Högskolan i Skövde

Background: Childhood cancer causes a big change in life for both the sick child and the whole family. Parents get more responsibility and need support, information, and involvement to manage the child´s illness and care.

Aim: To examine parents’ experiences of having a child with cancer.

Method: This study was done as a qualitative literature review, inspired by metasynthesis. Scientific articles were searched for in the databases CINAHL and PubMed. The articles were checked for quality and analyzed using Friberg’s analysis model.

Findings: The results showed that parents experienced shock, fear, uncertainty, and feelings of powerlessness when their child was diagnosed. Everyday life changed because of hospital stays, treatments, and new routines. This increased the parents’ practical and emotional responsibility. Relationships in the family were affected. Parents needed clear information, support from healthcare staff, and the chance to be involved in their child´s care. Hope, coping strategies, and gradual adaptation were important for handling the situation.

Conclusion: Parents of children with cancer need individual, family-centered, and continuous support from nurses. This can help parents feel safe, involved, and more able to manage the child’s illness.

Nowadays, achievements are a common feature in video games because they can motivate players. However, less attention has been given to understanding how achievements influence player motivation, therefore, this paper’s goal is to explore what motivates players to continue playing a game in order to collect achievements. This study reviews existing literature on achievements, including academic research and a case study of the popular gaming platform Steam, to identify key motivational factors. These findings provide the foundation for qualitative interviews with players who are highly motivated to complete achievements, exploring the motivations and emotions associated with achievement hunting. The results identified four main themes: player motivations, player experiences, social influences, and achievement design factors.

Syftet med denna studie var att undersöka vilken av databaseerna, MongoDB och CouchDB, i ett kluster bestående av fyra noder producerade lägsta responstider under olika data volym och olika antal returnerade bilddokument på sjukvårdsdata. Ett artefakt utvecklades bestående av tre lager; klientapplikation, serverapplikation och databas-klustrena. Resultatet från studien visade att MongoDB var snabbare än CouchDB, både under olika data volym och olika antal hämtade bilddokument. Den visade att organisationer bör användas sig av MongoDB-kluster för att uppnå låga responstider. Det finns flera sätt att driva vidare denna studie exempelvis, undersöka hur olika antalet noder påverkar prestandan och inkludera andra NoSQL-databaser.

Background: Euthanasia is a complex phenomenon where autonomy, dignity and suffering are at the center. The desire to hasten death is often based on physical, psychological, social and existential suffering. A stated wish to die may express a need for support and affirmation. The nurse's role is to work person-centered and ethically to alleviate suffering and strengthen participation.

Aim: To investigate how patients experience existential suffering in relation to the desire to end their life.

Method: The study was conducted as a qualitative literature review using relevant keywords related to existential suffering and the desire to end one's life. The material was analyzed using a qualitative literature review model to identify recurring themes that answered the study's purpose.

Findings: The results show that patients' wish to die was often based on a complex existential suffering in which hopelessness, loss of autonomy, dignity and meaning were central factors. The wish to die was often ambivalent and changeable. Supportive relationships, symptom relief and existential conversations could reduce suffering, strengthen the will to live and contribute to an increased sense of control and coherence.

Conclusion: Patients' wish to die is a complex expression of existential suffering, hopelessness and loss of autonomy. Person-centered support and existential conversations can reduce suffering and strengthen security, dignity and the will to live.

Background: Mental health problems among children and young people are increasing. Undetected mental health problems among students risk developing into psychiatric conditions or physical health problems that may lead to a reduced quality of life. Apart from suffering, children and adolescents affected by mental health issues are at risk of poorer academic performance. The school is an important setting for students and serves as a protective factor. School nurses have a unique role as they meet all students in the school. The interaction between school nurse and student creates an opportunity to identify mental health problems early.

im: The aim of the study was to describe school nurses´ experiences of working with students with mental health problems.

Method: The study was conducted as a systematic literature review with a qualitative approach, using meta-synthesis as the research method.

Results: The analysis resulted in four overarching themes with associated subthemes, which together described school nurses` experiences of working with students with mental health problems in school. The themes were named: relationships, accessibility and trust play a central role; Collaboration and communication are important factors; Competence, experience and professional challenges influence the work; and Preventive work is perceived as important.

Conclusion: School nurses´ work with mental health problems is complex and influenced by relationships, experience and organization conditions. Accessibility and relationship-building are central to early detection and providing support to students. At the same time, communication and resources are of great importance for the work.

Hepatocellular carcinoma (HCC) is a major global health challenge with limited therapeutic options for advanced disease. miRNAs are small non-coding RNAs that are frequently dysregulated in HCC and directly influence post-transcriptional gene regulation. This study adapted the miRFA bioinformatics pipeline to integrate paired miRNA and mRNA expression data from TCGA-LIHC (n = 368 matched patients) for the systematic identification of candidate repurposable drugs in HCC. Differential expression analysis using edgeR identified 173 dysregulated miRNAs and 5,101 dysregulated mRNA transcripts in tumour tissue relative to normal liver controls (FDR < 0.05, |log₂FC| > 1). Experimentally validated miRNA–mRNA interactions were retrieved via multiMiR and filtered by Pearson correlation across the matched cohort, yielding 24 candidate regulatory pairs (r = −0.151 to −0.215) distributed across three hub miRNAs that captured bidirectional dysregulation: hsa-mir-7706 and hsa-mir-1269 awere upregulated in tumour tissue, whereas hsa-mir-1258 was downregulated. KEGG pathwayenrichment of the 24 target genes identified Parathyroid hormone synthesis, secretion and action(hsa04928) as the single pathway surviving Benjamini–Hochberg correction (adjusted p = 0.02), driven by SGK1, EGR1, and MEF2C. Kaplan–Meier survival analysis of MT-ND5, the gene most strongly negatively correlated with its hub miRNA, did not reach statistical significance (log-rank p = 0.12). Insilico drug repurposing against the LINCS L1000 chemical perturbation database revealed strong mechanistic convergence among the top ten candidates on the PI3K/AKT/mTOR signalling axis (six often compounds), with the pan-HDAC inhibitor pracinostat as the second-ranked compound. This work provides a reproducible computational framework for transcript omics-based drug repurposing in HCCand identifies a set of candidate miRNA–mRNA pairs and compounds for future experimental investigation.

Denna studie undersöker hur olika typer av filmljud påverkar publikens emotionella respons och tolkning av en scen. Tidigare forskning har visat att ljud spelar en central roll i att förstärka narrativa och känslomässiga aspekter, men det finns begränsad kunskap om hur specifika ljudvariationer påverkar upplevelsen i detalj. För att undersöka detta genomfördes en experimentell studie där deltagare fick ta del av en visuell scen med två olika ljuddesignversioner. Deltagarna besvarade därefter en enkät om sin upplevelse. Resultaten visar att ljuddesignen har en tydlig inverkan på både emotionell respons och scenens tolkning. Studien bidrar med ökad förståelse för ljudets roll i audiovisuella medier och belyser vikten av medvetna designval. Framtida forskning kan vidare undersöka fler ljudtyper och kontexter för att fördjupa kunskapen inom området.

Breast cancer is a highly heterogeneous disease characterized by complex molecular interactions involving multiple biological pathways associated with tumor progression, therapeutic resistance, immune regulation, and genomic instability. Conventional functional enrichment approaches, such as over-representation analysis (ORA), are widely used to interpret high-throughput genomic datasets; however, these methods often analyze genes as independent entities and may therefore generate broad and overlapping biological categories that are difDicult to interpret in complex diseases. The aim of the present study was to investigate whether network-based annotation enrichment using the NetAn framework could improve the biological speciDicity, sensitivity, and interpretability of breast cancer associated gene sets compared with conventional enrichment approaches. 

