Search Results (756)

Background: Medication adherence is essential for treatment effectiveness and safety, but pharmacy students may find it difficult to assess adherence comprehensively during medication reviews (MRs). This study examined how pharmacy students assess medication adherence in real-world MRs and explored whether complementary adherence frameworks could support broader evaluation. Methods: This observational exploratory study was conducted in the integrated MSc (Master of Science) Pharmacy program at the University of Tartu, Estonia. During the internship, 21 pharmacy students performed a Brown Bag MR with patients aged 65 years or older who used at least 5 prescription medications. Data included patient interviews, e-prescription records, and a validated MR documentation form. An expert panel applied the World Health Organization Medication Adherence Model (WHO-MAM) and the Perceptions and Practicalities Approach (PAPA) to identify adherence determinants not captured by the student-used MR tool. Descriptive statistics and qualitative content analysis were used. Results: Students mainly documented therapy- and patient-related issues, such as incorrect dosing, side effects, and interactions, while socioeconomic and healthcare system factors were rarely identified. Students identified potential adherence-related issues in 19% of cases, whereas experts identified such issues in 57% of cases. Additional gaps included limited recognition of financial barriers, access difficulties, and social support factors. Conclusions: In this exploratory study, pharmacy students identified medication-use-related problems during MRs, but broader adherence-related determinants were less consistently documented. These preliminary findings suggest that structured frameworks such as WHO-MAM and PAPA may be useful for broadening adherence assessment in experiential pharmacy education. Full article

This study addresses the critical challenge of translating the profound social, spatial, and cultural dynamics of the traditional introverted Persian house into more tangible design metrics for contemporary Iranian housing. Relying on qualitative data from twenty-four diverse expert interviews across architecture, urban planning, and policy, the research demonstrates a broad consensus that the notion of replicating historical form is unsustainable. Instead, it indicates that the introverted configuration is likely a context-specific ontological imperative—viewed here as a fundamental socio-spatial requirement—rooted in measurable performance, serving simultaneous social, cultural, psychological, and environmental paradigms. The main findings show that preserving cultural continuity requires a shift from aesthetic conservation to prescriptive configuration. This logic is synthesised into a consolidated socio-spatial framework, whose originality lies in introducing three regulatory design instruments: (1) the sequenced depth and filtration protocol for spatial arrangement; (2) the controlled visual and environmental parameters for façade performance; and (3) the cultural adaptability and resilience requirement for functional programming. The framework’s prescriptive metrics, such as minimum space syntax values and the visual filtering coefficient, provide regulatory bodies with the precise technical tools necessary to enforce cultural protocols like privacy and dignity in high-density urban developments. While these metrics serve as an operationally promising model, they represent a theoretical framework that requires further empirical validation in diverse contemporary residential settings before mandatory regulatory adoption. This framework offers a pragmatic pathway for safeguarding Iranian housing’s cultural identity, ensuring future developments are certified not only for safety and structure, but for their adherence to the fundamental socio-spatial contract of the Persian dwelling. Full article

Systematic frameworks for describing podcast design remain scarce. Previous research on listening motives often treats podcasts as a monolithic category or focuses on specific genres, leaving open how motives vary across different design types. This dual-perspective investigation examines two questions: Which primary design types characterize German-language podcasts, and how are listening motives related to these design types? Using a multi-method qualitative approach, 30 podcasts were analyzed through iterative listening and 16 expert interviews to develop a typology of design. Additionally, 29 semi-structured listener interviews were examined via qualitative content analysis to identify usage motives and their associations with design types. The analysis identified three podcast design types—story, talk, and factual (STF)—each characterized by distinct structural and aesthetic features. The analysis further suggested that factual design types were primarily associated with cognitive motives, talk design types with social motives, and story design types with affective motives. The resulting STF model is a relevant framework for both academic research and practical applications in podcast production. The results further suggest that usage motives may be linked to these design types and thus indicates how podcast form and audience needs and gratifications may be interdependent. Full article

