Advantages and disadvantages of mobile applications for workplace health promotion: A scoping review
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SUBMITTER: Junker M
PROVIDER: S-EPMC10760718 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:BackgroundThe proliferation of mobile health (mHealth) applications is partly driven by the advancements in sensing and communication technologies, as well as the integration of artificial intelligence techniques. Data collected from mHealth applications, for example, on sensor devices carried by patients, can be mined and analyzed using artificial intelligence-based solutions to facilitate remote and (near) real-time decision-making in health care settings. However, such data often sit in data silos, and patients are often concerned about the privacy implications of sharing their raw data. Federated learning (FL) is a potential solution, as it allows multiple data owners to collaboratively train a machine learning model without requiring access to each other's raw data.ObjectiveThe goal of this scoping review is to gain an understanding of FL and its potential in dealing with sensitive and heterogeneous data in mHealth applications. Through this review, various stakeholders, such as health care providers, practitioners, and policy makers, can gain insight into the limitations and challenges associated with using FL in mHealth and make informed decisions when considering implementing FL-based solutions.MethodsWe conducted a scoping review following the guidelines of PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). We searched 7 commonly used databases. The included studies were analyzed and summarized to identify the possible real-world applications and associated challenges of using FL in mHealth settings.ResultsA total of 1095 articles were retrieved during the database search, and 26 articles that met the inclusion criteria were included in the review. The analysis of these articles revealed 2 main application areas for FL in mHealth, that is, remote monitoring and diagnostic and treatment support. More specifically, FL was found to be commonly used for monitoring self-care ability, health status, and disease progression, as well as in diagnosis and treatment support of diseases. The review also identified several challenges (eg, expensive communication, statistical heterogeneity, and system heterogeneity) and potential solutions (eg, compression schemes, model personalization, and active sampling).ConclusionsThis scoping review has highlighted the potential of FL as a privacy-preserving approach in mHealth applications and identified the technical limitations associated with its use. The challenges and opportunities outlined in this review can inform the research agenda for future studies in this field, to overcome these limitations and further advance the use of FL in mHealth.
| S-EPMC10186185 | biostudies-literature
Project description:BackgroundThe concept of mobile health has attracted considerable attention across the globe, as it provides both healthcare professionals and patients with a distinct means of information and resources.AimThis study was conducted with the aim of utilising mobile health (mHealth) applications by nurses and presenting a scenario of how and why they are utilised.MethodsThis study was a scoping review. Data collection was carried out by searching the related keywords in Google Scholar, Scopus, Cochrane, EMBASE, Ovid, and PubMed databases from January 2000 to March 2019.ResultsRegarding the reasons for using mobile applications by nurses, five objectives were identified, including learning and knowledge enhancement, treatment and improvement of the patient care process, diagnostic process, data and patient management, and health promotion. Effective factors in the nurses' use of mobile applications were categorised into eight themes: ease of use, usefulness, security and confidentiality, feasibility and functionality, design and use-interface, effectiveness, infrastructure, versatility, and social norms.ConclusionsMobile health applications have considerable potential in enhancing nurses' professional activities. This study contributes to both nursing and health policy by providing a scenario of how and why nurses use mobile health applications.
| S-EPMC9483232 | biostudies-literature
Project description:To outline current knowledge regarding workplace-based learning about health promotion in individual patient care. Scoping review. PubMed, ERIC, CINAHL and Web of Science from January 2000 to August 2023. We included articles about learning (activities) for healthcare professionals (in training), about health promotion in individual patient care and in the context of workplace-based learning. The studies were evaluated using a charting template and were analysed thematically using a template based on Designable Elements of Learning Environments model. From 7159 studies, we included 31 that described evaluations of workplace-based learning about health promotion, around a variety of health promotion topics, for different health professions. In the articles, health promotion was operationalised as knowledge, skills or attitudes related to specific lifestyle factors or more broadly, with concepts such as health literacy, advocacy and social determinants of health. We assembled an overview of spatial and instrumental, social, epistemic and temporal elements of learning environments in which health promotion is learnt. The studies included in our analysis varied greatly in their approach to health promotion topics and the evaluation of learning outcomes. Our findings suggest the importance of providing opportunities for health profession learners to engage in authentic practice situations and address potential challenges they may experience translating related theory into practice. Additionally, our results highlight the need for conscious and articulated integration of health promotion in curricula and assessment structures. We recommend the exploration of opportunities for health profession students, professionals and patients to learn about health promotion together. Additionally, we see potential in using participatory research methods to study future health promotion learning. Open Science Framework, https://doi.org/10.17605/OSF.IO/6QPTV.
