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Products 1.618

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The development and validation of a five factor model of sources of self-efficacy in clinical nursing education

Background: The aim of this study is to validate a newly developed nurses' self-efficacy sources inventory. We test the validity of a five-dimensional model of sources of self-efficacy, which we contrast with the traditional four-dimensional model based on Bandura's theoretical concepts. Methods: Confirmatory factor analysis was used in the development of the newly developed self-efficacy measure. Model fit was evaluated based upon commonly recommended goodness-of-fit indices, including the χ2 of the model fit, the Root Mean Square Error of approximation (RMSEA), the Tucker-Lewis Index (TLI), the Standardized Root Mean Square Residual (SRMR), and the Bayesian Information Criterion (BIC). Results: All 22 items of the newly developed five-factor sources of self-efficacy have high factor loadings (range .40-.80). Structural equation modeling showed that a five-factor model is favoured over the four-factor model. Conclusions and implications: Results of this study show that differentiation of the vicarious experience source into a peer- and expert based source reflects better how nursing students develop self-efficacy beliefs. This has implications for clinical learning environments: a better and differentiated use of self-efficacy sources can stimulate the professional development of nursing students.

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The development and validation of a five factor model of sources of self-efficacy in clinical nursing education

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Measurement errors in roentgen-stereophotogrammetric joint motion analysis

AbstractIn many biomechanical motion studies, kinematic parameters are estimated from position measurements on a number of landmarks. In the present investigation, dummy motion experiments are performed in order to study the error dependence of kinematic parameters on geometric factors (number of markers, isotropic vs anisotropic landmark distributions, landmark distribution size), on kinematic factors (rotation step magnitude, the presence of translational displacements, the distance of the landmarks' mean position to the rotation axis), and on anisotropically distributed measurement errors. The experimental results are compared with theoretical predictions of a previous error analysis assuming isotropic conditions for the measurement errors and for the spatial landmark distribution. In general, the experimental findings agree with the predictions of the error model. The kinematic parameters such as translations and rotations are well-determined by the model. In the helical motion description, the same applies for the finite rotation angle about and the finite shift along the helical axis. However, the direction and position of the helical axis are ill-determined. An anisotropic landmark distribution with relatively few markers located in the direction of the rotation axis will even aggravate the ill-posed nature of the finite helical axis estimation.

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Cross-classified multilevel models improved standard error estimates of covariates in clinical outcomes – a simulation study

ObjectiveTo compare estimates of effect and variability resulting from standard linear regression analysis and hierarchical multilevel analysis with cross-classified multilevel analysis under various scenarios.Study design and settingWe performed a simulation study based on a data structure from an observational study in clinical mental health care. We used a Markov chain Monte Carlo approach to simulate 18 scenarios, varying sample sizes, cluster sizes, effect sizes and between group variances. For each scenario, we performed standard linear regression, multilevel regression with random intercept on patient level, multilevel regression with random intercept on nursing team level and cross-classified multilevel analysis.ResultsApplying cross-classified multilevel analyses had negligible influence on the effect estimates. However, ignoring cross-classification led to underestimation of the standard errors of the covariates at the two cross-classified levels and to invalidly narrow confidence intervals. This may lead to incorrect statistical inference. Varying sample size, cluster size, effect size and variance had no meaningful influence on these findings.ConclusionIn case of cross-classified data structures, the use of a cross-classified multilevel model helps estimating valid precision of effects, and thereby, support correct inferences.

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Cross-classified multilevel models improved standard error estimates of covariates in clinical outcomes – a simulation study

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Intra-assessor reliability and measurement error of ultrasound measures for foot muscle morphology in older adults using a tablet-based ultrasound machine

