Högskolan i Skövde

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.

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.

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.

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.

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.

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.

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.

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.

Background Dementia is a complex disorder characterized by poor outcomes for the patients and high costs of care. After decades of research little is known about its mechanisms. Having prognostic estimates about dementia can help researchers, patients and public entities in dealing with this disorder. Thus, health data, machine learning and microsimulation techniques could be employed in developing prognostic estimates for dementia. Objective The goal of this paper is to present evidence on the state of the art of studies investigating and the prognosis of dementia using machine learning and microsimulation techniques. Method To achieve our goal we carried out a systematic literature review, in which three large databases -Pubmed, Socups and Web of Science were searched to select studies that employed machine learning or microsimulation techniques for the prognosis of dementia. A single backward snowballing was done to identify further studies. A quality checklist was also employed to assess the quality of the evidence presented by the selected studies, and low quality studies were removed. Finally, data from the final set of studies were extracted in summary tables. Results In total 37 papers were included. The data summary results showed that the current research is focused on the investigation of the patients with mild cognitive impairment that will evolve to Alzheimer's disease, using machine learning techniques. Microsimulation studies were concerned with cost estimation and had a populational focus. Neuroimaging was the most commonly used variable. Conclusions Prediction of conversion from MCI to AD is the dominant theme in the selected studies. Most studies used ML techniques on Neuroimaging data. Only a few data sources have been recruited by most studies and the ADNI database is the one most commonly used. Only two studies have investigated the prediction of epidemiological aspects of Dementia using either ML or MS techniques. Finally, care should be taken when interpreting the reported accuracy of ML techniques, given studies' different contexts.

OBJECTIVE: The objective of this paper is to investigate the goals and variables employed in the machine learning and microsimulation studies for the prognosis of dementia. METHOD: According to preset protocols, the Pubmed, Socups and Web of Science databases were searched to find studies that matched the defined inclusion/exclusion criteria, and then its references were checked for new studies. A quality checklist assessed the selected studies, and removed the low quality ones. The remaining ones (included set) had their data extracted and summarized. RESULTS: The summary of the data of the 37 included studies showed that the most common goal of the selected studies was the prediction of the conversion from mild cognitive impairment to Alzheimer's Disease, for studies that used machine learning, and cost estimation for the microsimulation ones. About the variables, neuroimaging was the most frequent used. CONCLUSIONS: The systematic literature review showed clear trends in prognosis of dementia research in what concerns machine learning techniques and microsimulation.

Background: Bone age assessment (BAA) is used in numerous pediatric clinical settings, as well as in legal settings when entities need an estimate of chronological age (CA) when valid documents are lacking. The latter case presents itself as critical since the law is harsher for adults and granted rights along with imputability changes drastically if the individual is a minor. Traditional BAA methods suffer from drawbacks such as exposure of minors to radiation, do not consider factors that might affect the bone age and they mostly focus on a single region. Given the critical scenarios in which BAA can affect the lives of young individuals it is important to focus on the drawbacks of the traditional methods and investigate the potential of estimating CA through BAA.

Objective: This paper aims to investigate CA estimation through BAA in young individuals of 14 to 21 years with machine learning methods, addressing the drawbacks in the research using magnetic resonance imaging (MRI), assessment of multiple ROIs and other factors that may affect the bone age.

Methods: MRI examinations of the radius, distal tibia, proximal tibia, distal femur and calcaneus were carried out on 465 males and 473 females subjects (14-21 years). Measures of weight and height were taken from the subjects and a questionnaire was given for additional information (self-assessed Tanner Scale, physical activity level, parents' origin, type of residence during upbringing). Two pediatric radiologists assessed, independently, the MRI images as to their stage of bone development (blinded to age, gender and each other). All the gathered information was used in training machine learning models for chronological age estimation and minor versus adults classification (threshold of 18 years). Different machine learning methods were investigated.

Results: The minor versus adults classification produced accuracies of 90% and 84%, for male and female subjects, respectively, with high recalls for the classification of minors. The chronological age estimation for the eight age groups (14-21 years) achieved mean absolute errors of 0.95 years and 1.24 years for male and female subjects, respectively. However, for the latter lower error occurred only for the ages of 14 and 15.

