Oulu University of Applied Sciences

The worldwide acceleration of digital transformation in healthcare underscores the need for professionals to continuously adapt and sustain robust digital health competence, shaped not only by individual characteristics and institutional environments but also by broader social, cultural, and geopolitical factors. This study aimed to identify distinct clusters of digital health competence among healthcare professionals across 19 diverse countries and regions, and to examine the factors influencing the development and distribution of these competence clusters. A cross-sectional international survey study was conducted between 2023 and 2024, using a validated survey instrument measuring digital health competence and its influencing factors. Data were collected from healthcare professionals in 19 countries and regions (n=6440; n=5945 used for this study), following a harmonised protocol with shared demographic templates and instruments. K-means cluster analysis was employed to derive digital competence profiles, with comparative analyses conducted to investigate associations between the identified clusters and individual characteristics (e.g., age, education, professional experience). Five distinct clusters of digital health competence were identified: (1) Beginners, (2) Developing Professionals, (3) Emerging Users, (4) Proficient Practitioners, and (5) Pioneers. Higher competence clusters (4 and 5) were associated with younger age, higher education, hospital-based work, and stronger perceived support from management, organisational structures, and colleagues. In contrast, lower-performing clusters reported limited digital engagement and minimal support. Perceived leadership influence, particularly managerial commitment to digital change, was a key differentiator across clusters. The findings demonstrate substantial variation in digital health competence across healthcare professionals internationally. Cluster-specific strategies, such as targeted upskilling, peer mentoring, and leadership engagement, are needed to address competence gaps. The results provide a foundation for policy development and workforce training frameworks aimed at strengthening digital readiness in global healthcare systems. Future research should explore longitudinal competence development and evaluate targeted interventions.

Immersive digital twin platforms are emerging as a key paradigm for advancing the understanding and management of hydrologic systems, by integrating interfaces and workflows within a unified conceptual architecture. This contribution presents the I-DT Hydro Framework, a conceptual model that defines the core components, interactions, and design principles of immersive digital twin platforms for water resources applications. The framework functions as a human-facing integration layer for a hydrologic digital twin architecture that includes data integration, multi-scale modeling, and simulation pipelines, continuously supported by real-time monitoring from remote sensing, in-situ observations, and crowdsourced data, and made accessible through immersive and interactive interfaces. A central element of the I-DT Hydro Framework is the role of immersive interfaces, enabled through extended reality (XR), which mediates between complex computational processes and human interpretation and decision-making. Hydrologic systems and the models used to represent them are inherently complex and often inaccessible to non-specialist users. Immersive experiences provide a new method for decision-makers with diverse domain expertise to access, explore, and interpret the knowledge generated by hydrologic data and models. The framework further illustrates how hybrid modeling and machine learning can be embedded within autonomous pipelines to support adaptive decision support systems under dynamic environmental conditions. By explicitly linking platform layers, workflows, and user interaction, the I-DT Hydro Framework provides a shared reference for the design and evaluation of immersive digital twin platforms, supporting scalability, interoperability, and stakeholder engagement in hydrologic digitization.

This paper examines the connectivity and beyond-connectivity requirements essential for water data ecosystems, highlighting the critical role of advanced communication technologies, such as 5G/6G, in enabling rapid, reliable data transmission for real-time monitoring and decision-making. Optimizing communication protocols supports robust infrastructure, interoperability among diverse sources, including environmental sensors, weather data, and utility-provided information, and seamless data integration and utilization, while promoting innovation, efficiency, and sustainability in water management.The study is structured in two main parts. First, it identifies specific connectivity and beyond-connectivity requirements, focusing on the integration of various water data sources and evaluating the efficacy of communication protocols to support dynamic data integration, including capabilities like artificial intelligence, sensing, and sustainability. This forms the foundation for subsequent analysis. Second, it analyzes and optimizes connectivity services offered by 5G/6G and beyond technologies to meet these requirements, considering factors such as energy efficiency, reliability, scalability, and integrated services like sensing, AI, and computation.The study aims to demonstrate that addressing these requirements enhances the integration and utilization of diverse water data, facilitating access to information, development of new solutions, improved understanding of water management challenges, and innovation in water supply through enhanced prediction models and more efficient, sustainable solutions. It identifies and optimizes key performance indicators (KPIs) as well as services derived from standardization bodies, tailored to water-related use cases such as leak detection, wastewater monitoring, and resource efficiency. These include ultra-low latency for critical alerts, high reliability for infrastructure control, energy efficiency in sensor networks, scalability for IoT-dense environments, and integrated AI for dynamic data processing. Anticipated insights reveal how water data ecosystems can overcome challenges like demand-supply gaps through efficient data collection, sharing, and utilization, while addressing barriers such as limited data availability and regulatory constraints. This necessitates clear visions, effective data-sharing mechanisms, and scalable architectures to drive innovation and reduce water loss.The proposed framework facilitates informed strategies and new opportunities for stakeholders in water utilities and related sectors. This study advances the understanding of digitalization in critical infrastructure, demonstrating how optimized connectivity can promote efficiency and sustainability in water management.

