The Experts below are selected from a list of 14154 Experts worldwide ranked by ideXlab platform
Ulrich Reininghaus - One of the best experts on this subject based on the ideXlab platform.
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evidence synthesis of digital interventions to mitigate the negative impact of the covid 19 pandemic on public mental health rapid meta review
Journal of Medical Internet Research, 2021Co-Authors: Christian Rauschenberg, Anita Schick, Dusan Hirjak, Andreas Seidler, Isabell Paetzold, Christian Apfelbacher, Steffi G Riedelheller, Ulrich ReininghausAbstract:Background: Accumulating evidence suggests the COVID-19 pandemic has negative effects on public mental health. Digital interventions that have been developed and evaluated in recent years may be used to mitigate the negative consequences of the pandemic. However, evidence-based recommendations on the use of existing telemedicine and internet-based (eHealth) and app-based mobile health (mHealth) interventions are lacking. Objective: The aim of this study was to investigate the theoretical and empirical base, user perspective, safety, effectiveness, and cost-effectiveness of digital interventions related to public mental health provision (ie, mental health promotion, prevention, and treatment of mental disorders) that may help to reduce the consequences of the COVID-19 pandemic. Methods: A rapid meta-review was conducted. The MEDLINE, PsycINFO, and CENTRAL databases were searched on May 11, 2020. Study inclusion criteria were broad and considered systematic reviews and meta-analyses that investigated digital tools for health promotion, prevention, or treatment of mental health conditions and determinants likely affected by the COVID-19 pandemic. Results: Overall, 815 peer-reviewed systematic reviews and meta-analyses were identified, of which 83 met the inclusion criteria. Our findings suggest that there is good evidence on the usability, safety, acceptance/satisfaction, and effectiveness of eHealth interventions. Evidence on mHealth apps is promising, especially if social components (eg, blended care) and strategies to promote adherence are incorporated. Although most digital interventions focus on the prevention or treatment of mental disorders, there is some evidence on mental health promotion. However, evidence on process quality, cost-effectiveness, and long-term effects is very limited. Conclusions: There is evidence that digital interventions are particularly suited to mitigating psychosocial consequences at the population level. In times of physical distancing, quarantine, and restrictions on social contacts, decision makers should develop digital strategies for continued mental health care and invest time and efforts in the development and implementation of mental health promotion and prevention programs.
Anita Bregenzer - One of the best experts on this subject based on the ideXlab platform.
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integration of ehealth tools in the process of workplace health promotion proposal for design and implementation
Journal of Medical Internet Research, 2018Co-Authors: Paulino Jimenez, Anita BregenzerAbstract:Background: Electronic health (eHealth) and mobile health (mHealth) tools can support and improve the whole process of workplace health promotion (WHP) projects. However, several challenges and opportunities have to be considered while integrating these tools in WHP projects. Currently, a large number of eHealth tools are developed for changing health behavior, but these tools can support the whole WHP process, including group administration, information flow, assessment, intervention development process, or evaluation. Objective: To support a successful implementation of eHealth tools in the whole WHP processes, we introduce a concept of WHP (life cycle model of WHP) with 7 steps and present critical and success factors for the implementation of eHealth tools in each step. Methods: We developed a life cycle model of WHP based on the World Health Organization (WHO) model of healthy workplace continual improvement process. We suggest adaptations to the WHO model to demonstrate the large number of possibilities to implement eHealth tools in WHP as well as possible critical points in the implementation process. Results: eHealth tools can enhance the efficiency of WHP in each of the 7 steps of the presented life cycle model of WHP. Specifically, eHealth tools can support by offering easier administration, providing an information and communication platform, supporting assessments, presenting and discussing assessment results in a dashboard, and offering interventions to change individual health behavior. Important success factors include the possibility to give automatic feedback about health parameters, create incentive systems, or bring together a large number of health experts in one place. Critical factors such as data security, anonymity, or lack of management involvement have to be addressed carefully to prevent nonparticipation and dropouts. Conclusions: Using eHealth tools can support WHP, but clear regulations for the usage and implementation of these tools at the workplace are needed to secure quality and reach sustainable results. [J Med Internet Res 2018;20(2):e65]
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integration of ehealth tools in the process of workplace health promotion proposal for design and implementation