A curated dataset consisting of 997 breast cancer associated genes was analyzed using conventional enrichment methods implemented in g:ProDiler and clusterProDiler, followed by network-based enrichment analysis using the NetAn workDlow. Protein–protein interaction data from STRINGdb v12.0 were used to construct interaction networks, perform network guided gene expansion, and identify interaction deDined functional clusters. Functional enrichment analysis was subsequently performed on both the complete gene set and the individual network clusters. Cytoscape was used for network visualization and topological analysis. 

Conventional enrichment analyses identiDied signiDicantly enriched pathways associated with PI3K-Akt signaling, MAPK signaling, estrogen signaling, homologous recombination, Fanconi anemia pathway, immune signaling, and DNA repair. Network analysis successfully mapped 709 genes to the STRING interaction network and generated a densely connected protein–protein interaction network containing 2,010 high-conDidence interactions. Network-based clustering identiDied biologically distinct functional modules associated with oncogenic signaling, epithelial differentiation, immune-inDlammatory signaling, and genome stability pathways. Comparative analyses further demonstrated that the clustered NetAn workDlow identiDied the highest number of tumor-relevant annotations while improving functional stratiDication and reducing enrichment redundancy relative to conventional ORA approaches. 

Collectively, the Dindings of this study demonstrate that incorporation of protein–protein interaction topology can improve interpretation of heterogeneous breast cancer associated gene sets by partitioning broad enrichment proDiles into biologically coherent interaction-deDined functional modules. These results support the value of network-based annotation enrichment approaches in systems biology, cancer genomics, and future precision oncology research. 

Determining the post-mortem interval (PMI) remains a challenging problem in forensic science. This study evaluates whether whole-transcriptome RNA-seq data can support quantitative PMI prediction. Four model types were trained, an elastic net, random forest, gradient boosting, and a feed forward neural network, to predict post-mortem ischemic time from 17,303 samples from the GTEx v8 database. These span 948 donors across 49 different tissue types. The feedforward neural network (FFNN) achieved the best performance after variance-based gene filtering, with a test mean absolute error (MAE) of 172.51 ± 0.83 minutes and R² of 0.50, confirmed by 5-fold donor-grouped cross-validation. Differential expression analysis identified 37,670 genes (74.6%) significantly associated with ischemic time, and a Shapley additive explanation (SHAP) importance analysis highlighted mitochondrial, histone, and other genes consistent with known post-mortem biology. Per-tissue prediction accuracy varied substantially. These results demonstrate that gene expression data contain structured, time-dependent information changes due to post-mortem conditions and which can be used for post-mortem time interval estimation.

Pancreatic cancer remains one of the deadliest cancers, with very poor survival rates and limited treatment options. Drug repurposing offers a faster and more cost-effective alternative to developing entirely new therapies, by identifying existing drugs that may be effective against this disease. The aim of this study was to develop a computational pipeline based on a Variational Autoencoder (VAE) to identify differentially expressed genes and potential drug repurposing candidates in pancreatic cancer using large-scale transcriptomic data. To achieve this, transcriptomic data from TCGA and GTEx were integrated, resulting in a dataset of 17,566 samples and 41,782 genes after filtering. A β-VAE model with a 32-dimensional latent space was trained using a progressive β-scheduling strategy (0.1 to 2.0) to learn meaningful representations of the data. Differentially expressed genes were identified using a three-component scoring approach that combined gene variance, latent-space Spearman correlation, and Welch t-test–based differential expression. Pathway enrichment analysis was performed using gProfiler, and drug repurposing candidates were identified through a combination of DGIdb and LINCS L1000 signatures via Enrichr, with results cross-validated against published literature. The VAE model converged successfully without evidence of overfitting. It achieves a silhouette score of 0.3711 and a centroid distance of 5.7476 between healthy and cancer samples in the latent space. Differential expression analysis identified 467 genes significant after Benjamini-Hochberg FDR correction, including 406 upregulated and 61 downregulated genes, with key genes such as TOP2A, RRM2, MYC, BRCA2, and CDK1 highlighted. Hub gene network analysis identified TP53 as the most central gene in the PDAC protein-protein interaction network, providing independent network-level support for the identification of MDM2 inhibitors as top drug repurposing candidates. Pathway enrichment analysis revealed strong enrichment of mitotic cell cycle processes (p = 4.00 × 10⁻¹¹). Drug repurposing analysis identified 18 high-confidence FDA-approved candidates, including the independent rediscovery of gemcitabine, olaparib, rucaparib, and paclitaxel, as well as novel candidates such as simvastatin and a cluster of MDM2 inhibitors. Overall, this study demonstrates that VAE-guided latent space analysis can effectively recover computationally prioritised drug candidates directly from transcriptomic data without prior disease-specific knowledge, several of which show promise for future clinical investigation. The findings support the use of deep generative models as complementary tools in computational drug repurposing for pancreatic cancer.

The rapid evolution of smart manufacturing from the automation-focused Industry 4.0 paradigm to the human-centric principles of Industry 5.0 presents a significant challenge for early STEM education. Existing educational robotics often rely on simplified toys that fail to convey the complexities of modern industrial environments. This thesis addresses this gap by designing and implementing a didactic demonstrator that bridges high-level industrial robotic technology with accessible, game-based learning. Following the Design Science Research Methodology (DSRM), an ABB IRB 140 industrial manipulator was integrated with an OPC UA Server communication protocol, computer vision (eye-in-hand camera), and a Digital Twin in RobotStudio. The system is controlled via an intuitive Human-Machine Interface (HMI) built in CODESYS, allowing users to interact safely with three pedagogical modules: a sensor vision-based pick-and-place task, a manual path-teaching simulation, and a safety and error management scenario. Ethical concerns when working with children—such as digital privacy, physical safety, and preventing emotional deception—were strictly addressed by excluding minors from testing and utilising hardware and software logic to simulate cobot-like behaviour. The technical evaluation demonstrated a highly accurate mathematical mapping of coordinates through homography and a functionally stable bidirectional data synchronisation. Ultimately, this cyber-physical prototype demonstrates the pedagogical potential of translating advanced industrial concepts into engaging learning experiences, paving the way for future tools that promote social sustainability in highly automated workspaces.

