Browsing by study line "ingen studieinriktning"

Objective. Depression is associated with increased risk of chronic disease, which may be at least partly due to poor health behaviors. Growing body of evidence has associated depression with unhealthy diet. However, the association of depression with diet quality in the long run is not well known. Furthermore, it is unclear if dietary interventions could mitigate the harmful association of depression with diet. This study examined the association of depression with diet both cross-sectionally and longitudinally in a population-based prospective cohort. The effectiveness of an early-onset dietary intervention in modifying these associations was investigated. Methods. The sample (n = 457) was from The Special Turku Coronary Risk Factor Intervention Project (STRIP). The intervention group (n = 209) had undergone a dietary intervention lasting from age of 7 months until age of 20 years. Depression was measured at age 20 using Beck Depression Inventory II (BDI-II). Diet quality was assessed at ages 20 and 26 using a diet score calculated based on food diaries. Missing values were replaced using multiple imputation by chained equations. Linear regression analyses were used to analyze the association of depression at age 20 with diet at ages 20 and 26, as well as the modifying effect of intervention group on these associations. Results. No cross-sectional association was found for depression and diet at age 20. Depression at age 20 was longitudinally associated with worse diet quality at age 26. The associations did not differ between intervention and control groups at either of the time points. Conclusions. Contrary to previous research, this study did not find cross-sectional association for depression with diet. However, this study offers novel information on longitudinal associations, suggesting that depression may have effects on diet quality that can manifest after several years. Dietary intervention was not found effective in modifying these associations. Since long-term effects on diet may be an important factor explaining the association of depression with chronic diseases, ways to mitigate the adverse consequences of depression for diet should be explored further.

Digital health technologies strive to facilitate physicians’ burdensome work, but their implementations seem to have brought new stressors. Adapting to new ways of working can take time, and positive changes may not be noticed until later. This study aimed to examine associations of longer-term perceived work change due to digitalisation and intensity of digital work with job strain among physicians. Differences in possible associations were examined according to the length of work experience. This study analysed cross-sectional data of the Electronic Health Records as Physicians’ Tools Study collected from physicians (N=4271) working in Finland between January and March 2021. Job strain was measured with three outcomes: stress related to information systems (SRIS), time pressure, and stress. Opinions about how work had changed in the past 3 years were assessed with six statements based on the goals of digitalisation. The intensity of digital work was measured by the number of information systems used and the frequency of telemedicine work conducted. The associations were examined in multivariable linear and logistic regression analyses and adjusted for background variables. The physicians’ mean SRIS and time pressure scores were 3.5 and 3.7, respectively (scales 1–5; a higher score indicated higher strain levels), and 60% reported stress. The majority disagreed with the statement regarding accelerated clinical encounters due to digitalisation, which was associated with higher SRIS (b=.23, 95% CI [.16, .30]) and time pressure (b=.12, 95% CI [.04, .20]). Disagreement with facilitated access to patient information was associated with higher SRIS (b=.15, 95% CI [.07, .23]) and disagreement with supported decision-making was associated with higher SRIS (b=.11, 95% CI [.05, .18]) and greater odds of stress (OR=1.26, 95% CI [1.06, 1.48]). The more active role of patients received the greatest agreement among the physicians, and this agreement was associated with higher time pressure (b=.11, 95% CI [.04, .19]) and greater odds of stress (OR=1.19, 95% CI [1.02, 1.40]). Agreement with progressed interprofessional collaboration was also associated with higher time pressure (b=.10, 95% CI [.02, .18]). Intensive information systems use and intensive telemedicine work were consistently significantly associated with all job strain outcomes. Moreover, a significant interaction effect was found, as physicians who did intensive telemedicine work and had less than 6 years of work experience reported the highest time pressure. Not all physicians have felt that digitalisation would have facilitated their work, not even in the longer term, which may expose them to different strains. Digitalisation appears as a long work change process, where physicians would need constant support. In particular, early-career physicians could benefit from training to promote the time management skills needed for telemedicine work. Moreover, the functions, usability and interoperability of digital health technologies should be developed to support clinical encounters better. It would also be essential to improve the availability of digital support for patients in society, as physicians’ job strain related to patient activation might imply patients’ weak readiness to self-manage their health digitally.