Journal of Medical Internet Research, 2018Co-Authors: Paulino Jimenez, Anita BregenzerAbstract:Background: Electronic health (eHealth) and mobile health (mHealth) tools can support and improve the whole process of workplace health promotion (WHP) projects. However, several challenges and opportunities have to be considered while integrating these tools in WHP projects. Currently, a large number of eHealth tools are developed for changing health behavior, but these tools can support the whole WHP process, including group administration, information flow, assessment, intervention development process, or evaluation. Objective: To support a successful implementation of eHealth tools in the whole WHP processes, we introduce a concept of WHP (life cycle model of WHP) with 7 steps and present critical and success factors for the implementation of eHealth tools in each step. Methods: We developed a life cycle model of WHP based on the World Health Organization (WHO) model of healthy workplace continual improvement process. We suggest adaptations to the WHO model to demonstrate the large number of possibilities to implement eHealth tools in WHP as well as possible critical points in the implementation process. Results: eHealth tools can enhance the efficiency of WHP in each of the 7 steps of the presented life cycle model of WHP. Specifically, eHealth tools can support by offering easier administration, providing an information and communication platform, supporting assessments, presenting and discussing assessment results in a dashboard, and offering interventions to change individual health behavior. Important success factors include the possibility to give automatic feedback about health parameters, create incentive systems, or bring together a large number of health experts in one place. Critical factors such as data security, anonymity, or lack of management involvement have to be addressed carefully to prevent nonparticipation and dropouts. Conclusions: Using eHealth tools can support WHP, but clear regulations for the usage and implementation of these tools at the workplace are needed to secure quality and reach sustainable results.
Sylvia Meek - One of the best experts on this subject based on the ideXlab platform.
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mobile health mHealth approaches and lessons for increased performance and retention of community health workers in low and middle income countries a review
Journal of Medical Internet Research, 2013Co-Authors: Karin Källander, O J Akpogheneta, James K Tibenderana, Z Hill, Lesong Conteh, Daniel Strachan, Augustinus Ten H A Asbroek, Betty R. Kirkwood, Sylvia MeekAbstract:Background: Mobile health (mHealth) describes the use of portable electronic devices with software applications to provide health services and manage patient information. With approximately 5 billion mobile phone users globally, opportunities for mobile technologies to play a formal role in health services, particularly in low- and middle-income countries, are increasingly being recognized. mHealth can also support the performance of health care workers by the dissemination of clinical updates, learning materials, and reminders, particularly in underserved rural locations in low- and middle-income countries where community health workers deliver integrated community case management to children sick with diarrhea, pneumonia, and malaria. Objective: Our aim was to conduct a thematic review of how mHealth projects have approached the intersection of cellular technology and public health in low- and middle-income countries and identify the promising practices and experiences learned, as well as novel and innovative approaches of how mHealth can support community health workers. Methods: In this review, 6 themes of mHealth initiatives were examined using information from peer-reviewed journals, websites, and key reports. Primary mHealth technologies reviewed included mobile phones, personal digital assistants (PDAs) and smartphones, patient monitoring devices, and mobile telemedicine devices. We examined how these tools could be used for education and awareness, data access, and for strengthening health information systems. We also considered how mHealth may support patient monitoring, clinical decision making, and tracking of drugs and supplies. Lessons from mHealth trials and studies were summarized, focusing on low- and middle-income countries and community health workers. Results: The review revealed that there are very few formal outcome evaluations of mHealth in low-income countries. Although there is vast documentation of project process evaluations, there are few studies demonstrating an impact on clinical outcomes. There is also a lack of mHealth applications and services operating at scale in low- and middle-income countries. The most commonly documented use of mHealth was 1-way text-message and phone reminders to encourage follow-up appointments, healthy behaviors, and data gathering. Innovative mHealth applications for community health workers include the use of mobile phones as job aides, clinical decision support tools, and for data submission and instant feedback on performance. Conclusions: With partnerships forming between governments, technologists, non-governmental organizations, academia, and industry, there is great potential to improve health services delivery by using mHealth in low- and middle-income countries. As with many other health improvement projects, a key challenge is moving mHealth approaches from pilot projects to national scalable programs while properly engaging health workers and communities in the process. By harnessing the increasing presence of mobile phones among diverse populations, there is promising evidence to suggest that mHealth can be used to deliver increased and enhanced health care services to individuals and communities, while helping to strengthen health systems. [J Med Internet Res 2013;15(1):e17]
Richard J Katz - One of the best experts on this subject based on the ideXlab platform.
