the goals that brings together a subset of departments. The illustration in Fig. 2 demonstrates the parameters involved in determining an individual's overall well-being, adapted from Keyes 2013 1 . These parameters and policies are distributed to various aligned departments, with experts trained to develop, implement, and monitor their respective departments. Thus, pursuing strategies to improve youth mental well-being requires communication and collaboration between experts from different communities of practice and social worlds. Municipalities collect data and conduct surveys among their resident population by age groups. A person of 18 years is considered a legal adult. Thus, datasets and surveys are also collected based on age intervals. Each department may employ different survey instruments, methods, and protocols to collect, maintain, and disseminate data, as appropriate to its area of expertise. This demonstrates the variety of ways each dataset is developed. For example, sports clubs in Stockholm collect data to determine compensation for various clubs based on the number of children and adolescents training at each club. The data on participation is normalized to every 100,000 individuals in a given municipality 10 , 11 . The income standard for youth is based on the percentage of the youth population. Well-being promotion strategies are planned and developed at the institutional level, such as programs for schools, sports clubs, and libraries. Departments would aggregate the data collected from various locations within the municipality by population group to preserve privacy and disseminate it to the public and other departments. Structure and Composition of Boundary Objects In their seminal paper 5 , Susan Leigh Star and James R Griesemer defined boundary objects and proposed an analytical framework for their application to studies in complex institutional settings. They were employed in anthropological studies of large institutions that bring together diverse communities of practice to achieve a common goal. Boundary objects are cognitive artifacts that are plastic enough to adapt to the local needs and constraints of several parties employing them, yet robust enough to maintain a common identity across the parties' domains. Thus, their definitions are broad, flexible, and loosely structured when used in general studies, but become firmly structured at individual levels 5 , 12 . Figure 2 illustrates the different kinds of boundary objects that Star et al. identify, along with some examples. Star et al 12 later noted the following as some of the broad properties of boundary objects that were observed: 1. Intersecting social worlds or communities of practices with a common objective. Social worlds and communities of practices refer to the domains of expertise and the skills and practices defined within them. For example, if sports are a social world, coaches and athletes would be considered part of their communities, with their norms and procedures. A boundary object requires that multiple such domains intersect for a common goal. This would be the necessary condition for the use of a boundary object. 2. The material or organizational structure of different types of boundary objects, i.e., different boundary objects exist for a given set of domains. 3. The scale or granularity of the study that the boundary objects represent; for example, boundary objects may be deployed between two groups within an organization or between two groups across two cities. 4. Boundary objects would enable different groups to collaborate without requiring consensus on individual concepts, procedures, or definitions. The boundary object would allow experts from one domain to map or represent expertise from another domain in terms of their local knowledge and experience, and to accommodate missing knowledge loosely; thus, they would create norms or entities that would allow them to work across domains without altering the definitions or contradictions within their own domain. 5. The ability to use boundary objects to collaborate without consensus enables the discovery of practice structures, norms, and standards for collaborative activities among different cooperating groups. Methods We utilized a network database to create visualizations that represent positive mental health perspectives 8 . Using the parameters identified for complete mental well-being in thriving individuals, we identified the datasets and departmental experts involved in working with youth well-being. We merged the datasets using a network database to enable querying across different datasets. We created a fused graph database using the Neo4j 13 software to combine the datasets. We broadly followed the following procedure to generate our network database: Using definitions from Swedish health authorities for mental well-being, we identify datasets with relevant parameters for tracking mental well-being. The identified datasets are from various national sources and different departments within the given municipalities. A list of the data models from the selected datasets is extracted. These models are then studied to identify various methods of fusion, along with the associated trade-offs for each technique. Finally, we implemented the identified approach and checked it based on the identified criteria. A detailed explanation of the network database's selection and the approach to its development will be described in a forthcoming article. The graph database thus helped us to generate visualizations that included topics of interest to experts from multiple domains. Therefore, we were able to create visualizations, such as those showing income levels and types of family living in a municipality, as well as the performance and health of youth, using the same dataset. Informed Consent As per Sections 2 and 3 in the Swedish Act (2003:460) on ethical review of research involving humans 14 , the study is not subject to ethical review as individuals participating in our workshops are not at physical or mental risk, and no identifiable information is collected from them. As per the guidelines of good research practices stated by the Swedish Research Council 15 , we informed the experts that participation in the workshops was voluntary. The potential participants for the workshops were all adults and experts associated with one of the municipality departments, and participated as part of their professional role. We requested and obtained consent from each participant before beginning every workshop. We informed participants about the research, the responsible university, and the responsible professor. The participants were informed that only transcripts from audio recordings of discussions would be used without identifying their names, and that the focus would be solely on the content of discussions. The participants were free to withhold or withdraw their consent, as per the rules laid out in the Swedish Act 14 , the guide to ethical review and good research practices from the Swedish Research Council 15 , and the Swedish Ethical Review Agency 16 . We collaborated with the municipalities of Lidingö and Nynäshamn. We utilized their assistance to identify experts involved in youth programs. The experts included personnel from schools, such as teachers and counselors, sports coaches, and administrators from the participating municipality. We presented the generated visualizations in workshop sessions with the experts from the municipalities. A set of example visualizations and the details of individual workshops are included in Appendices 1 and 2 for reference. The visualizations in the introductory workshops were developed based on parameters of mental well-being, focusing on comprehensive mental health. They provided an overview of the current data for the youth within the municipality. For a given workshop and municipality, experts were invited by the designated project manager. The invitation list was based on the role in collecting data, working with youth, or participating in health promotion programs. The invitees included educators, coaches, counselors, social workers, and policymakers. The participating experts discussed both the data in the visualizations and their own professional experiences and challenges within their departments. In subsequent workshop sessions, the visualizations were modified and new ones added based on the requests of participating experts for cross-domain visualizations. The discussions also shifted towards systemic constraints in data and experiences, including how data was collected and the limitations in its interpretation. We used transcripts from all the workshop discussions to analyze whether the fused data-driven visualizations functioned as boundary objects. We mapped the discussions to identify whether they were limited to the participants’ expertise. We noted any changes to the discussion themes that reflected systemic aspects