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  • 1.
    Aeddula, Omsri
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    Flyborg, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Larsson, Tobias
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Renvert, Stefan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health. Kristianstad University, SWE.
    A Solution with Bluetooth Low Energy Technology to Support Oral Healthcare Decisions for improving Oral Hygiene2021In: ACM International Conference Proceeding Series, Association for Computing Machinery (ACM), 2021, Vol. 1, p. 134-139Conference paper (Refereed)
    Abstract [en]

    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 

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    ICMHI-OKA
  • 2.
    Anderberg, Peter
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Abrahamsson, Linda
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    An instrument for measuring social participation to examine older adults' use of the internet as a social platform: Development and validation study2021In: JMIR Aging, E-ISSN 2561-7605, Vol. 4, no 2, article id e23591Article in journal (Refereed)
    Abstract [en]

    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.

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  • 3.
    Anderberg, Peter
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Barnestein-Fonseca, Pilar
    Hosp Reg Univ Malaga, ESP.
    Guzman-Parra, Jose
    Hosp Reg Univ Malaga, ESP.
    Garolera, Maite
    Consorci Sanitari Terrassa, ESP.
    Quintana, Maria
    Consorci Sanitari Terrassa, ESP.
    Mayoral-Cleries, Fermin
    Hosp Reg Univ Malaga, ESP.
    Lemmens, Evi
    Univ Coll Leuven Limburg, BEL.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    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 Trial2019In: JMIR Research Protocols, E-ISSN 1929-0748, Vol. 8, no 6, article id e13711Article in journal (Refereed)
    Abstract [en]

    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.

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  • 4.
    Anderberg, Peter
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Björling, Gunilla
    Swedish Red Cross University College, SWE.
    Stjernberg, Louise
    Swedish Red Cross University College, SWE.
    Bohman, Doris
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Analyzing nursing students’ relation to electronic health and technology as individuals and students and in their future career (the ENURSED study): Protocol for a longitudinal study2019In: Journal of Medical Internet Research, E-ISSN 1438-8871, Vol. 21, no 10, article id e14643Article in journal (Refereed)
    Abstract [en]

    Background: The nursing profession has undergone several changes in the past decades, and new challenges are to come in the future; patients are now cared for in their home, hospitals are more specialized, and primary care will have a key role. Health informatics is essential in all core competencies in nursing. From an educational perspective, it is of great importance that students are prepared for the new demands and needs of the patients. From a societal point of view, the society, health care included, is facing several challenges related to technological developments and digitization. Preparation for the next decade of nursing education and practice must be done, without the advantage of certainty. A training for not-yet-existing technologies where educators should not be limited by present practice paradigms is desirable. This study presents the design, method, and protocol for a study that investigates undergraduate nursing students’ internet use, knowledge about electronic health (eHealth), and attitudes to technology and how experiences of eHealth are handled during the education in a multicenter study. Objective: The primary aim of this research project is to describe the design of a longitudinal study and a qualitative substudy consisting of the following aspects that explore students’ knowledge about and relation to technology and eHealth: (1) what pre-existing knowledge and interest of this area the nursing students have and (2) how (and if) is it present in their education, (3) how do the students perceive this knowledge in their future career role, and (4) to what extent is the education capable of managing this knowledge? Methods: The study consists of two parts: a longitudinal study and a qualitative substudy. Students from the BSc in Nursing program from the Blekinge Institute of Technology, Karlskrona, Sweden, and from the Swedish Red Cross University College, Stockholm/Huddinge, Sweden, were included in this study. Results: The study is ongoing. Data analysis is currently underway, and the first results are expected to be published in 2019. Conclusions: This study presents the design of a longitudinal study and a qualitative substudy. The eHealth in Nursing Education eNursEd study will answer several important questions about nursing students’ attitudes toward and use of information and communications technology in their private life, their education, and their emerging profession. Knowledge from this study will be used to compare different nursing programs and students’ knowledge about and relation to technology and eHealth. Results will also be communicated back to nursing educators to improve the teaching of eHealth, health informatics, and technology. ©Peter Anderberg, Gunilla Björling, Louise Stjernberg, Doris Bohman.

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  • 5.
    Anderberg, Peter
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Eivazzadeh, Shahryar
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    A Novel Instrument for Measuring Older People's Attitudes Toward Technology (TechPH): Development and Validation2019In: Journal of Medical Internet Research, E-ISSN 1438-8871, Vol. 21, no 5, article id e13951Article in journal (Refereed)
    Abstract [en]

    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.

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  • 6.
    Anderberg, Peter
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Skär, Lisa
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Abrahamsson, Linda
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Older People's Use and Nonuse of the Internet in Sweden2020In: International Journal of Environmental Research and Public Health, ISSN 1661-7827, E-ISSN 1660-4601, Vol. 17, no 23, article id 9050Article in journal (Refereed)
    Abstract [en]

    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.

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    Older People's Use and Nonuse of the Internet in Sweden
  • 7.
    Andersson, Ewa K.
    et al.
    Linnaeus University.
    Moraes, Ana Luiza Dallora
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Marcinowicz, Ludmila
    Medical University of Bialystok, Poland.
    Stjernberg, Louise
    Malmö University.
    Björling, Gunilla
    Jönköping University.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Bohman, Doris
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Self-Reported eHealth literacy among nursing students in Sweden and Poland: The eNursEd cross-sectional multicentre study2023In: Health Informatics Journal, ISSN 1460-4582, E-ISSN 1741-2811, Vol. 29, no 4Article in journal (Refereed)
    Abstract [en]

    This study aimed to provide an understanding of nursing students’ self-reported eHealth literacy in Sweden and Poland. This cross-sectional multicentre study collected data via a questionnaire in three universities in Sweden and Poland. Descriptive statistics, the Spearman’s Rank Correlation Coefficient, Mann–Whitney U, and Kruskal–Wallis tests were used to analyse different data types. Age (in the Polish sample), semester, perceived computer or laptop skills, and frequency of health-related Internet searches were associated with eHealth literacy. No gender differences were evidenced in regard to the eHealth literacy. Regarding attitudes about eHealth, students generally agreed on the importance of eHealth and technical aspects of their education. The importance of integrating eHealth literacy skills in the curricula and the need to encourage the improvement of these skills for both students and personnel are highlighted, as is the importance of identifying students with lacking computer skills. © The Author(s) 2023.