We introduce a comprehensive observation and measurement framework designed to monitor ecosystem-level changes in a former peat extraction area using advanced instrumentation and digitalisation tools. This system aims to deliver accurate scientific data to support peatland management decisions and provide reference measurements for carbon emission calculations in the land use sector. In Finland, peat extraction for energy is being phased out as part of the green transition. Former extraction sites are commonly restored through rewetting, yet the short- and long-term impacts on water quality, greenhouse gas (GHG) emissions, and terrestrial and aquatic ecosystems remain poorly understood. To address this knowledge gap, we have established an intensive monitoring site at the Turvesuo–Miehonsuo peat extraction area in the Sanginjoki catchment near Oulu, Finland. Peat extraction ended in 2023, and rewetting is planned for 2025–2026. Our monitoring integrates online and cloud-based data transfer, model input, and visualisation from: 1) continuous high-frequency water quality and aquatic gas measurements, 2) eddy covariance and chamber-based GHG flux monitoring, 3) drone surveys for spatial variability assessment, 4) hydrological monitoring of surface and groundwater, 5) microbial and algal community analyses, and 6) detailed vascular plant and bryophyte inventories. This approach will provide a robust dataset for evaluating the environmental impacts of peatland rewetting using latest technological advances.

Businesses across sectors increasingly require biodiversity-related information to meet rising expectations for sustainability, transparency, and nature-positive action. Yet many firms continue to struggle with how biodiversity data can be meaningfully integrated into strategic decision-making and credible sustainability communication. This research introduces a theoretical lens for biodiversity-centric strategic marketing that positions open-access biodiversity data as a strategic enabler of business sustainability. Grounded in Resource-Advantage theory, the framework conceptualizes how firms build trust in systemic change through three interconnected forms of trust: trust in value chain actors, trust in biodiversity-related exchange actions, and trust in open-access biodiversity data. Together, these forms of trust strengthen corporate capacity to assess, disclose, and manage biodiversity impacts and dependencies across different stages of business activity.The study demonstrates how open-access biodiversity data (e.g., Biodiversity Intactness Index) and database (e.g., WWF Biodiversity Risk Filter) can support corporate biodiversity assessments and alignment with the Kunming–Montreal Global Biodiversity Framework. A key contribution is the development of a Corporate Site Biodiversity Index (CSBI), applied to 3,674 pharmaceutical corporate sites across the US, UK, Switzerland, France, Finland, India, and other regions. Empirically, CSBI significantly predicts site-level reputational capital (β = .46; t = 31.27; p < .001). Consistent with Resource-Advantage theory, this finding demonstrates how biodiversity-related intangible resources—trust, ethics, and sustainability legitimacy—translate into competitive advantage. CSBI operationalizes “trust in systemic change” by providing verifiable, data-driven evidence of nature-positive performance, creating decentralized stakeholder confidence that extends beyond traditional corporate communications.The research further illustrates how biodiversity data can support value-creation initiatives such as biodiversity-related innovation and the development of new strategic assets. This includes private biodiversity-focused funds, pioneering biodiversity bonds, and the conceptualization of synthetic stablecoins or other tokenized instruments in which biodiversity data serve as the underlying reference asset. These can be operationalized through decentralized ecosystems, including blockchain infrastructures such as the Solana and Ethereum networks.Overall, the study provides a scalable framework for businesses seeking to incorporate biodiversity data into sustainability marketing strategy. By integrating biodiversity-centric actions with transparent, data-driven marketing practices, companies can contribute to nature-positive outcomes while strengthening organizational resilience, reputational capital, and long-term legitimacy.