Pancreatic β-cell dysfunction is a central feature of type 2 diabetes (T2D) and involves coordinated alterations in β-cell identity, stress signaling, and metabolic function. Microbial metabolites have emerged as potential modulators of these processes, although their effects on integrated β-cell state remain incompletely understood. The aim of this study was to investigate how microbial metabolites influence pancreatic β-cell state under diabetogenic stress conditions using integrated transcriptomic, metabolic, and protein-level analyses. A β-Cell Identity Preservation Score (BCIPS) was developed using curated identity-associated and dysfunction-associated gene panels and validated across four independent human pancreatic islet and β-cell transcriptomic datasets comparing non-diabetic and T2D donors. Publicly available RNA-seq datasets derived from in vitro β-cell stress models, including mouse islets and INS-1 rat pancreatic β-cells treated with butyrate, urolithin A, or urolithin B, were further analyzed to investigate metabolite-associated transcriptomic rescue. Experimental validation was performed using INS-1 832/13 rat pancreatic β-cells exposed to glucolipotoxic stress, where microbial metabolites were evaluated using viability assays and exploratory western blot analysis. BCIPS was consistently reduced in T2D datasets across all validation cohorts, with representative ROC analyses demonstrating discriminatory capacity between diabetic and non-diabetic samples (AUC ≈ 0.75), while random-effects meta-analysis demonstrated a significant pooled effect size with no detectable heterogeneity between studies (I² ≈ 0%). Pathway enrichment analysis identified processes related to insulin secretion, oxidative phosphorylation, mitochondrial function, and cellular stress responses. In transcriptomic β-cell stress models, butyrate, urolithin A, and urolithin B improved BCIPS under stress conditions. In INS-1 832/13 glucolipotoxicity experiments, glucolipotoxicity reduced viability to approximately 66–81% of control levels, while GABA demonstrated the strongest preservation of viability under stress conditions (~99% viability at 0.3 mM). Exploratory western blot analyses in INS-1 832/13 cells indicated stress-associated reductions in PDX1 and FOXO1 protein expression, with trends toward partial preservation following metabolite treatment. The findings support a systems-level model in which microbial metabolites influence β-cell resilience through coordinated effects on transcriptomic state, metabolic viability, and protein-level regulation. However, the exploratory nature of the experimental validation and the limited number of biological replicates highlight the need for further mechanistic studies and larger-scale validation to clarify the therapeutic potential of microbial metabolites in diabetes-associated β-cell dysfunction.

Pathway enrichment analysis (PEA) is essential for translating transcriptomic data into biological insights. However, traditional mean-centric methods like Over-Representation Analysis (ORA) and Gene Set Enrichment Analysis (GSEA) often overlook the internal co-expression architecture of gene sets. This study evaluates these classical paradigms against GSCORE, a novel correlation-based enrichment engine, using colorectal cancer (CRC) data from the TCGA-COAD and TCGA-READ cohorts. 

Using a rigorous pipeline (DESeq2, VST), this study compared the performance of ORA, GSEA, and GSCORE across 647 primary tumor and 51 normal samples. While ORA and GSEA showed moderate congruence (𝐽𝑎𝑐𝑐𝑎𝑟𝑑 = 0.280 ) and captured standard hallmarks like cell cycle control, GSCORE identified a unique functional niche. It detected pathways with high co-expression density, such as the Golgi membrane and Nucleosome, which were entirely missed by classical analyses. 

Statistically, GSCORE demonstrated near-zero correlation with GSEA rankings (𝜌 = 0.086 ), confirming that it captures an orthogonal dimension of the transcriptome: connectivity density rather than distributional shifts. These findings suggest that while classical methods identify core disease signatures, correlation-based approaches like GSCORE reveal coordinated regulatory modules otherwise invisible to the researcher. Despite its computational complexity (𝑂(𝑛!)), GSCORE provides a high-sensitivity tool for detecting functional connectivity in the cancer transcriptome. 

Målet med denna studie är att jämföra WebAssembly med Rust gentemot Javascript där DOM-manipulationer fortfarande har ett fokus. Idag är Javascript det de facto språket som används på webben och diverse webbapplikationer. Det anses dock vara ineffektivt och opålitligt. Relativt nyligen har en föreslagen lösning tagits fram, nämligen WebAssembly. Det lovar nära native prestanda men har en omdiskuterad nackdel; inget stöd för direkt DOM-manipulation finns. För att mäta WebAssembly med Rust gentemot Javascript har ett kontrollerat experiment utformats, dock designat på ett sätt att simulera ett verkligt användningsområde genom varierande element och genererad mock-data. Studien avslutas med en analys av testdatan samt en diskussion om hur praktiskt användningen av Rust är på webben.

Background: Diabetes typ 2 is a chronic disease characterized by insulin resistance and impaired insulin secretion, resulting in elevated blood glucose levels. The condition can lead to serious complications such as cardiovascular disease, neuropathy, and renal impairment. The main risk factors are lifestyle-related, including physical inactivity, unhealthy diet, and obesity. Effective self-care is essential for achieving stable glycemic control and improving overall health and quality of life.

Aim: The aim of the literature study was to describe how patients with diabetes typ 2 experience lifestyle changes.

Method: The study was a qualitative literature review based on previous evidence-based research (Friberg, 2022b). The method focuses on individuals’ experiences and aims to increase the understanding of lifestyle changes in diabetes typ 2.

Findings: The results showed that lifestyle changes in diabetes typ 2 are influenced by knowledge, motivation, and support. Psychosocial factors and information from healthcare services played an important role in self-care and behavioral change.

Conclusion: Diabetes typ 2 has a long-term impact on individuals' lifestyles and requires extensive self-care that could be experienced as challenging. Lifestyle changes are influenced by knowledge, motivation, social support, and clear information from healthcare services. Person-centered and individually tailored support is essential to strengthen self-care.

Business Intelligence (BI) can help small and medium-sized enterprises (SMEs) improve decision-making through better access to data, reporting, and visualisation. However, BI initiatives in SMEs often face challenges related to limited resources, fragmented data, unclear business value, and weak integration into everyday work processes. This thesis investigates how a multi-tenant BI service for SMEs should be designed and managed to support cost-efficient onboarding, actual use in decision-making processes, and long-term sustainability. The study follows a Design Science Research approach combined with a qualitative method. Seven semi-structured interviews were conducted with BI specialists and SME representatives. The interview material was analysed thematically and used to formulate design requirements. These requirements were then operationalised in a framework, illustrated through a proof-of-concept, and evaluated through expert-based feedback. The findings show that a multi-tenant BI service should combine a standardized technical core with customer-specific configuration. The service should begin with business and data mapping, support trusted KPI definitions, connect dashboards to roles and decision routines, and be managed as a continuously evolving service. The thesis contributes a framework that links onboarding, usage, and long-term management in a coherent service model for BI in SMEs.

RUL prediction is a key in industrial maintenance with reducing costs and boosting reliability.Transformer models work good in this task where most studies look into accuracy and less into the uncertainty quality. This study investigates how model size and architectural complexity with transformer-based models affect prediction accuracy and uncertainty quantification quality in RUL prediction. Three transformer models with different complexity levels, small, medium and large is evaluated in to alongside a LSTM model as a benchmark on C-MAPSS dataset FD001 and FD004. Two uncertainty quantification methods, Stochastic Weight Averaging-Gaussian (SWAG) and deep ensembles is applied and evaluated using metrics for both prediction accuracy and uncertainty quality. The results show that increasing model size does not lead to consistently improved performance on either dataset. Deep Ensembles outperform SWAG when it comes to calibration and stability, giving coverage closer to the nominal level across different model sizes and datasets. The findings indicate a simpler model might be better in practice and what method to use for uncertainty quantification matters.