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  • 8.
    Behrens, Anders
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sleep disturbance predicts worse cognitive performance in subsequent years: A longitudinal population-based cohort study2023In: Archives of gerontology and geriatrics (Print), ISSN 0167-4943, E-ISSN 1872-6976, Vol. 106, article id 104899Article in journal (Refereed)
    Abstract [en]

    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. © 2022

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  • 9.
    Behrens, Anders
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    CoGNIT Automated Tablet Computer Cognitive Testing in Patients With Mild Cognitive Impairment: Feasibility Study2022In: JMIR Formative Research, E-ISSN 2561-326X, Vol. 6, no 3, article id e23589Article in journal (Refereed)
    Abstract [en]

    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.

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  • 10.
    Berner, Jesica
    et al.
    Blekinge Institute of Technology, Faculty of Health Sciences, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Health Sciences, Department of Health.
    Rennemark, Mikael
    Blekinge Institute of Technology, Faculty of Health Sciences, Department of Health.
    Berglund, Johan
    Blekinge Institute of Technology, Faculty of Health Sciences, Department of Health.
    Case Management for Frail Older Adults Through Tablet Computers and Skype2016In: Informatics for Health and Social Care, ISSN 1753-8157, E-ISSN 1753-8165, Vol. 41, no 4, p. 405-416Article in journal (Refereed)
    Abstract [en]

    Background: Frail older adults are high consumers of medical care due to their age and multiple chronic conditions. Regular contact with a case manager has been proven to increase well-being of frail older adults and reduce their number of health-care visits. Skype calls through tablet PCs can offer easier communication. Objective: This paper examines frail older adults’ use of tablet computers and Skype, with their case managers.Method: Interviews were conducted on 15 frail older adults. A content analysis was used to structure and analyze the data. Results: The results indicate that tablet computers were experienced in a positive way for most frail older adults. Conflicting feelings did emerge, however, as to whether the frail elderly would adopt this in the long run. Skype needs to be tested further as to whether this is a good solution for communication with their case managers. Strong technical support and well-functioning technology are important elements to facilitate use. Conclusion: Using Skype and tablet PCs do have potential for frail older adults, but need to be tested further. © 2015 Taylor & Francis

  • 11.
    Berner, Jessica
    et al.
    Vrije Universiteit Amsterdam, NLD.
    Aartsen, Marja
    Vrije Universiteit Amsterdam, NLD.
    Wahlberg, Maria
    Aging Research Centre, SWE.
    Elmståhl, Sölve
    Lund University, SWE.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Deeg, Dorly
    Vrije Universiteit Amsterdam, NLD.
    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 above2016In: Gerontechnology, ISSN 1569-1101, E-ISSN 1569-111X, Vol. 14, no 3, p. 157-168Article in journal (Refereed)
    Abstract [en]

    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.

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  • 12.
    Berner, Jessica
    et al.
    Amsterdam UMC, NLD.
    Comijs, Hannie
    Amsterdam UMC, NLD.
    Elmståhl, Sölve
    Lunds Universitet, SWE.
    Welmer, Anna Karin
    Stockholms universitet, SWE.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Deeg, Dorly
    Amsterdam UMC, NLD.
    Maintaining cognitive function with internet use: A two-country, six-year longitudinal study2019In: International psychogeriatrics, ISSN 1041-6102, E-ISSN 1741-203X, Vol. 31, no 7, p. 929-936Article in journal (Refereed)
    Abstract [en]

    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. © 2019 International Psychogeriatric Association.

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  • 13.
    Berner, Jessica
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Moraes, Ana Luiza Dallora
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Palm, Bruna
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Five-factor model, technology enthusiasm and technology anxiety2023In: Digital Health, E-ISSN 2055-2076, Vol. 9Article in journal (Refereed)
    Abstract [en]

    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. © The Author(s) 2023.

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  • 14.
    Berner, Jessica
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Moraes, Ana Luiza Dallora
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Technology anxiety and technology enthusiasm versus digital ageism2022In: Gerontechnology, ISSN 1569-1101, E-ISSN 1569-111X, Vol. 21, no 1Article in journal (Refereed)
    Abstract [en]

    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.

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  • 15.
    Berner, Jessica
    et al.
    Blekinge Institute of Technology, Faculty of Health Sciences, Department of Health.
    Rennemark, Mikael
    Blekinge Institute of Technology, Faculty of Health Sciences, Department of Health.
    Jogreus, Claes
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mathematics and Natural Sciences.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Health Sciences, Department of Health.
    Sköldunger, Anders
    Wahlberg, Maria
    Elmståhl, Sölve
    Berglund, Johan
    Blekinge Institute of Technology, Faculty of Health Sciences, Department of Health.
    Factors influencing Internet usage in older adults (65 years and above) living in rural and urban Sweden2015In: Health Informatics Journal, ISSN 1460-4582, E-ISSN 1741-2811, Vol. 21, no 3, p. 237-249Article in journal (Refereed)
    Abstract [en]

    Older adults living in rural and urban areas have shown to distinguish themselves in technology adoption; a clearer profile of their Internet use is important in order to provide better technological and health-care solutions. Older adults' Internet use was investigated across large to midsize cities and rural Sweden. The sample consisted of 7181 older adults ranging from 59 to 100 years old. Internet use was investigated with age, education, gender, household economy, cognition, living alone/or with someone and rural/urban living. Logistic regression was used. Those living in rural areas used the Internet less than their urban counterparts. Being younger and higher educated influenced Internet use; for older urban adults, these factors as well as living with someone and having good cognitive functioning were influential. Solutions are needed to avoid the exclusion of some older adults by a society that is today being shaped by the Internet.