Background To gain insight into the role of plantar intrinsic foot muscles in fall-related gait parameters in older adults, it is fundamental to assess foot muscles separately. Ultrasonography is considered a promising instrument to quantify the strength capacity of individual muscles by assessing their morphology. The main goal of this study was to investigate the intra-assessor reliability and measurement error for ultrasound measures for the morphology of selected foot muscles and the plantar fascia in older adults using a tablet-based device. The secondary aim was to compare the measurement error between older and younger adults and between two different ultrasound machines. Methods Ultrasound images of selected foot muscles and the plantar fascia were collected in younger and older adults by a single operator, intensively trained in scanning the foot muscles, on two occasions, 1–8 days apart, using a tablet-based and a mainframe system. The intra-assessor reliability and standard error of measurement for the cross-sectional area and/or thickness were assessed by analysis of variance. The error variance was statistically compared across age groups and machines. Results Eighteen physically active older adults (mean age 73.8 (SD: 4.9) years) and ten younger adults (mean age 21.9 (SD: 1.8) years) participated in the study. In older adults, the standard error of measurement ranged from 2.8 to 11.9%. The ICC ranged from 0.57 to 0.97, but was excellent in most cases. The error variance for six morphology measures was statistically smaller in younger adults, but was small in older adults as well. When different error variances were observed across machines, overall, the tablet-based device showed superior repeatability. Conclusions This intra-assessor reliability study showed that a tablet-based ultrasound machine can be reliably used to assess the morphology of selected foot muscles in older adults, with the exception of plantar fascia thickness. Although the measurement errors were sometimes smaller in younger adults, they seem adequate in older adults to detect group mean hypertrophy as a response to training. A tablet-based ultrasound device seems to be a reliable alternative to a mainframe system. This advocates its use when foot muscle morphology in older adults is of interest.

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Intra-assessor reliability and measurement error of ultrasound measures for foot muscle morphology in older adults using a tablet-based ultrasound machine

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Projects 15

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AI-enhanced Data Analysis

Developing a framework that integrates Advanced Language Models into the qualitative research process.Qualitative research, vital for understanding complex phenomena, is often limited by labour-intensive data collection, transcription, and analysis processes. This hinders scalability, accessibility, and efficiency in both academic and industry contexts. As a result, insights are often delayed or incomplete, impacting decision-making, policy development, and innovation. The lack of tools to enhance accuracy and reduce human error exacerbates these challenges, particularly for projects requiring large datasets or quick iterations. Addressing these inefficiencies through AI-driven solutions like AIDA can empower researchers, enhance outcomes, and make qualitative research more inclusive, impactful, and efficient.The AIDA project enhances qualitative research by integrating AI technologies to streamline transcription, coding, and analysis processes. This innovation enables researchers to analyse larger datasets with greater efficiency and accuracy, providing faster and more comprehensive insights. By reducing manual effort and human error, AIDA empowers organisations to make informed decisions and implement evidence-based policies more effectively. Its scalability supports diverse societal and industry applications, from healthcare to market research, fostering innovation and addressing complex challenges. Ultimately, AIDA contributes to improving research quality, accessibility, and societal relevance, driving advancements across multiple sectors.

Ongoing

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Bottom-up initiatieven in stedelijke gebiedsontwikkeling

Een bottom-up-initiatief is een project dat niet vanuit de overheid of instellingen (top) wordt gestart maar vanuit burgers of eindgebruikers (bottom). We kijken in dit onderzoek naar theorieën die de bottom-up-aanpak ondersteunen. Ook doen we aanbevelingen om bottom-up initiatieven beter en sneller te laten verlopen.Doel Het doel van dit onderzoek is om nieuwe theoretische inzichten en strategieën te ontwikkelen voor stedelijke gebiedsontwikkeling. Hierbij is een sterke focus op de bottom-up aanpak. Dit houdt in dat er gekeken wordt naar initiatieven en ideeën van gebruikers of burgers (bottom) in plaats van de plannen van de overheid of instellingen (top). De bottom-up aanpak heeft veel toegevoegde waarde, maar initiatiefnemers ervaren nog veel belemmeringen. Dit onderzoek wil bijdragen aan het verminderen van die belemmeringen. Resultaten Dit onderzoek loopt. Na afloop vind je hier een samenvatting van de resultaten. Looptijd 01 september 2017 - 01 september 2021 Aanpak Achter bottom-up processen in gebiedsontwikkeling zit nu vaak weinig theorie. Het zijn intuïtieve, trial-and-error processen. Eindgebruikers en burgers werken samen met professionele partijen maar dit is nu nog niet echt gestroomlijnd. Daarom kijken we hoe partijen samenwerken en waar verbeteringen mogelijk zijn. Deze kennis gebruiken we om een theoretische en wetenschappelijke basis voor bottom-up gebiedsontwikkeling te leggen. Hierin komt naar voren welke factoren gaan bepalen of een project succesvol zal zijn. Met deze inzichten kunnen bijvoorbeeld nieuwe strategieën ontwikkeld worden, die een combinatie kunnen zijn tussen een bottom-up en een top-down aanpak.