BackgroundHardly any previous studies have examined technology-based interventions among cardiac rehabilitees. The added value of technology and biopsychosocial factors in weight management should be studied more in cardiac rehabilitation.ObjectiveThis mixed method study aimed to examine what biopsychosocial factors predict WC reduction and what factors arise from the talk of cardiac rehabilitees during 12-month cardiac rehabilitation.MethodsA total of 59 rehabilitees (mean age 60, SD 6 years; 48/59, 81.3% male) were randomly assigned in pairs into the experimental group (n=29) or the reference group (n=30). Biopsychosocial outcomes were measured at baseline and after 6 and 12 months with a 6-minute walk test (6MWT), the World Health Organization Quality of Life Brief Form questionnaire, body mass, BMI, WC, age, and sex. Rehabilitees’ experiences were investigated using focus group interviews. Both groups received conventional cardiac rehabilitation. In addition, the experimental group used technology. Multiple linear regression was used to predict WC change in 0-6 months and 0-12 months. The qualitative data were analyzed with thematic analysis. Integrative analysis was used to create a research-based model.ResultsGroup allocation predicted WC reduction (P=.007), with the experimental group showing a greater reduction (b=2.5 cm) than the reference group in the 0-6 month analysis. A significant interaction between the reference group and 6MWT was observed (P=.04), meaning that improvement in 6MWT was associated with WC reduction. Baseline WC was marginally associated with a greater reduction in WC (P=.05). None of the independent variables predicted WC reduction in 0- to 12-month analyses. Three themes arose from the interviews with the experimental group: meaningful factors related to weight management, a goal-oriented approach to weight loss, and monitoring body composition. Two themes emerged from the reference group: motivation for change and unstable weight management. According to the integrative analysis, belonging to the experimental group was important. The research-based model highlighted that the added value of remote technology on WC reduction was largest at the beginning of rehabilitation (0-6 months). The rehabilitees’ talk in the experimental group was goal-oriented, and they talked about the achieved changes. In the reference group, the talk remained motivational, and their body composition changes were unstable.ConclusionsThe integrative model emphasizes the differences between the experimental and reference groups in weight management. The use of added remote technology seemed to explain the WC reduction. The rehabilitees reflected on behavioral changes in weight management. In the reference group, improved 6MWT distance was associated with decreased WC, but they talked about motivation for weight management and unstable changes in body composition. In the future, results should be verified by larger research groups and individual interviews, which can be combined with personal quantitative data.Trial RegistrationISRCTN Registry ISRCTN61225589; https://www.isrctn.com/ISRCTN61225589

ABSTRACT Regulations and the collective influence of the value chain compel business‐to‐business (B2B) actors within the nonwoven (NW) manufacturing industry to drive sustainable development. However, the literature rarely addresses how B2B actors aim to align with sustainable development to co‐create value and what challenges they face. Therefore, this study brings clarity to this question within the context of an international NW value chain that constitutes a significant part of technical textiles. The qualitative data were collected through two workshops ( n = 31) and 18 interviews comprehensively representing the NW value chain actors from a global perspective. Using abductive reasoning, we analyzed the data through the service‐dominant logic (SDL) lens. Our findings show that value creation comprises internal and external systemic‐level value co‐creation practices and challenges. This study contributes to the value creation literature by linking sustainable development to SDL, taking a systemic perspective on value creation and delineating the practices of value co‐creation.

