Påvirker endringer i aksje- og boligformue privat konsum? : en empirisk analyse på norske data

Denne oppgaven undersøker om endringer i aksje- og boligformue påvirker privat konsum i Norge. Videre drøftes en tilleggshypotese om at boligformue har større effekt på privat konsum enn aksjeformue, og en hypotese om at effekten fra boligformue har økt i de senere år. Oppgaven finner at endringer i både aksje- og boligformue påvirker privat konsum i norske husholdninger, som er i tråd med teori og internasjonale undersøkelser. Effekten fra boligformue er signifikant større enn effekten fra aksjeformue, som også støttes av en analyse av norsk aksje- og boligeierskap der norske husholdninger i stor grad eier egen bolig, men lite aksjer. Oppgaven finner indikasjoner på at effekten fra boligformue har økt fra midten av 2000-tallet, men kan ikke konkludere sikkert

Secure and Scalable Statistical Computation of Questionnaire Data in R

Collecting data via a questionnaire and analyzing them while preserving respondents’ privacy may increase the number of respondents and the truthfulness of their responses. It may also reduce the systematic differences between respondents and non-respondents. In this paper, we propose a privacy-preserving method for collecting and analyzing survey responses using secure multi-party computation (SMC). The method is secure under the semi-honest adversarial model. The proposed method computes a wide variety of statistics. Total and stratified statistical counts are computed using the secure protocols developed in this paper. Then, additional statistics, such as a contingency table, a chi-square test, an odds ratio, and logistic regression, are computed within the R statistical environment using the statistical counts as building blocks. The method was evaluated on a questionnaire dataset of 3,158 respondents sampled for a medical study and simulated questionnaire datasets of up to 50,000 respondents. The computation time for the statistical analyses linearly scales as the number of respondents increases. The results show that the method is efficient and scalable for practical use. It can also be used for other applications in which categorical data are collected

Analisis dan Implementasi Pencarian Kata Berbasis Konkordansi dan N-GRAM pada Terjemahan Al-Quran Berbahasa Indonesia

Pengkajian ayat-ayat Al-Quran sangatlah penting bagi umat muslim khususnya, namun sayang dalam pelaksanaannya masih menggunakan cara manual termasuk dalam pencarian ayat-ayat Al-Quran yang mengandung kata tertentu untuk dipergunakan sebagai contoh. Dengan menggunakan metode pencarian berbasis konkordansi, akan mempermudah dalam membantu pencarian seluruh ayat yang mengandung kata tertentu dengan kesamaan lema. Tidak hanya itu, dengan konkordansi dapat dilakukan pengolahan kata sehingga dapat menghasilkan informasi tambahan yang lebih lengkap. Salah satu pengolahan yang dapat digunakan untuk membantu adalah teori marcov assumption terkait n-gram. N-Gram akan membantu dalam mencari informasi terkait kombinasi kata tertentu dengan kata-kata disekitarnya

Open source software, the future of medical imaging?

Medical imaging and Picture Archiving and Communication Systems (PACS) in particular, have appeared to be one of the promising areas for Open Source Software (OSS). Open source medical imaging solutions do exist, including PACS, but are not widely deployed at hospitals and health care establishments, which prevents them from achieving their full potential. In most cases where medical OSS systems exist (i.e. not necessarily PACS), it is to a very limited degree, and typically out of sight of the common user. Research we have conducted on medical software companies in North Norway and three hospitals in Europe suggests that if open source medical software is to become a useful alternative to proprietary software, that firstly, the initiative must be taken by the public health services and secondly, that it will require a shift from software companies (from sale-value oriented to service oriented). However, it would be naïve to rely on existing proprietary companies to initiate such a change. Interviews revealed that some companies considered the possibilities of developing using an OSS model, but did not deem it to be profitable, whereas others stated that it was simply out of the question. They are not willing to risk their successful business models, because historically (and perhaps at the cost of quality) it pays to keep the inner workings of their software secret. Other reasons revealed for not using OSS were: poor support, prejudices and the unwillingness of proprietary companies to accept a new business model. We suggest that these problems can be overcome with the emergence of competence centers for OSS, and that if open source medical imaging, PACS projects in particular, are to get started, they are more likely to succeed if a hospital is involved. However, our suggestions can only be tested thoroughly if more implementations are done

Hvilke sykepleieutfordringer møter sykepleier på legevakt i distriktet i Troms og Finnmark?

