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Evaluating the Impact of Digital Support on Parental Stress in Swedish Child Health Care : Results From an Intervention Study
No full textIntroduction: The Swedish child health care (CHC) program provides voluntarily, at no cost, services for children from birth to 5 years old. Participation rates are 99% of Swedish parents enrolling their children in some form of CHC program. Parental groups, comprising parents with similar experiences, can help reduce parental stress and foster the development of effective coping strategies. The study is aimed at evaluating a digital support intervention involving parents, child health nurses, and researchers.Methods: This cluster-randomized, prospective pilot intervention study, conducted in northern Sweden, had three follow-up points: baseline, 4 months, and 8 months. Data were collected from autumn 2022 to late spring 2023 and evaluated effects on parental stress and satisfaction, eHealth literacy, and satisfaction with CHC, accessibility, and support. The 18-item Parental Stress Scale was used to assess parental stress and satisfaction. eHealth literacy was measured using the 10-item eHEALS scale, and parental satisfaction and opinions on accessibility to CHC were measured using a three-item Visual Analogue Scale. The intervention group was offered to participate in various digital activities, while the control group received the usual CHC.Results: Parental satisfaction and stress levels within and between the intervention and control groups showed no significant changes from baseline to 8 months. Regarding eHealth literacy, differences were observed between the groups; however, both groups demonstrated improvement at the 8-month follow-up. The control group scored higher in eHealth literacy from baseline. The same pattern was identified regarding the parents' perceptions of internet usability and importance. Concerning satisfaction with CHC, accessibility, and support, the control group scored higher at baseline. Interestingly, the lines of the intervention and control groups crossed over at the 8-month follow-up.Conclusion: Despite a limited outcome change, the results showed a tendency to benefit some parents. Our findings suggest that further evaluation, possibly with other more suitable measurements or questionnaires, an extended intervention period, and a larger sample, is necessary to understand the implications of these results fully
A multi-head deep fusion model for recognition of cattle foraging events using sound and movement signals
No full textMonitoring feeding behaviour is a relevant task for efficient herd management and the effective use of available resources in grazing cattle. The ability to automatically recognise animals’ feeding activities through the identification of specific jaw movements allows for the improvement of diet formulation, as well as early detection of metabolic problems and symptoms of animal discomfort, among other benefits. The use of sensors to obtain signals for such monitoring has become popular in the last two decades. The most frequently employed sensors include accelerometers, microphones, and cameras, each with its own set of advantages and drawbacks. An unexplored aspect is the simultaneous use of multiple sensors with the aim of combining signals in order to enhance the precision of the estimations. In this direction, this work introduces a deep neural network based on the fusion of acoustic and inertial signals, composed of convolutional, recurrent, and dense layers. The main advantage of this model is the combination of signals through the automatic extraction of features independently from each of them. The model has emerged from an exploration and comparison of different neural network architectures proposed in this work, which carry out information fusion at different levels. Feature-level fusion has outperformed data and decision-level fusion by at least a 0.14 based on the F1-score metric. Moreover, a comparison with state-of-the-art machine learning methods is presented, including traditional and deep learning approaches. The proposed model yielded an F1-score value of 0.802, representing a 14% increase compared to previous methods. Finally, results from an ablation study and post-training quantisation evaluation are also reported.
Efficient stochastic framework for availability improvement of stone door frame manufacturing plants using artificial neural networks and regression analysis
No full textThe main objective of this study is to introduce an efficient stochastic framework to improve the availability of the stone door frame manufacturing plants along with the reliability, maintainability, and dependability (RAMD) investigation and prediction of steady state availability of the plant using regression analysis (RA) and artificial neural networks (ANNs). The plant has five subsystems connected in series configuration. The RAMD methodology is employed to identify critical components that significantly impact the system's overall performance. For this purpose, a mathematical model is developed using Markov birth–death process and Chapman-Kolmogorov differential difference equations derived for steady state availability evaluation. The incorporation of exponential distribution for failure and repair rates, coupled with the Markovian technique, yields insights into the intricate variations within the system. Several goodness-of-fit metrics, such as R2, MAE, RMSE, and collinearity diagnostics, are used to evaluate the performance of the proposed model. Results show that in this application, ANN performs better than regression analysis. The findings showcase the efficacy of the proposed stochastic framework in achieving remarkable improvements in availability. Numerical outcomes, meticulously presented in structured tables and figures, provide tangible evidence of the framework's success. The novelty of the study lies in the strategic combination of these methodologies to achieve enhanced insights into availability improvement. By enhancing availability, the proposed framework directly influences production efficiency and overall plant performance. The findings of present work are valuable insights for industrial practitioners seeking resilient operational strategies.
