↓ Direkt till sidans innehåll
↓ Direkt till sidans sekundära innehåll (sidomenyn)

Träfflista för sökning "WFRF:(Sanmartin Berglund Johan Professor) "

Search: WFRF:(Sanmartin Berglund Johan Professor)

Result 1-50 of 94

Sort/group result

Sort by: Hits per page:

Enumeration	Reference	Cover	Find
1.	Aeddula, Omsri, 1993- (author) Navigating Data Challenges: AI-Driven Decision Support for Product-Service System Development 2024 Doctoral thesis (other academic/artistic)abstract Solution providers are transitioning from product-centric models to service-oriented solutions. This shift has led to the rise of Product-Service Systems (PSS), which offer a holistic approach by integrating physical products with associated services. However, the inherent complexity and collaborative nature of PSS development present a significant challenge: information gathering, analysis, and knowledge building. This is further amplified in the early stages of PSS development due to data challenges such as uncertainty, ambiguity, and complexity. This complicates informed decision-making, potentially leading to the risk of sub-optimal outcomes and impacting the success of final offerings.This research proposes an AI-powered data analysis approach to address these data challenges and augment the decision-making process of PSS development. The focus is on supporting early-stage decision-making, as decisions made at this stage greatly impact the success of final solutions. The research investigates how data can be utilized and visualized to extract actionable insights, ultimately facilitating informed decision-making.The presented research demonstrates that AI-powered data analysis effectively supports informed decision-making in early-stage PSS development. By extracting actionable insights from complex data, handling data limitations, and enabling informed strategic decisions, knowledge sharing, and collaboration are facilitated among stakeholders. Furthermore, integrating AI with visualization tools fosters knowledge building and a deeper understanding of system behavior, ultimately leading to more successful PSS solutions. The efficacy of AI-powered data analysis for handling diverse data types across application domains is demonstrated, potentially leading to benefits such as a deeper understanding of system behavior and proactive solution strategies. These advancements contribute to developing decision support systems specifically for PSS development.Overall, this research demonstrates the efficacy of AI-powered data analysis in overcoming data challenges and empowering decision-makers in early-stage PSS development. This translates to more informed choices, leading to the creation of successful and efficient PSS solutions.
2.	Georgsson, Mattias (author) Toward Patient-centered, Standardized, and Reproducible Approaches of Evaluating the Usability of mHealth Chronic Disease Self-management Systems for Diabetes 2018 Doctoral thesis (other academic/artistic)abstract Diabetes is a chronic disease affecting 422 million patients worldwide according to World Health Organization data with 30.3 million in the United States and 64 million in Europe. The prevalence speaks to the need for improved ways to support patients in disease self-management. mHealth solutions are increasingly used for this; however, usability is a current challenge affecting patients’ mHealth use. Recent literature emphasizes an increased focus on patient-centeredness in diabetes care, user-centeredness in chronic disease mHealth system design and standardized, systematic approaches for usability evaluation. The aim of this thesis and its individual studies was to incorporate these foci into the evaluation of two mobile health self-management systems for diabetes.Study I used ISO standard 9241-11 to examine the relationship between selected group characteristics of diabetes patients on specific interaction outcomes to quantitatively identify needed system modifications. Study II utilized a multi-method design to assess diabetes patients’ mHealth usage and combined two novel analytic methods to structure and analyze results. Study III used a modified, user-oriented heuristic evaluation (HE) method, validated tasks and in-depth severity factor ratings to identify critical problems from patients’ point of view. By developing and employing a modified, user-centered cognitive walkthrough method (UC-CW), study IV assessed its effectiveness and efficiency in finding relevant usability problems for users as well as patients’ acceptance. The modified CW was validated against the golden-standard user test with Think Aloud.Study I emphasized the importance of considering user characteristics in mHealth performance as these influenced interaction outcomes. All patients had difficulties with multiple-step tasks. Patients more recently diagnosed were able to perform tasks more successfully, with fewer errors and at faster times and had higher satisfaction scores; similar outcomes to the more experienced users. Educational level did not, however, seem to influence performance. In study II, the usability test with Think-Aloud (TA), in-depth interviews and questionnaires contributed to 19 consolidated issues, and triangulated on 5 critical usability problems for users. The combined analysis methods resulted in structured, categorized descriptions to aid in problem-solving. In Study III, the disease-related, critical information deficiencies found by expert evaluators using the modified, structured method also converged on and highlighted potentially adverse user concerns. Study IV demonstrated that the UC-CW found more critical user problems compared to the user test with TA despite both methods producing similar major average severity ratings and violations of heuristic categories. The modified method was more efficient per detected problem and experienced as less cognitively demanding and with a higher ease of use.These studies offer different approaches that include patient-centered, efficient and user-acceptable methods and method modifications to detect critical usability issues for users. Importantly, improved mHealth designs for users could mean improvement in interactions, interaction performance, increased adoption, and long-term perhaps even increased adherence to interventions for chronic conditions.
3.	Aeddula, Omsri, 1993-, et al. (author) AI-driven Ossification Assessment in Knee MRI : A Product-Service System Development for Informed Clinical Decision-Making Other publication (other academic/artistic)abstract Background: Traditionally, assessing the degree of ossification in the epiphyseal plate for growth plate development relies on manual evaluation, which can be inefficient due to the complexities of the distal femoral epiphysis anatomy. Existing methods lack efficient detection techniques.Method: This study proposes an AI-based decision support system, designed within a product-service system (PSS) framework, to automate ossification assessment and detection of the distal femoral epiphysis in knee magnetic resonance imaging (MRI) data. The system leverages advanced machine learning techniques, specifically two Convolutional Neural Networks (CNNs), combined with computer vision techniques. This intelligent system analyzes MRI slices to predict the optimal slice for analysis and identify variations in the degree of ossification within individual datasets.Results: The proposed method's effectiveness is demonstrated using a set of T2-weighted gradient echo grayscale knee MRI data. The system successfully detects the complex anatomy of the distal femoral epiphysis, revealing variations in the degree of ossification ranging from completely closed/open to fully open/closed regions.Conclusions: This study presents a robust and efficient AI-based method, integrated within a PSS framework, for measuring the degree of ossification in the distal femoral epiphysis. This approach automates ossification assessment, providing valuable insights for clinical decision-making by clinicians and forensic practitioners. The PSS framework ensures seamless integration of the AI technology into existing workflows.
4.	Flyborg, Johan, et al. (author) Results of objective brushing data recorded from a powered toothbrush used by elderly individuals with mild cognitive impairment related to values for oral health 2024 In: Clinical Oral Investigations. - : Springer Nature. - 1432-6981 .- 1436-3771. ; 28:1 Journal article (peer-reviewed)abstract Objectives: The study aimed to investigate how the objective use of a powered toothbrush in frequency and duration affects plaque index, bleeding on probing, and periodontal pocket depth ≥ 4 mm in elderly individuals with MCI. A second aim was to compare the objective results with the participants’ self-estimated brush use.Materials and methods: Objective brush usage data was extracted from the participants’ powered toothbrushes and related to the oral health variables plaque index, bleeding on probing, and periodontal pocket depth ≥ 4 mm. Furthermore, the objective usage data was compared with the participants’ self-reported brush usage reported in a questionnaire at baseline and 6- and 12-month examination.Results: Out of a screened sample of 213 individuals, 170 fulfilled the 12-month visit. The principal findings are that despite the objective values registered for frequency and duration being lower than the recommended and less than the instructed, using powered toothbrushes after instruction and information led to improved values for PI, BOP, and PPD ≥ 4 mm in the group of elderly with MIC.Conclusions: Despite lower brush frequency and duration than the generally recommended, using a powered toothbrush improved oral health. The objective brush data recorded from the powered toothbrush correlates poorly with the self-estimated brush use.Clinical relevance: Using objective brush data can become one of the factors in the collaboration to preserve and improve oral health in older people with mild cognitive impairment. Trial registration: ClinicalTrials.gov Identifier: NCT05941611, retrospectively registered 11/07/2023.
5.	Aeddula, Omsri, 1993-, et al. (author) A Solution with Bluetooth Low Energy Technology to Support Oral Healthcare Decisions for improving Oral Hygiene 2021 In: ACM International Conference Proceeding Series. - New York, NY, USA : Association for Computing Machinery (ACM). - 9781450389846 ; , s. 134-139 Conference paper (peer-reviewed)abstract The advent of powered toothbrushes and associated mobile health applications provides an opportunity to collect and monitor the data, however collecting reliable and standardized data from large populations has been associated with efforts from the participants and researchers. Finding a way to collect data autonomously and without the need for cooperation imparts the potential to build large knowledge banks. A solution with Bluetooth low energy technology is designed to pair a powered toothbrush with a single-core processor to collect raw data in a real-time scenario, eliminating the manual transfer of powered toothbrush data with mobile health applications. Associating powered toothbrush with a single-core processor is believed to provide reliable and comprehensible data of toothbrush use and propensities can be a guide to improve individual exhortation and general plans on oral hygiene quantifies that can prompt improved oral wellbeing. The method makes a case for an expanded chance to plan assistant capacities to protect or improve factors that influence oral wellbeing in individuals with mild cognitive impairment. The proposed framework assists with determining various parameters, which makes it adaptable and conceivable to execute in various oral care contexts
6.	Aeddula, Omsri, 1993- (author) Data-Driven Decision Support Systems for Product Development - A Data Exploration Study Using Machine Learning 2021 Licentiate thesis (other academic/artistic)abstract Modern product development is a complex chain of events and decisions. The ongoing digital transformation of society, increasing demands in innovative solutions puts pressure on organizations to maintain, or increase competitiveness. As a consequence, a major challenge in the product development is the search for information, analysis, and the build of knowledge. This is even more challenging when the design element comprises complex structural hierarchy and limited data generation capabilities. This challenge is even more pronounced in the conceptual stage of product development where information is scarce, vague, and potentially conflicting. The ability to conduct exploration of high-level useful information using a machine learning approach in the conceptual design stage would hence enhance be of importance to support the design decision-makers, where the decisions made at this stage impact the success of overall product development process.The thesis aims to investigate the conceptual stage of product development, proposing methods and tools in order to support the decision-making process by the building of data-driven decision support systems. The study highlights how the data can be utilized and visualized to extract useful information in design exploration studies at the conceptual stage of product development. The ability to build data-driven decision support systems in the early phases facilitates more informed decisions.The thesis presents initial descriptive study findings from the empirical studies, showing the capabilities of the machine learning approaches in extracting useful information, and building data-driven decision support systems. The thesis initially describes how the linear regression model and artificial neural networks extract useful information in design exploration, providing support for the decision-makers to understand the consequences of the design choices through cause-and-effect relationships on a detailed level. Furthermore, the presented approach also provides input to a novel visualization construct intended to enhance comprehensibility within cross-functional design teams. The thesis further studies how the data can be augmented and analyzed to extract the necessary information from an existing design element to support the decision-making process in an oral healthcare context.
7.	Christiansen, Line, 1986- (author) Using Mobile Health Technology to Support Health-related Quality of Life : From the Perspective of Older Adults with Cognitive Impairment 2022 Doctoral thesis (other academic/artistic)abstract The prevalence of cognitive impairment and illness increases with age. For older adults, maintaining or improving health-related quality of life (HRQoL) in the early stages of cognitive impairment is important to prevent consequences related to the progression of the condition. This thesis aims to identify factors affecting HRQoL and describe how mHealth technology can support HRQoL in older adults with cognitive impairment.Four studies were conducted using quantitative and qualitative approaches. A cross-sectional design was used to identify factors affecting older adults’ HRQoL (Study I) and investigate the relationship between mHealth technology use and self-rated quality of life (QoL) (Study III). A phenomenographical design was used to describe variations in older adults’ perceptions of mHealth technology and its impact on HRQoL (Study II). A prospective longitudinal design was used to examine older adults’ HRQoL changes over time (Study IV).Participants were selected from two longitudinal population studies using a purposive sampling strategy to include those aged 55 years and above with mild cognitive impairment or mild dementia. Data were obtained from questionnaires and semi-structured interviews. Data from the quantitative studies were analysed using statistical analysis, including descriptive and comparative analysis and regression analysis, while data from the qualitative study were examined using phenomenographical analysis in consecutive steps.The results showed that most older adults experienced good HRQoL with regard to both physical and mental health. The likelihood of having good-to-excellent QoL increased with age and was higher among males and those with higher education levels. Those diagnosed with dementia reported poorer HRQoL. Factors associated with low HRQoL included dependency in activities of daily living, receiving informal care and feelings of loneliness and pain. The use of mHealth technology was perceived as supportive in maintaining social interactions and facilitating independent living. The technology literacy levels among the study sample varied significantly. Those who reported having moderate-to-high technical skills and using the internet regularly via mHealth technology had higher odds of experiencing good-to-excellent QoL. No significant changes were observed in the older adults’ HRQoL over time in relation to the non-use and use of a customized mHealth application.The indicators of HRQoL are clinically relevant for the secondary prevention of dementia to help maintain good HRQoL in older adults with incipient cognitive impairment. The technology-related differences reflect the risk of digital exclusion. To improve preconditions for being digitally involved in society, societal initiatives that aim to empower the technology literacy level of older adults are needed.