Tema for denne masterstudien er å få et innblikk i arbeidshverdagen til legevaktsykepleiere i distriktet fra til sammen tre kommuner i Troms og Finnmark. Basert på lovverket har kommunene stor frihet i hvordan de velger å organisere legevaktene. Hensikten med studien er å belyse hvilke utfordringer legevaktsykepleiere i distriktet møter på. Studien har en kvalitativ tilnærming, der det empiriske materialet er samlet inn gjennom ett fokusgruppeintervju og fem individuelle dybdeintervju av legevaktsykepleiere fra distriktet. Her delte sykepleierne sine erfaringer og refleksjoner over sin praksiserfaring om utfordringer som de møter i arbeidshverdagen. Legevaktene i distriktet har ofte geografiske og værmessige utfordringer og lang vei til sykehus. Hele landet preges av sykepleiemangel, og det er intet unntak i distriktet. Sykepleierne jeg møtte, beskrev sitt arbeidsfelt som uforutsigbar, spennende, utfordrende og lærerik. De møter akutt syke pasienter som de prøver å hjelpe med bakgrunn i kliniske- og erfaringsbaserte kunnskap. De jobber ofte alene i stressende situasjoner og har lite tverrfaglige ressurser. Pasientene kjenner de gjerne fra tidligere. Med innsikt i pasientens helsehistorie, boforhold og hjemmesituasjon prøver de å hjelpe pasienten på best mulig måte. Sykepleierne er mye alene med mange oppgaver, og de må ta egne beslutninger for å berge liv. Vold, rus og trusler er blitt vanlig også i distriktene, og vinterhalvåret gir mange utfordringer innenfor pasienttransport til sykehus. Til tross for alle disse utfordringene forteller sykepleierne i min undersøkelse at de trives med arbeidet, det gir mening, de har godt kollegasamarbeid, og lærerike og spennende arbeidshverdager

Machine Learning in Chronic Pain Research: A Scoping Review

Given the high prevalence and associated cost of chronic pain, it has a significant impact on individuals and society. Improvements in the treatment and management of chronic pain may increase patients’ quality of life and reduce societal costs. In this paper, we evaluate state-of-the-art machine learning approaches in chronic pain research. A literature search was conducted using the PubMed, IEEE Xplore, and the Association of Computing Machinery (ACM) Digital Library databases. Relevant studies were identified by screening titles and abstracts for keywords related to chronic pain and machine learning, followed by analysing full texts. Two hundred and eighty-seven publications were identified in the literature search. In total, fifty-three papers on chronic pain research and machine learning were reviewed. The review showed that while many studies have emphasised machine learning-based classification for the diagnosis of chronic pain, far less attention has been paid to the treatment and management of chronic pain. More research is needed on machine learning approaches to the treatment, rehabilitation, and self-management of chronic pain. As with other chronic conditions, patient involvement and self-management are crucial. In order to achieve this, patients with chronic pain need digital tools that can help them make decisions about their own treatment and care

Combining multivariate statistics and the think-aloud protocol to assess Human-Computer Interaction barriers in symptom checkers