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  • 16.
    Brennan, Ciara
    et al.
    University of Iceland, ISL.
    Rice, James Gordon
    University of Iceland, ISL.
    Traustadóttir, Rannveig
    University of Iceland, ISL.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    How can states ensure access to personal assistance when service delivery is decentralized?: A multi-level analysis of Iceland, Norway and Sweden2017In: Scandinavian Journal of Disability Research, ISSN 1501-7419, E-ISSN 1745-3011, Vol. 19, no 4, p. 334-346Article in journal (Refereed)
    Abstract [en]

    Article 19 of the United Nations (UN) Convention on the Rights of Persons with Disabilities requires states to ensure that persons with disabilities have access to a range of support services, including personal assistance. The Convention is an agreement between state parties and the UN. However, in practice, disability services are often implemented at the local level. Drawing on the findings of qualitative research in Iceland, Norway and Sweden, this paper examines a paradox whereby states commit to ensure access to support services, but decentralize responsibility to autonomous and independent local governments. A multi-level governance framework is applied to analyse the findings of qualitative inquiry with policy-makers, local government officials and leaders of independent living organizations in all three Nordic countries. A multi-level analysis highlights the tensions and contradictions between decentralization and human rights commitments. © 2016 Nordic Network on Disability Research

  • 17. Brennan, Ciara
    et al.
    Traustadóttir, Rannveig
    Rice, James
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Negotiating independence, choice and autonomy: experiences of parents who coordinate personal assistance on behalf of their adult son or daughter2016In: Disability & Society, ISSN 0968-7599, E-ISSN 1360-0508, Vol. 31, no 5, p. 604-621Article in journal (Refereed)
    Abstract [en]

    Article 19 of the UN Convention on the Rights of Persons with Disabilities requires states to provide personal assistance services. This article is based on qualitative research in Iceland, Norway and Sweden, carried out between 2012 and 2013. The overall study focused broadly on the implementation of Article 19. This article, however, reports findings based on a particular group of participants within the larger study: non-disabled parents who coordinate personal assistance schemes for their adult son or daughter. The article examines the various ways in which the parents, the majority of whom were mothers, negotiate principles of independence, choice and autonomy for their adult son or daughter who requires intensive support, including assistance with communicating. The aim is to explore, in the context of the Convention and the principles of the independent living movement, how to acknowledge and conceptualise personal assistance schemes that require another person to manage on behalf of the user. © 2016 Informa UK Limited, trading as Taylor & Francis Group

  • 18.
    Christiansen, Line
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Lindberg, Catharina
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Skär, Lisa
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Using Mobile Health and the Impact on Health-Related Quality of Life: Perceptions of Older Adults with Cognitive Impairment2020In: International Journal of Environmental Research and Public Health, ISSN 1661-7827, E-ISSN 1660-4601, Vol. 17, no 8, article id 2650Article in journal (Refereed)
    Abstract [en]

    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.

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    Using Mobile Health and the Impact on Health-Related Quality of Life: Perceptions of Older Adults with Cognitive Impairment
  • 19.
    Christiansen, Line
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health. Blekinge Inst Technol, Karlskrona, Sweden..
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health. Blekinge Inst Technol, Karlskrona, Sweden..
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health. Blekinge Inst Technol, Karlskrona, Sweden.;Univ Skovde, Skovde, Sweden..
    Cellek, Selim
    Anglia Ruskin Univ, GBR.
    Zhang, Jufen
    Anglia Ruskin Univ, GBR.
    Lemmens, Evi
    Univ Coll Leuven Limburg, BEL.
    Garolera, Maite
    Consorci Sanitari Terrassa, Brain Cognit & Behav Clin ReBarcelona, ESP.
    Mayoral-Cleries, Fermin
    Reg Univ Hosp Malaga, ESP.
    Skär, Lisa
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health. Blekinge Inst Technol, Karlskrona, Sweden..
    Associations Between Mobile Health Technology use and Self-rated Quality of Life: A Cross-sectional Study on Older Adults with Cognitive Impairment2021In: Gerontology and geriatric medicine, E-ISSN 2333-7214, Vol. 7Article in journal (Refereed)
    Abstract [en]

    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.

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    Associations Between Mobile Health Technology use and Self-rated Quality of Life
  • 20.
    Christiansen, Line
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Lindberg, Catharina
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Skär, Lisa
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Health-related quality of life and related factors among a sample of older people with cognitive impairment2019In: Nursing Open, E-ISSN 2054-1058, Vol. 6, no 3, p. 849-859Article in journal (Refereed)
    Abstract [en]

    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.

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  • 21.
    Dallora Moraes, Ana Luiza
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Kvist, Ola
    KI, SWE.
    Mendes, Emilia
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Ruiz, Sandra
    KI, SWE.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Bone age assessment with various machine learning techniques: A systematic literature review and meta-analysis2019In: PLOS ONE, E-ISSN 1932-6203, Vol. 14, no 7, article id e0220242Article, review/survey (Refereed)
    Abstract [en]

    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.

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  • 22.
    Dallora Moraes, Ana Luiza
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Brogren, Martin
    Optriva AB, SWE.
    Kvist, Ola
    Karolinska, SWE.
    Ruiz, Sandra Diaz
    Karolinska, SWE.
    Dübbel, André
    Optriva AB, SWE.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Age assessment of youth and young adults using magnetic resonance imaging of the knee: A deep learning approach2019In: JMIR Medical Informatics, E-ISSN 2291-9694, Vol. 7, no 4, p. 419-436, article id e16291Article in journal (Refereed)
    Abstract [en]

    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.

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    Age assessment of youth and young adults using magnetic resonance imaging of the knee
  • 23.
    Ehn, Bodil Ekman
    et al.
    Hospital of Karlskrona, SWE.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Lilje, Stina Charlotta
    Karolinska Institutet, SWE.
    The process of opting for female permanent contraception: A qualitative study of women's experiences in Sweden2021In: Contraception, ISSN 0010-7824, E-ISSN 1879-0518, Vol. 103, no 1, p. 48-52Article in journal (Refereed)
    Abstract [en]

    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.