Conclusions: This paper proposed to investigate the CA estimation through BAA using machine learning methods in two ways: minor versus adults classification and CA estimation in eight age groups (14-21 years), while addressing the drawbacks in the research on BAA. The first achieved good results, however, for the second case BAA showed not precise enough for the classification.

Dementia is a neurodegenerative disorder that affects the older adult population. To date, no cure or treatment to change its course is available. Since changes in the brains of affected individuals could be evidenced as early as 10 years before the onset of symptoms, prognosis research should consider this time frame. This study investigates a broad decision tree multifactorial approach for the prediction of dementia, considering 75 variables regarding demographic, social, lifestyle, medical history, biochemical tests, physical examination, psychological assessment and health instruments. Previous work on dementia prognoses with machine learning did not consider a broad range of factors in a large time frame. The proposed approach investigated predictive factors for dementia and possible prognostic subgroups. This study used data from the ongoing multipurpose Swedish National Study on Aging and Care, consisting of 726 subjects (91 presented dementia diagnosis in 10 years). The proposed approach achieved an AUC of 0.745 and Recall of 0.722 for the 10-year prognosis of dementia. Most of the variables selected by the tree are related to modifiable risk factors; physical strength was important across all ages. Also, there was a lack of variables related to health instruments routinely used for the dementia diagnosis. 

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.

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.

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.

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.

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.

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.

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.

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.

Dementia is a neurological condition that primarily affects older adults and there is stillno cure or therapy available to cure it. The symptoms of dementia can appear as early as 10 yearsbefore the beginning of actual diagnosed dementia. Hence, machine learning (ML) researchershave 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 byimbalanced classes in the dataset. Past research did not address this issue well and did not takepreventative precautions. Different ML models were developed to illustrate this bias. To alleviate theproblem of bias, we deployed a synthetic minority oversampling technique (SMOTE) to balance thetraining process of the proposed ML model. The second issue is the poor classification accuracy ofML 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 boostmodel. The autoencoder is used to extract relevant features from the feature space and the Adaboostmodel is deployed for the classification of dementia by using an extracted subset of features. Thehyperparameters of the Adaboost model are fine-tuned using a grid search algorithm. Experimentalfindings reveal that the suggested learning system outperforms eleven similar systems which wereproposed in the literature. Furthermore, it was also observed that the proposed learning systemimproves 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%.

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 proposed 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.

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.

Aim To assess growth plate fusion by magnetic resonance imaging (MRI) and evaluate the correlation with sex, age, pubertal development, physical activity and BMI. Methods Wrist, knee and ankle of 958 healthy subjects aged 14.0-21.5 years old were examined using MRI and graded by two radiologists. Correlations of growth plate fusion score with age, pubertal development, physical activity and BMI were assessed. Results Complete growth plate fusion occurred in 75%, 85%, 97%, 98%, 98% and 90%, 97%, 95%, 97%, 98% (radius, femur, proximal- and distal tibia and calcaneus) in 17-year-old females and 19-year-old males, respectively. Complete fusion occurs approximately 2 years earlier in girls than in boys. Pubertal development correlated with growth plate fusion score (rho = 0.514-0.598 for the different growth plate sites) but regular physical activity did not. BMI also correlated with growth plate fusion (rho = 0.186-0.384). Stratified logistic regression showed increased odds ratio (OR F: 2.65-8.71; M: 1.71-4.03) for growth plate fusion of obese or overweight subects versus normal-weight subjects. Inter-observer agreement was high (Kappa = 0.87-0.94). Conclusion Growth plate fusion can be assessed by MRI; occurs in an ascending order, from the foot to the wrist; and is significantly influenced by sex, pubertal development and BMI, but not by physical activity.