beyond the individual knowledge of the participants, indicating that discussions shifted towards institutional elements. We deduce that this observation means that the individual experts were able to map each other’s domains and move towards a common goal. The following is a quote from a joint session held between the experts from Lidingö and Nynäshamn. The text is translated from Swedish: “ Yes, we recognize a lot of what you talk about. What I was thinking about. You said something about the police. What we do widely now is that we implement a working method that is inspired by the Stockholm model which deals with early coordinated efforts and this model is called Back the child. Region Skåne and Ystad municipality have produced it and it is about the Norrmalm police, Lidingö municipality and some local regional operations in Lidingö have joined forces and will work according to this method and there will be data. So that is to say if you are now going to take from the police. But it is still yes, when the police identify perhaps a risk to a young person or a family or a child and it is then risks that do not cause a report of concern to social services, but it is that you can identify something fragile or something before and then help with stakes. But it still is. We are still in that district. We don't have well-being then. So I think that would also be an assignment for us to really think about a little more. ” In Figure 3, we illustrate our analysis method and present a tabulation of our observations regarding the effect of visualizations on discussions. We compiled findings from all workshops conducted in Lidingö, Nynäshamn, and the joint seminars. Figure 3 Method for tabulating discussion topics and themes based on visualizations Results We analyzed the transcripts of the workshop discussions. We identified the topics discussed by the participating experts and tabulated them according to the discussion topics, visualizations, and changes in the topics throughout the workshop. Tables 1, 2, and 3 illustrate the observations from the Lidingö, Nynäshamn, and the joint workshops, respectively. For each workshop session, visualizations were generated with the fused dataset based on the parameters identified for complete mental health, as shown in Figure 1. For example, the first workshop in each municipality utilized visualizations of family, education, general health, and free-time activities, along with self-reported data from youth. Subsequent workshops presented data on free-time activities, school attendance, and student performance in various subjects. This demonstrates the evolution of discussion topics from standard data points to a more systemic view by all participants. Thus, we examined whether the discussions aligned with the workshop theme and whether they developed into systemic issues or specialized areas. We also observed whether discussions were not focused on any single participant's expertise but rather on multiple overlapping themes. A detailed discussion of the analysis of the workshop discussions has been published 17 . To illustrate this, consider the topic of “meaningful leisure activities”, the last row in Table 1. During the main discussions with high school students from Hesby High School, located in Lidingö, on how they define well-being for themselves, the topic of meaningful leisure activities was suggested and discussed by the students. We mark an “X” against the central theme of the workshop, indicating an “O” if the discussions evolved to a related topic. We marked a “-” to suggest that the talks did not include the themes. Similarly, in the workshop session focused on the theme of “meaningful leisure activities,” representatives from leisure centers led the discussion, which evolved to address issues related to policies supporting safety, education, and prospects for youth. Table 1: Analyzing topics of discussion in Lidingö workshops. “X” discussion topics match the workshop theme, “O” discussed topics from other themes, and “- “no debate on this theme. High school students from Hesby gymnasium Officials from Lidingö Representatives from leisure centers, libraries, the sports unit, general culture, etc. Social services, (KAA), Delta Ung, leisure center, school psychologist Defining well-being X O - O Introducing all available datasets - X - O Policy, support, safety, labor, education - O O X Youth not working or studying . O - - Meaningful leisure activities O - X - Table 1 illustrates the topics discussed in each workshop conducted in Lidingö, as well as the combination of the respective participants' expertise, and Table 2 illustrates the same for the transcripts from the workshops held with participants from Nynäshamn municipality. Table 2: Analyzing topics of discussion in Nynäshamn workshops. “X” discussion topics match the workshop theme, “O” discussed topics from other themes, and “- “no debate on this theme. Youth at the leisure center in Ösmo Officials from Nynäshamn Head of Leisure Centers + representative of secondary schools Officials from the upper secondary school, Campus Nynäshamn, social administration Defining well-being X - - O Introducing all available datasets X X O Policy, support, safety, labor, education O O O X Youth not working or studying - O - Meaningful leisure activities O O O - In the joint workshop sessions, the themes were set to common topics of interest between both municipalities, and the discussion topics were tabulated as before. Table 3 illustrates the results. Table 3: Analyzing topics of discussion in joint workshops. “X” discussion topics match the workshop theme, “O” discussed topics from other themes, and “- “no debate on this theme. Student Health Nynäshamn and Lidingö Managers School and Social Administration, culture & leisure - mixed Managers School and Social Administration, culture & leisure - mixed Role of schools in promoting well-being of youth X O - Well-being of youth - data and reasoning O X O Finalization of practical work in municipalities - - X As Tables 1, 2, and 3 illustrate, for a given participant group (a column), the discussions did evolve towards one or more topics beyond the expertise of the group present (‘O’ marks). The visualization in the workshops influenced discussion topics to shift towards other systemic aspects related to improving youth mental well-being. We utilize these observations to discuss the role of visualizations from a network-based, fused dataset in demonstrating their operation as a boundary object. Discussion Estimating youth mental well-being relies on data about their subjective experiences, the perspectives of experts working with them, and information collected through monitoring. Consequently, the data and expertise required to promote youth well-being span multiple domains and necessitate a systemic understanding for the effective implementation of strategies aimed at enhancing youth well-being. While well-being is defined in a broad sense, the experiences of youth in different municipalities can vary due to demographics, socioeconomic conditions, and access to social programs. This leads to a situation where the goal of improving well-being is shared among different departments and experts within a municipality, but the approach to achieving it differs based on the data and experience of the experts with the youth. The knowledge and expertise of individuals such as educators, care providers, or social program administrators can be challenging to capture and document. Consider two groups of experts who participated in the workshops in Nynäshamn. They consisted of educators from middle and high schools, physical training coaches, and instructors. The educators interpreted promoting youth well-being as keeping the youth in school, where they would be under the supervision of teachers and educators. Individual needs can then be identified and addressed. They also noted that once a student leaves their program, their history must accompany them as they transition into adulthood to prevent future challenges in seeking help. Similarly, the sports coaches interpreted that participating in physical activities is a means to promote youth well-being. They proposed studies to understand why physical activity decreases during the transition to adulthood. Educators specialize in pedagogy and curriculum development, and similarly, sports coaches are often athletes themselves, specializing in assessing an individual’s physical abilities and designing training programs. While there are shared concepts between coaches and educators, some terms and norms may differ. Challenges due to such overlaps are intensified when additional domains are involved. Thus, aspects influencing well-being and flourishing 8,16 are monitored by different departments within a municipality with experts from various social spheres. The promotion of youth mental well-being resembles the institutions studied by Leigh-Star et al 