Geospatial data is typically fragmented across many independent collections, each with its own schema and naming conventions. Such data is most often stored as GeoJSON, a text format in which each record, called a feature, pairs ordinary attributes with a geometry, meaning the coordinates that place it on the map as a point, line, or area. Answering a natural language question over such fragmented data requires two steps: routing the question to the collection that holds the answer, and translating it into the spatial or attribute filtering query that retrieves the relevant data. This thesis builds and compares four LLM-based retrieval pipelines, one embedding-based and three structured. The first, Vector RAG, creates vector embeddings of every feature, then retrieves by matching the semantic similarity between the query and the feature vectors, with no discrete selection step. The other three (PageIndex, Graph-Indexed, and LLM-connected PostGIS) are structured pipelines that first select the relevant collection and then query it. PageIndex prompts the LLM to choose from a compact summary of all collections. Graph-Indexed encodes the collections’ metadata as a knowledge graph the LLM traverses using Cypher, the query language for graph databases. LLM-connected PostGIS loads the collections into PostGIS, the spatial extension for PostgreSQL, and has the LLM generate SQLqueries against it. The retrieval pipelines were evaluated using Claude Sonnet 4.6 on a benchmark of 199 author-written questions spanning five types (spatial radius, nearest-feature, attribute filter, conversational, and unanswerable), each paired with a deterministically computed groundtruth answer, drawn from 40 GeoJSON collections across five Danish municipalities. The decisive factor was less how a query was executed than whether the correct collection was selected in the first place, and selecting it reliably depended far more on how the routingindex was structured than on any agentic refinement. The strongest structured pipeline, PageIndex, matched Vector RAG without surpassing it, scoring 1.71 against 1.76 on a scalefrom 0 (incorrect) to 3 (perfect) assigned by an LLM judge, a gap too small to be statistically significant. Enriching the routing index produced almost all of the improvement, whereas adding an agentic loop yielded no significant gain on any structured pipeline and reduced quality on two, Graph-Indexed and PostGIS. The structured pipelines were not meaningfully slower than Vector RAG, yet consumed roughly three times as many tokens per question, so the choice between paradigms comes down to operational cost rather than answer quality.

Detta examensarbete åsyftade genom en enkätstudie att kartlägga hur Power BI-användare med erfarenhet av verktyget Copilot i Power BI uppfattar det, för att ge en indikation om hur verktyget upplevs. Resultatet förväntas vara värdefullt som underlag för företag med intresse av verktyget och för framtida forskning. Studien genomfördes med en webbenkät som delades ut i olika grupper med Power BI som tema, i olika sociala medier. Webbenkäten delades och var öppen under 2025 mellan 12e och 25e maj. Enkäten bestod av 111 respondenter som hade erfarenhet av Copilot i Power BI. Frågorna behandlar demografi, användande av Copilot, generativ AI generellt, användande av andra generativa AI-verktyg och uppfattningar av Copilot i Power BI utifrån de fyra aspekterna effektivitet, tillförlitlighet, datasäkert och påverkan på kompetensbehov. Studiens resultat av de fyra aspekterna visar att av de i urvalet som använt Copilot i Power BI så anser 42% att Copilot i Power BI kan eller redan har förbättrat deras effektivitet, 14,4% ansåg att materialet Copilot i Power BI generar inte är pålitligt, 54% anser att det finns en risk att Copilot i Power BI kan få åtkomst till eller kan dela känslig data och hälften instämde att Copilot i Power BI minskar behovet av vissa färdigheter som annars krävs för att använda Power BI.

Background: Mental health problems among adolescents are increasing, while boys seek support less often than girls. This may delay identification and intervention, highlighting the importance of the school nurse’s health-promoting role. This literature review examines factors that influence boys’ help-seeking behavior in relation to mental health problems.

Aim: The aim of this systematic literature review was to highlight factors influencing boys’ willingness to seek help from the school nurse in cases of mental health problems.

Method: A systematic literature review with an inductive approach was conducted according to Polit and Beck’s nine-step model. Nine quality-appraised articles were analyzed using thematic analysis to identify factors influencing boys’ willingness to seek support for mental health problems from the school nurse.

Findings: Two main themes emerged from the findings, showing that boys’ willingness to seek help from the school nurse for mental health problems is influenced by several interacting factors. Overall, individual, sociocultural, and professional factors interact and affect boys’ opportunities and willingness to seek support for mental health problems.

Conclusion: Boys’ willingness to seek help for mental health problems is influenced by individual, sociocultural, and professional factors. Norms surrounding masculinity and perceived stigma constitute significant barriers, while accessible and trusting relationships with the school nurse promote help-seeking. The findings highlight the need for targeted interventions within school health services to reduce barriers and strengthen boys’ willingness to seek support.

This study investigates how Western game developers can overcome cultural differences to achieve authentic cultural representation, using the French-developed kung fu game Sifu (Sloclap, 2022) as a case study. Through qualitative analysis of developer interviews, game design, and player reviews, this research identifies two key strategies for success. First, the deep integration of a cultural insider a Pak Mei master Benjamin Colussi ensured authenticity from martial arts movements to philosophical foundations. Second, the team translated cultural concepts into core game mechanics, such as an aging system that embodies the philosophy that "kung fu means time" and a "Wude" ending that transforms martial virtue into gameplay goals. A comparison with Sloclap's previous game Absolver (Sloclap, 2017) further reveals a strategic shift from a broad, style-agnostic combat arena to a focused, culturally-grounded narrative. The study find that respectful cross-cultural game design requires ceding cultural authority to insiders and creatively embedding cultural philosophy into interactive systems, offering a valuable framework for future projects.

The study highlights young adults’ experiences of growing up in areas classified by the police as particularly vulnerable, with recurring police presence, and how police presence and labelling from the surrounding community have influenced their self-image. The study is based on a qualitative approach, using semi-structured interviews with ten young adults aged 18–26 from areas in Gothenburg, Stockholm, Linköping and Malmö. The material was analysed using reflexive thematic analysis. The results show that recurring police presence could be experienced ambivalently, as it could both provide a sense of safety in relation to insecurity in the area and, at the same time, contribute to experiences of suspicion, control and being singled out. The participants also described how the classification of the area as particularly vulnerable could follow them outside their residential area of upbringing through the perceptions of others and media representations, which affected how they experienced being treated and how they related to themselves and others. At the same time, it emerged that not all participants were affected in the same way or to the same extent by these experiences. Community, shared experiences and resistance emerged as significant ways of managing and renegotiating labelling. The study shows that recurring police presence and labelling from the surrounding community can shape young adults’ self-image through suspicion, prejudice and negative expectations, but that the impact varies between participants and can also give rise to belonging, agency and motivation for change.

Introduction: Despite physical activity being a central determinant of good health, many adults of working age do not achieve the recommended levels of activity. Physical inactivity therefore constitutes a significant public health challenge and contributes to increased morbidity and societal economic costs. To understand adults’ opportunities for physical activity, a holistic perspective is required that includes both individual and structural factors. Aim: The aim of this literature study was to investigate which factors influence the opportunity for physical activity among adults of working age. Method: The study was conducted as a literature review based on systematic searches in the databases Web of Science and Medline (EBSCO). A total of 20 scientific original articles were included. The included articles were quality appraised and analyzed using an inductive thematic approach, where themes were identified based on the content of the material without predetermined categories. Results: The results showed that the opportunity for physical activity was shaped by a complex interaction between different factors at multiple levels. At the individual level, time constraints, health problems, and low motivation emerged as central barriers, while perceived health benefits and knowledge acted as facilitators. At the interpersonal level, social support and social norms had both facilitating and limiting effects. Organizational factors, such as working hours, workload, and access to health-promoting initiatives, influenced opportunities for activity. At the societal level, infrastructure, safety, economic resources, and cultural norms were identified as important factors. Conclusion: Physical activity among adults of working age is influenced by a complex interplay of individual, social, organizational, and societal factors. To promote physical activity, multifaceted interventions at multiple levels are therefore required, combining individual support with organizational and structural measures. 