Aims: Pain is one of the most frequent reasons for seeking health care, and is thus a public health problem. Although there is a progressive increase in pain and impaired physical function with age, few studies are performed on older adults. The aim of this study was to investigate if there are associations between musculoskeletal pain interfering with normal life in older adults and physical and psychosocial workloads through life. Methods: The association of heavy physical workload and negative psychosocial workload and musculoskeletal pain interfering with normal life (SF 12) was analyzed by multiple logistic regression. The model was adjusted for eight background covariates: age, gender, growing-up environment, educational level, if living alone or not, obesity, smoking, and leisure physical activity. Results: Negative psychosocial and heavy physical workloads were independently associated with musculoskeletal pain interfering with normal life (adjusted OR: 4.44, 95% CI: 2.84-6.92), and (adjusted OR: 1.88, 95% CI: 1.20-2.93), respectively. The background covariates female gender and higher education were also associated with musculoskeletal pain interfering with normal life, and physical leisure activity was inversely associated. Conclusions: The findings suggest that negative psychosocial and heavy physical workloads are strongly associated with musculoskeletal pain interfering with normal life in older adults.

There are associations between pain, comorbidity and risk of falling, and falling increases the risk of mortality in older persons, but few studies have investigated the development of pain as a result of impaired physical function. The aim of this study was to examine possible associations between weak physical performance and the development of musculoskeletal pain that interferes with normal life in a sample of older adults. The sample derived from a national, longitudinal multicenter study; the Swedish National Study on Ageing and Care; SNAC-B. The participants (n = 490) were between 60 and 78 years at the baseline examinations. Three variables were chosen for the exposure physical function, from the baseline examinations; One Leg Stand, Grip strength and Sit-to-Stand. The outcome musculoskeletal pain that interferes with normal life was measured using EQ5D and SF-12 6 years later, and logistic regression was used to investigate possible associations between the exposures and the outcome. Maximum grip strength (Grippit) was inversely associated with musculoskeletal pain that interferes with normal life (OR 2.31; 95% CI 1.15-4.61), and One-Leg Stand and Sit-to-Stand were not associated with the development of pain (OR 1.30; 95% CI 0.64-2.64) and (OR 0.91; 95% CI 0.45-1.86), respectively. Weak grip strength was inversely associated with the development of musculoskeletal pain that interferes with normal life in older adults. Impaired proprioceptive function, strength and mobility in elderly with pain have been found in earlier research. Since pain increases the risk of falling, it is important to investigate if it may develop as a function of an impaired physical function. The results of the present study could be of importance for future prevention programs aiming to protect elderly from falling.

Background Health communication (HC) is a vast research field focusing on changing health behaviours, and rapidly evolving technology is creating different ways and possibilities to reach target groups and audiences. In the context of home care, a deeper understanding of HC is lacking, specifically for older persons with care needs and their informal caregivers. The aim of this concept analysis is to identify and construct the meaning of HC from the perspective of older persons in need of care in the home environment and their informal caregivers. Materials and methods This study utilised Rogers' (2000) Evolutionary Concept Analysis Method (EMCA) to create and construct a meaning of the concept of HC. The EMCA was based on a systematic literature review of scientific articles, using CINAHL, Pubmed and Inspec (2000-2017). A total of 29 articles were retrieved and analysed. Results The identified attributes of the concept were as follows: resources of the recipient, influence on decisions and advantages of tailored information. HC was described as both contributing to knowledge as well as being overwhelming where habits and resources influenced the use of information. The attributes led to the following descriptive definition of HC: 'Tailored HC, based on needs and resources of the recipient influence care decisions'. The home environment influenced HC by habits and interactions between older persons and their informal caregivers. Conclusions The home environment influenced HC in terms of social aspects of interactions and habits and between the older person and the informal caregiver. Tailored information with the use of technology contributed to knowledge in care of older persons and their informal caregivers. HC was shown to contribute to improve care for older people in their home environment.