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moving mobile health forward combining mHealth with community health workers bolsters heart failure care
Journal of Cardiac Failure, 2018Co-Authors: Gurusher Panjrath, Linda Bostrom, Linda Witkin, Richard J KatzAbstract:Background Telemedicine programs targeted towards vulnerable HF patients have had high expense and variable impact. Mobile Health (mHealth) based HF management has been limited by lack of frequent communication between patients and the health care team and adoption of mHealth due to failure to address both medical and social needs common to underserved patients. Community health workers (CHW) have been successful in improving self-care and reducing readmissions in many chronic diseases, however, a combination of CHW and mHealth has not been investigated. Goal of this pilot study was to implement an innovative strategy for mHealth adoption, and effectiveness by integrating it with CHWs for the management of HF in an underserved population. Methods mHealth app was provided to HF pts. Based on initial mHeath use, patients were assigned to continued mHeallth or CHW + mHealth. CHW attempted regular phone or home contacts. mHealth activity was monitored on online platform. Outcomes included mHealth adoption, medication adherence, ED visits/Hospitalization and QOL. Results A total of 111 patients were screened and 24 patients were enrolled (16 systolic; 9 male, mean age 52). Overall, adoption of mHealth was low. Eighty-seven phone contacts and 1 home visit were made over 6 months. Despite a high rate of reported medication adherence at baseline majority of the patients felt that adding CHW to mHealth was useful and their HF was better managed being in the program. Conclusion In this pilot study, combination of CHW with mHealth failed to enhance mHealth adoption. Despite poor adoption, the combination resulted in improvements in self-reported medication adherence, QOL and reduced hospitalization. Future studies need to address factors related to poor adoption among underserved HF patients.
Wayne Katon - One of the best experts on this subject based on the ideXlab platform.
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use of mobile health mHealth tools by primary care patients in the wwami region practice and research network wprn
Journal of the American Board of Family Medicine, 2014Co-Authors: Amy M Bauer, Tessa Rue, Gina A Keppel, Allison M Cole, Lauramae Baldwin, Wayne KatonAbstract:Purpose: The purpose of this study was to determine the prevalence of mobile health (mHealth) use among primary care patients and examine demographic and clinical correlates. Methods: Adult patients who presented to 1 of 6 primary care clinics in a practice-based research network in the northwest United States during a 2-week period received a survey that assessed smartphone ownership; mHealth use; sociodemographic characteristics (age, sex, race/ethnicity, health literacy); chronic conditions; and depressive symptoms (2-item Patient Health Questionnaire). Data analysis used descriptive statistics and mixed logistic regression. Results: Of 918 respondents (estimated response rate, 67.4%), 55% owned a smartphone, among whom 70% were mHealth users. In multivariate analyses, smartphone ownership and mHealth use were not associated with health literacy, chronic conditions, or depression but were less common among adults >45 years old (adjusted odds ratio, 0.07–0.39; P Conclusions: Use of mHealth technologies is lower among older adults but otherwise is common among primary care patients, including those with limited health literacy and those with chronic conditions. Findings support the potential role of mHealth in improving disease management among certain groups in need; however, greater involvement of health care providers may be important for realizing this potential.