Health and spa tourism is a rapidly growing sector that merges traditional healing with modern innovations to meet increasingly diverse client needs. Understanding professionals’ perspectives is crucial for developing sustainable strategies that enhance service quality, organizational performance, and long-term business viability. Drawing on qualitative narrative analysis and thematic network analysis, this study explores the key factors that spa tourism professionals in Băile Felix—the largest spa resort in Romania—associate with business success, competitive differentiation, and sustainable development. Data were collected through semi-structured interviews with 41 entrepreneurs and managers who provided detailed narratives on their strategic goals and market positioning. Rather than measuring customer psychological constructs directly, this study captures professionals’ expert attributions regarding service quality, staff professionalism, infrastructure investment, and economic objectives, and interprets these as managerial perceptions grounded in operational experience. Five research propositions guided the interpretive analysis: (P1) professionals narratively associate service quality and treatment diversity with perceived business performance and guest retention signals; (P2) staff professionalism and attitude are attributed as the primary drivers of competitive differentiation; (P3) infrastructure investment and innovation are framed as prerequisites for sustaining market positioning; (P4) the identified themes form a structurally interconnected network with key bridging nodes; and (P5) professional narratives reveal tensions between short-term economic objectives and longer-term commitments to service quality and sustainability. Thematic network analysis identified four central constructs—service quality and treatment diversity, staff professionalism and attitude, innovation and infrastructure investment, and economic and development objectives—and mapped 16 interconnected sub-themes, with modularity analysis (Q = 0.42) confirming a moderately cohesive structure. Sustainable innovation was operationalized across environmental efficiency, social value, and economic resilience dimensions, and found to be embedded systemically across multiple thematic clusters rather than treated as an isolated practice. The originality of this study lies in integrating narrative and thematic network analysis to reveal how these constructs co-evolve within a sustainability-oriented system, offering a novel methodological lens for spa tourism research in post-transitional Central and Eastern European contexts. Findings provide actionable insights for spa managers, policymakers, and investors seeking to balance modernization with tradition in resource-constrained destinations. Full article

Cardiovascular diseases are a growing public health challenge in Ethiopia, worsened by limited access to diagnostics, including ECG, and shortages of specialized expertise. AI-powered ECG offers potential to improve diagnostic accuracy, efficiency, and access in resource-limited settings, but its adoption is influenced by policy, regulatory, financing, and governance factors, which are not well understood in Ethiopia. This study explored these system-level determinants using qualitative methods from September to October 2025 across federal institutions, four regions, and five tertiary hospitals. Twenty-five stakeholders, including policymakers, regulators, digital health experts, and hospital leaders, were interviewed. Data were transcribed verbatim, coded inductively, and analyzed thematically. Six themes emerged: policy and governance, regulatory frameworks, financing and cost considerations, data governance and bias, integration barriers, and sustainability recommendations. Findings showed AI-powered ECG interpretation aligns with Ethiopia’s digital health and noncommunicable disease priorities, but the country lacks AI-specific health policies, clear regulations, and dedicated budgets. Financing is largely donor-dependent, data governance and algorithmic bias remain concerns, and infrastructure gaps and digital skill shortages limit readiness. Study participants recommended learning from prior digital health projects, coordinated scale-up, phased implementation, and continuous monitoring. Effective adoption will require context-specific policies, sustainable financing, robust regulation, strong data governance, and careful system integration to ensure equitable, responsible, and sustainable use. Full article

In the last decade, as cities increasingly seek sustainable development pathways within the cultural and creative economy, cultural-creative events have gained prominence as strategic instruments for urban transformation. Among them, city design weeks have emerged as complex service systems that connect creative industries, urban governance, and tourism development. This research aims to understand how cultural-creative events (represented by design weeks) facilitate sustainable tourism development from a service design perspective. Adopting a qualitative comparative research design, the study examines 30 design weeks selected through a cross-validated process with the World Design Weeks global network and UNESCO City of Design network. Data from 2020 to 2025 is collected primarily through expert interviews, official reports, and media materials in relation to the United Nations Sustainable Development Goals (SDGs). Grounded in the service design perspective, four Service Design Levels are summarized into 17 assessment dimensions, and experts applied Likert scale to evaluate the relative service intensity of each case. Through cross-case analysis, the findings reveal four distinct models of design weeks, reflecting different configurations of service intensity and strategic orientation. The study contributes theoretically by extending service design theory to cultural-creative tourism research, and practically by providing guidance for the organizers of cultural-creative events seeking to support sustainable city tourism development. Future research may incorporate quantitative impact assessments to further refine these models. Full article