Advertising has been an area of interest in linguistic research for the past decades due to its pervasiveness and role in shaping our notions and values in society. This study sets out to examine the socio-cultural practices in a specific field of advertising discourse, influencer marketing on social media. Influencer marketing is a recent branch of marketing, brought forth by the popularity of social media. In Influencer marketing, the products are marketed by individual influencers instead of corporations or companies. Brands turn to social media influencers in order to reach a wider audience and to utilize the influencers’ social media presence and their ability to influence their audience to promote their products and to turn this social power into capital. The hypothesis is that this key difference between traditional marketing and influencer marketing. The aim of this study is to present a critical discourse analysis to examine the social context and relationship between the influencer and the reader. The methodologic approach applied to the analysis of the data is critical discourse analysis, more specifically Norman Fairclough’s three-dimensional model. Critical discourse analysis and Fairclough’s model allow focus on the linguistic properties in addition to the production and reception processes of discourse and the socio-cultural practices within discourse. The data and its analysis deemed that influencer marketing reveals consumerist ideologies that promote purchasing of goods as a means to reach happiness and well-being, as presented by the social media influencers.

This thesis presents a complication risk comparison of the most used surgical interventions for benign prostatic hyperplasia (BPH). The investigated complications are the development of either a post-surgery BPH recurrence (reoperation), an urethral stricture or stress incontinence severe enough to require a surgical procedure for their treatment. The analysis is conducted with survival analysis methods on a data set of urological patients sourced from the Finnish Institute for Health and Welfare. The complication risk development is estimated with the Aalen-Johansen estimator and the effects of certain covariates on the complication risks is estimated with the Cox PH regression model. One of the regression covariates is the Charlson Comorbidity Index score, which attempts to quantify a disease load of a patient at a certain point in time as a single number. A novel Spark algorithm was designed to facilitate the efficient calculation of the Charlson Comorbidity Index score on a data set of the same size as the one used in the analyses here. The algorithm achieved at least similar performance to the previously available ones and scaled better on larger data sets and with stricter computing resource constraints. Both the urethral stricture and urinary incontinence endpoints suffered from a lower number of samples, which made the associated results less accurate. The estimated complication probabilities in both endpoint types were also so low that the BPH procedures couldn’t be reliably differentiated. In contrast, BPH reoperation risk analyses yielded noticeable differences among the initial BPH procedures. Regression analysis results suggested that the Charlson Comoborbidity Index score isn’t a particularly good predictor in any of the endpoints. However, certain cancer types that are included in the Charlson Comorbidity Index score did predict the endpoints well when used as separate covariates. An increase in the patient’s age was associated with a higher complication risk, but less so than expected. In the urethral stricture and urinary incontinence endpoints the number of preceding BPH operations was usually associated with a notable complication risk increase.

