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- Ammenwerth, Elske, et al.
(författare)
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International Comparison of Six Basic eHealth Indicators Across 14 Countries: An eHealth Benchmarking Study
- 2020
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Ingår i: Methods of Information in Medicine. - : Georg Thieme Verlag KG. - 0026-1270 .- 2511-705X. ; 59:S2, s. e46-e63
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Tidskriftsartikel (refereegranskat)abstract
- Background Many countries adopt eHealth applications to support patient-centered care. Through information exchange, these eHealth applications may overcome institutional data silos and support holistic and ubiquitous (regional or national) information logistics. Available eHealth indicators mostly describe usage and acceptance of eHealth in a country. The eHealth indicators focusing on the cross-institutional availability of patient-related information for health care professionals, patients, and care givers are rare. Objectives This study aims to present eHealth indicators on cross-institutional availability of relevant patient data for health care professionals, as well as for patients and their caregivers across 14 countries (Argentina, Australia, Austria, Finland, Germany, Hong Kong as a special administrative region of China, Israel, Japan, Jordan, Kenya, South Korea, Sweden, Turkey, and the United States) to compare our indicators and the resulting data for the examined countries with other eHealth benchmarks and to extend and explore changes to a comparable survey in 2017. We defined "availability of patient data" as the ability to access data in and to add data to the patient record in the respective country. Methods The invited experts from each of the 14 countries provided the indicator data for their country to reflect the situation on August 1, 2019, as date of reference. Overall, 60 items were aggregated to six eHealth indicators. Results Availability of patient-related information varies strongly by country. Health care professionals can access patients most relevant cross-institutional health record data fully in only four countries. Patients and their caregivers can access their health record data fully in only two countries. Patients are able to fully add relevant data only in one country. Finland showed the best outcome of all eHealth indicators, followed by South Korea, Japan, and Sweden. Conclusion Advancement in eHealth depends on contextual factors such as health care organization, national health politics, privacy laws, and health care financing. Improvements in eHealth indicators are thus often slow. However, our survey shows that some countries were able to improve on at least some indicators between 2017 and 2019. We anticipate further improvements in the future.
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2. |
- Craig, Wendy, et al.
(författare)
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Social Media Use and Cyber-Bullying: A Cross-National Analysis of Young People in 42 Countries
- 2020
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Ingår i: Journal of Adolescent Health. - : ELSEVIER SCIENCE INC. - 1054-139X .- 1879-1972. ; 66:6, s. S100-S108
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Social media use (SMU) has become an intrinsic part of adolescent life. Negative consequences of SMU for adolescent health could include exposures to online forms of aggression. We explored age, gender, and cross-national differences in adolescents engagement in SMU, then relationships between SMU and victimization and the perpetration of cyber-bullying. Methods: We used data on young people aged 11-15 years (weighted n = 180,919 in 42 countries) who participated in the 2017-2018 Health Behaviour in School-aged Children study to describe engagement in the three types of SMU (intense, problematic, and talking with strangers online) by age and gender and then in the perpetration and victimization of cyber-bullying. Relationships between SMU and cyber-bullying outcomes were estimated using Poisson regression (weighted n = 166,647 from 42 countries). Results: Variations in SMU and cyber-bullying follow developmental and gender-based patterns across countries. In pooled analyses, engagement in SMU related to cyber-bullying victimization (adjusted relative risks = 1.14 [95% confidence interval (CI): 1.10-1.19] to 1.48 [95% CI: 1.42-1.55]) and perpetration (adjusted relative risk = 1.31 [95% CI: 1.26-1.36] to 1.84 [95% CI: 1.74-1.95]). These associations were stronger for cyber-perpetration versus cyber-victimization and for girls versus boys. Problematic SMU was most strongly and consistently associated with cyber-bullying, both for victimization and perpetration. Stratified analyses showed that SMU related to cyber-victimization in 19%-45% of countries and to cyber-perpetration in 38%-86% of countries. Conclusions: Accessibility to social media and its pervasive use has led to new opportunities for online aggression. The time adolescents spend on social media, engage in problematic use, and talk to strangers online each relate to cyber-bullying and merit public health intervention. Problematic use of social media poses the strongest and most consistent risk. (C) 2020 Published by Elsevier Inc. on behalf of Society for Adolescent Health and Medicine.
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3. |
- Craig, Wendy, et al.
(författare)
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Social Media Use and Cyber-Bullying: A Cross-National Analysis of Young People in 42 Countries
- 2020
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Ingår i: Journal of Adolescent Health. - : Elsevier BV. - 1054-139X .- 1879-1972. ; 66:6
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Social media use (SMU) has become an intrinsic part of adolescent life. Negative consequences of SMU for adolescent health could include exposures to online forms of aggression. We explored age, gender, and cross-national differences in adolescents' engagement in SMU, then relationships between SMU and victimization and the perpetration of cyber-bullying. Methods: We used data on young people aged 11–15 years (weighted n = 180,919 in 42 countries) who participated in the 2017–2018 Health Behaviour in School-aged Children study to describe engagement in the three types of SMU (intense, problematic, and talking with strangers online) by age and gender and then in the perpetration and victimization of cyber-bullying. Relationships between SMU and cyber-bullying outcomes were estimated using Poisson regression (weighted n = 166,647 from 42 countries). Results: Variations in SMU and cyber-bullying follow developmental and gender-based patterns across countries. In pooled analyses, engagement in SMU related to cyber-bullying victimization (adjusted relative risks = 1.14 [95% confidence interval (CI): 1.10–1.19] to 1.48 [95% CI: 1.42–1.55]) and perpetration (adjusted relative risk = 1.31 [95% CI: 1.26–1.36] to 1.84 [95% CI: 1.74–1.95]). These associations were stronger for cyber-perpetration versus cyber-victimization and for girls versus boys. Problematic SMU was most strongly and consistently associated with cyber-bullying, both for victimization and perpetration. Stratified analyses showed that SMU related to cyber-victimization in 19%–45% of countries and to cyber-perpetration in 38%–86% of countries. Conclusions: Accessibility to social media and its pervasive use has led to new opportunities for online aggression. The time adolescents spend on social media, engage in problematic use, and talk to strangers online each relate to cyber-bullying and merit public health intervention. Problematic use of social media poses the strongest and most consistent risk.
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