8.	Eivazzadeh, Shahryar, 1975- (author) Evaluating Success Factors of Health Information Systems 2019 Doctoral thesis (other academic/artistic)abstract Health information systems are our technological response to the growing demand for health care. However, their success in their mission can be challenging due to the complexity of evaluating technological interventions in health care. In the series of studies compiled in this dissertation, we looked at the evaluation of these systems. We focused on the evaluation of factors that lead to success, where success is indicated by user satisfaction and can be induced by both intervention-specific and individual-specific factors.Study 1 developed a method, called UVON, to elicit and organise the user-demanded qualities in the outcomes of the health information system intervention. Through the application of the UVON method in the FI-STAR project, an EU project which developed and deployed seven e-health applications in seven member countries, ten categories of quality and their subcategories were identified. These qualities formed two questionnaires, specific to the patient and health professional users. Through the questionnaires, the patients and health-professionals users evaluated and graded both the occurrence of those demanded qualities in the project outcomes and their general satisfaction.Study 2 analysed the survey results to find out which of those ten qualities have the highest impact on satisfaction or can predict it better. Two partial least squares structural equation modelling (PLS-SEM) models were constructed, for the patient and health professionals, based on the Unified eValuation using ONtology (UVON) and survey outputs. The models showed that effectiveness is an important quality in creating satisfaction for both user groups. Besides, affordability for the health professionals and efficiency plus safety for the patients were the most influential. A satisfaction index is also introduced for simple and fast inferring of the changes in the outcome qualities.Study 5 recruited outputs and learnings from studies 1 and 2 to design a system that partially automates the process of evaluating success factors in health information systems, making it continuous and real-time, and replacing hard-to-run surveys with automatically captured indicators and analytics.Study 3 focused on individual-specific factors in using health information systems, particularly the technophilia personality trait. A short six-items instrument, called TechPH, was designed to measure technophilia in users, tuned for older users. The study recruited empirical data from the Swedish National Study on Aging and Care (SNAC) project. Two factors, labelled techAnxiety and techEnthusiams, are identified by the factor analysis method. A TechPH score was introduced as a scalar measurement of technophilia.Study 4 elicited and discussed the ethical challenges of evaluating and researching health information systems. Both a scoping review and a novel systematic postulation approach were recruited to identify twenty ethical challenges. The identified ethical challenges were discussed and mapped into a three-dimensional space of evaluation stages, demanded qualities, and major involving entities (stakeholder and artefacts), which fosters further postulation of ethical challenges.
9.	Idrisoglu, Alper (author) Voice for Decision Support in Healthcare Applied to Chronic Obstructive Pulmonary Disease Classification : A Machine Learning Approach 2024 Licentiate thesis (other academic/artistic)abstract Background: Advancements in machine learning (ML) techniques and voice technology offer the potential to harness voice as a new tool for developing decision-support tools in healthcare for the benefit of both healthcare providers and patients. Motivated by technological breakthroughs and the increasing integration of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare, numerous studies aim to investigate the diagnostic potential of ML algorithms in the context of voice-affecting disorders. This thesis focuses on respiratory diseases such as Chronic Obstructive Pulmonary Disease (COPD) and explores the potential of a decision support tool that utilizes voice and ML. This exploration exemplifies the intricate relationship between voice and overall health through the lens of applied health technology (AHT. This interdisciplinary nature of research recognizes the need for accurate and efficient diagnostic tools.Objective: The objectives of this licentiate thesis are twofold. Firstly, a Systematic Literature Review (SLR) thoroughly investigates the current state of ML algorithms in detecting voice-affecting disorders, pinpointing existing gaps and suggesting directions for future research. Secondly, the study focuses on respiratory health, specifically COPD, employing ML techniques with a distinct emphasis on the vowel "A". The aim is to explore hidden information that could potentially be utilized for the binary classification of COPD vs no COPD. The creation of a new Swedish COPD voice classification dataset is anticipated to enhance the experimental and exploratory dimensions of the research.Methods: In order to have a holistic view of a research field, one of the commonly utilized methods is to scan and analyze the literature. Therefore, Paper I followed the methodology of an SLR where existing journal publications were scanned and synthesized to create a holistic view in the realm of ML techniques employed to experiment on voice-affecting disorders. Based on the results from the SLR, Paper II focused on the data collection and experimentation for the binary classification of COPD, which was one of the gaps identified in the first study. Three distinct ML algorithms were investigated on the collected datasets through voice features, which consisted of recordings collected through a mobile application from participants 18 years old and above, and the most utilized performance measures were computed for the best outcome. Results: The summary of findings from Paper I reveals the dominance of Support Vector Machine (SVM) classifiers in voice disorder research, with Parkinson's Disease and Alzheimer's Disease as the most studied disorders. Gaps in research include underrepresented disorders, limited datasets in terms of number of participants, and a lack of interest in longitudinal studies. Paper II demonstrates promising results in COPD classification using ML and a newly developed dataset, offering insights into potential decision support tools for COPD diagnosis.Conclusion: The studies covered in this dissertation provide a comprehensive literature summary of ML techniques used to support decision-making on voice-affecting disorders for clinical outcomes. The findings contribute to understanding the diagnostic potential of using ML on vocal features and highlight avenues for future research and technology development. Nonetheless, the experiment reveals the potential of employing voice as a digital biomarker for COPD diagnosis using ML.
10.	Abbadi, Ahmad, et al. (author) Validation of the Health Assessment Tool (HAT) based on four aging cohorts from the Swedish National study on Aging and Care 2024 In: BMC Medicine. - : BioMed Central (BMC). - 1741-7015. ; 22:1 Journal article (peer-reviewed)abstract Background: As global aging accelerates, routinely assessing the functional status and morbidity burden of older patients becomes paramount. The aim of this study is to assess the validity of the comprehensive clinical and functional Health Assessment Tool (HAT) based on four cohorts of older adults (60 + years) from the Swedish National study on Aging and Care (SNAC) spanning urban, suburban, and rural areas.Methods: The HAT integrates five health indicators (gait speed, global cognition, number of chronic diseases, and basic and instrumental activities of daily living), providing an individual-level score between 0 and 10. The tool was constructed using nominal response models, first separately for each cohort and then in a harmonized dataset. Outcomes included all-cause mortality over a maximum follow-up of 16 years and unplanned hospital admissions over a maximum of 3 years of follow-up. The predictive capacity was assessed through the area under the curve (AUC) using logistic regressions. For time to death, Cox regressions were performed, and Harrell’s C-indices were reported. Results from the four cohorts were pooled using individual participant data meta-analysis and compared with those from the harmonized dataset.Results: The HAT demonstrated high predictive capacity across all cohorts as well as in the harmonized dataset. In the harmonized dataset, the AUC was 0.84 (95% CI 0.81–0.87) for 1-year mortality, 0.81 (95% CI 0.80–0.83) for 3-year mortality, 0.80 (95% CI 0.79–0.82) for 5-year mortality, 0.69 (95% CI 0.67–0.70) for 1-year unplanned admissions, and 0.69 (95% CI 0.68–0.70) for 3-year unplanned admissions. The Harrell’s C for time-to-death throughout 16 years of follow-up was 0.75 (95% CI 0.74–0.75).Conclusions: The HAT is a highly predictive, clinically intuitive, and externally valid instrument with potential for better addressing older adults’ health needs and optimizing risk stratification at the population level. © The Author(s) 2024.
11.	Berner, Jessica, et al. (author) Five-factor model, technology enthusiasm and technology anxiety 2023 In: Digital Health. - : Sage Publications. - 2055-2076. ; 9 Journal article (peer-reviewed)abstract Older adults need to participate in the digital society, as societal and personal changes and what they do with the remaining time that they have in their older years has an undeniable effect on motivation, cognition and emotion. Changes in personality traits were investigated in older adults over the period 2019–2021. Technology enthusiasm and technology anxiety are attitudes that affect the relationship to the technology used. The changes in the score of technology enthusiasm and technology anxiety were the dependent variables. They were investigated with personality traits, age, gender, education, whether someone lives alone, cognitive function, digital social participation (DSP) and health literacy as predictors of the outcome. The Edwards-Nunnally index and logistic regression were used. The results indicated that DSP, lower age, lower neuroticism and higher education were indicative of less technology anxiety. High DSP and high extraversion are indicative of technology enthusiasm. DSP and attitude towards technology seem to be key in getting older adults to stay active online.
12.	Eivazzadeh, Shahryar, 1975-, et al. (author) Design of a Semi-Automated and Continuous Evaluation System : Customized for Application in e-Health Other publication (other academic/artistic)abstract Background and ObjectivesSurvey-based evaluation of a system, such as measuring user’s satisfaction or patient-reported outcomes, entails a set of burdens that limits the feasibility, frequency, extendability, and continuity of the evaluation. Automating the evaluation process, that is reducing the burden of evaluators in questionnaire curation or minimizing the need for explicit user attention when collecting their attitudes, can make the evaluation more feasible, repeatable, extendible, continuous, and even flexible for improvement. An automated evaluation process can be enhanced to include features, such as the ability to handle heterogeneity in evaluation cases. Here, we represent the design of a system that makes it possible to have a semi-automated evaluation system. The design is presented and partially implemented in the context of health information systems, but it can be applied to other contexts of information system usages as well.MethodThe system was divided into four components. We followed a design research methodology to design the system, where each component reached a certain level of maturity. Already implemented and validated methods from previous studies were embedded within components, while they were extended with improved automation proposals or new features.ResultsA system was designed, comprised of four major components: Evaluation Aspects Elicitation, User Survey, Benchmark Path Model, and Alternative Metrics Replacement. All components have the essential maturity of identification of the problem, identification of solution objectives, and the overall design. In the overall design, the primary flow, process-entities, data-entities, and events for each component are identified and illustrated. Parts of some components have been already verified and demonstrated in real-world cases.ConclusionA system can be developed to minimize human burden, both for the evaluators and respondants, in survey-based evaluation. This system automates finding items to evaluate, creating questionnaire based on those items, surveying the users' attitude about those items, modeling the relations between the evaluation items, and incrementally changing the model to rely on automatically collected metrics, usually implicit indicators, collected from the users, instead of requiring their explicit expression of their attitudes. The system provides the possibility of minimal human burden, frequent repetition, continuity and real-time reporting, incremental upgrades regarding environmental changes, proper handling of heterogeneity, and a higher degree of objectivity.
13.	Eivazzadeh, Shahryar, 1975-, et al. (author) Most Influential Qualities in Creating Satisfaction Among the Users of Health Information Systems : Study in Seven European Union Countries 2018 In: JMIR Medical Informatics. - : JMIR Publications. - 2291-9694. ; 6:4 Journal article (peer-reviewed)abstract Background:Several models suggest how the qualities of a product or service influence user satisfaction. Models, such as the Customer Satisfaction Index (CSI), Technology Acceptance Model (TAM), and Delone and McLean Information Systems Success (D&M IS), demonstrate those relations and have been used in the context of health information systems.Objective:We want to investigate which qualities foster greater satisfaction among patient and professional users. In addition, we are interested in knowing to what extent improvement in those qualities can explain user satisfaction and if this makes user satisfaction a proxy indicator of those qualities.Methods:The Unified eValuation using ONtology (UVON) method was utilised to construct an ontology of the required qualities for seven e-health applications being developed in the FI-STAR project, a European Union (EU) project in e-health. The e-health applications were deployed across seven EU countries. The ontology included and unified the required qualities of those systems together with the aspects suggested by the Model for ASsessment of Telemedicine applications (MAST) evaluation framework. Two similar questionnaires, for 87 patient users and 31 health professional users, were elicited from the ontology. In the questionnaires, user was asked if the system has improved the specified qualities and if the user was satisfied with the system. The results were analysed using Kendall correlation coefficients matrices, incorporating the quality and satisfaction aspects. For the next step, two Partial Least Squares Structural Equation Modelling (PLS-SEM) path models were developed using the quality and satisfaction measure variables and the latent construct variables that were suggested by the UVON method.Results:Most of the quality aspects grouped by the UVON method are highly correlated. Strong correlations in each group suggest that the grouped qualities can be measures which reflect a latent quality construct. The PLS-SEM path analysis for the patients reveals that the effectiveness, safety, and efficiency of treatment provided by the system are the most influential qualities in achieving and predicting user satisfaction. For the professional users, effectiveness and affordability are the most influential. The parameters of the PLS-SEM that are calculated allow for the measurement of a user satisfaction index similar to CSI for similar health information systems.Conclusions:For both patients and professionals, the effectiveness of systems highly contributes to their satisfaction. Patients care about improvements in safety and efficiency, while professionals care about improvements in the affordability of treatments with health information systems. User satisfaction is reflected more in the users' evaluation of system output and fulfilment of expectations, but slightly less in how far the system is from ideal. Investigating satisfaction scores can be a simple, fast way to infer if the system has improved the abovementioned qualities in treatment and care.
