Universitetet i Agder
  • Kristiansand, Norway
Recent publications
Objective: To examine the relationships between sociodemographic characteristics, student academic information, social support, sense of coherence, anxiety, lifestyle, and quality of life among dental students. Methods: A cross-sectional study among 233 dental students in Brazil. We captured data on sociodemographic and socioeconomic characteristics, social support through Social Support Appraisal, psychosocial factors (sense of coherence and anxiety based on SOC-13 and Depression, Anxiety and Stress Scale-21 - anxiety subscale, respectively), lifestyle as per individual Lifestyle Profile and quality of life based on VERAS-Q. Data was analysed through Structural Equation Modelling. Results: Greater social support, higher sense of coherence, lower anxiety, better lifestyle directly predicted better quality of life. Male gender, city of origin did not differ from the city of the campus, higher social support and greater sense of coherence were indirectly linked with better quality of life via better lifestyle. Lower academic semester and higher social support indirectly predicted better quality of life via lower anxiety. Conclusion: Social support, sense of coherence, anxiety, and lifestyle were relevant factors directly associated with dental student's quality of life. Indirect pathways were observed between gender, moved home to attend dental course, academic semester, social support, sense of coherence, and quality of life.
In this review we integrate the scientific literature and results-proven practice and outline a novel framework for understanding the training and development of elite long-distance performance. Herein, we describe how fundamental training characteristics and well-known training principles are applied. World-leading track runners (i.e., 5000 and 10,000 m) and marathon specialists participate in 9 ± 3 and 6 ± 2 (mean ± SD) annual competitions, respectively. The weekly running distance in the mid-preparation period is in the range 160–220 km for marathoners and 130–190 km for track runners. These differences are mainly explained by more running kilometers on each session for marathon runners. Both groups perform 11–14 sessions per week, and ≥ 80% of the total running volume is performed at low intensity throughout the training year. The training intensity distribution vary across mesocycles and differ between marathon and track runners, but common for both groups is that volume of race-pace running increases as the main competition approaches. The tapering process starts 7–10 days prior to the main competition. While the African runners live and train at high altitude (2000–2500 m above sea level) most of the year, most lowland athletes apply relatively long altitude camps during the preparation period. Overall, this review offers unique insights into the training characteristics of world-class distance runners by integrating scientific literature and results-proven practice, providing a point of departure for future studies related to the training and development in the Olympic long-distance events.
Background The opioid antagonist extended-release naltrexone (XR-NTX) in the treatment of opioid use disorder (OUD) is effective in terms of safety, abstinence from opioid use and retention in treatment. However, it is unclear how patients experience and adjust to losing the possibility of achieving an opioid effect. This qualitative study is the first to explore how people with opioid dependence experience XR-NTX treatment, focusing on the process of treatment over time. Methods Using a purposive sampling strategy, semi-structured interviews were undertaken with 19 persons with opioid use disorder (15 men, four women, 22–55 years of age) participating in a clinical trial of XR-NTX in Norway. The interviewees had received at least three XR-NTX injections. Qualitative content analysis with an inductive approach was used. Findings Participants described that XR-NTX treatment had many advantages. However they still faced multiple challenges, some of which they were not prepared for. Having to find a new foothold and adapt to no longer gaining an effect from opioids due to the antagonist medication was challenging. This was especially true for those struggling emotionally and transitioning into the harmful use of non-opioid substances. Additional support was considered crucial. Even so, the treatment led to an opportunity to participate in society and reclaim identity. Participants had strong goals for the future and described that XR-NTX enabled a more meaningful life. Expectations of a better life could however turn into broken hopes. Although participants were largely optimistic about the future, thinking about the end of treatment could cause apprehension. Conclusions XR-NTX treatment offers freedom from opioids and can facilitate the recovery process for people with OUD. However, our findings also highlight several challenges associated with XR-NTX treatment, emphasizing the importance of monitoring emotional difficulties and increase of non-opioid substances during treatment. As opioid abstinence in itself does not necessarily equal recovery, our findings underscore the importance of seeing XR-NTX as part of a comprehensive, individualized treatment approach. Trial registration : Clinicaltrials.gov # NCT03647774, first Registered: Aug 28, 2018.
