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- Andersson, Ewa K., 1972-, et al.
(author)
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Self-Reported eHealth literacy among nursing students in Sweden and Poland : The eNursEd cross-sectional multicentre study
- 2023
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In: Health Informatics Journal. - : Sage Publications. - 1460-4582 .- 1741-2811. ; 29:4
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Journal article (peer-reviewed)abstract
- 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.
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2. |
- Berner, Jessica, et al.
(author)
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Five-factor model, technology enthusiasm and technology anxiety
- 2023
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In: Digital Health. - : Sage Publications. - 2055-2076. ; 9
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Journal article (peer-reviewed)abstract
- Older adults need to participate in the digital society, as societal and personal changes and what they do with the remaining time that they have in their older years has an undeniable effect on motivation, cognition and emotion. Changes in personality traits were investigated in older adults over the period 2019–2021. Technology enthusiasm and technology anxiety are attitudes that affect the relationship to the technology used. The changes in the score of technology enthusiasm and technology anxiety were the dependent variables. They were investigated with personality traits, age, gender, education, whether someone lives alone, cognitive function, digital social participation (DSP) and health literacy as predictors of the outcome. The Edwards-Nunnally index and logistic regression were used. The results indicated that DSP, lower age, lower neuroticism and higher education were indicative of less technology anxiety. High DSP and high extraversion are indicative of technology enthusiasm. DSP and attitude towards technology seem to be key in getting older adults to stay active online.
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- Berner, Jessica, et al.
(author)
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Technology anxiety and technology enthusiasm versus digital ageism
- 2022
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In: Gerontechnology. - : International Society for Gerontechnology (ISG). - 1569-1101 .- 1569-111X. ; 21:1
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Journal article (peer-reviewed)abstract
- Background: Europe has called attention to the importance of the e-inclusion of older adults. Society is indicating that the developers, websites, and devices are causing age bias in technology. This affects living independently, the values of ethical principles associated with an older person, and digital ageism: which is an age-related bias in artificial intelligence systems. Objective: This research attempts to investigate the instrument technology anxiety and enthusiasm, and assistive technology devices during the period 2019- 2021. This instrument may be a way to redress misconceptions about digital ageism. The assistive technology device that we will investigate in this study is the adoption of a service that is designed for online health consultations. Method: The participants are part of the longitudinal Swedish National Study on Aging and Care. Technology anxiety and technology enthusiasm are two factors, which aim to measure technophilia (vs technophobia) in older adults. The age range is 63 -99 years of age in 2019 T1 and 66 -101 in 2021 T2. Wilcoxon rank test was conducted to investigate technology enthusiasm, technology anxiety, and how they changed with time. An Edwards Nunnally index was then calculated for both variables to observe a significant change in score from T1 to T2. Mann Whitney U test was used to investigate the variables sex and health status with technology anxiety & technology enthusiasm in T1 & T2. Age, Cognitive function MMSE, and digital social participation were investigated through a Kruskall-Wallis test. A logistic regression was conducted with the significant variable. Results: Between 2019-2021, change in technology enthusiasm was based on less digital social participation (OR: 0.608; CI 95%: 0.476- 0.792). Technology anxiety was significantly higher due to age (OR: 1.086, CI 95%: 1.035-1.139) and less digital social participation (OR: 0.684; CI 95%: 0.522- 0.895). The want for online healthcare consultations was popular but usage was low. Conclusion: Staying active on- line and participating digitally may be a way to reduce digital ageism. However, digital ageism is a complex phenomenon, which requires different solutions in order to include older people and reduce an inaccurate categorisation of this group in the digital society.
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4. |
- Dallora Moraes, Ana Luiza, et al.