14.	Elmståhl, Sölve, et al. (author) The Life Satisfaction Index-A (LSI-A) : Normative Data for a General Swedish Population Aged 60 to 93 Years 2020 In: Clinical Interventions in Aging. - : Dove Medical Press. - 1176-9092 .- 1178-1998. ; 15, s. 2031-2039 Journal article (peer-reviewed)abstract Purpose of Study: To gain Swedish norm value for the Life Satisfaction Index-A (LSI-A) in a population 60-93+ years old stratified for sex and age and to relate these norm values with respect to number of chronic diseases and functional impairment. Materials and Methods: The study population included a random sample of 2656 men (45.7%) and 3159 (54.3%) women from the longitudinal national studies' "Good Aging in Skane" (GAS) and SNAC-B, both part of the Swedish National Study on Aging and Care (SNAC). Data on Neugartens Life Satisfaction Index-A (LSI-A), medical history, activities of daily life (ADL) and socio-demographics were collected through structured interviews and questionnaires. Results: Men scored significantly higher than women; 28.5, sd=6.9, and 27.3, sd=6.6, respectively, out of maximum 40 points. For both genders the scores decreased with age, mean score 6.0 points, lower for men and 7.1 points lower for women between 60 and 93+ years. The highest score was noted for healthy individuals where both men and women scored 29.5 points, sd=6.2. Increased number of chronic diseases and dependency in ADLs were associated with lower LS. Conclusion: Nom values here presented may facilitate assessments and evaluation of life satisfaction in the general elder population and as reference values to clinical trials. Female sex, rising age, morbidity and impaired functional ability were all associated with impaired LS.
15.	Flyborg, Johan, et al. (author) Measurement of body temperature in the oral cavity with a temperature sensor integrated with a powered toothbrush 2023 In: SN Applied Sciences. - : Springer Nature Switzerland AG. - 2523-3963 .- 2523-3971. ; 5:1 Journal article (peer-reviewed)abstract This paper presents a method for collecting core body temperature data via a temperature sensor integrated into a powered toothbrush. The purpose is to facilitate the collection of temperature data without any extended effort from the user. Twelve participants use a powered toothbrush with a temperature sensor mounted on the brush head twice daily for two months. The obtained values are compared with those from a conventional fever thermometer approved for intraoral use. The results show that the temperature sensor–integrated powered toothbrush can measure the core body temperature and provide values comparable to those provided by a traditional oral thermometer. The use of the device can facilitate disease monitoring, fertility control, and security solutions for the elderly. © 2022, The Author(s).
16.	Flyborg, Johan (author) The use of the intelligent powered toothbrush in health technology 2022 Licentiate thesis (other academic/artistic)abstract BackgroundApplied health technology is a research field that ties together several disciplines to improve and preserve the health and quality of life of individuals and society. Helping especially elderly to meet the above goals is an important and necessary task and assistive technology and collection of health data are part of this work.AimsPaper I aims to investigate whether the use of a powered toothbrush could maintain oral health in a group of individuals with MCI and if changes in oral health affect various aspects of quality of life. Paper II and III aims to examine the capacity of a powered toothbrush as a carrier and mediator of health-related data.MethodsFor papers I and II, the participants were recruited from the Swedish site of the multicenter project Support Monitoring And Reminder Technology for Mild Dementia and for paper III from the Department of Health at Blekinge Institute of Technology. In all three papers, a powered toothbrush has been used as a tool, sensor carrier and transmitter of data. For Quality-of-life assessment two instruments are used, The QoL-AD and OHIP 14.ResultsBy introducing an intelligent powered toothbrush in the group of older individuals with mild cognitive impairment we have showed that they, regardless of cognitive level,improved their scores for plaque index, bleeding index and deepened periodontal pockets ≥ 4mm, over 12 months. The quality-of-life instrument related to oral health improved in parallel with the improvement in oral health. Furthermore, it is possible to use the intelligent powered toothbrush both as a carrier for healt related sensors and to transfer user data via Bluetooth technology to a single-core processor that stores or forwards the data via Wifi to an external computer for processing, analysis and storage. A fesibility study regarding temperature sensor for measuring body temperature during toothbrushing have been evaluated and found to be comparable to traditional oral temperature measurement. ConclusionsAn intelligent powered toothbrush is a well-functioning tool for maintaining oral health in older people with mild cognitive impairment as well as for collecting and transferring brush and health data to external units for storage and analysis.
17.	Flyborg, Johan, et al. (author) Use of a powered toothbrush to improve oral health in individuals with mild cognitive impairment 2023 In: Gerodontology. - : John Wiley & Sons. - 0734-0664 .- 1741-2358. ; 40:1, s. 74-82 Journal article (peer-reviewed)abstract ObjectivesThe aim of the study is to investigate whether the use of a powered toothbrush could maintain oral health by reducing the dental plaque (PI), bleeding on probing (BOP), and periodontal pocket depth (PPD) ≥4 mm in a group of individuals with MCI and also if changes in oral health affect various aspects of quality of life.BackgroundPeople with cognitive impairment tend to have poor oral hygiene and poorer Quality of life. In the present study, the participants were asked to use a powered toothbrush for at least 2 min morning and evening and no restrictions were given against the use of other oral care products. The participant survey conducted at each examination demonstrated that 61.2% of participants at baseline claimed to have experience of using a powered toothbrush, 95.4% at 6 months and 95% after 12 months. At the same time, the use of manual toothbrushes dropped from 73.3% to 44.7% from baseline to the 12-month check-up. This shows that several participants continue to use the manual toothbrush in parallel with the powered toothbrush, but that there is a shift towards increased use of the powered toothbrush. Removal of dental biofilm is essential for maintaining good oral health. We investigated whether using a powered toothbrush reduces the presence of dental plaque, bleeding on probing and periodontal pockets ≥4 mm in a group of older individuals with mild cognitive impairment.Materials and methodsTwo hundred and thirteen individuals with the mean age of 75.3 years living without official home care and with a Mini-Mental State Examination (MMSE) score between 20 and 28 and a history of memory problems in the previous six months were recruited from the Swedish site of a multicenter project, Support Monitoring And Reminder Technology for Mild Dementia (SMART4MD) and screened for the study. The individuals received a powered toothbrush and thorough instructions on how to use it. Clinical oral examinations and MMSE tests were conducted at baseline, 6 and 12 months.ResultsOne hundred seventy participants, 36.5% women and 63.5% men, completed a 12-month follow-up. The use of a powered toothbrush resulted, for the entire group, in a significant decrease in plaque index from 41% at baseline to 31.5% after 12 months (P < .000). Within the same time frame, the values for bleeding on probing changed from 15.1% to 9.9% (P < .000) and the percentage of probing pocket depths ≥4 mm from 11.5% to 8.2% (P < .004). The observed improvements in the Oral Health Impact Profile 14 correlate with the clinical improvements of oral health.ConclusionThe use of a powered toothbrush was associated with a reduction of PI, BOP and PPD over 12 months even among individuals with low or declining MMSE score. An adequately used powered toothbrush maintain factors that affect oral health and oral health-related Quality of Life in people with mild cognitive impairment.
18.	Ghani, Zartashia, 1980-, et al. (author) Economic evaluation of a software application (Support, Monitoring and Reminder Technology for Mild Dementia [SMART4MD]) designed for older adults with mild cognitive impairment (MCI) Other publication (other academic/artistic)
19.	Ghani, Zartashia, 1980-, et al. (author) Short Term Economic Evaluation of the Digital Platform "Support, Monitoring and Reminder Technology for Mild Dementia" (SMART4MD) for People with Mild Cognitive Impairment and their Informal Caregivers 2022 In: Journal of Alzheimer's Disease. - : IOS Press. - 1387-2877 .- 1875-8908. ; 86:4, s. 1629-1641 Journal article (peer-reviewed)abstract Background: A randomized controlled trial of the SMART4MD tablet application was conducted for persons with mild cognitive impairment (PwMCI) and their informal caregivers to improve or maintain quality of life. Objective: The objective was to conduct economic evaluation of SMART4MD compared to standard care in Sweden from a healthcare provider perspective based on a 6-month follow-up period. Methods: Three hundred forty-five dyads were enrolled: 173 dyads in the intervention group and 172 in standard care. The primary outcome measures for PwMCI and informal caregivers were quality-adjusted life years (QALY). The results are presented as incremental cost-effectiveness ratios, and confidence intervals are calculated using non-parametric bootstrap procedure. Results: For PwMCI, the mean difference in total costs between intervention and standard care was (sic)12 (95%CI: -2090 to 2115) (US$ =(sic) 1.19) and the mean QALY change was -0.004 (95%CI: -0.009 to 0.002). For informal caregivers, the cost difference was -(sic)539 (95%CI: -2624 to 1545) and 0.003 (95%CI: -0.002 to 0.008) for QALY. The difference in cost and QALY for PwMCI and informal caregivers combined was -(sic)527 (95%CI: -3621 to 2568) and -0.001 (95%CI: -0.008 to 0.006). Although generally insignificant differences, this indicates that SMART4MD, compared to standard care was: 1) more costly and less effective for PwMCI, 2) less costly and more effective for informal caregivers, and 3) less costly and less effective for PwMCI and informal caregivers combined. Conclusion: The cost-effectiveness of SMART4MD over 6 months is inconclusive, although the intervention might be more beneficial for informal caregivers than PwMCI.
20.	Ghani, Zartashia, 1980-, et al. (author) The Cost-Effectiveness of Mobile Health (mHealth) Interventions for Older Adults : Systematic Review 2020 In: International Journal of Environmental Research and Public Health. - : MDPI. - 1661-7827 .- 1660-4601. ; 17:15 Research review (peer-reviewed)abstract The objective of this study was to critically assess and review empirical evidence on the cost-effectiveness of Mobile Health (mHealth) interventions for older adults. We systematically searched databases such as Pubmed, Scopus, and Cumulative Index to Nursing and Allied Literature (CINAHL) for peer-reviewed economic evaluations published in English from 2007 to 2018. We extracted data on methods and empirical evidence (costs, effects, incremental cost-effectiveness ratio) and assessed if this evidence supported the reported findings in terms of cost-effectiveness. The consolidated health economic evaluation reporting standards (CHEERS) checklist was used to assess the reporting quality of the included studies. Eleven studies were identified and categorized into two groups: complex smartphone communication and simple text-based communication. Substantial heterogeneity among the studies in terms of methodological approaches and types of intervention was observed. The cost-effectiveness of complex smartphone communication interventions cannot be judged due to lack of information. Limited evidence of cost-effectiveness was found for interventions related to simple text-based communications. Comprehensive economic evaluation studies are warranted to assess the cost-effectiveness of mHealth interventions designed for older adults.
21.	Idrisoglu, Alper, et al. (author) Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders : Systematic Literature Review 2023 In: Journal of Medical Internet Research. - : JMIR Publications. - 1438-8871. ; 25 Research review (peer-reviewed)abstract BACKGROUND: Normal voice production depends on the synchronized cooperation of multiple physiological systems, which makes the voice sensitive to changes. Any systematic, neurological, and aerodigestive distortion is prone to affect voice production through reduced cognitive, pulmonary, and muscular functionality. This sensitivity inspired using voice as a biomarker to examine disorders that affect the voice. Technological improvements and emerging machine learning (ML) technologies have enabled possibilities of extracting digital vocal features from the voice for automated diagnosis and monitoring systems. OBJECTIVE: This study aims to summarize a comprehensive view of research on voice-affecting disorders that uses ML techniques for diagnosis and monitoring through voice samples where systematic conditions, nonlaryngeal aerodigestive disorders, and neurological disorders are specifically of interest. METHODS: This systematic literature review (SLR) investigated the state of the art of voice-based diagnostic and monitoring systems with ML technologies, targeting voice-affecting disorders without direct relation to the voice box from the point of view of applied health technology. Through a comprehensive search string, studies published from 2012 to 2022 from the databases Scopus, PubMed, and Web of Science were scanned and collected for assessment. To minimize bias, retrieval of the relevant references in other studies in the field was ensured, and 2 authors assessed the collected studies. Low-quality studies were removed through a quality assessment and relevant data were extracted through summary tables for analysis. The articles were checked for similarities between author groups to prevent cumulative redundancy bias during the screening process, where only 1 article was included from the same author group. RESULTS: In the analysis of the 145 included studies, support vector machines were the most utilized ML technique (51/145, 35.2%), with the most studied disease being Parkinson disease (PD; reported in 87/145, 60%, studies). After 2017, 16 additional voice-affecting disorders were examined, in contrast to the 3 investigated previously. Furthermore, an upsurge in the use of artificial neural network-based architectures was observed after 2017. Almost half of the included studies were published in last 2 years (2021 and 2022). A broad interest from many countries was observed. Notably, nearly one-half (n=75) of the studies relied on 10 distinct data sets, and 11/145 (7.6%) used demographic data as an input for ML models. CONCLUSIONS: This SLR revealed considerable interest across multiple countries in using ML techniques for diagnosing and monitoring voice-affecting disorders, with PD being the most studied disorder. However, the review identified several gaps, including limited and unbalanced data set usage in studies, and a focus on diagnostic test rather than disorder-specific monitoring. Despite the limitations of being constrained by only peer-reviewed publications written in English, the SLR provides valuable insights into the current state of research on ML-based voice-affecting disorder diagnosis and monitoring and highlighting areas to address in future research.