  • 24.
    Eivazzadeh, Shahryar
    et al.
    Blekinge Institute of Technology, Faculty of Health Sciences, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Health Sciences, Department of Health.
    Johan, Berglund
    Blekinge Institute of Technology, Faculty of Health Sciences, Department of Health.
    Tobias, Larsson
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    Designing with Priorities and Thresholds for Health Care Heterogeneity: The Approach of Constructing Parametric Ontology2015Conference paper (Refereed)
    Abstract [en]

    Designing systems working in health care needs complying with the heterogeneous, overlapping, non-overlapping, competing, or even contradicting requirements expressed by the various actors of the health care complex environment, including regulatory bodies. The unification method introduced in this paper, utilized ontological struc- tures to unify heterogeneous requirements in different levels of ab- straction. Also the weighting and threshold algorithms defined upon the ontology structure allows to both prioritize the requirements and align design resources upon that priority, at the same time to enforce regulatory requirements in an easy, clear and integrated way and reject designs which cannot comply with them. Application of the method introduced in this paper is not limited to health care, but it might be applied in design for any heterogeneous environment.

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  • 25.
    Eivazzadeh, Shahryar
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Larsson, Tobias
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    Fricker, Samuel
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering. University of Applied Sciences and Arts Northwestern Switzerland.
    Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Evaluating Health Information Systems Using Ontologies2016In: JMIR Medical Informatics, E-ISSN 2291-9694, Vol. 4, no 2, article id e20Article in journal (Refereed)
    Abstract [en]

    Background: There are several frameworks that attempt to address the challenges of evaluation of health information systems by offering models, methods, and guidelines about what to evaluate, how to evaluate, and how to report the evaluation results. Model-based evaluation frameworks usually suggest universally applicable evaluation aspects but do not consider case-specific aspects. On the other hand, evaluation frameworks that are case specific, by eliciting user requirements, limit their output to the evaluation aspects suggested by the users in the early phases of system development. In addition, these case-specific approaches extract different sets of evaluation aspects from each case, making it challenging to collectively compare, unify, or aggregate the evaluation of a set of heterogeneous health information systems.

    Objectives: The aim of this paper is to find a method capable of suggesting evaluation aspects for a set of one or more health information systems—whether similar or heterogeneous—by organizing, unifying, and aggregating the quality attributes extracted from those systems and from an external evaluation framework.

    Methods: On the basis of the available literature in semantic networks and ontologies, a method (called Unified eValuation using Ontology; UVON) was developed that can organize, unify, and aggregate the quality attributes of several health information systems into a tree-style ontology structure. The method was extended to integrate its generated ontology with the evaluation aspects suggested by model-based evaluation frameworks. An approach was developed to extract evaluation aspects from the ontology that also considers evaluation case practicalities such as the maximum number of evaluation aspects to be measured or their required degree of specificity. The method was applied and tested in Future Internet Social and Technological Alignment Research (FI-STAR), a project of 7 cloud-based eHealth applications that were developed and deployed across European Union countries.

    Results: The relevance of the evaluation aspects created by the UVON method for the FI-STAR project was validated by the corresponding stakeholders of each case. These evaluation aspects were extracted from a UVON-generated ontology structure that reflects both the internally declared required quality attributes in the 7 eHealth applications of the FI-STAR project and the evaluation aspects recommended by the Model for ASsessment of Telemedicine applications (MAST) evaluation framework. The extracted evaluation aspects were used to create questionnaires (for the corresponding patients and health professionals) to evaluate each individual case and the whole of the FI-STAR project.

    Conclusions: The UVON method can provide a relevant set of evaluation aspects for a heterogeneous set of health information systems by organizing, unifying, and aggregating the quality attributes through ontological structures. Those quality attributes can be either suggested by evaluation models or elicited from the stakeholders of those systems in the form of system requirements. The method continues to be systematic, context sensitive, and relevant across a heterogeneous set of health information systems.

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  • 26.
    Eivazzadeh, Shahryar
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Fiedler, Markus
    Blekinge Institute of Technology, Faculty of Computing, Department of Technology and Aesthetics.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Larsson, Tobias
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    Design of a Semi-Automated and Continuous Evaluation System: Customized for Application in e-HealthManuscript (preprint) (Other academic)
    Abstract [en]

    Background and Objectives

    Survey-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.

    Method

    The 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.

    Results

    A 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.

    Conclusion

    A 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.

  • 27.
    Eivazzadeh, Shahryar
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Larsson, Tobias
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    Fiedler, Markus
    Blekinge Institute of Technology, Faculty of Computing, Department of Technology and Aesthetics.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Most Influential Qualities in Creating Satisfaction Among the Users of Health Information Systems: A Study in Seven EU Countries2018In: JMIR Medical Informatics, Vol. 6, no 4, p. 3-21Article in journal (Refereed)
    Abstract [en]

    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.

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  • 28.
    Eivazzadeh, Shahryar
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Skär, Lisa
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Ethical Challenges of Evaluating Health Information SystemsManuscript (preprint) (Other academic)
    Abstract [en]

    Background

    Evaluating 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.

    Objectives

    This 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.

    Method

    Through 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.

    Results

    The 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.

    Conclusion

    Evaluating 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.

  • 29. Ekelin, Annelie
    et al.
    Anderberg, Peter
    Reddy, Kishore
    The Augment Project: Co-Constructive Mapping and Support of Accessibility and Participation2010In: Lecture Notes in Computer Science, Springer Verlag , 2010, Vol. 6229/2010, p. 95-103Conference paper (Refereed)
    Abstract [en]

    This paper presents an ongoing multi-disciplinary research-and development project in which we are exploring emerging methods and practices for participatory design of tools and content of accessibility information in India and Sweden, based on user created content. The initial development of the AUGMENT-Project also includes the production of a prototype for sharing information. The joint set up and unfolding of public digital spaces and co-operative creation of processes and infrastructure for user-driven accessibility information is making use of existing handheld mobile phones which offer the possibility to upload pictures and comments via an application with a map-based interface. The research initiative is exploring and comparing cross-cultural participatory methods for cultivation of shared transformational spaces. The paper discusses both the notion of user-driven content and co-creation of tools and methods, drawing upon the tradition of Scandinavian Systems Design, explicitly arguing for direct user-representation in systems development.