(author)
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A decision tree multifactorial approach for predicting dementia in a 10 years’ time
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Other publication (other academic/artistic)abstract
- Background: Dementia is a complex neurological disorder, to which little is known about its mechanisms and no therapeutic treatment was identified, to date, to revert or alleviate its symptoms. It affects the older adults population causing a progressive cognitive decline that can become severe enough to impair the individuals' independence and functioning. In this scenario, the prognosis research, directed to identify modifiable risk factors in order to delay or prevent its development, in a big enough time frame is substantially important.Objective: This study investigates a decision tree multifactorial approach for the prognosis of dementia of individuals, not diagnosed with this disorder at baseline, and their development (or not) of dementia in a time frame of 10 years. Methods: This study retrieved data from the Swedish National Study on Aging and Care, which consisted of 726 subjects (313 males and 413 females), of which 91 presented a diagnosis of dementia at the 10-year study mark. A K-nearest neighbors multiple imputation method was employed to handle the missing data. A wrapper feature selection was employed to select the best features in a set of 75 variables, which considered factors related to demographic, social, lifestyle, medical history, biochemical test, physical examination, psychological assessment and diverse health instruments relevant to dementia evaluation. Lastly, a cost-sensitive decision tree approach was employed in order to build predictive models in an stratified nested cross-validation experimental setup.Results: The proposed approach achieved an AUC of 0.745 and Recall of 0.722 for the 10-year prognosis of dementia. Our findings showed that most of the variables selected by the tree are related to modifiable risk factors, of which physical strength was an important factor across all ages of the sample. Also, there was a lack of variables related to the health instruments routinely used for the dementia diagnosis that might not be sensitive enough to predict dementia in a 10 years’ time.Conclusions: The proposed model identified diverse modifiable factors, in a 10 years’ time from diagnosis, that could be investigated for possible interventions in order to delay or prevent the dementia onset.
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5. |
- Dallora Moraes, Ana Luiza, et al.
(author)
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Age assessment of youth and young adults using magnetic resonance imaging of the knee : A deep learning approach
- 2019
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In: JMIR Medical Informatics. - : JMIR PUBLICATIONS. - 2291-9694. ; 7:4, s. 419-436
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Journal article (peer-reviewed)abstract
- Background: Bone age assessment (BAA) is an important tool for diagnosis and in determining the time of treatment in a number of pediatric clinical scenarios, as well as in legal settings where it is used to estimate the chronological age of an individual where valid documents are lacking. Traditional methods for BAA suffer from drawbacks, such as exposing juveniles to radiation, intra- and interrater variability, and the time spent on the assessment. The employment of automated methods such as deep learning and the use of magnetic resonance imaging (MRI) can address these drawbacks and improve the assessment of age. Objective: The aim of this paper is to propose an automated approach for age assessment of youth and young adults in the age range when the length growth ceases and growth zones are closed (14-21 years of age) by employing deep learning using MRI of the knee. Methods: This study carried out MRI examinations of the knee of 402 volunteer subjects-221 males (55.0%) and 181 (45.0%) females-aged 14-21 years. The method comprised two convolutional neural network (CNN) models: the first one selected the most informative images of an MRI sequence, concerning age-assessment purposes; these were then used in the second module, which was responsible for the age estimation. Different CNN architectures were tested, both training from scratch and employing transfer learning. Results: The CNN architecture that provided the best results was GoogLeNet pretrained on the ImageNet database. The proposed method was able to assess the age of male subjects in the range of 14-20.5 years, with a mean absolute error (MAE) of 0.793 years, and of female subjects in the range of 14-19.5 years, with an MAE of 0.988 years. Regarding the classification of minors-with the threshold of 18 years of age-an accuracy of 98.1% for male subjects and 95.0% for female subjects was achieved. Conclusions: The proposed method was able to assess the age of youth and young adults from 14 to 20.5 years of age for male subjects and 14 to 19.5 years of age for female subjects in a fully automated manner, without the use of ionizing radiation, addressing the drawbacks of traditional methods. © 2019 Journal of Medical Internet Research. All rights reserved.
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6. |
- Dallora Moraes, Ana Luiza, et al.