22.	Idrisoglu, Alper, et al. (author) COPDVD : Automated Classification of Chronic Obstructive Pulmonary Disease on a New Developed and Evaluated Voice Dataset Other publication (other academic/artistic)abstract AbstractBackground: Chronic obstructive pulmonary disease (COPD) is a severe condition affecting millions worldwide, leading to numerous annual deaths. The absence of significant symptoms in its early stages promotes high underdiagnosis rates for the affected people. Besides pulmonary function failure, another harmful problem of COPD is the systematical effects, e.g., heart failure or voice distortion. However, the systematic effects of COPD might provide valuable information for early detection. In other words, symptoms caused by systematic effects could be helpful to detect the condition in its early stages.Objective: The proposed study aims to: (i) investigate whether the voice features extracted from the vowel "A" phonation carry information that can be predictive of COPD by employing Machine Learning (ML); and (ii) develop a voice dataset based on the evaluation of the features.Methods: Forty-eight participants were recruited from the pool of research clinic visitors at Blekinge Institute of Technology (BTH) in Sweden between January 2022 and May 2023. A dataset consisting of 1246 recordings from 48 participants was gathered. The collection of voice recordings containing the vowel "A" phonation commenced following an information and consent meeting with each participant using the VoiceDiagnistic application. The collected voice data was subjected to silence segment removal, feature extraction of baseline acoustic features, and Mel Frequency Cepstrum Coefficients (MFCC). Sociodemographic data was also collected from the participants. Three ML models were investigated for the binary classification of COPD and healthy controls: Random Forest (RF), Support Vector Machine (SVM), and CatBoost (CB). A nested k-fold cross-validation approach was employed. Additionally, the hyperparameters were optimized using grid-search on each ML model. For best performance assessment, accuracy, F1-score, precision, and recall metrics were computed. Afterward, we further examined the best classifier by utilizing the Area Under the Curve (AUC), Average Precision (AP), and SHapley Additive exPlanations (SHAP) feature importance measures. Results: The classifiers RF, SVM, and CB achieved a maximum accuracy of 77%, 69%, and 78% on the test set and 93%, 78% and 97% on the validation set, respectively. The CB classifier outperformed RF and SVM. After further investigation of the best-performing classifier, CB demonstrated the highest performance, producing an AUC of 82% and AP of 76%. In addition to age and gender, the mean values of baseline acoustic and MFCC features demonstrate high importance and deterministic characteristics for classification performance in both test and validation sets, though in varied order. Conclusion: This study concludes that the vowel "A" recordings contain information that can be captured by the CatBoost classifier with high accuracy for the classification of COPD. Additionally, baseline acoustic and MFCC features, in conjunction with age and gender information, can be employed for classification purposes and benefit healthcare for decision support in COPD diagnosis. Lastly, we believe that the newly developed voice dataset will be a valuable resource to researchers within the domain.
23.	Javeed, Ashir, 1989-, et al. (author) Breaking barriers : a statistical and machine learning-based hybrid system for predicting dementia 2023 In: Frontiers in Bioengineering and Biotechnology. - : Frontiers Media S.A.. - 2296-4185. ; 11 Journal article (peer-reviewed)abstract Introduction: Dementia is a condition (a collection of related signs and symptoms) that causes a continuing deterioration in cognitive function, and millions of people are impacted by dementia every year as the world population continues to rise. Conventional approaches for determining dementia rely primarily on clinical examinations, analyzing medical records, and administering cognitive and neuropsychological testing. However, these methods are time-consuming and costly in terms of treatment. Therefore, this study aims to present a noninvasive method for the early prediction of dementia so that preventive steps should be taken to avoid dementia. Methods: We developed a hybrid diagnostic system based on statistical and machine learning (ML) methods that used patient electronic health records to predict dementia. The dataset used for this study was obtained from the Swedish National Study on Aging and Care (SNAC), with a sample size of 43040 and 75 features. The newly constructed diagnostic extracts a subset of useful features from the dataset through a statistical method (F-score). For the classification, we developed an ensemble voting classifier based on five different ML models: decision tree (DT), naive Bayes (NB), logistic regression (LR), support vector machines (SVM), and random forest (RF). To address the problem of ML model overfitting, we used a cross-validation approach to evaluate the performance of the proposed diagnostic system. Various assessment measures, such as accuracy, sensitivity, specificity, receiver operating characteristic (ROC) curve, and Matthew’s correlation coefficient (MCC), were used to thoroughly validate the devised diagnostic system’s efficiency. Results: According to the experimental results, the proposed diagnostic method achieved the best accuracy of 98.25%, as well as sensitivity of 97.44%, specificity of 95.744%, and MCC of 0.7535. Discussion: The effectiveness of the proposed diagnostic approach is compared to various cutting-edge feature selection techniques and baseline ML models. From experimental results, it is evident that the proposed diagnostic system outperformed the prior feature selection strategies and baseline ML models regarding accuracy.
24.	Javeed, Ashir, 1989-, et al. (author) Decision Support System for Predicting Mortality in Cardiac Patients Based on Machine Learning 2023 In: Applied Sciences. - : MDPI. - 2076-3417. ; 13:8 Journal article (peer-reviewed)abstract Researchers have proposed several automated diagnostic systems based on machine learning and data mining techniques to predict heart failure. However, researchers have not paid close attention to predicting cardiac patient mortality. We developed a clinical decision support system for predicting mortality in cardiac patients to address this problem. The dataset collected for the experimental purposes of the proposed model consisted of 55 features with a total of 368 samples. We found that the classes in the dataset were highly imbalanced. To avoid the problem of bias in the machine learning model, we used the synthetic minority oversampling technique (SMOTE). After balancing the classes in the dataset, the newly proposed system employed a (Formula presented.) statistical model to rank the features from the dataset. The highest-ranked features were fed into an optimized random forest (RF) model for classification. The hyperparameters of the RF classifier were optimized using a grid search algorithm. The performance of the newly proposed model ((Formula presented.) _RF) was validated using several evaluation measures, including accuracy, sensitivity, specificity, F1 score, and a receiver operating characteristic (ROC) curve. With only 10 features from the dataset, the proposed model (Formula presented.) _RF achieved the highest accuracy of 94.59%. The proposed model (Formula presented.) _RF improved the performance of the standard RF model by 5.5%. Moreover, the proposed model (Formula presented.) _RF was compared with other state-of-the-art machine learning models. The experimental results show that the newly proposed decision support system outperforms the other machine learning systems using the same feature selection module ((Formula presented.)).
25.	Javeed, Ashir, 1989-, et al. (author) Optimizing Depression Prediction in Older Adults : A Comparative Study of Feature Extraction and Machine Learning Models 2024 Conference paper (peer-reviewed)abstract Depression emerged as a major public health concern in older adults, and timely prediction of depression has become a difficult problem in medical informatics. The latest studies have attentiveed on feature transformation and selection for better depression prediction. In this study, we assess the performance of various feature extraction algorithms, including principal component analysis (PCA), independent component analysis (ICA), locally linear Embedding (LLE), and t-distributed stochastic neighbor embedding (TSNE). These algorithms are combined with machine learning (ML) classifier algorithms such as Gaussian Naive Bayes (GNB), Logistic Regression (LR), K- nearest-neighbor (KNN), and Decision Tree (DT) to enhance depression prediction. In total, sixteen automated integrated systems are constructed based on the above-mentioned feature extraction methods and ML classifiers. The performance of all of these integrated models is assessed using data from the Swedish National Study on Aging and Care (SNAC). According to the experimental results, the PCA algorithm combined with the Logistic Regression (LR) model provides 89.04% depression classification accuracy. As a result, it is demonstrated that the PCA is a more suitable feature extraction method for depression data than ICA, LLE, and TSNE.
26.	Javeed, Ashir, 1989-, et al. (author) Predictive Power of XGBoost_BiLSTM Model : A Machine-Learning Approach for Accurate Sleep Apnea Detection Using Electronic Health Data 2023 In: International Journal of Computational Intelligence Systems. - : Springer Nature. - 1875-6891 .- 1875-6883. ; 16:1 Journal article (peer-reviewed)abstract Sleep apnea is a common disorder that can cause pauses in breathing and can last from a few seconds to several minutes, as well as shallow breathing or complete cessation of breathing. Obstructive sleep apnea is strongly associated with the risk of developing several heart diseases, including coronary heart disease, heart attack, heart failure, and stroke. In addition, obstructive sleep apnea increases the risk of developing irregular heartbeats (arrhythmias), which can lead to low blood pressure. To prevent these conditions, this study presents a novel machine-learning (ML) model for predicting sleep apnea based on electronic health data that provides accurate predictions and helps in identifying the risk factors that contribute to the development of sleep apnea. The dataset used in the study includes 75 features and 10,765 samples from the Swedish National Study on Aging and Care (SNAC). The proposed model is based on two modules: the XGBoost module assesses the most important features from feature space, while the Bidirectional Long Short-Term Memory Networks (BiLSTM) module classifies the probability of sleep apnea. Using a cross-validation scheme, the proposed XGBoost_BiLSTM algorithm achieves an accuracy of 97% while using only the six most significant features from the dataset. The model’s performance is also compared with conventional long-short-term memory networks (LSTM) and other state-of-the-art ML models. The results of the study suggest that the proposed model improved the diagnosis and treatment of sleep apnea by identifying the risk factors.
27.	Anderberg, Peter, et al. (author) A Novel Instrument for Measuring Older People's Attitudes Toward Technology (TechPH) : Development and Validation 2019 In: Journal of Medical Internet Research. - : JMIR PUBLICATIONS, INC. - 1438-8871. ; 21:5 Journal article (peer-reviewed)abstract Background: The use of health technology by older people is coming increasingly in focus with the demographic changes. Health information technology is generally perceived as an important factor in enabling increased quality of life and reducing the cost of care for this group. Age-appropriate design and facilitation of technology adoption are important to ensure functionality and removal of various barriers to usage. Development of assessment tools and instruments for evaluating older persons' technology adoption and usage as well as measuring the effects of the interventions are of high priority. Both usability and acceptance of a specific technology or service are important factors in evaluating the impact of a health information technology intervention. Psychometric measures are seldom included in evaluations of health technology. However, basic attitudes and sentiments toward technology (eg, technophilia) could be argued to influence both the level of satisfaction with the technology itself as well as the perception of the health intervention outcome. Objective: The purpose of this study is to develop a reduced and refined instrument for measuring older people's attitudes and enthusiasm for technology based on relevant existing instruments for measuring technophilia A requirement of the new instrument is that it should be short and simple to make it usable for evaluation of health technology for older people. Methods: Initial items for the TechPH questionnaire were drawn from a content analysis of relevant existing technophilia measure instruments. An exploratory factor analysis was conducted in a random selection of persons aged 65 years or older (N=374) on eight initial items. The scale was reduced to six items, and the internal consistency and reliability of the scale were examined. Further validation was made by a confirmatory factor analysis (CFA). Results: The exploratory factor analysis resulted in two factors. These factors were analyzed and labeled techEnthusiasm and techAnxiety. They demonstrated relatively good internal consistency (Cronbach alpha=.72 and .68, respectively). The factors were confirmed in the CFA and showed good model fit (chi(2)(8)=21.2, chi(2)/df=2.65, comparative fit index=0.97, adjusted goodness-of-fit index=0.95, root mean square error of approximation=0.067, standardized root mean square residual=0.036). Conclusions: The construed TechPH score showed expected relations to external real-world criteria, and the two factors showed interesting internal relations. Different technophilia personality traits distinguish clusters with different behaviors of adaptation as well as usage of new technology. Whether there is an independent association with the TechPH score against outcomes in health technology projects needs to be shown in further studies. The instrument must also be validated in different contexts, such as other countries.