Hosting capacity knowledge is of great importance for distribution utilities to assess the amount of PV capacity possible to accommodate without troubling the operation of the grid. In this paper, a novel method to quantify the hosting capacity of low voltage grids is presented. The method starts considering a state of fully exploited building rooftop solar potential. A downward process is proposed—from the starting state with expected violations on the grid operation to a state with no violations. In this process, the installed PV capacity is progressively reduced. The reductions are made sequentially and selectively aiming to mitigate specific violations: nodes overvoltage, lines overcurrent and transformer overloading. Evaluated on real data of fourteen low voltage grids from Austria, the method proposed exhibits benefits in terms of higher hosting capacities and lower computational costs compared to stochastic methods. Furthermore, it also quantifies hosting capacity expansions achievable by overcoming the effect of the violations. The usage of a potential different from solar rooftops is also presented, demonstrating that a user-defined potential allows to quantify the hosting capacity in a more general setting with the method proposed.
Periods of economic recession are typically accompanied by the use of cost-cutting actions, such as wage cuts or freezes, increased workloads and reduced training expenditures. While such actions are expected to boost performance, at least in the short-term, their effects on employee attitudes and behaviours at work have been the subject of much research. In this study, we examine how management's use of cost-cutting actions could have a detrimental impact on two aspects of the employment relations climate—the quality of employee–management relations and the level of employees’ trust in management; further, we investigate how these relationships might lead to an increase in employee complaints against their organisations. Using multilevel data from 21,981 employees in 1,923 workplaces, we show that the use of cost-cutting actions violates the psychological contract, which, in turn, contributes to strained relations between employees and management. However, in workplaces where employees are actively involved in decision-making, cost-cutting actions are less likely to have a negative impact. We discuss the theoretical and practical implications of our study using psychological contract theory.
Cyberbullying behavior (CB) on social media is complex because its perpetrators exhibit varied demographic characteristics and personalities. Prior studies have applied Big Five (Big5) and Dark Tetrads (Dark4) personality traits (PTs) along with demographic attributes, using symmetrical modelling, but revealed mixed and inconsistent results. This paper applies an asymmetric modelling approach using complexity and configurational theories to develop configurations of PTs and demography to predict CB. The online survey data have been analyzed using fuzzy set qualitative comparative analysis (fsQCA) technique. Regarding Big5 PTs, our findings reveal that, for instance, people scoring high in conscientiousness, neuroticism, openness and low in agreeableness undertake cyberbullying. For Dark4 PTs, the combination of either psychopathy and sadism or Machiavellianism and psychopathy leads to cyberbullying. As for demographic attributers, educated young married people, irrespective of gender, are likely to commit cyberbullying. Our all-inclusive model reveals that social media bullies, regardless of their gender, marital status, and social media experience, are young, educated, neurotic, conscientious, psychopathic, and sadistic with high Machiavellianism and low agreeableness. Further, we suggest configurations to reduce cyberbullying. The findings are discussed with implications for theory and practice.
Rain erosion is one of the most detrimental factors contributing to wind turbine blade (WTB) coating fatigue damage especially for utility-scale wind turbines (WTs). To prevent rain erosion induced WTB coating fatigue damage, this paper proposes a deep reinforcement learning (DRL)-based optimization method for finding the optimal rotor speed under different rain intensities and wind speeds. First, an efficient physics-based model for predicting WTB coating fatigue damage considering the comprehensive blade coating fatigue mechanism, rain intensity distribution, and wind speed distribution is presented. Then, a WT rotor speed design optimization problem is constructed to search for the optimal rotor speed under different rain intensity and wind speed conditions. To address the challenge of optimizing the efficiency, the original design optimization problem is converted into a DRL-based design optimization model. A hybrid reward is proposed to enhance the DRL agent trained by a deep deterministic policy gradient algorithm. Finally, the proposed DRL-based design optimization method is utilized to guide the optimal rotor speed scheduling of a 5-MW WT under given wind speed and rain intensity conditions. The results show that the proposed method could extend the predicted WTB blade coating fatigue life by 2.55 times with a minor reduction in the energy yield (0.027%) compared to the original rotor speed schedule that only considers maximum power capture. The computational time of the proposed method is reduced significantly compared to that of the traditional gradient and evolutional design optimization methods.
The concept of affordances has become central in information systems literature. However, existing perspectives fall short in providing details on the relational aspect of affordances, which can influence actors' perception of them. To increase granularity and specificity in this regard, researchers have suggested that it be supplemented with other concepts or theories. In this article, we argue that the Heideggerian concepts of ‘familiarity’ and ‘referential totality’ are well suited for increasing our understanding of the relational aspects of affordances in information systems research. To explore this idea, we conducted a case study of a project concerning the development of a digital twin (i.e., digital representation of a physical asset) in the Norwegian grid sector. We found that users' familiarity with the digital twin totality enabled them to perceive digital twin affordances, and that without this familiarity, affordances remained latent for the users. Through our study, we offer a nuanced perspective on the relational aspect of affordance perception, contributing to affordance theory in that regard. Further, we contribute to practice and information systems research by providing valuable insights into how digital twins are understood and applied in practice.