Artificial intelligence has been considered as a transformative element capable of reshaping STEM education into equitable, resource-efficient, and scalable learning environments. However, realizing this potential requires striking a careful balance between technological innovation, pedagogical considerations, and ethical concerns. This study sought to examine the implementation of artificial intelligence (AI) tools by STEM university faculty members in Saudi Arabia to promote Sustainable Development Goal 4 (quality education). While doing so, the study attempted to explore how Saudi STEM university faculty members integrated AI tools in their instructional practices and analyze their perceptions towards these tools. To achieve these goals, the study employed an explanatory sequential mixed-methods design. In the first phase of data collection, a close-ended questionnaire was applied to a random sample of (324) STEM university faculty members. The second phase involved gathering qualitative data using a semi-structured interview administered to 12 purposively selected experts. Key quantitative findings revealed an overall AI integration at a medium level with a mean of (2.71) and standard deviation of (0.36) across three instructional practices, namely planning, implementation, and assessment. The highest integration level was in assessment (M = 2.93, medium) while the lowest was in planning (M = 2.61, medium). The results also revealed that the participants’ perceptions towards integrating AI tools were highly positive (M = 4.00, high), albeit with some concerns regarding the effect of excessive and unguided use of AI tools on students’ higher-order thinking skills, particularly the risk of AI functioning merely as an information delivery mechanism rather than serving its more pedagogically valuable role as a brainstorming scaffold. Furthermore, the study unveiled a number of barriers to integrating AI tools, including the weakness of digital infrastructure, lack of professional development, the limited credibility of AI-generated content, and ethical concerns related to academic integrity and copyrights. The research suggests the establishment of a sustainable digital environment by improving the infrastructure, providing specific training in accordance with the principles of sustainability, and implementing policies that promote equitable, transparent, and responsible integration of AI. These strategies can coordinate the growth of technology with the larger needs of the quality of education, inclusion, and sustainability of STEM education in the long term. Full article

Background/Objectives: Wearable activity monitors and sensor-based devices are increasingly used to quantify mobility, load, and recovery in orthopaedic patients, yet clinicians lack practical guidance on selection, implementation, and interpretation. This qualitative expert consensus study synthesized real-world experiences from leaders in orthopaedics, rehabilitation, biomechanics, and digital health who implemented wearables at scale. Methods: Semi-structured interviews were conducted with 16 experts (64% response rate) recruited via hybrid purposive and snowball sampling. Participants included orthopaedic surgeons and research scientists with 124 cumulative years of wearable experience across over 9000 monitored patients. Interviews addressed device selection, clinical workflow, data management, and adoption barriers. Data were charted into a structured extraction matrix and analyzed using Inductive Thematic Analysis and a Framework Approach, reported per COREQ guidelines. Results: Experts utilized diverse sensor platforms across arthroplasty, trauma, spine, and sports medicine. Four key themes emerged: (1) device selection prioritized usability and patient compliance over technical sophistication; (2) workflow required defined team roles to manage data volume and avoid clinical burden; (3) patient engagement favored simplified, actionable feedback amid divergent views on data transparency; (4) future outlook anticipated AI-driven proactive risk prediction. Conclusions: No single wearable suits all orthopaedic practices; success hinges on aligning sensor placement with clinical questions, rigorous data quality checks, and integration into care plans. This study offers a practical checklist and roadmap for point-of-care adoption. Full article

Background: Most penicillin allergy labels are documented in early childhood and result from events of low risk for allergy. In Germany, evidence-based strategies to evaluate the likelihood of a true penicillin allergy are still lacking. As general practitioner input is indispensable regarding required resources for the implementation of successful delabeling strategies in outpatient care, a mixed-methods study in Baden-Württemberg, Germany explored untapped delabeling potential and conditions for successful initiatives based on their experiences, to support preservation of penicillin as a treatment option and prevent resistance development. Methods: A cross-sectional convergent mixed-methods study was conducted with an online survey and semi-structured interviews. The survey link and invitation to participate in an interview was sent to randomly selected publicly available e-mail addresses. Survey data were analyzed descriptively. Qualitative data were analyzed inductively based on thematic analysis. Results: n = 101 survey questionnaires and n = 15 interviews were analyzed regarding relevance, experiences, framework conditions, and potential approaches to delabeling. All participants with limited recollection of the index reaction. Most participants considered delabeling a highly relevant topic in general practice. Delabeling efforts were discouraged by lack of time, expertise, and remuneration, and uncertainty due to missing guidelines. Taking a sufficient medical history and, if necessary, subsequent testing were seen as one approach to delabeling. For a standardized approach in primary care, patient and care provider education, precise guideline recommendations, and delabeling expert teams were suggested. Conclusions: The findings mirror aspects already identified in international research. A nationwide survey with general practitioners could confirm that addressing necessary resources and systemic adjustments would support effective penicillin allergy delabeling in outpatient care. Full article