Population ageing within Europe has major social and economic consequences. One of the most devastating conditions that predominantly affects older people is dementia. The SMART4MD (Support Monitoring and Reminder Technology for Mild Dementia) project aims to develop and test a health application specifically designed for people with mild dementia. The aim of this feasibility study was to evaluate the design of the SMART4MD protocol, including recruitment, screening, baseline examination and data management, and to test the SMART4MD application for functionality and usability before utilization in a full-scale study. The feasibility study tested the protocol and the app in Spain and Sweden. A total of nineteen persons with cognitive impairment, and their informal caregivers, individually performed a task-based usability test of the SMART4MD app model in a clinical environment, followed by four-week testing of the app in the home environment. By employing a user-centered design approach, the SMART4MD application proved to be an adequate and feasible interface for an eHealth intervention. In the final usability test, a score of 81% satisfied users was obtained. The possibility to test the application in all the procedures included in the study generated important information on how to present the technology to the users and how to improve these procedures. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Purpose To describe nurse anesthetists’ experiences using smart glasses to monitor patients’ vital signs during anesthesia care. Methods Data was collected through individual semi-structured interviews with seven nurse anesthetists who had used smart glasses, with a customized application for monitoring vital signs, during clinical anesthesia care. Data was analyzed using thematic content analysis. Results An overarching theme became evident during analysis; Facing and embracing responsibility. Being a nurse anesthetist entails a great responsibility, and the participants demonstrated that they shouldered this responsibility with pride. The theme was divided in two sub-themes. The first of these, A new way of working, comprised the categories Adoption and Utility. This involved incorporating smart glasses into existing routines in order to provide safe anesthesia care. The second sub-theme, Encountering side effects, consisted of the categories Obstacles and Personal affect. This sub-theme concerned the possibility to use smart glasses as intended, as well as the affect on nurse anesthetists as users. Conclusion Smart glasses improved access to vital signs and enabled continuous monitoring regardless of location. Continued development and improvement, both in terms of the application software and the hardware, are necessary for smart glasses to meet nurse anesthetists’ needs in clinical practice. Copyright: 

The national Rikshandbokenfor child healthcare, is a web-based guideline for child health care in Sweden containing knowledge- and methodological guidance and a national child health care program in progress to be implemented. The aim with the study was to examine child health care nurses use and ways of understanding the national web-basedRikshandbokenfor child health care.  Mixed method with sequential explanatory design in two phases was used; a web-survey with descriptive statistic followed by telephone interviews with phenomenographic analysis. The study showed variations in use and contribute with deeper knowledge of child healthcare nurse´s ways of understanding the unit RHB whose varied parts interact with each other. To be reliable, useful and relevant for nurses in their context, Rikshandbokenmust be kept updated and involve the end-users in the development process. Access to technical devices and optimal use of the possibilities with information and communication technology, the national web-based Rikshandbokencan be a resource for continuing learning and a tool in everyday work and a possible determinant to an equal child healthcare. The study contributes with valuable knowledge when designing web-based clinical practice guidelines for healthcare, making them useful and relevant for the end-users

Aim: The aim of this study was to investigate child health-care coordinators’ experiences of being a facilitator for the implementation of a new national child health-care programme in the form of a web-based national guide. Methods: The study was based on eight remote, online focus groups, using Skype for Business. A qualitative content analysis was performed. Results: The analysis generated three categories: adapt to a local context, transition challenges and led by strong incentives. There were eight subcategories. In the latent analysis, the theme ‘Being a facilitator: a complex role’ was formed to express the child health-care coordinators’ experiences. Conclusions: Facilitating a national guideline or decision support in a local context is a complex task that requires an advocating and mediating role. For successful implementation, guidelines and decision support, such as a web-based guide and the new child health-care programme, must match professional consensus and needs and be seen as relevant by all. Participation in the development and a strong bottom-up approach was important, making the web-based guide and the programme relevant to whom it is intended to serve, and for successful implementation. The study contributes valuable knowledge when planning to implement a national web-based decision support and policy programme in a local health-care context.

Rikshandboken i Barnhälsovård is a Swedish Web-based guide for child healthcare, providing quality-ensured guidelines and support contributing to equality in child healthcare among all children. In 2015, a new child healthcare program was implemented and made available in this Web-based guide. The aim of this study was to investigate how child healthcare nurses use Rikshandboken i Barnhälsovård and factors affecting its use. The study was a comprehensive Web survey of 2376 child healthcare nurses in Sweden answered by 1309. Statistical processing was performed using descriptive and analytical methods. Rikshandboken i Barnhälsovård was widely used by the respondents, but regional differences and number of years in the profession affected the use. Almost all nurses were satisfied with the usability, content, and design and felt that a national guide for child healthcare is important. This indicates that an established Web-based national guide is an appropriate setting when a new national program is implemented. In order to achieve an equal and equitable child healthcare, it is essential that all nurses use the national guide to provide evidence-based practice. The value of main child healthcare units as regional facilitators in the innovation process of Rikshandboken i Barnhälsovård should not be underestimated.