Introduction: Involuntary loneliness is a public health problem that has consequences for public health and for the individual. Involuntary loneliness is an individual experience that stems from the individual’s social needs not being met. Involuntary loneliness occurs when social relationships don’t meet the individual’s needs. Older adults are particularly vulnerable to involuntary loneliness, which may be due to age-related changes such as deteriorating health, loss of partners and friends. There are knowledge gaps about which strategies older adults use to manage and reduce involuntary loneliness. Aim: The aim of the study was to investigate which strategies elderly people use to reduce and manage involuntary loneliness, highlighted in a Nordic perspective. Methods: The study was conducted as a structured literature study with a qualitative approach. The analysis method was a thematic analysis of ten quality- reviewed articles. Scientific articles were search in the databases MEDLINE (EBSCO) and Web of Science. Results: Thematic analysis was carried out and resulted in three main themes: social security, meaningful activities and social life, and personal autonomy. These were based on eight sub- themes: community belonging, routines, togetherness, places for social relationship, meaningful activity, choosing relationships yourself, new knowledge, self-confidence. Conclusion: The results from the study show that the strategies that older adults use are not in fact isolated from each other but interact with each other. Social security interacts in meaningful activities and social life which also interact in participation and independence. Social interaction such as small talk in local areas contributes to social security. Activities and hobbies create routines but also new knowledge that contributes to a sense of context. The study underlines the importance of designing cities and communities that enable social participations and independence well into old age.

Background: It is estimated that over 230 million girls have been subjected to female genital mutilation (UNICEF, 2024). Female genital mutilation is practiced in several part of the world, in line with increased migration, the tradition also occurs in Sweden, among others. According to the National Board of Health and Welfare (2023), it is estimated that 68 000 women have been subjected to female genital mutilation and around 13 000 to 23 000 girls are at risk of being subjected in Sweden. Which makes the issue relevant in the work of the school nurse, 

Aim: To describe the school nurse´s experiences of identifying girls who are at risk of or have been subjected to female genital mutilation. 

Method: Qualitative interviews, with 12 school nurses who participated from Götaland (region in southern Sweden) in Sweden. 

Findings: Three main categories emerged from the analysis: Strategy for identification, Challenges in the meeting, and Organization and the impact of the organization. 

Conclusion: School nurses experience showed that daring to ask questions, good relationships and raising the topic in health discussions, were important factors in the identification work to detect girls who were exposed to female genital mutilation. While lack of routines was a factor that made the work more difficult. 

Introduction: AI-generated health communication often maintains high technical quality, yet research indicates that trust diminishes once the source is identified. For public health practice, it is crucial to understand how AI linguistic patterns affect trust independently of source identity. 

Aim: To investigate and compare how recipients' perceived trust is affected by the design of health messages (AI vs. human) under blinded conditions. 

Methods: A quantitative study with a single-blind between-groups design was conducted (N = 150). Using convenience sampling, participants were assigned to evaluate either an AIgenerated or a human-authored text. Initial tests were performed to examine group comparability and variable reliability. Data were analyzed using independent t-tests, where technical attitude variables were treated separately. 

Results: The study observed significant differences in favor of the AI-generated message regarding total trust (p=.032), ease of use (p=.003) and expertise (p=.028). No significant difference could be detected for attractiveness or usefulness. Furthermore, the participants general attitude toward AI displayed no stattistically significant correlation with perceived trust (p=0.58). 

Conclusion: The results of the study indicate that the AI-generated message tended to be perceived as more trustworthy and professional than the human authored one within the investigated sample. However, due to differences in the age structure of the grops, the conclusions should be drawn with caution. Nevertheless, the results suggest that AI has potential as complement to public health communnication, provided that ethical transparency is considered.  

This study explores how players experience the balance between playfulness and scientific contribution within gameplay-driven citizen science systems. BioGo, a mobile serious game currently in development focused on species-identification and biodiversity documentation, was used as a case for examining this relationship. Six participants were observed, interviewed and asked to complete questionnaires while interacting with the application. Through a thematic analysis, four themes related to participant experience were identified. The results suggest that participants generally did not experience playfulness and scientific contribution as competing dimensions. Instead, a more dynamic relationship between the two was observed. Playfulness acted primarily as the source of engagement, while scientific contribution provided meaning and legitimacy to the experience. Additional observations highlight tensions related to gameplay systems, participation trust and perceptions of contribution. The findings provide implications for future design of gameplay-driven biodiversity citizen science applications and serious games.

Introduction: Digital health communication is widely used to influence knowledge, attitudes and health-related behaviours. Previous research shows that such communication is shaped by gendered norms and stereotypical assumptions about health, responsibility and the body. However, research on how sex and gender are constructed within the Swedish context is limited. Aim: The study explored how health, sex and gender are constructed in the digital health communication of the Rosa Bandet (Pink Ribbon) and Mustaschkampen (Blue Ribbon) campaigns using critical discourse analysis. Method: This study was conducted using a qualitative design and critical discourse analysis, based on Carol Bacchi’s “What’s the problem represented to be?” approach. The material mainly consisted of publicly available material from the Rosa Bandet and Mustaschkampen websites. The material examined problem representations, subject positions, silences and gendered formulation. The material was analysed using both deductive and inductive logic, in order to identify recurring themes in the communication. Results: The results showed that health was constructed as an individual responsibility but framed differently by gender. Rosa Bandet emphasised bodily vigilance, continuous self-monitoring and community, whereas Mustaschkampen highlighted simplified actions such as testing and donation. The results were organised using the different dimensions of Sense of coherence, SOC - meaningfulness, comprehensibility and manageability - to situate the findings within a salutogenic perspective. Communication patterns featured gendered symbols, simplified messages and silences around structural factors such as access to care and unequal health conditions. Conclusion: The study shows that the campaigns’ digital health communication not only provides information about health and cancer but also actively shape ideas about gender, responsibility and agency. These patterns risk reproducing gender norms and individualised understandings of health while obscuring structural perspectives.

With ever-evolving AI systems, game development has been permanently transformed. What originally took human developers and artists many hours to make, modern AI models can complete the same task in a fraction of the time. With such figures, it would be easy to assume that generative AI can completely take over game development from human hands. This notion is put to the test, examining the capabilities of current generative AI tools in the role of an autonomous developer and analyzing where and why human intervention is still necessary in a game development pipeline. The results show a big discrepancy in “perceived” AI efficiency vs its practical application; with humans still holding the keys to mainstream game productions.

Background: Mental ill health among upper secondary school students has increased and commonly includes stress, anxiety, low mood, and sleep difficulties. School nurses play a central role within student health services by identifying and supporting students with mental health problems at an early stage. However, there is limited knowledge re-garding school nurses’ experiences of this work.

Aim: The aim was to illuminate school nurses’ experiences of working with mental ill health among upper secondary school students.

Method: The study had a qualitative design with an inductive approach. Data were collected through a web-based questionnaire with open-ended questions answered by 20 school nurses working in upper secondary schools. The material was analysed using qualitative content analysis.

Findings: The results showed that mental ill health was identified through changes in students’ everyday functioning, health dialogues, and signals from school staff. Trust, supportive conversations, and collaboration were identified as central aspects of the work. Lack of time, limited resources, and unclear responsibilities in collaboration were described as significant challenges.

Conclusion: School nurses have an important role in promoting mental health and providing early support to upper secondary school students. To strengthen this work, organisational conditions that enable preventive work, continuity, and effective collab-oration within student health services are needed.