Overweight and obesity during pregnancy are associated with increased maternal and neonatal risks, yet scalable interventions addressing the psychological processes underlying health behaviours remain limited. This study describes the development and formative evaluation of DEMETRA, a chatbot delivering an Acceptance and Commitment Therapy (ACT)-informed intervention to promote healthier lifestyles in pregnant women. In line with Phase 1 of the Obesity-Related Behavioral Intervention Trials framework, a multidisciplinary team developed a six-session digital program delivered via a rule-based virtual assistant. A mixed-methods design was employed to assess acceptability, usability, and perceived relevance among a heterogeneous stakeholder sample. Sixteen stakeholders (psychologists, communication experts, nutritionists, clinicians, and non-overweight, expectant women or those who had recently delivered) participated in iterative testing; 15 completed quantitative measures (Semantic Differential scales, uMARS, BUS-11) and 16 completed semi-structured interviews. Non-parametric analyses indicated significantly positive evaluations across most communication and content domains, particularly clarity and language appropriateness, whereas session duration and several engagement-related dimensions did not significantly differ from neutrality. Qualitative findings confirmed strengths in clarity, non-stigmatising tone, and multimedia support, while identifying limited personalisation and message pacing as key areas for refinement. Overall, findings provide formative evidence that ACT-informed principles can be translated into a chatbot-delivered antenatal program and highlight concrete priorities for optimisation (e.g., personalisation and message pacing). Because end-user testing did not include overweight/obese pregnant women and the sample was small and heterogeneous, conclusions regarding acceptability/feasibility in the intended clinical population remain preliminary; the results primarily support iterative refinement and subsequent proof-of-concept testing in the target group. Full article

Background/Objectives: Integrating heterogeneous One Health time series into transparent and usable surveillance workflows remains difficult because data preparation, modeling, and interpretation are often separated across tools. In this paper, we introduce OH-MEMA (One Health Mixed-Effects Modeling and Analytics), an interactive visual analytics framework that integrates heterogeneous One Health data streams, including human clinical outcomes, environmental factors, and wastewater surveillance data, to support syndromic surveillance and pandemic preparedness. Methods: The system enables users to upload and analyze multi-source datasets through an interactive web-based interface. The modeling component supports fixed effects for multi-source predictors, random effects for spatial, temporal, and demographic grouping variables, optional random slopes, and rolling time-series validation. Model results are visualized as time series comparing observed and predicted outcomes, with evaluation metrics including Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and correlation. To support iterative exploration, the system incorporates analytic provenance through a visual model tree that records prior configurations. Results: OH-MEMA was validated through both quantitative and qualitative evaluations. Quantitatively, mixed-effects models were assessed across multiple counties and outcomes using RMSE, MAE, and correlation, demonstrating robust predictive performance. Qualitatively, expert users, including epidemiologists and disease surveillance analysts, evaluated the system using the NASA Task Load Index and open-ended interviews, indicating improved interpretability, manageable cognitive workload, and effective workflow integration. Conclusions: OH-MEMA provides an interpretable, human-in-the-loop platform for exploratory forecasting and comparative model analysis in syndromic surveillance. The framework effectively bridges data integration, modeling, and interpretation, supporting user-centered analytical reasoning and decision-making in One Health applications. Full article

This study examines the role of artificial intelligence (AI) technologies in identifying and sustaining leadership talent within the educational sector in Oman, addressing the increasing demand for evidence-based and innovative approaches to leadership development. A qualitative phenomenological research design was employed to explore how AI experts and educational leaders perceive, evaluate, and conceptualize AI-driven tools for leadership talent identification and sustainability. In-depth semi-structured interviews were conducted with 25 participants from three major Omani educational institutions. Data were analyzed using thematic analysis, allowing systematic identification of recurring patterns, conceptual relationships, and shared professional insights. The findings indicate that AI applications—including big data analytics, behavioral assessment tools, competency identification platforms, and predictive analytics—provide effective mechanisms for early detection and assessment of leadership potential. Furthermore, integrating AI into personalized professional development programs and continuous performance evaluation contributes to the long-term sustainability and strategic utilization of leadership talent. This study underscores the potential of AI to enhance strategic leadership planning within educational institutions. The results expand our empirical understanding of AI-driven leadership development and offer practical insights for implementing AI-informed strategies in Oman and the broader Gulf region. Full article