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  • 30.
    Ferati, Mexhid
    et al.
    Linnaeus University, SWE.
    Bertoni, Marco
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    Dalipi, Fisnik
    Linnaeus University, SWE.
    Kurti, Arianit
    Linnaeus University, SWE.
    Jokela, Päivi
    Linnaeus University, SWE.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Mirijamdotter, Anita
    Linnaeus University, SWE.
    Tackling the Sustainability of Digital Aging Innovations Through Design Thinking and Systems Thinking Perspectives2021In: Communications in Computer and Information Science CCIS / [ed] Pissaloux E., Papadopoulos G.A., Achilleos A., Velázquez R., Springer Science and Business Media Deutschland GmbH , 2021, Vol. 1538, p. 179-184Conference paper (Refereed)
    Abstract [en]

    The digitalization of society brings many opportunities and challenges, especially on how we organize the welfare society in the future. This becomes especially pertinent as we are heading toward a global increase of older people, which will strain healthcare and bring the challenge of building sustainable solutions. In this paper, we argue that the unsustainable solutions within healthcare are due to them being defined and ‘solved’ with a single approach or approaches used in silos. We advocate that a more sustainable solution could be achieved by combining systems thinking and design thinking perspectives throughout the entire process—from problem definition to solution offering. A benefit of such combined perspectives is the ability to develop a shared context among all stakeholders, which helps uncover unique tacit knowledge from their experience. This will serve as a solid foundation to generate unconventional ideas that will lead to sustainable and satisfactory solutions. © 2021, Springer Nature Switzerland AG.

  • 31.
    Flyborg, Johan
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Renvert, Stefan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Isaksson, Ulrika
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Measurement of body temperature in the oral cavity with a temperature sensor integrated with a powered toothbrush2023In: SN Applied Sciences, ISSN 2523-3963, E-ISSN 2523-3971, Vol. 5, no 1, article id 22Article in journal (Refereed)
    Abstract [en]

    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).

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  • 32.
    Flyborg, Johan
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Renvert, Stefan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Larsson, Tobias
    Blekinge Institute of Technology, Faculty of Engineering, Department of Mechanical Engineering.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Results of objective brushing data recorded from a powered toothbrush used by elderly individuals with mild cognitive impairment related to values for oral health2024In: Clinical Oral Investigations, ISSN 1432-6981, E-ISSN 1436-3771, Vol. 28, no 1, article id 8Article in journal (Refereed)
    Abstract [en]

    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. © 2023, The Author(s).

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  • 33.
    Flyborg, Johan
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Renvert, Stefan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Use of a powered toothbrush to improve oral health in individuals with mild cognitive impairment2023In: Gerodontology, ISSN 0734-0664, E-ISSN 1741-2358, Vol. 40, no 1, p. 74-82Article in journal (Refereed)
    Abstract [en]

    Objectives

    The 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.

    Background

    People 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 methods

    Two 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.

    Results

    One 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.

    Conclusion

    The 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.

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  • 34.
    Frögren, Joakim
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Quitana, M.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Designing a model app for older persons with cognitive impairment: insights from a usability perspective2018In: Gerontechnology, ISSN 1569-1101, E-ISSN 1569-111X, Vol. 17, p. 80-Article in journal (Refereed)
    Abstract [en]

    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.

  • 35.
    Ghani, Zartashia
    et al.
    Blekinge Institute of Technology, Faculty of Health Sciences, Department of Health. Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Jarl, Johan
    Lunds universitet, SWE.
    Saha, Sanjib
    Lunds universitet, SWE.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Andersson, Martin
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Economic evaluation of a software application (Support, Monitoring and Reminder Technology for Mild Dementia [SMART4MD]) designed for older adults with mild cognitive impairment (MCI)Manuscript (preprint) (Other academic)
  • 36.
    Ghani, Zartashia
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Jarl, Johan
    Lund University, SWE.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Andersson, Martin
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    The cost-effectiveness of mobile health (Mhealth) interventions for older adults: Systematic review2020In: International Journal of Environmental Research and Public Health, ISSN 1661-7827, E-ISSN 1660-4601, Vol. 17, no 15, p. 1-13, article id 5290Article, review/survey (Refereed)
    Abstract [en]

    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. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

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    The cost-effectiveness of mobile health (Mhealth) interventions for older adults
  • 37.
    Ghani, Zartashia
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Saha, Sanjib
    Lund University, SWE.
    Jarl, Johan
    Lund University, SWE.
    Andersson, Martin
    Blekinge Institute of Technology, Faculty of Engineering, Department of Industrial Economics.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    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 Caregivers2022In: Journal of Alzheimer's Disease, ISSN 1387-2877, E-ISSN 1875-8908, Vol. 86, no 4, p. 1629-1641Article in journal (Refereed)
    Abstract [en]

    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.

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  • 38.
    Ghazi, Sarah Nauman
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Berner, Jesica
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Moraes, Ana Luiza Dallora
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Psychological Health and Digital Social Participation of the Older Adults during the COVID-19 Pandemic in Blekinge, Sweden—An Exploratory Study2022In: International Journal of Environmental Research and Public Health, E-ISSN 1660-4601, Vol. 19, no 6, article id 3711Article in journal (Refereed)
    Abstract [en]

    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.

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  • 39.
    Ghazi, Sarah Nauman
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Berner, Jessica
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    The prevalence of eHealth literacy and its relationship with perceived health status and psychological distress during Covid-19: a cross-sectional study of older adults in Blekinge, Sweden2023In: BMC Geriatrics, ISSN 1471-2318, E-ISSN 1471-2318, Vol. 23, no 1, article id 5Article in journal (Refereed)
    Abstract [en]

    Background and aims: eHealth literacy is important as it influences health-promoting behaviors and health. The ability to use eHealth resources is essential to maintaining health, especially during COVID-19 when both physical and psychological health were affected. This study aimed to assess the prevalence of eHealth literacy and its association with psychological distress and perceived health status among older adults in Blekinge, Sweden. Furthermore, this study aimed to assess if perceived health status influences the association between eHealth literacy and psychological distress.