Avhandlingens syfte är att undersöka hur orenhet, äckel och hot skapar konstskräck i utvalda berättelser från Clive Barkers Books of Blood och Thomas Ligottis Songs of a Dead Dreamer. Båda verken är novellsamlingar från 1980-talet, och kan klassificeras som skräcklitteratur. Min analys koncentrerar sig på hotfulla utrymmen och omgivningar i novellerna och beskrivningar av abjekta och äckliga kroppar. Min analys grundar sig på Noël Carrolls teori om hur konstskräck, en sorts fiktiv skräckkänsla som kan uppstå genom att läsa skräcklitteratur, alltid består av en kombination av både äckel och hot. Äcklet innehåller alltid någon form av orenhet, och det orena skapas då någon kategorisk gräns överträds. Jag använder mig dessutom av Julia Kristevas koncept om abjektet, som också beskriver något orent och innebär en sorts gränsöverträdelse; abjektet är någonting som är en blandning av vanligtvis skilda kategorier och kan skapa en våldsam chock för den som vittnar en blandning eller störning av dessa kategorier. Jag använder också Martha Nussbaums teori om äckel för att analysera det orena i verken. Min analys visar hur karaktärernas trygga utrymmen som beskrivs i verken invaderas av olika monster och väsen som är orena, och förvandlar dem till hotfulla omgivningar genom sin närvaro. Dessa inkräktare kan vara olika varelser, som spöken, demoner och mördare, eller mer abstrakta varelser och krafter som symboliserar ett mer ogripbart hot. I Barkers noveller sker invasionen ofta stegvis i större, allmänna utrymmen som storstäder, och i Ligottis verk i mer privata omgivningar som det egna hemmet. Avhandlingen undersöker också varför äckliga och orena kroppar ses som abjekt: kropparna bryter någon sorts kategorisk gräns och orsakar en djup och radikal störning i vår världsbild eller självbild som följd. I Barkers noveller skapas olika kroppsabjekt bl.a. via skildringar av kroppar med sjukliga egenskaper och drag som påminner om lik, genom att beskriva överträdelser av accepterade gränser gällande fysisk kontakt med djur och detaljerade beskrivningar av lidande människokroppar. I Ligottis verk riktas abjektet och äcklet i stället mot den egna kroppen, då karaktärerna eller deras kroppsdelar ofta genomgår olika formskiftningar och förvandlingar eller smittas ner med främmande substanser. De abjekta monsterkropparna kan symbolisera delar i olika förtryckande samhällssystem, och dessa system tvingar ofta karaktärerna att bli en del av dessa hierarkier. Hotet som monstren och de abjekta kropparna skapar kan vara enbart fysiskt, men också ha moraliska, psykologiska eller politiska nivåer och kan rikta sig mot enskilda karaktärer eller större samhällen och gemenskaper. De orena skräckfigurerna representerar och förkroppsligar alla dessa hot, och när de möts i skräcklitteratur, fungerar de som fysiska manifestationer och spegelbilder av karaktärernas rädslor och skapar konstskräck.

The content we see is increasingly determined by ever more advanced recommender systems, and popular social media platform TikTok represents the forefront of this development (See Chapter 1). There has been much speculation about the workings of these recommender systems, but precious little systematic, controlled study (See Chapter 2). To improve our understanding of these systems, I developed sock puppet bots that consume content on TikTok as a normal user would (See Chapter 3). This allowed me to run controlled experiments to see how the TikTok recommender system would respond to sock puppets exhibiting different behaviors and preferences in a Finnish context, and how this would differ from the results obtained by earlier investigations (See Chapter 4). This research was done as part of a journalistic investigation in collaboration with Long Play. I found that TikTok appears to have adjusted their recommender system to personalize content seen by users to a much lesser degree, likely in response to a previous investigation by the WSJ. However, I came to the conclusion that, while sock puppet audits can be useful, they are not a sufficiently scalable solution to algorithm governance, and other types of audits with more internal access are needed (See Chapter 5).

Objectives. Autism spectrum disorder (ASD) is a neurobiological developmental disorder that involves challenges in social interaction and restricted/repetitive behaviors. Since generalization and maintenance of acquired skills is essential in the rehabilitation of ASD, it is important to integrate interventions into the home environment by parental guidance. There has been some research on the rehabilitation of children with ASD in Finland, but no research has been conducted on the guidance of parents from the perspective of speech therapist. The purpose of this study is to find out the views of parental guidance from speech therapists who rehabilitate children with ASD. Interviews with speech therapists will clarify the ways in which parents of children with ASD are guided through speech therapy and the challenges and contributing factors in parental guidance. Methods.The research method was a semi-structured interview. Five speech pathologists with experience in the rehabilitation of ASD were interviewed. The interviews were recorded and transcribed. The data was analyzed by content analysis. Results and conclusion. Parental guidance of children with ASD was divided into information sharing, interaction & discussion and direct guidance. The challenges were parental strain, parent attitude and in some cases multiculturalism. Contributing factors appeared in training practices and home conditions. Challenges and benefits were influenced by the individuality of families. Speech therapists hoped for more opportunities to arrange separate parental guidance sessions so that they would be able to discuss deeper about the methods and family situation without the child’s presence. Speech therapists considered parental guidance important in the rehabilitation of children with ASD because, with the guidance of parents it helped to increase skills in everyday life and guaranteed training intensity. As parental strain was identified as a challenge in this study, it would be important to explore how they could be more effectively supported during rehabilitation. In addition, it could be explored whether separate parental guidance sessions should be increased or whether the number of parental guidance sessions has been adapted through the development of new working practices.