Introduction Previous studies show substantial mode share effects from e-bikes. E-bike owners cycle more and drive less car than they would without access to an e-bike. Support schemes for e-bikes exist in a number of countries, but knowledge about the effect of subsidies on active transport is limited. The aim of this study is to assess the mode change and active mobility effects of a subvention scheme for e-bikes in Norway. Methods To boost the uptake of e-bikes, Oslo City Council introduced a subvention program (€500) for e-bike purchasers in 2016. Applicants answered to a web-survey at two time points, including a travel diary and questions about overall bicycle usage. In addition, a sub sample used an app to track all their transport activities for two following months (one period of time). Results The survey results from the trial group (N = 382) were compared with two control groups: one from an outside sample of individuals (N = 665) and one consisting of subvention receivers who had not yet purchased the e-bike (N = 214). The survey data shows that the cycling mode share for the trial group increased in the range of 17–22 per cent-points (depending on comparison group) after subsidised e-bike purchase, whereas the app data (comparing mode distribution according to the length of e-bike ownership) suggest a 5 to 14 per cent-point increase. For overall bicycle usage, the survey data shows a significant increase for the trial group in the range of 11.6–19.3 km, compared to the control groups. Conclusion The subvention led to a modal shift (i.e. more cycling) and more overall cycling activity. Our findings indicate that financial incentives may contribute to a boost in active transport, even when the subvention is of a simplistic kind that does not target specific population segments.
Scholars and industry stakeholders have exhibited an interest in identifying the underlying dimensions of viral memes. However, the recipe for creating a viral meme remains obscure. This study makes a phenomenological contribution by examining viral memes, exploring the antecedents (i.e., content‐related factors, customer‐related factors, and media‐related factors), consequences, and moderating factors using a mixed‐method approach. The study presents a holistic framework for creating viral memes based on the viewpoints of customers and industry stakeholders. Four quantitative studies (i.e., a lab experiment, an online quasi‐experiment, an event study, and a brand recall study) validate the theoretical model identified in the qualitative study. The research points to the potential of viral memes in marketing communications to enhance brand recall and brand engagement. The study found that viral memes are topical and highly relatable and are thus well received by the target groups, which increases customer engagement and brand recall. The marketers can adopt the findings of this study to design content for memes that consumers find relevant, iconic, humorous, and spreadable. Furthermore, marketers can use customer‐related factors suggested in the theoretical framework for enhancing escapism, social gratification, and content gratification for their target customers which in turn shall organically increase their reach within their target segments and enhance brand performance in terms of brand recall and brand engagement.
This conceptual study provides insight into the strategic behaviors of firms facing slow growth in times of economic stagnation. Recognizing the inevitability of periods of economic stagnation—with another downturn expected as early as 2022, we note that most industry classifications are considered mature and characterized by a few extremely large companies in each industry group. We introduce the Fortune 500 as an important cross-industry collective of these large firms and suggest that they now comprise an institutional field. This development explains their isomorphic behavior during the recession triggered by the financial crisis of 2008 as well as their subsequent motivation for change. Using the pertinent literature from institutional theory and organizational change, we posit that the appropriate firm-level response (strategic choice) during periods of slow growth is to maintain legitimacy and membership in the field by adopting a proactive approach that focuses on improving top-line growth. We synthesize frameworks found in the literature and provide a “menu” of five strategic options companies should consider to turn their firms around by redirecting growth from the short term to the long term. We discuss implications for boards and executives anticipating significant economic deceleration.
Social media celebrities (SMCs) and social media platforms (SMPs) have become indispensable in today's business and marketing settings. Drawing on the celebrity influence model (CIM), this study examines the impact of SMCs on their followers' purchase intention and the moderating influence of SMP usage on the relationships between (a) SMCs and their followers' purchase intention, (b) para-social relationships (PSR) and purchase intention, and (c) identification and purchase intention. We collected 665 valid responses via an online questionnaire in China and then employed partial least squares structural equation modelling (PLS-SEM) to examine the proposed relationships between the variables. The findings revealed that SMCs do not significantly influence their followers' purchase intention directly; however, they do exert such influence through PSR and identification. The results further indicated that SMP usage moderates the effect of PSR and identification on purchase intention. Our study offers both theoretical and managerial contributions. Theoretically, the incorporation of CIM into this study's model augments the PSR and identification literature in the context of SMCs. Again, the moderating effect of SMP usage that we reveal is novel in the social media literature. In practice, marketers in China should consider the credibility and rapport a particular social media celebrity has with his or her followers before contracting that particular celebrity to endorse their products.