[EN] Symptom checkers are software tools that allow users to submit a set of symptoms and receive advice related to them in the form of a diagnosis list, health information or triage. The heterogeneity of their potential users and the number of different components in their user interfaces can make testing with end-users unaffordable. We designed and executed a two-phase method to test the respiratory diseases module of the symptom checker Erdusyk. Phase I consisted of an online test with a large sample of users (n = 53). In Phase I, users evaluated the system remotely and completed a questionnaire based on the Technology Acceptance Model. Principal Component Analysis was used to correlate each section of the interface with the questionnaire responses, thus identifying which areas of the user interface presented significant contributions to the technology acceptance. In the second phase, the think-aloud procedure was executed with a small number of samples (n = 15), focusing on the areas with significant contributions to analyze the reasons for such contributions. Our method was used effectively to optimize the testing of symptom checker user interfaces. The method allowed kept the cost of testing at reasonable levels by restricting the use of the think-aloud procedure while still assuring a high amount of coverage. The main barriers detected in Erdusyk were related to problems understanding time repetition patterns, the selection of levels in scales to record intensities, navigation, the quantification of some symptom attributes, and the characteristics of the symptoms. (C) 2017 Elsevier Inc. All rights reserved.This work was supported by Helse Nord [grant HST1121-13], the Faculty of Health Sciences from UIT The Arctic University of Norway [researcher code 1108], and The Research Council of Norway [grant 248150/O70]. We thank Professor Emeritus Rafael Romero-Villafranca for reviewing the statistical analysis of this paper.Marco-Ruiz, L.; Bones, E.; De La Asuncion, E.; Gabarron, E.; Aviles-Solis, JC.; Lee, E.; Traver Salcedo, V.... (2017). Combining multivariate statistics and the think-aloud protocol to assess Human-Computer Interaction barriers in symptom checkers. Journal of Biomedical Informatics. 74:104-122. https://doi.org/10.1016/j.jbi.2017.09.002S1041227

The Norwegian PraksisNett: a nationwide practice-based research network with a novel IT infrastructure

Clinical research in primary care is relatively scarce. Practice-based research networks (PBRNs) are research infrastructures to overcome hurdles associated with conducting studies in primary care. In Norway, almost all 5.4 million inhabitants have access to a general practitioner (GP) through a patient-list system. This gives opportunity for a PBRN with reliable information about the general population. The aim of the current paper is to describe the establishment, organization and function of PraksisNett (the Norwegian Primary Care Research Network). Materials and Methods We describe the development, funding and logistics of PraksisNett as a nationwide PBRN. Results PraksisNett received funding from the Research Council of Norway for an establishment period of five years (2018–2022). It is comprised of two parts; a human infrastructure (employees, including academic GPs) organized as four regional nodes and a coordinating node and an IT infrastructure comprised by the Snow system in conjunction with the Medrave M4 system. The core of the infrastructure is the 92 general practices that are contractually linked to PraksisNett. These include 492 GPs, serving almost 520,000 patients. Practices were recruited during 2019–2020 and comprise a representative mix of rural and urban settings spread throughout all regions of Norway. Conclusion Norway has established a nationwide PBRN to reduce hurdles for conducting clinical studies in primary care. Improved infrastructure for clinical studies in primary care is expected to increase the attractiveness for studies on the management of disorders and diseases in primary care and facilitate international research collaboration. This will benefit both patients, GPs and society in terms of improved quality of care.publishedVersio

Søvnforstyrrelser og forskrivning av hypnotika i allmennpraksis – en PraksisNett-studie

Source at https://helse-bergen.no/nasjonal-kompetansetjeneste-for-sovnsykdommer-sovno/tidsskriftet-sovn.Søvnforstyrrelser er svært utbredt i befolkningen. Insomni er den vanligste søvnforstyrrelsen med en forekomst på omkring 10-20 % [1, 2]. Forekomsten ser ut til å være økende i befolkningen [1]. Blant pasienter på venterommet hos norske fastleger er forekomsten så høy som rundt 50 % ifølge to tidligere studier [3, 4]. Insomni utgjør en risikofaktor for utvikling av psykiske lidelser [5] og er identifisert som en mulig kausal årsaksfaktor for en rekke negative helseutfall [6]. Selv om sovemedisiner kun er anbefalt ved akutte søvnplager [7], er forskrivning av sovemedisiner også for langvarige plager svært vanlig [8]. Medikamentgruppen hypnotika inkluderer benzodiazepiner, benzodiazepinlignende sovemidler (z preparater) og melatoninpreparater. I klinisk praksis benyttes av og til også andre preparater enn hypnotika mot søvnproblemer, inkludert antidepressiva, antihistaminer og antipsykotika [9]