| S-EPMC10649380 | biostudies-literature
Project description:BackgroundThis paper studies the role of mobile applications in promoting physical activity and user loyalty to them. In doing so, our study offers fresh insights into the role of mobile applications in promoting physical activity and healthier lifestyles, filling gaps in the existing body of research.MethodsA non-probability purposive sample of adults who engage in physical exercise and use monitoring apps was selected, and semi-structured interviews were used to collect information.ResultsOur findings are suggestive that (i) physical exercise is more strongly associated with the continuous use of applications than with specific loyalty strategies; (ii) widespread use of apps that record and display historical results can boost regular physical activity, as users are motivated to surpass their previous outcomes. These results support the principle that 'more is better' in practice and intensity, suggesting that mobile technologies should be integrated into national health plans.ConclusionsMobile technologies should be encouraged by public policies, as these tools offer an accessible alternative for promoting public health. Policies could subsidize or facilitate the development of applications that integrate self-monitoring and personalized health plans aligned with public health guidelines. They could also include educational campaigns informing the population about these technologies' benefits and explaining how to use them to improve physical and mental health.
| S-EPMC11892298 | biostudies-literature
Project description:BackgroundArtificial intelligence (AI) is an umbrella term for various algorithms and rapidly emerging technologies with huge potential for workplace health promotion and prevention (WHPP). WHPP interventions aim to improve people's health and well-being through behavioral and organizational measures or by minimizing the burden of workplace-related diseases and associated risk factors. While AI has been the focus of research in other health-related fields, such as public health or biomedicine, the transition of AI into WHPP research has yet to be systematically investigated.ObjectiveThe systematic scoping review aims to comprehensively assess an overview of the current use of AI in WHPP. The results will be then used to point to future research directions. The following research questions were derived: (1) What are the study characteristics of studies on AI algorithms and technologies in the context of WHPP? (2) What specific WHPP fields (prevention, behavioral, and organizational approaches) were addressed by the AI algorithms and technologies? (3) What kind of interventions lead to which outcomes?MethodsA systematic scoping literature review (PRISMA-ScR [Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews]) was conducted in the 3 academic databases PubMed, Institute of Electrical and Electronics Engineers, and Association for Computing Machinery in July 2023, searching for papers published between January 2000 and December 2023. Studies needed to be (1) peer-reviewed, (2) written in English, and (3) focused on any AI-based algorithm or technology that (4) were conducted in the context of WHPP or (5) an associated field. Information on study design, AI algorithms and technologies, WHPP fields, and the patient or population, intervention, comparison, and outcomes framework were extracted blindly with Rayyan and summarized.ResultsA total of 10 studies were included. Risk prevention and modeling were the most identified WHPP fields (n=6), followed by behavioral health promotion (n=4) and organizational health promotion (n=1). Further, 4 studies focused on mental health. Most AI algorithms were machine learning-based, and 3 studies used combined deep learning algorithms. AI algorithms and technologies were primarily implemented in smartphone apps (eg, in the form of a chatbot) or used the smartphone as a data source (eg, Global Positioning System). Behavioral approaches ranged from 8 to 12 weeks and were compared to control groups. Additionally, 3 studies evaluated the robustness and accuracy of an AI model or framework.ConclusionsAlthough AI has caught increasing attention in health-related research, the review reveals that AI in WHPP is marginally investigated. Our results indicate that AI is promising for individualization and risk prediction in WHPP, but current research does not cover the scope of WHPP. Beyond that, future research will profit from an extended range of research in all fields of WHPP, longitudinal data, and reporting guidelines.Trial registrationOSF Registries osf.io/bfswp; https://osf.io/bfswp.
| S-EPMC11372327 | biostudies-literature
Project description:IntroductionPerinatal and maternal mortality rates remain high in India compared to global levels, and there is significant heterogeneity in outcomes across Indian states. Many mobile health (mHealth) interventions have been developed to improve maternal and infant health outcomes in India, however it is unclear how mHealth can best support women in this culturally and resource diverse setting. Therefore, we aimed to identify mHealth interventions targeting women and their families in the perinatal period in India, identify barriers and facilitators to their uptake, and future research directions.MethodsThe Preferred Reporting Items for Systematic Reviews and Meta-Analyses and Joanna Briggs Institute guidelines for scoping reviews was used for study selection and screening and the mHealth evidence reporting and assessment checklist was used for evaluating mHealth interventions. PubMed, CINAHL, Global Health, and ACM digital library were searched for records up to 2 April 2023. Studies were included where women who were pregnant, planning for a child, or in the 12 months after delivery, and their families, living in India received health advice via a technological medium.Results1,783 records were screened, 29 met the inclusion criteria, describing 22 different mHealth interventions. Most frequent behavioural targets for interventions were breastfeeding, antenatal nutrition, and infant healthcare. Most interventions communicated to women through one-way communication methods, most frequently SMS. Participants reported positive views of mHealth, reported facilitators included group communication, use of non-maternal informative content, and a pictorial information format. Reported barriers included household responsibilities, technical difficulties, difficulty accessing a phone and difficulty understanding, or misinterpreting messages.DiscussionWe conclude that mHealth interventions are acceptable to women in India during the perinatal period. However, current interventions lack evidence of long term behavioural change and fail to report on features important in sustainability and scalability, namely network infrastructure, data security and interoperability. We propose the need for a framework to understand existing cultural beliefs and support structures to avoid early intervention failure. Future research should investigate multimodal mHealth interventions for behavioural change, identify the appropriate frequency and format of mHealth messages, and address access limitations such as shared mobile phone ownership, and illiteracy rates.