Speech enables easy human-to-human communication as well as human-to-machine interaction. However, the quality of speech degrades due to background noise in the environment, such as drone noise embedded in speech during search and rescue operations. Similarly, helicopter noise, airplane noise, and station noise reduce the quality of speech. Speech enhancement algorithms reduce background noise, resulting in a crystal clear and noise-free conversation. For many applications, it is also necessary to process these noisy speech signals at the edge node level. Thus, we propose implicit Wiener filter-based algorithm for speech enhancement using edge computing system. In the proposed algorithm, a first order recursive equation is used to estimate the noise. The performance of the proposed algorithm is evaluated for two speech utterances, one uttered by a male speaker and the other by a female speaker. Both utterances are degraded by different types of non-stationary noises such as exhibition, station, drone, helicopter, airplane, and white Gaussian stationary noise with different signal-to-noise ratios. Further, we compare the performance of the proposed speech enhancement algorithm with the conventional spectral subtraction algorithm. Performance evaluations using objective speech quality measures demonstrate that the proposed speech enhancement algorithm outperforms the spectral subtraction algorithm in estimating the clean speech from the noisy speech. Finally, we implement the proposed speech enhancement algorithm, in addition to the spectral subtraction algorithm, on the Raspberry Pi 4 Model B, which is a low power edge computing device.
Background Despite anterior cruciate ligament (ACL) re-ruptures being common, research on patient experiences after knee trauma has primarily focused on the time after primary ACL reconstruction. Integrating qualitative research and patient experiences can facilitate researchers and clinicians in understanding the burden of an ACL re-rupture. The aim of the study was to explore the experiences of an ACL re-rupture journey in young active females aiming to return to knee-strenuous sports after primary ACL reconstruction. Method Fifteen young (19[range 16–23] years old) active females who suffered an ACL re-rupture were interviewed with semi-structured interviews. Qualitative content analysis using deductive approach based on Wiese-Bjornstal’s ‘integrated model of response to sport injury’ was used. Results The results are presented in two timelines 1) from first ACL injury to ACL re-rupture, and 2) from ACL re-rupture to present day, and further stratified according to the domains of the ‘integrated model of psychological response to injury’. Results in the first timeline are summarised into seven categories: Finding hope for the journey; Accepting my ACL injury; I succeeded; What matters now? Who am I?; Where will this end? What is going to happen? In the second timeline, eight categories were identified: Fighting spirit; A helping hand; Working hard; I am a new me; I am destroyed; Loneliness; Painful changes; and, I could have made it to the pro´s. Conclusion Young active females who suffered an ACL re-rupture did not express any positive experience following their first ACL injury, however, in contrast, expressed positive experiences and personal growth after going through the ACL re-rupture journey, characterized by a lot of struggling, and ultimately led to the experience of becoming a new, stronger person.
An intrusion detection system, often known as an IDS, is extremely important for preventing attacks on a network, violating network policies, and gaining unauthorized access to a network. The effectiveness of IDS is highly dependent on data preprocessing techniques and classification models used to enhance accuracy and reduce model training and testing time. For the purpose of anomaly identification, researchers have developed several machine learning and deep learning-based algorithms; nonetheless, accurate anomaly detection with low test and train times remains a challenge. Using a hybrid feature selection approach and a deep neural network-(DNN-) based classifier, the authors of this research suggest an enhanced intrusion detection system (IDS). In order to construct a subset of reduced and optimal features that may be used for classification, a hybrid feature selection model that consists of three methods, namely, chi square, ANOVA, and principal component analysis (PCA), is applied. These methods are referred to as "the big three." On the NSL-KDD dataset, the suggested model receives training and is then evaluated. The proposed method was successful in achieving the following results: a reduction of input data by 40%, an average accuracy of 99.73%, a precision score of 99.75%, an F1 score of 99.72%, and an average training and testing time of 138% and 2.7 seconds, respectively. The findings of the experiments demonstrate that the proposed model is superior to the performance of the other comparison approaches.