28.	Anderberg, Peter, et al. (author) An instrument for measuring social participation to examine older adults' use of the internet as a social platform : Development and validation study 2021 In: JMIR Aging. - : JMIR Publications Inc.. - 2561-7605. ; 4:2 Journal article (peer-reviewed)abstract Background: Older people's use of the internet is increasingly coming into focus with the demographic changes of a growing older population. Research reports several benefits of older people's internet use and highlights problems such as various forms of inequality in use within the group. There is a need for consistent measurements to follow the development and use of the internet in this group and to be able to compare groups both within and between countries, as well as follow the changes over time. Objective: The aim of this study was to create an instrument to measure an older person's perception of the benefits of their online social participation, unconnected to specific applications and services. The instrument to measure internet social participation proposed in this paper builds on social participation factors and is a multidimensional construct incorporating both social relations and societal connectedness. Methods: A short instrument for measuring social participation over the internet was created. An exploratory factor analysis (EFA) was conducted in a random selection of persons aged 65 years or older (n=193) on 10 initial items. Further validation was made by confirmatory factor analysis (CFA) in the remaining group (n=193). Results: A 1-factor solution for the social internet score was decided upon after exploratory factor analysis (EFA; based on a random sample of half the data set). None of the questionnaire items were excluded based on the EFA, as they all had high loadings, the lowest being 0.61. The Cronbach α coefficient was.92. The 1-factor solution explained 55% of the variance. CFA was performed and included all 10 questionnaire items in a 1-factor solution. Indices of goodness of fit of the model showed room for improvement. Removal of 4 questions in a stepwise procedure resulted in a 6-item model (χ26=13.985; χ2/degrees of freedom=1.554; comparative fit index=0.992; root mean square error of approximation=0.054; standardized root mean square residual=0.025). Conclusions: The proposed instrument can be used to measure digital social participation and coherence with society. The factor analysis is based on a sufficient sample of the general population of older adults in Sweden, and overall the instrument performed as expected. © Peter Anderberg, Linda Abrahamsson, Johan Sanmartin Berglund. Originally published in JMIR Aging (https://aging.jmir.org),17.05.2021. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Aging, is properly cited. The complete bibliographic information, a link to the original publication on https://aging.jmir.org, as well as this copyright and license information must be included.
29.	Anderberg, Peter, et al. (author) Older people’s use and nonuse of the internet in Sweden 2020 In: International Journal of Environmental Research and Public Health. - : MDPI. - 1661-7827 .- 1660-4601. ; 17:23, s. 1-11 Journal article (peer-reviewed)abstract The use of the internet has considerably increased over recent years, and the importance of internet use has also grown as services have gone online. Sweden is largely an information society like other countries with high reported use amongst European countries. In line with digitalization development, society is also changing, and many activities and services today take place on the internet. This development could potentially lead to those older persons who do not use the internet or do not follow the development of services on the internet finding it difficult to take part in information and activities that no longer occur in the physical world. This has led to a digital divide between groups, where the older generations (60+), in particular, have been affected. In a large study of Sweden’s adult population in 2019, 95 percent of the overall population was said to be internet users, and the corresponding number for users over 66 years of age was 84%. This study shows that the numbers reported about older peoples’ internet use, most likely, are vastly overestimated and that real use is significantly lower, especially among the oldest age groups. We report that 62.4% of the study subjects are internet users and that this number most likely also is an overestimation. When looking at nonresponders to the questionnaire, we find that they display characteristics generally attributed to non-use, such as lower education, lower household economy, and lower cognitive functioning.
30.	Anderberg, Peter, et al. (author) The Effects of the Digital Platform Support Monitoring and Reminder Technology for Mild Dementia (SMART4MD) for People With Mild Cognitive Impairment and Their Informal Carers : Protocol for a Pilot Randomized Controlled Trial 2019 In: JMIR Research Protocols. - : JMIR PUBLICATIONS, INC. - 1929-0748. ; 8:6 Journal article (peer-reviewed)abstract Background: Many countries are witnessing a trend of growth in the number and proportion of older adults within the total population. In Europe, population aging has had and will continue to have major social and economic consequences. This is a fundamentally positive development where the added life span is of great benefit for both the individual and the society. Yet, the risk for the individual to contract noncommunicable diseases and disability increases with age. This may adversely affect the individual's ability to live his or her life in the way that is desired. Cognitive conditions constitute a group of chronic diseases that predominantly affects older people. Recent technology advancements can help support the day-to-day living activities at home for people with cognitive impairments. Objective: A digital platform (Support Monitoring and Reminder for Mild Dementia; SMART4MD) is created to improve or maintain the quality of life for people with mild cognitive impairment (PwMCI) and their carers. The platform will provide reminders, information, and memory support in everyday life, with the purpose of giving structure and lowering stress. In the trial, we will include participants with a diagnosed neurocognitive disorder as well as persons with an undiagnosed subjective memory problem and cognitive impairment, that is, 20 to 28 points on the Mini-Mental State Examination. Methods: A pragmatic, multicenter RCT is being conducted in Spain, Sweden, and Belgium. The targets for recruitment are 1200 dyads-split into an intervention group and a control group that are in usual care. Intervention group participants will be provided with a data-enabled computer tablet with the SMART4MD app. Its core functionalities, intended to be used daily at home, are based on reminders, cognitive supporting activities, and sharing health information. Results: Inclusion of participants started in December 2017, and recruitment is expected to end in February 2019. Furthermore, there will be 3 follow-up visits at 6, 12, and 18 months after the baseline visit. Conclusions: This RCT is expected to offer benefits at several levels including in-depth knowledge of the possibilities of introducing a holistic multilayered information and communication technology solution for this group. SMART4MD has been developed in a process involving the structured participation of PwMCI, their informal carers, and clinicians. The adoption of SMART4MD faces the challenge of this age group's relative unfamiliarity with digital devices and services. However, this challenge can also be an opportunity for developing a digital device tailored to a group at risk of digital exclusion. This research responds to the wider call for the development of digital devices which are accessible and affordable to older people and this full scale RCT can hopefully serve as a model for further studies in this field.
31.	Axén, Anna, 1984-, et al. (author) Loneliness in Relation to Social Factors and Self-Reported Health Among Older Adults : A Cross-Sectional Study 2023 In: Journal of Primary Care & Community Health. - : Sage Publications. - 2150-1319 .- 2150-1327. ; 14 Journal article (peer-reviewed)abstract BACKGROUND: Loneliness is described as a public health problem and can be both a consequence of aging and a cause of ill health. Lonely older adults tend to have difficulties making new social connections, essential in reducing loneliness. Loneliness often varies over time, but established loneliness tends to persist. Maintaining good health is fundamental throughout the life course. Social connections change with aging, which can contribute to loneliness. AIM: This study aimed to investigate loneliness in relation to social factors and self-reported health among older adults. METHOD: A cross-sectional research design was used based on data from the Swedish National Study on Aging and Care, Blekinge (SNAC-B), from February 2019 to April 2021. Statistical analysis consisted of descriptive and inferential analysis. RESULTS: Of n = 394 participants, 31.7% (n = 125) stated loneliness. Close emotional connections were necessary for less loneliness. Loneliness was more common among those who did not live with their spouse or partner and met more rarely. Furthermore, seeing grandchildren and neighbors less often increased loneliness, and a more extensive social network decreased loneliness. CONCLUSION: This study underlined the importance of social connections and having someone to share a close, emotional connection with to reduce loneliness.
32.	Behrens, Anders, et al. (author) CoGNIT Automated Tablet Computer Cognitive Testing in Patients With Mild Cognitive Impairment : Feasibility Study 2022 In: JMIR Formative Research. - : JMIR Publications Inc.. - 2561-326X. ; 6:3 Journal article (peer-reviewed)abstract Background: Early diagnosis of cognitive disorders is becoming increasingly important. Limited resources for specialist assessment and an increasing demographical challenge warrants the need for efficient methods of evaluation. In response, CoGNIT, a tablet app for automatic, standardized, and efficient assessment of cognitive function, was developed. Included tests span the cognitive domains regarded as important for assessment in a general memory clinic (memory, language, psychomotor speed, executive function, attention, visuospatial ability, manual dexterity, and symptoms of depression). Objective: The aim of this study was to assess the feasibility of automatic cognitive testing with CoGNIT in older patients with symptoms of mild cognitive impairment (MCI). Methods: Patients older than 55 years with symptoms of MCI (n=36) were recruited at the research clinic at the Blekinge Institute of Technology (BTH), Karlskrona, Sweden. A research nurse administered the Mini-Mental State Exam (MMSE) and the CoGNIT app on a tablet computer. Technical and testing issues were documented. Results: The test battery was completed by all 36 patients. One test, the four-finger-tapping test, was performed incorrectly by 42% of the patients. Issues regarding clarity of instructions were found in 2 tests (block design test and the one finger-tapping test). Minor software bugs were identified. Conclusions: The overall feasibility of automatic cognitive testing with the CoGNIT app in patients with symptoms of MCI was good. The study highlighted tests that did not function optimally. The four-finger-tapping test will be discarded, and minor improvements to the software will be added before further studies and deployment in the clinic. © 2022 JMIR Publications Inc.. All right reserved.
33.	Behrens, Anders, et al. (author) Sleep disturbance predicts worse cognitive performance in subsequent years : A longitudinal population-based cohort study 2023 In: Archives of gerontology and geriatrics (Print). - : Elsevier. - 0167-4943 .- 1872-6976. ; 106 Journal article (peer-reviewed)abstract Background: Poor sleep is a potential modifiable risk factor for later life development cognitive impairment. The aim of this study is to examine if subjective measures of sleep duration and sleep disturbance predict future cognitive decline in a population-based cohort of 60, 66, 72 and 78-year-olds with a maximal follow up time of 18 years. Methods: This study included participants from the Swedish National Study on Ageing and Care – Blekinge, with assessments 2001–2021. A cohort of 60 (n = 478), 66 (n = 623), 72 (n = 662) and 78 (n = 548) year-olds, were assessed at baseline and every 6 years until 78 years of age. Longitudinal associations between sleep disturbance (sleep scale), self-reported sleep duration and cognitive tests (Mini Mental State Examination and the Clock drawing test) were examined together with typical confounders (sex, education level, hypertension, hyperlipidemia, smoking status, physical inactivity and depression). Results: There was an association between sleep disturbance at age 60 and worse cognitive function at ages 60, 66 and 72 years in fully adjusted models. The association was attenuated after bootstrap-analysis for the 72-year-olds. The items of the sleep scale most predictive of later life cognition regarded nightly awakenings, pain and itching and daytime naps. Long sleep was predictive of future worse cognitive function. Conclusion: Sleep disturbance was associated with worse future cognitive performance for the 60-year-olds, which suggests poor sleep being a risk factor for later life cognitive decline. Questions regarding long sleep, waking during the night, pain and itching and daytime naps should be further explored in future research and may be targets for intervention.
34.	Bengtsson, Viveca Wallin, et al. (author) Periodontitis related to cardiovascular events and mortality : a long-time longitudinal study 2021 In: Clinical Oral Investigations. - : Springer Science and Business Media Deutschland GmbH. - 1432-6981 .- 1436-3771. ; 25:6, s. 4085-4095 Journal article (peer-reviewed)abstract Objective: The present study assessed if individuals ≥ 60 years of age with periodontitis are more likely to develop stroke or ischemic heart diseases, or at a higher risk of death for 17 years. Material and methods: At baseline individuals ≥ 60 received a dental examination including a panoramic radiograph. Periodontitis was defined as having ≥ 30% sites with ≥ 5-mm distance from the cementoenamel junction to the marginal bone level. Medical records were annually reviewed from 2001 to 2018. Findings from the medical records identifying an ICD-10 code of stroke and ischemic heart diseases or death were registered. Results: Associations between periodontitis and incidence of ischemic heart disease were found in this 17-year follow-up study in all individuals 60–93 years (HR: 1.5, CI: 1.1–2.1, p = 0.017), in women (HR: 2.1, CI: 1.3–3.4, p = 0.002), and in individuals 78–96 years (HR: 1.7, CI: 1.0–2.6, p = 0.033). Periodontitis was associated with mortality in all individuals (HR: 1.4, CI: 1.2–1.8, p = 0.002), specifically in men (HR: 1.5, CI: 1.1–1.9, p = 0.006) or in ages 60–72 years (HR: 2.2, CI: 1.5–3.2, p = 0.000). Periodontitis was more prevalent among men (OR: 1.8, CI: 1.3–2.4, p = 0.000). Conclusions: Individuals with periodontitis have an increased risk for future events of ischemic heart diseases and death. Clinical relevance: Improving periodontal health in older individuals may reduce overall mortality and ischemic heart diseases. Both dental and medical professionals should be aware of the associations and ultimately cooperate. © 2021, The Author(s).