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COP in de HU

Hogeschool Utrecht en politie Midden-Nederland werken samen in een community of practice om politiemedewerkers te professionaliseren en studenten te enthousiasmeren voor een carrière bij de politie. In COP komen deze activiteiten samen.Doel Vanuit een convenant tussen politie Midden-Nederland, lectoraat Kennisanalyse Sociale Veiligheid en het Instituut voor Veiligheid komen politiepraktijk, onderzoek en onderwijs samen in een community of practice. De politie wil bijscholing op onderwerpen waar de HU expertise heeft. Daarnaast krijgen studenten een unieke inkijk in de politiepraktijk waardoor de instroom van nieuwe politieprofessionals wordt vergroot. Relevantie “Door afstemming over belangrijke maatschappelijke thema’s in het veiligheidsdomein met de politie en ketenpartners zal er meer direct relevant, praktijkgericht onderzoek worden gedaan. De samenwerking biedt ons verder mogelijkheden om potentiële politiemedewerkers en talenten te werven en om studenten te helpen in hun eigen ontwikkeling.” (Politie Midden-Nederland) Activiteiten Vakdagen voor hulpofficieren van justitie & onderzoek naar hun ontwikkelbehoeften; Onderzoek naar ontwikkelbehoeften van operationeel experts; Werven in de wijk; Doorlopend studentonderzoek in verschillende politieteams: in beeld brengen wat jongvolwassenen weerhoudt of juist aantrekt om bij de politie te gaan werken Ook zo nieuwsgierig naar wat de politie nu allemaal écht doet? COP Talks: Tijdens COP Talks krijg je een exclusieve kijk in de keuken van deze bijzondere organisatie. Voor HU-studenten door politieprofessionals: De tramaanslag; Terrorisme in beeld; Achter de zedenzaak. COP Walks: Excursies naar de politie: studenten zien en horen de praktijk van binnenuit; Utrecht-Zuid – gebiedsgebonden politiewerk; Amersfoort – grootschalig optreden en evenementen. Almere – cold case team. 4x per jaar Platform Paardenveld waarin dragers van het convenant uitwisselen over actuele thema’s en gezamenlijke activiteiten. Studentopdrachten Wij zijn graag ‘makelaar’ tussen politiepraktijk en studenten. Heb je een mooie stageopdracht of onderzoeksvraag? Neem dan contact met ons op. Looptijd 01 januari 2022 - 31 december 2025

Ongoing

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Defending against Implementation attackS Through mAchiNe learning Techniques

Today, embedded devices such as banking/transportation cards, car keys, and mobile phones use cryptographic techniques to protect personal information and communication. Such devices are increasingly becoming the targets of attacks trying to capture the underlying secret information, e.g., cryptographic keys. Attacks not targeting the cryptographic algorithm but its implementation are especially devastating and the best-known examples are so-called side-channel and fault injection attacks. Such attacks, often jointly coined as physical (implementation) attacks, are difficult to preclude and if the key (or other data) is recovered the device is useless. To mitigate such attacks, security evaluators use the same techniques as attackers and look for possible weaknesses in order to “fix” them before deployment. Unfortunately, the attackers’ resourcefulness on the one hand and usually a short amount of time the security evaluators have (and human errors factor) on the other hand, makes this not a fair race. Consequently, researchers are looking into possible ways of making security evaluations more reliable and faster. To that end, machine learning techniques showed to be a viable candidate although the challenge is far from solved. Our project aims at the development of automatic frameworks able to assess various potential side-channel and fault injection threats coming from diverse sources. Such systems will enable security evaluators, and above all companies producing chips for security applications, an option to find the potential weaknesses early and to assess the trade-off between making the product more secure versus making the product more implementation-friendly. To this end, we plan to use machine learning techniques coupled with novel techniques not explored before for side-channel and fault analysis. In addition, we will design new techniques specially tailored to improve the performance of this evaluation process. Our research fills the gap between what is known in academia on physical attacks and what is needed in the industry to prevent such attacks. In the end, once our frameworks become operational, they could be also a useful tool for mitigating other types of threats like ransomware or rootkits.