(author)
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Bone age assessment with various machine learning techniques : A systematic literature review and meta-analysis
- 2019
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In: PLOS ONE. - : Public Library of Science. - 1932-6203. ; 14:7
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Research review (peer-reviewed)abstract
- Background The assessment of bone age and skeletal maturity and its comparison to chronological age is an important task in the medical environment for the diagnosis of pediatric endocrinology, orthodontics and orthopedic disorders, and legal environment in what concerns if an individual is a minor or not when there is a lack of documents. Being a time-consuming activity that can be prone to inter- and intra-rater variability, the use of methods which can automate it, like Machine Learning techniques, is of value. Objective The goal of this paper is to present the state of the art evidence, trends and gaps in the research related to bone age assessment studies that make use of Machine Learning techniques. Method A systematic literature review was carried out, starting with the writing of the protocol, followed by searches on three databases: Pubmed, Scopus and Web of Science to identify the relevant evidence related to bone age assessment using Machine Learning techniques. One round of backward snowballing was performed to find additional studies. A quality assessment was performed on the selected studies to check for bias and low quality studies, which were removed. Data was extracted from the included studies to build summary tables. Lastly, a meta-analysis was performed on the performances of the selected studies. Results 26 studies constituted the final set of included studies. Most of them proposed automatic systems for bone age assessment and investigated methods for bone age assessment based on hand and wrist radiographs. The samples used in the studies were mostly comprehensive or bordered the age of 18, and the data origin was in most of cases from United States and West Europe. Few studies explored ethnic differences. Conclusions There is a clear focus of the research on bone age assessment methods based on radiographs whilst other types of medical imaging without radiation exposure (e.g. magnetic resonance imaging) are not much explored in the literature. Also, socioeconomic and other aspects that could influence in bone age were not addressed in the literature. Finally, studies that make use of more than one region of interest for bone age assessment are scarce. Copyright: © 2019 Dallora et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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9. |
- Dellkvist, Helen, et al.
(author)
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The use of a digital life story to support person-centred care of older adults with dementia : A scoping review
- 2024
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In: Digital Health. - : Sage Publications. - 2055-2076. ; 10
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Research review (peer-reviewed)abstract
- IntroductionA life story (LS) is a tool healthcare professionals (HCPs) use to help older adults with dementia preserve their identities by sharing their stories. Applied health technology can be considered a niche within welfare technology. Combining technology and nursing, such as using life stories in digital form, may support person-centred care and allow HCPs to see the person behind the disease.ObjectiveThe study's objective was to summarise and describe the use of life stories in digital form in the daily care of older adults with dementia.MethodsA scoping review was conducted in five stages. Database searches were conducted in Cinahl, PubMed, Scopus, Web of Science, and Google Scholar; 31 articles were included. A conventional qualitative content analysis of the collected data was conducted.ResultsThe qualitative analysis resulted in three categories: (1) benefits for older adults, (2) influence on HCPs’ work, and (3) obstacles to implementing a digital LS in daily care.ConclusionOlder adults with dementia can receive person-centred care through a digital LS based on their wishes. A digital LS can enable symmetric communication and serve as an intergenerational communication tool. It can be used to handle behavioural symptoms. Using a digital LS in the later stages of dementia may differ from using it earlier in dementia. However, it may compensate for weakening abilities in older adults by enhancing social interaction.
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10. |
- Ghazi, Sarah Nauman, 1989-, et al.
(author)
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Psychological Health and Digital Social Participation of the Older Adults during the COVID-19 Pandemic in Blekinge, Sweden—An Exploratory Study
- 2022
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In: International Journal of Environmental Research and Public Health. - : MDPI. - 1661-7827 .- 1660-4601. ; 19:6
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Journal article (peer-reviewed)abstract
- COVID-19 has affected the psychological health of older adults directly and indirectly through recommendations of social distancing and isolation. Using the internet or digital tools to participate in society, one might mitigate the effects of COVID-19 on psychological health. This study explores the social participation of older adults through internet use as a social platform during COVID-19 and its relationship with various psychological health aspects. In this study, we used the survey as a research method, and we collected data through telephonic interviews; and online and paper-based questionnaires. The results showed an association of digital social participation with age and feeling lack of company. Furthermore, in addition, to the increase in internet use in older adults in Sweden during COVID-19, we conclude that digital social participation is essential to maintain psychological health in older adults.
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