We study the Newman--Unti (NU) group from the viewpoint of infinite-dimensional geometry. The NU group is a topological group in a natural coarse topology, but it does not become a manifold and hence a Lie group in this topology. To obtain a manifold structure we consider a finer Whitney-type topology. This turns the unit component of the NU group into an infinite-dimensional Lie group. We then study the Lie theoretic properties of this group. Surprisingly, the group operations of the full NU group become discontinuous, whence the NU group does not support a Lie group structure. The NU group contains the Bondi--Metzner--Sachs (BMS) group as a subgroup, whose Lie group structure was constructed in a previous article. The lack of a Lie group structure on the NU group implies that, despite the known splitting of the NU Lie algebra into a direct sum of Lie ideals of the Lie algebras of the BMS group and conformal rescalings, the BMS group cannot be embedded as a Lie subgroup into the NU group.
Background The growth in response-shift methods has enabled a stronger empirical foundation to investigate response-shift phenomena in quality-of-life (QOL) research; but many of these methods utilize certain language in framing the research question(s) and interpreting results that treats response-shift effects as “bias,” “noise,” “nuisance,” or otherwise warranting removal from the results rather than as information that matters. The present project will describe the various ways in which researchers have framed the questions for investigating response-shift issues and interpreted the findings, and will develop a nomenclature for such that highlights the important information about resilience reflected by response-shift findings. Methods A scoping review was done of the QOL and response-shift literature (n = 1100 articles) from 1963 to 2020. After culling only empirical response-shift articles, raters characterized how investigators framed and interpreted study research questions (n = 164 articles). Results Of 10 methods used, papers using four of them utilized terms like “bias” and aimed to remove response-shift effects to reveal “true change.” Yet, the investigators’ reflections on their own conclusions suggested that they do not truly believe that response shift is error to be removed. A structured nomenclature is proposed for discussing response-shift results in a range of research contexts and response-shift detection methods. Conclusions It is time for a concerted and focused effort to change the nomenclature of those methods that demonstrated this misinterpretation. Only by framing and interpreting response shift as information, not bias, can we improve our understanding and methods to help to distill outcomes with and without response-shift effects.
This research aims to extend the literature on knowledge hiding and tourism by integrating the theoretical frameworks of social exchange and social learning. Employee knowledge hiding has scarcely been examined in the tourism literature while leader knowledge hiding has not been analysed at all. Recognising that knowledge hiding can seriously undermine the ability of employees to offer innovative customer service and that leaders’ knowledge hiding may trigger knowledge hiding chain reactions among tourism employees, this study attempts to fill this gap. Utilising multi-source, multi-timed and multi-level data, we hypothesise a multi-level mediation wherein leader knowledge hiding trickles down to employee knowledge hiding, which, in turn, negatively affects team organisational citizenship behaviour and positively affects team interpersonal deviance. The “trickle-down” effect of leader knowledge hiding to employee knowledge hiding is then positively moderated by perceived organisational politics, which amplifies this relationship. Relevant theoretical and managerial implications are presented.
The literature offers valuable insights into various aspects of service recovery and service outcomes. However, the available findings are limited relative to the size of the ever-expanding service economy. In particular, past studies have left more granular nuances of the association between service recovery strategies and service outcomes, such as the mediating role of forgiveness or the valence of forgiveness, under-explored. Recognising that an improved understanding of recovery from failures is crucial for sustaining positive customer–brand relationships in the service economy, the present study investigates the mediating effect of the valence of forgiveness (both exoneration and resentment) on the association between various service recovery strategies (apology, compensation and voice) and service outcomes (brand trust and negative word of mouth [NWOM]) in the context of food delivery apps (FDAs). We tested the proposed model by analysing data from 294 FDA users who had experienced FDA service failures and recovery efforts in the recent past. The findings suggest that recovery strategies are associated with exoneration, resentment and brand trust but not with NWOM. While exoneration mediates the association of these strategies with both brand trust and NWOM, resentment mediates only the association of these strategies with NWOM. Finally, the severity of previously experienced service failures and the speed of the service provider’s response moderates the association of the valence of forgiveness with brand trust and NWOM. By uncovering the key role of the valence of forgiveness in service recovery, our study offers significant theoretical and practical implications for stakeholders.
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3,059 members
Inger Beate Larsen
  • Department of Psychosocial Health
Dagrun Engeset
  • Department of Nutrition and Public Health
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Kristiansand, Norway
Head of institution
Prof. Sunniva Whittaker
Website
www.uia.no