5,6,12,19,20 . A municipality is assumed to be an institution where various experts work towards the common objective of promoting youth mental well-being. Thus, each expert’s department would represent a different “social world” with its own set of language, practices, and norms. A boundary object-based approach enables an incremental approach, where experts can use them to map data, knowledge, and experience between their respective domains. This would allow “collaboration without consensus”. We used visualizations from a fused dataset as boundary objects. The visual medium provided a conceptually neutral space in which to observe and interpret knowledge from all expert participants. It also served as a prop to elicit discussions on experiences and interpretations of the data presented. We employed this strategy to foster a systemic perspective among experts through workshops that engaged them with data on youth well-being parameters. In our workshops, we began with general visualizations related to complete well-being for youth in each municipality. The first session’s visualizations were generated based on parameters identified for complete well-being 8 . During discussion sessions, experts shared their conceptualization of well-being based on their own experience and data collected within their departments. In subsequent discussions, they identified common areas where they shared similarities, had contradictions, and complementary experiences. For the same example of coaches and educators, both worked with youth at school or in physical activities. Some strategies were effective in building team dynamics and routines. In subsequent workshops, they requested new visualizations and specific combinations of visualizations, such as identifying youth who may not be participating in any education or physical activities, youth unemployment, and registrations for higher education. Tables 1, 2, and 3 capture such deviations and mappings between different groups of audiences in Lidingö, Nynäshamn, and joint sessions, respectively. The deviations in discussion topics demonstrated aspects that were common or contradictory among the participating groups, reflecting the properties of a boundary object. The new visualizations from different departments evolved into a “horizontal” view of the system/departments involved with the youth. The boundary object-based approach acknowledges the institutional framework, the diverse communities of practice, and the shared goal of youth well-being. While boundary objects can take many forms, our approach employed visualizations. This offers us two key advantages. Data visuals tend to be neutral in their presentation of data. This enables experts to interpret observations according to their respective domains, without imposing constraints on definitions or standards. Consequently, this approach supports incremental development of concepts and inferences. Thus, policymakers and practitioners can agree on common aspects and identify differences to establish norms more quickly and accurately. It allowed us to work with the existing data infrastructure and departmental practices. Instead of developing a new model, data visualizations leverage existing infrastructure and foster discussions around current practices. By repeating this approach with all municipalities, we can eventually develop a repository of such boundary object visualizations and fused datasets to identify common aspects of youth well-being promotion across all municipalities in Sweden. This leads to a schema of domains that transitions from a fragmented to a federated state, with boundary objects bridging these social spaces and their associated languages. It is an interconnected infrastructure that is both conceptual and data-centric. This approach enables the bottom-up construction of ontologies for a specific domain of discourse within the social world of practice and composition, utilizing boundary objects, and thereby provides the basis for a “boundary infrastructure” 12 that fosters a collective, shared memory. Conclusion The results demonstrate that the visualizations had a significant impact on the discussions among the participating experts. While the talks began with the workshop theme, the visualizations prompted a shift in focus to move beyond participants’ experiences with youth to more systemic perspectives on the effects on youth well-being in their municipality. This was observed in the form of requests for further data visualizations, which required the combination or aggregation of data from various sources during the sessions. Our approach utilized a fused dataset, allowing us to generate new visualizations during discussions. We also observed that some groups were able to take a broader systemic perspective than others. In each session, it was beneficial to display visualizations of data from various functions and backgrounds to further mutual understanding of the complexity of mental health prevention and promotion. Thus, we can conclude that the visualizations generated with fused datasets functioned as a boundary object, enabling experts from a municipality to explore the promotion of youth wellbeing from a systemic perspective, thereby going beyond their own experiences and expertise. Limitations The development and management of workshops require time commitments from experts across various departments within each municipality. Additionally, close collaboration is essential to access specific datasets and to expand and integrate them with the existing network datasets. Therefore, one of the significant challenges has been securing commitments from different municipalities. We plan to overcome this by incrementally building and demonstrating the results through existing collaborations and then expanding to other municipalities via demonstrations. Declarations Acknowledgments This project was a collaboration with Petra Lindfors and Kari Trost of Stockholm University, Elisabet Rendahl from Region Stockholm, and Jenny Furstenbach from Nyfikenhet AB. The authors wish to thank the many collaborators from the municipalities of Lidingö and Nynäshamn, Sweden. Funding declaration Region Stockholm funded Harsha Krishna, Adam S Darwich, and Sebastiaan Meijer within the Research and Innovation portfolio. Competing interests The authors declare no competing interests. Availability of materials and data The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Identifying information No identifying information that could identify individuals has been used. Author Information Authors and Affiliations Harsha Krishna, Doctoral Student, Division of Health Informatics and Logistics, KTH Royal Institute of Technology, Stockholm, Sweden. [email protected] ORCID: 0000-0001-8178-9688 Eswaran Subrahmanian , Research Professor, Carnegie Mellon University, Pittsburgh, USA. [email protected] ORCID: 0000-0002-4639-627X Adam S Darwich, Associate Professor, Division of Health Informatics and Logistics, KTH Royal Institute of Technology, Stockholm, Sweden. [email protected] ORCID: 0000-0001-8218-4306 Sebastiaan Meijer, Professor, Department Head of School, Division of Health Informatics and Logistics, KTH Royal Institute of Technology, Stockholm, Sweden. [email protected] ORCID: 0000-0003-1126-3781 Contributions All authors edited the manuscript. HK performed the survey of datasets and data models and designed the network database. HK and SM designed data dashboards and conducted workshops in Swedish. ES and AD contributed to the development of the theory and observations. Corresponding author Harsha Krishna, [email protected] Room: 7116, Hälsovägen 11C, 141 57 Huddinge, Stockholm, Sweden. Ph: +46 0728447902 References Keyes, C. L. M. Promoting and Protecting Positive Mental Health: Early and Often Throughout the Lifespan. in Mental Well-Being (ed Keyes, C. L. M.) 3–28 (Springer Netherlands, Dordrecht, doi: 10.1007/978-94-007-5195-8_1 . (2013). Lindfors, P. Physiological Correlates of Mental Well-Being. in Mental Well-Being 259–274 (Springer Netherlands, doi: 10.1007/978-94-007-5195-8_12 . (2013). OECD. Measuring subjective well-being. in OECD Guidelines on Measuring Subjective Well-being 139–178 & OECD. ( (2013). 10.1787/9789264191655-7-en SKR. Begrepp inom området psykisk hälsa . (2022). https://skr.se/download/18.1c90461a17cda637a4363ded/1636721711698/PM_Begrepp-inom-omradet-psykisk-halsa-TA.pdf Star, S. L. & Griesemer, J. R. 