Man-made climate change is empirically proven and places ethical and strategic responsibility on the current generation to mitigate risks for future generations. Within this context, the selection of future energy carriers is a central determinant of sustainable development. While electrification is widely promoted, particularly in the transport sector, it is associated with complex production chains, critical raw material dependencies, unresolved recycling challenges, and potential resource scarcity. Synthetic fuels therefore re-emerge as a potential complementary option, especially for applications that are difficult to electrify directly. However, their role remains controversial due to efficiency losses and cost challenges. This paper uses qualitative research based on expert interviews to investigate the role of synthetic fuels in the sustainable management of energy transition and responsible practices. A total of 11 experts, representing the energy sector, research institutions, engineering fields, environmental organizations, and political–regulatory contexts participated. The analysis focused on four dimensions—efficiency, awareness, knowledge, and acceptance. The findings have shown that synthetic fuels are not a universal substitute for fossil fuels but a highly conditional option for hard-to-electrify applications. Efficiency losses, limited renewable electricity availability, knowledge gaps, conceptual ambiguity, and acceptance challenges significantly constrain their systemic role. The paper concludes that synthetic fuels can only make a meaningful contribution under strict conditions, with clear prioritization, realistic expectations, and coherent long-term policy frameworks aligned with intergenerational responsibility and genuine sustainability. The findings should be interpreted primarily within the German and European policy and innovation context, as the expert sample is largely embedded in institutions operating in this environment. Nevertheless, the insights provide relevant indications for broader international debates on the role of synthetic fuels in energy transition. Full article

Due to their unique structural and operational characteristics, stadiums create substantial environmental impacts throughout their lifecycle. Assessing the environmental sustainability (ES) of stadiums is important to identify opportunities for targeted improvements and enabling a transition towards environmentally sustainable stadiums (ESSs). This paper investigates how sustainability certification systems and green building rating schemes (GBRSs) can be optimised for effective application in stadiums to improve ES outcomes. A qualitative exploratory approach using in-depth semi-structured interviews, followed by the thematic analysis of qualitative data using NVivo, was applied to examine the suitability of existing certifications and rating systems in stadiums. Twenty stadium and sustainability experts from diverse global regions participated in semi-structured interviews. Three overarching themes emerged, offering insights into how ES certifications and GBRSs can be optimised for use in stadium settings. These themes encompass the ES challenges that stadiums face and the benefits and limitations of existing assessment tools. This study identified “Green Operations and Advanced Leadership” (GOAL) as the only sustainability certification designed specifically for application in venues and stadiums. This paper proposes a set of recommendations to improve the application of certifications and GBRSs in stadiums. These recommendations enable designers, stadium owners, and decision makers to advance stadium sustainability through the more effective use of certification frameworks and rating systems. Full article

The city of Ghadames, which includes a UNESCO World Heritage Site along with other local heritage sites such as Roman ruins, an Ottoman fortress, and a traditional mud village, exemplifies the challenges of conserving heritage in conflict-affected and neglected urban environments. This study aims to analyse the cumulative, long-term human threats, such as neglect, weak governance, and uncontrolled tourism, that gradually erode the city’s cultural fabric. The study uses a qualitative, interpretive approach, analysing official documents and conducting semi-structured interviews with local officials and heritage management experts. The findings indicate that human risks in Ghadames are not primarily due to direct actions but rather result from systemic neglect and fragmented governance, which exacerbate the vulnerability of tangible heritage. The results also reveal that the lack of comprehensive conservation policies, along with centralised heritage management and reliance on short-term, reactive measures, such as temporary restoration or tourism-focused initiatives, has led to damage that could become irreversible over time. The paper argues that successful and sustainable heritage conservation requires integrating community-based governance, long-term policy reform, and participatory risk management. It situates these findings within the broader context of Libya’s heritage, which serves as the foundation of national memory. It emphasises that addressing human risks as cumulative processes, rather than as temporary events, is crucial to safeguarding Libyan cultural heritage and ensuring its sustainability for future generations. By examining Ghadames as a case study, the paper proposes a model for sustainable heritage protection across Libya’s vulnerable cultural landscapes. Full article