35.	Berner, Jessica, et al. (author) A cross-national and longitudinal study on predictors in starting and stopping Internet use (2001-2013) by Swedish and Dutch older adults 66 years and above 2016 In: Gerontechnology. - : International Society for Gerontechnology. - 1569-1101 .- 1569-111X. ; 14:3, s. 157-168 Journal article (peer-reviewed)abstract Background The Internet and information communication technology is today considered as a means to sustain active and healthy aging, and to provide better care for the aging population. There is an increase in prevalence in older adults using the Internet, however many are still not using the Internet. This study therefore, investigated predictors in starting and stopping Internet use by older adults between 2001-2013 in Sweden and the Netherlands. These represent currently two of the highest older adult Internet users in Europe. The aim of this study was to examine, first, if there was a different starting and stopping rate in Sweden and the Netherlands; second, if the predictors age, gender, education, rural/urban living, living alone/not, cognition and functional limitations have different effects in either country. Methods A cross-national and longitudinal design was chosen. Data was used from the Longitudinal Aging study Amsterdam (LASA) and the Swedish National Study on Aging and Care (SNAC). Cox regression analyses were done to test the predictors over time with starting or stopping Internet use. An interaction term ‘variable*country’ was then considered for each variable, if significant, leading to a stratification into a multivariate model per country. Results More older adults started use in the Netherlands (19%); lower in age, normal cognitive functioning, living alone, fewer functional limitations and lower education were predictive of starting. In Sweden fewer started (10.3%), where being female was the only significant predictor of starting use. Both countries did not have many people stopping use; in the Netherlands (3%) they were younger in age and living urban, whereas in Sweden (1.7%), they had lower cognitive functioning. Conclusion Results indicate that there are differences between countries in starting use. These differences can possibly be explained by the early adoption of the Internet in Sweden. The new findings that the older adults living alone and lower educated are now going online, are positive regarding the theme of active aging. For those stopping use, the differences are more country-specific. More research is needed in order to understand better what an older adult was using the Internet for and why they stop. © 2016. Gerontechnology. All Rights Reserved.
36.	Berner, Jessica, et al. (author) Maintaining cognitive function with internet use : a two-country, six-year longitudinal study 2019 In: International psychogeriatrics. - : Cambridge University Press. - 1041-6102 .- 1741-203X. ; 31:7, s. 929-936 Journal article (peer-reviewed)abstract Objectives: Maintaining good cognitive function with aging may be aided by technology such as computers, tablets, and their applications. Little research so far has investigated whether internet use helps to maintain cognitive function over time.Design: Two population-based studies with a longitudinal design from 2001/2003 (T1) to 2007/2010 (T2).Setting: Sweden and the Netherlands.Participants: Older adults aged 66 years and above from the Swedish National Study on Ageing and Care (N = 2,564) and from the Longitudinal Aging Study Amsterdam (N = 683).Measurements: Internet use was self-reported. Using the scores from the Mini-Mental State Examination (MMSE) from T1 and T2, both a difference score and a significant change index was calculated. Linear and logistic regression analysis were performed with difference score and significant change index, respectively, as the dependent variable and internet use as the independent variable, and adjusted for sex, education, age, living situation, and functional limitations. Using a meta-analytic approach, summary coefficients were calculated across both studies.Results: Internet use at baseline was 26.4% in Sweden and 13.3% in the Netherlands. Significant cognitive decline over six years amounted to 9.2% in Sweden and 17.0% in the Netherlands. Considering the difference score, the summary linear regression coefficient for internet use was-0.32 (95% CI:-0.62,-0.02). Considering the significant change index, the summary odds ratio for internet use was 0.54 (95% CI: 0.37, 0.78).Conclusions: The results suggest that internet use might play a role in maintaining cognitive functioning. Further research into the specific activities that older adults are doing on the internet may shine light on this issue.
37.	Berner, Jessica, et al. (author) Technology anxiety and technology enthusiasm versus digital ageism 2022 In: Gerontechnology. - : International Society for Gerontechnology (ISG). - 1569-1101 .- 1569-111X. ; 21:1 Journal article (peer-reviewed)abstract Background: Europe has called attention to the importance of the e-inclusion of older adults. Society is indicating that the developers, websites, and devices are causing age bias in technology. This affects living independently, the values of ethical principles associated with an older person, and digital ageism: which is an age-related bias in artificial intelligence systems. Objective: This research attempts to investigate the instrument technology anxiety and enthusiasm, and assistive technology devices during the period 2019- 2021. This instrument may be a way to redress misconceptions about digital ageism. The assistive technology device that we will investigate in this study is the adoption of a service that is designed for online health consultations. Method: The participants are part of the longitudinal Swedish National Study on Aging and Care. Technology anxiety and technology enthusiasm are two factors, which aim to measure technophilia (vs technophobia) in older adults. The age range is 63 -99 years of age in 2019 T1 and 66 -101 in 2021 T2. Wilcoxon rank test was conducted to investigate technology enthusiasm, technology anxiety, and how they changed with time. An Edwards Nunnally index was then calculated for both variables to observe a significant change in score from T1 to T2. Mann Whitney U test was used to investigate the variables sex and health status with technology anxiety & technology enthusiasm in T1 & T2. Age, Cognitive function MMSE, and digital social participation were investigated through a Kruskall-Wallis test. A logistic regression was conducted with the significant variable. Results: Between 2019-2021, change in technology enthusiasm was based on less digital social participation (OR: 0.608; CI 95%: 0.476- 0.792). Technology anxiety was significantly higher due to age (OR: 1.086, CI 95%: 1.035-1.139) and less digital social participation (OR: 0.684; CI 95%: 0.522- 0.895). The want for online healthcare consultations was popular but usage was low. Conclusion: Staying active on- line and participating digitally may be a way to reduce digital ageism. However, digital ageism is a complex phenomenon, which requires different solutions in order to include older people and reduce an inaccurate categorisation of this group in the digital society.
38.	Berner, Jessica, et al. (author) Technology anxiety and technology enthusiasm versus digital ageism 2022 In: Gerontechnology. - : International Society for Gerontechnology. - 1569-1101 .- 1569-111X. ; 21:1 Journal article (peer-reviewed)abstract Background: Europe has called attention to the importance of the e-inclusion of older adults. Society is indicating that the developers, websites, and devices are causing age bias in technology. This affects living independently, the values of ethical principles associated with an older person, and digital ageism: which is an age-related bias in artificial intelligence systems. Objective: This research attempts to investigate the instrument technology anxiety and enthusiasm, and assistive technology devices during the period 2019-2021. This instrument may be a way to redress misconceptions about digital ageism. The assistive technology device that we will investigate in this study is the adoption of a service that is designed for online health consultations. Method: The participants are part of the longitudinal Swedish National Study on Aging and Care. Technology anxiety and technology enthusiasm are two factors, which aim to measure technophilia (vs technophobia) in older adults. The age range is 63 -99 years of age in 2019 T1 and 66 -101 in 2021 T2. Wilcoxon rank test was conducted to investigate technology enthusiasm, technology anxiety, and how they changed with time. An Edwards Nunnally index was then calculated for both variables to observe a significant change in score from T1 to T2. Mann Whitney U test was used to investigate the variables sex and health status with technology anxiety & technology enthusiasm in T1 & T2. Age, Cognitive function MMSE, and digital social participation were investigated through a Kruskall-Wallis test. A logistic regression was conducted with the significant variable. Results: Between 2019-2021, change in technology enthusiasm was based on less digital social participation (OR: 0.608; CI 95%: 0.476-0.792). Technology anxiety was significantly higher due to age (OR: 1.086, CI 95%: 1.035-1.139) and less digital social participation (OR: 0.684; CI 95%: 0.522-0.895). The want for online healthcare consultations was popular but usage was low. Conclusion: Staying active online and participating digitally may be a way to reduce digital ageism. However, digital ageism is a complex phenomenon, which requires different solutions in order to include older people and reduce an inaccurate categorisation of this group in the digital society © 2022,Gerontechnology. All Rights Reserved.
39.	Boutry, Céline, et al. (author) The Adjuvanted Recombinant Zoster Vaccine Confers Long-Term Protection Against Herpes Zoster : Interim Results of an Extension Study of the Pivotal Phase 3 Clinical Trials ZOE-50 and ZOE-70 2022 In: Clinical Infectious Diseases. - : Oxford University Press. - 1058-4838 .- 1537-6591. ; 74:8, s. 1459-1467 Journal article (peer-reviewed)abstract Efficacy against herpes zoster and immune responses to the adjuvanted recombinant zoster vaccine plateaued at high levels between 5.1 and 7.1 years (mean) post-vaccination, suggesting that its clinical benefit in older adults is sustained for at least 7 years post-vaccination. Background This ongoing follow-up study evaluated the persistence of efficacy and immune responses for 6 additional years in adults vaccinated with the glycoprotein E (gE)-based adjuvanted recombinant zoster vaccine (RZV) at age >= 50 years in 2 pivotal efficacy trials (ZOE-50 and ZOE-70). The present interim analysis was performed after >= 2 additional years of follow-up (between 5.1 and 7.1 years [mean] post-vaccination) and includes partial data for year (Y) 8 post-vaccination. Methods Annual assessments were performed for efficacy against herpes zoster (HZ) from Y6 post-vaccination and for anti-gE antibody concentrations and gE-specific CD4[2+] T-cell (expressing >= 2 of 4 assessed activation markers) frequencies from Y5 post-vaccination. Results Of 7413 participants enrolled for the long-term efficacy assessment, 7277 (mean age at vaccination, 67.2 years), 813, and 108 were included in the cohorts evaluating efficacy, humoral immune responses, and cell-mediated immune responses, respectively. Efficacy of RZV against HZ through this interim analysis was 84.0% (95% confidence interval [CI], 75.9-89.8) from the start of this follow-up study and 90.9% (95% CI, 88.2-93.2) from vaccination in ZOE-50/70. Annual vaccine efficacy estimates were >84% for each year since vaccination and remained stable through this interim analysis. Anti-gE antibody geometric mean concentrations and median frequencies of gE-specific CD4[2+] T cells reached a plateau at approximately 6-fold above pre-vaccination levels. Conclusions Efficacy against HZ and immune responses to RZV remained high, suggesting that the clinical benefit of RZV in older adults is sustained for at least 7 years post-vaccination.
40.	Christiansen, Line, et al. (author) Associations Between Mobile Health Technology use and Self-rated Quality of Life : A Cross-sectional Study on Older Adults with Cognitive Impairment 2021 In: Gerontology and geriatric medicine. - : Sage Publications. - 2333-7214. ; 7, s. 1-8 Journal article (peer-reviewed)abstract Background: Quality of life (QoL) is affected even at early stages in older adults with cognitive impairment. The use of mobile health (mHealth) technology can offer support in daily life and improve the physical and mental health of older adults. However, a clarification of how mHealth technology can be used to support the QoL of older adults with cognitive impairment is needed. Objective: To investigate factors affecting mHealth technology use in relation to self-rated QoL among older adults with cognitive impairment. Methods: A cross-sectional research design was used to analyse mHealth technology use and QoL in 1,082 older participants. Baseline data were used from a multi-centered randomized controlled trial including QoL, measured by the Quality of Life in Alzheimer’s Disease (QoL-AD) Scale, as the outcome variable. Data were analyzed using logistic regression models. Results: Having moderately or high technical skills in using mHealth technology and using the internet via mHealth technology on a daily or weekly basis was associated with good to excellent QoL in older adults with cognitive impairment. Conclusions: The variation in technical skills and internet use among the participants can be interpreted as an obstacle for mHealth technology to support QoL. © The Author(s) 2021.
41.	Christiansen, Line, et al. (author) Health-related quality of life and related factors among a sample of older people with cognitive impairment 2019 In: Nursing Open. - : Wiley-Blackwell Publishing Inc.. - 2054-1058. ; 6:3, s. 849-859 Journal article (peer-reviewed)abstract Aim: This study aimed to identify factors affecting health-related quality of life (HRQoL) of older adults with cognitive impairment and to describe the association of these factors with different components of HRQoL. Design: A cross-sectional, descriptive research design was used. Methods: Data were collected from 247 individuals aged 60 years and older from a Swedish longitudinal cohort study. The Short-Form Health Survey-12 (SF-12) and EuroQol (EQ-5D) were used to assess HRQoL. The data were analysed using descriptive and comparative statistics. Results: The present study identified several factors that influenced HRQoL of older adults with cognitive impairment. The results of a multiple logistic regression analysis revealed that the following factors were associated with physical and mental HRQoL: dependency in activities of daily living (ADL), receiving informal care and feelings of loneliness and pain. © 2019 The Authors. Nursing Open published by John Wiley & Sons Ltd.
42.	Christiansen, Line, et al. (author) Using Mobile Health and the Impact on Health-Related Quality of Life : Perceptions of Older Adults with Cognitive Impairment 2020 In: International Journal of Environmental Research and Public Health. - : MDPI. - 1661-7827 .- 1660-4601. ; 17:8 Journal article (peer-reviewed)abstract Digital health technologies such as mobile health (mHealth) are considered to have the potential to support the needs of older adults with cognitive impairment. However, the evidence for improving health with the use of mHealth applications is of limited quality. Few studies have reported on the consequences of technology use concerning the older adults' quality of life. The purpose of this study was to describe perceptions of mHealth and its impact on health-related quality of life (HRQoL) among older adults with cognitive impairment. The study was conducted using a qualitative design with a phenomenographic approach. A total of 18 older participants with cognitive impairment were interviewed. The interviews were analyzed in order to apply phenomenography in a home-care context. The results showed variations in the older adults' perceptions that were comprised within three categories of description; Require technology literacy, Maintain social interaction, and Facilitate independent living. In conclusion, the development and design of mHealth technologies need to be tailored based on older adults´ needs in order to be understood and perceived as useful in a home-care context. For mHealth to support HRQoL, healthcare should be provided in a way that encourages various forms of communication and interaction.