Chemical reaction optimization is an iterative process that targets identifying reaction conditions that maximize reaction output, typically yield. The evolution of optimization techniques has progressed from intuitive approaches to simple heuristics, and more recently, to statistical methods such as Design of Experiments approach. Bayesian optimization, which iteratively updates beliefs about a response surface and suggests parameters both exploiting conditions near the known optima and exploring uncharted regions, has shown promising results by reducing the number of experiments needed for finding the optimum in various optimization tasks. In chemical reaction optimization, the method allows minimizing the number of experiments required for finding the optimal reaction conditions. Automated tools like pipetting robots hold potential to accelerate optimization by executing multiple reactions concurrently. The integration of Bayesian optimization to automation reduces not only the workload and throughput but also optimization efficiency. However, adoption of these advanced techniques faces a barrier, as chemists often lack proficiency in machine learning and programming. To bridge this gap, Automated Chemical Reaction Optimization Software (ACROS) is introduced. This tool orchestrates an optimization loop: Bayesian optimization suggests reaction candidates, the parameters are translated into commands for a pipetting robot, the robot executes the operations, a chemist interprets the results, and data is fed back to the software for suggesting the next reaction candidates. The optimization tool was evaluated empirically using a numerical test function, in a Direct Arylation reaction dataset, and in real-time optimization of Sonogashira and Suzuki coupling reactions. The findings demonstrate that Bayesian optimization efficiently identifies optimal conditions, outperforming Design of Experiments approach, particularly in optimizing discrete parameters in batch settings. Three acquisition functions; Expected Improvement, Log Expected Improvement and Upper Confidence Bound; were compared. It can be concluded that expected improvement-based methods are more robust, especially in batch settings with process constraints.

Puumala orthohantavirus (PUUV) is a single stranded negative sense RNA virus, carried by the bank vole (Myodes glareolus). Like other orthohantaviruses, it does not cause visible symptoms in the host species, but when transmitted to humans, it can cause a mild version of hemorrhagic fever with renal syndrome (HFRS) called nephropathia epidemica (NE). PUUV is the only pathogenic orthohantavirus that is endemic to Finland, where it has a relatively high incidence of approximately 35 in 100 000 inhabitants or 1000 to 3000 diagnosed cases annually. Here we describe a miniaturized immunofluorescence assay (mini-IFA) for measuring antibody response against PUUV from bank vole whole blood and heart samples as well as from patient serum samples. The method outline was based on the work done by Pietiäinen et al., (2022), but it was adapted for the detection of PUUV antibodies. Transfected cells expressing the PUUV structural proteins (N, GPC, Gn and Gc) were used instead of PUUV infected cells, which allowed for performing all steps outside of bio-safety level 3 (BSL3) conditions. This method also enables the simultaneous measurement of IgM, IgA and IgG antibody response from each sample in a more efficient and higher output manner, when compared to traditional immunofluorescence methods. Our results show that the method is effective for testing large amounts of samples for PUUV antibodies and it allows for quick and convenient access to high-quality images that can be used for both detecting interesting targets for future studies, as well as producing a visual archive of the test results.

Real estate appraisal, or property valuation, requires strong expertise in order to be performed successfully, thus being a costly process to produce. However, with structured data on historical transactions, the use of machine learning (ML) enables automated, data-driven valuation which is instant, virtually costless and potentially more objective compared to traditional methods. Yet, fully ML-based appraisal is not widely used in real business applications, as the existing solutions are not sufficiently accurate and reliable. In this study, we introduce an interpretable ML model for real estate appraisal using hierarchical linear modelling (HLM). The model is learned and tested with an empirical dataset of apartment transactions in the Helsinki area, collected during the past decade. As a result, we introduce a model which has competitive predictive performance, while being simultaneously explainable and reliable. The main outcome of this study is the observation that hierarchical linear modelling is a very potential approach for automated real estate appraisal. The key advantage of HLM over alternative learning algorithms is its balance of performance and simplicity: this algorithm is complex enough to avoid underfitting but simple enough to be interpretable and easy to productize. Particularly, the ability of these models to output complete probability distributions quantifying the uncertainty of the estimates make them suitable for actual business use cases where high reliability is required.