    Methods: This cross-sectional study (October 2021-December 2021) included 678 older adults’ as participants of the Swedish National Study on Aging and Care, Blekinge (SNAC-B). These participants were sent questionnaires about their use of Information and Communications Technology (ICT) during the COVID-19 pandemic. In this study, we conducted the statistical analysis using the Kruskal-Wallis one-way analysis of variance, Kendall’s tau-b rank correlation, and multiple linear regression.

    Results: We found that 68.4% of the participants had moderate to high levels of eHealth literacy in the population. Being female, age <75<75 years, and having a higher education are associated with high eHealth literacy (𝑝<0.05p<0.05). eHealth literacy is significantly correlated (𝜏τ=0.12, p-value=0.002) and associated with perceived health status (𝛽β=0.39, p-value=0.008). It is also significantly correlated (𝜏τ=-0.12, p-value=0.001) and associated with psychological distress (𝛽β=-0.14, p-value=0.002). The interaction of eHealth literacy and good perceived health status reduced psychological distress (𝛽β=-0.30, p-value=0.002).

    Conclusions: In our cross-sectional study, we found that the point prevalence of eHealth literacy among older adults living in Blekinge, Sweden is moderate to high, which is a positive finding. However, there are still differences among older adults based on factors such as being female, younger than 75 years, highly educated, in good health, and without psychological distress. The results indicated that psychological distress could be mitigated during the pandemic by increasing eHealth literacy and maintaining good health status. 

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  • 40.
    Guzman-Parra, Jose
    et al.
    University Regional Hospital of Malaga, ESP.
    Barnestein-Fonseca, Pilar
    University Regional Hospital of Malaga, ESP.
    Guerrero-Pertiñez, Gloria
    University Regional Hospital of Malaga, ESP.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Jimenez-Fernandez, Luis
    University Regional Hospital of Malaga, ESP.
    Valero-Moreno, Esperanza
    University Regional Hospital of Malaga, ESP.
    Goodman-Casanova, Jessica Marian
    University Regional Hospital of Malaga, ESP.
    Cuesta-Vargas, Antonio Ignacio
    Universidad de Málaga, ESP.
    Garolera Freixa, Maite
    Consorci Sanitari de Terrassa, ESP.
    Quintana, María
    Consorci Sanitari de Terrassa, ESP.
    García-Betances, Rebeca Isabel
    Universidad Politécnica, ESP.
    Lemmens, Evi
    University Colleges Leuven-Limburg, BEL.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Mayoral-Cleries, Fermín
    University Regional Hospital of Malaga, ESP.
    Attitudes and use of information and communication technologies in older adults with mild cognitive impairment or early stages of dementia and their caregivers: cross-sectional study2020In: Journal of Medical Internet Research, E-ISSN 1438-8871, Vol. 22, no 6, article id e17253Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Information and communication technologies are promising tools to increase the quality of life of people with dementia or mild cognitive impairment and that of their caregivers. However, there are barriers to their use associated with sociodemographic factors and negative attitudes, as well as inadequate knowledge about technologies. OBJECTIVE: The aim of this study was to analyze technophilia (attitudes toward new technologies) and the use of smartphones and tablets along with associated factors in people with dementia/mild cognitive impairment and their caregivers. METHODS: Data from the first visit of the Support Monitoring and Reminder for Mild Dementia (SMART4MD) randomized multicenter clinical trial were used for this analysis. Data were obtained from two European countries, Spain and Sweden, and from three centers: Consorci Sanitari de Terrassa (Catalonia, Spain), Servicio Andaluz de Salud (Andalusia, Spain), and the Blekinge Institute of Technology (Sweden). Participants with a score between 20 and 28 in the Mini Mental State Examination, with memory problems (for more than 6 months), and who were over the age of 55 years were included in the study, along with their caregivers. The bivariate Chi square and Mann-Whitney tests, and multivariate linear and logistic regression models were used for statistical analysis. RESULTS: A total of 1086 dyads were included (N=2172). Overall, 299 (27.53%) of people with dementia/mild cognitive impairment had a diagnosis of dementia. In addition, 588 (54.14%) of people with dementia/mild cognitive impairment reported using a smartphone almost every day, and 106 (9.76%) used specific apps or software to support their memory. Among the caregivers, 839 (77.26%) used smartphones and tablets almost every day, and 181 (16.67%) used specific apps or software to support their memory. The people with dementia/mild cognitive impairment showed a lower level of technophilia in comparison to that of their caregivers after adjusting for confounders (B=0.074, P=.02) with differences in technology enthusiasm (B=0.360, P<.001), but not in technology anxiety (B=-0.042, P=.37). Technophilia was associated with lower age (B=-0.009, P=.004), male gender (B=-0.160, P<.001), higher education level (P=.01), living arrangement (living with children vs single; B=-2.538, P=.01), country of residence (Sweden vs Spain; B=0.256, P<.001), lower depression (B=-0.046, P<.001), and better health status (B=0.004, P<.001) in people with dementia/mild cognitive impairment. Among caregivers, technophilia was associated with comparable sociodemographic factors (except for living arrangement), along with a lower caregiver burden (B=-0.005, P=.04) and better quality of life (B=0.348, P<.001). CONCLUSIONS: Technophilia was associated with a better quality of life and sociodemographic variables in people with dementia/mild cognitive impairment and caregivers, suggesting potential barriers for technological interventions. People with dementia/mild cognitive impairment frequently use smartphones and tablets, but the use of specific apps or software to support memory is limited. Interventions using these technologies are needed to overcome barriers in this population related to sociodemographic characteristics and the lack of enthusiasm for new technologies. TRIAL REGISTRATION: ClinicalTrials.gov NCT03325699; https://clinicaltrials.gov/ct2/show/NCT03325699. ©Jose Guzman-Parra, Pilar Barnestein-Fonseca, Gloria Guerrero-Pertiñez, Peter Anderberg, Luis Jimenez-Fernandez, Esperanza Valero-Moreno, Jessica Marian Goodman-Casanova, Antonio Cuesta-Vargas, Maite Garolera, Maria Quintana, Rebeca I García-Betances, Evi Lemmens, Johan Sanmartin Berglund, Fermin Mayoral-Cleries. Originally published in the Journal of Medical Internet Research (http://www.jmir.o

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    Attitudes and Use of Information and Communication Technologies in Older Adults With Mild Cognitive Impairment or Early Stages of Dementia and Their Caregivers
  • 41.
    Idrisoglu, Alper
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Moraes, Ana Luiza Dallora
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders: Systematic Literature Review2023In: Journal of Medical Internet Research, E-ISSN 1438-8871, Vol. 25, article id e46105Article, review/survey (Refereed)
    Abstract [en]

    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. © 2023 Journal of Medical Internet Research. All rights reserved.