Påverkar partiers skolbesök elevernas politiska intresse? : En Policy brief
No full textEn skola i demokrati? En studie av politiska företrädares skolbesök (SkolDem
Normer i svenska och norska barnböcker : En studie som analyserar barnböcker ur ett normkritiskt perspektiv
No full textI denna studie har vi analyserat svensk och norsk barnlitteratur som läses på förskolor utifrån ett normkritiskt perspektiv. Syftet var att undersöka och jämföra hur fördelningen bland normkategorierna kön, etnicitet och funktionsvariation synliggjordes i dessa två länder. Urvalet fördelades på fem svenska och fem norska barnböcker som analyserades, genom en innehållsanalys av både kvalitativ och kvantitativ metod för att närma oss innehållet samt för att kunna se fördelningen bland karaktärerna. Vi har tagit inspiration av Hirdmans (1988) teorier och Nikolajevas (2013) schema i studerandet av kön, essentialismen har framstått i analysen av etnicitet och Crip teorin har setts i funktionsvariation. Resultatet visar på att framställningen av kön och etnicitetsnormer till största del består av stereotypiskt innehåll då pronomen han och vithetsnormen domineras i det svenska och norska litteraturinnehållet. Resultatet visar också på en brist när det kommer till representationer av karaktärer med olika funktionsvariationer. Slutsatser vi dragit är att det finns en maktobalans kring normer och värderingar i litteraturens innehåll. Idealet är det manliga könet, vithetsnormen samt den funktionsdugliga kroppen som synliggörs. Vidare kan litteratur för barn enligt tidigare forskning bidra till deras identitetsutveckling samt förståelse för sin omvärld och ta del av andras levnadsätt. Därmed har pedagogers roll och medvetenhet en betydelse när det kommer till litteratur som presenteras för barnen. Detta kan medföra förändringar samt utmana normer och värderingar.Betyg i Ladok 2025-06-04.</p
Therapist-Guided Internet-Delivered Acceptance-Enhanced Behavior Therapy for Skin-Picking Disorder : A Randomized Controlled Trial
No full textDespite its high prevalence, individuals suffering from skin-picking disorder (SPD) face limited access to treatment due to several factors, including geographical and economic barriers, as well as a shortage of properly trained therapists. Offering Internet-delivered therapy could be a solution to these barriers. This study aimed to evaluate the efficacy of therapist-guided Internet-delivered acceptance-enhanced behavior therapy (iBT) for SPD compared to a wait-list control condition. Participants randomized to the intervention group received 10 weeks of iBT (n = 35), while those in the control group were placed on a wait-list (n = 35). The primary outcome was the Skin Picking Scale—Revised (SPS-R). Mixed-model regression analyses demonstrated a significantly greater improvement in SPD symptoms in the iBT group compared to the control group at posttreatment (between-group difference −5.1 points, F = 9.69, p <.001). The between-group effect size was in the large range, with a bootstrapped d of 1.3 (95% CI [0.92, 1.69]). At posttreatment, 43% of the participants in the iBT group were classified as responders, and 31% were in remission, compared to 0% responders and 3% in remission in the control group. At the 6-month follow-up, the SPD symptoms had increased compared to posttreatment. However, the improvement from pretreatment remained significant. Participants reported a high level of satisfaction and credibility of the treatment, and a perceived good level of working alliance. Compared to wait-list control, iBT is an efficacious treatment for SPD at posttreatment and follow-up, with the potential to substantially increase the availability and access to evidence-based treatment for this disorder. Replication studies, particularly those comparing iBT to an active control, are warranted.