DEI (Diversity, Equity and Inclusion) has over recent decades developed into a central policy area within multinational companies and is often associated with both organizational legitimacy and social responsibility. At the same time, DEI has in recent years become increasingly politically and legally contested in the United States, where a growing backlash has changed the conditions for how organizations can conduct and communicate their work. This creates tensions for Swedish multinational companies that must balance global DEI policies with local institutional requirements in the U.S. context. The purpose of this study is therefore to analyze how Swedish multinational companies relate to the backlash against DEI policies in the United States and how organizations manage the tension between global DEI policies and local institutional conditions. The study was conducted using a qualitative research design and is based on semistructured interviews with HR professionals and individuals with insight into DEI work within six Swedish multinational companies operating in the United States. The empirical material was analyzed through thematic analysis using a deductive approach based on institutional theory, institutional duality, institutional complexity, and Oliver’s (1991) organizational strategies. The findings show that Swedish multinational companies manage the tension between global DEI policies and local institutional conditions by combining multiple organizational strategies simultaneously. Organizations adapt programs, language, and communication in order to ensure legal compliance and local legitimacy in the United States, while simultaneously attempting to uphold their global values and continue parts of their DEI work internally. The study demonstrates that DEI work is not abandoned, but rather reshaped in terms of expression, language, and visibility depending on the institutional context.

This thesis evaluates Sip2play, a mug-based tangible user interface designed as a game controller for supporting the intake of medication and supplements in liquid form among children. The system translates the physical act of drinking into real-time input for a mobile game. This study explores whether integrating gameplay into a routine health-related activity can reduce children’s rejection of medicine and support medication adherence. The system is analysed on a theoretical basis using two complementary human–computer interaction taxonomies. Fishkin’s taxonomy is applied to examine embodiment and metaphor. Rivière’s taxonomy is used to analyse the system’s physical and digital structure through the DTOC model and bodiness classifications. A mixed-methods user study with children was conducted using rating scales, interviews, and observations. Results show high levels of enjoyment and motivation, with generally positive usability feedback. Overall, Sip2play demonstrates the potential of tangible game-based interfaces to support engagement in health-related behaviours.

Serious games in the fields of education have typically been focused on the students learning, rather than the teacher’s teaching. This study explores the design and development of a serious game with the intention of integrating instructors into the gameplay and development process. The system is explored and then evaluated from a perspective of usability, in order to determine the practical value of developing such a system. Features present in the prototype were developed after the needs and suggestions of instructors working in collaboration with the development. The results show positive benefits of adding instructor-related features to the game, while at the same time highlighting issues with features and their practical use. Instructors present during development expressed great interest in further development, promoting that this kind of collaboration should be explored further to establish a clearer relationship between instructors and serious game development.

Samtidigt som spel blir mer inkluderande, utvecklas även deras karaktärsskapare. Trots det finns det begränsningar i karaktärsskapare, som kan göra det svårt för transpersoner och personer med könsöverskridande identitet att skapa en karaktär att relatera till och uppleva spelvärlden genom. I arbetet undersöks och dekonstrueras könsroller i spel för att testa arbetets problemformulering. En artefakt skapades för att ge transpersoner och personer med könsöverskridande identitet möjlighet att ge sina perspektiv och erfarenhet i karaktärsskapare. En semistrukturerad intervju genomfördes och resulterade i ett antal slutsatser: Respondenterna värdesätter möjligheten att skapa en karaktär de kan relatera till, samt möjligheten att utgå från en neutral karaktärsmodell.

This work researched the area of positive patterns to use when creating positive trans characters in video games. Trans characters in video games are few and often a misrepresentation which has negative consequences on trans people in real life as they can affirm negative stereotypes and stigma. When positively portrayed, it instead has positive consequences for trans people as well as how they are viewed. It analyzed three video games through content analysis based on the questioning framework used in previous research. Five patterns were found that outlines how a trans character can be represented in a positive light and why. Interviews and surveys were used to evaluate two texts, one where negative patterns were used and one with the positive ones and the participants preferred the text utilizing the positive patterns. The artefact for this thesis are the patterns that are outlined in a detailed manner with explanations. Future work would include a larger sample of games to analyse to further the framework, as well as a prototype to test the patterns within their environment, which is video games.

Introduction: Educational attainment (EA) is negatively associated with body mass index (BMI), but less is known about the association between EA and adult BMI change. We analysed the role of genetic and environmental factors in the associations between EA and BMI trajectory components over adulthood.

Data and methods: Pooled data from 59,490 twins aged 31–99 years (49% women) across 11 cohorts with EA and repeated measures of BMI were used. BMI trajectory components (baseline BMI and BMI change per decade) were estimated using linear mixed-effects (LME) and delta slope methods. EA was derived by regressing years of education on birth year and cohort. Associations between EA and BMI trajectories were evaluated with LME models in both cohort-specific and pooled data. Genetic and environmental contributions were evaluated using structural equation modelling.

Results: EA was more strongly negatively associated with baseline BMI and BMI change (mean of 1.31 and 1.32 kg/m2 per decade in men and women, respectively) in women (β = –0.14 kg/m², 95% CI: –0.15 to –0.12; β = –0.02 kg/m²/decade, 95% CI: –0.03 to –0.01, respectively) than in men (β = –0.07, 95% CI: –0.08 to –0.06; β = –0.01, 95% CI: –0.02 to –0.001, respectively). The associations between baseline BMI and EA were explained by genetic factors in men (r_A= –0.10) and by both genetic (r_A = –0.17) and unique environmental factors (r_E = –0.07) in women. For BMI change, the associations with EA were explained by genetic factors (r_A = –0.04 in men; –0.06 in women).

Conclusion: Individuals with higher EA tend to have lower baseline BMI and slower BMI increases across adulthood. These associations are primarily genetically mediated.

As many new anomaly detection algorithms emerge there is a need to evaluate them in real-world environments. This study evaluates the performance of different multivariate time-series anomaly detection algorithms applied to log data in an industrial setting. The models are trained, fine tuned and tested on two datasets, one provided by a company representing a real-world dataset and the second being the publicly available HAI Security dataset. As real-world industrial datasets are often unlabelled, clustering is used to create pseudo-labels for the company dataset. Model performance is evaluated using AUC-PR, AUC-ROC, and F1 score. The results indicate a significant difference in model performance across all metrics on both datasets, with LOF consistently achieving the best scores across both datasets. These results provide insights into the applicability of anomaly detection algorithms in real-world industrial environments, although future work is needed to address computational efficiency and real-world deployment evaluation with experts.

Background: Leadership in military and other high-risk environments places particular demands on trust between leaders and their followers. The Swedish Armed Forces highlights that an officer must build trust within one's group in order to overcome challenges together. Previous research has mainly focused on the soldiers' perceptions of what creates trust, where less attention has been brought to what military leaders actually do to build trust. Therefore, there is a need to study how officers experience and manage the process of building trust to their subordinates.

Purpose: The purpose of this study is to develop an understanding of how officers seek to build trust to conscripted and professional soldiers, and which factors may influence this process?

Research questions: How do officers describe their efforts to build trust with conscripts and professional soldiers, and which factors may influence this process?

Method: The study was based on a qualitative method, with seven semi-structured interviews as the main method for data collection, where the respondents were officers working in the Swedish Armed Forces. The collected data were analyzed using a thematic analysis. An abductive approach was applied to make optimal use of the empirical data.