43.	Criten, Sladjana, et al. (author) Oral health status among 60-year-old individuals born in 1941-1943 and 1954-1955 and 81-year-old individuals born in 1922-1924 and 1933-1934, respectively : a cross-sectional study 2022 In: Clinical Oral Investigations. - : Springer Berlin/Heidelberg. - 1432-6981 .- 1436-3771. ; :11, s. 6733-6742 Journal article (peer-reviewed)abstract Objective This study aimed to analyze the oral health status of four different birth cohorts: two cohorts of 60-year-olds born in 1941-1943 and 1954-1955 and 2 cohorts of 81-year-olds born in 1920-1922 and 1933-1934. Material and methods The study was based on data from an ongoing longitudinal population project, The Swedish National Study on Aging and Care (SNAC). Oral health status was repeatedly examined clinically and radiographically in 2001-2003 and 2014-2015, including 60- and 81-year-olds, in total 412 individuals. Statistical analyses were performed using independent-samples t test and Pearson's chi(2) test. Results More individuals were dentate in 2014-2015 compared to 2001-2003 in the two age groups: 60 and 81 years (p < 0.001 for both). The mean number of teeth increased in the 60-year-olds from 24.2 to 27.0 and in the 81-year-olds from 14.3 to 20.2. The numbers of at least one intact tooth increased for both age groups (p < 0.001 and p < 0.004, respectively). In the age groups 81 years, there was an increase in having at least one PPD >= 6 mm (p < 0.016) and bone loss >= 5 mm (p < 0.029) between the two examinations. No such differences were found in the age groups of 60 years. Conclusion Over 13 years, oral health improved for both 60- and 81-year-old age groups. The most significant changes were in the 81-year-olds where oral health had improved except for periodontal status.
44.	Dallora Moraes, Ana Luiza, et al. (author) Age assessment of youth and young adults using magnetic resonance imaging of the knee : A deep learning approach 2019 In: JMIR Medical Informatics. - : JMIR PUBLICATIONS. - 2291-9694. ; 7:4, s. 419-436 Journal article (peer-reviewed)abstract Background: Bone age assessment (BAA) is an important tool for diagnosis and in determining the time of treatment in a number of pediatric clinical scenarios, as well as in legal settings where it is used to estimate the chronological age of an individual where valid documents are lacking. Traditional methods for BAA suffer from drawbacks, such as exposing juveniles to radiation, intra- and interrater variability, and the time spent on the assessment. The employment of automated methods such as deep learning and the use of magnetic resonance imaging (MRI) can address these drawbacks and improve the assessment of age. Objective: The aim of this paper is to propose an automated approach for age assessment of youth and young adults in the age range when the length growth ceases and growth zones are closed (14-21 years of age) by employing deep learning using MRI of the knee. Methods: This study carried out MRI examinations of the knee of 402 volunteer subjects-221 males (55.0%) and 181 (45.0%) females-aged 14-21 years. The method comprised two convolutional neural network (CNN) models: the first one selected the most informative images of an MRI sequence, concerning age-assessment purposes; these were then used in the second module, which was responsible for the age estimation. Different CNN architectures were tested, both training from scratch and employing transfer learning. Results: The CNN architecture that provided the best results was GoogLeNet pretrained on the ImageNet database. The proposed method was able to assess the age of male subjects in the range of 14-20.5 years, with a mean absolute error (MAE) of 0.793 years, and of female subjects in the range of 14-19.5 years, with an MAE of 0.988 years. Regarding the classification of minors-with the threshold of 18 years of age-an accuracy of 98.1% for male subjects and 95.0% for female subjects was achieved. Conclusions: The proposed method was able to assess the age of youth and young adults from 14 to 20.5 years of age for male subjects and 14 to 19.5 years of age for female subjects in a fully automated manner, without the use of ionizing radiation, addressing the drawbacks of traditional methods. © 2019 Journal of Medical Internet Research. All rights reserved.
45.	Dallora Moraes, Ana Luiza, et al. (author) Bone age assessment with various machine learning techniques : A systematic literature review and meta-analysis 2019 In: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 14:7 Research review (peer-reviewed)abstract Background The assessment of bone age and skeletal maturity and its comparison to chronological age is an important task in the medical environment for the diagnosis of pediatric endocrinology, orthodontics and orthopedic disorders, and legal environment in what concerns if an individual is a minor or not when there is a lack of documents. Being a time-consuming activity that can be prone to inter- and intra-rater variability, the use of methods which can automate it, like Machine Learning techniques, is of value. Objective The goal of this paper is to present the state of the art evidence, trends and gaps in the research related to bone age assessment studies that make use of Machine Learning techniques. Method A systematic literature review was carried out, starting with the writing of the protocol, followed by searches on three databases: Pubmed, Scopus and Web of Science to identify the relevant evidence related to bone age assessment using Machine Learning techniques. One round of backward snowballing was performed to find additional studies. A quality assessment was performed on the selected studies to check for bias and low quality studies, which were removed. Data was extracted from the included studies to build summary tables. Lastly, a meta-analysis was performed on the performances of the selected studies. Results 26 studies constituted the final set of included studies. Most of them proposed automatic systems for bone age assessment and investigated methods for bone age assessment based on hand and wrist radiographs. The samples used in the studies were mostly comprehensive or bordered the age of 18, and the data origin was in most of cases from United States and West Europe. Few studies explored ethnic differences. Conclusions There is a clear focus of the research on bone age assessment methods based on radiographs whilst other types of medical imaging without radiation exposure (e.g. magnetic resonance imaging) are not much explored in the literature. Also, socioeconomic and other aspects that could influence in bone age were not addressed in the literature. Finally, studies that make use of more than one region of interest for bone age assessment are scarce. Copyright: © 2019 Dallora et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
46.	Ehn, Bodil, et al. (author) The process of opting for female permanent contraception : A qualitative study of women's experiences in Sweden 2021 In: Contraception. - : Elsevier. - 0010-7824 .- 1879-0518. ; 103:1, s. 48-52 Journal article (peer-reviewed)abstract Objectives: We aimed to explore Swedish women's decision-making experiences regarding permanent contraception. Study design: In this study, we included 17 women aged 30–48 who were scheduled to undergo female permanent contraceptive procedures. We conducted semistructured interviews using two broad open-ended questions. We analyzed these data using systematic text condensation based on the principles of psychological phenomenological analysis. Results: The interviewees experienced no counseling or support from health care workers regarding permanent contraception until they specifically asked for it. Participants reported that they themselves place the responsibility of permanent contraception solely on women. Consequently, our participants described feeling hesitancy and ambivalence in the process of deciding to have the procedure. Once the decision was made and the women were on the waiting lists for surgery, they experienced relief and empowerment. Conclusions: Our findings suggest that health care providers in Sweden miss opportunities to support patient-centered decision-making regarding permanent contraception. This study indicates that women make deliberate and considered decisions regarding permanent contraception and are best positioned to know when the procedure should take place in their reproductive lives. Implication statements: Health care professionals should discuss permanent contraception as an option with all women desiring contraception to allow them to decide if that method is right for them. © 2020 Elsevier Inc.
47.	Eivazzadeh, Shahryar, 1975-, et al. (author) Ethical Challenges of Evaluating Health Information Systems Other publication (other academic/artistic)abstract BackgroundEvaluating and researching health information systems are interventions of their kind and might lead to ethical complexities and challenges. Most of those challenges are inherited from the more general fields of research and evaluation, health studies, and information systems studies. Beyond those challenges, this field has its particular traits, regarding the involved stakeholders, required values or qualities, or the process which can raise field-specific or context-specific ethical challenges.ObjectivesThis paper reports and discusses some of the challenges of evaluating and researching health information systems by taking a systematic approach in finding, postulating, and analyzing them.MethodThrough a scoping review, a set of ethical challenges, regarding the evaluation and research of health information systems, were extracted. From the same set of articles, the acting entities, including stakeholders and artefacts, were identified. From a sample of seven cases of health information systems, a set of demanded impact qualities were extracted. From the literature, the evaluation stages were elicited. The acting entities, required qualities, and the evaluation stages were combined to create a three-dimensional space. The space contained the ethical challenges extracted from the scoping review and helped to postulate more items.ResultsThe final list of identified items contains 20 possible ethical challenges that can be caused or raised by evaluating or researching health information systems and technologies. The ethical challenges are discussed, based on their probable stage of occurrence. The three-dimensional space and the method of populating it is proposed as an effective method in similar cases of discovering ethical challenges.ConclusionEvaluating or researching health information systems can raise ethical challenges, that we have identified 20 of them in this article. All the challenges were discussed, such as the actual value of evaluation, breach of privacy, risks for safety, problems with usability and accessibility, conflict of interests, problems with the informed consent, and miscommunication. The novel approach for elicitation of the ethical challenges introduced in this article might be applied in other similar studies.
48.	Ferguson, Murdo, et al. (author) Lot-to-lot immunogenicity consistency of the respiratory syncytial virus prefusion F protein vaccine in older adults 2024 In: Vaccine: X. - : Elsevier. - 2590-1362. ; 18 Journal article (peer-reviewed)abstract Background: Previous phase 3 studies showed that the AS01E-adjuvanted respiratory syncytial virus (RSV) prefusion F protein-based vaccine for older adults (RSVPreF3 OA) is well tolerated and efficacious in preventing RSV-associated lower respiratory tract disease in adults ≥ 60 years of age. This study evaluated lot-to-lot immunogenicity consistency, reactogenicity, and safety of three RSVPreF3 OA lots. Methods: This phase 3, multicenter, double-blind study randomized (1:1:1) participants ≥ 60 years of age to receive one of three RSVPreF3 OA lots. Serum RSVPreF3-binding immunoglobulin G (IgG) concentration was assessed at baseline and 30 days post-vaccination. Lot-to-lot consistency was demonstrated if the two-sided 95 % confidence intervals (CIs) of the RSVPreF3-binding IgG geometric mean concentration (GMC) ratios between each lot pair at 30 days post-vaccination were within 0.67 and 1.50. Solicited adverse events (AEs) within four days, unsolicited AEs within 30 days, and serious AEs (SAEs) and potential immune-mediated diseases within six months post-vaccination were recorded. Results: A total of 757 participants received RSVPreF3 OA, of whom 708 were included in the per-protocol set (234, 237, and 237 participants for each lot). Lot-to-lot consistency was demonstrated: GMC ratios were 1.06 (95 % CI: 0.94–1.21), 0.92 (0.81–1.04), and 0.87 (0.77–0.99) between the lot pairs (lot 1/2; 1/3; 2/3). For the three lots, the RSVPreF3-binding IgG concentration increased 11.84-, 11.29-, and 12.46-fold post-vaccination compared to baseline. The reporting rates of solicited and unsolicited AEs, SAEs, and potential immune-mediated diseases were balanced between lots. Twenty-one participants reported SAEs; one of these–a case of atrial fibrillation–was considered by the investigator as vaccine-related. SAEs with a fatal outcome were reported for four participants, none of which were considered by the investigator as vaccine-related. Conclusion: This study demonstrated lot-to-lot immunogenicity consistency of three RSVPreF3 OA vaccine lots and indicated that the vaccine had an acceptable safety profile. ClinicalTrials.gov: NCT05059301. © 2024 GSK
49.	Frögren, Joakim, et al. (author) Designing a model app for older persons with cognitive impairment : insights from a usability perspective 2018 In: Gerontechnology. - : International Society for Gerontechnology. - 1569-1101 .- 1569-111X. ; 17, s. 80- Journal article (peer-reviewed)abstract Purpose Research indicates that health-oriented applications on mobile units such as smartphones and PDAs, so called mHealth applications, can be useful to support older persons with cognitive impairment and their informal caregivers1. However, several studies suggest that a prerequisite for older persons to start using computer-based technology is that it offers individual customization according to personal preference 2,3,4. In the ongoing Horizon 2020 project SMART4MD (Support, Monitoring And Reminder Technology for older persons with Mild Dementia), an health-oriented model app has been developed through a user-centered process involving stakeholders in six European countries and with an emphasis on customization to allow for the various needs of older persons with cognitive impairment and their informal caregivers. The aim of this study is to gain insights about the specific needs of the target group and success factors related to the user-centered design process. Method Within the frames of the SMART4MD project, an initial Feasibility study was conducted in two countries (Spain and Sweden) simultaneously, in which in total nineteen persons with cognitive impairment aged 66-93, and their respective informal caregivers, performed a taskbased usability test of the SMART4MD model app individually in a clinical setting, followed by a four-week testing of the app in their home environment. Finally, a usability evaluation was done through individual structured interviews. Results & Discussion The result indicates that less exposure to similar technology affects both ability and self-esteem when confronted with the model app, and that evaluating usability with the target group using standard forms within usability testing requires pre-cautions. © 2018 International Society for Gerontechnology.
50.	Ghazi, Sarah Nauman, 1989-, et al. (author) Psychological Health and Digital Social Participation of the Older Adults during the COVID-19 Pandemic in Blekinge, Sweden—An Exploratory Study 2022 In: International Journal of Environmental Research and Public Health. - : MDPI. - 1661-7827 .- 1660-4601. ; 19:6 Journal article (peer-reviewed)abstract COVID-19 has affected the psychological health of older adults directly and indirectly through recommendations of social distancing and isolation. Using the internet or digital tools to participate in society, one might mitigate the effects of COVID-19 on psychological health. This study explores the social participation of older adults through internet use as a social platform during COVID-19 and its relationship with various psychological health aspects. In this study, we used the survey as a research method, and we collected data through telephonic interviews; and online and paper-based questionnaires. The results showed an association of digital social participation with age and feeling lack of company. Furthermore, in addition, to the increase in internet use in older adults in Sweden during COVID-19, we conclude that digital social participation is essential to maintain psychological health in older adults.