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Krishna","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAsElEQVRIiWNgGAWjYBACAyBmZmBIkJNg4CFRi7EEG6laEmcQrcWc/ezjzwU1aekz5/ceYPxRQYQWy550M+kZx3JyZ7PxJTDznCHGYQfS2Jh52Cpy57HxGDAzthGj5fwz5s88/yrS5YBaGH/+I0bLjTQGad62nARpoBYG3gaitDxjk+btSzOc2ZZjcJjnGFEOSwM67FuyvMThM4YPf9QQoQUFHCBVwygYBaNgFIwCHAAA5nAvnWbUu+YAAAAASUVORK5CYII=","orcid":"","institution":"KTH Royal Institute of Technology","correspondingAuthor":true,"prefix":"","firstName":"Harsha","middleName":"","lastName":"Krishna","suffix":""},{"id":584319829,"identity":"2defc96e-7377-4296-8649-43e11942c34c","order_by":1,"name":"Eswaran Subrahmanian","email":"","orcid":"","institution":"Carnegie Mellon University","correspondingAuthor":false,"prefix":"","firstName":"Eswaran","middleName":"","lastName":"Subrahmanian","suffix":""},{"id":584319830,"identity":"c75f1951-f0d1-4fa9-9c7a-92e9b5198771","order_by":2,"name":"Adam S Darwich","email":"","orcid":"","institution":"KTH Royal Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Adam","middleName":"S","lastName":"Darwich","suffix":""},{"id":584319831,"identity":"2823f208-cd40-464e-8c47-e55a7685219d","order_by":3,"name":"Sebastiaan Meijer","email":"","orcid":"","institution":"KTH Royal Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Sebastiaan","middleName":"","lastName":"Meijer","suffix":""}],"badges":[],"createdAt":"2025-09-24 09:10:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7701657/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7701657/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101870551,"identity":"ac6f7e09-2884-4490-a4cd-77e41ff28b9e","added_by":"auto","created_at":"2026-02-04 13:12:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":219617,"visible":true,"origin":"","legend":"\u003cp\u003eParameters involved in determining youth well-being.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7701657/v1/7a994d8bdbd92a99d7507ec5.png"},{"id":101870506,"identity":"43597f17-3922-4655-be35-276dc9fa8986","added_by":"auto","created_at":"2026-02-04 13:12:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":179788,"visible":true,"origin":"","legend":"\u003cp\u003eTypes of boundary objects based on their contents, adapted from\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7701657/v1/e4c9b50f72b93d38baecaec7.png"},{"id":101870441,"identity":"7e881d40-39d2-4265-9793-05185ccbf398","added_by":"auto","created_at":"2026-02-04 13:11:53","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1073074,"visible":true,"origin":"","legend":"\u003cp\u003eMethod for tabulating discussion topics and themes based on visualizations\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7701657/v1/80bba981f739ad305f8473c2.jpeg"},{"id":101870734,"identity":"563e05e8-a87d-4a6c-a552-a68ba0b98425","added_by":"auto","created_at":"2026-02-04 13:13:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1898883,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7701657/v1/24dca682-a94f-4b67-9307-ab897505f753.pdf"},{"id":101870438,"identity":"6a0ffbdd-c8ff-4874-923f-6883dedd2654","added_by":"auto","created_at":"2026-02-04 13:11:52","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":698532,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7701657/v1/a73d44bb74e3a6d1801d38bd.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Role of boundary objects in identifying cross-sectoral promotion strategies for youth mental well-being in Stockholm municipalities","fulltext":[{"header":"Introduction","content":"\u003cp\u003eYouth mental well-being depends on multiple factors, such as socioeconomic, cultural, demographic, and environmental factors. These factors determine the youth’s lived experiences; thus, monitoring them would track their ability to pursue a fulfilling life\u003csup\u003e1–3\u003c/sup\u003e. Stockholm, too, has municipalities that employ various departments with specific responsibilities, as well as experts to monitor and implement interventions aimed at improving the well-being of youth residing within them\u003csup\u003e4\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, within a given municipality, different departments exhibit variations based on the resident population. These differences include youth population demographics, socioeconomic factors, and geographic location, such as their distances from activity hubs. Additionally, internal factors such as the home environment, pre-existing conditions, physical activity levels, and access to various support systems also play a role. This leads to differences in perspectives among multiple departments regarding the youth well-being promotion strategies that could be employed. These strategies necessitate collaboration among various departments and experts. It has been a challenge to communicate effectively across different expertise and experience within departments.\u003c/p\u003e\n\u003cp\u003eFor example, departments working with the youth include the education system through schools or the health system through health centers. At schools, educators would observe the youth in the school environment. They collect data and have experience interacting with them and their families. The health systems would also interact with youth for routine examinations and health monitoring; however, they would only do so when approached by the youth. The combined data and experience from both domains would provide a better perspective on an individual's overall health, but this would require a fusion of experiences and norms learned within each community of practice, including medicine and pedagogy. As knowledge from more departments is added, the fusion processes become complex. This has led to the development of knowledge gaps between them.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo overcome these gaps and identify effective strategies for promoting youth well-being, we propose utilizing boundary objects to achieve this goal. Boundary objects are cognitive artifacts with properties of two or more participating domains. Participants collaborate by interacting through boundary objects, allowing them to communicate knowledge and experience. \u0026nbsp;Thus, they enable people from different social worlds to interact by bridging the gap through the transformation of methods and representations between the participating social worlds\u003csup\u003e5\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eBoundary objects can facilitate communication between different experts and departments, thereby bridging the knowledge gaps that arise from various domains of expertise to create a comprehensive view of well-being across the municipality. Figure 1 illustrates the basic mechanism of the boundary object concept. Consider an example of a construction project; blueprints function as boundary objects by bridging the knowledge between architects, contractors, and builders. Architects have expertise in design and planning, contractors in procurement, and builders in assembling materials and executing. Their common goal and collective sense-making are in the creation of a building.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBoundary objects were employed in the seminal works of Leigh Star et al.\u003csup\u003e5–7\u003c/sup\u003e, where they studied various large institutions that brought together experts from diverse fields to achieve a common goal within their institutions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe applied the concept of boundary objects to create a set of data visualizations that incorporated data from aspects affecting youth mental well-being, using the well-being continuum model\u003csup\u003e8\u003c/sup\u003e. To develop these visualizations, we constructed a network database of various datasets maintained by the departments. We then employed this database to generate visualizations, which we used in workshops with experts and stakeholders from multiple departments to discuss the promotion of youth mental well-being. A detailed discussion of the data and technical setup is under review.\u003c/p\u003e\n\u003cp\u003eAs an institution, municipalities have a common goal across all their departments to promote youth well-being. All departments involved, with their diverse sets of expertise and communities of practice, should work together to achieve this common goal. Using this problem frame, we proposed that data-driven visualizations created from fused datasets can serve as boundary objects between different departments, facilitating the identification of strategies that promote youth well-being. These boundary object visualizations would enable experts to identify overlaps and divergences among the various areas of expertise involved in promoting youth well-being across different municipalities in Stockholm.\u003c/p\u003e\n\u003cp\u003eIn this paper, we analyze the operation of the visualization boundary objects within the municipalities of Lidingö and Nynäshamn. We argue that deploying this approach across multiple municipalities of Stockholm would create a data and conceptual “boundary infrastructure,” which can lead to the development of standards and norms for youth mental well-being across different municipalities of Stockholm. Besides the development of standards, the boundary information infrastructure would provide the ability to perform comprehensive and coherent analysis over time of the effectiveness of well-being interventions.