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- Anderberg, Peter, et al.
(författare)
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A Novel Instrument for Measuring Older People's Attitudes Toward Technology (TechPH) : Development and Validation
- 2019
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Ingår i: Journal of Medical Internet Research. - : JMIR PUBLICATIONS, INC. - 1438-8871. ; 21:5
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Tidskriftsartikel (refereegranskat)abstract
- Background: The use of health technology by older people is coming increasingly in focus with the demographic changes. Health information technology is generally perceived as an important factor in enabling increased quality of life and reducing the cost of care for this group. Age-appropriate design and facilitation of technology adoption are important to ensure functionality and removal of various barriers to usage. Development of assessment tools and instruments for evaluating older persons' technology adoption and usage as well as measuring the effects of the interventions are of high priority. Both usability and acceptance of a specific technology or service are important factors in evaluating the impact of a health information technology intervention. Psychometric measures are seldom included in evaluations of health technology. However, basic attitudes and sentiments toward technology (eg, technophilia) could be argued to influence both the level of satisfaction with the technology itself as well as the perception of the health intervention outcome. Objective: The purpose of this study is to develop a reduced and refined instrument for measuring older people's attitudes and enthusiasm for technology based on relevant existing instruments for measuring technophilia A requirement of the new instrument is that it should be short and simple to make it usable for evaluation of health technology for older people. Methods: Initial items for the TechPH questionnaire were drawn from a content analysis of relevant existing technophilia measure instruments. An exploratory factor analysis was conducted in a random selection of persons aged 65 years or older (N=374) on eight initial items. The scale was reduced to six items, and the internal consistency and reliability of the scale were examined. Further validation was made by a confirmatory factor analysis (CFA). Results: The exploratory factor analysis resulted in two factors. These factors were analyzed and labeled techEnthusiasm and techAnxiety. They demonstrated relatively good internal consistency (Cronbach alpha=.72 and .68, respectively). The factors were confirmed in the CFA and showed good model fit (chi(2)(8)=21.2, chi(2)/df=2.65, comparative fit index=0.97, adjusted goodness-of-fit index=0.95, root mean square error of approximation=0.067, standardized root mean square residual=0.036). Conclusions: The construed TechPH score showed expected relations to external real-world criteria, and the two factors showed interesting internal relations. Different technophilia personality traits distinguish clusters with different behaviors of adaptation as well as usage of new technology. Whether there is an independent association with the TechPH score against outcomes in health technology projects needs to be shown in further studies. The instrument must also be validated in different contexts, such as other countries.
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| 2. |
- Anderberg, Peter, et al.
(författare)
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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 study
- 2019
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Ingår i: Journal of Medical Internet Research. - : Journal of Medical Internet Research. - 1438-8871. ; 21:10
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Tidskriftsartikel (refereegranskat)abstract
- 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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| 3. |
- Guzman-Parra, Jose, et al.
(författare)
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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 : cross-sectional study
- 2020
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Ingår i: Journal of Medical Internet Research. - : JMIR Publications. - 1438-8871. ; 22:6
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 4. |
- Idrisoglu, Alper, et al.
(författare)
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Applied Machine Learning Techniques to Diagnose Voice-Affecting Conditions and Disorders : Systematic Literature Review
- 2023
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Ingår i: Journal of Medical Internet Research. - : JMIR Publications. - 1438-8871. ; 25
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Forskningsöversikt (refereegranskat)abstract
- BACKGROUND: Normal voice production depends on the synchronized cooperation of multiple physiological systems, which makes the voice sensitive to changes. Any systematic, neurological, and aerodigestive distortion is prone to affect voice production through reduced cognitive, pulmonary, and muscular functionality. This sensitivity inspired using voice as a biomarker to examine disorders that affect the voice. Technological improvements and emerging machine learning (ML) technologies have enabled possibilities of extracting digital vocal features from the voice for automated diagnosis and monitoring systems. OBJECTIVE: This study aims to summarize a comprehensive view of research on voice-affecting disorders that uses ML techniques for diagnosis and monitoring through voice samples where systematic conditions, nonlaryngeal aerodigestive disorders, and neurological disorders are specifically of interest. METHODS: This systematic literature review (SLR) investigated the state of the art of voice-based diagnostic and monitoring systems with ML technologies, targeting voice-affecting disorders without direct relation to the voice box from the point of view of applied health technology. Through a comprehensive search string, studies published from 2012 to 2022 from the databases Scopus, PubMed, and Web of Science were scanned and collected for assessment. To minimize bias, retrieval of the relevant references in other studies in the field was ensured, and 2 authors assessed the collected studies. Low-quality studies were removed through a quality assessment and relevant data were extracted through summary tables for analysis. The articles were checked for similarities between author groups to prevent cumulative redundancy bias during the screening process, where only 1 article was included from the same author group. RESULTS: In the analysis of the 145 included studies, support vector machines were the most utilized ML technique (51/145, 35.2%), with the most studied disease being Parkinson disease (PD; reported in 87/145, 60%, studies). After 2017, 16 additional voice-affecting disorders were examined, in contrast to the 3 investigated previously. Furthermore, an upsurge in the use of artificial neural network-based architectures was observed after 2017. Almost half of the included studies were published in last 2 years (2021 and 2022). A broad interest from many countries was observed. Notably, nearly one-half (n=75) of the studies relied on 10 distinct data sets, and 11/145 (7.6%) used demographic data as an input for ML models. CONCLUSIONS: This SLR revealed considerable interest across multiple countries in using ML techniques for diagnosing and monitoring voice-affecting disorders, with PD being the most studied disorder. However, the review identified several gaps, including limited and unbalanced data set usage in studies, and a focus on diagnostic test rather than disorder-specific monitoring. Despite the limitations of being constrained by only peer-reviewed publications written in English, the SLR provides valuable insights into the current state of research on ML-based voice-affecting disorder diagnosis and monitoring and highlighting areas to address in future research.
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