| S-EPMC11631862 | biostudies-literature
Project description:ObjectiveThis systematic review aims to analyze current capabilities, challenges, and impact of self-directed mobile health (mHealth) research applications such as those based on the ResearchKit platform.Materials and methodsA systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. English publications were included if: 1) mobile applications were used in the context of large-scale collection of data for biomedical research, and not as medical or behavioral intervention of any kind, and 2) all activities related to participating in research and data collection methods were executed remotely without any face-to-face interaction between researchers and study participants.ResultsThirty-six unique ResearchKit apps were identified. The majority of the apps were used to conduct observational studies on general citizens and generate large datasets for secondary research. Nearly half of the apps were focused on chronic conditions in adults.DiscussionThe ability to generate large biomedical datasets on diverse populations that can be broadly shared and re-used was identified as a promising feature of mHealth research apps. Common challenges were low participation retention, uncertainty regarding how use patterns influence data quality, need for data validation, and privacy concerns.ConclusionResearchKit and other mHealth-based studies are well positioned to enhance development and validation of novel digital biomarkers as well as generate new biomedical knowledge through retrospective studies. However, in order to capitalize on these benefits, mHealth research studies must strive to improve retention rates, implement rigorous data validation strategies, and address emerging privacy and security challenges.
| S-EPMC7647150 | biostudies-literature
Project description:ObjectivesIn recent years, the use of mobile health applications (mHealth apps) to deliver care for patients with breast cancer has increased exponentially. This study aimed to summarize the available evidence on developing mHealth apps to care for patients with breast cancer and identify the need for systematic efforts.MethodsA scoping review was performed according to Arksey and O'Malley's framework, aiming to identify eligible research studies in PubMed, CINAHL, and Web of Science between January 2010 and December 2020. All identified studies were screened, extracted, and analyzed independently by two reviewers.ResultsA total of 676 studies were retrieved, and eight eligible studies were finally included. Four themes emerged: the involvement of patients and health professionals in the phases of design and development, patients' preferences, the characteristics of patients, and the motivators to use mHealth apps. The results indicated promising prospects for using mHealth apps to care for patients with breast cancer and identified the need for systematic efforts to develop and validate relevant apps.ConclusionsThe attributes of patient characteristics, needs, and patient-reported outcomes data are vital components for developing mHealth apps for patients with breast cancer. Additionally, collaborative efforts, including patients, nurses, and other significant health professionals, should develop mHealth apps for breast cancer care. Additional research focusing on the design and development of mHealth apps for patients with breast cancer is warranted.
| S-EPMC8488816 | biostudies-literature
Project description:ObjectiveTo summarize the research literature about safety concerns with consumer-facing health apps and their consequences.Materials and methodsWe searched bibliographic databases including PubMed, Web of Science, Scopus, and Cochrane libraries from January 2013 to May 2019 for articles about health apps. Descriptive information about safety concerns and consequences were extracted and classified into natural categories. The review was conducted in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) statement.ResultsOf the 74 studies identified, the majority were reviews of a single or a group of similar apps (n = 66, 89%), nearly half related to disease management (n = 34, 46%). A total of 80 safety concerns were identified, 67 related to the quality of information presented including incorrect or incomplete information, variation in content, and incorrect or inappropriate response to consumer needs. The remaining 13 related to app functionality including gaps in features, lack of validation for user input, delayed processing, failure to respond to health dangers, and faulty alarms. Of the 52 reports of actual or potential consequences, 5 had potential for patient harm. We also identified 66 reports about gaps in app development, including the lack of expert involvement, poor evidence base, and poor validation.ConclusionsSafety of apps is an emerging public health issue. The available evidence shows that apps pose clinical risks to consumers. Involvement of consumers, regulators, and healthcare professionals in development and testing can improve quality. Additionally, mandatory reporting of safety concerns is needed to improve outcomes.
| S-EPMC7025360 | biostudies-literature
Project description:Worksite-based programs to improve workforce health and well-being (Workplace Health Promotion (WHP)) have been advanced as conduits for improved worker productivity and decreased health care costs. There has been a countervailing health economics contention that return on investment (ROI) does not merit preventive health investment. METHODS/PROCEDURES: Pertinent studies were reviewed and results reconsidered. A simple economic model is presented based on conventional and alternate assumptions used in cost benefit analysis (CBA), such as discounting and negative value. The issues are presented in the format of 3 conceptual dilemmas.In some occupations such as nursing, the utility of patient survival and staff health is undervalued. WHP may miss important components of work related health risk. Altering assumptions on discounting and eliminating the drag of negative value radically change the CBA value.Simple monetization of a work life and calculation of return on workforce health investment as a simple alternate opportunity involve highly selective interpretations of productivity and utility.
| S-EPMC4562175 | biostudies-other