\u003c/p\u003e"},{"header":"Background","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eMunicipalities of Stockholm\u003c/h2\u003e \u003cp\u003eStockholm is divided into 290 municipalities. Each municipality has various departments responsible for governing and implementing programs for its residents. Municipalities have departments for education, culture, social support, environment, sports, health, and other related areas. They may be further subdivided based on the size and complexity of each municipality. The complete mental health continuum\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e (see Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) identifies factors that influence youth mental well-being. Thus, departments responsible for education, environment, social support, culture, and sports must collaborate to gain insight into promoting the mental well-being of youth in that municipality.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eEach municipality records the status of youth mental well-being and undertakes various programs to promote it through multiple surveys. For a given municipality, improving the mental well-being of resident youths is one of the goals that brings together a subset of departments. The illustration in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e demonstrates the parameters involved in determining an individual's overall well-being, adapted from Keyes 2013\u003csup\u003e1\u003c/sup\u003e. These parameters and policies are distributed to various aligned departments, with experts trained to develop, implement, and monitor their respective departments. Thus, pursuing strategies to improve youth mental well-being requires communication and collaboration between experts from different communities of practice and social worlds.\u003c/p\u003e \u003cp\u003eMunicipalities collect data and conduct surveys among their resident population by age groups. A person of 18 years is considered a legal adult. Thus, datasets and surveys are also collected based on age intervals. Each department may employ different survey instruments, methods, and protocols to collect, maintain, and disseminate data, as appropriate to its area of expertise. This demonstrates the variety of ways each dataset is developed. For example, sports clubs in Stockholm collect data to determine compensation for various clubs based on the number of children and adolescents training at each club. The data on participation is normalized to every 100,000 individuals in a given municipality\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The income standard for youth is based on the percentage of the youth population.\u003c/p\u003e \u003cp\u003eWell-being promotion strategies are planned and developed at the institutional level, such as programs for schools, sports clubs, and libraries. Departments would aggregate the data collected from various locations within the municipality by population group to preserve privacy and disseminate it to the public and other departments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStructure and Composition of Boundary Objects\u003c/h2\u003e \u003cp\u003eIn their seminal paper\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, Susan Leigh Star and James R Griesemer defined boundary objects and proposed an analytical framework for their application to studies in complex institutional settings. They were employed in anthropological studies of large institutions that bring together diverse communities of practice to achieve a common goal. Boundary objects are cognitive artifacts that are plastic enough to adapt to the local needs and constraints of several parties employing them, yet robust enough to maintain a common identity across the parties' domains. Thus, their definitions are broad, flexible, and loosely structured when used in general studies, but become firmly structured at individual levels\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates the different kinds of boundary objects that Star et al. identify, along with some examples.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eStar et al\u003csup\u003e12\u003c/sup\u003e later noted the following as some of the broad properties of boundary objects that were observed:\u003c/p\u003e \u003cp\u003e1. Intersecting social worlds or communities of practices with a common objective. Social worlds and communities of practices refer to the domains of expertise and the skills and practices defined within them. For example, if sports are a social world, coaches and athletes would be considered part of their communities, with their norms and procedures. A boundary object requires that multiple such domains intersect for a common goal. This would be the necessary condition for the use of a boundary object.\u003c/p\u003e \u003cp\u003e2. The material or organizational structure of different types of boundary objects, i.e., different boundary objects exist for a given set of domains.\u003c/p\u003e \u003cp\u003e3. The scale or granularity of the study that the boundary objects represent; for example, boundary objects may be deployed between two groups within an organization or between two groups across two cities.\u003c/p\u003e \u003cp\u003e4. Boundary objects would enable different groups to collaborate without requiring consensus on individual concepts, procedures, or definitions. The boundary object would allow experts from one domain to map or represent expertise from another domain in terms of their local knowledge and experience, and to accommodate missing knowledge loosely; thus, they would create norms or entities that would allow them to work across domains without altering the definitions or contradictions within their own domain.\u003c/p\u003e \u003cp\u003e5. The ability to use boundary objects to collaborate without consensus enables the discovery of practice structures, norms, and standards for collaborative activities among different cooperating groups.\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cp\u003eWe utilized a network database to create visualizations that represent positive mental health perspectives\u003csup\u003e8\u003c/sup\u003e. Using the parameters identified for complete mental well-being in thriving individuals, we identified the datasets and departmental experts involved in working with youth well-being. We merged the datasets using a network database to enable querying across different datasets.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe created a fused graph database using the Neo4j\u003csup\u003e13\u003c/sup\u003e software to combine the datasets. We broadly followed the following procedure to generate our network database:\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eUsing definitions from Swedish health authorities for mental well-being, we identify datasets with relevant parameters for tracking mental well-being. The identified datasets are from various national sources and different departments within the given municipalities.\u003c/li\u003e\n \u003cli\u003eA list of the data models from the selected datasets is extracted. These models are then studied to identify various methods of fusion, along with the associated trade-offs for each technique.\u003c/li\u003e\n \u003cli\u003eFinally, we implemented the identified approach and checked it based on the identified criteria.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eA detailed explanation of the network database\u0026apos;s selection and the approach to its development will be described in a forthcoming article.\u003c/p\u003e\n\u003cp\u003eThe graph database thus helped us to generate visualizations that included topics of interest to experts from multiple domains. Therefore, we were able to create visualizations, such as those showing income levels and types of family living in a municipality, as well as the performance and health of youth, using the same dataset.\u003c/p\u003e\n\u003ch2\u003eInformed Consent\u003c/h2\u003e\n\u003cp\u003eAs per Sections 2 and 3 in the Swedish Act (2003:460) on ethical review of research involving humans\u003csup\u003e14\u003c/sup\u003e, the study is not subject to ethical review as individuals participating in our workshops are not at physical or mental risk, and no identifiable information is collected from them.