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  • 42.
    Idrisoglu, Alper
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Moraes, Ana Luiza Dallora
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Cheddad, Abbas
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Jakobsson, Andreas
    Lunds universitet.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    COPDVD: Automated Classification of Chronic Obstructive Pulmonary Disease on a New Developed and Evaluated Voice DatasetManuscript (preprint) (Other academic)
    Abstract [en]

    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.

  • 43.
    Javeed, Ashir
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Ghazi, Ahmad Nauman
    Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.
    Noor, Adeeb
    King Abdulaziz University, Saudi Arabia.
    Elmståhl, Sölve
    Lund University.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Breaking barriers: a statistical and machine learning-based hybrid system for predicting dementia2024In: Frontiers in Bioengineering and Biotechnology, E-ISSN 2296-4185, Vol. 11, article id 1336255Article in journal (Refereed)
    Abstract [en]

    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.

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  • 44.
    Javeed, Ashir
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Moraes, Ana Luiza Dallora
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Ali, Arif
    University of Science and Technology Bannu, Pakistan.
    Ali, Liaqata
    University of Science and Technology Bannu, Pakistan.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Machine Learning for Dementia Prediction: A Systematic Review and Future Research Directions2023In: Journal of medical systems, ISSN 0148-5598, E-ISSN 1573-689X, Vol. 47, no 1, article id 17Article, review/survey (Refereed)
    Abstract [en]

    Nowadays, Artificial Intelligence (AI) and machine learning (ML) have successfully provided automated solutions to numerous real-world problems. Healthcare is one of the most important research areas for ML researchers, with the aim of developing automated disease prediction systems. One of the disease detection problems that AI and ML researchers have focused on is dementia detection using ML methods. Numerous automated diagnostic systems based on ML techniques for early prediction of dementia have been proposed in the literature. Few systematic literature reviews (SLR) have been conducted for dementia prediction based on ML techniques in the past. However, these SLR focused on a single type of data modality for the detection of dementia. Hence, the purpose of this study is to conduct a comprehensive evaluation of ML-based automated diagnostic systems considering different types of data modalities such as images, clinical-features, and voice data. We collected the research articles from 2011 to 2022 using the keywords dementia, machine learning, feature selection, data modalities, and automated diagnostic systems. The selected articles were critically analyzed and discussed. It was observed that image data driven ML models yields promising results in terms of dementia prediction compared to other data modalities, i.e., clinical feature-based data and voice data. Furthermore, this SLR highlighted the limitations of the previously proposed automated methods for dementia and presented future directions to overcome these limitations. © 2023, The Author(s).

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  • 45.
    Javeed, Ashir
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Moraes, Ana Luiza Dallora
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Ali, Arif
    University of Science and Technology Bannu, Pakistan.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Ali, Liaqat
    University of Science and Technology Bannu, Pakistan.
    Predicting Dementia Risk Factors Based on Feature Selection and Neural Networks2023In: Computers, Materials and Continua, ISSN 1546-2218, E-ISSN 1546-2226, Vol. 75, no 2, p. 2491-2508Article in journal (Refereed)
    Abstract [en]

    Dementia is a disorder with high societal impact and severe consequences for its patients who suffer from a progressive cognitive decline that leads to increased morbidity, mortality, and disabilities. Since there is a consensus that dementia is a multifactorial disorder, which portrays changes in the brain of the affected individual as early as 15 years before its onset, prediction models that aim at its early detection and risk identification should consider these characteristics. This study aims at presenting a novel method for ten years prediction of dementia using on multifactorial data, which comprised 75 variables. There are two automated diagnostic systems developed that use genetic algorithms for feature selection, while artificial neural network and deep neural network are used for dementia classification. The proposed model based on genetic algorithm and deep neural network had achieved the best accuracy of 93.36%, sensitivity of 93.15%, specificity of 91.59%, MCC of 0.4788, and performed superior to other 11 machine learning techniques which were presented in the past for dementia prediction. The identified best predictors were: age, past smoking habit, history of infarct, depression, hip fracture, single leg standing test with right leg, score in the physical component summary and history of TIA/RIND. The identification of risk factors is imperative in the dementia research as an effort to prevent or delay its onset. © 2023 Tech Science Press. All rights reserved.

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  • 46.
    Javeed, Ashir
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Moraes, Ana Luiza Dallora
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    An Intelligent Learning System for Unbiased Prediction of Dementia Based on Autoencoder and Adaboost Ensemble Learning2022In: Life, E-ISSN 2075-1729, Vol. 12, no 7, article id 1097Article in journal (Refereed)
    Abstract [en]

    Dementia is a neurological condition that primarily affects older adults and there is still no cure or therapy available to cure it. The symptoms of dementia can appear as early as 10 years before the beginning of actual diagnosed dementia. Hence, machine learning (ML) researchers have presented several methods for early detection of dementia based on symptoms. However, these techniques suffer from two major flaws. The first issue is the bias of ML models caused by imbalanced classes in the dataset. Past research did not address this issue well and did not take preventative precautions. Different ML models were developed to illustrate this bias. To alleviate the problem of bias, we deployed a synthetic minority oversampling technique (SMOTE) to balance the training process of the proposed ML model. The second issue is the poor classification accuracy of ML models, which leads to a limited clinical significance. To improve dementia prediction accuracy, we proposed an intelligent learning system that is a hybrid of an autoencoder and adaptive boost model. The autoencoder is used to extract relevant features from the feature space and the Adaboost model is deployed for the classification of dementia by using an extracted subset of features. The hyperparameters of the Adaboost model are fine-tuned using a grid search algorithm. Experimental findings reveal that the suggested learning system outperforms eleven similar systems which were proposed in the literature. Furthermore, it was also observed that the proposed learning system improves the strength of the conventional Adaboost model by 9.8% and reduces its time complexity. Lastly, the proposed learning system achieved classification accuracy of 90.23%, sensitivity of 98.00% and specificity of 96.65%.