Skapa referenser, mejla, bekava och länka

Permalink

Result 1-50 of 94

Refine your search

Type of publication: journal article (74); other publication (6); doctoral thesis (5); research review (3); licentiate thesis (3); conference paper (2); show more...; book chapter (1); show less...

Type of content: peer-reviewed (77); other academic/artistic (17)

Author/Editor: Sanmartin Berglund, ... (93); Anderberg, Peter (47); Moraes, Ana Luiza Da ... (16); Skär, Lisa, 1964- (11); Anderberg, Peter, Pr ... (10); Renvert, Stefan (9); show more...; Elmståhl, Sölve (8); Larsson, Tobias, Pro ... (8); Renvert, Stefan, 195 ... (6); Berner, Jessica (6); Flyborg, Johan (5); Eivazzadeh, Shahryar ... (5); Flodmark, Carl-Erik (5); Diaz, Sandra (4); Aeddula, Omsri, 1993 ... (4); Nilsson, Ola, 1970- (4); Bohman, Doris (4); Garolera, Maite (4); Andersson, Martin (3); Wimo, Anders (3); Wall, Johan (3); Jarl, Johan (3); Ali, Liaqat (3); Rombo, Lars (3); Fiedler, Markus (3); Quintana, Maria (3); Mayoral-Cleries, Fer ... (3); Lemmens, Evi (3); Olander, Ewy (3); Söderlin, Maria K (3); Andersson, Pia (3); Ghazi, Ahmad Nauman, ... (3); Bengtsson, Viveca Wa ... (3); Persson, Gösta Rutge ... (3); Fagerström, Cecilia, ... (2); Lilje, Stina (2); Abrahamsson, Linda (2); Saha, Sanjib (2); Alfredsson, Joakim (2); Welmer, Anna-Karin (2); Berg, Sören (2); Svedjeholm, Rolf (2); Barnestein-Fonseca, ... (2); Guzman-Parra, Jose (2); Nilsson, Helena (2); Mendes, Emilia (2); Lindberg, Catharina (2); Behrens, Anders (2); Vesikari, Timo (2); Pauksens, Karlis (2); show less...

University: Blekinge Institute of Technology (93); University of Skövde (44); Lund University (19); Karolinska Institutet (19); Kristianstad University College (15); Malmö University (8); show more...; Linnaeus University (7); Uppsala University (6); Stockholm University (6); Örebro University (5); Linköping University (3); University of Gothenburg (1); Sophiahemmet University College (1); show less...

Language: English (94)

Research subject (UKÄ/SCB): Medical and Health Sciences (85); Natural sciences (14); Engineering and Technology (8); Social Sciences (4); Agricultural Sciences (1)

Year

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

LIBRIS.kb.se

Copy and save the link in order to return to this view