\u003c/p\u003e\n\u003cp\u003eAs per the guidelines of good research practices stated by the Swedish Research Council\u003csup\u003e15\u003c/sup\u003e, we informed the experts that participation in the workshops was voluntary. The potential participants for the workshops were all adults and experts associated with one of the municipality departments, and participated as part of their professional role. We requested and obtained consent from each participant before beginning every workshop. We informed participants about the research, the responsible university, and the responsible professor. The participants were informed that only transcripts from audio recordings of discussions would be used without identifying their names, and that the focus would be solely on the content of discussions. The participants were free to withhold or withdraw their consent, as per the rules laid out in the Swedish Act\u003csup\u003e14\u003c/sup\u003e, the guide to ethical review and good research practices from the Swedish Research Council\u003csup\u003e15\u003c/sup\u003e, and the Swedish Ethical Review Agency\u003csup\u003e16\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eWe collaborated with the municipalities of Liding\u0026ouml; and Nyn\u0026auml;shamn. We utilized their assistance to identify experts involved in youth programs. The experts included personnel from schools, such as teachers and counselors, sports coaches, and administrators from the participating municipality. We presented the generated visualizations in workshop sessions with the experts from the municipalities. A set of example visualizations and the details of individual workshops are included in Appendices 1 and 2 for reference.\u003c/p\u003e\n\u003cp\u003eThe visualizations in the introductory workshops were developed based on parameters of mental well-being, focusing on comprehensive mental health. They provided an overview of the current data for the youth within the municipality. For a given workshop and municipality, experts were invited by the designated project manager. The invitation list was based on the role in collecting data, working with youth, or participating in health promotion programs. The invitees included educators, coaches, counselors, social workers, and policymakers.\u003c/p\u003e\n\u003cp\u003eThe participating experts discussed both the data in the visualizations and their own professional experiences and challenges within their departments. In subsequent workshop sessions, the visualizations were modified and new ones added based on the requests of participating experts for cross-domain visualizations. The discussions also shifted towards systemic constraints in data and experiences, including how data was collected and the limitations in its interpretation.\u003c/p\u003e\n\u003cp\u003eWe used transcripts from all the workshop discussions to analyze whether the fused data-driven visualizations functioned as boundary objects. We mapped the discussions to identify whether they were limited to the participants\u0026rsquo; expertise. We noted any changes to the discussion themes that reflected systemic aspects beyond the individual knowledge of the participants, indicating that discussions shifted towards institutional elements. We deduce that this observation means that the individual experts were able to map each other\u0026rsquo;s domains and move towards a common goal.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe following is a quote from a joint session held between the experts from Liding\u0026ouml; and Nyn\u0026auml;shamn. The text is translated from Swedish:\u003c/p\u003e\n\u003cp\u003e\u0026ldquo;\u003cem\u003eYes, we recognize a lot of what you talk about. What I was thinking about. You said something about the police. What we do widely now is that we implement a working method that is inspired by the Stockholm model which deals with early coordinated efforts and this model is called Back the child. Region Sk\u0026aring;ne and Ystad municipality have produced it and it is about the Norrmalm police, Liding\u0026ouml; municipality and some local regional operations in Liding\u0026ouml; have joined forces and will work according to this method and there will be data. So that is to say if you are now going to take from the police. But it is still yes, when the police identify perhaps a risk to a young person or a family or a child and it is then risks that do not cause a report of concern to social services, but it is that you can identify something fragile or something before and then help with stakes. But it still is. We are still in that district. We don\u0026apos;t have well-being then. So I think that would also be an assignment for us to really think about a little more.\u003c/em\u003e\u0026rdquo;\u003c/p\u003e\n\u003cp\u003eIn Figure 3, we illustrate our analysis method and present a tabulation of our observations regarding the effect of visualizations on discussions. We compiled findings from all workshops conducted in Liding\u0026ouml;, Nyn\u0026auml;shamn, and the joint seminars.\u003c/p\u003e\n\u003cp\u003eFigure 3 Method for tabulating discussion topics and themes based on visualizations\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eWe analyzed the transcripts of the workshop discussions. We identified the topics discussed by the participating experts and tabulated them according to the discussion topics, visualizations, and changes in the topics throughout the workshop. Tables 1, 2, and 3 illustrate the observations from the Lidingö, Nynäshamn, and the joint workshops, respectively. For each workshop session, visualizations were generated with the fused dataset based on the parameters identified for complete mental health, as shown in Figure 1. For example, the first workshop in each municipality utilized visualizations of family, education, general health, and free-time activities, along with self-reported data from youth. Subsequent workshops presented data on free-time activities, school attendance, and student performance in various subjects. This demonstrates the evolution of discussion topics from standard data points to a more systemic view by all participants.\u003c/p\u003e\n\u003cp\u003eThus, we examined whether the discussions aligned with the workshop theme and whether they developed into systemic issues or specialized areas. We also observed whether discussions were not focused on any single participant's expertise but rather on multiple overlapping themes. A detailed discussion of the analysis of the workshop discussions has been published\u003csup\u003e17\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eTo illustrate this, consider the topic of “meaningful leisure activities”, the last row in Table 1. During the main discussions with high school students from Hesby High School, located in Lidingö, on how they define well-being for themselves, the topic of meaningful leisure activities was suggested and discussed by the students. We mark an “X” against the central theme of the workshop, indicating an “O” if the discussions evolved to a related topic. We marked a “-” to suggest that the talks did not include the themes. Similarly, in the workshop session focused on the theme of “meaningful leisure activities,” representatives from leisure centers led the discussion, which evolved to address issues related to policies supporting safety, education, and prospects for youth.\u003c/p\u003e\n\u003cp\u003eTable 1: Analyzing topics of discussion in Lidingö workshops. “X” discussion topics match the workshop theme, “O” discussed topics from other themes, and “- “no debate on this theme.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHigh school students from Hesby gymnasium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOfficials from Lidingö\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRepresentatives from leisure centers, libraries, the sports unit, general culture, etc.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSocial services, (KAA), Delta Ung, leisure center, school psychologist\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDefining well-being\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIntroducing all available datasets\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePolicy, support, safety, labor, education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYouth not working or studying\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMeaningful leisure activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 1 illustrates the topics discussed in each workshop conducted in Lidingö, as well as the combination of the respective participants' expertise, and Table 2 illustrates the same for the transcripts from the workshops held with participants from Nynäshamn municipality.\u003c/p\u003e\n\u003cp\u003eTable 2: Analyzing topics of discussion in Nynäshamn workshops. “X” discussion topics match the workshop theme, “O” discussed topics from other themes, and “- “no debate on this theme.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYouth at the leisure center in Ösmo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOfficials from Nynäshamn\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHead of Leisure Centers + representative of secondary schools\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOfficials from the upper secondary school, Campus Nynäshamn, social administration\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDefining well-being\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIntroducing all available datasets\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePolicy, support, safety, labor, education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYouth not working or studying\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMeaningful leisure activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn the joint workshop sessions, the themes were set to common topics of interest between both municipalities, and the discussion topics were tabulated as before. Table 3 illustrates the results.