Conclusion: The process of building trust differs between the different contexts. When working with conscripts, the officer needs to focus on maintaining trust, whereas with professional soldiers, the officer is required to establish and build trust. Due to the fact that officers perceive that conscripts show a higher initial level of trust than professional soldiers, which is partly due to the officers´ self-confidence, the conscripts´ limited knowledge of the organization, their position of dependency and their trust in the Swedish Armed Forces as an organization. For professional soldiers, initial trust is primarily influenced by prior experiences, shared background and prejudices. The results show that there are differences between the contexts in terms of what builds trust. However, some factors are shared across both contexts, namely demonstrated competence, relationship-building and honesty.

This thesis examines the factors shaping individual willingness to adopt Agentic AI (AAI) in marketing and sales within the European context. As AAI is still an emerging and relatively underexplored technology, the study addresses a gap in the literature by investigating how organisational conditions, individual perceptions, and emotional responses influence adoption in practice. The research adopts an exploratory qualitative design based on 11 semi-structured interviews with professionals from firms across different European industries. The data were analysed thematically and used to develop the AAI Context-Emotion ACE Model, an original framework that integrates macro-level contextual factors with micro-level cognitive and emotional mechanisms.

The findings suggest that AAI adoption is influenced by the immaturity of the technology, organisational readiness, regulatory pressure, and market dynamics, as well as by perceived risk, effort expectancy, and performance expectancy. These factors give rise to two contrasting emotional orientations: scepticism, rooted in uncertainty and operational concern, and enthusiasm, driven by expectations of efficiency, strategic value, and growth. In addition, the study identifies three individual modifiers – age, professional role, and personal traits – that shape how AAI is interpreted and evaluated within organisations. Overall, the thesis demonstrates that AAI adoption is not only a structural or technological process, but also a deeply human and emotional one, shaped by the interaction between context and individual interpretation.

This thesis examines gender in gaming and how social identity theory and gender bias affect the targeted audiences of marketing campaigns. Women gamers make up about half of all gamers, yet receive less attention from marketers. Additionally, when marketers do focus on women, they are marketed stereotypically “girly” games, such as “casual”, “cosy”, and domestic chore games.

Women are often viewed as less capable, less competitive, and less serious about gaming. Video games have historically been perceived as masculine, placing them into male gender roles. While gender is a social construct and is something that you do rather than are, falling outside of this can lead to questioning one’s social identity. This questioning can lead some members to shed a role, such as gaming identity, to better fit into their other roles, such as gender identity.

This thesis incorporates a social constructionist ontological viewpoint and an interpretivist epistemological stance. Anonymous semi-structured interviews generated qualitative research data to identify patterns in the gaming industry on gender-targeted and gender-neutral marketing.

The findings suggest that larger companies are more likely to use demographic data in audience segmentation, whereas smaller companies often rely on community engagement and comparisons with similar titles. Despite claims of gender neutrality, marketing decisions frequently remained influenced by genre conventions, historical industry norms, and assumptions regarding gaming audiences.

This study contributes to the literature on gender, marketing, and digital technologies within the gaming sector by demonstrating how gendered assumptions may persist within marketing decision-making through established industry practices and audience construction processes. The findings further suggest that reliance on established marketing conventions may reproduce gendered industry norms while limiting opportunities for competitive differentiation.

This thesis is a qualitative study based on seven semi-structured interviews with managers in different organizational contexts. The goal is to have a better understanding of how managers view the impact of digitalization on their work with performance evaluation and employee follow-up. The study is guided by the research question: How do managers perceive and describe that digitalization has affected their work with follow-up and evaluation of employees? The interview material was analyzed using thematic analysis to identify recurring patterns and variations in managers’ experiences, with focus on digital tools, assessment bases, communication, and the balance between control and support.

Results and conclusion

The results show that digital tools frequently serve as a crucial infrastructure for follow-up and evaluation, improving managerial overview and traceability. However, data that can be measured does not fully show performance, so professional judgment, contextual interpretation, and communication are crucial. The study also demonstrates that while digital feedback might increase productivity, it may also lead to more misunderstandings when social cues and nuance are reduced. The general conclusion is that the effects of digitalization have non-uniform effects: the same tools can be regarded as both controlling and helpful, and perceived legitimacy is highly dependent on discourse, channel choice, transparency, and appropriate follow-up intensity.

Background: Digitalisation and the increase in remote and hybrid work have changed the conditions for how managers lead, coordinate and follow up employees. When work is carried out through digital systems, new opportunities for structure and overview arise, but also challenges related to trust, visibility and control.

Purpose: The purpose of this study was to examine how managers design management control and follow-up of employees in digitalised work environments where work is performed fully or partly remotely.

Method: The study was conducted as a qualitative interview study based on semi-structured interviews with nine managers from different types of organisations. The material was analysed thematically and interpreted in relation to the study’s theoretical framework.

Results: The results show that management control is mainly designed through clear goals, distribution of responsibility, meeting routines and digital communication channels. Follow-up is carried out through results, digital visibility, meetings and dialogue. Digital tools are used to create overview and coordination, but they do not replace managerial judgment or the relationship with employees.

Conclusion: The study shows that digital management control and follow-up need to be understood as a balance between structure, visibility and trust. Digital tools can support managers’ work, but their meaning depends on how they are used and the organizational context in which they are applied.

The purpose of this study is to investigate and create a greater understanding of how first-line managers within the Swedish correctional system manage the demands and resources of the work in a context characterized by emotional labor. Special focus has been placed on how managers regulate emotions in their professional role and which coping strategies they use to manage stress and emotional strain.

The study has been carried out using a qualitative method where eight semi-structured interviews were conducted with first line managers active in some of the correctional service’s operational areas in Western Sweden. The empirical data was analyzed thematically based on theories of emotional labor and coping strategies.

The results show that the role of first-line manager involves a complex work situation requiring the balancing of organizational demands, personnel responsibilities, and responsibility for incarcerated individuals. The respondents state that they basically need to regulate their emotions on a daily basis through both surface and deep acting in order to be perceived as professional and legitimate in the professional role. Problem-focused coping strategies that include planning, structure and social support appear to be the most sustainable over time, while emotion-focused strategies such as avoidance and distancing increase the risk of emotional burnout in the long term.

The study contributes to increased understanding of the psychosocial work environment of first-line managers in correctional services and shows the importance of organizational support to prevent stress and emotional burnout.

Artificial intelligence (AI) has recently taken an increasingly important role in improving the efficiency of the recruitment process. At the same time, previous research indicates that AI systems are not always entirely neutral in recruitment systems. This is because the systems have been trained on historical data and human intelligence, which has created bias and skewed results. Despite this, there is limited knowledge about how recruiters preferences influence the use of AI in the recruitment process, and whether the interaction between the recruiter and AI can contribute to bias. The study used a qualitative methodology involving semistructured interviews with 12 recruiters and one software developer who have experience with AI in recruitment. The study shows that AI is primarily used as support in the early stages of the recruitment process, with humans remaining the final decision makers. Furthermore, the study shows that AI systems are not always perceived as reliable and objective, due to the risk of existing bias in the systems design. It also emerges that the recruiters preferences influence how AI systems are used and how recommendations are interpreted. The study indicates that bias does not stem from one part or the other, but rather from the interaction between the recruiter and the system.