Introduction: theoretical knowledge supports decision-making, autonomy, and reflective thinking. It plays a key role in the holistic development of young athletes, especially in sports like football, where constant interaction with the environment demands adaptive responses. To enhance these skills, a methodological approach based on contextualized games and comprehension strategies is proposed. Objective: to design a grassroots football training program grounded in the Teaching Games for Understanding (TGfU) approach, emphasizing the development of understanding and to analyze its impact on the theoretical knowledge of young football players. Hypothesis: players will develop their theoretical knowledge, reflected in greater conceptual enrichment and a more tactical orientation in the interpretation of game actions. Methodology: a preexperimental study with repeated measures was conducted. Twelve U12 players participated. The 13-session program incorporated six reflective strategies: (1 and 2) game performance self-assessment and peer assessment; (3) guided discovery; (4) use of a tactical board; (5) freeze and reconstruct; and (6) debate of ideas during time-outs. The impact was evaluated through questionnaires, analysis of self-assessed game performance, and the coach’s journal. Results: a significant improvement in theoretical knowledge was observed, along with an evolution in the type of knowledge expressed, with increased presence of tactical components. Three phases were identified: an initial stage of low participation, an intermediate stage of acceptance, active engagement and development, and a final stage of consolidation and transfer. Conclusions: the use of TGfU, with an emphasis on strategies for developing theoretical knowledge, has the potential to improve tactical understanding, foster reflective habits, and enrich players' specific vocabulary.

Purpose This study investigates how increased virtuality and remote participation in dispersed project environments affect inter-organizational collaboration and identifies the managerial approaches needed to adapt and maintain effective collaboration throughout the project lifecycle. Design/methodology/approach A qualitative research design was employed to explore and analyze managerial practices in virtual, inter-organizational settings. Data were collected and interpreted to understand key challenges of virtual collaboration and how managers adapt their strategies in response to reduced physical interaction and increased distance between project participants. Findings The study reveals that successful collaboration in virtual project environments requires recognition of the challenges posed by distance and diminished face-to-face contact. It highlights the importance of integrating these factors into project strategy and emphasizes the need for holistic planning and implementation of virtual collaboration mechanisms aligned with project goals. Originality/value This research contributes to project management literature by offering novel and topical insights into how inter-organizational collaboration can be effectively managed and facilitated in increasingly virtual project settings. It highlights the importance of adapting managerial practices to support virtual collaboration in dispersed projects.

ABSTRACTIntroduction: The clearance of brain metabolites increases during sleep, in association with increased spectral power of the three main cerebrospinal fluid (CSF) flow drivers: cardiovascular, respiratory, and vasomotor brain pulsations. However, little is known about how the increased power of these pulsations affects the velocity and direction of fluid flow in the sleeping brain.Objectives: To address this knowledge gap, we mapped the CSF oscillatory flow velocity in relation to the changing physiological pulsations in the brains of 22 healthy volunteers during sleep and waking.Methods: We used the ultrafast magnetic resonance imaging sequence known as magnetic resonance encephalography (MREG) for tracing the pulsatile movement of water molecules inside the cranium. First, we conducted a phantom validation study with optical flow analysis to confirm that MREG accurately tracks pulsatile water molecule flow in a porous tissue medium. Next, we obtained MREG recordings for mapping the three physiological pulsations without aliasing in the human brain across the awake and sleep states; we thereby quantified the brain‐wide 3D velocity →V vectors (i.e., the velocity vs and 3D direction v^) of each pulsation band, using comprehensive dense optical flow analysis during EEG‐verified sleep in comparison to the awake state. Finally, we assessed relationships among the spectral power of the physiological pulsations, their 3D velocity →V, and slow‐delta EEG power, which is known to depict the increased interstitial volume during sleep.Results: In our phantom study, dense optical flow analysis reliably detected water flow in tissue driven by external pulsations. In healthy volunteers, sleep increased flow velocities (→V) of the pulsations by more than 20% in concert with elevations in respiratory pulsations and vasomotor waves, while the velocity of cardiovascular pulsations (vs) declined by the same percentage. There was a significant anticorrelation between cardiac mean spectral power and slow delta EEG mean power, and a significant correlation between vasomotor mean spectral power and slow delta EEG mean power over the whole brain.Conclusions: Phantom studies validated the optic flow analysis of fast MREG recordings. Sleep altered the 3D velocity dynamics of all neurofluidic brain pulsations in a manner consistent with increased interstitial space and greater fluid exchange, thus supporting the glymphatic model wherein physiological pulsations drive bulk flow during sleep.