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3: Analyzing topics of discussion in joint workshops. “X” discussion topics match the workshop theme, “O” discussed topics from other themes, and “- “no debate on this theme.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eStudent Health Nynäshamn and Lidingö\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eManagers School and Social Administration, culture \u0026amp; leisure - mixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eManagers School and Social Administration, culture \u0026amp; leisure - mixed\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eRole of schools in promoting well-being of youth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWell-being of youth - data and reasoning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFinalization of practical work in municipalities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAs Tables 1, 2, and 3 illustrate, for a given participant group (a column), the discussions did evolve towards one or more topics beyond the expertise of the group present (‘O’ marks). The visualization in the workshops influenced discussion topics to shift towards other systemic aspects related to improving youth mental well-being. We utilize these observations to discuss the role of visualizations from a network-based, fused dataset in demonstrating their operation as a boundary object.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eEstimating youth mental well-being relies on data about their subjective experiences, the perspectives of experts working with them, and information collected through monitoring. Consequently, the data and expertise required to promote youth well-being span multiple domains and necessitate a systemic understanding for the effective implementation of strategies aimed at enhancing youth well-being.\u003c/p\u003e\n\u003cp\u003eWhile well-being is defined in a broad sense, the experiences of youth in different municipalities can vary due to demographics, socioeconomic conditions, and access to social programs. This leads to a situation where the goal of improving well-being is shared among different departments and experts within a municipality, but the approach to achieving it differs based on the data and experience of the experts with the youth. The knowledge and expertise of individuals such as educators, care providers, or social program administrators can be challenging to capture and document.\u003c/p\u003e\n\u003cp\u003eConsider two groups of experts who participated in the workshops in Nynäshamn. They consisted of educators from middle and high schools, physical training coaches, and instructors. The educators interpreted promoting youth well-being as keeping the youth in school, where they would be under the supervision of teachers and educators. Individual needs can then be identified and addressed. They also noted that once a student leaves their program, their history must accompany them as they transition into adulthood to prevent future challenges in seeking help. Similarly, the sports coaches interpreted that participating in physical activities is a means to promote youth well-being. They proposed studies to understand why physical activity decreases during the transition to adulthood. Educators specialize in pedagogy and curriculum development, and similarly, sports coaches are often athletes themselves, specializing in assessing an individual’s physical abilities and designing training programs. While there are shared concepts between coaches and educators, some terms and norms may differ. Challenges due to such overlaps are intensified when additional domains are involved. Thus, aspects influencing well-being and flourishing\u003csup\u003e8,16\u003c/sup\u003e are monitored by different departments within a municipality with experts from various social spheres.\u003c/p\u003e\n\u003cp\u003eThe promotion of youth mental well-being resembles the institutions studied by Leigh-Star et al\u003csup\u003e5,6,12,19,20\u003c/sup\u003e. A municipality is assumed to be an institution where various experts work towards the common objective of promoting youth mental well-being. Thus, each expert’s department would represent a different “social world” with its own set of language, practices, and norms.\u0026nbsp;A boundary object-based approach enables an incremental approach, where experts can use them to map data, knowledge, and experience between their respective domains. This would allow “collaboration without consensus”. We used visualizations from a fused dataset as boundary objects. The visual medium provided a conceptually neutral space in which to observe and interpret knowledge from all expert participants. It also served as a prop to elicit discussions on experiences and interpretations of the data presented. We employed this strategy to foster a systemic perspective among experts through workshops that engaged them with data on youth well-being parameters.\u003c/p\u003e\n\u003cp\u003eIn our workshops, we began with general visualizations related to complete well-being for youth in each municipality. The first session’s visualizations were generated based on parameters identified for complete well-being\u003csup\u003e8\u003c/sup\u003e. During discussion sessions, experts shared their conceptualization of well-being based on their own experience and data collected within their departments. In subsequent discussions, they identified common areas where they shared similarities, had contradictions, and complementary experiences. For the same example of coaches and educators, both worked with youth at school or in physical activities. Some strategies were effective in building team dynamics and routines. In subsequent workshops, they requested new visualizations and specific combinations of visualizations, such as identifying youth who may not be participating in any education or physical activities, youth unemployment, and registrations for higher education. Tables 1, 2, and 3 capture such deviations and mappings between different groups of audiences in Lidingö, Nynäshamn, and joint sessions, respectively. The deviations in discussion topics demonstrated aspects that were common or contradictory among the participating groups, reflecting the properties of a boundary object. The new visualizations from different departments evolved into a “horizontal” view of the system/departments involved with the youth.\u003c/p\u003e\n\u003cp\u003eThe boundary object-based approach acknowledges the institutional framework, the diverse communities of practice, and the shared goal of youth well-being. While boundary objects can take many forms, our approach employed visualizations. This offers us two key advantages.\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003eData visuals tend to be neutral in their presentation of data. This enables experts to interpret observations according to their respective domains, without imposing constraints on definitions or standards. Consequently, this approach supports incremental development of concepts and inferences. Thus, policymakers and practitioners can agree on common aspects and identify differences to establish norms more quickly and accurately.\u003c/li\u003e\n \u003cli\u003eIt allowed us to work with the existing data infrastructure and departmental practices. Instead of developing a new model, data visualizations leverage existing infrastructure and foster discussions around current practices.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eBy repeating this approach with all municipalities, we can eventually develop a repository of such boundary object visualizations and fused datasets to identify common aspects of youth well-being promotion across all municipalities in Sweden. This leads to a schema of domains that transitions from a fragmented to a federated state, with boundary objects bridging these social spaces and their associated languages. \u0026nbsp; It is an interconnected infrastructure that is both conceptual and data-centric. This approach enables the bottom-up construction of ontologies for a specific domain of discourse within the social world of practice and composition, utilizing boundary objects, and thereby provides the basis for a “boundary infrastructure”\u003csup\u003e12\u003c/sup\u003e that fosters a collective, shared memory.