Predictors of language and reading outcomes in 12-year-old children born very preterm
No full textAim: To investigate predictors of language and reading outcomes in 12-year-old Swedish children born very preterm (<32 gestational weeks) in 2004–2007. Method: Children born very preterm (n = 78, 43 girls), and term-born controls (n = 50, 32 girls), were examined on verbal IQ, semantic and phonemic fluency, sentence recall, reading fluency, word and phonological decoding at 12 years of age. The results were related to neonatal characteristics, language development, measured with Bayley-III, at 2.5 years corrected age, and concurrent non-verbal IQ. Results: Preterm children showed language and reading difficulties that were not completely accounted for by level of concurrent non-verbal IQ. Extremely preterm born children (<28 gestational weeks) demonstrated specific linguistic weaknesses. Administration of antenatal steroids, retinopathy of prematurity and persistent ductus arteriosus explained unique variance in language and reading outcomes. Language assessments at 2.5 years had low predictive value for language and reading outcomes at age 12. Conclusion: Language and reading difficulties in 12-year-old children born preterm were not fully explained by concurrent non-verbal IQ, and were not reliably predicted by language assessments at 2.5 years. Renewed language assessments at school age are warranted for identifying children with persisting linguistic difficulties.
Snow sports-specific extension of the IOC consensus statement : methods for recording and reporting epidemiological data on injury and illness in sports
No full textThe International Olympic Committee's (IOC) consensus statement on 'methods for recording and reporting of epidemiological data on injury and illness in sport' recommended standardising methods to advance data collection and reporting consistency. However, additional aspects need to be considered when these methods are applied to specific sports settings. Therefore, we have developed a snow sports-specific extension of the IOC statement to promote the harmonisation of injury and illness registration methods among athletes of all levels and categories in the different disciplines governed by the International Ski and Snowboard Federation (FIS), which is also applicable to other related snow sports such as biathlon, ski mountaineering, and to some extent, para snow sports. The panel was selected with the aim of representing as many different areas of expertise/backgrounds, perspectives and diversity as possible, and all members were assigned to thematic subgroups based on their profiles. After panel formation, all members were provided with an initial draft of this extension, which was used as a basis for discussion of aspects specific to the discipline, application context, level and sex within their snow sports subgroup topic. The outcomes were then aligned with the IOC's existing consensus recommendations and incorporated into a preliminary manuscript draft. The final version of this snow sports-specific extension was developed and approved in two iterative rounds of manuscript revisions by all consensus panel members and a final meeting to clarify open discussion points. This snow sports-specific extension of the IOC statement is intended to guide researchers, international and national sports governing bodies, and other entities recording and reporting epidemiological data in snow sports to help standardise data from different sources for comparison and future research
A noise-robust acoustic method for recognizing foraging activities of grazing cattle
No full textFarmers must continuously improve their livestock production systems to remain competitive in the growing dairy market. Precision livestock farming technologies provide individualized monitoring of animals on commercial farms, optimizing livestock production. Continuous acoustic monitoring is a widely accepted sensing technique used to estimate the daily rumination and grazing time budget of free-ranging cattle. However, typical environmental and natural noises on pastures noticeably affect the performance limiting the practical application of current acoustic methods. In this study, we present the operating principle and generalization capability of an acoustic method called Noise-Robust Foraging Activity Recognizer (NRFAR). The proposed method determines foraging activity bouts by analyzing fixed-length segments of identified jaw movement events produced during grazing and rumination. The additive noise robustness of the NRFAR was evaluated for several signal-to-noise ratios using stationary Gaussian white noise and four different nonstationary natural noise sources. In noiseless conditions, NRFAR reached an average balanced accuracy of 86.4%, outperforming two previous acoustic methods by more than 7.5%. Furthermore, NRFAR performed better than previous acoustic methods in 77 of 80 evaluated noisy scenarios (53 cases with p<0.05). NRFAR has been shown to be effective in harsh free-ranging environments and could be used as a reliable solution to improve pasture management and monitor the health and welfare of dairy cows. The instrumentation and computational algorithms presented in this publication are protected by a pending patent application: AR P20220100910. Web demo available at: https://sinc.unl.edu.ar/web-demo/nrfar.
Situation awareness in active shooter events
No full textActive shooter events require swift action. This study examines situation awareness during these incidents, focusing on how officers transition from less confrontational approaches to more confrontational, life-saving tactics. Using qualitative research based on observations from six active shooter training exercises, the study highlights key factors such as information, experience, and shared mental models that influence situation awareness. The findings reveal that while officers are willing to take risks, they often struggle to adopt the necessary speed and dominance needed to neutralize the threat effectively.