Colorectal cancer remains a major cause of cancer-related morbidity and mortality, and improved blood-based biomarkers are needed to support earlier diagnosis, better disease classification, and improved treatment strategies. This study aimed to evaluate plasma protein signatures capable of discriminating colorectal cancer from other cancer types in a pan-cancer setting. Public proximity extension assay plasma proteomics data from 1,477 cancer patients representing 12 cancer types and 1,463 proteins were analysed. After preprocessing, exploratory analysis, differential expression analysis, and functional enrichment analysis, three supervised machinelearning methods were evaluated: Elastic Net, Random Forest, and support vector machine with radial basis function kernel. Full-proteome Elastic Net and support vector machine models showed the strongest imbalanced test-set performance, with AUC values of 0.988 and 0.983, respectively. Reduced-panel analyses showed that the colorectal cancer-associated signal could be compressed, but not reduced indefinitely. A 30-protein consensus panel retained strong discrimination, whereas a seven-protein shared panel preserved only limited threshold-based classification utility. Balanced analyses further showed that reduced-panel performance depended on panel size and feature-ranking strategy. Larger Elastic Net-ranked panels performed strongest from 20 proteins onward in balanced repeated cross-validation, with the top-100 Elastic Net-ranked panel evaluated using support vector machine with radial basis function kernel achieving the highest mean AUC of 0.995. Very small panels were better supported by Random Forest, support vector machine, or mean-ranked feature selection. Overall, plasma protein profiles discriminated colorectal cancer from other cancer types, but performance depended on retaining enough complementary protein information and matching feature-selection strategy to panel size and classifier. 

Digitalization and artificial intelligence (AI), have changed how service work is carried out. In service work, AI can be used to make work more efficient, search for information more quickly and reduce certain administrative tasks. At the same time, AI can also raise questions and uncertainty about how work roles and work tasks may change in the future. This study aims to examine how employees experience the integration of AI in service work, as well as which opportunities and challenges it presents for bank advisors and specialist consultants. The study examines this through three different frameworks: The Technology Acceptance Model (TAM), The Unified Theory of Acceptance and Use of Technology (UTAUT) and job insecurity. Based on these models and concept as a framework, a qualitative method with semi-structured interviews was used. In total, 14 interviews were conducted, with 7 employees from each industry. The results show that AI is primarily experienced as a support in work. The employees describe that AI can save time, make it easier to find information and help with administrative and more knowledge-based tasks. At the same time, there are challenges, for example that employees do not always fully trust AI that the technology can be difficult to use and that there is some concern about how work may change. The analysis shows that AI is used and experienced in different ways in the two industries. For the bank advisors AI is mostly used as a tool before or after customer meetings, while for the specialist consultants AI is used more in daily work. The conclusion is that AI can be a valuable support in service work, but that the technology needs to be adapted to the industry, work tasks and employees needs. AI works best when it helps employees without removing their own responsibility, judgement or importance in the meeting with the customer. 

Hybrid work has become an established form of work in many organizations, which means that work takes place both at the physical workplace and remotely. The change does not only affect where work is performed but also changes the structure and processes of the organizational culture – how it is created, expressed and maintained – in the hybrid work context. The study is based on Schein’s (2004; 2010) analytical model of the levels of organizational culture and Alvesson’s (2013; 2015) perspective on organizational culture as a sensemaking process. The purpose of the present study is to analyze managers’ own experience of organizational culture in relation to hybrid work, with a focus on the challenges and opportunities they experience in maintaining a shared organizational culture.

The present study is based on a qualitative method, where twelve managers in the private service sector were interviewed through semi-structured interviews. A thematic analysis of the interview material has been performed to identify recurring patterns and themes, where the theoretical framework formed the basis for the design of the main themes of the empirical work, which are then reconnected to the analysis.

The result shows that the organizational culture in hybrid work contexts increasingly needs to be maintained through active and conscious actions. When spontaneous interaction, informal conversations and physical sensory impressions decrease, managers play a more central role in interpreting, carrying and conveying the organizational culture. The present study also shows that aspects of organizational culture that were previously implied now require formal processes of sensemaking to become more visible in hybrid work.

Background: The Swedish Armed Forces is a complex organization where cooperation between individuals is central, which makes the relationship between manager and employee meaningful. In organizational contexts, trust can be seen as a central aspect of the relationship between the manager and the employee. Trust is also a complex and changing phenomenon that is influenced by factors such as the manager´s behavior, social exchanges between manager and employee, and how it develops over time.

Purpose: The purpose of this study is to examine how leaders’ behaviors within the Swedish Armed Forces are perceived to contribute to shaping employees’ trust in their leader. This is based on the employees’ own experiences and aims to develop an understanding of how these experiences can be interpreted in relation to trust and relationship-building behaviors.

Method: This study used a qualitative method. The data was collected through semi-structured interviews with 12 employees who work as soldiers within the Swedish Armed Forces. The collected data was analyzed using a thematic analysis where main themes and patterns were identified and categorized, with support from theory about trust and social exchange.

Conclusion: The results of the study show that the employees trust is influenced by how the manager's behavior is experienced in practice. The manager’s competence, goodwill and integrity are seen as central factors for creating and maintaining trust. The result also shows that trust develops over time through a mutual social exchange between manager and employee, where balance in the relationship contributes to increased trust.

Governance in the public sector has become increasingly complex in recent decades, as demands for control, monitoring, and accountability coexist with a growing emphasis on trust and professional discretion. Although trust-based governance is promoted as a central ideal, extensive control structures remain, partly rooted in historically established practices and governance ideals. This tension is particularly evident within the Swedish Prison and Probation Service, a safety-critical organization characterized by strong requirements for legal certainty and documentation. The aim of this study is to explore how first-line managers within the Swedish Prison and Probation Service navigate the tension between trust and control in their everyday leadership practices, and how leadership is shaped by institutional conditions.

The study adopts a qualitative case study approach, with empirical data collected through semi-structured interviews and analyzed using neo-institutional theory and paradox theory. The findings show that trust and control do not appear as opposites in practice, but rather as intertwined and interdependent dimensions of managerial work. At the same time, the findings demonstrate that this relationship is shaped by previously established structures and institutionalized beliefs that continue to influence how managers interpret and manage their discretion. Control emerges as a necessary condition linked to accountability and legal requirements, while trust is associated with professional judgement and discretion. Furthermore, the study shows that managers handle the tension through different forms of paradox work, shifting between separation, integration, and acceptance depending on the situation. The study thereby contributes to an increased understanding of how trust-based governance is practiced in a context where control is strongly institutionalized, while also highlighting that the tension between trust and control contributes a central and enduring part of managers' daily leadership, shaped by both contemporary governance demands and historically established ways of organizing and managing work.

Denna studie undersöker svarstider mellan Node.js (Express) och PHP (Laravel) i kontextet av e-bokstjänster. Genom ett kontrollerat experiment implementerades två funktionellt identiska REST-API:er, där mätningar av responstid och belastning genomfördes under varierande datamängder baserade på ett realistiskt dataset för e-bokstjänster. Resultatet visar att Express hade en betydligt lägre svarstid under låg till medelhög belastning. Vid större datamängder per anrop sker däremot en konvergens i svarstid där Express kan begränsas, medan Laravel visar en mer linjär och stabil skalbarhet. Slutsatsen visar att valet av ramverk är avgörande för systemets stabilitet beroende på den förväntade datavolymen. Framtida forskning bör inkludera upprepning av experimentet allteftersom PHP genomgår ytterligare exekveringsoptimeringar, samt utforska integrationen av artificiell intelligens för utveckling av autonom optimering av resurshantering.