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe results demonstrate that the visualizations had a significant impact on the discussions among the participating experts. While the talks began with the workshop theme, the visualizations prompted a shift in focus to move beyond participants’ experiences with youth to more systemic perspectives on the effects on youth well-being in their municipality. This was observed in the form of requests for further data visualizations, which required the combination or aggregation of data from various sources during the sessions. Our approach utilized a fused dataset, allowing us to generate new visualizations during discussions. We also observed that some groups were able to take a broader systemic perspective than others. In each session, it was beneficial to display visualizations of data from various functions and backgrounds to further mutual understanding of the complexity of mental health prevention and promotion.\u003c/p\u003e\n\u003cp\u003eThus, we can conclude that the visualizations generated with fused datasets functioned as a boundary object, enabling experts from a municipality to explore the promotion of youth wellbeing from a systemic perspective, thereby going beyond their own experiences and expertise.\u003c/p\u003e"},{"header":"Limitations","content":"\u003cp\u003eThe development and management of workshops require time commitments from experts across various departments within each municipality. Additionally, close collaboration is essential to access specific datasets and to expand and integrate them with the existing network datasets. Therefore, one of the significant challenges has been securing commitments from different municipalities.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe plan to overcome this by incrementally building and demonstrating the results through existing collaborations and then expanding to other municipalities via demonstrations.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eThis project was a collaboration with Petra Lindfors and Kari Trost of Stockholm University, Elisabet Rendahl from Region Stockholm, and Jenny Furstenbach from Nyfikenhet AB. The authors wish to thank the many collaborators from the municipalities of Lidingö and Nynäshamn, Sweden.\u003c/p\u003e\n\u003cp\u003eFunding declaration\u003c/p\u003e\n\u003cp\u003eRegion Stockholm funded Harsha Krishna, Adam S Darwich, and Sebastiaan Meijer within the Research and Innovation portfolio.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003eAvailability of materials and data\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eIdentifying information\u003c/p\u003e\n\u003cp\u003eNo identifying information that could identify individuals has been used.\u003c/p\u003e\n\u003cp\u003eAuthor Information\u003c/p\u003e\n\u003cp\u003eAuthors and Affiliations\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHarsha Krishna,\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDoctoral Student,\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDivision of Health Informatics and Logistics,\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKTH Royal Institute of Technology, Stockholm, Sweden.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\[email protected]\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eORCID: 0000-0001-8178-9688\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEswaran\u0026nbsp;\u003c/em\u003e\u003cem\u003eSubrahmanian\u003c/em\u003e\u003cem\u003e,\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eResearch Professor,\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCarnegie Mellon University, Pittsburgh, USA.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\[email protected]\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eORCID:\u003c/em\u003e \u003cem\u003e0000-0002-4639-627X\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAdam S Darwich,\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAssociate Professor,\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDivision of Health Informatics and Logistics,\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKTH Royal Institute of Technology, Stockholm, Sweden.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\[email protected]\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eORCID: 0000-0001-8218-4306\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eSebastiaan Meijer,\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eProfessor, Department Head of School,\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDivision of Health Informatics and Logistics,\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eKTH Royal Institute of Technology, Stockholm, Sweden.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\[email protected]\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eORCID: 0000-0003-1126-3781\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eContributions\u003c/p\u003e\n\u003cp\u003eAll authors edited the manuscript.\u003c/p\u003e\n\u003cp\u003eHK performed the survey of datasets and data models and designed the network database. HK and SM designed data dashboards and conducted workshops in Swedish. ES and AD contributed to the development of the theory and observations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCorresponding author\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eHarsha Krishna,\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\[email protected]\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eRoom: 7116, Hälsovägen 11C,\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e141 57 Huddinge,\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eStockholm, Sweden.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ePh:\u0026nbsp;\u003c/em\u003e+46 0728447902\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKeyes, C. L. M. Promoting and Protecting Positive Mental Health: Early and Often Throughout the Lifespan. in Mental Well-Being (ed Keyes, C. L. 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This makes the identification of strategies for promoting well-being, as well as the observation of progress and effects, challenging. It requires different departments to collaborate and achieve a comprehensive interpretation of underlying data, which is typically bound to the various professions involved.\u003c/p\u003e \u003cp\u003eIn this article, we frame a given municipality in Stockholm as an institution comprising multiple departments with diverse expertise. Using this framing, we demonstrate that data-driven visualizations and a network-based database, fused from various datasets, serve as boundary objects, helping experts from different departments to identify promotion strategies for youth well-being, despite differences in their expertise, knowledge, and definitions of well-being.\u003c/p\u003e \u003cp\u003eWe used these visualizations in workshops with experts and analyzed their interactions. We applied this method in two separate municipalities of Stockholm, Liding\u0026ouml; and Nyn\u0026auml;shamn. We examined the impact of visualizations on workshop discussions to verify the operation of visualizations produced from a fused dataset as boundary objects. We further utilize this framing to propose a set of \u0026ldquo;boundary infrastructure\u0026rdquo; for Stockholm by extending our approach to other municipalities.\u003c/p\u003e","manuscriptTitle":"Role of boundary objects in identifying cross-sectoral promotion strategies for youth mental well-being in Stockholm municipalities","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-04 13:08:57","doi":"10.21203/rs.3.rs-7701657/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"157360521575489055566890207124764537087","date":"2026-05-12T13:48:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-26T05:41:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"299059661323011269899953376229322457020","date":"2026-03-18T04:38:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-02T10:40:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-27T17:12:57+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-10-29T07:32:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-23T07:56:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-10-23T07:53:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"60efd0cc-b1b5-4cba-a2cb-035710039a4e","owner":[],"postedDate":"February 4th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"157360521575489055566890207124764537087","date":"2026-05-12T13:48:05+00:00","index":181,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":62159882,"name":"Humanities/Complex networks"},{"id":62159883,"name":"Social science/Complex networks"},{"id":62159884,"name":"Physical sciences/Mathematics and computing"}],"tags":[],"updatedAt":"2026-02-04T13:08:58+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-04 13:08:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7701657","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7701657","identity":"rs-7701657","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}