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  • 47.
    Javeed, Ashir
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Moraes, Ana Luiza Dallora
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Idrisoglu, Alper
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Ali, Liaqat
    University of Science and Technology Bannu, Pakistan.
    Rauf, Hafiz Tayyab
    Staffordshire University, UK.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Early Prediction of Dementia Using Feature Extraction Battery (FEB) and Optimized Support Vector Machine (SVM) for Classification2023In: Biomedicines, E-ISSN 2227-9059, Vol. 11, no 2, article id 439Article in journal (Refereed)
    Abstract [en]

    Dementia is a cognitive disorder that mainly targets older adults. At present, dementia has no cure or prevention available. Scientists found that dementia symptoms might emerge as early as ten years before the onset of real disease. As a result, machine learning (ML) scientists developed various techniques for the early prediction of dementia using dementia symptoms. However, these methods have fundamental limitations, such as low accuracy and bias in machine learning (ML) models. To resolve the issue of bias in the proposed ML model, we deployed the adaptive synthetic sampling (ADASYN) technique, and to improve accuracy, we have proposed novel feature extraction techniques, namely, feature extraction battery (FEB) and optimized support vector machine (SVM) using radical basis function (rbf) for the classification of the disease. The hyperparameters of SVM are calibrated by employing the grid search approach. It is evident from the experimental results that the newly pr oposed model (FEB-SVM) improves the dementia prediction accuracy of the conventional SVM by 6%. The proposed model (FEB-SVM) obtained 98.28% accuracy on training data and a testing accuracy of 93.92%. Along with accuracy, the proposed model obtained a precision of 91.80%, recall of 86.59, F1-score of 89.12%, and Matthew’s correlation coefficient (MCC) of 0.4987. Moreover, the newly proposed model (FEB-SVM) outperforms the 12 state-of-the-art ML models that the researchers have recently presented for dementia prediction.

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  • 48.
    Javeed, Ashir
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Saleem, Muhammad Asim
    Chulalongkorn University, Thailand.
    Moraes, Ana Luiza Dallora
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Ali, Liaqat
    University Science & Technology Bannu, Pakistan.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Decision Support System for Predicting Mortality in Cardiac Patients Based on Machine Learning2023In: Applied Sciences, E-ISSN 2076-3417, Vol. 13, no 8, article id 5188Article in journal (Refereed)
    Abstract [en]

    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 ?(2) 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 (?(2)_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 ?(2)_RF achieved the highest accuracy of 94.59%. The proposed model ?(2)_RF improved the performance of the standard RF model by 5.5%. Moreover, the proposed model ?(2)_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 (?(2)).

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  • 49.
    Javeed, Ashir
    et al.
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Moraes, Ana Luiza Dallora
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Saleem, Muhammad Asim
    Chulalongkorn University, Thailand.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Predictive Power of XGBoost_BiLSTM Model: A Machine-Learning Approach for Accurate Sleep Apnea Detection Using Electronic Health Data2023In: International Journal of Computational Intelligence Systems, ISSN 1875-6891, E-ISSN 1875-6883, Vol. 16, no 1, article id 188Article in journal (Refereed)
    Abstract [en]

    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. © 2023, The Author(s).

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  • 50.
    Kvist, Ola F. T.
    et al.
    Karolinska Univ Hosp, SWE.
    Moraes, Ana Luiza Dallora
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Nilsson, Ola
    Karolinska Inst, SWE.
    Anderberg, Peter
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Sanmartin Berglund, Johan
    Blekinge Institute of Technology, Faculty of Engineering, Department of Health.
    Flodmark, Carl-Erik
    Lund Univ, SWE.
    Diaz, Sandra
    Karolinska Univ Hosp, SWE.
    Comparison of reliability of magnetic resonance imaging using cartilage and T1-weighted sequences in the assessment of the closure of the growth plates at the knee2020In: Acta Radiologica Open, E-ISSN 2058-4601, Vol. 9, no 9, article id 2058460120962732Article in journal (Refereed)
    Abstract [en]

    Background: Growth development is traditionally evaluated with plain radiographs of the hand and wrist to visualize bone structures using ionizing radiation. Meanwhile, MRI visualizes bone and cartilaginous tissue without radiation exposure. Purpose: To determine the state of growth plate closure of the knee in healthy adolescents and young adults and compare the reliability of staging using cartilage sequences and T1-weighted (T1W) sequence between pediatric and general radiologists. Material and Methods: A prospective, cross-sectional study of MRI of the knee with both cartilage and T1W sequences was performed in 395 male and female healthy subjects aged between 14.0 and 21.5 years old. The growth plate of the femur and the tibia were graded using a modified staging scale by two pediatric and two general radiologists. Femur and tibia were graded separately with both sequences. Results: The intraclass correlation was overall excellent. The inter- and intra-observer agreement for pediatric radiologists on T1W was 82% (kappa = 0.73) and 77% (kappa = 0.65) for the femur and 90% (kappa = 0.82) and 87% (kappa = 0.75) for the tibia. The inter-observer agreement for general radiologists on T1W was 69% (kappa = 0.56) for the femur and 56% (kappa = 0.34) for the tibia. Cohen's kappa coefficient showed a higher inter- and intra-observer agreement for cartilage sequences than for T1W: 93% (kappa = 0.86) and 89% (kappa = 0.79) for the femur and 95% (kappa = 0.90) and 91% (kappa = 0.81) for the tibia. Conclusion: Cartilage sequences are more reliable than T1W sequence in the assessment of the growth plate in adolescents and young adults. Pediatric radiology experience is preferable.

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    Comparison of reliability of magneticresonance imaging using cartilageand T1-weighted sequences in theassessment of the closure of thegrowth plates at the knee
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