Ongoing

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Development of ROS1-positive cell lines to improve personalized therapy in lung cancer patients

Every year in the Netherlands around 10.000 people are diagnosed with non-small cell lung cancer, commonly at advanced stages. In 1 to 2% of patients, a chromosomal translocation of the ROS1 gene drives oncogenesis. Since a few years, ROS1+ cancer can be treated effectively by targeted therapy with the tyrosine kinase inhibitor (TKI) crizotinib, which binds to the ROS1 protein, impairs the kinase activity and thereby inhibits tumor growth. Despite the successful treatment with crizotinib, most patients eventually show disease progression due to development of resistance. The available TKI-drugs for ROS1+ lung cancer make it possible to sequentially change medication as the disease progresses, but this is largely a ‘trial and error’ approach. Patients and their doctors ask for better prediction which TKI will work best after resistance occurs. The ROS1 patient foundation ‘Stichting Merels Wereld’ raises awareness and brings researchers together to close the knowledge gap on ROS1-driven oncogenesis and increase the options for treatment. As ROS1+ lung cancer is rare, research into resistance mechanisms and the availability of cell line models are limited. Medical Life Sciences & Diagnostics can help to improve treatment by developing new models which mimic the situation in resistant tumor cells. In the current proposal we will develop novel TKI-resistant cell lines that allow screening for improved personalized treatment with TKIs. Knowledge of specific mutations occurring after resistance will help to predict more accurately what the next step in patient treatment could be. This project is part of a long-term collaboration between the ROS1 patient foundation ‘Stichting Merels Wereld’, the departments of Pulmonary Oncology and Pathology of the UMCG and the Institute for Life Science & Technology of the Hanzehogeschool. The company Vivomicx will join our consortium, adding expertise on drug screening in complex cell systems.

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Effectief burgerschapsonderwijs over maatschappelijk gepolariseerde vraagstukken

Burgerschapsonderwijs wordt in een polariserende samenleving steeds belangrijker. Een uitdaging is het bespreken van maatschappelijk gepolariseerde vraagstukken, zoals zwarte piet, terrorisme en migratie, en daarmee bij te dragen aan de burgerschapsvorming van jongeren. Docenten zijn zoekende naar manieren om deze onderwerpen te behandelen. Met dit onderzoek willen we meer inzicht krijgen in de manieren waarop docenten vorm kunnen geven aan kritische dialogen over maatschappelijke gepolariseerde vraagstukken. Er wordt daarbij specifiek aandacht besteed aan het aanleren van basisvaardigheden en -houdingen voor dialoog. Een consortium van HvA, UvA, scholen van onder meer de Scholenpanels Burgerschap, de NVLM, VGN en Dialooggroep Burgerschap Amsterdam, gaat een interventie ontwikkelen gericht op het bespreken van deze onderwerpen voor alle maatschappijvakken in vmbo en havo/vwo. In het project wordt onderzocht wat de effecten zijn van de interventie op het burgerschap van leerlingen waarbij docenten hebben deelgenomen aan een professionaliseringstraject. In fase 1 van het project wordt, uitgaande van de kaders van de wetenschappelijke literatuur, samen met expertdocenten een prototype van de interventie bestaande uit handelingsprotocollen (gericht op basisvaardigheden en -houdingen voor dialoog), lessenseries (gericht op het voeren van kritische dialogen over maatschappelijk gepolariseerde vraagstukken) en een professionaliseringstraject ontwikkeld. In fase 2 worden interventie en professionaliseringstraject uitgeprobeerd, geëvalueerd en bijgesteld. In fase 3 wordt de effectiviteit van de ontwikkelde interventie onderzocht onder een grote groep docenten en leerlingen in een quasi-experimenteel design met een voormeting, nameting, retentiemeting en controlegroep. Het onderzoek levert kennis op over hoe docenten maatschappelijke gepolariseerde vraagstukken effectief kunnen inzetten om de burgerschapsvorming van leerlingen te bevorderen. Daarbij levert het project evidence-based handelingsprotocollen, lessenseries en een professionaliseringstraject op voor docenten van de maatschappijvakken in het voortgezet onderwijs. De lesmaterialen zijn zo vormgegeven dat ze toepasbaar zijn bij uiteenlopende maatschappelijk gepolariseerde vraagstukken die docenten in hun lessen aan de orde willen stellen.

Ongoing

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Encryption for all

This project addresses the fundamental societal problem that encryption as a technique is available since decades, but has never been widely adopted, mostly because it is too difficult or cumbersome to use for the public at large. PGP illustrates this point well: it is difficult to set-up and use, mainly because of challenges in cryptographic key management. At the same time, the need for encryption has only been growing over the years, and has become an urgent problem with stringent requirements – for instance for electronic communication between doctors and patients – in the General Data Protection Regulation (GDPR) and with systematic mass surveillance activities of internationally operating intelligence agencies. The interdisciplinary project "Encryption for all" addresses this fundamental problem via a combination of cryptographic design and user experience design. On the cryptographic side it develops identity-based and attribute-based encryption on top of the attribute-based infrastructure provided by the existing IRMA-identity platform. Identity-based encryption (IBE) is a scientifically well-established technique, which addresses the key management problem in an elegant manner, but IBE has found limited application so far. In this project it will be developed to a practically usable level, exploiting the existing IRMA platform for identification and retrieval of private keys. Attribute-based encryption (ABE) has not reached the same level of maturity yet as IBE, and will be a topic of further research in this project, since it opens up attractive new applications: like a teacher encrypting for her students only, or a company encrypting for all employees with a certain role in the company. On the user experience design side, efforts will be focused on making these encryption techniques really usable (i.e., easy to use, effective, efficient, error resistant) for everyone (e.g., also for people with disabilities or limited digital skills). To do so, an iterative, human-centred and inclusive design approach will be adopted. On a fundamental level, scientific questions will be addressed, such as how to promote the use of security and privacy-enhancing technologies through design, and whether and how usability and accessibility affect the acceptance and use of encryption tools. Here, theories of nudging and boosting and the unified theory of technology acceptance and use (known as UTAUT) will serve as a theoretical basis. On a more applied level, standards like ISO 9241-11 on usability and ISO 9241-220 on the human-centred design process will serve as a guideline. Amongst others, interface designs will be developed and focus groups, participatory design sessions, expert reviews and usability evaluations with potential users of various ages and backgrounds will be conducted, in a user experience and observation laboratory available at HAN University of Applied Sciences. In addition to meeting usability goals, ensuring that the developed encryption techniques also meet national and international accessibility standards will be a particular point of focus. With respect to usability and accessibility, the project will build on the (limited) usability design experiences with the mobile IRMA application.

Ongoing

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Few-shot training van niet-Euclidische diepe visuele representatiemodellen via model-assisted labeling

Computer Vision (CV) is een tak binnen de Artificiële Intelligentie (AI) die zich bezig houdt met visuele herkenning van patronen in afbeeldingen of videos. Daarbij wordt gebruik gemaakt van diepe representatiemodellen, die gebaseerd zijn op Euclidische geometrie. Dit betekent dat deze modellen getraind zijn op basis van een vlakke geometrische representatie. In veel gevallen sluit deze representatie niet goed aan bij de echte wereld. Visuele illusies, zoals Sheppard’s “Terror Subterra”, geven aanwijzingen waar de discrepanties zitten. Bij een verplaatsing van het monster op de horizontale en verticale as in een vlakke representatie lijkt het alsof het monster van grootte veranderd, terwijl dit in werkelijkheid niet zo is: beide monsters zijn exact even groot. Een verplaatsing van een object in de echte wereld heeft zo vaak invloed op de schaal dat onze hersenen erdoor misleid kunnen worden. Recente vorderingen in CV laten de potentie zien van de toepassing van niet-Euclidische geometrie voor het leren van visuele eigenschappen. Het verschil tussen de twee is met name dat de representatieve kracht van niet-Euclidische geometrie groter is. In een niet-Euclidische representatie kan de schaal van Shepard’s monster bij verplaatsing in de ruimte op een natuurlijke manier gepresenteerd worden, waardoor het beeld consistent blijft met onze visuele perceptie ervan. In dit onderzoek willen we de impact evalueren van niet-Euclidische visuele representatiemodellen op het verzamelen, ordenen en annoteren van de data die nodig is voor het trainen van deze nieuwe diepe representatiemodellen. Dit willen we doen we aan de hand van drie CV-problemen die praktische toepassingen dienen buiten de context van de academische wetenschap: beeldmerkherkenning in reclamevideo’s (bij Alpha.one), winkelpanddetectie in gelijkhoekige (visoogobjectief) video’s (bij The Big Data Company) en visuele inspectie van de binnenkant van cilindervormige opslagtanks (bij ScanTank).

Ongoing

Products 1.618

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The development and validation of a five factor model of sources of self-efficacy in clinical nursing education

PDF

product

Measurement errors in roentgen-stereophotogrammetric joint motion analysis

PDF

product

Cross-classified multilevel models improved standard error estimates of covariates in clinical outcomes – a simulation study

MULTIFILE

product

Intra-assessor reliability and measurement error of ultrasound measures for foot muscle morphology in older adults using a tablet-based ultrasound machine

MULTIFILE